scholarly journals Trait-specific Selection Signature Detection Reveals Novel Loci of Meat Quality in Large White Pigs

2021 ◽  
Vol 12 ◽  
Author(s):  
Yu Shen ◽  
Haiyan Wang ◽  
Jiahao Xie ◽  
Zixuan Wang ◽  
Yunlong Ma
Keyword(s):  
Candidate Genes ◽  
Meat Quality ◽  
Genetic Improvement ◽  
Genetic Basis ◽  
Muscle Development ◽  
Fixation Index ◽  
Quality Traits ◽  
Selection Signatures ◽  
Meat Quality Traits ◽  
Improvement Programs

In past decades, meat quality traits have been shaped by human-driven selection in the process of genetic improvement programs. Exploring the potential genetic basis of artificial selection and mapping functional candidate genes for economic traits are of great significance in genetic improvement of pigs. In this study, we focus on investigating the genetic basis of five meat quality traits, including intramuscular fat content (IMF), drip loss, water binding capacity, pH at 45 min (pH45min), and ultimate pH (pH24h). Through making phenotypic gradient differential population pairs, Wright’s fixation index (FST) and the cross-population extended haplotype homozogysity (XPEHH) were applied to detect selection signatures for these five traits. Finally, a total of 427 and 307 trait-specific selection signatures were revealed by FST and XPEHH, respectively. Further bioinformatics analysis indicates that some genes, such as USF1, NDUFS2, PIGM, IGSF8, CASQ1, and ACBD6, overlapping with the trait-specific selection signatures are responsible for the phenotypes including fat metabolism and muscle development. Among them, a series of promising trait-specific selection signatures that were detected in the high IMF subpopulation are located in the region of 93544042-95179724bp on SSC4, and the genes harboring in this region are all related to lipids and muscle development. Overall, these candidate genes of meat quality traits identified in this analysis may provide some fundamental information for further exploring the genetic basis of this complex trait.

scholarly journals Phenotypic and expression QTL integration allows the refinement of loci associated with pig carcass and meat quality traits

2021 ◽  
Author(s):  
Frédéric Hérault ◽  
Annie Vincent ◽  
Ando Yoanne Randriamanantena ◽  
Marie Damon ◽  
Pierre Cherel ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Meat Quality ◽  
Calcium Homeostasis ◽  
Complex Traits ◽  
Regulatory Networks ◽  
Muscle Development ◽  
Quality Trait ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
Genome Wide

Abstract Background: Many quantitative trait loci (QTLs) affecting pig meat and carcass quality traits have been reported. However, in most cases, the length of these phenotypic QTLs (pQTLs) is large. Hence, the identification of candidate genes and causative polymorphisms hidden behind those pQTLs remains a difficult task. Combining gene expression, phenotype and genotype data in an integrative genomics approach may help to identify regulatory networks and pathways underlying such complex traits. In the present study, we used genome-wide association study (GWAS) and linkage disequilibrium linkage analysis (LDLA) approaches to identify longissimus muscle (LM) and semimembranosus muscle (SM) expression QTLs (eQTLs). The locations of these eQTLs were compared to those of pQTLs previously mapped in the same population of commercial-type pigs. Colocalized eQTLs/pQTLs could help to identify candidate genes and pathways involved in pig carcass and meat quality trait determination. Results: Both approaches led us to identify 1,253 and 1,109 genome-wide significant eQTLs for LM and SM, respectively. We identified only one common eQTL between the two muscles and a few significant common eQTLs between methodologies : 16 in SM and 1 in LM. A total of 192 overlapping locations were identified between eQTLs and pQTLs. Colocalization highlighted some genes involved in muscle development, adipogenic processes or ion calcium homeostasis. These eQTLs allowed us to refine previously identified pQTLs related to carcass and meat quality traits. However, in most cases, the refined loci were still large and contained several coding and noncoding genes. Conclusions: Our results shed light on the muscle-specific genetic control governing mRNA expression and hence controlling the development of pig carcass and meat quality traits. Moreover, colocations between eQTLs and pQTLs implicated genes potentially involved in muscle development, adipogenic processes or ion calcium homeostasis in the pathways governing these traits. Finally, our results allowed us to refine QTLs controlling meat quality traits and to highlight the possible involvement of long noncoding RNAs in the architecture of regulatory networks governing complex traits such as pig carcass and meat quality traits.

scholarly journals Phenotypic and genetic variation of ultraviolet–visible-infrared spectral wavelengths of bovine meat

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giovanni Bittante ◽  
Simone Savoia ◽  
Alessio Cecchinato ◽  
Sara Pegolo ◽  
Andrea Albera
Keyword(s):  
Meat Quality ◽  
Genetic Improvement ◽  
Near Infrared ◽  
Infrared Region ◽  
Phenotypic Variance ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
Infrared Spectral ◽  
Portable Spectrometers ◽  
Absorbance Spectra

