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Everman ER, Macdonald SJ. Gene expression variation underlying tissue-specific responses to copper stress in Drosophila melanogaster. G3 (BETHESDA, MD.) 2024; 14:jkae015. [PMID: 38262701 PMCID: PMC11021028 DOI: 10.1093/g3journal/jkae015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/04/2024] [Accepted: 01/08/2024] [Indexed: 01/25/2024]
Abstract
Copper is one of a handful of biologically necessary heavy metals that is also a common environmental pollutant. Under normal conditions, copper ions are required for many key physiological processes. However, in excess, copper results in cell and tissue damage ranging in severity from temporary injury to permanent neurological damage. Because of its biological relevance, and because many conserved copper-responsive genes respond to nonessential heavy metal pollutants, copper resistance in Drosophila melanogaster is a useful model system with which to investigate the genetic control of the heavy metal stress response. Because heavy metal toxicity has the potential to differently impact specific tissues, we genetically characterized the control of the gene expression response to copper stress in a tissue-specific manner in this study. We assessed the copper stress response in head and gut tissue of 96 inbred strains from the Drosophila Synthetic Population Resource using a combination of differential expression analysis and expression quantitative trait locus mapping. Differential expression analysis revealed clear patterns of tissue-specific expression. Tissue and treatment specific responses to copper stress were also detected using expression quantitative trait locus mapping. Expression quantitative trait locus associated with MtnA, Mdr49, Mdr50, and Sod3 exhibited both genotype-by-tissue and genotype-by-treatment effects on gene expression under copper stress, illuminating tissue- and treatment-specific patterns of gene expression control. Together, our data build a nuanced description of the roles and interactions between allelic and expression variation in copper-responsive genes, provide valuable insight into the genomic architecture of susceptibility to metal toxicity, and highlight candidate genes for future functional characterization.
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Affiliation(s)
- Elizabeth R Everman
- School of Biological Sciences, The University of Oklahoma, 730 Van Vleet Oval, Norman, OK 73019, USA
| | - Stuart J Macdonald
- Molecular Biosciences, University of Kansas, 1200 Sunnyside Ave, Lawrence, KS 66045, USA
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2
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Freitas FAO, Brito LF, Fanalli SL, Gonçales JL, da Silva BPM, Durval MC, Ciconello FN, de Oliveira CS, Nascimento LE, Gervásio IC, Gomes JD, Moreira GCM, Silva-Vignato B, Coutinho LL, de Almeida VV, Cesar ASM. Identification of eQTLs using different sets of single nucleotide polymorphisms associated with carcass and body composition traits in pigs. BMC Genomics 2024; 25:14. [PMID: 38166730 PMCID: PMC10759680 DOI: 10.1186/s12864-023-09863-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Mapping expression quantitative trait loci (eQTLs) in skeletal muscle tissue in pigs is crucial for understanding the relationship between genetic variation and phenotypic expression of carcass traits in meat animals. Therefore, the primary objective of this study was to evaluate the impact of different sets of single nucleotide polymorphisms (SNP), including scenarios removing SNPs pruned for linkage disequilibrium (LD) and SNPs derived from SNP chip arrays and RNA-seq data from liver, brain, and skeletal muscle tissues, on the identification of eQTLs in the Longissimus lumborum tissue, associated with carcass and body composition traits in Large White pigs. The SNPs identified from muscle mRNA were combined with SNPs identified in the brain and liver tissue transcriptomes, as well as SNPs from the GGP Porcine 50 K SNP chip array. Cis- and trans-eQTLs were identified based on the skeletal muscle gene expression level, followed by functional genomic analyses and statistical associations with carcass and body composition traits in Large White pigs. RESULTS The number of cis- and trans-eQTLs identified across different sets of SNPs (scenarios) ranged from 261 to 2,539 and from 29 to 13,721, respectively. Furthermore, 6,180 genes were modulated by eQTLs in at least one of the scenarios evaluated. The eQTLs identified were not significantly associated with carcass and body composition traits but were significantly enriched for many traits in the "Meat and Carcass" type QTL. The scenarios with the highest number of cis- (n = 304) and trans- (n = 5,993) modulated genes were the unpruned and LD-pruned SNP set scenarios identified from the muscle transcriptome. These genes include 84 transcription factor coding genes. CONCLUSIONS After LD pruning, the set of SNPs identified based on the transcriptome of the skeletal muscle tissue of pigs resulted in the highest number of genes modulated by eQTLs. Most eQTLs are of the trans type and are associated with genes influencing complex traits in pigs, such as transcription factors and enhancers. Furthermore, the incorporation of SNPs from other genomic regions to the set of SNPs identified in the porcine skeletal muscle transcriptome contributed to the identification of eQTLs that had not been identified based on the porcine skeletal muscle transcriptome alone.
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Affiliation(s)
- Felipe André Oliveira Freitas
- Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil
- Department of Animal Sciences, Purdue University, West Lafayette, IN, 47907, USA
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN, 47907, USA
- Faculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635- 900, SP, Brazil
| | - Simara Larissa Fanalli
- Faculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635- 900, SP, Brazil
| | - Janaína Lustosa Gonçales
- Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil
| | | | - Mariah Castro Durval
- Faculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635- 900, SP, Brazil
| | - Fernanda Nery Ciconello
- Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil
| | | | | | - Izally Carvalho Gervásio
- Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil
| | - Julia Dezen Gomes
- Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil
| | | | - Bárbara Silva-Vignato
- Faculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635- 900, SP, Brazil
| | - Luiz Lehmann Coutinho
- Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil
| | - Vivian Vezzoni de Almeida
- College of Veterinary Medicine and Animal Science, Federal University of Goiás, Goiânia, 74001-970, GO, Brazil
| | - Aline Silva Mello Cesar
- Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil.
- Faculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635- 900, SP, Brazil.
