@article{jackson_christie_reynolds_marais_tii‐kuzu_caballero_kampman_visser_naidoo_kain_et al._2021, title={A genome‐wide SNP genotyping resource for tropical pine tree species}, volume={22}, ISSN={1755-098X 1755-0998}, url={http://dx.doi.org/10.1111/1755-0998.13484}, DOI={10.1111/1755-0998.13484}, abstractNote={AbstractWe performed gene and genome targeted SNP discovery towards the development of a genome‐wide, multispecies genotyping array for tropical pines. Pooled RNA‐seq data from shoots of seedlings from five tropical pine species was used to identify transcript‐based SNPs resulting in 1.3 million candidate Affymetrix SNP probe sets. In addition, we used a custom 40 K probe set to perform capture‐seq in pooled DNA from 81 provenances representing the natural ranges of six tropical pine species in Mexico and Central America resulting in 563 K candidate SNP probe sets. Altogether, 300 K RNA‐seq (72%) and 120 K capture‐seq (28%) derived SNP probe sets were tiled on a 420 K screening array that was used to genotype 576 trees representing the 81 provenances and commercial breeding material. Based on the screening array results, 50 K SNPs were selected for commercial SNP array production including 20 K polymorphic SNPs for P. patula, P. tecunumanii, P. oocarpa and P. caribaea, 15 K for P. greggii and P. maximinoi, 13 K for P. elliottii and 8K for P. pseudostrobus. We included 9.7 K ancestry informative SNPs that will be valuable for species and hybrid discrimination. Of the 50 K SNP markers, 25% are polymorphic in only one species, while 75% are shared by two or more species. The Pitro50K SNP chip will be useful for population genomics and molecular breeding in this group of pine species that, together with their hybrids, represent the majority of fast‐growing tropical and subtropical pine plantations globally.}, number={2}, journal={Molecular Ecology Resources}, publisher={Wiley}, author={Jackson, Colin and Christie, Nanette and Reynolds, Sharon Melissa and Marais, Gerhard C. and Tii‐kuzu, Yokateme and Caballero, Madison and Kampman, Tamanique and Visser, Erik A. and Naidoo, Sanushka and Kain, Dominic and et al.}, year={2021}, month={Aug}, pages={695–710} }
 @article{caballero_lauer_bennett_zaman_mcevoy_acosta_jackson_townsend_eckert_whetten_et al._2021, title={Toward genomic selection in Pinus taeda: Integrating resources to support array design in a complex conifer genome}, volume={9}, ISSN={["2168-0450"]}, url={https://doi.org/10.1002/aps3.11439}, DOI={10.1002/aps3.11439}, abstractNote={PremiseAn informatics approach was used for the construction of an Axiom genotyping array from heterogeneous, high‐throughput sequence data to assess the complex genome of loblolly pine (Pinus taeda).MethodsHigh‐throughput sequence data, sourced from exome capture and whole genome reduced‐representation approaches from 2698 trees across five sequence populations, were analyzed with the improved genome assembly and annotation for the loblolly pine. A variant detection, filtering, and probe design pipeline was developed to detect true variants across and within populations. From 8.27 million variants, a total of 642,275 were evaluated and 423,695 of those were screened across a range‐wide population.ResultsThe final informatics and screening approach delivered an Axiom array representing 46,439 high‐confidence variants to the forest tree breeding and genetics community. Based on the annotated reference genome, 34% were located in or directly upstream or downstream of genic regions.DiscussionThe Pita50K array represents a genome‐wide resource developed from sequence data for an economically important conifer, loblolly pine. It uniquely integrates independent projects that assessed trees sampled across the native range. The challenges associated with the large and repetitive genome are addressed in the development of this resource.}, number={6}, journal={APPLICATIONS IN PLANT SCIENCES}, publisher={Wiley}, author={Caballero, Madison and Lauer, Edwin and Bennett, Jeremy and Zaman, Sumaira and McEvoy, Susan and Acosta, Juan and Jackson, Colin and Townsend, Laura and Eckert, Andrew and Whetten, Ross W. and et al.}, year={2021}, month={Jun} }