Single-Step Genome Wide Association Study Identifies QTL Signals for Untrimmed and Trimmed Thigh Weight in Italian Crossbred Pigs for Dry-Cured Ham Production

Protected Designation of Origin (PDO) dry-cured ham is the most important product in the Italian pig breeding industry, mainly oriented to produce heavy pig carcasses to obtain hams of the right weight and maturity. Recently, along with the traditional traits swine breeding programs have aimed to include novel carcass traits. The identification at the genome level of quantitative trait loci (QTLs) affecting such new traits helps to reveal their genetic determinism and may provide information to be integrated in prediction models in order to improve prediction accuracy as well as to identify candidate genes underlying such traits. This study aimed to estimate genetic parameters and perform a single step genome wide association studies (ssGWAS) on novel carcass traits such as untrimmed (UTW) and trimmed thigh weight (TTW) in two pig crossbred lines approved for the ham production of the Italian PDO. With this purpose, phenotypes were collected from ~1800 animals and 240 pigs were genotyped with Illumina PorcineSNP60 Beadchip. The single-step genomic BLUP procedure was used for the heritability estimation and to implement the ssGWAS. QTL were characterized based on the variance of 10-SNP sliding window genomic estimated breeding values. Moderate heritabilities were detected and QTL signals were identified on chromosome 1, 4, 6, 7, 11 and 15 for both traits. As expected, the genetic correlation among the two traits was very high (~0.99). The QTL regions encompassed a total of 249 unique candidate genes, some of which were already reported in association with growth, carcass or ham weight traits in pigs. Although independent studies are required to further verify our findings and disentangle the possible effects of specific linkage disequilibrium in our population, our results support the potential use of such new QTL information in future breeding programs to improve the reliability of genomic prediction.

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Genome-wide association studies and meta-analysis uncovers new candidate genes for growth and carcass traits in pigs

PLoS ONE ◽

10.1371/journal.pone.0205576 ◽

2018 ◽

Vol 13 (10) ◽

pp. e0205576 ◽

Cited By ~ 4

Author(s):

Iulia Blaj ◽

Jens Tetens ◽

Siegfried Preuß ◽

Jörn Bennewitz ◽

Georg Thaller

Keyword(s):

Candidate Genes ◽

Association Studies ◽

Meta Analysis ◽

Carcass Traits ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide

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Genome-wide Association Study for Carcass Primal Cut Yields Using Single-step Bayesian Approach in Hanwoo Cattle

Frontiers in Genetics ◽

10.3389/fgene.2021.752424 ◽

2021 ◽

Vol 12 ◽

Author(s):

Masoumeh Naserkheil ◽

Hossein Mehrban ◽

Deukmin Lee ◽

Mi Na Park

Keyword(s):

Quantitative Trait Loci ◽

Candidate Genes ◽

Quantitative Trait ◽

Single Step ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Trait Loci ◽

Genomic Regions ◽

Hanwoo Cattle

The importance of meat and carcass quality is growing in beef cattle production to meet both producer and consumer demands. Primal cut yields, which reflect the body compositions of carcass, could determine the carcass grade and, consequently, command premium prices. Despite its importance, there have been few genome-wide association studies on these traits. This study aimed to identify genomic regions and putative candidate genes related to 10 primal cut traits, including tenderloin, sirloin, striploin, chuck, brisket, top round, bottom round, shank, flank, and rib in Hanwoo cattle using a single-step Bayesian regression (ssBR) approach. After genomic data quality control, 43,987 SNPs from 3,745 genotyped animals were available, of which 3,467 had phenotypic records for the analyzed traits. A total of 16 significant genomic regions (1-Mb window) were identified, of which five large-effect quantitative trait loci (QTLs) located on chromosomes 6 at 38–39 Mb, 11 at 21–22 Mb, 14 at 6–7 Mb and 26–27 Mb, and 19 at 26–27 Mb were associated with more than one trait, while the remaining 11 QTLs were trait-specific. These significant regions were harbored by 154 genes, among which TOX, FAM184B, SPP1, IBSP, PKD2, SDCBP, PIGY, LCORL, NCAPG, and ABCG2 were noteworthy. Enrichment analysis revealed biological processes and functional terms involved in growth and lipid metabolism, such as growth (GO:0040007), muscle structure development (GO:0061061), skeletal system development (GO:0001501), animal organ development (GO:0048513), lipid metabolic process (GO:0006629), response to lipid (GO:0033993), metabolic pathways (bta01100), focal adhesion (bta04510), ECM–receptor interaction (bta04512), fat digestion and absorption (bta04975), and Rap1 signaling pathway (bta04015) being the most significant for the carcass primal cut traits. Thus, identification of quantitative trait loci regions and plausible candidate genes will aid in a better understanding of the genetic and biological mechanisms regulating carcass primal cut yields.

