Literature DB >> 23898176

Pinpointing genes underlying the quantitative trait loci for root-knot nematode resistance in palaeopolyploid soybean by whole genome resequencing.

Xiangyang Xu1, Liang Zeng, Ye Tao, Tri Vuong, Jinrong Wan, Roger Boerma, Jim Noe, Zenglu Li, Steve Finnerty, Safiullah M Pathan, J Grover Shannon, Henry T Nguyen.   

Abstract

The objective of this study was to use next-generation sequencing technologies to dissect quantitative trait loci (QTL) for southern root-knot nematode (RKN) resistance into individual genes in soybean. Two hundred forty-six recombinant inbred lines (RIL) derived from a cross between Magellan (susceptible) and PI 438489B (resistant) were evaluated for RKN resistance in a greenhouse and sequenced at an average of 0.19× depth. A sequence analysis pipeline was developed to identify and validate single-nucleotide polymorphisms (SNPs), infer the parental source of each SNP allele, and genotype the RIL population. Based on 109,273 phased SNPs, recombination events in RILs were identified, and a total of 3,509 bins and 3,489 recombination intervals were defined. About 50.8% of bins contain 1 to 10 genes. A linkage map was subsequently constructed by using bins as molecular markers. Three QTL for RKN resistance were identified. Of these, one major QTL was mapped to bin 10 of chromosome 10, which is 29.7 kb in size and harbors three true genes and two pseudogenes. Based on sequence variations and gene-expression analysis, the candidate genes underlying the major QTL for RKN resistance were pinpointed. They are Glyma10g02150 and Glyma10g02160, encoding a pectin methylesterase inhibitor and a pectin methylesterase inhibitor -pectin methylesterase, respectively. This QTL mapping approach not only combines SNP discovery, SNP validation, and genotyping, but also solves the issues caused by genome duplication and repetitive sequences. Hence, it can be widely used in crops with a reference genome to enhance QTL mapping accuracy.

Entities:  

Keywords:  high resolution linkage map; high throughput genotyping

Mesh:

Substances:

Year:  2013        PMID: 23898176      PMCID: PMC3746920          DOI: 10.1073/pnas.1222368110

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  23 in total

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