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3
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Zhao W, Cai Z, Wei C, Ma X, Yu B, Fu X, Zhang T, Gu Y, Zhang J. Functional identification of PGM1 in the regulating development and depositing of inosine monophosphate specific for myoblasts. Front Vet Sci 2023; 10:1276582. [PMID: 38164393 PMCID: PMC10758172 DOI: 10.3389/fvets.2023.1276582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 11/21/2023] [Indexed: 01/03/2024] Open
Abstract
Background Inosine monophosphate (IMP) is naturally present in poultry muscle and plays a key role in improving meat flavour. However, IMP deposition is regulated by numerous genes and complex molecular networks. In order to excavate key candidate genes that may regulate IMP synthesis, we performed proteome and metabolome analyses on the leg muscle, compared to the breast muscle control of 180-day-old Jingyuan chickens (hens), which had different IMP content. The key candidate genes identified by a differential analysis were verified to be associated with regulation of IMP-specific deposition. Results The results showed that the differentially expressed (DE) proteins and metabolites jointly involve 14 metabolic pathways, among which the purine metabolic pathway closely related to IMP synthesis and metabolism is enriched with four DE proteins downregulated (with higher expression in breast muscles than in leg muscles), including adenylate kinase 1 (AK1), adenosine monophosphate deaminase 1 (AMPD1), pyruvate kinase muscle isoenzyme 2 (PKM2) and phosphoglucomutase 1 (PGM1), six DE metabolites, Hypoxanthine, Guanosine, L-Glutamine, AICAR, AMP and Adenylsuccinic acid. Analysis of PGM1 gene showed that the high expression of PGM1 promoted the proliferation and differentiation of myoblasts and inhibited the apoptosis of myoblasts. ELISA tests have shown that PGM1 reduced adenosine triphosphate (ATP) and IMP and uric acid (UA), while enhancing the biosynthesis of hypoxanthine (HX). In addition, up-regulation of PGM1 inhibited the expression of purine metabolism pathway related genes, and promoted the IMP de novo and salvage synthesis pathways. Conclusion This study preliminarily explored the mechanism of action of PGM1 in regulating the growth and development of myoblasts and specific IMP deposition in Jingyuan chickens, which provided certain theoretical basis for the development and utilization of excellent traits in Jingyuan chickens.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Juan Zhang
- College of Animal Science and Technology, Ningxia University, Yinchuan, China
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4
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Li LY, Xiao SJ, Tu JM, Zhang ZK, Zheng H, Huang LB, Huang ZY, Yan M, Liu XD, Guo YM. A further survey of the quantitative trait loci affecting swine body size and carcass traits in five related pig populations. Anim Genet 2021; 52:621-632. [PMID: 34182604 DOI: 10.1111/age.13112] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/16/2021] [Indexed: 12/13/2022]
Abstract
Breeding for good meat quality performance while maintaining large body size and desirable carcass traits has been the major challenge for modern swine selective breeding. To address this goal, in the present work we studied five related populations produced by two commercial breeds (Berkshire and Duroc) and two Chinese breeds (Licha black pig and Lulai black pig). A single-trait GWAS performed on 20 body size and carcass traits using a self-developed China Chip-1 porcine SNP50K BeadChip identified 11 genome-wide significant QTL on nine chromosomes and 22 suggestive QTL on 15 chromosomes. For the 11 genome-wide significant QTL, eight were detected in at least two populations, and the rest were population-specific and only mapped in Shanxia black pig. Most of the genome-wide significant QTL were pleiotropic; for example, the QTL around 75.65 Mb on SSC4 was associated with four traits at genome-wide significance level. After screening the genes within 50 kb of the top SNP for each genome-wide significant QTL, NR6A1 and VRTN were chosen as candidate genes for vertebrae number; PLAG1 and BMP2 were identified as candidate genes for body size; and MC4R was the strong candidate gene for body weight. The four genes have been reported as candidates for thoracic vertebrae number, lumbar vertebrae number, carcass length and body weight respectively in previous studies. The effects of VRTN on thoracic vertebrae number, carcass length and body length have been verified in Shanxia black pig. Therefore, the VRTN genotype could be used in gene-assisted selection, and this could accelerate genetic improvement of body size and carcass traits in Shanxia black pig.
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Affiliation(s)
- L-Y Li
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - S-J Xiao
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - J-M Tu
- Jiangxi Shanxia Swine Genetic Investment Company Limited, Dingnan, Jiangxi, 341900, China
| | - Z-K Zhang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - H Zheng
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China.,Jiangxi Shanxia Swine Genetic Investment Company Limited, Dingnan, Jiangxi, 341900, China
| | - L-B Huang
- Jiangxi Shanxia Swine Genetic Investment Company Limited, Dingnan, Jiangxi, 341900, China
| | - Z-Y Huang
- Jiangxi Shanxia Swine Genetic Investment Company Limited, Dingnan, Jiangxi, 341900, China
| | - M Yan
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - X-D Liu
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
| | - Y-M Guo
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, 330045, China
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5
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Daza KR, Velez-Irizarry D, Casiró S, Steibel JP, Raney NE, Bates RO, Ernst CW. Integrated Genome-Wide Analysis of MicroRNA Expression Quantitative Trait Loci in Pig Longissimus Dorsi Muscle. Front Genet 2021; 12:644091. [PMID: 33859669 PMCID: PMC8042294 DOI: 10.3389/fgene.2021.644091] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Accepted: 02/24/2021] [Indexed: 01/19/2023] Open
Abstract
Determining mechanisms regulating complex traits in pigs is essential to improve the production efficiency of this globally important protein source. MicroRNAs (miRNAs) are a class of non-coding RNAs known to post-transcriptionally regulate gene expression affecting numerous phenotypes, including those important to the pig industry. To facilitate a more comprehensive understanding of the regulatory mechanisms controlling growth, carcass composition, and meat quality phenotypes in pigs, we integrated miRNA and gene expression data from longissimus dorsi muscle samples with genotypic and phenotypic data from the same animals. We identified 23 miRNA expression Quantitative Trait Loci (miR-eQTL) at the genome-wide level and examined their potential effects on these important production phenotypes through miRNA target prediction, correlation, and colocalization analyses. One miR-eQTL miRNA, miR-874, has target genes that colocalize with phenotypic QTL for 12 production traits across the genome including backfat thickness, dressing percentage, muscle pH at 24 h post-mortem, and cook yield. The results of our study reveal genomic regions underlying variation in miRNA expression and identify miRNAs and genes for future validation of their regulatory effects on traits of economic importance to the global pig industry.
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Affiliation(s)
- Kaitlyn R Daza
- Department of Animal Science, Michigan State University, East Lansing, MI, United States
| | - Deborah Velez-Irizarry
- Department of Animal Science, Michigan State University, East Lansing, MI, United States
| | - Sebastian Casiró
- Department of Animal Science, Michigan State University, East Lansing, MI, United States
| | - Juan P Steibel
- Department of Animal Science, Michigan State University, East Lansing, MI, United States
| | - Nancy E Raney
- Department of Animal Science, Michigan State University, East Lansing, MI, United States
| | - Ronald O Bates
- Department of Animal Science, Michigan State University, East Lansing, MI, United States
| | - Catherine W Ernst
- Department of Animal Science, Michigan State University, East Lansing, MI, United States
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6
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Rafiepour M, Ebrahimie E, Vahidi MF, Salekdeh GH, Niazi A, Dadpasand M, Liang D, Si J, Ding X, Han J, Zhang Y, Qanbari S. Whole-Genome Resequencing Reveals Adaptation Prior to the Divergence of Buffalo Subspecies. Genome Biol Evol 2020; 13:5976760. [PMID: 33179728 DOI: 10.1093/gbe/evaa231] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/28/2020] [Indexed: 01/30/2023] Open
Abstract
The application of high-throughput genotyping or sequencing data helps us to understand the genomic response to natural and artificial selection. In this study, we scanned the genomes of five indigenous buffalo populations belong to three recognized breeds, adapted to different geographical and agro-ecological zones in Iran, to unravel the extent of genomic diversity and to localize genomic regions and genes underwent past selection. A total of 46 river buffalo whole genomes, from West and East Azerbaijan, Gilan, Mazandaran, and Khuzestan provinces, were resequenced. Our sequencing data reached to a coverage above 99% of the river buffalo reference genome and an average read depth around 9.2× per sample. We identified 20.55 million SNPs, including 63,097 missense, 707 stop-gain, and 159 stop-loss mutations that might have functional consequences. Genomic diversity analyses showed modest structuring among Iranian buffalo populations following frequent gene flow or admixture in the recent past. Evidence of positive selection was investigated using both differentiation (Fst) and fixation (Pi) metrics. Analysis of fixation revealed three genomic regions in all three breeds with aberrant polymorphism contents on BBU2, 20, and 21. Fixation signal on BBU2 overlapped with the OCA2-HERC2 genes, suggestive of adaptation to UV exposure through pigmentation mechanism. Further validation using resequencing data from other five bovine species as well as the Axiom Buffalo Genotyping Array 90K data of river and swamp buffaloes indicated that these fixation signals persisted across river and swamp buffaloes and extended to taurine cattle, implying an ancient evolutionary event occurred before the speciation of buffalo and taurine cattle. These results contributed to our understanding of major genetic switches that took place during the evolution of modern buffaloes.
