Submitted to: Plant and Animal Genome Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: December 15, 2011
Publication Date: January 17, 2012
Citation: Larson, S.R., Mott, I.W., Bushman, B.S., Wang, R. 2012. Genetic resources and genomic diversity in the perennial triticeae grasses. Plant and Animal Genome Conference Proceedings. Technical Abstract: The perennial Triticeae grasses comprise hundreds of diverse species, organized into genomically defined genera based on chromosome pairing studies of interspecific hybrids. Our objective is to develop expressed gene sequence tag (EST) markers and genetic maps for these divergent genomes to further elucidate and utilize genetic diversity among these important germplasm resources. A total of 27,273 (EST) unigenes were initially sequenced by Sanger technique from diploid Pseudoroegneria (St genome), allotetraploid Elymus (StH genomes), and allotetraploid Leymus (NsXm genomes) with an average read length of about 861 bp. Approximately 85% of these ESTs were aligned to the Oryza genome sequence and PCR primer pairs were designed for simple sequence repeat (SSR) motifs and untranslated regions (UTRs) of 3615 ESTs. A total of 350 EST-SSR markers and 26 lignin biosynthesis EST-UTRs were used to construct genetic maps and identify two sets of seven homoeologous chromosomes of allotetraploid Leymus (n=2x=14) based known patterns of synteny between rice, wheat, and the rice-Leymus EST alignments. Similarly, a total of 79 Elymus (StH) and 35 Pseudoroegneria (St) EST markers were used to construct genetic maps and identify and distinguish the seven St-genome and seven H-genome chromosomes of allotetraploid Elymus (n=2x=14). An additional 234,472 EST isotigs (average 485 bp) were obtained from transcriptome sequences of hexaploid Thinopyrum intermedium (EeEbSt genomes) and some key diploids including Psathyrostachys jencea (Ns), Thinopyrum bessarbicum (Eb), and Thinopyrum juncea (Ee) using next-generation techniques. These markers and maps were used to identify and manipulate quantitative trait loci (QTLs) controlling functionally important grass traits.