Accurate and efficient estimation of local heritability using summary statistics and the linkage disequilibrium matrix

Li, Hui; Mazumder, Rahul; Lin, Xihong

doi:10.1038/s41467-023-43565-9

Cited by 5 publications

(1 citation statement)

References 77 publications

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“…The basic principle of genome-wide association analysis is linkage disequilibrium. Linkage disequilibrium is a non-random association of alleles at different loci and a key indicator of population heritability ( 27–29 ). GWAS analysis does not completely rely on population pedigree information and can directly locate the target traits and SNP sites through genome-wide SNP linkage disequilibrium.…”

Section: Discussionmentioning

confidence: 99%

Genome-wide association analysis of fleece traits in Northwest Xizang white cashmere goat

Lu,

Suo,

Yan

et al. 2024

Front. Vet. Sci.

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Northwest Xizang White Cashmere Goat (NXWCG) is the first new breed of cashmere goat in the Xizang Autonomous Region. It has significant characteristics of extremely high fineness, gloss, and softness. Genome-wide association analysis is an effective biological method used to measure the consistency and correlation of genotype changes between two molecular markers in the genome. In addition, it can screen out the key genes affecting the complex traits of biological individuals. The aim of this study was to analyze the genetic mechanism of cashmere trait variation in NXWCG and to discover SNP locus and key genes closely related to traits such as superfine cashmere. Additionally, the key genes near the obtained significant SNPs were analyzed by gene function annotation and biological function mining. In this study, the phenotype data of the four traits (cashmere length, fiber length, cashmere diameter, and cashmere production) were collected. GGP_Goat_70K SNP chip was used for genotyping the ear tissue DNA of the experimental group. Subsequently, the association of phenotype data and genotype data was performed using Gemma-0.98.1 software. A linear mixed model was used for the association study. The results showed that four fleece traits were associated with 18 significant SNPs at the genome level and 232 SNPs at the chromosome level, through gene annotated from Capra hircus genome using assembly ARS1. A total of 107 candidate genes related to fleece traits were obtained. Combined with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, we can find that CLNS1A, CCSER1, RPS6KC1, PRLR, KCNRG, KCNK9, and CLYBL can be used as important candidate genes for fleece traits of NXWCG. We used Sanger sequencing and suitability chi-square test to further verify the significant loci and candidate genes screened by GWAS, and the results show that the base mutations loci on the five candidate genes, CCSER1 (snp12579, 34,449,796, A → G), RPS6KC1 (snp41503, 69,173,527, A → G), KCNRG (snp41082, 67,134,820, G → A), KCNK9 (14:78472665, 78,472,665, G → A), and CLYBL (12: 9705753, 9,705,753, C → T), significantly affect the fleece traits of NXWCG. The results provide a valuable basis for future research and contribute to a better understanding of the genetic structure variation of the goat.

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Section: Discussionmentioning

confidence: 99%

Genome-wide association analysis of fleece traits in Northwest Xizang white cashmere goat

Lu,

Suo,

Yan

et al. 2024

Front. Vet. Sci.

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Local genetic correlation via knockoffs reduces confounding due to cross-trait assortative mating

Ma,

Wang,

Border

et al. 2024

The American Journal of Human Genetics

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Improved heritability partitioning and enrichment analyses using summary statistics with graphREML

Li,

Kamath,

Mazumder

et al. 2024

Preprint

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Heritability enrichment analysis using data from Genome-Wide Association Studies (GWAS) is often used to understand the functional basis of genetic architecture. Stratified LD score regression (SLDSC) is a widely used method-of-moments estimator for heritability enrichment, but S-LDSC has low statistical power compared with likelihood-based approaches. We introduce graphREML, a precise and powerful likelihood-based heritability partition and enrichment analysis method. graphREML operates on GWAS summary statistics and linkage disequilibrium graphical models (LDGMs), whose sparsity makes likelihood calculations tractable. We validate our method using extensive simulations and in analyses of a wide range of real traits. On average across traits, graphREML produces enrichment estimates that are concordant with S-LDSC, indicating that both methods are unbiased; however, graphREML identifies 2.5 times more significant trait-annotation enrichments, demonstrating greater power compared to the moment-based S-LDSC approach. graphREML can also more flexibly model the relationship between the annotations of a SNP and its heritability, producing well-calibrated estimates of per-SNP heritability.

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Accurate and efficient estimation of local heritability using summary statistics and the linkage disequilibrium matrix

Cited by 5 publications

References 77 publications

Genome-wide association analysis of fleece traits in Northwest Xizang white cashmere goat

Genome-wide association analysis of fleece traits in Northwest Xizang white cashmere goat

Local genetic correlation via knockoffs reduces confounding due to cross-trait assortative mating

Improved heritability partitioning and enrichment analyses using summary statistics with graphREML

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