@article{teng_gao_yin_bai_liu_zeng_bai_cai_zhao_li_et al._2024, title={A compendium of genetic regulatory effects across pig tissues}, volume={1}, ISSN={["1546-1718"]}, DOI={10.1038/s41588-023-01585-7}, abstractNote={AbstractThe Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.}, journal={NATURE GENETICS}, author={Teng, Jinyan and Gao, Yahui and Yin, Hongwei and Bai, Zhonghao and Liu, Shuli and Zeng, Haonan and Bai, Lijing and Cai, Zexi and Zhao, Bingru and Li, Xiujin and et al.}, year={2024}, month={Jan} }
 @article{lozada-soto_maltecca_jiang_cole_vanraden_tiezzi_2024, title={Effect of germplasm exchange strategies on genetic gain, homozygosity, and genetic diversity in dairy stud populations: A simulation study}, url={https://doi.org/10.3168/jds.2024-24992}, DOI={10.3168/jds.2024-24992}, abstractNote={While genomic selection has led to considerable improvements in genetic gain, it has also seemingly led to increased rates of inbreeding and homozygosity, which can negatively affect genetic diversity and the long-term sustainability of dairy populations. Using genotypes from US Holstein animals from 3 distinct stud populations, we performed a simulation study consisting of 10 rounds of selection, with each breeding population composed of 200 males and 2000 females. The investigated selection strategies consisted of selection using true breeding values (TBV), estimated breeding values (EBV), estimated breeding values penalized for the average future genomic inbreeding of progeny (PEN-EBV), or random selection (RAND). We also simulated several germplasm exchange strategies where the germplasm of males from other populations was used for breeding. These strategies included exchanging males based on EBV, PEN-EBV, low genomic future inbreeding of progeny (GFI), or randomly (RAND). Variations of several parameters, such as the correlation between the selection objectives of populations and the size of the exchange, were simulated. Penalizing genetic merit to minimize genomic inbreeding of progeny provided similar genetic gain and reduced the average homozygosity of populations compared with the EBV strategy. Germplasm exchange was found to generally provide long-term benefits to all stud populations. In both the short and long-term, germplasm exchange using the EBV or PEN-EBV strategies provided more cumulative genetic progress than the no-exchange strategy; the amount of long-term genetic progress achieved with germplasm exchange using these strategies was higher for scenarios with a higher genetic correlation between the traits selected by the studs and for a larger size of the exchange. Both the PEN-EBV and GFI exchange strategies allowed decreases in homozygosity and provided significant benefits to genetic diversity compared with other strategies, including larger average minor allele frequencies and smaller proportions of markers near fixation. Overall, this study showed the value of breeding strategies to balance genetic progress and genetic diversity and the benefits of cooperation between studs to ensure the sustainability of their respective breeding programs.}, journal={Journal of Dairy Science}, author={Lozada-Soto, Emmanuel A. and Maltecca, Christian and Jiang, Jicai and Cole, John B. and VanRaden, Paul M. and Tiezzi, Francesco}, year={2024}, month={Aug} }
 @article{zhuo_du_diao_li_zhou_jiang_jiang_liu_2024, title={MAGE: metafounders-assisted genomic estimation of breeding value, a novel additive-dominance single-step model in crossbreeding systems}, volume={40}, ISSN={["1367-4811"]}, DOI={10.1093/bioinformatics/btae044}, abstractNote={Abstract Motivation Utilizing both purebred and crossbred data in animal genetics is widely recognized as an optimal strategy for enhancing the predictive accuracy of breeding values. Practically, the different genetic background among several purebred populations and their crossbred offspring populations limits the application of traditional prediction methods. Several studies endeavor to predict the crossbred performance via the partial relationship, which divides the data into distinct sub-populations based on the common genetic background, such as one single purebred population and its corresponding crossbred descendant. However, this strategy makes prediction inaccurate due to ignoring half of the parental information of crossbreed animals. Furthermore, dominance effects, although playing a significant role in crossbreeding systems, cannot be modeled under such a prediction model. Results To overcome this weakness, we developed a novel multi-breed single-step model using metafounders to assess ancestral relationships across diverse breeds under a unified framework. We proposed to use multi-breed dominance combined relationship matrices to model additive and dominance effects simultaneously. Our method provides a straightforward way to evaluate the heterosis of crossbreeds and the breeding values of purebred parents efficiently and accurately. We performed simulation and real data analyses to verify the potential of our proposed method. Our proposed model improved prediction accuracy under all scenarios considered compared to commonly used methods. Availability and implementation The software for implementing our method is available at https://github.com/CAU-TeamLiuJF/MAGE.}, number={2}, journal={BIOINFORMATICS}, author={Zhuo, Yue and Du, Heng and Diao, Chenguang and Li, Weining and Zhou, Lei and Jiang, Li and Jiang, Jicai and Liu, Jianfeng}, year={2024}, month={Feb} }
 @article{jiang_2024, title={MPH: fast REML for large-scale genome partitioning of quantitative genetic variation}, volume={40}, ISSN={["1367-4811"]}, url={https://doi.org/10.1093/bioinformatics/btae298}, DOI={10.1093/bioinformatics/btae298}, abstractNote={Abstract Motivation Genome partitioning of quantitative genetic variation is useful for dissecting the genetic architecture of complex traits. However, existing methods, such as Haseman–Elston regression and linkage disequilibrium score regression, often face limitations when handling extensive farm animal datasets, as demonstrated in this study. Results To overcome this challenge, we present MPH, a novel software tool designed for efficient genome partitioning analyses using restricted maximum likelihood. The computational efficiency of MPH primarily stems from two key factors: the utilization of stochastic trace estimators and the comprehensive implementation of parallel computation. Evaluations with simulated and real datasets demonstrate that MPH achieves comparable accuracy and significantly enhances convergence, speed, and memory efficiency compared to widely used tools like GCTA and LDAK. These advancements facilitate large-scale, comprehensive analyses of complex genetic architectures in farm animals. Availability and implementation The MPH software is available at https://jiang18.github.io/mph/.}, number={5}, journal={BIOINFORMATICS}, author={Jiang, Jicai}, editor={Schwartz, RussellEditor}, year={2024}, month={May} }
 @article{lin_flowers_jiang_knauer_lin_2024, title={The effect of temperature-humidity index in different pregnancy stages on litter traits in Taiwan Landrace sows}, volume={102}, ISSN={["1525-3163"]}, DOI={10.1093/jas/skae102.025}, abstractNote={Abstract Because of climate change, annual average temperatures are gradually rising. Hence, increasing heat stress can impair the litter traits of Taiwanese sows located in tropical and subtropical zones. However, some pregnancy stages may be impacted more by heat stress than other periods. Thus, the purpose of this study was to demonstrate the effect of temperature-humidity index (THI) in different pregnancy stages on total number born (TNB), number born alive (NBA), and stillborn rate (STB). Data were collected in two Taiwanese farms from 2008 to 2021 for TNB, NBA, and STB, while weather data were collected from the closest respective weather station. There were 4,247 and 6,812 pure line Landrace record from farm 1 and farm 2, respectively. Pregnancy stages included 28 d before mating (BEFORE), mating to 30 d of pregnancy (EARLY), 31 to 70 d of pregnancy (MIDDLE), and 71 d of pregnancy to farrowing (LATE). Average THI was calculated in each pregnancy stage and regression coefficients were estimated by linear mixed models within ASReml. A two-trait analysis was used to estimate regression coefficients and genetic correlations among TNB, NBA, and STB. Results showed THI impacted (P < 0.05) TNB and NBA BEFORE and EARLY, while THI influenced (P < 0.05) STB EARLY and MIDDLE. Regression coefficients for TNB were -0.0069 and -0.0228 for BEFORE and EARLY, respectively. For NBA, regression coefficients were 0.0106 and -0.0391 for BEFORE and EARLY, respectively. Regression coefficients for STB were -0.0651 and 0.1332 for EARLY and MIDDLE, respectively. Heritability estimates for TNB, NBA, and STB were 0.168, 0.113, and 0.069, respectively. Genetic correlations between TNB with NBA and STB were 0.913 and 0.539, respectively. While the genetic correlation between NBA and STB was 0.158. In conclusion, THI impacted BEFORE and EARLY stages for TNB and NBA, while the stages of EARLY and MIDDLE were impacted by THI for STB. Hence, control of the environments in these specific stages for sows could improve the performance of litter traits.}, journal={JOURNAL OF ANIMAL SCIENCE}, author={Lin, Kai-Hsiang and Flowers, Billy and Jiang, Jicai and Knauer, Mark and Lin, En-Chung}, year={2024}, month={May}, pages={20–20} }
 @article{ackerson_kuhn_gondro_jiang_maltecca_rohrer_rosen_smith_tuggle_huang_2024, title={Trio-binning Assemblies of the Duroc and Landrace swine breeds}, volume={102}, ISSN={["1525-3163"]}, DOI={10.1093/jas/skae234.589}, abstractNote={Abstract The current swine reference genome, based on a single Duroc individual, has contributed to many significant advances but also carries limitations in many applications. Reference alleles receive substantial bias from alignment-based approaches. Additionally, structural DNA variants are difficult to identify and represent relative to the linear reference genome. As a result, DNA variants more likely to affect complex quantitative traits are understudied and warrant further investigation. In this study, a trio-binning approach was utilized to produce haplotype-resolved assemblies of a Duroc x Landrace hybrid. The Duroc sire and Landrace dam were sequenced via short-read technology (Illumina), and the hybrid offspring was sequenced via long-read technology (PacBio HiFi). A total of 117 Gb HiFi data was produced, equivalent to approximately 47X coverage of the swine genome. Two highly contiguous and high-quality assemblies were produced using hifiasm. The assembled maternal (Landrace) and paternal (Duroc) genomes had a contig N50 of 76.7 Mb and 55.0 Mb, respectively, both of which surpass that of the current reference genome Sscrofa11.1 (48.2 Mb). Furthermore, the maternal and paternal genomes contained 113.6 Mb and 116.0 Mb of novel sequences relative to the reference, respectively. The Benchmarking Universal Single-Copy Orthologue (BUSCO) scores were approximately 96%, indicating high completeness. The computed assembly QVs were found to be >Q40. Compared with short-read technology, whole genome mapping identified substantially more large SVs (> 50bp). These haplotype-resolved assemblies and additional existing assemblies will serve as the basis for the production of a swine pangenome.}, journal={JOURNAL OF ANIMAL SCIENCE}, author={Ackerson, Leland K. and Kuhn, Kristen and Gondro, Cedric and Jiang, Jicai and Maltecca, Christian and Rohrer, Gary A. and Rosen, Benjamin D. and Smith, Timothy and Tuggle, Christopher K. and Huang, Wen}, year={2024}, month={Sep}, pages={523–523} }
 @article{ackerson_kuhn_gondro_jiang_maltecca_rohrer_rosen_smith_tuggle_huang_2024, title={Trio-binning Assemblies of the Duroc and Landrace swine breeds}, volume={102}, ISSN={["1525-3163"]}, DOI={10.1093/jas/skae234.5}, journal={JOURNAL OF ANIMAL SCIENCE}, author={Ackerson, Leland K. and Kuhn, Kristen and Gondro, Cedric and Jiang, Jicai and Maltecca, Christian and Rohrer, Gary A. and Rosen, Benjamin D. and Smith, Timothy and Tuggle, Christopher K. and Huang, Wen}, year={2024}, month={Sep}, pages={523–523} }
 @article{wang_maltecca_tiezzi_huang_jiang_2023, title={123 Benchmarking of Artificial Neural Network Models for Genomic Prediction of Quantitative Traits in Pigs}, volume={101}, ISSN={0021-8812 1525-3163}, url={http://dx.doi.org/10.1093/jas/skad281.022}, DOI={10.1093/jas/skad281.022}, abstractNote={Abstract
               Artificial neural networks (ANN) are a type of machine learning model that has been applied to various genomic problems, with the ability to learn non-linear relationships and model high-dimensional data. ANNs also have the potential in genomic prediction by capturing the intricate relationship between genetic variants and phenotypes. However, there is currently a limited effort to investigate the performance and feasibility of ANNs for pig genomic predictions. In this study, we evaluated the predictive performance of TensorFlow’s ANN models with one-layer, two-layer, and three-layer structures (with zero, one, and two hidden layers, respectively), in comparison with five linear methods, including GBLUP, LDAK, BayesR, SLEMM and scikit-learn’s ridge regression using data of six quantitative traits including off-test body weight (WT), off-test back fat thickness (BF), off-test loin muscle depth (MS), number of piglets born alive (NBA), number of piglets born dead (NBD), and number of piglets weaned (NW). Furthermore, we assessed the computational efficiency of ANNs on both CPU and GPU. The benchmarking was based on cross-validations of 26,190 genotyped pigs. We employed hyperband tuning to optimize the hyper-parameters and select the best model among one-layer, two-layer, and three-layer structures. Results showed that the one-layer structure, which is equivalent to ridge regression, yielded the best performance comparable to that of GBLUP. Using the optimal hyper-parameters for two-layer and three-layer structures, ANNs underperformed GBLUP in terms of accuracy. Of the five linear methods, BayesR and SLEMM performed similarly and the best, followed by LDAK, scikit-learn’s ridge regression, and GBLUP. Moreover, SLEMM was the fastest, which completed training with 21k individuals and 30k SNPs in 2.6 minutes. Compared with CPUs, GPUs exhibited a comparable computational speed for one-layer ANN but offered significant gains in computational efficiency for multi-layer ANNs. Based on our analysis of optimal hyper-parameters for two-layer ANN with BF, we found that using a GPU can lead to a five-fold increase in processing speed compared with using a conventional CPU, but it is still slower than GBLUP. In addition, hyper-parameter tuning (particularly for L2 regularization and the number of dense units in hidden layers) is critical for improving the genomic prediction accuracy in pigs. In conclusion, we found ANN with up to three layers could not improve genomic predictions compared with routine linear methods for pig quantitative traits.}, number={Supplement_3}, journal={Journal of Animal Science}, publisher={Oxford University Press (OUP)}, author={Wang, Junjian and Maltecca, Christian and Tiezzi, Francesco and Huang, Yijian and Jiang, Jicai}, year={2023}, month={Nov}, pages={17–18} }
 @article{liang_prakapenka_vanraden_jiang_ma_da_2023, title={A Million-Cow Genome-Wide Association Study of Three Fertility Traits in US Holstein Cows}, volume={24}, ISSN={["1422-0067"]}, url={https://doi.org/10.3390/ijms241310496}, DOI={10.3390/ijms241310496}, abstractNote={A genome-wide association study (GWAS) of the daughter pregnancy rate (DPR), cow conception rate (CCR), and heifer conception rate (HCR) using 1,001,374–1,194,736 first-lactation Holstein cows and 75,140–75,295 SNPs identified 7567, 3798, and 726 additive effects, as well as 22, 27, and 25 dominance effects for DPR, CCR, and HCR, respectively, with log10(1/p) > 8. Most of these effects were new effects, and some new effects were in or near genes known to affect reproduction including GNRHR, SHBG, and ESR1, and a gene cluster of pregnancy-associated glycoproteins. The confirmed effects included those in or near the SLC4A4-GC-NPFFR2 and AFF1 regions of Chr06 and the KALRN region of Chr01. Eleven SNPs in the CEBPG-PEPD-CHST8 region of Chr18, the AFF1-KLHL8 region of Chr06, and the CCDC14-KALRN region of Chr01 with sharply negative allelic effects and dominance values for the recessive homozygous genotypes were recommended for heifer culling. Two SNPs in and near the AGMO region of Chr04 that were sharply negative for HCR and age at first calving, but slightly positive for the yield traits could also be considered for heifer culling. The results from this study provided new evidence and understanding about the genetic variants and genome regions affecting the three fertility traits in U.S. Holstein cows.}, number={13}, journal={INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES}, author={Liang, Zuoxiang and Prakapenka, Dzianis and VanRaden, Paul M. and Jiang, Jicai and Ma, Li and Da, Yang}, year={2023}, month={Jul} }
 @article{gao_marceau_iqbal_torres-vazquez_neupane_jiang_liu_ma_2023, title={Genome-wide association analysis of heifer livability and early first calving in Holstein cattle}, volume={24}, ISSN={["1471-2164"]}, DOI={10.1186/s12864-023-09736-0}, abstractNote={Abstract
                Background
                The survival and fertility of heifers are critical factors for the success of dairy farms. The mortality of heifers poses a significant challenge to the management and profitability of the dairy industry. In dairy farming, achieving early first calving of heifers is also essential for optimal productivity and sustainability. Recently, Council on Dairy Cattle Breeding (CDCB) and USDA have developed new evaluations of heifer health and fertility traits. However, the genetic basis of these traits has yet to be thoroughly studied.
              
