Genomic partitioning of growth traits using a high-density single nucleotide polymorphism array in Hanwoo (Korean cattle)

Objective: The objective of this study was to characterize the number of loci affecting growth traits and the distribution of single nucleotide polymorphism (SNP) effects on growth traits, and to understand the genetic architecture for growth traits in Hanwoo (Korean cattle) using genome-wide association study (GWAS), genomic partitioning, and hierarchical Bayesian mixture models.Methods: GWAS: A single-marker regression-based mixed model was used to test the association between SNPs and causal variants. A genotype relationship matrix was fitted as a random effect in this linear mixed model to correct the genetic structure of a sire family. Genomic restricted maximum likelihood and BayesR: A priori information included setting the fixed additive genetic variance to a pre-specified value; the first mixture component was set to zero, the second to 0.0001×σ_g^2, the third 0.001 × σ_g^2, d the fourth to 0.01 × σ_g^2. BayesR fixed a priori information was not more than 1% of the genetic variance for each of the SNPs affecting the mixed distribution.Results: The GWAS revealed common genomic regions of 2 Mb on bovine chromosome 14 (BTA14) and 3 had a moderate effect that may contain causal variants for body weight at 6, 12, 18, and 24 months. This genomic region explained approximately 10% of the variance against total additive genetic variance and body weight heritability at 12, 18, and 24 months. BayesR identified the exact genomic region containing causal SNPs on BTA14, 3, and 22. However, the genetic variance explained by each chromosome or SNP was estimated to be very small compared to the total additive genetic variance. Causal SNPs for growth trait on BTA14 explained only 0.04% to 0.5% of the genetic varianceConclusion: Segregating mutations have a moderate effect on BTA14, 3, and 19; many other loci with small effects on growth traits at different ages were also identified.

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Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds

Genetics Selection Evolution ◽

10.1186/s12711-021-00671-w ◽

2021 ◽

Vol 53 (1) ◽

Author(s):

Miguel Gozalo-Marcilla ◽

Jaap Buntjer ◽

Martin Johnsson ◽

Lorena Batista ◽

Federico Diez ◽

...

Keyword(s):

Candidate Genes ◽

Genetic Variance ◽

Mixed Model ◽

Linear Mixed Model ◽

Insulin Signalling ◽

Additive Genetic Variance ◽

Genomic Region ◽

Carcass Composition ◽

Backfat Thickness ◽

Genomic Regions

Abstract Background Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgrounds. Methods Data comprised 275,590 pigs from eight lines with diverse genetic backgrounds (breeds included Large White, Landrace, Pietrain, Hampshire, Duroc, and synthetic lines) genotyped and imputed for 71,324 single-nucleotide polymorphisms (SNPs). For each line, we estimated SNP associations using a univariate linear mixed model that accounted for genomic relationships. SNPs with significant associations were identified using a threshold of p < 10–6 and used to define genomic regions of interest. The proportion of genetic variance explained by a genomic region was estimated using a ridge regression model. Results We found significant associations with backfat thickness for 264 SNPs across 27 genomic regions. Six genomic regions were detected in three or more lines. The average estimate of the SNP-based heritability was 0.48, with estimates by line ranging from 0.30 to 0.58. The genomic regions jointly explained from 3.2 to 19.5% of the additive genetic variance of backfat thickness within a line. Individual genomic regions explained up to 8.0% of the additive genetic variance of backfat thickness within a line. Some of these 27 genomic regions also explained up to 1.6% of the additive genetic variance in lines for which the genomic region was not statistically significant. We identified 64 candidate genes with annotated functions that can be related to fat metabolism, including well-studied genes such as MC4R, IGF2, and LEPR, and more novel candidate genes such as DHCR7, FGF23, MEDAG, DGKI, and PTN. Conclusions Our results confirm the polygenic architecture of backfat thickness and the role of genes involved in energy homeostasis, adipogenesis, fatty acid metabolism, and insulin signalling pathways for fat deposition in pigs. The results also suggest that several less well-understood metabolic pathways contribute to backfat development, such as those of phosphate, calcium, and vitamin D homeostasis.

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Narrow-sense heritability estimation of complex traits using identity-by-descent information

10.1101/164848 ◽

2017 ◽

Author(s):

Luke M. Evans ◽

Rasool Tahmasbi ◽

Matthew Jones ◽

Scott I. Vrieze ◽

Gonçalo R. Abecasis ◽

...

