Construction of genotyping-by-sequencing based high-density genetic maps and QTL mapping for fusarium wilt resistance in pigeonpea

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作者
Rachit K. Saxena
Vikas K. Singh
Sandip M. Kale
Revathi Tathineni
Swathi Parupalli
Vinay Kumar
Vanika Garg
Roma R. Das
Mamta Sharma
K. N. Yamini
S. Muniswamy
Anuradha Ghanta
Abhishek Rathore
C. V. Sameer Kumar
K. B. Saxena
P. B. Kavi Kishor
Rajeev K. Varshney
机构
[1] International Crops Research Institute for the Semi-Arid Tropics,Agricultural Research Station (ARS)
[2] Professor Jayashankar Telangana State Agricultural University,Gulbarga
[3] University of Agricultural Sciences (UAS),School of Plant Biology and Institute of Agriculture
[4] Osmania University,undefined
[5] The University of Western Australia,undefined
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Scientific Reports | / 7卷
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摘要
Fusarium wilt (FW) is one of the most important biotic stresses causing yield losses in pigeonpea. Genetic improvement of pigeonpea through genomics-assisted breeding (GAB) is an economically feasible option for the development of high yielding FW resistant genotypes. In this context, two recombinant inbred lines (RILs) (ICPB 2049 × ICPL 99050 designated as PRIL_A and ICPL 20096 × ICPL 332 designated as PRIL_B) and one F2 (ICPL 85063 × ICPL 87119) populations were used for the development of high density genetic maps. Genotyping-by-sequencing (GBS) approach was used to identify and genotype SNPs in three mapping populations. As a result, three high density genetic maps with 964, 1101 and 557 SNPs with an average marker distance of 1.16, 0.84 and 2.60 cM were developed in PRIL_A, PRIL_B and F2, respectively. Based on the multi-location and multi-year phenotypic data of FW resistance a total of 14 quantitative trait loci (QTLs) including six major QTLs explaining >10% phenotypic variance explained (PVE) were identified. Comparative analysis across the populations has revealed three important QTLs (qFW11.1, qFW11.2 and qFW11.3) with upto 56.45% PVE for FW resistance. This is the first report of QTL mapping for FW resistance in pigeonpea and identified genomic region could be utilized in GAB.
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