                Results
                Leveraging the extensive U.S dairy genomic database maintained at CDCB, we conducted large-scale GWAS analyses of two heifer traits, livability and early first calving. Despite the large sample size, we found no major QTL for heifer livability. However, we identified a major QTL in the bovine MHC region associated with early first calving. Our GO analysis based on nearby genes detected 91 significant GO terms with a large proportion related to the immune system. This QTL in the MHC region was also confirmed in the analysis of 27 K bull with imputed sequence variants. Since these traits have few major QTL, we evaluated the genome-wide distribution of GWAS signals across different functional genomics categories. For heifer livability, we observed significant enrichment in promotor and enhancer-related regions. For early calving, we found more associations in active TSS, active Elements, and Insulator. We also identified significant enrichment of CDS and conserved variants in the GWAS results of both traits. By linking GWAS results and transcriptome data from the CattleGTEx project via TWAS, we detected four and 23 significant gene-trait association pairs for heifer livability and early calving, respectively. Interestingly, we discovered six genes for early calving in the Bovine MHC region, including two genes in lymph node tissue and one gene each in blood, adipose, hypothalamus, and leukocyte.
              
                Conclusion
                Our large-scale GWAS analyses of two heifer traits identified a major QTL in the bovine MHC region for early first calving. Additional functional enrichment and TWAS analyses confirmed the MHC QTL with relevant biological evidence. Our results revealed the complex genetic basis of heifer health and fertility traits and indicated a potential connection between the immune system and reproduction in cattle.
              }, number={1}, journal={BMC GENOMICS}, author={Gao, Yahui and Marceau, Alexis and Iqbal, Victoria and Torres-Vazquez, Jose Antonio and Neupane, Mahesh and Jiang, Jicai and Liu, George E. and Ma, Li}, year={2023}, month={Oct} }
 @article{lozada-soto_gaddis_tiezzi_jiang_ma_toghiani_van raden_maltecca_2023, title={Inbreeding depression for producer-recorded udder, metabolic, and reproductive diseases in US dairy cattle}, volume={107}, ISSN={0022-0302}, url={http://dx.doi.org/10.3168/jds.2023-23909}, DOI={10.3168/jds.2023-23909}, abstractNote={This study leveraged a growing data set of producer-recorded phenotypes for mastitis, reproductive diseases (metritis and retained placenta), and metabolic diseases (ketosis, milk fever, and displaced abomasum) to investigate the potential presence of inbreeding depression for these disease traits. Phenotypic, pedigree, and genomic information were obtained for 354,043 and 68,292 US Holstein and Jersey cows, respectively. Total inbreeding coefficients were calculated using both pedigree and genomic information; the latter included inbreeding estimates obtained using a genomic relationship matrix and runs of homozygosity (ROH). We also generated inbreeding coefficients based on the generational inbreeding for recent and old pedigree inbreeding, for different ROH length classes, and for recent and old homozygous-by-descent segment-based inbreeding. Estimates on the liability scale revealed significant evidence of inbreeding depression for reproductive disease traits, with an increase in total pedigree and genomic inbreeding showing a notable effect for recent inbreeding. However, we found inconsistent evidence for inbreeding depression for mastitis or any metabolic diseases. Notably, in Holsteins, the probability of developing displaced abomasum decreased with inbreeding, particularly for older inbreeding. Estimates of disease probability for cows with low, average, and high inbreeding levels did not significantly differ across any inbreeding coefficient and trait combination, indicating that while inbreeding may impact disease incidence, it likely plays a smaller role compared with management and environmental factors.}, number={5}, journal={Journal of Dairy Science}, publisher={American Dairy Science Association}, author={Lozada-Soto, Emmanuel A. and Gaddis, Kristen L. Parker and Tiezzi, Francesco and Jiang, Jicai and Ma, Li and Toghiani, Sajjad and Van Raden, Paul M. and Maltecca, Christian}, year={2023}, month={Dec}, pages={3032–3046} }
 @article{marceau_wang_iqbal_jiang_liu_ma_2023, title={Investigation of lncRNA in <i>Bos taurus</i> Mammary Tissue during Dry and Lactation Periods}, volume={14}, ISSN={["2073-4425"]}, url={https://doi.org/10.3390/genes14091789}, DOI={10.3390/genes14091789}, abstractNote={This study aims to collect RNA-Seq data from Bos taurus samples representing dry and lactating mammary tissue, identify lncRNA transcripts, and analyze findings for their features and functional annotation. This allows for connections to be drawn between lncRNA and the lactation process. RNA-Seq data from 103 samples of Bos taurus mammary tissue were gathered from publicly available databases (60 dry, 43 lactating). The samples were filtered to reveal 214 dry mammary lncRNA transcripts and 517 lactating mammary lncRNA transcripts. The lncRNAs met common lncRNA characteristics such as shorter length, fewer exons, lower expression levels, and less sequence conservation when compared to the genome. Interestingly, several lncRNAs showed sequence similarity to genes associated with strong hair keratin intermediate filaments. Human breast cancer research has associated strong hair keratin filaments with mammary tissue cellular resilience. The lncRNAs were also associated with several genes/proteins that linked to pregnancy using expression correlation and gene ontology. Such findings indicate that there are crucial relationships between the lncRNAs found in mammary tissue and the development of the tissue, to meet both the animal’s needs and our own production needs; these relationships should be further investigated to ensure that we continue to breed the most resilient, efficient dairy cattle.}, number={9}, journal={GENES}, author={Marceau, Alexis and Wang, Junjian and Iqbal, Victoria and Jiang, Jicai and Liu, George E. and Ma, Li}, year={2023}, month={Sep} }
 @article{cheng_maltecca_vanraden_jeffrey r. o'connell_ma_jiang_2023, title={SLEMM: million-scale genomic predictions with window-based SNP weighting}, volume={39}, ISSN={["1367-4811"]}, url={https://doi.org/10.1093/bioinformatics/btad127}, DOI={10.1093/bioinformatics/btad127}, abstractNote={Abstract
               
                  Motivation
                  The amount of genomic data is increasing exponentially. Using many genotyped and phenotyped individuals for genomic prediction is appealing yet challenging.
               
               
                  Results
                  We present SLEMM (short for Stochastic-Lanczos-Expedited Mixed Models), a new software tool, to address the computational challenge. SLEMM builds on an efficient implementation of the stochastic Lanczos algorithm for REML in a framework of mixed models. We further implement SNP weighting in SLEMM to improve its predictions. Extensive analyses on seven public datasets, covering 19 polygenic traits in three plant and three livestock species, showed that SLEMM with SNP weighting had overall the best predictive ability among a variety of genomic prediction methods including GCTA’s empirical BLUP, BayesR, KAML, and LDAK’s BOLT and BayesR models. We also compared the methods using nine dairy traits of ∼300k genotyped cows. All had overall similar prediction accuracies, except that KAML failed to process the data. Additional simulation analyses on up to 3 million individuals and 1 million SNPs showed that SLEMM was advantageous over counterparts as for computational performance. Overall, SLEMM can do million-scale genomic predictions with an accuracy comparable to BayesR.
               