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Affiliation(s)
- Mostafa Rafiepour
- Institute of Biotechnology, School of Agriculture, Shiraz University, Iran.,Department of System Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.,Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, Agricultural University, Beijing, China
| | - Esmaeil Ebrahimie
- Institute of Biotechnology, School of Agriculture, Shiraz University, Iran.,Genomics Research Platform, School of Life Sciences, Melbourne, Victoria, Australia.,School of Animal and Veterinary Sciences, The University of Adelaide, South Australia, Australia
| | - Mohammad Farhad Vahidi
- Department of Animal Biotechnology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Ghasem Hosseini Salekdeh
- Department of System Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Ali Niazi
- Institute of Biotechnology, School of Agriculture, Shiraz University, Iran
| | - Mohammad Dadpasand
- Department of Animal Science, School of Agriculture, Shiraz University, Iran
| | - Dong Liang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, Agricultural University, Beijing, China
| | - Jingfang Si
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, Agricultural University, Beijing, China
| | - Xiangdong Ding
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, Agricultural University, Beijing, China
| | - Jianlin Han
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China.,International Livestock Research Institute (ILR), Nairobi, Kenya
| | - Yi Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, Agricultural University, Beijing, China
| | - Saber Qanbari
- Institute of Genetics and Biometry, Leibniz Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
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7
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Liu Y, Liu X, Zheng Z, Ma T, Liu Y, Long H, Cheng H, Fang M, Gong J, Li X, Zhao S, Xu X. Genome-wide analysis of expression QTL (eQTL) and allele-specific expression (ASE) in pig muscle identifies candidate genes for meat quality traits. Genet Sel Evol 2020; 52:59. [PMID: 33036552 PMCID: PMC7547458 DOI: 10.1186/s12711-020-00579-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 09/28/2020] [Indexed: 12/23/2022] Open
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.
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Affiliation(s)
- Yan Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Xiaolei Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Zhiwei Zheng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Tingting Ma
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Ying Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Huan Long
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Huijun Cheng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Ming Fang
- Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture and Rural Affairs, Fisheries College, Jimei University, Xiamen, 361021 China
| | - Jing Gong
- Colleges of Informatics, Huazhong Agricultural University, Wuhan, 430070 China
| | - Xinyun Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
| | - Xuewen Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, 430070 China
- Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Wuhan, 430070 China
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8
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Carmelo VAO, Kadarmideen HN. Genetic variations (eQTLs) in muscle transcriptome and mitochondrial genes, and trans-eQTL molecular pathways in feed efficiency from Danish breeding pigs. PLoS One 2020; 15:e0239143. [PMID: 32941478 PMCID: PMC7498092 DOI: 10.1371/journal.pone.0239143] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 08/31/2020] [Indexed: 01/08/2023] Open
Abstract
Feed efficiency (FE) is a key trait in pig production, as improvement in FE has positive economic and environmental impact. FE is a complex phenotype and testing animals for FE is costly. Therefore, there has been a desire to find functionally relevant single nucleotide polymorphisms (SNPs) as biomarkers, to improve our biological understanding of FE as well as accuracy of genomic prediction for FE. We have performed a cis- and trans- eQTL (expression quantitative trait loci) analysis, in a population of Danbred Durocs (N = 11) and Danbred Landrace (N = 27) using both a linear and ANOVA model based on muscle tissue RNA-seq. We analyzed a total of 1425x19179 or 2.7x107 Gene-SNP combinations in eQTL detection models for FE. The 1425 genes were from RNA-Seq based differential gene expression analyses using 25880 genes related to FE and additionally combined with mitochondrial genes. The 19179 SNPs were from applying stringent quality control and linkage disequilibrium filtering on genotype data using a GGP Porcine HD 70k SNP array. We applied 1000 fold bootstrapping and enrichment analysis to further validate and analyze our detected eQTLs. We identified 13 eQTLs with FDR < 0.1, affecting several genes found in previous studies of commercial pig breeds. Examples include MYO19, CPT1B, ACSL1, IER5L, CPT1A, SUCLA2, CSRNP1, PARK7 and MFF. The bootstrapping results showed statistically significant enrichment (p-value<2.2x10-16) of eQTLs with p-value < 0.01 in both cis and trans-eQTLs. Enrichment analysis of top trans-eQTLs revealed high enrichment for gene categories and gene ontologies associated with genomic context and expression regulation. This included transcription factors (p-value = 1.0x10-13), DNA-binding (GO:0003677, p-value = 8.9x10-14), DNA-binding transcription factor activity (GO:0003700,) nucleus gene (GO:0005634, p-value<2.2x10-16), negative regulation of expression (GO:0010629, p-value<2.2x10-16). These results would be useful for future genome assisted breeding of pigs to improve FE, and in the improved understanding of the functional mechanism of trans eQTLs.
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Affiliation(s)
- Victor A. O. Carmelo
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Haja N. Kadarmideen
- Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
- * E-mail:
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9
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Leal-Gutiérrez JD, Elzo MA, Mateescu RG. Identification of eQTLs and sQTLs associated with meat quality in beef. BMC Genomics 2020; 21:104. [PMID: 32000679 PMCID: PMC6993519 DOI: 10.1186/s12864-020-6520-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 01/20/2020] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Transcription has a substantial genetic control and genetic dissection of gene expression could help us understand the genetic architecture of complex phenotypes such as meat quality in cattle. The objectives of the present research were: 1) to perform eQTL and sQTL mapping analyses for meat quality traits in longissimus dorsi muscle; 2) to uncover genes whose expression is influenced by local or distant genetic variation; 3) to identify expression and splicing hot spots; and 4) to uncover genomic regions affecting the expression of multiple genes. RESULTS Eighty steers were selected for phenotyping, genotyping and RNA-seq evaluation. A panel of traits related to meat quality was recorded in longissimus dorsi muscle. Information on 112,042 SNPs and expression data on 8588 autosomal genes and 87,770 exons from 8467 genes were included in an expression and splicing quantitative trait loci (QTL) mapping (eQTL and sQTL, respectively). A gene, exon and isoform differential expression analysis previously carried out in this population identified 1352 genes, referred to as DEG, as explaining part of the variability associated with meat quality traits. The eQTL and sQTL mapping was performed using a linear regression model in the R package Matrix eQTL. Genotype and year of birth were included as fixed effects, and population structure was accounted for by including as a covariate the first PC from a PCA analysis on genotypic data. The identified QTLs were classified as cis or trans using 1 Mb as the maximum distance between the associated SNP and the gene being analyzed. A total of 8377 eQTLs were identified, including 75.6% trans, 10.4% cis, 12.5% DEG trans and 1.5% DEG cis; while 11,929 sQTLs were uncovered: 66.1% trans, 16.9% DEG trans, 14% cis and 3% DEG cis. Twenty-seven expression master regulators and 13 splicing master regulators were identified and were classified as membrane-associated or cytoskeletal proteins, transcription factors or DNA methylases. These genes could control the expression of other genes through cell signaling or by a direct transcriptional activation/repression mechanism. CONCLUSION In the present analysis, we show that eQTL and sQTL mapping makes possible positional identification of gene and isoform expression regulators.
