Identification of the genomic regions contributing for heat stress tolerance in wheat (Triticum aestivum L. em. Thell) under multi environmental conditions
Loading...
Date
2023-02
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
G. B. Pant University of Agriculture & Technology, Pantnagar-263145
Abstract
Wheat is the third most important cereal crop grown worldwide which provides 25% - 50%
calorific needs of growing human population and is the staple source of diet for millions of people all
over the world. With the ever increasing global average temperature, wheat is considerably subjected
to heat stress. Heat stress tolerance is a stage-specific and developmentally regulated quantitative trait.
Hence genetic dissection of this quantitative trait through QTL mapping Mendelizes trait behaviour
thus easing the selection and improvement for heat stress tolerance. In the present investigation, 192
Recombinant Inbred lines (RILs) derived from the cross between PBN51 and Raj4014 were evaluated
under multi environmental conditions (GBPUAT, Pantnagar, BHU, Varanasi and SKUAST, Jammu)
for QTL mapping for different morpho-physiological and yield traits viz days to heading (DH), days
to maturity (DM), grain filling duration (GFD), plant height (PH), spike length (SL), number of
spikelets per spike (SPS), number of grains per spike (GPS), number of productive tillers per meter
(TPM), grain weight per spike (GWPS), thousand grain weight (TGW), grain yield per plot (YPP),
canopy temperature depression (CTD), Normalised difference vegetation index (NDVI) and relative
chlorophyll content. In correlation studies, grain yield per plot showed significant positive correlation
with TGW, GWPS, TPM, SPAD (at pre booting stage), GPS, CTD (at heading stage), GFD, PH and
was found to be negatively correlated with DH. Genotype and Genotype x Environment interaction
analysis by GGE biplots revealed that the lines 143, 5, 132, 97 and 156 were ideal as they had higher
mean grain yield per plot as well as stable across environments. Among the environments,
Jammu_2017-18_LS was found to be more representative of the genotypes for YPP. For QTL
mapping, the RILs were genotyped with 83 polymorphic SSR markers and genetic linkage map was
created using ICIM v4.2 software. Through Inclusive Composite Interval Mapping, a total of 31 QTLs
with LOD scores more than 3.0 were identified on 21 genomic regions across 14 chromosomes with
chromosome 1A harbouring 4 QTLs. Among these, 6 QTLs were found to be major, explaining PVE
of more than 9%. These QTLs are designated as QGfd.pant_5B, QGps.pant_1A, QGps.pant_3A,
QGwps.pant_1A, QTgw.pant_7A-1 and QTgw.pant_7D. Under multi-environmental evaluation, 10
QTLs were found to be consistent across two or more environments and 4 genomic regions on
chromosomes 1A, 3A, 5B and 7D were found to be associated with two or more traits. The QTLs thus
identified can be used in marker assisted selection after fine mapping and validation.
Description
Keywords
Citation
Theses of Ph.D