               
                  Availability and implementation
                  The software is available at https://github.com/jiang18/slemm.
               }, number={3}, journal={BIOINFORMATICS}, author={Cheng, Jian and Maltecca, Christian and VanRaden, Paul M. and Jeffrey R. O'Connell and Ma, Li and Jiang, Jicai}, editor={Schwartz, RussellEditor}, year={2023}, month={Mar} }
 @misc{jiang_2023, title={Simulated Sequence Genotypes}, url={https://figshare.com/articles/dataset/Simulated_Sequence_Genotypes/24432948}, DOI={10.6084/m9.figshare.24432948}, abstractNote={A simulated dataset for demonstrating how to partition heritability by functional annotations using MPH (https://jiang18.github.io/mph/)}, author={Jiang, Jicai}, year={2023}, month={Oct} }
 @misc{jiang_2023, title={sequence-genotypes.zip}, url={https://figshare.com/articles/dataset/sequence-genotypes_zip/24431263}, DOI={10.6084/m9.figshare.24431263}, abstractNote={test}, author={Jiang, Jicai}, year={2023}, month={Oct} }
 @article{duan_jiang_he_2022, title={Editorial: Bridging (Epi-) Genomics and Environmental Changes: The Livestock Research}, volume={13}, ISSN={["1664-8021"]}, DOI={10.3389/fgene.2022.961232}, abstractNote={impact aberrant transcriptomic}, journal={FRONTIERS IN GENETICS}, author={Duan, Jingyue Ellie and Jiang, Jicai and He, Yanghua}, year={2022}, month={Jul} }
 @article{he_tiezzi_jiang_howard_huang_gray_choi_maltecca_2022, title={Exploring methods to summarize gut microbiota composition for microbiability estimation and phenotypic prediction in swine}, volume={100}, ISSN={["1525-3163"]}, url={https://doi.org/10.1093/jas/skac231}, DOI={10.1093/jas/skac231}, abstractNote={Abstract
               The microbial composition resemblance among individuals in a group can be summarized in a square covariance matrix and fitted in linear models. We investigated eight approaches to create the matrix that quantified the resemblance between animals based on the gut microbiota composition. We aimed to compare the performance of different methods in estimating trait microbiability and predicting growth and body composition traits in three pig breeds. This study included 651 purebred boars from either breed: Duroc (n = 205), Landrace (n = 226), and Large White (n = 220). Growth and body composition traits, including body weight (BW), ultrasound backfat thickness (BF), ultrasound loin depth (LD), and ultrasound intramuscular fat (IMF) content, were measured on live animals at the market weight (156 ± 2.5 d of age). Rectal swabs were taken from each animal at 158 ± 4 d of age and subjected to 16S rRNA gene sequencing. Eight methods were used to create the microbial similarity matrices, including 4 kernel functions (Linear Kernel, LK; Polynomial Kernel, PK; Gaussian Kernel, GK; Arc-cosine Kernel with one hidden layer, AK1), 2 dissimilarity methods (Bray-Curtis, BC; Jaccard, JA), and 2 ordination methods (Metric Multidimensional Scaling, MDS; Detrended Correspondence analysis, DCA). Based on the matrix used, microbiability estimates ranged from 0.07 to 0.21 and 0.12 to 0.53 for Duroc, 0.03 to 0.21 and 0.05 to 0.44 for Landrace, and 0.02 to 0.24 and 0.05 to 0.52 for Large White pigs averaged over traits in the model with sire, pen, and microbiome, and model with the only microbiome, respectively. The GK, JA, BC, and AK1 obtained greater microbiability estimates than the remaining methods across traits and breeds. Predictions were made within each breed group using four-fold cross-validation based on the relatedness of sires in each breed group. The prediction accuracy ranged from 0.03 to 0.18 for BW, 0.08 to 0.31 for BF, 0.21 to 0.48 for LD, and 0.04 to 0.16 for IMF when averaged across breeds. The BC, MDS, LK, and JA achieved better accuracy than other methods in most predictions. Overall, the PK and DCA exhibited the worst performance compared to other microbiability estimation and prediction methods. The current study shows how alternative approaches summarized the resemblance of gut microbiota composition among animals and contributed this information to variance component estimation and phenotypic prediction in swine.}, number={9}, journal={JOURNAL OF ANIMAL SCIENCE}, author={He, Yuqing and Tiezzi, Francesco and Jiang, Jicai and Howard, Jeremy and Huang, Yijian and Gray, Kent and Choi, Jung-Woo and Maltecca, Christian}, year={2022}, month={Sep} }
 @article{lozada-soto_tiezzi_jiang_cole_vanraden_maltecca_2022, title={Genomic characterization of autozygosity and recent inbreeding trends in all major breeds of US dairy cattle}, volume={105}, ISSN={["1525-3198"]}, url={https://doi.org/10.3168/jds.2022-22116}, DOI={10.3168/jds.2022-22116}, abstractNote={Maintaining a genetically diverse dairy cattle population is critical to preserving adaptability to future breeding goals and avoiding declines in fitness. This study characterized the genomic landscape of autozygosity and assessed trends in genetic diversity in 5 breeds of US dairy cattle. We analyzed a sizable genomic data set containing 4,173,679 pedigreed and genotyped animals of the Ayrshire, Brown Swiss, Guernsey, Holstein, and Jersey breeds. Runs of homozygosity (ROH) of 2 Mb or longer in length were identified in each animal. The within-breed means for number and the combined length of ROH were highest in Jerseys (62.66 ± 8.29 ROH and 426.24 ± 83.40 Mb, respectively; mean ± SD) and lowest in Ayrshires (37.24 ± 8.27 ROH and 265.05 ± 85.00 Mb, respectively). Short ROH were the most abundant, but moderate to large ROH made up the largest proportion of genome autozygosity in all breeds. In addition, we identified ROH islands in each breed. This revealed selection patterns for milk production, productive life, health, and reproduction in most breeds and evidence for parallel selective pressure for loci on chromosome 6 between Ayrshire and Brown Swiss and for loci on chromosome 20 between Holstein and Jersey. We calculated inbreeding coefficients using 3 different approaches, pedigree-based (FPED), marker-based using a genomic relationship matrix (FGRM), and segment-based using ROH (FROH). The average inbreeding coefficient ranged from 0.06 in Ayrshires and Brown Swiss to 0.08 in Jerseys and Holsteins using FPED, from 0.22 in Holsteins to 0.29 in Guernsey and Jerseys using FGRM, and from 0.11 in Ayrshires to 0.17 in Jerseys using FROH. In addition, the effective population size at past generations (5-100 generations ago), the yearly rate of inbreeding, and the effective population size in 3 recent periods (2000-2009, 2010-2014, and 2015-2018) were determined in each breed to ascertain current and historical trends of genetic diversity. We found a historical trend of decreasing effective population size in the last 100 generations in all breeds and breed differences in the effect of the recent implementation of genomic selection on inbreeding accumulation.}, number={11}, journal={JOURNAL OF DAIRY SCIENCE}, author={Lozada-Soto, Emmanuel A. and Tiezzi, Francesco and Jiang, Jicai and Cole, John B. and VanRaden, Paul M. and Maltecca, Christian}, year={2022}, month={Nov}, pages={8956–8971} }
 @article{marceau_gao_baldwin_li_jiang_liu_ma_2022, title={Investigation of rumen long noncoding RNA before and after weaning in cattle}, volume={23}, ISSN={["1471-2164"]}, DOI={10.1186/s12864-022-08758-4}, abstractNote={Abstract
                Background
                This study aimed to identify long non-coding RNA (lncRNA) from the rumen tissue in dairy cattle, explore their features including expression and conservation levels, and reveal potential links between lncRNA and complex traits that may indicate important functional impacts of rumen lncRNA during the transition to the weaning period.
              
                Results
                A total of six cattle rumen samples were taken with three replicates from before and after weaning periods, respectively. Total RNAs were extracted and sequenced with lncRNA discovered based on size, coding potential, sequence homology, and known protein domains. As a result, 404 and 234 rumen lncRNAs were identified before and after weaning, respectively. However, only nine of them were shared under two conditions, with 395 lncRNAs found only in pre-weaning tissues and 225 only in post-weaning samples. Interestingly, none of the nine common lncRNAs were differentially expressed between the two weaning conditions. LncRNA averaged shorter length, lower expression, and lower conservation scores than the genome overall, which is consistent with general lncRNA characteristics. By integrating rumen lncRNA before and after weaning with large-scale GWAS results in cattle, we reported significant enrichment of both pre- and after-weaning lncRNA with traits of economic importance including production, reproduction, health, and body conformation phenotypes.
              
