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Importance of correcting genomic relationships in single-locus QTL mapping model with an advanced backcross population.

ABSTRACT: Advanced backcross (AB) populations have been widely used to identify and utilize beneficial alleles in various crops such as rice, tomato, wheat, and barley. For the development of an AB population, a controlled crossing scheme is used and this controlled crossing along with the selection (both natural and artificial) of agronomically adapted alleles during the development of AB population may lead to unbalanced allele frequencies in the population. However, it is commonly believed that interval mapping of traits in experimental crosses such as AB populations is immune to the deviations from the expected frequencies under Mendelian segregation. Using two AB populations and simulated data sets as examples, we describe the severity of the problem caused by unbalanced allele frequencies in quantitative trait loci mapping and demonstrate how it can be corrected using the linear mixed model having a polygenic effect with the covariance structure (genomic relationship matrix) calculated from molecular markers.

SUBMITTER: Mathew B

PROVIDER: S-EPMC8495747 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Importance of correcting genomic relationships in single-locus QTL mapping model with an advanced backcross population.

Mathew Boby B Léon Jens J Dadshani Said S Pillen Klaus K Sillanpää Mikko J MJ Naz Ali Ahmad AA

G3 (Bethesda, Md.) 20210601 6

Advanced backcross (AB) populations have been widely used to identify and utilize beneficial alleles in various crops such as rice, tomato, wheat, and barley. For the development of an AB population, a controlled crossing scheme is used and this controlled crossing along with the selection (both natural and artificial) of agronomically adapted alleles during the development of AB population may lead to unbalanced allele frequencies in the population. However, it is commonly believed that interva ...[more]

PMID: 33822941

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Project description:Aphanomyces euteiches is the most damaging soilborne pea pathogen in France. Breeding of pea resistant varieties combining a diversity of quantitative trait loci (QTL) is a promising strategy considering previous research achievements in dissecting polygenic resistance to A. euteiches. The objective of this study was to provide an overview of the diversity of QTL and marker haplotypes for resistance to A. euteiches, by integrating a novel QTL mapping study in advanced backcross (AB) populations with previous QTL analyses and genome-wide association study (GWAS) using common markers. QTL analysis was performed in two AB populations derived from the cross between the susceptible spring pea variety "Eden" and the two new sources of partial resistance "E11" and "LISA". The two AB populations were genotyped using 993 and 478 single nucleotide polymorphism (SNP) markers, respectively, and phenotyped for resistance to A. euteiches in controlled conditions and in infested fields at two locations. GWAS and QTL mapping previously reported in the pea-Aphanomyces collection and from four recombinant inbred line (RIL) populations, respectively, were updated using a total of 1,850 additional markers, including the markers used in the Eden x E11 and Eden x LISA populations analysis. A total of 29 resistance-associated SNPs and 171 resistance QTL were identified by GWAS and RIL or AB QTL analyses, respectively, which highlighted 10 consistent genetic regions confirming the previously reported QTL. No new consistent resistance QTL was detected from both Eden x E11 and Eden x LISA AB populations. However, a high diversity of resistance haplotypes was identified at 11 linkage disequilibrium (LD) blocks underlying consistent genetic regions, especially in 14 new sources of resistance from the pea-Aphanomyces collection. An accumulation of favorable haplotypes at these 11 blocks was confirmed in the most resistant pea lines of the collection. This study provides new SNP markers and rare haplotypes associated with the diversity of Aphanomyces root rot resistance QTL investigated, which will be useful for QTL pyramiding strategies to increase resistance levels in future pea varieties.

Project description:The application of genomic selection to sheep breeding could lead to substantial increases in profitability of wool production due to the availability of accurate breeding values from single nucleotide polymorphism (SNP) data. Several key traits determine the value of wool and influence a sheep's susceptibility to fleece rot and fly strike. Our aim was to predict genomic estimated breeding values (GEBV) and to compare three methods of combining information across traits to map polymorphisms that affect these traits.GEBV for 5726 Merino and Merino crossbred sheep were calculated using BayesR and genomic best linear unbiased prediction (GBLUP) with real and imputed 510,174 SNPs for 22 traits (at yearling and adult ages) including wool production and quality, and breech conformation traits that are associated with susceptibility to fly strike. Accuracies of these GEBV were assessed using fivefold cross-validation. We also devised and compared three approximate multi-trait analyses to map pleiotropic quantitative trait loci (QTL): a multi-trait genome-wide association study and two multi-trait methods that use the output from BayesR analyses. One BayesR method used local GEBV for each trait, while the other used the posterior probabilities that a SNP had an effect on each trait.BayesR and GBLUP resulted in similar average GEBV accuracies across traits (~0.22). BayesR accuracies were highest for wool yield and fibre diameter (>0.40) and lowest for skin quality and dag score (<0.10). Generally, accuracy was higher for traits with larger reference populations and higher heritability. In total, the three multi-trait analyses identified 206 putative QTL, of which 20 were common to the three analyses. The two BayesR multi-trait approaches mapped QTL in a more defined manner than the multi-trait GWAS. We identified genes with known effects on hair growth (i.e. FGF5, STAT3, KRT86, and ALX4) near SNPs with pleiotropic effects on wool traits.The mean accuracy of genomic prediction across wool traits was around 0.22. The three multi-trait analyses identified 206 putative QTL across the ovine genome. Detailed phenotypic information helped to identify likely candidate genes.

Dataset Information

Importance of correcting genomic relationships in single-locus QTL mapping model with an advanced backcross population.

Publications

Importance of correcting genomic relationships in single-locus QTL mapping model with an advanced backcross population.

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