Multi-model genome-wide association and genomic prediction analysis of 16 agronomic, physiological and quality related traits in ICARDA spring wheat

Published Date
October 28, 2021
Type
Journal Article
Multi-model genome-wide association and genomic prediction analysis of 16 agronomic, physiological and quality related traits in ICARDA spring wheat
Authors:
Admas Alemu
Sufian Suliman Mohammed Elhassan Ali, Adel Hagras, Sherif Thabet, Ayed Al-Abdallat, Awadalla Abdalla Abdelmula, Wuletaw Tadesse

Identification and exploration of the
genetic architecture of traits related to yield, quality,
and drought and heat tolerance is important for yield
and quality improvement of wheat through markerassisted
selection. One hundred and ninety-two spring
wheat genotypes were tested at two heat-stress locations
in Sudan (Wad Medani and Dongula), a drought
stress site in Morocco (Marchouch) and a site with
high yield potential in Egypt (Sids) in replicated trials
during the 2015–2016 and 2016–2017 cropping seasons.
A total of 10,577 single nucleotide polymorphism
markers identified from the 15 K wheat SNP
assay were used in a genome-wide association (GWA)
study and genomic prediction for 16 phenotypic traits
related to yield, quality and drought and heat tolerance.
Significant marker-trait associations were
detected across GWAS models for all traits. Most
detected marker-trait associations (MTAs) were environment-
specific, signifying the presence of high
quantitative trait loci-by-environment (QTL x E)
interaction. Chromosome arm 5AL had significant
multi-model MTAs for grain yield and yield-related
traits at the heat-stress locations.

Citation:
Admas Alemu, Sufian Suliman Mohammed Elhassan Ali, Adel Hagras, Sherif Thabet, Ayed Al-Abdallat, Awadalla Abdalla Abdelmula, Wuletaw Tadesse. (28/10/2021). Multi-model genome-wide association and genomic prediction analysis of 16 agronomic, physiological and quality related traits in ICARDA spring wheat. Euphytica, 217 (11).
Keywords:
gwas
snp
abiotic stress
agronomic traits
common wheat
genomic selection