                Conclusions
                The majority of rumen lncRNAs are uniquely expressed in one of the two weaning conditions, indicating a functional role of lncRNA in rumen development and transition of weaning. Notably, both pre- and post-weaning lncRNA showed significant enrichment with a variety of complex traits in dairy cattle, suggesting the importance of rumen lncRNA for cattle performance in the adult stage. These relationships should be further investigated to better understand the specific roles lncRNAs are playing in rumen development and cow performance.
              }, number={1}, journal={BMC GENOMICS}, author={Marceau, Alexis and Gao, Yahui and Baldwin, Ransom L. and Li, Cong-jun and Jiang, Jicai and Liu, George E. and Ma, Li}, year={2022}, month={Jul} }
 @article{cheng_tiezzi_howard_maltecca_jiang_2022, title={The Addition of Epistatic Genetic Effects Increases Genomic Prediction Accuracy for Reproduction and Production Traits in Duroc Pigs Using Genomic Models}, url={https://doi.org/10.21203/rs.3.rs-1182452/v1}, DOI={10.21203/rs.3.rs-1182452/v1}, abstractNote={Abstract
        Background: Genomic selection has been implemented in livestock genetic evaluations for years. However, currently most genomic selection models only consider the additive effects associated with SNP markers and nonadditive genetic effects have been for the most part ignored. Methods: Production traits for 26,735 to 27,647 Duroc pigs and reproductive traits for 5,338 sows were used, including off-test body weight (WT), off-test back fat (BF), off-test loin muscle depth (MS), number born alive (NBA), number born dead (NBD), and number weaned (NW). All animals were genotyped with the PorcineSNP60K Bead Chip. Variance components were estimated using a linear mixed model that includes inbreeding coefficient, additive, dominance, additive-by-additive, additive-by-dominance, dominance-by-dominance effect, and common litter environmental effect. Genomic prediction performance, including all nonadditive genetic effects, was compared with a reduced model that included only additive genetic effect. Results: Significant estimates of additive-by-additive effect variance were observed for NBA, BF, and WT (31%, 9%, and 10%, respectively). Production traits showed significant large estimates of additive-by-dominance variance (9%-23%). MS also showed large estimate of dominance-by-dominance variance (10%). Dominance effect variance estimates were low for all traits (0%-2%). Compared to the reduced model, prediction accuracies using the full model, including nonadditive effects, increased significantly by 12%, 12%, and 1% for NBA, WT, and MS, respectively. A strong dominance association signal with BF was identified near AK5.Conclusions: Sizable estimates of epistatic effects were found for the reproduction and production traits, while the dominance effect was relatively small for all traits yet significant for all production traits. Including nonadditive effects, especially epistatic effects in the genomic prediction model, significantly improved prediction accuracy for NBA, WT, and MS.}, author={Cheng, Jian and Tiezzi, Francesco and Howard, Jeremy and Maltecca, Christian and Jiang, Jicai}, year={2022}, month={Jan} }
 @article{wang_hicks_jiang_liu_2022, title={Transcriptome Analysis of Chicken Reveals the Impact of Herpesvirus of Turkeys on Bursa RNA Expression in Marek's Disease Virus Infections}, volume={100}, ISSN={["1525-3163"]}, DOI={10.1093/jas/skac247.392}, abstractNote={Abstract
               Marek’s disease virus (MDV) is an oncogenic herpesvirus that causes various clinical syndromes in chicken. MDV early infection induces a transient immunosuppression and harbored in B cells of the bursa during the cytolysis phase of its replication cycle. One of the most commonly used commercial vaccines is Herpesvirus of Turkeys (HVT), which is a nonpathogenic virus of domestic turkey and may influence the expression of RNA. The aim of this study is to characterize the regulation of bursa gene in MDV infections and the impact of HVT vaccination on RNA expression in MDV-infected chickens. We used RNA-seq on the bursa samples to compare the transcriptome differences among MDV-infected chickens, HVT-infected chickens, co-infected chickens and uninfected control groups at 4, 7, 14 and 21 days post infection. Meanwhile, we also compared the expression at three different time points to examine alterations in the expression pattern. The result of differential gene expression showed that 14 days post infection might be the point in time when HVT worked. At false discovery (FDR) < 0.05 and fold change (FC) ≥2, we found 745, 218 and 76 genes in MDV-infected chickens, HVT-infected chickens and co-infected chickens respectively as differentially expressed compared with control group and 713 genes between MDV-infected chickens and co-infected chickens at 14 dpi. KEGG and GO enrichment analysis showed that these genes were highly enriched for Lysosome, immune response, inflammatory response, plasma membrane and so on. Overall, these findings help to better understand host-pathogen interaction in the bursa and elucidate the mechanism how HVT contribute to resist MDV. Further investigation of the roles of these candidate genes and signaling pathways in the regulation of MDV-HVT interaction may lead new directions for the development of drugs or cultivation of highly MDV resistant chickens.}, journal={JOURNAL OF ANIMAL SCIENCE}, author={Wang, Junjian and Hicks, Julie and Jiang, Jicai and Liu, Hsiao-Ching}, year={2022}, month={Oct}, pages={215–215} }
 @article{he_tiezzi_jiang_howard_huang_gray_choi_maltecca_2022, title={Use of Host Feeding Behavior and Gut Microbiome Data in Estimating Variance Components and Predicting Growth and Body Composition Traits in Swine}, volume={13}, ISSN={["2073-4425"]}, url={https://doi.org/10.3390/genes13050767}, DOI={10.3390/genes13050767}, abstractNote={The purpose of this study was to investigate the use of feeding behavior in conjunction with gut microbiome sampled at two growth stages in predicting growth and body composition traits of finishing pigs. Six hundred and fifty-one purebred boars of three breeds: Duroc (DR), Landrace (LR), and Large White (LW), were studied. Feeding activities were recorded individually from 99 to 163 days of age. The 16S rRNA gene sequences were obtained from each pig at 123 ± 4 and 158 ± 4 days of age. When pigs reached market weight, body weight (BW), ultrasound backfat thickness (BF), ultrasound loin depth (LD), and ultrasound intramuscular fat (IMF) content were measured on live animals. Three models including feeding behavior (Model_FB), gut microbiota (Model_M), or both (Model_FB_M) as predictors, were investigated. Prediction accuracies were evaluated through cross-validation across genetic backgrounds using the leave-one-breed-out strategy and across rearing environments using the leave-one-room-out approach. The proportions of phenotypic variance of growth and body composition traits explained by feeding behavior ranged from 0.02 to 0.30, and from 0.20 to 0.52 when using gut microbiota composition. Overall prediction accuracy (averaged over traits and time points) of phenotypes was 0.24 and 0.33 for Model_FB, 0.27 and 0.19 for Model_M, and 0.40 and 0.35 for Model_FB_M for the across-breed and across-room scenarios, respectively. This study shows how feeding behavior and gut microbiota composition provide non-redundant information in predicting growth in swine.}, number={5}, journal={GENES}, publisher={MDPI AG}, author={He, Yuqing and Tiezzi, Francesco and Jiang, Jicai and Howard, Jeremy T. and Huang, Yijian and Gray, Kent and Choi, Jung-Woo and Maltecca, Christian}, year={2022}, month={May} }
 @article{prakapenka_liang_jiang_ma_da_2021, title={A Large-Scale Genome-Wide Association Study of Epistasis Effects of Production Traits and Daughter Pregnancy Rate in US Holstein Cattle}, volume={12}, ISSN={["2073-4425"]}, DOI={10.3390/genes12071089}, abstractNote={Epistasis is widely considered important, but epistasis studies lag those of SNP effects. Genome-wide association study (GWAS) using 76,109 SNPs and 294,079 first-lactation Holstein cows was conducted for testing pairwise epistasis effects of five production traits and three fertility traits: milk yield (MY), fat yield (FY), protein yield (PY), fat percentage (FPC), protein percentage (PPC), and daughter pregnancy rate (DPR). Among the top 50,000 pairwise epistasis effects of each trait, the five production traits had large chromosome regions with intra-chromosome epistasis. The percentage of inter-chromosome epistasis effects was 1.9% for FPC, 1.6% for PPC, 10.6% for MY, 29.9% for FY, 39.3% for PY, and 84.2% for DPR. Of the 50,000 epistasis effects, the number of significant effects with log10(1/p) ≥ 12 was 50,000 for FPC and PPC, and 10,508, 4763, 4637 and 1 for MY, FY, PY and DPR, respectively, and A × A effects were the most frequent epistasis effects for all traits. Majority of the inter-chromosome epistasis effects of FPC across all chromosomes involved a Chr14 region containing DGAT1, indicating a potential regulatory role of this Chr14 region affecting all chromosomes for FPC. The epistasis results provided new understanding about the genetic mechanism underlying quantitative traits in Holstein cattle.}, number={7}, journal={GENES}, author={Prakapenka, Dzianis and Liang, Zuoxiang and Jiang, Jicai and Ma, Li and Da, Yang}, year={2021}, month={Jul} }
 @article{shen_freebern_jiang_maltecca_cole_liu_ma_2021, title={Effect of Temperature and Maternal Age on Recombination Rate in Cattle}, volume={12}, ISSN={["1664-8021"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85111940376&partnerID=MN8TOARS}, DOI={10.3389/fgene.2021.682718}, abstractNote={Meiotic recombination is a fundamental biological process that facilitates meiotic division and promotes genetic diversity. Recombination is phenotypically plastic and affected by both intrinsic and extrinsic factors. The effect of maternal age on recombination rates has been characterized in a wide range of species, but the effect’s direction remains inconclusive. Additionally, the characterization of temperature effects on recombination has been limited to model organisms. Here we seek to comprehensively determine the impact of genetic and environmental factors on recombination rate in dairy cattle. Using a large cattle pedigree, we identified maternal recombination events within 305,545 three-generation families. By comparing recombination rate between parents of different ages, we found a quadratic trend between maternal age and recombination rate in cattle. In contrast to either an increasing or decreasing trend in humans, cattle recombination rate decreased with maternal age until 65 months and then increased afterward. Combining recombination data with temperature information from public databases, we found a positive correlation between environmental temperature during fetal development of offspring and recombination rate in female parents. Finally, we fitted a full recombination rate model on all related factors, including genetics, maternal age, and environmental temperatures. Based on the final model, we confirmed the effect of maternal age and environmental temperature during fetal development of offspring on recombination rate with an estimated heritability of 10% (SE = 0.03) in cattle. Collectively, we characterized the maternal age and temperature effects on recombination rate and suggested the adaptation of meiotic recombination to environmental stimuli in cattle. Our results provided first-hand information regarding the plastic nature of meiotic recombination in a mammalian species.}, journal={FRONTIERS IN GENETICS}, author={Shen, Botong and Freebern, Ellen and Jiang, Jicai and Maltecca, Christian and Cole, John B. and Liu, George E. and Ma, Li}, year={2021}, month={Jul} }
 @article{jiang_2021, title={On the Use of Z-Scores for Fine-Mapping with Related Individuals}, volume={10}, url={https://doi.org/10.1101/2021.10.10.463846}, DOI={10.1101/2021.10.10.463846}, abstractNote={AbstractUsing summary statistics from genome-wide association studies (GWAS) has been widely used for fine-mapping complex traits in humans. The statistical framework was largely developed for unrelated samples. Though it is possible to apply the framework to fine-mapping with related individuals, extensive modifications are needed. Unfortunately, this has often been ignored in summary-statistics-based fine-mapping with related individuals. In this paper, we show in theory and simulation what modifications are necessary to extend the use of summary statistics to related individuals. The analysis also demonstrates that though existing summary-statistics-based fine-mapping methods can be adapted for related individuals, they appear to have no computational advantage over individual-data-based methods.}, publisher={Cold Spring Harbor Laboratory}, author={Jiang, Jicai}, year={2021}, month={Oct} }
 @article{fang_cai_liu_canela-xandri_gao_jiang_rawlik_li_schroeder_rosen_et al._2020, title={Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle}, volume={30}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85085586286&partnerID=MN8TOARS}, DOI={10.1101/gr.250704.119}, abstractNote={By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testis-specific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.}, number={5}, journal={Genome Research}, author={Fang, L. and Cai, W. and Liu, S. and Canela-Xandri, O. and Gao, Y. and Jiang, J. and Rawlik, K. and Li, B. and Schroeder, S.G. and Rosen, B.D. and et al.}, year={2020}, pages={790–801} }
 @article{lozada‐soto_maltecca_wackel_flowers_gray_he_huang_jiang_tiezzi_2020, title={Evidence for recombination variability in purebred swine populations}, volume={138}, ISSN={0931-2668 1439-0388}, url={http://dx.doi.org/10.1111/jbg.12510}, DOI={10.1111/jbg.12510}, abstractNote={AbstractThis study aimed to investigate interpopulation variation due to sex, breed and age, and the intrapopulation variation in the form of genetic variance for recombination in swine. Genome‐wide recombination rate and recombination occurrences (RO) were traits studied in Landrace (LR) and Large White (LW) male and female populations. Differences were found for sex, breed, sex‐breed interaction, and age effects for genome‐wide recombination rate and RO at one or more chromosomes. Dams were found to have a higher genome‐wide recombination rate and RO at all chromosomes than sires. LW animals had higher genome‐wide recombination rate and RO at seven chromosomes but lower at two chromosomes than LR individuals. The sex‐breed interaction effect did not show any pattern not already observable by sex. Recombination increased with increasing parity in females, while in males no effect of age was observed. We estimated heritabilities and repeatabilities for both investigated traits and obtained the genetic correlation between male and female genome‐wide recombination rate within each of the two breeds studied. Estimates of heritability and repeatability were low (h2 = 0.01–0.26; r = 0.18–0.42) for both traits in all populations. Genetic correlations were high and positive, with estimates of 0.98 and 0.94 for the LR and LW breeds, respectively. We performed a GWAS for genome‐wide recombination rate independently in the four sex/breed populations. The results of the GWAS were inconsistent across the four populations with different significant genomic regions identified. The results of this study provide evidence of variability for recombination in purebred swine populations.}, number={2}, journal={Journal of Animal Breeding and Genetics}, publisher={Wiley}, author={Lozada‐Soto, Emmanuel A. and Maltecca, Christian and Wackel, Hanna and Flowers, William and Gray, Kent and He, Yuqing and Huang, Yijian and Jiang, Jicai and Tiezzi, Francesco}, year={2020}, month={Sep}, pages={259–273} }
 @article{freebern_santos_fang_jiang_parker gaddis_liu_vanraden_maltecca_cole_ma_2020, title={GWAS and fine-mapping of livability and six disease traits in Holstein cattle}, volume={21}, ISSN={["1471-2164"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85077786273&partnerID=MN8TOARS}, DOI={10.1186/s12864-020-6461-z}, abstractNote={Abstract
                Background
                Health traits are of significant economic importance to the dairy industry due to their effects on milk production and associated treatment costs. Genome-wide association studies (GWAS) provide a means to identify associated genomic variants and thus reveal insights into the genetic architecture of complex traits and diseases. The objective of this study is to investigate the genetic basis of seven health traits in dairy cattle and to identify potential candidate genes associated with cattle health using GWAS, fine mapping, and analyses of multi-tissue transcriptome data.
              
                Results
                We studied cow livability and six direct disease traits, mastitis, ketosis, hypocalcemia, displaced abomasum, metritis, and retained placenta, using de-regressed breeding values and more than three million imputed DNA sequence variants. After data edits and filtering on reliability, the number of bulls included in the analyses ranged from 11,880 (hypocalcemia) to 24,699 (livability). GWAS was performed using a mixed-model association test, and a Bayesian fine-mapping procedure was conducted to calculate a posterior probability of causality to each variant and gene in the candidate regions. The GWAS detected a total of eight genome-wide significant associations for three traits, cow livability, ketosis, and hypocalcemia, including the bovine Major Histocompatibility Complex (MHC) region associated with livability. Our fine-mapping of associated regions reported 20 candidate genes with the highest posterior probabilities of causality for cattle health. Combined with transcriptome data across multiple tissues in cattle, we further exploited these candidate genes to identify specific expression patterns in disease-related tissues and relevant biological explanations such as the expression of Group-specific Component (GC) in the liver and association with mastitis as well as the Coiled-Coil Domain Containing 88C (CCDC88C) expression in CD8 cells and association with cow livability.
              