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Affiliation(s)
| | - Mauricio A Elzo
- Department of Animal Sciences, University of Florida, Gainesville, FL, USA
| | - Raluca G Mateescu
- Department of Animal Sciences, University of Florida, Gainesville, FL, USA
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10
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Bergamaschi M, Maltecca C, Fix J, Schwab C, Tiezzi F. Genome-wide association study for carcass quality traits and growth in purebred and crossbred pigs1. J Anim Sci 2020; 98:skz360. [PMID: 31768540 PMCID: PMC6978898 DOI: 10.1093/jas/skz360] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Accepted: 11/25/2019] [Indexed: 12/29/2022] Open
Abstract
Carcass quality traits such as back fat (BF), loin depth (LD), and ADG are of extreme economic importance for the swine industry. This study aimed to (i) estimate the genetic parameters for such traits and (ii) conduct a single-step genome-wide association study (ssGWAS) to identify genomic regions that affect carcass quality and growth traits in purebred (PB) and three-way crossbred (CB) pigs. A total of 28,497 PBs and 135,768 CBs pigs were phenotyped for BF, LD, and ADG. Of these, 4,857 and 3,532 were genotyped using the Illumina PorcineSNP60K Beadchip. After quality control, 36,328 SNPs were available and were used to perform an ssGWAS. A bootstrap analysis (n = 1,000) and a signal enrichment analysis were performed to declare SNP significance. Genome regions were based on the variance explained by significant 10-SNP sliding windows. Estimates of PB heritability (SE) were 0.42 (0.019) for BF, 0.39 (0.020) for LD, and 0.35 (0.021) for ADG. Estimates of CB heritability were 0.49 (0.042) for BF, 0.27 (0.029) for LD, and 0.12 (0.021) for ADG. Genetic correlations (SE) across the two populations were 0.81 (0.02), 0.79 (0.04), and 0.56 (0.05), for BF, LD, and ADG, respectively. The variance explained by significant regions for each trait in PBs ranged from 1.51% to 1.35% for BF, from 4.02% to 3.18% for LD, and from 2.26% to 1.45% for ADG. In CBs, the variance explained by significant regions ranged from 1.88% to 1.37% for BF, from 1.29% to 1.23% for LD, and from 1.54% to 1.32% for ADG. In this study, we have described regions of the genome that determine carcass quality and growth traits of PB and CB pigs. These results provide evidence that there are overlapping and nonoverlapping regions in the genome influencing carcass quality and growth traits in PBs and three-way CB pigs.
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Affiliation(s)
| | - Christian Maltecca
- Department of Animal Science, North Carolina State University, Raleigh, NC
| | | | | | - Francesco Tiezzi
- Department of Animal Science, North Carolina State University, Raleigh, NC
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11
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González-Prendes R, Mármol-Sánchez E, Quintanilla R, Castelló A, Zidi A, Ramayo-Caldas Y, Cardoso TF, Manunza A, Cánovas Á, Amills M. About the existence of common determinants of gene expression in the porcine liver and skeletal muscle. BMC Genomics 2019; 20:518. [PMID: 31234802 PMCID: PMC6591854 DOI: 10.1186/s12864-019-5889-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Accepted: 06/07/2019] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND The comparison of expression QTL (eQTL) maps obtained in different tissues is an essential step to understand how gene expression is genetically regulated in a context-dependent manner. In the current work, we have compared the transcriptomic and eQTL profiles of two porcine tissues (skeletal muscle and liver) which typically show highly divergent expression profiles, in 103 Duroc pigs genotyped with the Porcine SNP60 BeadChip (Illumina) and with available microarray-based measurements of hepatic and muscle mRNA levels. Since structural variation could have effects on gene expression, we have also investigated the co-localization of cis-eQTLs with copy number variant regions (CNVR) segregating in this Duroc population. RESULTS The analysis of differential expresssion revealed the existence of 1204 and 1490 probes that were overexpressed and underexpressed in the gluteus medius muscle when compared to liver, respectively (|fold-change| > 1.5, q-value < 0.05). By performing genome scans in 103 Duroc pigs with available expression and genotypic data, we identified 76 and 28 genome-wide significant cis-eQTLs regulating gene expression in the gluteus medius muscle and liver, respectively. Twelve of these cis-eQTLs were shared by both tissues (i.e. 42.8% of the cis-eQTLs identified in the liver were replicated in the gluteus medius muscle). These results are consistent with previous studies performed in humans, where 50% of eQTLs were shared across tissues. Moreover, we have identified 41 CNVRs in a set of 350 pigs from the same Duroc population, which had been genotyped with the Porcine SNP60 BeadChip by using the PennCNV and GADA softwares, but only a small proportion of these CNVRs co-localized with the cis-eQTL signals. CONCLUSION Despite the fact that there are considerable differences in the gene expression patterns of the porcine liver and skeletal muscle, we have identified a substantial proportion of common cis-eQTLs regulating gene expression in both tissues. Several of these cis-eQTLs influence the mRNA levels of genes with important roles in meat (CTSF) and carcass quality (TAPT1), lipid metabolism (TMEM97) and obesity (MARC2), thus evidencing the practical importance of dissecting the genetic mechanisms involved in their expression.
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Affiliation(s)
- Rayner González-Prendes
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, Bellaterra, 08193, Barcelona, Spain.,Departament de Producció Animal-Agrotecnio Center, Universitat de Lleida, 191 Rovira Roure, 25198, Lleida, Spain
| | - Emilio Mármol-Sánchez
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, Bellaterra, 08193, Barcelona, Spain
| | - Raquel Quintanilla
- Animal Breeding and Genetics Program, Institute for Research and Technology in Food and Agriculture (IRTA), Torre Marimon, 08140, Caldes de Montbui, Spain
| | - Anna Castelló
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, Bellaterra, 08193, Barcelona, Spain.,Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain
| | - Ali Zidi
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, Bellaterra, 08193, Barcelona, Spain
| | - Yuliaxis Ramayo-Caldas
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, Bellaterra, 08193, Barcelona, Spain
| | - Tainã Figueiredo Cardoso
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, Bellaterra, 08193, Barcelona, Spain.,CAPES Foundation, Ministry of Education of Brazil, Brasilia D. F, Zip Code 70.040-020, Brazil
| | - Arianna Manunza
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, Bellaterra, 08193, Barcelona, Spain
| | - Ángela Cánovas
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, Bellaterra, 08193, Barcelona, Spain.,Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Road East, Guelph, Ontario, N1G 2W1, Canada
| | - Marcel Amills
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, Bellaterra, 08193, Barcelona, Spain. .,Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain.
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12
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Zhuang Z, Li S, Ding R, Yang M, Zheng E, Yang H, Gu T, Xu Z, Cai G, Wu Z, Yang J. Meta-analysis of genome-wide association studies for loin muscle area and loin muscle depth in two Duroc pig populations. PLoS One 2019; 14:e0218263. [PMID: 31188900 PMCID: PMC6561594 DOI: 10.1371/journal.pone.0218263] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 05/29/2019] [Indexed: 01/07/2023] Open
Abstract
Loin muscle area (LMA) and loin muscle depth (LMD) are important traits influencing the production performance of breeding pigs. However, the genetic architecture of these two traits is still poorly understood. To discern the genetic architecture of LMA and LMD, a material consisting of 6043 Duroc pigs belonging to two populations with different genetic backgrounds was collected and applied in genome-wide association studies (GWAS) with a genome-wide distributed panel of 50K single nucleotide polymorphisms (SNPs). To improve the power of detection for common SNPs, we conducted a meta-analysis in these two pig populations and uncovered additional significant SNPs. As a result, we identified 75 significant SNPs for LMA and LMD on SSC6, 7, 12, 16, and 18. Among them, 25 common SNPs were associated with LMA and LMD. One pleiotropic quantitative trait locus (QTL), which was located on SSC7 with a 283 kb interval, was identified to affect LMA and LMD. Marker ALGA0040260 is a key SNP for this QTL, explained 1.77% and 2.48% of the phenotypic variance for LMA and LMD, respectively. Another genetic region on SSC16 (709 kb) was detected and displayed prominent association with LMA and the peak SNP, WU_10.2_16_35829257, contributed 1.83% of the phenotypic variance for LMA. Further bioinformatics analysis determined eight promising candidate genes (GCLC, GPX8, DAXX, FGF21, TAF11, SPDEF, NUDT3, and PACSIN1) with functions in glutathione metabolism, adipose and muscle tissues development and lipid metabolism. This study provides the first GWAS for the LMA and LMD of Duroc breed to analyze the underlying genetic variants through a large sample size. The findings further advance our understanding and help elucidate the genetic architecture of LMA, LMD and growth-related traits in pigs.