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Single-step genome-wide association studies (GWAS) and post-GWAS analyses to identify genomic regions and candidate genes for milk yield in Brazilian Girolando cattle

Journal of Dairy Science ◽

10.3168/jds.2019-17890 ◽

2020 ◽

Vol 103 (11) ◽

pp. 10347-10360

Author(s):

Pamela I. Otto ◽

Simone E.F. Guimarães ◽

Mario P.L. Calus ◽

Jeremie Vandenplas ◽

Marco A. Machado ◽

...

Keyword(s):

Candidate Genes ◽

Milk Yield ◽

Association Studies ◽

Single Step ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Genomic Regions

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A meta-analysis of genome-wide association studies for average daily gain and lean meat percentage in two Duroc pig populations

BMC Genomics ◽

10.1186/s12864-020-07288-1 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Shenping Zhou ◽

Rongrong Ding ◽

Fanming Meng ◽

Xingwang Wang ◽

Zhanwei Zhuang ◽

...

Keyword(s):

Candidate Genes ◽

Growth And Development ◽

Genetic Architecture ◽

Association Studies ◽

Meta Analysis ◽

Average Daily Gain ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Daily Gain

Abstract Background Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs. Results In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development. Conclusions We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.

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Integration of a single-step genome-wide association study with a multi-tissue transcriptome analysis provides novel insights into the genetic basis of wool and weight traits in sheep

Genetics Selection Evolution ◽

10.1186/s12711-021-00649-8 ◽

2021 ◽

Vol 53 (1) ◽

Author(s):

Bingru Zhao ◽

Hanpeng Luo ◽

Xixia Huang ◽

Chen Wei ◽

Jiang Di ◽

...

Keyword(s):

Association Study ◽

Candidate Genes ◽

Genetic Improvement ◽

Genome Wide Association Study ◽

Growth Traits ◽

Fibre Diameter ◽

Single Step ◽

Genome Wide Association ◽

Six Traits ◽

Genome Wide

Abstract Background Genetic improvement of wool and growth traits is a major goal in the sheep industry, but their underlying genetic architecture remains elusive. To improve our understanding of these mechanisms, we conducted a weighted single-step genome-wide association study (WssGWAS) and then integrated the results with large-scale transcriptome data for five wool traits and one growth trait in Merino sheep: mean fibre diameter (MFD), coefficient of variation of the fibre diameter (CVFD), crimp number (CN), mean staple length (MSL), greasy fleece weight (GFW), and live weight (LW). Results Our dataset comprised 7135 individuals with phenotype data, among which 1217 had high-density (HD) genotype data (n = 372,534). The genotypes of 707 of these animals were imputed from the Illumina Ovine single nucleotide polymorphism (SNP) 54 BeadChip to the HD Array. The heritability of these traits ranged from 0.05 (CVFD) to 0.36 (MFD), and between-trait genetic correlations ranged from − 0.44 (CN vs. LW) to 0.77 (GFW vs. LW). By integrating the GWAS signals with RNA-seq data from 500 samples (representing 87 tissue types from 16 animals), we detected tissues that were relevant to each of the six traits, e.g. liver, muscle and the gastrointestinal (GI) tract were the most relevant tissues for LW, and leukocytes and macrophages were the most relevant cells for CN. For the six traits, 54 quantitative trait loci (QTL) were identified covering 81 candidate genes on 21 ovine autosomes. Multiple candidate genes showed strong tissue-specific expression, e.g. BNC1 (associated with MFD) and CHRNB1 (LW) were specifically expressed in skin and muscle, respectively. By conducting phenome-wide association studies (PheWAS) in humans, we found that orthologues of several of these candidate genes were significantly (FDR < 0.05) associated with similar traits in humans, e.g. BNC1 was significantly associated with MFD in sheep and with hair colour in humans, and CHRNB1 was significantly associated with LW in sheep and with body mass index in humans. Conclusions Our findings provide novel insights into the biological and genetic mechanisms underlying wool and growth traits, and thus will contribute to the genetic improvement and gene mapping of complex traits in sheep.

