Comparative genetic mapping and genomic region collinearity analysis of the powdery mildew resistance gene Pm41.

KEY MESSAGE: By applying comparative genomics analyses, a high-density genetic linkage map narrowed the powdery mildew resistance gene Pm41 originating from wild emmer in a sub-centimorgan genetic interval. Wheat powdery mildew, caused by Blumeria graminis f. sp. tritici, results in large yield losses worldwide. A high-density genetic linkage map of the powdery mildew resistance gene Pm41, originating from wild emmer (Triticum turgidum var. dicoccoides) and previously mapped to the distal region of chromosome 3BL bin 0.63-1.00, was constructed using an F5:6 recombinant inbred line population derived from a cross of durum wheat cultivar Langdon and wild emmer accession IW2. By applying comparative genomics analyses, 19 polymorphic sequence-tagged site markers were developed and integrated into the Pm41 genetic linkage map. Ultimately, Pm41 was mapped in a 0.6 cM genetic interval flanked by markers XWGGC1505 and XWGGC1507, which correspond to 11.7, 19.2, and 24.9 kb orthologous genomic regions in Brachypodium, rice, and sorghum, respectively. The XWGGC1506 marker co-segregated with Pm41 and could be served as a starting point for chromosome landing and map-based cloning as well as marker-assisted selection of Pm41. Detailed comparative genomics analysis of the markers flanking the Pm41 locus in wheat and the putative orthologous genes in Brachypodium, rice, and sorghum suggests that the gene order is highly conserved between rice and sorghum. However, intra-chromosome inversions and re-arrangements are evident in the wheat and Brachypodium genomic regions, and gene duplications are also present in the orthologous genomic regions of Pm41 in wheat, indicating that the Brachypodium gene model can provide more useful information for wheat marker development.

Substantial contribution of genetic variation in the expression of transcription factors to phenotypic variation revealed by eRD-GWAS.

BACKGROUND: There are significant limitations in existing methods for the genome-wide identification of genes whose expression patterns affect traits. RESULTS: The transcriptomes of five tissues from 27 genetically diverse maize inbred lines were deeply sequenced to identify genes exhibiting high and low levels of expression variation across tissues or genotypes. Transcription factors are enriched among genes with the most variation in expression across tissues, as well as among genes with higher-than-median levels of variation in expression across genotypes. In contrast, transcription factors are depleted among genes whose expression is either highly stable or highly variable across genotypes. We developed a Bayesian-based method for genome-wide association studies (GWAS) in which RNA-seq-based measures of transcript accumulation are used as explanatory variables (eRD-GWAS). The ability of eRD-GWAS to identify true associations between gene expression variation and phenotypic diversity is supported by analyses of RNA co-expression networks, protein-protein interaction networks, and gene regulatory networks. Genes associated with 13 traits were identified using eRD-GWAS on a panel of 369 maize inbred lines. Predicted functions of many of the resulting trait-associated genes are consistent with the analyzed traits. Importantly, transcription factors are significantly enriched among trait-associated genes identified with eRD-GWAS. CONCLUSIONS: eRD-GWAS is a powerful tool for associating genes with traits and is complementary to SNP-based GWAS. Our eRD-GWAS results are consistent with the hypothesis that genetic variation in transcription factor expression contributes substantially to phenotypic diversity.

High-density genetic linkage map construction and QTL mapping of grain shape and size in the wheat population Yanda1817 × Beinong6.

High-density genetic linkage maps are necessary for precisely mapping quantitative trait loci (QTLs) controlling grain shape and size in wheat. By applying the Infinium iSelect 9K SNP assay, we have constructed a high-density genetic linkage map with 269 F 8 recombinant inbred lines (RILs) developed between a Chinese cornerstone wheat breeding parental line Yanda1817 and a high-yielding line Beinong6. The map contains 2431 SNPs and 128 SSR & EST-SSR markers in a total coverage of 3213.2 cM with an average interval of 1.26 cM per marker. Eighty-eight QTLs for thousand-grain weight (TGW), grain length (GL), grain width (GW) and grain thickness (GT) were detected in nine ecological environments (Beijing, Shijiazhuang and Kaifeng) during five years between 2010-2014 by inclusive composite interval mapping (ICIM) (LOD ≥ 2.5). Among which, 17 QTLs for TGW were mapped on chromosomes 1A, 1B, 2A, 2B, 3A, 3B, 3D, 4A, 4D, 5A, 5B and 6B with phenotypic variations ranging from 2.62% to 12.08%. Four stable QTLs for TGW could be detected in five and seven environments, respectively. Thirty-two QTLs for GL were mapped on chromosomes 1B, 1D, 2A, 2B, 2D, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6B, 7A and 7B, with phenotypic variations ranging from 2.62% to 44.39%. QGl.cau-2A.2 can be detected in all the environments with the largest phenotypic variations, indicating that it is a major and stable QTL. For GW, 12 QTLs were identified with phenotypic variations range from 3.69% to 12.30%. We found 27 QTLs for GT with phenotypic variations ranged from 2.55% to 36.42%. In particular, QTL QGt.cau-5A.1 with phenotypic variations of 6.82-23.59% was detected in all the nine environments. Moreover, pleiotropic effects were detected for several QTL loci responsible for grain shape and size that could serve as target regions for fine mapping and marker assisted selection in wheat breeding programs.