Genebank genomics highlights the diversity of a global barley collection

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Genebanks hold comprehensive collections of cultivars, landraces and crop wild relatives of all major food crops, but their detailed characterization has so far been limited to sparse core sets. The analysis of genome-wide genotyping-by-sequencing data for almost all barley accessions of the German ex situ genebank provides insights into the global population structure of domesticated barley and points out redundancies and coverage gaps in one of the world's major genebanks. Our large sample size and dense marker data afford great power for genome-wide association scans. We detect known and novel loci underlying morphological traits differentiating barley genepools, find evidence for convergent selection for barbless awns in barley and rice and show that a major-effect resistance locus conferring resistance to bymovirus infection has been favored by traditional farmers. This study outlines future directions for genomics-assisted genebank management and the utilization of germplasm collections for linking natural variation to human selection during crop evolution.

Related collections

Most cited references 40

Record: found
Abstract: not found
Article: not found

Multiple Comparisons among Means

Olive Jean Dunn (1961)

0 comments Cited 650 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data

(2013)

Motivation: Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. Results: We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. Availability: http://samtools.sourceforge.net. Contact: hengli@broadinstitute.org.

0 comments Cited 433 times – based on 0 reviews

Preprint

     Review now

Bookmark

Record: found
Abstract: found
Article: not found

Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice.

Kenji Yano, Eiji Yamamoto, Koichiro Aya … (2016)

A genome-wide association study (GWAS) can be a powerful tool for the identification of genes associated with agronomic traits in crop species, but it is often hindered by population structure and the large extent of linkage disequilibrium. In this study, we identified agronomically important genes in rice using GWAS based on whole-genome sequencing, followed by the screening of candidate genes based on the estimated effect of nucleotide polymorphisms. Using this approach, we identified four new genes associated with agronomic traits. Some genes were undetectable by standard SNP analysis, but we detected them using gene-based association analysis. This study provides fundamental insights relevant to the rapid identification of genes associated with agronomic traits using GWAS and will accelerate future efforts aimed at crop improvement.