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E-MAGMA: an eQTL-informed method to identify risk genes using genome-wide association study summary statistics

Bioinformatics ◽

10.1093/bioinformatics/btab115 ◽

2021 ◽

Author(s):

Zachary F Gerring ◽

Angela Mina-Vargas ◽

Eric R Gamazon ◽

Eske M Derks

Keyword(s):

Genome Wide Association ◽

Chromosome 1 ◽

Supplementary Information ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Tissue Specific ◽

Complex Disorders ◽

Risk Variants ◽

Genome Wide ◽

Causal Genes

Abstract Motivation Genome-wide association studies have successfully identified multiple independent genetic loci that harbour variants associated with human traits and diseases, but the exact causal genes are largely unknown. Common genetic risk variants are enriched in non-protein-coding regions of the genome and often affect gene expression (expression quantitative trait loci, eQTL) in a tissue-specific manner. To address this challenge, we developed a methodological framework, E-MAGMA, which converts genome-wide association summary statistics into gene-level statistics by assigning risk variants to their putative genes based on tissue-specific eQTL information. Results We compared E-MAGMA to three eQTL informed gene-based approaches using simulated phenotype data. Phenotypes were simulated based on eQTL reference data using GCTA for all genes with at least one eQTL at chromosome 1. We performed 10 simulations per gene. The eQTL-h2 (i.e., the proportion of variation explained by the eQTLs) was set at 1%, 2%, and 5%. We found E-MAGMA outperforms other gene-based approaches across a range of simulated parameters (e.g. the number of identified causal genes). When applied to genome-wide association summary statistics for five neuropsychiatric disorders, E-MAGMA identified more putative candidate causal genes compared to other eQTL-based approaches. By integrating tissue-specific eQTL information, these results show E-MAGMA will help to identify novel candidate causal genes from genome-wide association summary statistics and thereby improve the understanding of the biological basis of complex disorders. Availability A tutorial and input files are made available in a github repository: https://github.com/eskederks/eMAGMA-tutorial. Supplementary information Supplementary data are available at Bioinformatics online.

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Identification of Novel Genome-Wide Associations for Oral Inflammatory Traits

10.21203/rs.3.rs-104530/v1 ◽

2020 ◽

Author(s):

Yanjiao Jin ◽

Jie Yang ◽

Shuyue Zhang ◽

Jin Li ◽

Songlin Wang

Keyword(s):

Candidate Genes ◽

Immune Regulation ◽

Functional Annotation ◽

Inflammatory Diseases ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Protein Protein Interaction ◽

Genome Wide ◽

Causal Variants

Abstract Background: Oral diseases impact the majority of the world’s population. The following traits are common in oral inflammatory diseases: mouth ulcers, painful gums, bleeding gums, loose teeth, and toothache. Despite the prevalence of genome-wide association studies, the associations between these traits and common genomic variants, and whether pleiotropic loci are shared by some of these traits remain poorly understood. Methods: In this work, we conducted multi-trait joint analyses based on the summary statistics of genome-wide association studies of these five oral inflammatory traits from the UK Biobank, each of which is comprised of over 10,000 cases and over 300,000 controls. We estimated the genetic correlations between the five traits. We conducted fine-mapping and functional annotation based on multi-omics data to better understand the biological functions of the potential causal variants at each locus. To identify the pathways in which the candidate genes were mainly involved, we applied gene-set enrichment analysis, and further performed protein-protein interaction (PPI) analyses.Results: We identified 39 association signals that surpassed genome-wide significance, including three that were shared between two or more oral inflammatory traits, consistent with a strong correlation. Among these genome-wide significant loci, two were novel for both painful gums and toothache. We performed fine-mapping and identified causal variants at each novel locus. Further functional annotation based on multi-omics data suggested IL10 and IL12A/TRIM59 as potential candidate genes at the novel pleiotropic loci, respectively. Subsequent analyses of pathway enrichment and protein-protein interaction networks suggested the involvement of candidate genes at genome-wide significant loci in immune regulation.Conclusions: Our results highlighted the importance of immune regulation in the pathogenesis of oral inflammatory diseases. Some common immune-related pleiotropic loci or genetic variants are shared by multiple oral inflammatory traits. These findings will be beneficial for risk prediction, prevention, and therapy of oral inflammatory diseases.