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Affiliation(s)
- Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, P.R. China
| | - Shaoyun Li
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, P.R. China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, P.R. China
| | - Ming Yang
- National Engineering Research Center for Breeding Swine Industry, Guangdong Wens Foodstuffs Group Co., Ltd, Guangdong, P.R. China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, P.R. China
| | - Huaqiang Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, P.R. China
| | - Ting Gu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, P.R. China
| | - Zheng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, P.R. China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, P.R. China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, P.R. China
- National Engineering Research Center for Breeding Swine Industry, Guangdong Wens Foodstuffs Group Co., Ltd, Guangdong, P.R. China
- * E-mail: (JY); (ZW)
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, P.R. China
- * E-mail: (JY); (ZW)
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13
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González-Prendes R, Quintanilla R, Mármol-Sánchez E, Pena RN, Ballester M, Cardoso TF, Manunza A, Casellas J, Cánovas Á, Díaz I, Noguera JL, Castelló A, Mercadé A, Amills M. Comparing the mRNA expression profile and the genetic determinism of intramuscular fat traits in the porcine gluteus medius and longissimus dorsi muscles. BMC Genomics 2019; 20:170. [PMID: 30832586 PMCID: PMC6399881 DOI: 10.1186/s12864-019-5557-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Accepted: 02/22/2019] [Indexed: 12/23/2022] Open
Abstract
Background Intramuscular fat (IMF) content and composition have a strong impact on the nutritional and organoleptic properties of porcine meat. The goal of the current work was to compare the patterns of gene expression and the genetic determinism of IMF traits in the porcine gluteus medius (GM) and longissimus dorsi (LD) muscles. Results A comparative analysis of the mRNA expression profiles of the pig GM and LD muscles in 16 Duroc pigs with available microarray mRNA expression measurements revealed the existence of 106 differentially expressed probes (fold-change > 1.5 and q-value < 0.05). Amongst the genes displaying the most significant differential expression, several loci belonging to the Hox transcription factor family were either upregulated (HOXA9, HOXA10, HOXB6, HOXB7 and TBX1) or downregulated (ARX) in the GM muscle. Differences in the expression of genes with key roles in carbohydrate and lipid metabolism (e.g. FABP3, ORMDL1 and SLC37A1) were also detected. By performing a GWAS for IMF content and composition traits recorded in the LD and GM muscles of 350 Duroc pigs, we identified the existence of one region on SSC14 (110–114 Mb) displaying significant associations with C18:0, C18:1(n-7), saturated and unsaturated fatty acid contents in both GM and LD muscles. Moreover, we detected several genome-wide significant associations that were not consistently found in both muscles. Further studies should be performed to confirm whether these associations are muscle-specific. Finally, the performance of an eQTL scan for 74 genes, located within GM QTL regions and with available microarray measurements of gene expression, made possible to identify 14 cis-eQTL regulating the expression of 14 loci, and six of them were confirmed by RNA-Seq. Conclusions We have detected significant differences in the mRNA expression patterns of the porcine LD and GM muscles, evidencing that the transcriptomic profile of the skeletal muscle tissue is affected by anatomical, metabolic and functional factors. A highly significant association with IMF composition on SSC14 was replicated in both muscles, highlighting the existence of a common genetic determinism, but we also observed the existence of a few associations whose magnitude and significance varied between LD and GM muscles. Electronic supplementary material The online version of this article (10.1186/s12864-019-5557-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Rayner González-Prendes
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain
| | - Raquel Quintanilla
- Animal Breeding and Genetics Program, Institute for Research and Technology in Food and Agriculture (IRTA), Rovira Roure 191, 25198, Lleida, Spain
| | - Emilio Mármol-Sánchez
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain
| | - Ramona N Pena
- Departament de Ciència Animal, Universitat de Lleida-Agrotecnio Centre, 25198, Lleida, Spain
| | - Maria Ballester
- Animal Breeding and Genetics Program, Institute for Research and Technology in Food and Agriculture (IRTA), Rovira Roure 191, 25198, Lleida, Spain
| | - Tainã Figueiredo Cardoso
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain.,CAPES Foundation, Ministry of Education of Brazil, Brasilia, DF, 70.040-020, Brazil
| | - Arianna Manunza
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain
| | - Joaquim Casellas
- Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain
| | - Ángela Cánovas
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Road East, Guelph, Ontario, N1G 2W1, Canada
| | - Isabel Díaz
- Institute for Research and Technology in Food and Agriculture (IRTA), Tecnologia dels Aliments, 17121, Monells, Spain
| | - José Luis Noguera
- Animal Breeding and Genetics Program, Institute for Research and Technology in Food and Agriculture (IRTA), Rovira Roure 191, 25198, Lleida, Spain
| | - Anna Castelló
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain.,Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain
| | - Anna Mercadé
- Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain
| | - Marcel Amills
- Department of Animal Genetics, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain. .,Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain.
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14
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Velez-Irizarry D, Casiro S, Daza KR, Bates RO, Raney NE, Steibel JP, Ernst CW. Genetic control of longissimus dorsi muscle gene expression variation and joint analysis with phenotypic quantitative trait loci in pigs. BMC Genomics 2019; 20:3. [PMID: 30606113 PMCID: PMC6319002 DOI: 10.1186/s12864-018-5386-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 12/18/2018] [Indexed: 12/21/2022] Open
Abstract
Background Economically important growth and meat quality traits in pigs are controlled by cascading molecular events occurring during development and continuing throughout the conversion of muscle to meat. However, little is known about the genes and molecular mechanisms involved in this process. Evaluating transcriptomic profiles of skeletal muscle during the initial steps leading to the conversion of muscle to meat can identify key regulators of polygenic phenotypes. In addition, mapping transcript abundance through genome-wide association analysis using high-density marker genotypes allows identification of genomic regions that control gene expression, referred to as expression quantitative trait loci (eQTL). In this study, we perform eQTL analyses to identify potential candidate genes and molecular markers regulating growth and meat quality traits in pigs. Results Messenger RNA transcripts obtained with RNA-seq of longissimus dorsi muscle from 168 F2 animals from a Duroc x Pietrain pig resource population were used to estimate gene expression variation subject to genetic control by mapping eQTL. A total of 339 eQTL were mapped (FDR ≤ 0.01) with 191 exhibiting local-acting regulation. Joint analysis of eQTL with phenotypic QTL (pQTL) segregating in our population revealed 16 genes significantly associated with 21 pQTL for meat quality, carcass composition and growth traits. Ten of these pQTL were for meat quality phenotypes that co-localized with one eQTL on SSC2 (8.8-Mb region) and 11 eQTL on SSC15 (121-Mb region). Biological processes identified for co-localized eQTL genes include calcium signaling (FERM, MRLN, PKP2 and CHRNA9), energy metabolism (SUCLG2 and PFKFB3) and redox hemostasis (NQO1 and CEP128), and results support an important role for activation of the PI3K-Akt-mTOR signaling pathway during the initial conversion of muscle to meat. Conclusion Co-localization of eQTL with pQTL identified molecular markers significantly associated with both economically important phenotypes and gene transcript abundance. This study reveals candidate genes contributing to variation in pig production traits, and provides new knowledge regarding the genetic architecture of meat quality phenotypes. Electronic supplementary material The online version of this article (10.1186/s12864-018-5386-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - Sebastian Casiro
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA
| | - Kaitlyn R Daza
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA
| | - Ronald O Bates
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA
| | - Nancy E Raney
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA
| | - Juan P Steibel
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA.,Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, 48824, USA
| | - Catherine W Ernst
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA.