                Conclusions
                Collectively, our analyses report six significant associations and 20 candidate genes of cattle health. With the integration of multi-tissue transcriptome data, our results provide useful information for future functional studies and better understanding of the biological relationship between genetics and disease susceptibility in cattle.
              }, number={1}, journal={BMC GENOMICS}, author={Freebern, Ellen and Santos, Daniel J. A. and Fang, Lingzhao and Jiang, Jicai and Parker Gaddis, Kristen L. and Liu, George E. and VanRaden, Paul M. and Maltecca, Christian and Cole, John B. and Ma, Li}, year={2020}, month={Jan} }
 @article{jiang_ma_prakapenka_vanraden_cole_da_2019, title={A large-scale genome-wide association study in U.S. Holstein cattle}, volume={10}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85067882157&partnerID=MN8TOARS}, DOI={10.3389/fgene.2019.00412}, abstractNote={Genome-wide association study (GWAS) is a powerful approach to identify genomic regions and genetic variants associated with phenotypes. However, only limited mutual confirmation from different studies is available. We conducted a large-scale GWAS using 294,079 first-lactation Holstein cows and identified new additive and dominance effects on five production traits, three fertility traits, and somatic cell score. Four chromosomes had the most significant SNP effects on the five production traits, a Chr14 region containing DGAT1 mostly had positive effects on fat yield and negative effects on milk and protein yields, the 88.07–89.60 Mb region of Chr06 with SLC4A4, GC, NPFFR2, and ADAMTS3 for milk and protein yields, the 30.03–36.67 Mb region of Chr20 with C6 and GHR for milk yield, and the 88.19–88.88 Mb region with ABCC9 as well as the 91.13–94.62 Mb region of Chr05 with PLEKHA5, MGST1, SLC15A5, and EPS8 for fat yield. For fertility traits, the SNP in GC of Chr06, and the SNPs in the 65.02–69.43 Mb region of Chr01 with COX17, ILDR1, and KALRN had the most significant effects for daughter pregnancy rate and cow conception rate, whereas SNPs in AFF1 of Chr06, the 47.54–52.79 Mb region of Chr07, TSPAN4 of Chr29, and NPAS1 of Chr18 had the most significant effects for heifer conception rate. For somatic cell score, GC of Chr06 and PRLR of Chr20 had the most significant effects. A small number of dominance effects were detected for the production traits with far lower statistical significance than the additive effects and for fertility traits with similar statistical significance as the additive effects. Analysis of allelic effects revealed the presence of uni-allelic, asymmetric, and symmetric SNP effects and found the previously reported DGAT1 antagonism was an extreme antagonistic pleiotropy between fat yield and milk and protein yields among all SNPs in this study.}, number={MAY}, journal={Frontiers in Genetics}, author={Jiang, J. and Ma, L. and Prakapenka, D. and VanRaden, P.M. and Cole, J.B. and Da, Y.}, year={2019} }
 @article{fang_zhou_liu_jiang_bickhart_null_li_schroeder_rosen_cole_et al._2019, title={Comparative analyses of sperm DNA methylomes among human, mouse and cattle provide insights into epigenomic evolution and complex traits}, volume={14}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85063393683&partnerID=MN8TOARS}, DOI={10.1080/15592294.2019.1582217}, abstractNote={ABSTRACT Sperm DNA methylation is crucial for fertility and viability of offspring but epigenome evolution in mammals is largely understudied. By comparing sperm DNA methylomes and large-scale genome-wide association study (GWAS) signals between human and cattle, we aimed to examine the DNA methylome evolution and its associations with complex phenotypes in mammals. Our analysis revealed that genes with conserved non-methylated promoters (e.g., ANKS1A and WNT7A) among human and cattle were involved in common system and embryo development, and enriched for GWAS signals of body conformation traits in both species, while genes with conserved hypermethylated promoters (e.g., TCAP and CD80) were engaged in immune responses and highlighted by immune-related traits. On the other hand, genes with human-specific hypomethylated promoters (e.g., FOXP2 and HYDIN) were engaged in neuron system development and enriched for GWAS signals of brain-related traits, while genes with cattle-specific hypomethylated promoters (e.g., LDHB and DGAT2) mainly participated in lipid storage and metabolism. We validated our findings using sperm-retained nucleosome, preimplantation transcriptome, and adult tissue transcriptome data, as well as sequence evolutionary features, including motif binding sites, mutation rates, recombination rates and evolution signatures. In conclusion, our results demonstrate important roles of epigenome evolution in shaping the genetic architecture underlying complex phenotypes, hence enhance signal prioritization in GWAS and provide valuable information for human neurological disorders and livestock genetic improvement.}, number={3}, journal={Epigenetics}, author={Fang, L. and Zhou, Y. and Liu, S. and Jiang, J. and Bickhart, D.M. and Null, D.J. and Li, B. and Schroeder, S.G. and Rosen, B.D. and Cole, J.B. and et al.}, year={2019}, pages={260–276} }
 @article{jiang_cole_freebern_da_vanraden_ma_2019, title={Functional annotation and Bayesian fine-mapping reveals candidate genes for important agronomic traits in Holstein bulls}, volume={2}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85070881839&partnerID=MN8TOARS}, DOI={10.1038/s42003-019-0454-y}, abstractNote={AbstractA hundred years of data collection in dairy cattle can facilitate powerful studies of complex traits. Cattle GWAS have identified many associated genomic regions. With increasing numbers of cattle sequenced, fine-mapping of causal variants is becoming possible. Here we imputed selected sequence variants to 27,214 Holstein bulls that have highly reliable phenotypes for 35 production, reproduction, and body conformation traits. We performed single-marker scans for the 35 traits and multi-trait tests of the three trait groups, revealing 282 candidate QTL for fine-mapping. We developed a Bayesian Fine-MAPping approach (BFMAP) to integrate fine-mapping with functional enrichment analysis. Our fine-mapping identified 69 promising candidate genes, including ABCC9, VPS13B, MGST1, SCD, MKL1, CSN1S1 for production, CHEK2, GC, KALRN for reproduction, and TMTC2, ARRDC3, ZNF613, CCND2, FGF6 for conformation traits. Collectively, these results demonstrated the utility of BFMAP, identified candidate genes, and enhanced our understanding of the genetic basis of cattle complex traits.}, number={1}, journal={Communications Biology}, author={Jiang, J. and Cole, J.B. and Freebern, E. and Da, Y. and VanRaden, P.M. and Ma, L.}, year={2019} }
 @article{fang_jiang_li_zhou_freebern_vanraden_cole_liu_ma_2019, title={Genetic and epigenetic architecture of paternal origin contribute to gestation length in cattle}, volume={2}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85070884992&partnerID=MN8TOARS}, DOI={10.1038/s42003-019-0341-6}, abstractNote={AbstractThe length of gestation can affect offspring health and performance. Both maternal and fetal effects contribute to gestation length; however, paternal contributions to gestation length remain elusive. Using genome-wide association study (GWAS) in 27,214 Holstein bulls with millions of gestation records, here we identify nine paternal genomic loci associated with cattle gestation length. We demonstrate that these GWAS signals are enriched in pathways relevant to embryonic development, and in differentially methylated regions between sperm samples with long and short gestation length. We reveal that gestation length shares genetic and epigenetic architecture in sperm with calving ability, body depth, and conception rate. While several candidate genes are detected in our fine-mapping analysis, we provide evidence indicating ZNF613 as a promising candidate for cattle gestation length. Collectively, our findings support that the paternal genome and epigenome can impact gestation length potentially through regulation of the embryonic development.}, number={1}, journal={Communications Biology}, author={Fang, L. and Jiang, J. and Li, B. and Zhou, Y. and Freebern, E. and Vanraden, P.M. and Cole, J.B. and Liu, G.E. and Ma, L.}, year={2019} }
 @article{fang_zhou_liu_jiang_bickhart_null_li_schroeder_rosen_cole_et al._2019, title={Integrating Signals from Sperm Methylome Analysis and Genome-Wide Association Study for a Better Understanding of Male Fertility in Cattle}, volume={3}, url={https://doi.org/10.3390/epigenomes3020010}, DOI={10.3390/epigenomes3020010}, abstractNote={Decreased male fertility is a big concern in both human society and the livestock industry. Sperm DNA methylation is commonly believed to be associated with male fertility. However, due to the lack of accurate male fertility records (i.e., limited mating times), few studies have investigated the comprehensive impacts of sperm DNA methylation on male fertility in mammals. In this study, we generated 10 sperm DNA methylomes and performed a preliminary correlation analysis between signals from sperm DNA methylation and signals from large-scale (n = 27,214) genome-wide association studies (GWAS) of 35 complex traits (including 12 male fertility-related traits). We detected genomic regions, which experienced DNA methylation alterations in sperm and were associated with aging and extreme fertility phenotypes (e.g., sire-conception rate or SCR). In dynamic hypomethylated regions (HMRs) and partially methylated domains (PMDs), we found genes (e.g., HOX gene clusters and microRNAs) that were involved in the embryonic development. We demonstrated that genomic regions, which gained rather than lost methylations during aging, and in animals with low SCR were significantly and selectively enriched for GWAS signals of male fertility traits. Our study discovered 16 genes as the potential candidate markers for male fertility, including SAMD5 and PDE5A. Collectively, this initial effort supported a hypothesis that sperm DNA methylation may contribute to male fertility in cattle and revealed the usefulness of functional annotations in enhancing biological interpretation and genomic prediction for complex traits and diseases.}, number={2}, journal={Epigenomes}, publisher={MDPI AG}, author={Fang, Lingzhao and Zhou, Yang and Liu, Shuli and Jiang, Jicai and Bickhart, Derek M. and Null, Daniel J. and Li, Bingjie and Schroeder, Steven G. and Rosen, Benjamin D. and Cole, John B. and et al.}, year={2019}, month={May}, pages={10} }
 @article{shen_jiang_seroussi_liu_ma_2018, title={Characterization of recombination features and the genetic basis in multiple cattle breeds}, volume={19}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85046114236&partnerID=MN8TOARS}, DOI={10.1186/s12864-018-4705-y}, abstractNote={Crossover generated by meiotic recombination is a fundamental event that facilitates meiosis and sexual reproduction. Comparative studies have shown wide variation in recombination rate among species, but the characterization of recombination features between cattle breeds has not yet been performed. Cattle populations in North America count millions, and the dairy industry has genotyped millions of individuals with pedigree information that provide a unique opportunity to study breed-level variations in recombination.Based on large pedigrees of Jersey, Ayrshire and Brown Swiss cattle with genotype data, we identified over 3.4 million maternal and paternal crossover events from 161,309 three-generation families. We constructed six breed- and sex-specific genome-wide recombination maps using 58,982 autosomal SNPs for two sexes in the three dairy cattle breeds. A comparative analysis of the six recombination maps revealed similar global recombination patterns between cattle breeds but with significant differences between sexes. We confirmed that male recombination map is 10% longer than the female map in all three cattle breeds, consistent with previously reported results in Holstein cattle. When comparing recombination hotspot regions between cattle breeds, we found that 30% and 10% of the hotspots were shared between breeds in males and females, respectively, with each breed exhibiting some breed-specific hotspots. Finally, our multiple-breed GWAS found that SNPs in eight loci affected recombination rate and that the PRDM9 gene associated with hotspot usage in multiple cattle breeds, indicating a shared genetic basis for recombination across dairy cattle breeds.Collectively, our results generated breed- and sex-specific recombination maps for multiple cattle breeds, provided a comprehensive characterization and comparison of recombination patterns between breeds, and expanded our understanding of the breed-level variations in recombination features within an important livestock species.}, number={1}, journal={BMC Genomics}, author={Shen, B. and Jiang, J. and Seroussi, E. and Liu, G.E. and Ma, L.}, year={2018} }
 @article{determination of quantitative trait nucleotides by concordance analysis between quantitative trait loci and marker genotypes of us holsteins_2018, volume={101}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85049952777&partnerID=MN8TOARS}, DOI={10.3168/jds.2018-14816}, abstractNote={Experimental designs that exploit family information can provide substantial predictive power in quantitative trait nucleotide discovery projects. Concordance between quantitative trait locus genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 30 trait-by-chromosomal segment effects segregating in the US Holstein population with probabilities of <10-20 to accept the null hypotheses of no segregating gene affecting the trait within the chromosomal segment. Genotypes for 83 grandsires and 17,217 sons were determined by either complete sequence or imputation for 3,148,506 polymorphisms across the entire genome; 471 Holstein bulls had a complete genome sequence, including 64 of the grandsires. Complete concordance was obtained only for stature on chromosome 14 and daughter pregnancy rate on chromosome 18. For each quantitative trait locus, effects of the 30 polymorphisms with highest concordance scores for the analyzed trait were computed by stepwise regression for predicted transmitting abilities of 26,750 bulls with progeny test and imputed genotypes. Effects for stature on chromosome 11, daughter pregnancy rate on chromosome 18, and protein percentage on chromosome 20 met 3 criteria: complete or almost complete concordance, nominal significance of the polymorphism effect after correction for all other polymorphisms, and marker coefficient of determination >40% of total multiple-regression coefficient of determination for the 30 polymorphisms with highest concordance. An intronic variant marker on chromosome 5 at 93,945,738 bp explained 7% of variance for fat percentage and 74% of total multiple-marker regression variance but was concordant for only 24 of 30 families. The missense polymorphism Phe279Tyr in GHR at 31,909,478 bp on chromosome 20 was confirmed as the causative mutation for fat and protein concentration. For effect on fat percentage on chromosome 14, 12 additional missense polymorphisms were found that had almost complete concordance with the suggested causative polymorphism (missense mutation Ala232Glu in DGAT1). The only polymorphism found likely to improve predictive power for genomic evaluation of dairy cattle was on chromosome 15; that polymorphism had a frequency of 0.45 for the allele with economically positive effects on all production traits.}, number={10}, journal={Journal of Dairy Science}, year={2018}, pages={9089–9107} }