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Genome-wide association study reveals candidate genes for flowering time in cowpea (Vigna unguiculata [L.] Walp)

10.1101/2021.04.01.438123 ◽

2021 ◽

Author(s):

Dev Paudel ◽

Rocheteau Dareus ◽

Julia Rosenwald ◽

Maria Munoz-Amatriain ◽

Esteban Rios

Keyword(s):

Flowering Time ◽

Candidate Genes ◽

Vigna Unguiculata ◽

Association Studies ◽

Snp Markers ◽

Genome Wide Association ◽

Human Consumption ◽

Phenotypic Variance ◽

Genome Wide Association Studies ◽

Genome Wide

Cowpea (Vigna unguiculata [L.] Walp., diploid, 2n = 22) is a major crop used as a protein source for human consumption as well as a quality feed for livestock. It is drought and heat tolerant and has been bred to develop varieties that are resilient to changing climates. Plant adaptation to new climates and their yield are strongly affected by flowering time. Therefore, understanding the genetic basis of flowering time is critical to advance cowpea breeding. The aim of this study was to perform genome-wide association studies (GWAS) to identify marker trait associations for flowering time in cowpea using single nucleotide polymorphism (SNP) markers. A total of 367 accessions from a cowpea mini-core collection were evaluated in Ft. Collins, CO in 2019 and 2020, and 292 accessions were evaluated in Citra, FL in 2018. These accessions were genotyped using the Cowpea iSelect Consortium Array that contained 51,128 SNPs. GWAS revealed seven reliable SNPs for flowering time that explained 8-12% of the phenotypic variance. Candidate genes including FT, GI, CRY2, LSH3, UGT87A2, LIF2, and HTA9 that are associated with flowering time were identified for the significant SNP markers. Further efforts to validate these loci will help to understand their role in flowering time in cowpea, and it could facilitate the transfer of some of this knowledge to other closely related legume species.

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Current knowledge in hypertension genetics: mosaic theory, candidate genes and genome-wide association studies

Arterial’naya Gipertenziya (Arterial Hypertension) ◽

10.18705/1607-419x-2020-26-5-490-500 ◽

2020 ◽

Vol 26 (5) ◽

pp. 490-500

Author(s):

A. O. Konradi

Keyword(s):

Candidate Genes ◽

High Performance ◽

New Technologies ◽

Current Knowledge ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Modern Approach ◽

Genome Wide

The article reviews monogenic forms of hypertension, data on the role of heredity of essential hypertension and candidate genes, as well as genome-wide association studies. Modern approach for the role of genetics is driven by implementation of new technologies and their productivity. High performance speed of new technologies like genome-wide association studies provide data for better knowledge of genetic markers of hypertension. The major goal nowadays for research is to reveal molecular pathways of blood pressure regulation, which can help to move from populational to individual level of understanding of pathogenesis and treatment targets.

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Genome-Wide Association Studies of 39 Seed Yield-Related Traits in Sesame (Sesamum indicum L.)

International Journal of Molecular Sciences ◽

10.3390/ijms19092794 ◽

2018 ◽

Vol 19 (9) ◽

pp. 2794 ◽

Cited By ~ 5

Author(s):

Rong Zhou ◽

Komivi Dossa ◽

Donghua Li ◽

Jingyin Yu ◽

Jun You ◽

...

Keyword(s):

Candidate Genes ◽

Seed Yield ◽

Association Studies ◽

Oil Quality ◽

Genome Wide Association ◽

Oilseed Crop ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Highly Correlated ◽

Capsule Size

Sesame is poised to become a major oilseed crop owing to its high oil quality and adaptation to various ecological areas. However, the seed yield of sesame is very low and the underlying genetic basis is still elusive. Here, we performed genome-wide association studies of 39 seed yield-related traits categorized into five major trait groups, in three different environments, using 705 diverse lines. Extensive variation was observed for the traits with capsule size, capsule number and seed size-related traits, found to be highly correlated with seed yield indexes. In total, 646 loci were significantly associated with the 39 traits (p < 10−7) and resolved to 547 quantitative trait loci QTLs. We identified six multi-environment QTLs and 76 pleiotropic QTLs associated with two to five different traits. By analyzing the candidate genes for the assayed traits, we retrieved 48 potential genes containing significant functional loci. Several homologs of these candidate genes in Arabidopsis are described to be involved in seed or biomass formation. However, we also identified novel candidate genes, such as SiLPT3 and SiACS8, which may control capsule length and capsule number traits. Altogether, we provided the highly-anticipated basis for research on genetics and functional genomics towards seed yield improvement in sesame.

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