Keyword(s):

Complex Traits ◽

Genetic Variance ◽

Additive Genetic Variance ◽

Fundamental Parameter ◽

Last Common Ancestor ◽

Narrow Sense ◽

Narrow Sense Heritability ◽

Heritability Estimation ◽

Causal Variants ◽

Heritability Estimates

ABSTRACTHeritability is a fundamental parameter in genetics. Traditional estimates based on family or twin studies can be biased due to shared environmental or non-additive genetic variance. Alternatively, those based on genotyped or imputed variants typically underestimate narrow-sense heritability contributed by rare or otherwise poorly-tagged causal variants. Identical-by-descent (IBD) segments of the genome share all variants between pairs of chromosomes except new mutations that have arisen since the last common ancestor. Therefore, relating phenotypic similarity to degree of IBD sharing among classically unrelated individuals is an appealing approach to estimating the near full additive genetic variance while avoiding biases that can occur when modeling close relatives. We applied an IBD-based approach (GREML-IBD) to estimate heritability in unrelated individuals using phenotypic simulation with thousands of whole genome sequences across a range of stratification, polygenicity levels, and the minor allele frequencies of causal variants (CVs). IBD-based heritability estimates were unbiased when using unrelated individuals, even for traits with extremely rare CVs, but stratification led to strong biases in IBD-based heritability estimates with poor precision. We used data on two traits in ~120,000 people from the UK Biobank to demonstrate that, depending on the trait and possible confounding environmental effects, GREML-IBD can be applied successfully to very large genetic datasets to infer the contribution of very rare variants lost using other methods. However, we observed apparent biases in this real data that were not predicted from our simulation, suggesting that more work may be required to understand factors that influence IBD-based estimates.

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BARTweb: a web server for transcription factor association analysis

10.1101/2020.02.17.952838 ◽

2020 ◽

Cited By ~ 1

Author(s):

Wenjing Ma ◽

Zhenjia Wang ◽

Yifan Zhang ◽

Neal E. Magee ◽

Yang Chen ◽

...

Keyword(s):

Gene Regulation ◽

Association Analysis ◽

A Priori ◽

Genomic Region ◽

Sequence Motif ◽

Regulation Of Transcription ◽

Motif Analysis ◽

Active Transcription ◽

Differential Gene ◽

Priori Information

ABSTRACTIdentifying active transcription factors (TFs) that bind to cis-regulatory regions in the genome to regulate differential gene expression is a key task in gene regulation research. TF binding profiles from numerous existing ChIP-seq data can be utilized for association analysis with query data for TF identification, as alternative to DNA sequence motif analysis. Here, we present BARTweb, an interactive webserver for identifying TFs whose genomic binding patterns associate with input genomic features, by leveraging over 13,000 public ChIP-seq datasets for human and mouse. Using an updated Binding Analysis for Regulation of Transcription (BART) algorithm, BARTweb can identify functional TFs that regulate a gene set, or have a binding profile correlated with a ChIP-seq profile or enriched in a genomic region set, without a priori information of the cell type. Compared with the original BART package, BARTweb substantially reduces the execution time of a typical job by two orders of magnitude. We also show that BARTweb outperforms other existing tools in identifying true TFs from collected experimental data. BARTweb is a useful webserver for performing functional analysis of gene regulation. BARTweb is freely available at http://bartweb.org.

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The Contribution of Copy Number Variants and Single Nucleotide Polymorphisms to the Additive Genetic Variance of Carcass Traits in Cattle

Frontiers in Genetics ◽

10.3389/fgene.2021.761503 ◽

2021 ◽

Vol 12 ◽

Author(s):

Pierce Rafter ◽

Isobel Claire Gormley ◽

Andrew C. Parnell ◽

Saeid Naderi ◽

Donagh P. Berry

Keyword(s):