AbstractSpectroscopic predictions can be used for the genetic improvement of meat quality traits in cattle. No information is however available on the genetics of meat absorbance spectra. This research investigated the phenotypic variation and the heritability of meat absorbance spectra at individual wavelengths in the ultraviolet–visible and near-infrared region (UV–Vis-NIR) obtained with portable spectrometers. Five spectra per instrument were taken on the ribeye surface of 1185 Piemontese young bulls from 93 farms (13,182 Herd-Book pedigree relatives). Linear animal model analyses of 1481 single-wavelengths from UV–Vis-NIRS and 125 from Micro-NIRS were carried out separately. In the overlapping regions, the proportions of phenotypic variance explained by batch/date of slaughter (14 ± 6% and 17 ± 7%,), rearing farm (6 ± 2% and 5 ± 3%), and the residual variances (72 ± 10% and 72 ± 5%) were similar for the UV–Vis-NIRS and Micro-NIRS, but additive genetics (7 ± 2% and 4 ± 2%) and heritability (8.3 ± 2.3% vs 5.1 ± 0.6%) were greater with the Micro-NIRS. Heritability was much greater for the visible fraction (25.2 ± 11.4%), especially the violet, blue and green colors, than for the NIR fraction (5.0 ± 8.0%). These results allow a better understanding of the possibility of using the absorbance of visible and infrared wavelengths correlated with meat quality traits for the genetic improvement in beef cattle.

scholarly journals Genome-wide analysis of expression QTL (eQTL) and allele-specific expression (ASE) in pig muscle identifies candidate genes for meat quality traits

2020 ◽  
Vol 52 (1) ◽  
Author(s):  
Yan Liu ◽  
Xiaolei Liu ◽  
Zhiwei Zheng ◽  
Tingting Ma ◽  
Ying Liu ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Meat Quality ◽  
Quality Traits ◽  
Q Value ◽  
Specific Expression ◽  
Allele Specific Expression ◽  
Meat Quality Traits ◽  
Genome Wide ◽  
A Genome ◽  
Allele Specific

Abstract Background Genetic analysis of gene expression level is a promising approach for characterizing candidate genes that are involved in complex economic traits such as meat quality. In the present study, we conducted expression quantitative trait loci (eQTL) and allele-specific expression (ASE) analyses based on RNA-sequencing (RNAseq) data from the longissimus muscle of 189 Duroc × Luchuan crossed pigs in order to identify some candidate genes for meat quality traits. Results Using a genome-wide association study based on a mixed linear model, we identified 7192 cis-eQTL corresponding to 2098 cis-genes (p ≤ 1.33e-3, FDR ≤ 0.05) and 6400 trans-eQTL corresponding to 863 trans-genes (p ≤ 1.13e-6, FDR ≤ 0.05). ASE analysis using RNAseq SNPs identified 9815 significant ASE-SNPs in 2253 unique genes. Integrative analysis between the cis-eQTL and ASE target genes identified 540 common genes, including 33 genes with expression levels that were correlated with at least one meat quality trait. Among these 540 common genes, 63 have been reported previously as candidate genes for meat quality traits, such as PHKG1 (q-value = 1.67e-6 for the leading SNP in the cis-eQTL analysis), NUDT7 (q-value = 5.67e-13), FADS2 (q-value = 8.44e-5), and DGAT2 (q-value = 1.24e-3). Conclusions The present study confirmed several previously published candidate genes and identified some novel candidate genes for meat quality traits via eQTL and ASE analyses, which will be useful to prioritize candidate genes in further studies.

scholarly journals An Integrative Analysis of Transcriptome and GWAS Data to Identify Potential Candidate Genes Influencing Meat Quality Traits in Pigs

2021 ◽  
Vol 12 ◽  
Author(s):  
Xianxian Liu ◽  
Junjie Zhang ◽  
Xinwei Xiong ◽  
Congying Chen ◽  
Yuyun Xing ◽  
...  
Keyword(s):  
Gene Expression ◽  
Candidate Genes ◽  
Meat Quality ◽  
Integrative Analysis ◽  
Potential Candidate ◽  
Quality Traits ◽  
Eqtl Mapping ◽  
Meat Quality Traits ◽  
Genome Wide ◽  
A Genome

Understanding the genetic factors behind meat quality traits is of great significance to animal breeding and production. We previously conducted a genome-wide association study (GWAS) for meat quality traits in a White Duroc × Erhualian F2 pig population using Illumina porcine 60K SNP data. Here, we further investigate the functional candidate genes and their network modules associated with meat quality traits by integrating transcriptomics and GWAS information. Quantitative trait transcript (QTT) analysis, gene expression QTL (eQTL) mapping, and weighted gene co-expression network analysis (WGCNA) were performed using the digital gene expression (DGE) data from 493 F2 pig’s muscle and liver samples. Among the quantified 20,108 liver and 23,728 muscle transcripts, 535 liver and 1,014 muscle QTTs corresponding to 416 and 721 genes, respectively, were found to be significantly (p < 5 × 10−4) correlated with 22 meat quality traits measured on longissiums dorsi muscle (LM) or semimembranosus muscle (SM). Transcripts associated with muscle glycolytic potential (GP) and pH values were enriched for genes involved in metabolic process. There were 42 QTTs (for 32 genes) shared by liver and muscle tissues, of which 10 QTTs represent GP- and/or pH-related genes, such as JUNB, ATF3, and PPP1R3B. Furthermore, a genome-wide eQTL mapping revealed a total of 3,054 eQTLs for all annotated transcripts in muscle (p < 2.08 × 10−5), including 1,283 cis-eQTLs and 1771 trans-eQTLs. In addition, WGCNA identified five modules relevant to glycogen metabolism pathway and highlighted the connections between variations in meat quality traits and genes involved in energy process. Integrative analysis of GWAS loci, eQTL, and QTT demonstrated GALNT15/GALNTL2 and HTATIP2 as strong candidate genes for drip loss and pH drop from postmortem 45 min to 24 h, respectively. Our findings provide valuable insights into the genetic basis of meat quality traits and greatly expand the number of candidate genes that may be valuable for future functional analysis and genetic improvement of meat quality.

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