Author: Leonardo Abdiel Crespo Herrera

Fifty years of semi-dwarf spring wheat breeding at CIMMYT: Grain yield progress in optimum, drought and heat stress environments

Suchismita Mondal Somak Dutta Leonardo Abdiel Crespo Herrera JULIO HUERTA_ESPINO Hans-Joachim Braun Ravi Singh (2019)

This dataset provides supplementary files related to fifty years of semi-dwarf spring wheat breeding at CIMMYT: Grain yield progress in optimum, drought and heat stress environments.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication Data for: Allocation of wheat lines in sparse testing for genome-based multi-environment prediction

Leonardo Abdiel Crespo Herrera Ravi Singh Suchismita Mondal Philomin Juliana DIEGO JARQUIN Jose Crossa (2021)

Sparse testing can be used in plant breeding and genome-based prediction. In sparse testing not all of the lines are sown in all environments. The phenotypic and genotypic data files provided in this dataset were used to execute an analysis of three general cases of the composition of the sparse testing allocation design for wheat breeding.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication Data for: Measurements for multi-trait genomic-enabled prediction accuracy in multi-year breeding trials

Daniel Runcie Maria Itria Ibba Osval Antonio Montesinos-Lopez Leonardo Abdiel Crespo Herrera Alison Bentley Jose Crossa (2021)

Several different genome-based prediction models are available for the analysis of multi-trait data in genomic selection. The supplemental files included in this dataset provide six extensive multi-trait wheat datasets (quality and grain yield) that enable the comparison of performance of genomic-enabled-prediction when calculating the prediction accuracy using different methods. The related article describes the results of the analysis and reports that trait grain yield prediction performance is better under a multi-trait model as compared with the single-trait model.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Replication Data for: Elucidating the genetics of grain yield and stress-resilience in bread wheat using a large-scale genome-wide association mapping study with 55,568 lines

Philomin Juliana Ravi Singh Jesse Poland Sandesh Kumar Shrestha JULIO HUERTA_ESPINO Govindan Velu Suchismita Mondal Leonardo Abdiel Crespo Herrera UTTAM KUMAR Thomas Payne (2021)

A large-scale genome-wide association study was carried out to dissect the genetic architecture of wheat grain yield potential and stress-resilience. Based on the findings, grain yield-associated marker profiles were generated for a large panel of 73,142 wheat lines and the grain-yield favorable allele frequencies were also determined. The marker profile data are presented in this dataset.

Dataset

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Haplotype-based genome-wide association study unveils stable genomic regions for grain yield in CIMMYT spring bread wheat

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

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA