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1.
Data Brief ; 41: 107933, 2022 Apr.
Article in English | MEDLINE | ID: mdl-35242915

ABSTRACT

Higher yield and broad adaptation to drought-prone environments are key targets of wheat breeding programs. This can be achieved through a complete knowledge of the genetic architecture of yield and its related traits. This brief article provides analysed mean data used in the research article entitled "QTL mapping for nine drought-responsive agronomic traits in bread wheat under irrigated and rain-fed environments" (Gahlaut et al., 2017). Phenotypic data were recorded on nine important agronomic traits on a doubled haploid (DH) mapping population derived from the cross Kukri/Excalibur. For recording this data, the mapping population was grown during three crop seasons (2010-11 to 2012-13) at four separate locations in India, both under irrigated and rain-fed environments. This dataset is valuable for wheat breeders to better understand the genetic basis of drought tolerance in wheat.

3.
PLoS One ; 12(8): e0182857, 2017.
Article in English | MEDLINE | ID: mdl-28793327

ABSTRACT

In bread wheat, QTL interval mapping was conducted for nine important drought responsive agronomic traits. For this purpose, a doubled haploid (DH) mapping population derived from Kukri/Excalibur was grown over three years at four separate locations in India, both under irrigated and rain-fed environments. Single locus analysis using composite interval mapping (CIM) allowed detection of 98 QTL, which included 66 QTL for nine individual agronomic traits and 32 QTL, which affected drought sensitivity index (DSI) for the same nine traits. Two-locus analysis allowed detection of 19 main effect QTL (M-QTL) for four traits (days to anthesis, days to maturity, grain filling duration and thousand grain weight) and 19 pairs of epistatic QTL (E-QTL) for two traits (days to anthesis and thousand grain weight). Eight QTL were common in single locus analysis and two locus analysis. These QTL (identified both in single- and two-locus analysis) were distributed on 20 different chromosomes (except 4D). Important genomic regions on chromosomes 5A and 7A were also identified (5A carried QTL for seven traits and 7A carried QTL for six traits). Marker-assisted recurrent selection (MARS) involving pyramiding of important QTL reported in the present study, together with important QTL reported earlier, may be used for improvement of drought tolerance in wheat. In future, more closely linked markers for the QTL reported here may be developed through fine mapping, and the candidate genes may be identified and used for developing a better understanding of the genetic basis of drought tolerance in wheat.


Subject(s)
Droughts , Environment , Quantitative Trait Loci , Stress, Physiological/genetics , Triticum/genetics , Agricultural Irrigation , Chromosome Mapping , India , Rain
4.
PLoS One ; 12(6): e0179208, 2017.
Article in English | MEDLINE | ID: mdl-28604800

ABSTRACT

Intensive crop breeding has increased wheat yields and production in India. Wheat improvement in India typically involves selecting yield and component traits under non-hostile soil conditions at regional scales. The aim of this study is to quantify G*E interactions on yield and component traits to further explore site-specific trait selection for hostile soils. Field experiments were conducted at six sites (pH range 4.5-9.5) in 2013-14 and 2014-15, in three agro-climatic regions of India. At each site, yield and component traits were measured on 36 genotypes, representing elite varieties from a wide genetic background developed for different regions. Mean grain yields ranged from 1.0 to 5.5 t ha-1 at hostile and non-hostile sites, respectively. Site (E) had the largest effect on yield and component traits, however, interactions between genotype and site (G*E) affected most traits to a greater extent than genotype alone. Within each agro-climatic region, yield and component traits correlated positively between hostile and non-hostile sites. However, some genotypes performed better under hostile soils, with site-specific relationships between yield and component traits, which supports the value of ongoing site-specific selection activities.


Subject(s)
Quantitative Trait, Heritable , Soil , Stress, Physiological , Triticum/genetics , Breeding , Edible Grain/genetics , Genotype , India , Phenotype , Seasons , Seeds/genetics
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