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Author: deepmala sehgal
Editorial: genetics and genomics to enhance crop production, towards food security
deepmala sehgal Arron Carter (2021)
Article
Candidate Genes Association Mapping Genomic Selection CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ABIOTIC STRESS DISEASE RESISTANCE GENES CHROMOSOME MAPPING MARKER-ASSISTED SELECTION GENE EDITING CROP IMPROVEMENT
deepmala sehgal Susanne Dreisigacker (2020)
The genotypic data included in this dataset were generated using DArTseq by the SAGA genotyping laboratory in Mexico. The dataset contains 8,154 SNPs on candidate varieties from Kazakhstan and those released by CIMMYT-ICARDA-IWWIP program. These were evaluated for tan spot resistance at Kazakhstan.
Dataset
Juan Burgueño deepmala sehgal (2019)
Phenotypic evaluation of the Linked Topcross Population 1 (LTP1) from the MasAgro Biodiversidad - Seeds of Discovery Initiative under drought, heat, and irrigated conditions.
Dataset
Selection signatures in the CIMMYT International Elite Spring and Semi-arid Wheat Yield Trials
Umesh Rosyara deepmala sehgal Susanne Dreisigacker (2021)
Article
CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING LINES WHEAT PLANT GENETICS GENOMICS
Genomic selection models based on integration of GWAS loci and epistatic interactions
deepmala sehgal Suchismita Mondal Ravi Singh Susanne Dreisigacker (2020)
The potential to integrate consistent associations identified from GWAS as fixed variables in GP models to improve prediction accuracy for complex traits (for example, grain yield) has not been investigated comprehensively in wheat. Here, we untangled the genetic architecture of grain yield and yield stability by haplotypes-based GWAS and epistatic scan of the genome. We then integrated robust and stable associations (and interacting loci) as fixed effects in GP models to investigate the importance of these associations in improving prediction accuracies of the said traits. We concluded that the utility of GP incorporating GWAS results is noteworthy for GY when GWAS results identify significant and robust genomic regions.
Dataset
deepmala sehgal Susanne Dreisigacker zafer mert EMEL SELMA OZER Alexey Morgounov (2016)
Turkish landraces were genotyped using GBS and phenotyped for grain yield and yield component traits and stripe rust resistance at three locations. The data was used for a genome wide association study and important marker-trait associations were identified.
Dataset
Alexey Morgounov fatih ozdemir Mesut KESER Abdelfattah DABABAT Susanne Dreisigacker Hafiz Muminjanov Ajit Nehe awais rasheed Mozaffar Roostaei deepmala sehgal Rajiv Sharma (2021)
Article
Molecular Markers CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT AGROBIODIVERSITY LANDRACES VARIETIES YIELD COMPONENTS GENETIC MARKERS
deepmala sehgal Suchismita Mondal Leonardo Abdiel Crespo Herrera Govindan Velu Philomin Juliana JULIO HUERTA_ESPINO Sandesh Kumar Shrestha Jesse Poland Ravi Singh Susanne Dreisigacker (2020)
Genetic architecture of grain yield (GY) has been extensively investigated in wheat using genome wide association study (GWAS) approach. However, most studies have used small panel sizes in combination with large genotypic data, typical examples of the so-called ‘large p small n’ or ‘short-fat data’ problem. Further, use of bi-allelic SNPs accentuated ‘missing heritability’ issues and therefore reported markers had limited impact in wheat breeding. We performed haplotype-based GWAS using 519 haplotype blocks on seven large cohorts of advanced CIMMYT spring bread wheat lines comprising overall 6,333 genotypes. In addition, epistatic interactions among the genome-wide haplotypes were investigated, an important aspect which has not yet been fully explored in wheat GWAS in order to address the missing heritability. Our results unveiled the intricate genetic architecture of GY controlled by both main and epistatic effects. The importance of these results from practical applications in the CIMMYT breeding program is discussed.
Dataset