Gains in QTL Detection Using an Ultra-High Density SNP Map Based on Population Sequencing Relative to Traditional RFLP/SSR Markers

Huge efforts have been invested in the last two decades to dissect the genetic bases of complex traits including yields of many crop plants, through quantitative trait locus (QTL) analyses. However, almost all the studies were based on linkage maps constructed using low-throughput molecular markers, e.g. restriction fragment length polymorphisms (RFLPs) and simple sequence repeats (SSRs), thus are mostly of low density and not able to provide precise and complete information about the numbers and locations of the genes or QTLs controlling the traits. In this study, we constructed an ultra-high density genetic map based on high quality single nucleotide polymorphisms (SNPs) from low-coverage sequences of a recombinant inbred line (RIL) population of rice, generated using new sequencing technology. The quality of the map was assessed by validating the positions of several cloned genes including GS3 and GW5/qSW5, two major QTLs for grain length and grain width respectively, and OsC1, a qualitative trait locus for pigmentation. In all the cases the loci could be precisely resolved to the bins where the genes are located, indicating high quality and accuracy of the map. The SNP map was used to perform QTL analysis for yield and three yield-component traits, number of tillers per plant, number of grains per panicle and grain weight, using data from field trials conducted over years, in comparison to QTL mapping based on RFLPs/SSRs. The SNP map detected more QTLs especially for grain weight, with precise map locations, demonstrating advantages in detecting power and resolution relative to the RFLP/SSR map. Thus this study provided an example for ultra-high density map construction using sequencing technology. Moreover, the results obtained are helpful for understanding the genetic bases of the yield traits and for fine mapping and cloning of QTLs.

[1]  Jialing Yao,et al.  Linking differential domain functions of the GS3 protein to natural variation of grain size in rice , 2010, Proceedings of the National Academy of Sciences.

[2]  Xuehui Huang,et al.  High-throughput genotyping by whole-genome resequencing. , 2009, Genome research.

[3]  Qifa Zhang,et al.  Non-random distribution of T-DNA insertions at various levels of the genome hierarchy as revealed by analyzing 13 804 T-DNA flanking sequences from an enhancer-trap mutant library. , 2007, The Plant journal : for cell and molecular biology.

[4]  Qifa Zhang,et al.  Genetic dissection of an elite rice hybrid revealed that heterozygotes are not always advantageous for performance. , 2002, Genetics.

[5]  R. Visser,et al.  Construction of a 10,000-Marker Ultradense Genetic Recombination Map of Potato: Providing a Framework for Accelerated Gene Isolation and a Genomewide Physical Map , 2006, Genetics.

[6]  A. Melchinger,et al.  Quantitative Trait Locus Mapping Based on Resampling in a Vast Maize Testcross Experiment and Its Relevance to Quantitative Genetics for Complex Traits , 2004, Genetics.

[7]  E. Mardis.  The impact of next-generation sequencing technology on genetics. , 2008, Trends in genetics : TIG.

[8]  Cai-guo Xu,et al.  Characterization of the main effects, epistatic effects and their environmental interactions of QTLs on the genetic basis of yield traits in rice , 2002, Theoretical and Applied Genetics.

[9]  H. Leung,et al.  Mutant Resources in Rice for Functional Genomics of the Grasses[W] , 2009, Plant Physiology.

[10]  Cai-guo Xu,et al.  A global analysis of QTLs for expression variations in rice shoots at the early seedling stage. , 2010, The Plant journal : for cell and molecular biology.

[11]  Daoxiu Zhou,et al.  Development of enhancer trap lines for functional analysis of the rice genome. , 2003, The Plant journal : for cell and molecular biology.

[12]  Robbie Waugh,et al.  Gene expression quantitative trait locus analysis of 16 000 barley genes reveals a complex pattern of genome-wide transcriptional regulation. , 2008, The Plant journal : for cell and molecular biology.

[13]  Linda Cardle,et al.  Single-feature polymorphism discovery in the barley transcriptome , 2005, Genome Biology.

[14]  Kaworu Ebana,et al.  Deletion in a gene associated with grain size increased yields during rice domestication , 2008, Nature Genetics.

