Average information residual maximum likelihood in practice

Gilmour, A.

doi:10.1111/jbg.12398

Cited by 16 publications

(7 citation statements)

References 35 publications

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“…Data analysis was performed using linear mixed models in ASReml‐R v.4 (Gilmour, 2019). The mixed model approach was performed with variance components estimation using the residual maximum likelihood, tests of significance were performed by using a likelihood ratio test for random effects variances and a Wald test for fixed effect factors (Gilmour et al., 1995).…”

Section: Methodsmentioning

confidence: 99%

Phenotypic diversity for phenological and agronomic traits in the UC‐Riverside cowpea (Vigna unguiculata L. Walp) mini‐core collection

et al. 2021

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Cowpea (Vigna unguiculata L. Walp) is a multipurpose crop widely cultivated in tropical and subtropical regions around the world. Characterizing cowpea phenotypes in germplasm collections is a crucial step to ensure future breeding efforts in the species. In this study, we estimated variance components and calculated genetic parameters for eight traits in 292 accessions from the University of California Riverside cowpea mini‐core collection, along with three lines released by the USDA, and seven cultivars. Broad‐sense heritability (H2) ranged from .21 to .83 for all accessions evaluated in Year 1, and from .16 to .83 for traits evaluated in 100 accessions during Year 2. Genotype × year correlations ranged from .45 to .99, illustrating consistency in phenotypic performance for some traits. Positive trait correlations were estimated for plant height and days to flowering, biomass at flowering (R1), and biomass at pod maturity (R6). Biomass at R1 and R6 were highly positively correlated. The USDA line US‐1137 showed high biomass production and can be used as forage and cover crop, whereas US‐1136, US 1138, and the cultivar Iron Clay showed superior traits as dual‐purpose (grain and/or fodder). Several accessions from the mini‐core outperformed cultivars and represent valuable genetic resources that can contribute to cowpea improvement. Moreover, these results showed that multiyear and/or multienvironment studies are needed to reliable select improved germplasm for agronomic traits. This study will provide cowpea breeders and geneticists with valuable phenotypic data to start new breeding efforts, and/or opportunities for gene discovery for key phenological and agronomic traits.

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Section: Methodsmentioning

confidence: 99%

Phenotypic diversity for phenological and agronomic traits in the UC‐Riverside cowpea (Vigna unguiculata L. Walp) mini‐core collection

et al. 2021

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“…Random effects were fitted as follows: G is genotype effect of the i th clone, B is the effect of the j th block, R is the effect of the k th replicate, L is the location of the l th location, Y is the effect of the m th year, GXL is the interactive effect of the i th clone and the l th location, and GXY is the interaction effect of the i th clone and the mth year. This was performed using the mixed model tool Echidna ( Gilmour 2019 ).…”

Section: Methodsmentioning

confidence: 99%

Genome-wide imputation using the practical haplotype graph in the heterozygous crop cassava

Long

Bradbury

Romay

et al. 2021

G3 Genes|Genomes|Genetics

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Genomic applications such as genomic selection and genome-wide association have become increasingly common since the advent of genome sequencing. The cost of sequencing has decreased in the past two decades; however, genotyping costs are still prohibitive to gathering large datasets for these genomic applications, especially in nonmodel species where resources are less abundant. Genotype imputation makes it possible to infer whole-genome information from limited input data, making large sampling for genomic applications more feasible. Imputation becomes increasingly difficult in heterozygous species where haplotypes must be phased. The practical haplotype graph (PHG) is a recently developed tool that can accurately impute genotypes, using a reference panel of haplotypes. We showcase the ability of the PHG to impute genomic information in the highly heterozygous crop cassava (Manihot esculenta). Accurately phased haplotypes were sampled from runs of homozygosity across a diverse panel of individuals to populate PHG, which proved more accurate than relying on computational phasing methods. The PHG achieved high imputation accuracy, using sparse skim-sequencing input, which translated to substantial genomic prediction accuracy in cross-validation testing. The PHG showed improved imputation accuracy, compared to a standard imputation tool Beagle, especially in predicting rare alleles.

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“…The five models were fitted using the Echidna Mixed Model software (Gilmour, 2019). The model with best fit to the data was the one with the lowest Akaike Information Criterion (AIC) value (Akaike, 1974).…”

Section: Crop Sciencementioning

confidence: 99%

Analysis of advanced generation multistage field trials data in autogamous plant breeding: An evaluation in common Bean

et al. 2023

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The performance of inbred lines in advanced endogamous generation is commonly evaluated in successive generations of testing and selection, which we defined as "multistage field trials" (MSFT). MSFT data routinely exhibit heterogeneity of (co)variances at several levels due to genetic and/or statistical imbalance. Nowadays, mixed models have been widely used to deal with unbalanced data. However, few studies on common bean have addressed the use of a mixed model approach with modeling of (co)variance structures for random effects in MSFT. Furthermore, factor analysis and genotype-ideotype distance (FAI-BLUP) selection index was originally proposed using best linear unbiased predictions from individual analysis. In this regard, we aimed to study the implications of modeling (co)variance structures for random effects in the estimation of genetic parameters and evaluate the accuracy and efficiency of inbred line selection by the modeled FAI-BLUP approach. A total of five trials were evaluated from 2018 to 2020. The results revealed that the unstructured covariance matrix fitted better for grain yield, whereas the matrix with uniform correlation and heterogeneity of variances fitted better for grain aspect and plant architecture. The modeled FAI-BLUP approach increased the values of selection accuracy and selection efficiency. Our results suggest that modeling the different structures of (co)variances and selecting the best-performing genotypes by modeled FAI-BLUP approach should be used in common bean assays involving unbalanced data.

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Average information residual maximum likelihood in practice

Cited by 16 publications

References 35 publications

Phenotypic diversity for phenological and agronomic traits in the UC‐Riverside cowpea (Vigna unguiculata L. Walp) mini‐core collection

Phenotypic diversity for phenological and agronomic traits in the UC‐Riverside cowpea (Vigna unguiculata L. Walp) mini‐core collection

Genome-wide imputation using the practical haplotype graph in the heterozygous crop cassava

Analysis of advanced generation multistage field trials data in autogamous plant breeding: An evaluation in common Bean

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