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QTL map meets population genomics: an application to rice.

ABSTRACT: Genes involved in the transition from wild to cultivated crop species should be of great agronomic importance. Population genomic approaches utilizing genome resequencing data have been recently applied for this purpose, although it only reports a large list of candidate genes with no biological information. Here, by resequencing more than 30 genomes altogether of wild rice Oryza rufipogon and cultivated rice O. sativa, we identified a number of regions with clear footprints of selection during the domestication process. We then focused on identifying candidate domestication genes in these regions by utilizing the wealth of QTL information in rice. We were able to identify a number of interesting candidates such as transcription factors that should control key domestication traits such as shattering, awn length, and seed dormancy. Other candidates include those that might have been related to the improvement of grain quality and those that might have been involved in the local adaptation to dry conditions and colder environments. Our study shows that population genomic approaches and QTL mapping information can be used together to identify genes that might be of agronomic importance.

SUBMITTER: Fawcett JA

PROVIDER: S-EPMC3871663 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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QTL map meets population genomics: an application to rice.

Fawcett Jeffrey A JA Kado Tomoyuki T Sasaki Eriko E Takuno Shohei S Yoshida Kentaro K Sugino Ryuichi P RP Kosugi Shunichi S Natsume Satoshi S Mitsuoka Chikako C Uemura Aiko A Takagi Hiroki H Abe Akira A Ishii Takashige T Terauchi Ryohei R Innan Hideki H

PloS one 20131223 12

Genes involved in the transition from wild to cultivated crop species should be of great agronomic importance. Population genomic approaches utilizing genome resequencing data have been recently applied for this purpose, although it only reports a large list of candidate genes with no biological information. Here, by resequencing more than 30 genomes altogether of wild rice Oryza rufipogon and cultivated rice O. sativa, we identified a number of regions with clear footprints of selection during ...[more]

PMID: 24376738

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Project description:Genome-wide detection of quantitative trait loci (QTL) hotspots underlying variation in many molecular and phenotypic traits has been a key step in various biological studies since the QTL hotspots are highly informative and can be linked to the genes for the quantitative traits. Several statistical methods have been proposed to detect QTL hotspots. These hotspot detection methods rely heavily on permutation tests performed on summarized QTL data or individual-level data (with genotypes and phenotypes) from the genetical genomics experiments. In this article, we propose a statistical procedure for QTL hotspot detection by using the summarized QTL (interval) data collected in public web-accessible databases. First, a simple statistical method based on the uniform distribution is derived to convert the QTL interval data into the expected QTL frequency (EQF) matrix. And then, to account for the correlation structure among traits, the QTL for correlated traits are grouped together into the same categories to form a reduced EQF matrix. Furthermore, a permutation algorithm on the EQF elements or on the QTL intervals is developed to compute a sliding scale of EQF thresholds, ranging from strict to liberal, for assessing the significance of QTL hotspots. With grouping, much stricter thresholds can be obtained to avoid the detection of spurious hotspots. Real example analysis and simulation study are carried out to illustrate our procedure, evaluate the performances and compare with other methods. It shows that our procedure can control the genome-wide error rates at the target levels, provide appropriate thresholds for correlated data and is comparable to the methods using individual-level data in hotspot detection. Depending on the thresholds used, more than 100 hotspots are detected in GRAMENE rice database. We also perform a genome-wide comparative analysis of the detected hotspots and the known genes collected in the Rice Q-TARO database. The comparative analysis reveals that the hotspots and genes are conformable in the sense that they co-localize closely and are functionally related to relevant traits. Our statistical procedure can provide a framework for exploring the networks among QTL hotspots, genes and quantitative traits in biological studies. The R codes that produce both numerical and graphical outputs of QTL hotspot detection in the genome are available on the worldwide web http://www.stat.sinica.edu.tw/chkao/.

Project description:BackgroundLinkage maps are an integral resource for dissection of complex genetic traits in plant and animal species. Canonical map construction follows a well-established workflow: an initial discovery phase where genetic markers are mined from a small pool of individuals, followed by genotyping of selected mapping populations using sets of marker panels. A newly developed sequence-based marker technology, Restriction site Associated DNA (RAD), enables synchronous single nucleotide polymorphism (SNP) marker discovery and genotyping using massively parallel sequencing. The objective of this research was to assess the utility of RAD markers for linkage map construction, employing barley as a model system. Using the published high density EST-based SNP map in the Oregon Wolfe Barley (OWB) mapping population as a reference, we created a RAD map using a limited set of prior markers to establish linakge group identity, integrated the RAD and prior data, and used both maps for detection of quantitative trait loci (QTL).ResultsUsing the RAD protocol in tandem with the Illumina sequence by synthesis platform, a total of 530 SNP markers were identified from initial scans of the OWB parental inbred lines--the "dominant" and "recessive" marker stocks--and scored in a 93 member doubled haploid (DH) mapping population. RAD sequence data from the structured population was converted into allele genotypes from which a genetic map was constructed. The assembled RAD-only map consists of 445 markers with an average interval length of 5 cM, while an integrated map includes 463 RAD loci and 2383 prior markers. Sequenced RAD markers are distributed across all seven chromosomes, with polymorphic loci emanating from both coding and noncoding regions in the Hordeum genome. Total map lengths are comparable and the order of common markers is identical in both maps. The same large-effect QTL for reproductive fitness traits were detected with both maps and the majority of these QTL were coincident with a dwarfing gene (ZEO) and the VRS1 gene, which determines the two-row and six-row germplasm groups of barley.ConclusionsWe demonstrate how sequenced RAD markers can be leveraged to produce high quality linkage maps for detection of single gene loci and QTLs. By combining SNP discovery and genotyping into parallel sequencing events, RAD markers should be a useful molecular breeding tool for a range of crop species. Expected improvements in cost and throughput of second and third-generation sequencing technologies will enable more powerful applications of the sequenced RAD marker system, including improvements in de novo genome assembly, development of ultra-high density genetic maps and association mapping.

Dataset Information

QTL map meets population genomics: an application to rice.

Publications

QTL map meets population genomics: an application to rice.

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