High-Density GBS-Based Genetic Linkage Map Construction and QTL Identification Associated With Yellow Mosaic Disease Resistance in Bitter Gourd (Momordica charantia L.) - Kaur, Gurpreet; Pathak, Mamta; Singla, Deepak; Sharma, Abhishek; Chhuneja, Parveen; Sarao, Navraj Kaur (Frontiers in Plant Science, 2021)
Yellow mosaic disease (YMD) in bitter gourd (Momordica charantia) is a devastating disease that seriously affects its yield. Although there is currently no effective method to control the disease, breeding of resistant varieties is the most effective and economic option. Moreover, quantitative trait locus (QTL) associated with resistance to YMD have not yet been reported. With the objective of mapping yellow mosaic disease resistance in bitter gourd, the susceptible parent ‘Punjab-14’ and the resistant parent ‘PAUBG-6’ were crossed to obtain F4 mapping population comprising 101 individuals. In the present study, genotyping-by-sequencing (GBS) approach was used to develop the genetic linkage map. The map contained 3,144 single nucleotide polymorphism (SNP) markers, consisted of 15 linkage groups and spanned for 2415.2 cM with an average marker distance of 0.7 cM. By adopting the artificial and field inoculation techniques, F4:5 individuals were phenotyped for disease resistance in Nethouse (2019), Rainy (2019) and Spring season (2020). The QTL analysis using the genetic map and phenotyping data identified three QTLs qYMD.pau_3.1, qYMD.pau_4.1 and qYMD.pau_5.1 on chromosome 3, 4 and 5 respectively. Among these, qYMD.pau_3.1, qYMD.pau_4.1 QTLs were identified in rainy season explaining 13.5 % and 21.6 % phenotypic variance respectively whereas in spring season, qYMD.pau_4.1 and qYMD.pau_5.1 QTLs were observed with 17.5 and 22.1 % phenotypic variance respectively. Only one QTL qYMD.pau_5.1 was identified for disease resistance under nethouse conditions with 15.6 % phenotypic variance. To our knowledge, this is the first report on the identification of QTLs associated with YMD resistance in bitter gourd using SNP markers. The information generated in this study is very useful in future for fine-mapping and for marker-assisted for disease resistance.