@article{tiezzi_parker-gaddis_cole_clay_maltecca_2015, title={A Genome-Wide Association Study for Clinical Mastitis in First Parity US Holstein Cows Using Single-Step Approach and Genomic Matrix Re-Weighting Procedure}, volume={10}, ISSN={["1932-6203"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84922687710&partnerID=MN8TOARS}, DOI={10.1371/journal.pone.0114919}, abstractNote={Clinical mastitis (CM) is one of the health disorders with large impacts on dairy farming profitability and animal welfare. The objective of this study was to perform a genome-wide association study (GWAS) for CM in first-lactation Holstein. Producer-recorded mastitis event information for 103,585 first-lactation cows were used, together with genotype information on 1,361 bulls from the Illumina BovineSNP50 BeadChip. Single-step genomic-BLUP methodology was used to incorporate genomic data into a threshold-liability model. Association analysis confirmed that CM follows a highly polygenic mode of inheritance. However, 10-adjacent-SNP windows showed that regions on chromosomes 2, 14 and 20 have impacts on genetic variation for CM. Some of the genes located on chromosome 14 (LY6K, LY6D, LYNX1, LYPD2, SLURP1, PSCA) are part of the lymphocyte-antigen-6 complex (LY6) known for its neutrophil regulation function linked to the major histocompatibility complex. Other genes on chromosome 2 were also involved in regulating immune response (IFIH1, LY75, and DPP4), or are themselves regulated in the presence of specific pathogens (ITGB6, NR4A2). Other genes annotated on chromosome 20 are involved in mammary gland metabolism (GHR, OXCT1), antibody production and phagocytosis of bacterial cells (C6, C7, C9, C1QTNF3), tumor suppression (DAB2), involution of mammary epithelium (OSMR) and cytokine regulation (PRLR). DAVID enrichment analysis revealed 5 KEGG pathways. The JAK-STAT signaling pathway (cell proliferation and apoptosis) and the ‘Cytokine-cytokine receptor interaction’ (cytokine and interleukines response to infectious agents) are co-regulated and linked to the ‘ABC transporters’ pathway also found here. Gene network analysis performed using GeneMania revealed a co-expression network where 665 interactions existed among 145 of the genes reported above. Clinical mastitis is a complex trait and the different genes regulating immune response are known to be pathogen-specific. Despite the lack of information in this study, candidate QTL for CM were identified in the US Holstein population.}, number={2}, journal={PLOS ONE}, author={Tiezzi, Francesco and Parker-Gaddis, Kristen L. and Cole, John B. and Clay, John S. and Maltecca, Christian}, year={2015}, month={Feb} }
 @article{maltecca_parker_cassady_2012, title={Application of multiple shrinkage methods to genomic predictions}, volume={90}, ISSN={["1525-3163"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84861848308&partnerID=MN8TOARS}, DOI={10.2527/jas.2011-4350}, abstractNote={New challenges have arisen with the development of large marker panels for livestock species. Models easily become overparameterized when all available markers are included. Solutions have led to the development of shrinkage or regularization techniques. The objective of this study was the application and comparison of Bayesian LASSO (B-L), thick-tailed (Student-t), and semiparametric multiple shrinkage methods. The B-L and Student-t methods were also each analyzed within a single shrinkage and a multiple shrinkage framework. Simulated and real data were used to evaluate each method's performance. Real data consisted of SNP genotypes of 4,069 Holstein sires. Traits included in analysis of real data were milk, fat, protein yield, and somatic cell score. The performance of each model was compared based on correlations between true and predicted genomic predicted transmitting abilities. Model performance was also compared with the performance of routinely used methods such as Bayes-A and GBLUP through cross-validation techniques. When using simulated data regardless of shrinkage framework, shrinkage models outperformed genomic BLUP (GBLUP). The average advantage of shrinkage models ranged from 1% to approximately 8% depending on the prior specification. When analyzing real data, shrinkage models slightly outperformed GBLUP for most traits. Shrinkage models were better able to model traits for which 1 or more SNP of large effect have been identified. Overall, results suggested a relatively small advantage in multiple shrinkage models. Multiple shrinkage methods could represent a useful alternative to current methods of prediction; however, their performance in a variety of scenarios needs to be investigated further.}, number={6}, journal={JOURNAL OF ANIMAL SCIENCE}, author={Maltecca, Christian and Parker, Kristen L. and Cassady, Joseph P.}, year={2012}, month={Jun}, pages={1777–1787} }
 @misc{maltecca_parker_cassandro_2010, title={Accomplishments and new challenges in dairy genetic evaluations}, volume={9}, ISSN={["1828-051X"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-78449279892&partnerID=MN8TOARS}, DOI={10.4081/ijas.2010.e68}, abstractNote={This review presents the evolution of dairy genetic methods to estimate breeding values. For centuries, human action has shaped animal populations by choosing progenitors of the next generation. Since the twentieth century, applied concepts were integrated into a new discipline, quantitative genetics. The past quarter-century in genetic evaluation of dairy cattle has been marked by evolution in methodology and computer capacity, expansion in the array of evaluated traits, and globalization. Selection index was replaced by mixed model procedures and animal models replaced sire and sire-maternal grandsire models. Recently, application of Bayesian theory to breeding values prediction and variance components estimation has become standard. Individual test-day observations have been used more effectively in the estimation of lactation yield as direct input to evaluation models. Computer speed and storage are less limiting in choosing procedures. National evaluations combined internationally provide evaluations for bulls from all participating countries on each of the national scales, facilitating choices from among many more bulls. Selection within countries has increased inbreeding and the use of similar genetics across countries reduces the previously available genetic diversity. Finally, considerable progress in genomics has created a new tool, genomic selection. The collection and analysis of several types of phenotypic data to evaluate genetic merit will continue to be the most important tool for genetic progress in the foreseeable future. Information will increasingly be obtained from smaller reference populations and the extrapolation from these data will require careful validation.}, number={4}, journal={ITALIAN JOURNAL OF ANIMAL SCIENCE}, author={Maltecca, Christian and Parker, Kristen L. and Cassandro, Martino}, year={2010}, pages={360–368} }