 @article{jiang_cole_da_vanraden_ma_2018, title={Fast Bayesian fine-mapping of 35 production, reproduction and body conformation traits in dairy cattle}, volume={9}, url={https://doi.org/10.1101/428227}, DOI={10.1101/428227}, abstractNote={AbstractImputation has been routinely used to infer sequence variants in large genotyped populations based on reference populations of sequenced individuals. With increasing numbers of animals sequenced and the implementation of the 1000 Bull Genomes Project, fine-mapping of causal variants for complex traits is becoming possible in cattle. Using 404 ancestor bull sequences as reference, we imputed over 3 million selected sequence variants to 27,214 Holstein bulls with highly reliable phenotypes (breeding values) for 35 production, reproduction, and body conformation traits. We first performed whole-genome single-marker scans for each of the 35 traits using a mixed-model association test. The single-trait association statistics were then merged into multi-trait tests of 3 trait groups: production, reproduction, and body conformation. Both single- and multi-trait GWAS results were used to identify 282 candidate QTL regions for fine-mapping in the cattle genome. To facilitate fast and powerful fine-mapping analyses, we developed a Bayesian Fine-MAPping approach (BFMAP) to integrate fine-mapping with functional enrichment analysis. Our fine-mapping results identified 69 promising candidate genes for dairy traits, including ABCC9, VPS13B, MGST1, SCD, MKL1, and CSN1S1 for production traits; CHEK2, GC, and KALRN for reproduction traits; and TMTC2, ARRDC3, ZNF613, CCND2, and FGF6 for body conformation traits. Based on existing functional annotation data for cattle, we revealed biologically meaningful enrichment in our fine-mapped variants that can be readily tested in functional validation studies. In summary, these results demonstrated the utility of a fast Bayesian approach for fine-mapping and functional enrichment analysis, identified candidate causative genes and variants, and enhanced our understanding of the genetic basis of complex traits in dairy cattle.}, publisher={Cold Spring Harbor Laboratory}, author={Jiang, Jicai and Cole, John B. and Da, Yang and VanRaden, Paul M. and Ma, Li}, year={2018}, month={Sep} }
 @article{feng_jiang_padhi_ning_fu_wang_mrode_liu_2017, title={Characterization of genome-wide segmental duplications reveals a common genomic feature of association with immunity among domestic animals}, volume={18}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85018526602&partnerID=MN8TOARS}, DOI={10.1186/s12864-017-3690-x}, abstractNote={Segmental duplications (SDs) commonly exist in plant and animal genomes, playing crucial roles in genomic rearrangement, gene innovation and the formation of copy number variants. However, they have received little attention in most livestock species.Aiming at characterizing SDs across the genomes of diverse livestock species, we mapped genome-wide SDs of horse, rabbit, goat, sheep and chicken, and also enhanced the existing SD maps of cattle and pig genomes based on the most updated genome assemblies. We adopted two different detection strategies, whole genome analysis comparison and whole genome shotgun sequence detection, to pursue more convincing findings. Accordingly we identified SDs for each species with the length of from 21.7 Mb to 164.1 Mb, and 807 to 4,560 genes were harboured within the SD regions across different species. More interestingly, many of these SD-related genes were involved in the process of immunity and response to external stimuli. We also found the existence of 59 common genes within SD regions in all studied species except goat. These common genes mainly consisted of both UDP glucuronosyltransferase and Interferon alpha families, implying the connection between SDs and the evolution of these gene families.Our findings provide insights into livestock genome evolution and offer rich genomic sources for livestock genomic research.}, number={1}, journal={BMC Genomics}, author={Feng, X. and Jiang, J. and Padhi, A. and Ning, C. and Fu, J. and Wang, A. and Mrode, R. and Liu, J.-F.}, year={2017} }
 @article{zhou_shen_jiang_padhi_park_oswalt_sattler_telugu_chen_cole_et al._2018, title={Construction of PRDM9 allele-specific recombination maps in cattle using large-scale pedigree analysis and genome-wide single sperm genomics}, volume={25}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85046689913&partnerID=MN8TOARS}, DOI={10.1093/dnares/dsx048}, abstractNote={Abstract PRDM9 contributes to hybrid sterility and species evolution. However, its role is to be confirmed in cattle, a major domesticated livestock species. We previously found an association near PRDM9 with cattle recombination features, but the causative variants are still unknown. Using millions of genotyped cattle with pedigree information, we characterized five PRDM9 alleles and generated allele-specific recombination maps. By examining allele-specific recombination patterns, we observed the impact of PRDM9 on global distribution of recombination, especially in the two ends of chromosomes. We also showed strong associations between recombination hotspot regions and functional mutations within PRDM9 zinc finger domain. More importantly, we found one allele of PRDM9 to be very different from others in both protein composition and recombination landscape, indicating the causative role of this allele on the association between PRDM9 and cattle recombination. When comparing recombination maps from sperm and pedigree data, we observed similar genome-wide recombination patterns, validating the quality of pedigree-based results. Collectively, these evidence supported PRDM9 alleles as causal variants for the reported association with cattle recombination. Our study comprehensively surveyed the bovine PRDM9 alleles, generated allele-specific recombination maps, and expanded our understanding of the role of PRDM9 on genome distribution of recombination.}, number={2}, journal={DNA Research}, publisher={Oxford University Press (OUP)}, author={Zhou, Yang and Shen, Botong and Jiang, Jicai and Padhi, Abinash and Park, Ki-Eun and Oswalt, Adam and Sattler, Charles G and Telugu, Bhanu P and Chen, Hong and Cole, John B and et al.}, year={2018}, pages={183–194} }
 @article{jiang_shen_o’connell_vanraden_cole_ma_2017, title={Dissection of additive, dominance, and imprinting effects for production and reproduction traits in Holstein cattle}, volume={18}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85020042345&partnerID=MN8TOARS}, DOI={10.1186/s12864-017-3821-4}, abstractNote={Although genome-wide association and genomic selection studies have primarily focused on additive effects, dominance and imprinting effects play an important role in mammalian biology and development. The degree to which these non-additive genetic effects contribute to phenotypic variation and whether QTL acting in a non-additive manner can be detected in genetic association studies remain controversial. To empirically answer these questions, we analyzed a large cattle dataset that consisted of 42,701 genotyped Holstein cows with genotyped parents and phenotypic records for eight production and reproduction traits. SNP genotypes were phased in pedigree to determine the parent-of-origin of alleles, and a three-component GREML was applied to obtain variance decomposition for additive, dominance, and imprinting effects. The results showed a significant non-zero contribution from dominance to production traits but not to reproduction traits. Imprinting effects significantly contributed to both production and reproduction traits. Interestingly, imprinting effects contributed more to reproduction traits than to production traits. Using GWAS and imputation-based fine-mapping analyses, we identified and validated a dominance association signal with milk yield near RUNX2, a candidate gene that has been associated with milk production in mice. When adding non-additive effects into the prediction models, however, we observed little or no increase in prediction accuracy for the eight traits analyzed. Collectively, our results suggested that non-additive effects contributed a non-negligible amount (more for reproduction traits) to the total genetic variance of complex traits in cattle, and detection of QTLs with non-additive effect is possible in GWAS using a large dataset.}, number={1}, journal={BMC Genomics}, author={Jiang, J. and Shen, B. and O’Connell, J.R. and VanRaden, P.M. and Cole, J.B. and Ma, L.}, year={2017} }
 @article{padhi_shen_jiang_zhou_liu_ma_2017, title={Ruminant-specific multiple duplication events of PRDM9 before speciation}, volume={17}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85015787763&partnerID=MN8TOARS}, DOI={10.1186/s12862-017-0892-4}, abstractNote={Understanding the genetic and evolutionary mechanisms of speciation genes in sexually reproducing organisms would provide important insights into mammalian reproduction and fitness. PRDM9, a widely known speciation gene, has recently gained attention for its important role in meiotic recombination and hybrid incompatibility. Despite the fact that PRDM9 is a key regulator of recombination and plays a dominant role in hybrid incompatibility, little is known about the underlying genetic and evolutionary mechanisms that generated multiple copies of PRDM9 in many metazoan lineages. The present study reports (1) evidence of ruminant-specific multiple gene duplication events, which likely have had occurred after the ancestral ruminant population diverged from its most recent common ancestor and before the ruminant speciation events, (2) presence of three copies of PRDM9, one copy (lineages I) in chromosome 1 (chr1) and two copies (lineages II & III) in chromosome X (chrX), thus indicating the possibility of ancient inter- and intra-chromosomal unequal crossing over and gene conversion events, (3) while lineages I and II are characterized by the presence of variable tandemly repeated C2H2 zinc finger (ZF) arrays, lineage III lost these arrays, and (4) C2H2 ZFs of lineages I and II, particularly the amino acid residues located at positions −1, 3, and 6 have evolved under strong positive selection. Our results demonstrated two gene duplication events of PRDM9 in ruminants: an inter-chromosomal duplication that occurred between chr1 and chrX, and an intra-chromosomal X-linked duplication, which resulted in two additional copies of PRDM9 in ruminants. The observation of such duplication between chrX and chr1 is rare and may possibly have happened due to unequal crossing-over millions of years ago when sex chromosomes were independently derived from a pair of ancestral autosomes. Two copies (lineages I & II) are characterized by the presence of variable sized tandem-repeated C2H2 ZFs and evolved under strong positive selection and concerted evolution, supporting the notion of well-established Red Queen hypothesis. Collectively, gene duplication, concerted evolution, and positive selection are the likely driving forces for the expansion of ruminant PRDM9 sub-family.}, number={1}, journal={BMC Evolutionary Biology}, author={Padhi, A. and Shen, B. and Jiang, J. and Zhou, Y. and Liu, G.E. and Ma, L.}, year={2017} }
 @article{wang_shen_jiang_li_ma_2016, title={Effect of sex, age and genetics on crossover interference in cattle}, volume={6}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84999737996&partnerID=MN8TOARS}, DOI={10.1038/srep37698}, abstractNote={AbstractCrossovers generated by homologous recombination ensure proper chromosome segregation during meiosis. Crossover interference results in chiasmata being more evenly distributed along chromosomes, but the mechanism underlying crossover interference remains elusive. Based on large pedigrees of Holstein and Jersey cattle with genotype data, we extracted three-generation families, including 147,327 male and 71,687 female meioses in Holstein, and 108,163 male and 37,008 female meioses in Jersey, respectively. We identified crossovers in these meioses and fitted the Housworth-Stahl “interference-escape” model to study crossover interference patterns in the cattle genome. Our result reveals that the degree of crossover interference is stronger in females than in males. We found evidence for inter-chromosomal variation in the level of crossover interference, with smaller chromosomes exhibiting stronger interference. In addition, crossover interference levels decreased with maternal age. Finally, sex-specific GWAS analyses identified one locus near the NEK9 gene on chromosome 10 to have a significant effect on crossover interference levels. This locus has been previously associated with recombination rate in cattle. Collectively, this large-scale analysis provided a comprehensive description of crossover interference across chromosome, sex and age groups, identified associated candidate genes, and produced useful insights into the mechanism of crossover interference.}, journal={Scientific Reports}, author={Wang, Z. and Shen, B. and Jiang, J. and Li, J. and Ma, L.}, year={2016} }
 @article{xie_li_li_ran_wang_jiang_zhao_2016, title={Identification of copy number variations in Xiang and Kele pigs}, volume={11}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84959423337&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0148565}, abstractNote={Xiang and Kele pigs are two well-known local Chinese pig breeds that possess rich genetic resources and have enormous economic and scientific value. We performed a comprehensive genomic analysis of the copy number variations (CNVs) in these breeds. CNVs are one of the most important forms of genomic variation and have profound effects on phenotypic variation. In this study, PorcineSNP60 genotyping data from 98 Xiang pigs and 22 Kele pigs were used to identify CNVs. In total, 172 candidate CNV regions (CNVRs) were identified, ranging from 3.19 kb to 8175.26 kb and covering 80.41 Mb of the pig genome. Approximately 56.40% (97/172) of the CNVRs overlapped with those identified in seven previous studies, and 43.60% (75/172) of the identified CNVRs were novel. Of the identified CNVRs, 82 (47 gain, 33 loss, and two gain-loss events that covered 4.58 Mb of the pig genome) were found only in a Xiang population with a large litter size. In contrast, 13 CNVRs (8 gain and 5 loss events) were unique to a Xiang population with small litter sizes, and 30 CNVRs (14 loss and 16 gain events) were unique to Kele pigs. The CNVRs span approximately 660 annotated Sus scrofa genes that are significantly enriched for specific biological functions, such as sensory perception, cognition, reproduction, ATP biosynthetic processes, and neurological processes. Many CNVR-associated genes, particularly the genes involved in reproductive traits, differed between the Xiang populations with large and small litter sizes, and these genes warrant further investigation due to their importance in determining the reproductive performance of Xiang pigs. Our results provide meaningful information about genomic variation, which may be useful in future assessments of the associations between CNVs and important phenotypes in Xiang and Kele pigs to ultimately help protect these rare breeds.}, number={2}, journal={PLoS ONE}, author={Xie, J. and Li, R. and Li, S. and Ran, X. and Wang, J. and Jiang, J. and Zhao, P.}, year={2016} }