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15
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Zhang Z, Zhang Q, Xiao Q, Sun H, Gao H, Yang Y, Chen J, Li Z, Xue M, Ma P, Yang H, Xu N, Wang Q, Pan Y. Distribution of runs of homozygosity in Chinese and Western pig breeds evaluated by reduced-representation sequencing data. Anim Genet 2018; 49:579-591. [DOI: 10.1111/age.12730] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/28/2018] [Indexed: 02/02/2023]
Affiliation(s)
- Zhe Zhang
- Department of Animal Science; School of Agriculture and Biology; Shanghai Jiao Tong University; Shanghai 200240 China
- Shanghai Key Laboratory of Veterinary Biotechnology; Shanghai 200240 China
| | - Qianqian Zhang
- Animal Genetics, Bioinformatics and Breeding; University of Copenhagen; Frederiksberg 1870 Denmark
| | - Qian Xiao
- Department of Animal Science; School of Agriculture and Biology; Shanghai Jiao Tong University; Shanghai 200240 China
- Shanghai Key Laboratory of Veterinary Biotechnology; Shanghai 200240 China
| | - Hao Sun
- Department of Animal Science; School of Agriculture and Biology; Shanghai Jiao Tong University; Shanghai 200240 China
- Shanghai Key Laboratory of Veterinary Biotechnology; Shanghai 200240 China
| | - Hongding Gao
- Center for Quantitative Genetics and Genomics; Department of Molecular Biology and Genetics; Aarhus University; 8830 Tjele Denmark
| | - Yumei Yang
- Department of Animal Science; School of Agriculture and Biology; Shanghai Jiao Tong University; Shanghai 200240 China
- Shanghai Key Laboratory of Veterinary Biotechnology; Shanghai 200240 China
| | - Jiucheng Chen
- College of Animal Sciences; Zhejiang University; Hangzhou 310058 China
| | - Zhengcao Li
- College of Animal Sciences; Zhejiang University; Hangzhou 310058 China
| | - Ming Xue
- National Station of Animal Husbandry; Beijing 100125 China
| | - Peipei Ma
- Department of Animal Science; School of Agriculture and Biology; Shanghai Jiao Tong University; Shanghai 200240 China
- Shanghai Key Laboratory of Veterinary Biotechnology; Shanghai 200240 China
| | - Hongjie Yang
- National Station of Animal Husbandry; Beijing 100125 China
| | - Ningying Xu
- College of Animal Sciences; Zhejiang University; Hangzhou 310058 China
| | - Qishan Wang
- Department of Animal Science; School of Agriculture and Biology; Shanghai Jiao Tong University; Shanghai 200240 China
- Shanghai Key Laboratory of Veterinary Biotechnology; Shanghai 200240 China
| | - Yuchun Pan
- Department of Animal Science; School of Agriculture and Biology; Shanghai Jiao Tong University; Shanghai 200240 China
- Shanghai Key Laboratory of Veterinary Biotechnology; Shanghai 200240 China
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16
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Martínez-Montes ÁM, Fernández A, Muñoz M, Noguera JL, Folch JM, Fernández AI. Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed. PLoS One 2018. [PMID: 29522525 PMCID: PMC5844516 DOI: 10.1371/journal.pone.0190184] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and haplotype analyses for growth, fatness and premier cut weights in three different genetic backgrounds, backcrosses based on Iberian pigs, which has a major role in the analysis due to its high productive relevance. The results revealed nine common QTL regions, three segregating in all three backcrosses on SSC1, 0–3 Mb, for body weight, on SSC2, 3–9 Mb, for loin bone-in weight, and on SSC7, 3 Mb, for shoulder weight, and six segregating in two of the three backcrosses, on SSC2, SSC4, SSC6 and SSC10 for backfat thickness, shoulder and ham weights. Besides, 18 QTL regions were specifically identified in one of the three backcrosses, five identified only in BC_LD, seven in BC_DU and six in BC_PI. Beyond identifying and validating QTL, candidate genes and gene variants within the most interesting regions have been explored using functional annotation, gene expression data and SNP identification from RNA-Seq data. The results allowed us to propose a promising list of candidate mutations, those identified in PDE10A, DHCR7, MFN2 and CCNY genes located within the common QTL regions and those identified near ssc-mir-103-1 considered PANK3 regulators to be further analysed.
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Affiliation(s)
- Ángel M. Martínez-Montes
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain
| | - Almudena Fernández
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain
| | - María Muñoz
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain
- Centro de I+D en Cerdo Ibérico, Zafra, Badajoz, Spain
| | - Jose Luis Noguera
- Departament de Genètica i Millora Animal, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Lleida, Spain
| | - Josep M. Folch
- Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona (UAB), Bellaterra, Spain
- Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), Consorci CSIC-IRTA-UAB-UB, Campus UAB, Bellaterra, Spain
| | - Ana I. Fernández
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Madrid, Spain
- * E-mail:
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17
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González-Prendes R, Quintanilla R, Amills M. Investigating the genetic regulation of the expression of 63 lipid metabolism genes in the pig skeletal muscle. Anim Genet 2017; 48:606-610. [DOI: 10.1111/age.12586] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/12/2017] [Indexed: 01/22/2023]
Affiliation(s)
- R. González-Prendes
- Department of Animal Genetics; Center for Research in Agricultural Genomics (CSIC-IRTA-UAB-UB); Campus de la Universitat Autònoma de Barcelona Bellaterra 08193 Spain
| | - R. Quintanilla
- Animal Breeding and Genetics Program; Institut de Recerca i Tecnologia Agroalimentàries (IRTA); Torre Marimon Caldes de Montbui 08140 Spain
| | - M. Amills
- Department of Animal Genetics; Center for Research in Agricultural Genomics (CSIC-IRTA-UAB-UB); Campus de la Universitat Autònoma de Barcelona Bellaterra 08193 Spain
- Departament de Ciència Animal i dels Aliments; Facultat de Veterinària; Universitat Autònoma de Barcelona; Bellaterra 08193 Spain
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18
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Daza KR, Steibel JP, Velez-Irizarry D, Raney NE, Bates RO, Ernst CW. Profiling and characterization of a longissimus dorsi muscle microRNA dataset from an F 2 Duroc × Pietrain pig resource population. GENOMICS DATA 2017; 13:50-53. [PMID: 28736700 PMCID: PMC5508516 DOI: 10.1016/j.gdata.2017.07.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Revised: 07/03/2017] [Accepted: 07/04/2017] [Indexed: 11/12/2022]
Abstract
To elucidate the effects of microRNA (miRNA) regulation in skeletal muscle of adult pigs, miRNA expression profiling was performed with RNA extracted from longissimus dorsi (LD) muscle samples from 174 F2 pigs (~ 5.5 months of age) from a Duroc × Pietrain resource population. Total RNA was extracted from LD samples, and libraries were sequenced on an Illumina HiSeq 2500 platform in 1 × 50 bp format. After processing, 232,826,977 total reads were aligned to the Sus scrofa reference genome (v10.2.79), with 74.8% of total reads mapping successfully. The miRDeep2 software package was utilized to quantify annotated Sus scrofa mature miRNAs from miRBase (Release 21) and to predict candidate novel miRNA precursors. Among the retained 295 normalized mature miRNA expression profiles sscmiR1, sscmiR133a3p, sscmiR378, sscmiR206, and sscmiR10b were the most abundant, all of which have previously been shown to be expressed in pig skeletal muscle. Additionally, 27 unique candidate novel miRNA precursors were identified exhibiting homologous sequence to annotated human miRNAs. The composition of classes of small RNA present in this dataset was also characterized; while the majority of unique expressed sequence tags were not annotated in any of the queried databases, the most abundantly expressed class of small RNA in this dataset was miRNAs. This data provides a resource to evaluate miRNA regulation of gene expression and effects on complex trait phenotypes in adult pig skeletal muscle. The raw sequencing data were deposited in the Sequence Read Archive, BioProject PRJNA363073.
