Construction of high-quality recombination maps with low-coverage genomic sequencing for joint linkage analysis in maize

doi:10.1186/s12915-015-0187-4

	Construction of high-quality recombination maps with low-coverage genomic sequencing for joint linkage analysis in maize
	Li, Chunhui 1; Li, Yongxiang 1; Bradbury, Peter J.3; Wu, Xun 1; Shi, Yunsu 1; Song, Yanchun 1; Zhang, Dengfeng 1; Rodgers-Melnick, Eli 2; Buckler, Edward S.2,3; Zhang, Zhiwu 2,4
刊名	BMC BIOLOGY
	2015
卷号	13 页码:-
关键词	Recombination bin map Sequencing Joint linkage analysis Nested association mapping population Maize
ISSN号	1741-7007
DOI	10.1186/s12915-015-0187-4
通讯作者	Li, Chunhui
英文摘要	Background: A genome-wide association study (GWAS) is the foremost strategy used for finding genes that control human diseases and agriculturally important traits, but it often reports false positives. In contrast, its complementary method, linkage analysis, provides direct genetic confirmation, but with limited resolution. A joint approach, using multiple linkage populations, dramatically improves resolution and statistical power. For example, this approach has been used to confirm that many complex traits, such as flowering time controlling adaptation in maize, are controlled by multiple genes with small effects. In addition, genotyping by sequencing (GBS) at low coverage not only produces genotyping errors, but also results in large datasets, making the use of high-throughput sequencing technologies computationally inefficient or unfeasible.Results: In this study, we converted raw SNPs into effective recombination bins. The reduced bins not only retain the original information, but also correct sequencing errors from low-coverage genomic sequencing. To further increase the statistical power and resolution, we merged a new temperate maize nested association mapping (NAM) population derived in China (CN-NAM) with the existing maize NAM population developed in the US (US-NAM). Together, the two populations contain 36 families and 7,000 recombinant inbred lines (RILs). One million SNPs were generated for all the RILs with GBS at low coverage. We developed high-quality recombination maps for each NAM population to correct genotyping errors and improve the computational efficiency of the joint linkage analysis. The original one million SNPs were reduced to 4,932 and 5,296 recombination bins with average interval distances of 0.34 cM and 0.28 cM for CN-NAM and US-NAM, respectively. The quantitative trait locus (QTL) mapping for flowering time (days to tasseling) indicated that the high-density, recombination bin map improved resolution of QTL mapping by 50 % compared with that using a medium-density map. We also demonstrated that combining the CN-NAM and US-NAM populations improves the power to detect QTL by 50 % compared to single NAM population mapping. Among the QTLs mapped by joint usage of the US-NAM and CN-NAM maps, 25 % of the QTLs overlapped with known flowering-time genes in maize.Conclusion: This study provides directions and resources for the research community, especially maize researchers, for future studies using the recombination bin strategy for joint linkage analysis. Available resources include efficient usage of low-coverage genomic sequencing, detailed positions for genes controlling maize flowering, and recombination bin maps and flowering-time data for both CN and US NAMs. Maize researchers even have the opportunity to grow both CN and US NAM populations to study the traits of their interest, as the seeds of both NAM populations are available from the seed repository in China and the US.
学科主题	Biology
语种	英语
出版者	BIOMED CENTRAL LTD
WOS记录号	WOS:000361428500001
内容类型	期刊论文
源URL	[http://111.203.20.206/handle/2HMLN22E/4662]
专题	作物科学研究所_种质资源保存与研究中心
作者单位	1.Chinese Acad Agr Sci, Inst Crop Sci, Beijing 100193, Peoples R China 2.Cornell Univ, Institute Genom Div, Ithaca, NY 14850 USA 3.ARS, USA Dept Agr, New York, NY USA 4.Washington State Univ, Dept Crop & Soil Sci, Pullman, WA 99164 USA
推荐引用方式 GB/T 7714	Li, Chunhui,Li, Yongxiang,Bradbury, Peter J.,et al. Construction of high-quality recombination maps with low-coverage genomic sequencing for joint linkage analysis in maize[J]. BMC BIOLOGY,2015,13:-.
APA	Li, Chunhui.,Li, Yongxiang.,Bradbury, Peter J..,Wu, Xun.,Shi, Yunsu.,...&Wang, Tianyu.(2015).Construction of high-quality recombination maps with low-coverage genomic sequencing for joint linkage analysis in maize.BMC BIOLOGY,13,-.
MLA	Li, Chunhui,et al."Construction of high-quality recombination maps with low-coverage genomic sequencing for joint linkage analysis in maize".BMC BIOLOGY 13(2015):-.