Regression Analysis ◽

Candidate Genes ◽

Copy Number ◽

Genetic Variance ◽

Additive Genetic Variance ◽

Carcass Traits ◽

Copy Number Variants ◽

Nucleotide Polymorphisms ◽

Lasso Regression ◽

Single Nucleotide

The relative contributions of both copy number variants (CNVs) and single nucleotide polymorphisms (SNPs) to the additive genetic variance of carcass traits in cattle is not well understood. A detailed understanding of the relative importance of CNVs in cattle may have implications for study design of both genomic predictions and genome-wide association studies. The first objective of the present study was to quantify the relative contributions of CNV data and SNP genotype data to the additive genetic variance of carcass weight, fat, and conformation for 945 Charolais, 923 Holstein-Friesian, and 974 Limousin sires. The second objective was to jointly consider SNP and CNV data in a least absolute selection and shrinkage operator (LASSO) regression model to identify genomic regions associated with carcass weight, fat, and conformation within each of the three breeds separately. A genomic relationship matrix (GRM) based on just CNV data did not capture any variance in the three carcass traits when jointly evaluated with a SNP-derived GRM. In the LASSO regression analysis, a total of 987 SNPs and 18 CNVs were associated with at least one of the three carcass traits in at least one of the three breeds. The quantitative trait loci (QTLs) corresponding to the associated SNPs and CNVs overlapped with several candidate genes including previously reported candidate genes such as MSTN and RSAD2, and several potential novel candidate genes such as ACTN2 and THOC1. The results of the LASSO regression analysis demonstrated that CNVs can be used to detect associations with carcass traits which were not detected using the set of SNPs available in the present study. Therefore, the CNVs and SNPs available in the present study were not redundant forms of genomic data.

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Estimation of non-additive genetic variance in human complex traits from a large sample of unrelated individuals

10.1101/2020.11.09.375501 ◽

2020 ◽

Author(s):

Valentin Hivert ◽

Julia Sidorenko ◽

Florian Rohart ◽

Michael E Goddard ◽

Jian Yang ◽

...

Keyword(s):

Complex Traits ◽

Genetic Variance ◽

Additive Genetic Variance ◽

Sampling Variance ◽

Analysis Model ◽

Additive Variance ◽

Snp Data ◽

Causal Variants ◽

The Uk ◽

Epistatic Variance

AbstractNon-additive genetic variance for complex traits is traditionally estimated from data on relatives. It is notoriously difficult to estimate without bias in non-laboratory species, including humans, because of possible confounding with environmental covariance among relatives. In principle, non-additive variance attributable to common DNA variants can be estimated from a random sample of unrelated individuals with genome-wide SNP data. Here, we jointly estimate the proportion of variance explained by additive , dominance and additive-by-additive genetic variance in a single analysis model. We first show by simulations that our model leads to unbiased estimates and provide new theory to predict standard errors estimated using either least squares or maximum likelihood. We then apply the model to 70 complex traits using 254,679 unrelated individuals from the UK Biobank and 1.1M genotyped and imputed SNPs. We found strong evidence for additive variance (average across traits . In contrast, the average estimate of across traits was 0.001, implying negligible dominance variance at causal variants tagged by common SNPs. The average epistatic variance across the traits was 0.058, not significantly different from zero because of the large sampling variance. Our results provide new evidence that genetic variance for complex traits is predominantly additive, and that sample sizes of many millions of unrelated individuals are needed to estimate epistatic variance with sufficient precision.

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Additive and Dominance Genomic Analysis for Litter Size in Purebred and Crossbred Iberian Pigs

Genes ◽

10.3390/genes13010012 ◽

2021 ◽

Vol 13 (1) ◽

pp. 12

Author(s):

Houssemeddine Srihi ◽

José Luis Noguera ◽

Victoria Topayan ◽

Melani Martín de Hijas ◽

Noelia Ibañez-Escriche ◽

...

Keyword(s):