 @article{zhu_zhu_jiang_niu_wang_wu_xu_chen_zhang_gao_et al._2016, title={The impact of variable degrees of freedom and scale parameters in Bayesian methods for genomic prediction in Chinese Simmental beef cattle}, volume={11}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84969529212&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0154118}, abstractNote={Three conventional Bayesian approaches (BayesA, BayesB and BayesCπ) have been demonstrated to be powerful in predicting genomic merit for complex traits in livestock. A priori, these Bayesian models assume that the non-zero SNP effects (marginally) follow a t-distribution depending on two fixed hyperparameters, degrees of freedom and scale parameters. In this study, we performed genomic prediction in Chinese Simmental beef cattle and treated degrees of freedom and scale parameters as unknown with inappropriate priors. Furthermore, we compared the modified methods (BayesFA, BayesFB and BayesFCπ) with their corresponding counterparts using simulation datasets. We found that the modified methods with distribution assumed to the two hyperparameters were beneficial for improving the predictive accuracy. Our results showed that the predictive accuracies of the modified methods were slightly higher than those of their counterparts especially for traits with low heritability and a small number of QTLs. Moreover, cross-validation analysis for three traits, namely carcass weight, live weight and tenderloin weight, in 1136 Simmental beef cattle suggested that predictive accuracy of BayesFCπ noticeably outperformed BayesCπ with the highest increase (3.8%) for live weight using the cohort masking cross-validation.}, number={5}, journal={PLoS ONE}, author={Zhu, B. and Zhu, M. and Jiang, J. and Niu, H. and Wang, Y. and Wu, Y. and Xu, L. and Chen, Y. and Zhang, L. and Gao, X. and et al.}, year={2016} }
 @article{yang_jiang_liu_wang_guo_zhang_jiang_2016, title={Differential expression of genes in milk of dairy cattle during lactation}, volume={47}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84952360249&partnerID=MN8TOARS}, DOI={10.1111/age.12394}, abstractNote={SummaryThe milk fat globule (MFG) is one of the most representative of mammary gland tissues and can be utilized to study gene expression of lactating cows during lactation. In this study, RNA‐seq technology was employed to detect differential expression of genes in MFGs at day 10 and day 70 after calving between two groups of cows with extremely high (H group) and low (L group) 305‐day milk yield, milk fat yield and milk protein yield. In total, 1232, 81, 429 and 178 significantly differentially expressed genes (false discovery rate q < 0.05) were detected between H10 and L10, H70 and L70, H10 and H70, and L10 and L70 respectively. Gene Ontology enrichment and pathway analysis revealed that these differentially expressed genes were enriched in biological processes involved in mammary gland development, protein and lipid metabolism process, signal transduction, cellular process, differentiation and immune function. Among these differentially expressed genes, 178 (H10 vs. L10), 4 (H70 vs. L70), 68 (H10 vs. H70) and 22 (L10 vs. L70) were found to be located within previously reported QTL regions for milk production traits. Based on these results, some promising candidate genes for milk production traits in dairy cattle were suggested.}, number={2}, journal={Animal Genetics}, author={Yang, J. and Jiang, J. and Liu, X. and Wang, H. and Guo, G. and Zhang, Q. and Jiang, L.}, year={2016}, pages={174–180} }
 @article{wang_jiang_wang_kang_zhang_liu_2015, title={Improved detection and characterization of copy number variations among diverse pig breeds by array CGH}, volume={5}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84930855069&partnerID=MN8TOARS}, DOI={10.1534/g3.115.018473}, abstractNote={AbstractAs a major component of genomic variation, copy number variations (CNVs) are considered as promising markers for some phenotypic and economically important traits in domestic animals. Using a custom-designed 1M array CGH (aCGH), we performed CNV discovery in 12 pig samples from one Asian wild boar population, six Chinese indigenous breeds, and two European commercial breeds. In total, we identified 758 CNV regions (CNVRs), covering 47.43 Mb of the pig genome sequence. Of the total porcine genes, 1295 genes were completely or partially overlapped with the identified CNVRs, which enriched in the terms related to sensory perception of the environment, neurodevelopmental processes, response to external stimuli, and immunity. Further probing the potential functions of these genes, we also found a suite of genes related important traits, which make them a promising resource for exploring the genetic basis of phenotype differences among diverse pig breeds. Compared with previous relevant studies, the current study highlights that different platforms can complement each other, and the combined implementation of different platforms is beneficial to achieve the most comprehensive CNV calls. CNVs detected in diverse populations herein are essentially complementary to the CNV map in the pig genome, which would be helpful for understanding the pig genome variants and investigating the associations between various phenotypes and CNVs.}, number={6}, journal={G3: Genes, Genomes, Genetics}, author={Wang, J. and Jiang, J. and Wang, H. and Kang, H. and Zhang, Q. and Liu, J.-F.}, year={2015}, pages={1253–1261} }
 @article{jiang_zhang_ma_li_wang_liu_2015, title={Joint prediction of multiple quantitative traits using a Bayesian multivariate antedependence model}, volume={115}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84930864947&partnerID=MN8TOARS}, DOI={10.1038/hdy.2015.9}, abstractNote={Predicting organismal phenotypes from genotype data is important for preventive and personalized medicine as well as plant and animal breeding. Although genome-wide association studies (GWAS) for complex traits have discovered a large number of trait- and disease-associated variants, phenotype prediction based on associated variants is usually in low accuracy even for a high-heritability trait because these variants can typically account for a limited fraction of total genetic variance. In comparison with GWAS, the whole-genome prediction (WGP) methods can increase prediction accuracy by making use of a huge number of variants simultaneously. Among various statistical methods for WGP, multiple-trait model and antedependence model show their respective advantages. To take advantage of both strategies within a unified framework, we proposed a novel multivariate antedependence-based method for joint prediction of multiple quantitative traits using a Bayesian algorithm via modeling a linear relationship of effect vector between each pair of adjacent markers. Through both simulation and real-data analyses, our studies demonstrated that the proposed antedependence-based multiple-trait WGP method is more accurate and robust than corresponding traditional counterparts (Bayes A and multi-trait Bayes A) under various scenarios. Our method can be readily extended to deal with missing phenotypes and resequence data with rare variants, offering a feasible way to jointly predict phenotypes for multiple complex traits in human genetic epidemiology as well as plant and livestock breeding.}, number={1}, journal={Heredity}, publisher={Springer Nature}, author={Jiang, J and Zhang, Q and Ma, L and Li, J and Wang, Z and Liu, J-F}, year={2015}, month={Apr}, pages={29–36} }
 @article{wang_jiang_wang_kang_zhang_liu_2014, title={Enhancing genome-wide copy number variation identification by high density array CGH using diverse resources of pig breeds}, volume={9}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84900298286&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0087571}, abstractNote={Copy number variations (CNVs) are important forms of genomic variation, and have attracted extensive attentions in humans as well as domestic animals. In the study, using a custom-designed 2.1 M array comparative genomic hybridization (aCGH), genome-wide CNVs were identified among 12 individuals from diverse pig breeds, including one Asian wild population, six Chinese indigenous breeds and two modern commercial breeds (Yorkshire and Landrace), with one individual of the other modern commercial breed, Duroc, as the reference. A total of 1,344 CNV regions (CNVRs) were identified, covering 47.79 Mb (∼1.70%) of the pig genome. The length of these CNVRs ranged from 3.37 Kb to 1,319.0 Kb with a mean of 35.56 Kb and a median of 11.11 Kb. Compared with similar studies reported, most of the CNVRs (74.18%) were firstly identified in present study. In order to confirm these CNVRs, 21 CNVRs were randomly chosen to be validated by quantitative real time PCR (qPCR) and a high rate (85.71%) of confirmation was obtained. Functional annotation of CNVRs suggested that the identified CNVRs have important function, and may play an important role in phenotypic and production traits difference among various breeds. Our results are essential complementary to the CNV map in the pig genome, which will provide abundant genetic markers to investigate association studies between various phenotypes and CNVs in pigs.}, number={1}, journal={PLoS ONE}, author={Wang, J. and Jiang, J. and Wang, H. and Kang, H. and Zhang, Q. and Liu, J.-F.}, year={2014} }
 @article{jiang_wang_wang_zhang_kang_feng_wang_yin_bao_zhang_et al._2014, title={Global copy number analyses by next generation sequencing provide insight into pig genome variation}, volume={15}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84904080523&partnerID=MN8TOARS}, DOI={10.1186/1471-2164-15-593}, abstractNote={Copy number variations (CNVs) confer significant effects on genetic innovation and phenotypic variation. Previous CNV studies in swine seldom focused on in-depth characterization of global CNVs. Using whole-genome assembly comparison (WGAC) and whole-genome shotgun sequence detection (WSSD) approaches by next generation sequencing (NGS), we probed formation signatures of both segmental duplications (SDs) and individualized CNVs in an integrated fashion, building the finest resolution CNV and SD maps of pigs so far. We obtained copy number estimates of all protein-coding genes with copy number variation carried by individuals, and further confirmed two genes with high copy numbers in Meishan pigs through an enlarged population. We determined genome-wide CNV hotspots, which were significantly enriched in SD regions, suggesting evolution of CNV hotspots may be affected by ancestral SDs. Through systematically enrichment analyses based on simulations and bioinformatics analyses, we revealed CNV-related genes undergo a different selective constraint from those CNV-unrelated regions, and CNVs may be associated with or affect pig health and production performance under recent selection. Our studies lay out one way for characterization of CNVs in the pig genome, provide insight into the pig genome variation and prompt CNV mechanisms studies when using pigs as biomedical models for human diseases.}, number={1}, journal={BMC Genomics}, author={Jiang, J. and Wang, J. and Wang, H. and Zhang, Y. and Kang, H. and Feng, X. and Wang, J. and Yin, Z. and Bao, W. and Zhang, Q. and et al.}, year={2014} }
 @article{jiang_liu_yang_wang_jiang_liu_he_ding_liu_zhang_2014, title={Targeted resequencing of GWAS loci reveals novel genetic variants for milk production traits}, volume={15}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84925677026&partnerID=MN8TOARS}, DOI={10.1186/1471-2164-15-1105}, abstractNote={Genome wide association study (GWAS) has been proven to be a powerful tool for detecting genomic variants associated with complex traits. However, the specific genes and causal variants underlying these traits remain unclear. Here, we used target-enrichment strategy coupled with next generation sequencing technique to study target regions which were found to be associated with milk production traits in dairy cattle in our previous GWAS. Among the large amount of novel variants detected by targeted resequencing, we selected 200 SNPs for further association study in a population consisting of 2634 cows. Sixty six SNPs distributed in 53 genes were identified to be associated significantly with on milk production traits. Of the 53 genes, 26 were consistent with our previous GWAS results. We further chose 20 significant genes to analyze their mRNA expression in different tissues of lactating cows, of which 15 were specificly highly expressed in mammary gland. Our study illustrates the potential for identifying causal mutations for milk production traits using target-enrichment resequencing and extends the results of GWAS by discovering new and potentially functional mutations.}, number={1}, journal={BMC Genomics}, author={Jiang, L. and Liu, X. and Yang, J. and Wang, H. and Jiang, J. and Liu, L. and He, S. and Ding, X. and Liu, J. and Zhang, Q.}, year={2014} }
 @article{pan_zhang_jiang_jiang_zhang_liu_2013, title={Genome-Wide Detection of Selective Signature in Chinese Holstein}, volume={8}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84875518103&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0060440}, abstractNote={Selective signatures in whole genome can help us understand the mechanisms of selection and target causal variants for breeding program. In present study, we performed Extended Haplotype Homozygosity (EHH) tests to identify significant core regions harboring such signals in Chinese Holstein, and then verified the biological significance of these identified regions based on commonly-used bioinformatics analyses. Results showed a total of 125 significant regions in entire genome containing some of important functional genes such as LEP, ABCG2, CSN1S1, CSN3 and TNF based on the Gene Ontology database. Some of these annotated genes involved in the core regions overlapped with those identified in our previous GWAS as well as those involved in a recently constructed candidate gene database for cattle, further indicating these genes under positive selection maybe underlie milk production traits and other important traits in Chinese Holstein. Furthermore, in the enrichment analyses for the second level GO terms and pathways, we observed some significant terms over represented in these identified regions as compared to the entire bovine genome. This indicates that some functional genes associated with milk production traits, as reflected by GO terms, could be clustered in core regions, which provided promising evidence for the exploitability of the core regions identified by EHH tests. Findings in our study could help detect functional candidate genes under positive selection for further genetic and breeding research in Chinese Holstein.}, number={3}, journal={PLoS ONE}, author={Pan, D. and Zhang, S. and Jiang, J. and Jiang, L. and Zhang, Q. and Liu, J.F.}, year={2013} }
 @article{jiang_jiang_yang_liu_wang_wang_ding_liu_zhang_2013, title={Genome-wide detection of copy number variations using high-density SNP genotyping platforms in Holsteins}, volume={14}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84874233545&partnerID=MN8TOARS}, DOI={10.1186/1471-2164-14-131}, abstractNote={Abstract
          
