Dataset Information

Analysis of single nucleotide polymorphisms based on RNA sequencing data of diverse bio-geographical accessions in barley.

ABSTRACT: Barley is one of the founder crops of Old world agriculture and has become the fourth most important cereal worldwide. Information on genome-scale DNA polymorphisms allows elucidating the evolutionary history behind domestication, as well as discovering and isolating useful genes for molecular breeding. Deep transcriptome sequencing enables the exploration of sequence variations in transcribed sequences; such analysis is particularly useful for species with large and complex genomes, such as barley. In this study, we performed RNA sequencing of 20 barley accessions, comprising representatives of several biogeographic regions and a wild ancestor. We identified 38,729 to 79,949 SNPs in the 19 domesticated accessions and 55,403 SNPs in the wild barley and revealed their genome-wide distribution using a reference genome. Genome-scale comparisons among accessions showed a clear differentiation between oriental and occidental barley populations. The results based on population structure analyses provide genome-scale properties of sub-populations grouped to oriental, occidental and marginal groups in barley. Our findings suggest that the oriental population of domesticated barley has genomic variations distinct from those in occidental groups, which might have contributed to barley's domestication.

SUBMITTER: Takahagi K

PROVIDER: S-EPMC5018957 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Analysis of single nucleotide polymorphisms based on RNA sequencing data of diverse bio-geographical accessions in barley.

Takahagi Kotaro K Uehara-Yamaguchi Yukiko Y Yoshida Takuhiro T Sakurai Tetsuya T Shinozaki Kazuo K Mochida Keiichi K Saisho Daisuke D

Scientific reports 20160912

Barley is one of the founder crops of Old world agriculture and has become the fourth most important cereal worldwide. Information on genome-scale DNA polymorphisms allows elucidating the evolutionary history behind domestication, as well as discovering and isolating useful genes for molecular breeding. Deep transcriptome sequencing enables the exploration of sequence variations in transcribed sequences; such analysis is particularly useful for species with large and complex genomes, such as bar ...[more]

PMID: 27616653

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Project description:The advent of high throughput sequencing technology has enabled the 1000 Genomes Project Pilot 3 to generate complete sequence data for more than 906 genes and 8,140 exons representing 697 subjects. The 1000 Genomes database provides a critical opportunity for further interpreting disease associations with single nucleotide polymorphisms (SNPs) discovered from genetic association studies. Currently, direct sequencing of candidate genes or regions on a large number of subjects remains both cost- and time-prohibitive.To accelerate the translation from discovery to functional studies, we propose an in silico gene sequencing method (ISS), which predicts phased sequences of intragenic regions, using SNPs. The key underlying idea of our method is to infer diploid sequences (a pair of phased sequences/alleles) at every functional locus utilizing the deep sequencing data from the 1000 Genomes Project and SNP data from the HapMap Project, and to build prediction models using flanking SNPs. Using this method, we have developed a database of prediction models for 611 known genes. Sequence prediction accuracy for these genes is 96.26% on average (ranges 79%-100%). This database of prediction models can be enhanced and scaled up to include new genes as the 1000 Genomes Project sequences additional genes on additional individuals. Applying our predictive model for the KCNJ11 gene to the Wellcome Trust Case Control Consortium (WTCCC) Type 2 diabetes cohort, we demonstrate how the prediction of phased sequences inferred from GWAS SNP genotype data can be used to facilitate interpretation and identify a probable functional mechanism such as protein changes.Prior to the general availability of routine sequencing of all subjects, the ISS method proposed here provides a time- and cost-effective approach to broadening the characterization of disease associated SNPs and regions, and facilitating the prioritization of candidate genes for more detailed functional and mechanistic studies.

Dataset Information

Analysis of single nucleotide polymorphisms based on RNA sequencing data of diverse bio-geographical accessions in barley.

Publications

Analysis of single nucleotide polymorphisms based on RNA sequencing data of diverse bio-geographical accessions in barley.

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