Litter Size ◽

Genetic Variance ◽

Mixed Model ◽

Additive Genetic Variance ◽

Genetic Correlations ◽

Genomic Analysis ◽

Gxe Interaction ◽

Genomic Regions ◽

Additive Genetic Effects ◽

Selection Of

INGA FOOD S. A., as a Spanish company that produces and commercializes fattened pigs, has produced a hybrid Iberian sow called CASTÚA by crossing the Retinto and Entrepelado varieties. The selection of the parental populations is based on selection criteria calculated from purebred information, under the assumption that the genetic correlation between purebred and crossbred performance is high; however, these correlations can be less than one because of a GxE interaction or the presence of non-additive genetic effects. This study estimated the additive and dominance variances of the purebred and crossbred populations for litter size, and calculated the additive genetic correlations between the purebred and crossbred performances. The dataset consisted of 2030 litters from the Entrepelado population, 1977 litters from the Retinto population, and 1958 litters from the crossbred population. The individuals were genotyped with a GeneSeek® GGP Porcine70K HDchip. The model of analysis was a ‘biological’ multivariate mixed model that included additive and dominance SNP effects. The estimates of the additive genotypic variance for the total number born (TNB) were 0.248, 0.282 and 0.546 for the Entrepelado, Retinto and Crossbred populations, respectively. The estimates of the dominance genotypic variances were 0.177, 0.172 and 0.262 for the Entrepelado, Retinto and Crossbred populations. The results for the number born alive (NBA) were similar. The genetic correlations between the purebred and crossbred performance for TNB and NBA—between the brackets—were 0.663 in the Entrepelado and 0.881 in Retinto poplulations. After backsolving to obtain estimates of the SNP effects, the additive genetic variance associated with genomic regions containing 30 SNPs was estimated, and we identified four genomic regions that each explained > 2% of the additive genetic variance in chromosomes (SSC) 6, 8 and 12: one region in SSC6, two regions in SSC8, and one region in SSC12.

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Genetic structure of growth and phenological traits in Salix viminalis

Canadian Journal of Forest Research ◽

10.1139/x00-175 ◽

2001 ◽

Vol 31 (2) ◽

pp. 276-282 ◽

Cited By ~ 2

Author(s):

Ann Christin Rönnberg-Wästljung

Keyword(s):

Linkage Disequilibrium ◽

Genetic Structure ◽

Genetic Variance ◽

Growth Traits ◽

Additive Genetic Variance ◽

Geographic Origin ◽

Salix Viminalis ◽

Parental Origin ◽

Dominance Genetic Variance ◽

Sexual Propagation

The genetic structure of Salix viminalis L. for different growth traits and bud flush has been studied. The aim was also to study differences in the genetic structure due to geographic origin and type of trait. Two incomplete factorial crossings with parental clones originating from Poland and Sweden were used. Growth traits showed a high amount of dominance genetic variance independent of parental origin. It is suggested that inbreeding depression found in S. viminalis could be a biological cause of the high levels of dominance as an alternative to overestimation due to epistasis. There were significant differences in amount of dominance genetic variance between the two origins for three of the nine growth traits. The higher number of characters influenced by dominance in the pedigree with Swedish origin can possibly be explained by linkage disequilibrium, since S. viminalis in Sweden has been introduced from Germany and Poland, and no sexual propagation of the species in Sweden has been reported. Bud flush showed high additive genetic variance in contrast to the growth traits. In the breeding for biomass production of S. viminalis, the high amount of dominance has to be taken into consideration.

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BARTweb: a web server for transcriptional regulator association analysis

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqab022 ◽

2021 ◽

Vol 3 (2) ◽

Cited By ~ 1

Author(s):

Wenjing Ma ◽

Zhenjia Wang ◽

Yifan Zhang ◽

Neal E Magee ◽

Yayi Feng ◽

...

Keyword(s):

Gene Regulation ◽

Association Analysis ◽

A Priori ◽

Web Server ◽

Regulatory Elements ◽

Genomic Region ◽

Sequence Motif ◽

Regulation Of Transcription ◽

Motif Analysis ◽

Priori Information

Abstract Identifying active transcriptional regulators (TRs) associating with cis-regulatory elements in the genome to regulate gene expression is a key task in gene regulation research. TR binding profiles from numerous public ChIP-seq data can be utilized for association analysis with query data for TR identification, as an alternative to DNA sequence motif analysis. However, integration of the massive ChIP-seq datasets has been a major challenge in such approaches. Here we present BARTweb, an interactive web server for identifying TRs whose genomic binding patterns associate with input genomic features, by leveraging over 13 000 public ChIP-seq datasets for human and mouse. Using an updated binding analysis for regulation of transcription (BART) algorithm, BARTweb can identify functional TRs that regulate a gene set, have a binding profile correlated with a ChIP-seq profile or are enriched in a genomic region set, without a priori information of the cell type. BARTweb can be a useful web server for performing functional analysis of gene regulation. BARTweb is freely available at http://bartweb.org and the source code is available at https://github.com/zanglab/bart2.