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Affiliation(s)
- Kaitlyn R Daza
- Department of Animal Science, Michigan State University, East Lansing, MI 48824, USA
| | - Juan P Steibel
- Department of Animal Science, Michigan State University, East Lansing, MI 48824, USA.,Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA
| | | | - Nancy E Raney
- Department of Animal Science, Michigan State University, East Lansing, MI 48824, USA
| | - Ronald O Bates
- Department of Animal Science, Michigan State University, East Lansing, MI 48824, USA
| | - Catherine W Ernst
- Department of Animal Science, Michigan State University, East Lansing, MI 48824, USA
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19
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Discovering Single Nucleotide Polymorphisms Regulating Human Gene Expression Using Allele Specific Expression from RNA-seq Data. Genetics 2016; 204:1057-1064. [PMID: 27765809 DOI: 10.1534/genetics.115.177246] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2015] [Accepted: 09/07/2016] [Indexed: 12/20/2022] Open
Abstract
The study of the genetics of gene expression is of considerable importance to understanding the nature of common, complex diseases. The most widely applied approach to identifying relationships between genetic variation and gene expression is the expression quantitative trait loci (eQTL) approach. Here, we increased the computational power of eQTL with an alternative and complementary approach based on analyzing allele specific expression (ASE). We designed a novel analytical method to identify cis-acting regulatory variants based on genome sequencing and measurements of ASE from RNA-sequencing (RNA-seq) data. We evaluated the power and resolution of our method using simulated data. We then applied the method to map regulatory variants affecting gene expression in lymphoblastoid cell lines (LCLs) from 77 unrelated northern and western European individuals (CEU), which were part of the HapMap project. A total of 2309 SNPs were identified as being associated with ASE patterns. The SNPs associated with ASE were enriched within promoter regions and were significantly more likely to signal strong evidence for a regulatory role. Finally, among the candidate regulatory SNPs, we identified 108 SNPs that were previously associated with human immune diseases. With further improvements in quantifying ASE from RNA-seq, the application of our method to other datasets is expected to accelerate our understanding of the biological basis of common diseases.
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20
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Suravajhala P, Kogelman LJA, Kadarmideen HN. Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare. Genet Sel Evol 2016; 48:38. [PMID: 27130220 PMCID: PMC4850674 DOI: 10.1186/s12711-016-0217-x] [Citation(s) in RCA: 100] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2015] [Accepted: 04/16/2016] [Indexed: 02/06/2023] Open
Abstract
In the past years, there has been a remarkable development of high-throughput omics (HTO) technologies such as genomics, epigenomics, transcriptomics, proteomics and metabolomics across all facets of biology. This has spearheaded the progress of the systems biology era, including applications on animal production and health traits. However, notwithstanding these new HTO technologies, there remains an emerging challenge in data analysis. On the one hand, different HTO technologies judged on their own merit are appropriate for the identification of disease-causing genes, biomarkers for prevention and drug targets for the treatment of diseases and for individualized genomic predictions of performance or disease risks. On the other hand, integration of multi-omic data and joint modelling and analyses are very powerful and accurate to understand the systems biology of healthy and sustainable production of animals. We present an overview of current and emerging HTO technologies each with a focus on their applications in animal and veterinary sciences before introducing an integrative systems genomics framework for analysing and integrating multi-omic data towards improved animal production, health and welfare. We conclude that there are big challenges in multi-omic data integration, modelling and systems-level analyses, particularly with the fast emerging HTO technologies. We highlight existing and emerging systems genomics approaches and discuss how they contribute to our understanding of the biology of complex traits or diseases and holistic improvement of production performance, disease resistance and welfare.
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Affiliation(s)
- Prashanth Suravajhala
- Department of Large Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 7, 1870, Frederiksberg C, Denmark
| | - Lisette J A Kogelman
- Department of Large Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 7, 1870, Frederiksberg C, Denmark
| | - Haja N Kadarmideen
- Department of Large Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 7, 1870, Frederiksberg C, Denmark.
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21
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Gene map of large yellow croaker (Larimichthys crocea) provides insights into teleost genome evolution and conserved regions associated with growth. Sci Rep 2015; 5:18661. [PMID: 26689832 PMCID: PMC4687042 DOI: 10.1038/srep18661] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2015] [Accepted: 11/23/2015] [Indexed: 12/05/2022] Open
Abstract
The genetic map of a species is essential for its whole genome assembly and can be applied to the mapping of important traits. In this study, we performed RNA-seq for a family of large yellow croakers (Larimichthys crocea) and constructed a high-density genetic map. In this map, 24 linkage groups comprised 3,448 polymorphic SNP markers. Approximately 72.4% (2,495) of the markers were located in protein-coding regions. Comparison of the croaker genome with those of five model fish species revealed that the croaker genome structure was closer to that of the medaka than to the remaining four genomes. Because the medaka genome preserves the teleost ancestral karyotype, this result indicated that the croaker genome might also maintain the teleost ancestral genome structure. The analysis also revealed different genome rearrangements across teleosts. QTL mapping and association analysis consistently identified growth-related QTL regions and associated genes. Orthologs of the associated genes in other species were demonstrated to regulate development, indicating that these genes might regulate development and growth in croaker. This gene map will enable us to construct the croaker genome for comparative studies and to provide an important resource for selective breeding of croaker.
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22
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Exome Capture with Heterologous Enrichment in Pig (Sus scrofa). PLoS One 2015; 10:e0139328. [PMID: 26431395 PMCID: PMC4592256 DOI: 10.1371/journal.pone.0139328] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2015] [Accepted: 09/11/2015] [Indexed: 12/26/2022] Open
Abstract
The discovery of new protein-coding DNA variants related to carcass traits is very important for the Italian pig industry, which requires heavy pigs with higher thickness of subcutaneous fat for Protected Designation of Origin (PDO) productions. Exome capture techniques offer the opportunity to focus on the regions of DNA potentially related to the gene and protein expression. In this research a human commercial target enrichment kit was used to evaluate its performances for pig exome capture and for the identification of DNA variants suitable for comparative analysis. Two pools of 30 pigs each, crosses of Italian Duroc X Large White (DU) and Commercial hybrid X Large White (HY), were used and NGS libraries were prepared with the SureSelectXT Target Enrichment System for Illumina Paired-End Sequencing Library (Agilent). A total of 140.2 M and 162.5 M of raw reads were generated for DU and HY, respectively. Average coverage of all the exonic regions for Sus scrofa (ENSEMBL Sus_scrofa.Sscrofa10.2.73.gtf) was 89.33X for DU and 97.56X for HY; and 35% of aligned bases uniquely mapped to off-target regions. Comparison of sequencing data with the Sscrofa10.2 reference genome, after applying hard filtering criteria, revealed a total of 232,530 single nucleotide variants (SNVs) of which 20.6% mapped in exonic regions and 49.5% within intronic regions. The comparison of allele frequencies of 213 randomly selected SNVs from exome sequencing and the same SNVs analyzed with a Sequenom MassARRAY® system confirms that this “human-on-pig” approach offers new potentiality for the identification of DNA variants in protein-coding genes.
