Mavi, Gurvinder SinghHarjap Singh2022-11-112022-11-112021Harjap Singh (2021). Mapping of the Stripe rust resistance gene(s) in a nested RIL population of wheat (Unpublished M.Sc. thesis). Punjab Agricultural University, Ludhiana, Punjab, India.https://krishikosh.egranth.ac.in/handle/1/5810189771Wheat stripe rust, caused by the fungal pathogen Puccinia striiformis f. sp. tritici, is one of the most devastating diseases of wheat in China and causes serious yield losses. Resistance genes are urgently needed by wheat breeding programs to combat this disease. In the present study, genetic analysis of stripe rust resistance was conducted on segregated F3 and F4 populations derived from the cross of susceptible parent PBW 621 and resistant line IC529090 and IC445316. The results showed that the resistance of stripe rust was controlled by 2 genes. In addition, GBS of the parental lines PBW 621 and IC 445316 and the corresponding bulked pools derived from homozygous resistant or susceptible F4 lines was implemented to identify single-nucleotide polymorphism (SNPs).DNA was normalized and the pool of 10 resistant and the 10 susceptible plants was made. QTSeqR package (available in R) was utilized for the bulk-segregant analysis of yellow rust using two different methods GPrime and DeltaSNP. A straightforward pipeline for analysis has been designed with the plant breeder and geneticist in mind: (i) import SNP data, (ii) filter SNPs that may complicate analysis, (iii) perform BSAs, (iv) plot results, and (v) export the data. A vignette with a stepby-step guide is available at https://github.com/bmansfeld/QTLseqr/blob/master vignettes/ QTLseqr.pdf. Nineteen (19) significant SNPs were identified by the Gprime method and 3 significant SNPs by the Delta SNP method and the 3 significant SNPs by both the Gprime and the delta SNP method. Novelty of the identified genes an be confirmed with further genetic analysis which can then be useful to broaden the narrow rust resistance spectrum in hexaploid wheat.EnglishThesis