[15]  C. Mundt,et al.  Effect of population size on the estimation of QTL: a test using resistance to barley stripe rust , 2005, Theoretical and Applied Genetics.

[16]  G. Droc,et al.  High throughput T-DNA insertion mutagenesis in rice: a first step towards in silico reverse genetics. , 2004, The Plant journal : for cell and molecular biology.

[17]  Daniel R. Richards,et al.  Direct allelic variation scanning of the yeast genome. , 1998, Science.

[18]  K. Jung,et al.  T-DNA insertional mutagenesis for functional genomics in rice. , 2000, The Plant journal : for cell and molecular biology.

[19]  S. Schuster.  Next-generation sequencing transforms today's biology , 2008, Nature Methods.

[20]  Jinping Hua,et al.  Single-locus heterotic effects and dominance by dominance interactions can adequately explain the genetic basis of heterosis in an elite rice hybrid , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[21]  Qifa Zhang,et al.  Genome-wide association studies of 14 agronomic traits in rice landraces , 2010, Nature Genetics.

[22]  S. Jackson,et al.  Next-generation sequencing technologies and their implications for crop genetics and breeding. , 2009, Trends in biotechnology.

[23]  Trupti Joshi,et al.  Single Feature Polymorphism Discovery in Rice , 2007, PloS one.

[24]  Detlef Weigel,et al.  Large-scale identification of single-feature polymorphisms in complex genomes. , 2003, Genome research.

[25]  Zhijun Cheng,et al.  Isolation and initial characterization of GW5, a major QTL associated with rice grain width and weight , 2008, Cell Research.

[26]  Z. Zeng.  Precision mapping of quantitative trait loci. , 1994, Genetics.

[27]  Qifa Zhang,et al.  Genetic and molecular bases of rice yield. , 2010, Annual review of plant biology.

[28]  Hao Wu,et al.  R/qtl: QTL Mapping in Experimental Crosses , 2003, Bioinform..

[29]  R R Mir,et al.  Array-based high-throughput DNA markers for crop improvement , 2008, Heredity.

[30]  Y. Sano,et al.  Allelic Diversification at the C (OsC1) Locus of Wild and Cultivated Rice , 2004, Genetics.

[31]  Qifa Zhang,et al.  Genetic bases of appearance quality of rice grains in Shanyou 63, an elite rice hybrid , 2000, Theoretical and Applied Genetics.

[32]  Jinghua Xiao,et al.  Single feature polymorphisms between two rice cultivars detected using a median polish method , 2009, Theoretical and Applied Genetics.

[33]  Lei Wang,et al.  Natural variation in Ghd7 is an important regulator of heading date and yield potential in rice , 2008, Nature Genetics.

[34]  Nori Kurata,et al.  Rice expression atlas in reproductive development. , 2010, Plant & cell physiology.

[35]  Bin Han,et al.  GS3, a major QTL for grain length and weight and minor QTL for grain width and thickness in rice, encodes a putative transmembrane protein , 2006, Theoretical and Applied Genetics.

[36]  Li Liu,et al.  A dynamic gene expression atlas covering the entire life cycle of rice. , 2010, The Plant journal : for cell and molecular biology.

[37]  Hua Yan,et al.  QTLs for low nitrogen tolerance at seedling stage identified using a recombinant inbred line population derived from an elite rice hybrid , 2005, Theoretical and Applied Genetics.

[38]  Xuehui Huang,et al.  Mapping 49 quantitative trait loci at high resolution through sequencing-based genotyping of rice recombinant inbred lines , 2010, Theoretical and Applied Genetics.

[39]  Qi Feng,et al.  Parent-independent genotyping for constructing an ultrahigh-density linkage map based on population sequencing , 2010, Proceedings of the National Academy of Sciences.

[40]  John A. Hamilton,et al.  The TIGR Rice Genome Annotation Resource: improvements and new features , 2006, Nucleic Acids Res..

[41]  R. Doerge,et al.  Global eQTL Mapping Reveals the Complex Genetic Architecture of Transcript-Level Variation in Arabidopsis , 2007, Genetics.