AUTHOR=Singh Narinder , Wu Shuangye , Tiwari Vijay , Sehgal Sunish , Raupp John , Wilson Duane , Abbasov Mehraj , Gill Bikram , Poland Jesse TITLE=Genomic Analysis Confirms Population Structure and Identifies Inter-Lineage Hybrids in Aegilops tauschii JOURNAL=Frontiers in Plant Science VOLUME=10 YEAR=2019 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2019.00009 DOI=10.3389/fpls.2019.00009 ISSN=1664-462X ABSTRACT=

Aegilops tauschii, the D-genome donor of bread wheat, Triticum aestivum, is a storehouse of genetic diversity, and an important resource for future wheat improvement. Genomic and population analysis of 549 Ae. tauschii and 103 wheat accessions was performed by using 13,135 high quality SNPs. Population structure, principal component, and cluster analysis confirmed the differentiation of Ae. tauschii into two lineages; lineage 1 (L1) and lineage 2 (L2), the latter being the wheat D-genome donor. Lineage L1 contributes only 2.7% of the total introgression from Ae. tauschii for a set of United States winter wheat lines, confirming the great amount of untapped genetic diversity in L1. Lineage L2 accessions had overall greater allelic diversity and wheat accessions had the least allelic diversity. Both lineages also showed intra-lineage differentiation with L1 being driven by longitudinal gradient and L2 differentiated by altitude. There has previously been little reported on natural hybridization between L1 and L2. We found nine putative inter-lineage hybrids in the population structure analysis, each containing numerous lineage-specific private alleles from both lineages. One hybrid was confirmed as a recombinant inbred between the two lineages, likely artificially post collection. Of the remaining eight putative hybrids, a group of seven from Georgia carry 713 SNPs with private alleles, which points to the possibility of a novel L1–L2 hybrid lineage. To facilitate the use of Ae. tauschii in wheat improvement, a MiniCore consisting of 29 L1 and 11 L2 accessions, has been developed based on genotypic, phenotypic and geographical data. MiniCore reduces the collection size by over 10-fold and captures 84% of the total allelic diversity in the whole collection.