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Multisite genetic parameter estimates from a Callitropsis nootkatensis diallel study with clonally replicated progeny

Canadian Journal of Forest Research ◽

10.1139/cjfr-2014-0331 ◽

2015 ◽

Vol 45 (6) ◽

pp. 689-697 ◽

Cited By ~ 1

Author(s):

John H. Russell ◽

João Costa e Silva ◽

Brian S. Baltunis

Keyword(s):

Genetic Variance ◽

Mixed Model ◽

Linear Mixed Model ◽

Additive Genetic Variance ◽

Genetic Parameter ◽

Genetic Correlations ◽

Parameter Estimates ◽

Narrow Sense ◽

Spatially Correlated ◽

Crown Form

Clonally replicated Callitropsis nootkatensis (D. Don) D.P. Little progeny from partial diallels were established in nine trials on coastal British Columbia, Canada. The trials were assessed for height, diameter, and crown form at age 12 years. An individual-genotype, linear mixed model with spatially correlated residuals was used to estimate the variance components and related genetic parameters. The majority of the estimated genetic variance for all traits was additive, and nonadditive genetic variance was predominantly due to dominance effects. Narrow-sense heritabilities for height and diameter at individual sites varied from 0.07 to 0.39, whereas for crown form, they were all less than 0.1. Dominance and epistasis ratios were, for the most part, lower than narrow-sense heritabilities. Common across-site additive and nonadditive genetic correlations were strongly positive and not significantly different from 1.0 for the majority of traits across sites within a series. Significant levels of additive genetic variance, coupled with insignificant to low nonadditive genetic variance for growth and crown form, would seem to be contrary to developing a clonal testing and deployment program. However, the lack of viable orchard seed and the faster delivery of genetic gain to reforestation, as well as more accurate forward selections based on additive genetic effects, makes this strategy viable for C. nootkatensis.

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Adaptability in tropical beef cattle: genetic parameters of growth, adaptive and temperament traits in a crossbred population

Australian Journal of Experimental Agriculture ◽

10.1071/ea05045 ◽

2005 ◽

Vol 45 (8) ◽

pp. 971 ◽

Cited By ~ 43

Author(s):

K. C. Prayaga ◽

J. M. Henshall

Keyword(s):

Beef Cattle ◽

Genetic Parameters ◽

Genetic Variance ◽

Growth Traits ◽

Additive Genetic Variance ◽

Average Daily Gain ◽

Genetic Correlations ◽

Temperament Traits ◽

Indicator Traits ◽

Daily Gain

Adaptability in tropical beef cattle can be assessed by measurable traits such as growth under the influence of environmental stressors, by parasite resistance as measured by indicator traits such as tick counts (TICK) and faecal egg counts of worms (EPG), by heat resistance as measured by indicator traits such as rectal temperatures (TEMP) and coat scores (COAT) and, to a certain extent, temperament of the animal as measured by flight time (FT). Data from a crossbreeding experiment involving various genotypes derived from tropically adapted British, Sanga-derived, Zebu cross, Zebu and Continental beef cattle breeds were analysed to estimate variance components and genetic parameters of growth, adaptive and temperament traits. Breed group differences were accounted for by including fractional coefficients of direct and maternal additive and dominance genetic effects as covariates. In the univariate analyses, 6 models were compared ranging from the simplest model with animal as the only random effect to the full model comprising direct and maternal additive genetic variance and their covariance and the permanent environment effect due to dam (growth traits) and animal (adaptive and temperament traits). The heritability estimates were 0.41, 0.21, 0.19, 0.28, 0.41 and 0.15 for birth weight (BWT), weaning weight (WWT), preweaning average daily gain (PREADG), yearling weight (YWT), final weight at about 18 months of age (FWT) and post-weaning average daily gain (POADG), respectively. The maternal component of additive genetic variance as a proportion of phenotypic variance in BWT, WWT and PREADG was 0.15, 0.10 and 0.10, respectively. The heritability estimates for TICK, EPG, TEMP, COAT and FT were 0.13, 0.24, 0.12, 0.26 and 0.20, respectively. High positive genetic and phenotypic correlations were observed among growth traits. Low (insignificant) genetic correlations were observed between TICK, EPG and growth traits. However, genetic correlations between growth traits and heat tolerance traits (TEMP and COAT) were moderately negative implying that as the ability of an animal to handle heat stress increases, growth also increases at the genetic level. Genetic correlations among TICK, EPG and TEMP were moderately positive, suggesting that closely-linked genes affect these adaptive traits. The significant negative genetic relationship between TEMP and FT suggests that cattle with high heat resistance have desirable temperament. With the increasing crossbred populations in the northern Australian beef cattle industry, the best breeding strategy should aim to exploit both crossbreeding and within population selection to make improvements in growth, adaptive and temperament traits to increase overall productivity of the enterprise.

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