            Background
            Copy number variations (CNVs) are widespread in the human or animal genome and are a significant source of genetic variation, which has been demonstrated to play an important role in phenotypic diversity. Advances in technology have allowed for identification of a large number of CNVs in cattle. Comprehensive explore novel CNVs in the bovine genome would provide valuable information for functional analyses of genome structural variation and facilitating follow-up association studies between complex traits and genetic variants.
          
          
            Results
            In this study, we performed a genome-wide CNV detection based on high-density SNP genotyping data of 96 Chinese Holstein cattle. A total of 367 CNV regions (CNVRs) across the genome were identified, which cover 42.74Mb of the cattle genome and correspond to 1.61% of the genome sequence. The length of the CNVRs on autosomes range from 10.76 to 2,806.42 Kb with an average of 96.23 Kb. 218 out of these CNVRs contain 610 annotated genes, which possess a wide spectrum of molecular functions. To confirm these findings, quantitative PCR (qPCR) was performed for 17 CNVRs and 13(76.5%) of them were successfully validated.
          
          
            Conclusions
            Our study demonstrates the high density SNP array can significantly improve the accuracy and sensitivity of CNV calling. Integration of different platforms can enhance the detection of genomic structure variants. Our results provide a significant replenishment for the high resolution map of copy number variation in the bovine genome and valuable information for investigation of genomic structural variation underlying traits of interest in cattle.
          }, number={1}, journal={BMC Genomics}, author={Jiang, L. and Jiang, J. and Yang, J. and Liu, X. and Wang, J. and Wang, H. and Ding, X. and Liu, J. and Zhang, Q.}, year={2013} }
 @article{wang_wang_jiang_kang_feng_zhang_liu_2013, title={Identification of Genome-Wide Copy Number Variations among Diverse Pig Breeds Using SNP Genotyping Arrays}, volume={8}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84880730380&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0068683}, abstractNote={Copy number variations (CNVs) are important forms of genetic variation complementary to SNPs, and can be considered as promising markers for some phenotypic and economically important traits or diseases susceptibility in domestic animals. In the present study, we performed a genome-wide CNV identification in 14 individuals selected from diverse populations, including six types of Chinese indigenous breeds, one Asian wild boar population, as well as three modern commercial foreign breeds. We identified 63 CNVRs in total, which covered 9.98 Mb of polymorphic sequence and corresponded to 0.36% of the genome sequence. The length of these CNVRs ranged from 3.20 to 827.21 kb, with an average of 158.37 kb and a median of 97.85 kb. Functional annotation revealed these identified CNVR have important molecular function, and may play an important role in exploring the genetic basis of phenotypic variability and disease susceptibility among pigs. Additionally, to confirm these potential CNVRs, we performed qPCR for 12 randomly selected CNVRs and 8 of them (66.67%) were confirmed successfully. CNVs detected in diverse populations herein are essential complementary to the CNV map in the pig genome, which provide an important resource for studies of genomic variation and the association between various economically important traits and CNVs.}, number={7}, journal={PLoS ONE}, author={Wang, J. and Wang, H. and Jiang, J. and Kang, H. and Feng, X. and Zhang, Q. and Liu, J.-F.}, year={2013} }
 @article{wang_jiang_fu_jiang_ding_liu_zhang_2012, title={A genome-wide detection of copy number variations using SNP genotyping arrays in swine}, volume={13}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84862529082&partnerID=MN8TOARS}, DOI={10.1186/1471-2164-13-273}, abstractNote={Abstract
          
            Background
            Copy Number Variations (CNVs) have been shown important in both normal phenotypic variability and disease susceptibility, and are increasingly accepted as another important source of genetic variation complementary to single nucleotide polymorphism (SNP). Comprehensive identification and cataloging of pig CNVs would be of benefit to the functional analyses of genome variation.
          
          
            Results
            In this study, we performed a genome-wide CNV detection based on the Porcine SNP60 genotyping data of 474 pigs from three pure breed populations (Yorkshire, Landrace and Songliao Black) and one Duroc × Erhualian crossbred population. A total of 382 CNV regions (CNVRs) across genome were identified, which cover 95.76Mb of the pig genome and correspond to 4.23% of the autosomal genome sequence. The length of these CNVRs ranged from 5.03 to 2,702.7kb with an average of 250.7kb, and the frequencies of them varied from 0.42 to 20.87%. These CNVRs contains 1468 annotated genes, which possess a great variety of molecular functions, making them a promising resource for exploring the genetic basis of phenotypic variation within and among breeds. To confirmation of these findings, 18 CNVRs representing different predicted status and frequencies were chosen for validation via quantitative real time PCR (qPCR). Accordingly, 12 (66.67%) of them was successfully confirmed.
          
          
            Conclusions
            Our results demonstrated that currently available Porcine SNP60 BeadChip can be used to capture CNVs efficiently. Our study firstly provides a comprehensive map of copy number variation in the pig genome, which would be of help for understanding the pig genome and provide preliminary foundation for investigating the association between various phenotypes and CNVs.
          }, number={1}, journal={BMC Genomics}, author={Wang, J. and Jiang, J. and Fu, W. and Jiang, L. and Ding, X. and Liu, J.-F. and Zhang, Q.}, year={2012} }
 @article{zhou_liu_jiang_yu_zhang_2012, title={Differential gene expression profiling of porcine epithelial cells infected with three enterotoxigenic Escherichia coli strains}, volume={13}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84867605132&partnerID=MN8TOARS}, DOI={10.1186/1471-2164-13-330}, abstractNote={Abstract
          
            Background
            Enterotoxigenic Escherichia coli (ETEC) is one of the most important pathogenic bacteria causing severe diarrhoea in human and pigs. In ETEC strains, the fimbrial types F4 and F18 are commonly found differently colonized within the small intestine and cause huge economic losses in the swine industry annually worldwide. To address the underlying mechanism, we performed a transcriptome study of porcine intestinal epithelial cells (IPEC-J2) with and without infection of three representative ETEC strains.
          
          
            Results
            A total 2443, 3493 and 867 differentially expressed genes were found in IPEC-J2 cells infected with F4ab ETEC (CF4ab), with F4ac ETEC (CF4ac) and with F18ac ETEC (CF18ac) compared to the cells without infection (control), respectively. The number of differentially expressed genes between CF4ab and CF4ac, CF4ab and CF18ac, and CF4ac and CF18ac were 77, 1446 and 1629, respectively. The gene ontology and pathway analysis showed that the differentially expressed genes in CF4ab
              vs control are significantly involved in cell-cycle progress and amino acid metabolism, while the clustered terms of the differentially expressed genes in CF4ac
              vs control comprise immune, inflammation and wounding response and apoptosis as well as cell cycle progress and proteolysis. Differentially expressed genes between CF18ac
              vs control are mainly involved in cell-cycle progression and immune response. Furthermore, fundamental differences were observed in expression levels of immune-related genes among the three ETEC treatments, especially for the important pro-inflammatory molecules, including IL-6, IL-8, TNF-α, CCL20, CXCL2 etc.
          
          
            Conclusions
            The discovery in this study provides insights into the interaction of porcine intestinal epithelial cells with F4 ETECs and F18 ETEC, respectively. The genes induced by ETECs with F4 versus F18 fimbriae suggest why ETEC with F4 may be more virulent compared to F18 which seems to elicit milder effects.
          }, number={1}, journal={BMC Genomics}, author={Zhou, C. and Liu, Z. and Jiang, J. and Yu, Y. and Zhang, Q.}, year={2012} }
 @article{jiang_jiang_wang_ding_liu_zhang_2012, title={Genome-Wide Identification of Copy Number Variations in Chinese Holstein}, volume={7}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84868688073&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0048732}, abstractNote={Recent studies of mammalian genomes have uncovered the vast extent of copy number variations (CNVs) that contribute to phenotypic diversity. Compared to SNP, a CNV can cover a wider chromosome region, which may potentially incur substantial sequence changes and induce more significant effects on phenotypes. CNV has been becoming an alternative promising genetic marker in the field of genetic analyses. Here we firstly report an account of CNV regions in the cattle genome in Chinese Holstein population. The Illumina Bovine SNP50K Beadchips were used for screening 2047 Holstein individuals. Three different programes (PennCNV, cnvPartition and GADA) were implemented to detect potential CNVs. After a strict CNV calling pipeline, a total of 99 CNV regions were identified in cattle genome. These CNV regions cover 23.24 Mb in total with an average size of 151.69 Kb. 52 out of these CNV regions have frequencies of above 1%. 51 out of these CNV regions completely or partially overlap with 138 cattle genes, which are significantly enriched for specific biological functions, such as signaling pathway, sensory perception response and cellular processes. The results provide valuable information for constructing a more comprehensive CNV map in the cattle genome and offer an important resource for investigation of genome structure and genomic variation underlying traits of interest in cattle.}, number={11}, journal={PLoS ONE}, author={Jiang, L. and Jiang, J. and Wang, J. and Ding, X. and Liu, J. and Zhang, Q.}, year={2012} }
 @article{jiang_jiang_zhou_fu_liu_zhang_2011, title={Snat: A SNP annotation tool for bovine by integrating various sources of genomic information}, volume={12}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-80053497706&partnerID=MN8TOARS}, DOI={10.1186/1471-2156-12-85}, abstractNote={Abstract
          
            Background
            Most recently, with maturing of bovine genome sequencing and high throughput SNP genotyping technologies, a large number of significant SNPs associated with economic important traits can be identified by genome-wide association studies (GWAS). To further determine true association findings in GWAS, the common strategy is to sift out most promising SNPs for follow-up replication studies. Hence it is crucial to explore the functional significance of the candidate SNPs in order to screen and select the potential functional ones. To systematically prioritize these statistically significant SNPs and facilitate follow-up replication studies, we developed a bovine SNP annotation tool (Snat) based on a web interface.
          
          
            Results
            With Snat, various sources of genomic information are integrated and retrieved from several leading online databases, including SNP information from dbSNP, gene information from Entrez Gene, protein features from UniProt, linkage information from AnimalQTLdb, conserved elements from UCSC Genome Browser Database and gene functions from Gene Ontology (GO), KEGG PATHWAY and Online Mendelian Inheritance in Animals (OMIA). Snat provides two different applications, including a CGI-based web utility and a command-line version, to access the integrated database, target any single nucleotide loci of interest and perform multi-level functional annotations. For further validation of the practical significance of our study, SNPs involved in two commercial bovine SNP chips, i.e., the Affymetrix Bovine 10K chip array and the Illumina 50K chip array, have been annotated by Snat, and the corresponding outputs can be directly downloaded from Snat website. Furthermore, a real dataset involving 20 identified SNPs associated with milk yield in our recent GWAS was employed to demonstrate the practical significance of Snat.
          
          
            Conclusions
            To our best knowledge, Snat is one of first tools focusing on SNP annotation for livestock. Snat confers researchers with a convenient and powerful platform to aid functional analyses and accurate evaluation on genes/variants related to SNPs, and facilitates follow-up replication studies in the post-GWAS era.
          }, journal={BMC Genetics}, author={Jiang, J. and Jiang, L. and Zhou, B. and Fu, W. and Liu, J.-F. and Zhang, Q.}, year={2011} }