Abstract
High-density genetic maps are essential for high resolution mapping of quantitative traits. Here, we present a new genetic map for an Arabidopsis Bayreuth × Shahdara recombinant inbred line (RIL) population, built on RNA-seq data. RNA-seq analysis on 160 RILs of this population identified 30,049 single-nucleotide polymorphisms (SNPs) covering the whole genome. Based on a 100-kbp window SNP binning method, 1059 bin-markers were identified, physically anchored on the genome. The total length of the RNA-seq genetic map spans 471.70 centimorgans (cM) with an average marker distance of 0.45 cM and a maximum marker distance of 4.81 cM. This high resolution genotyping revealed new recombination breakpoints in the population. To highlight the advantages of such high-density map, we compared it to two publicly available genetic maps for the same population, comprising 69 PCR-based markers and 497 gene expression markers derived from microarray data, respectively. In this study, we show that SNP markers can effectively be derived from RNA-seq data. The new RNA-seq map closes many existing gaps in marker coverage, saturating the previously available genetic maps. Quantitative trait locus (QTL) analysis for published phenotypes using the available genetic maps showed increased QTL mapping resolution and reduced QTL confidence interval using the RNA-seq map. The new high-density map is a valuable resource that facilitates the identification of candidate genes and map-based cloning approaches.
Highlights
Quantitative trait locus (QTL) analysis has successfully identified a large number of genetic loci that contribute to the regulation of quantitative phenotypes
The success of QTL mapping is determined by the mapping resolution which mainly depends on the size of the population, the complexity of the phenotype, and the number of available markers
Single-nucleotide polymorphisms calling resulted in 185,354 single-nucleotide polymorphisms (SNPs) distributed over the five chromosomes, ranging from 26,514 SNPs for chromosome 2 to 48,151 SNPs for chromosome 1 (Figure 1)
Summary
Quantitative trait locus (QTL) analysis has successfully identified a large number of genetic loci that contribute to the regulation of quantitative phenotypes. In combination with a genetic map, quantitative variation in gene expression measured in a segregating population enables the identification of expression QTLs (eQTLs). Differences in gene expression measured with microarrays as a result of probe hybridization sensitivity to underlying sequence polymorphisms have been used to derive SNP-based markers (West et al, 2006; Zych et al, 2015, 2017). Further genotyping efforts on a subset of these RILs have introduced markers derived from gene expression data with microarrays, saturating the original map (West et al, 2006; Salathia et al, 2007; Zych et al, 2015). We present the construction of a high-resolution genetic map from RNA-seq data of 160 RILs. We validate and show the improvements of this new map by performing a QTL analysis with publicly available phenotypic data (Joosen et al, 2012)
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