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23
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Peñagaricano F, Valente BD, Steibel JP, Bates RO, Ernst CW, Khatib H, Rosa GJM. Exploring causal networks underlying fat deposition and muscularity in pigs through the integration of phenotypic, genotypic and transcriptomic data. BMC SYSTEMS BIOLOGY 2015; 9:58. [PMID: 26376630 PMCID: PMC4574162 DOI: 10.1186/s12918-015-0207-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2015] [Accepted: 09/04/2015] [Indexed: 12/23/2022]
Abstract
BACKGROUND Joint modeling and analysis of phenotypic, genotypic and transcriptomic data have the potential to uncover the genetic control of gene activity and phenotypic variation, as well as shed light on the manner and extent of connectedness among these variables. Current studies mainly report associations, i.e. undirected connections among variables without causal interpretation. Knowledge regarding causal relationships among genes and phenotypes can be used to predict the behavior of complex systems, as well as to optimize management practices and selection strategies. Here, we performed a multistep procedure for inferring causal networks underlying carcass fat deposition and muscularity in pigs using multi-omics data obtained from an F2 Duroc x Pietrain resource pig population. RESULTS We initially explored marginal associations between genotypes and phenotypic and expression traits through whole-genome scans, and then, in genomic regions with multiple significant hits, we assessed gene-phenotype network reconstruction using causal structural learning algorithms. One genomic region on SSC6 showed significant associations with three relevant phenotypes, off-midline10th-rib backfat thickness, loin muscle weight, and average intramuscular fat percentage, and also with the expression of seven genes, including ZNF24, SSX2IP, and AKR7A2. The inferred network indicated that the genotype affects the three phenotypes mainly through the expression of several genes. Among the phenotypes, fat deposition traits negatively affected loin muscle weight. CONCLUSIONS Our findings shed light on the antagonist relationship between carcass fat deposition and lean meat content in pigs. In addition, the procedure described in this study has the potential to unravel gene-phenotype networks underlying complex phenotypes.
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Affiliation(s)
- Francisco Peñagaricano
- Department of Animal Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA.
- Present Address: Department of Animal Sciences, and University of Florida Genetics Institute, University of Florida, Gainesville, FL, 326111, USA.
| | - Bruno D Valente
- Department of Animal Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA.
- Dairy Science, University of Wisconsin-Madison, Madison, WI, 53706, USA.
| | - Juan P Steibel
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA.
| | - Ronald O Bates
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA.
| | - Catherine W Ernst
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA.
| | - Hasan Khatib
- Department of Animal Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA.
| | - Guilherme J M Rosa
- Department of Animal Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA.
- Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA.
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24
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Reeb PD, Bramardi SJ, Steibel JP. Assessing Dissimilarity Measures for Sample-Based Hierarchical Clustering of RNA Sequencing Data Using Plasmode Datasets. PLoS One 2015; 10:e0132310. [PMID: 26162080 PMCID: PMC4498680 DOI: 10.1371/journal.pone.0132310] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2015] [Accepted: 06/11/2015] [Indexed: 01/03/2023] Open
Abstract
Sample- and gene- based hierarchical cluster analyses have been widely adopted as tools for exploring gene expression data in high-throughput experiments. Gene expression values (read counts) generated by RNA sequencing technology (RNA-seq) are discrete variables with special statistical properties, such as over-dispersion and right-skewness. Additionally, read counts are subject to technology artifacts as differences in sequencing depth. This possesses a challenge to finding distance measures suitable for hierarchical clustering. Normalization and transformation procedures have been proposed to favor the use of Euclidean and correlation based distances. Additionally, novel model-based dissimilarities that account for RNA-seq data characteristics have also been proposed. Adequacy of dissimilarity measures has been assessed using parametric simulations or exemplar datasets that may limit the scope of the conclusions. Here, we propose the simulation of realistic conditions through creation of plasmode datasets, to assess the adequacy of dissimilarity measures for sample-based hierarchical clustering of RNA-seq data. Consistent results were obtained using plasmode datasets based on RNA-seq experiments conducted under widely different conditions. Dissimilarity measures based on Euclidean distance that only considered data normalization or data standardization were not reliable to represent the expected hierarchical structure. Conversely, using either a Poisson-based dissimilarity or a rank correlation based dissimilarity or an appropriate data transformation, resulted in dendrograms that resemble the expected hierarchical structure. Plasmode datasets can be generated for a wide range of scenarios upon which dissimilarity measures can be evaluated for sample-based hierarchical clustering analysis. We showed different ways of generating such plasmodes and applied them to the problem of selecting a suitable dissimilarity measure. We report several measures that are satisfactory and the choice of a particular measure may rely on the availability on the software pipeline of preference.
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Affiliation(s)
- Pablo D. Reeb
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, United States of America
- Department of Statistics, Universidad Nacional del Comahue, Cinco Saltos, Rio Negro, Argentina
| | - Sergio J. Bramardi
- Department of Statistics, Universidad Nacional del Comahue, Cinco Saltos, Rio Negro, Argentina
- College of Agricultural and Forest Sciences, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentina
| | - Juan P. Steibel
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, United States of America
- Department of Animal Science, Michigan State University, East Lansing, Michigan, United States of America
- * E-mail:
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25
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A hidden Markov approach for ascertaining cSNP genotypes from RNA sequence data in the presence of allelic imbalance by exploiting linkage disequilibrium. BMC Bioinformatics 2015; 16:61. [PMID: 25887316 PMCID: PMC4351697 DOI: 10.1186/s12859-015-0479-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Accepted: 01/27/2015] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Allelic specific expression (ASE) increases our understanding of the genetic control of gene expression and its links to phenotypic variation. ASE testing is implemented through binomial or beta-binomial tests of sequence read counts of alternative alleles at a cSNP of interest in heterozygous individuals. This requires prior ascertainment of the cSNP genotypes for all individuals. To meet the needs, we propose hidden Markov methods to call SNPs from next generation RNA sequence data when ASE possibly exists. RESULTS We propose two hidden Markov models (HMMs), HMM-ASE and HMM-NASE that consider or do not consider ASE, respectively, in order to improve genotyping accuracy. Both HMMs have the advantages of calling the genotypes of several SNPs simultaneously and allow mapping error which, respectively, utilize the dependence among SNPs and correct the bias due to mapping error. In addition, HMM-ASE exploits ASE information to further improve genotype accuracy when the ASE is likely to be present. Simulation results indicate that the HMMs proposed demonstrate a very good prediction accuracy in terms of controlling both the false discovery rate (FDR) and the false negative rate (FNR). When ASE is present, the HMM-ASE had a lower FNR than HMM-NASE, while both can control the false discovery rate (FDR) at a similar level. By exploiting linkage disequilibrium (LD), a real data application demonstrate that the proposed methods have better sensitivity and similar FDR in calling heterozygous SNPs than the VarScan method. Sensitivity and FDR are similar to that of the BCFtools and Beagle methods. The resulting genotypes show good properties for the estimation of the genetic parameters and ASE ratios. CONCLUSIONS We introduce HMMs, which are able to exploit LD and account for the ASE and mapping errors, to simultaneously call SNPs from the next generation RNA sequence data. The method introduced can reliably call for cSNP genotypes even in the presence of ASE and under low sequencing coverage. As a byproduct, the proposed method is able to provide predictions of ASE ratios for the heterozygous genotypes, which can then be used for ASE testing.
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26
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Lopes MS, Bastiaansen JWM, Harlizius B, Knol EF, Bovenhuis H. A genome-wide association study reveals dominance effects on number of teats in pigs. PLoS One 2014; 9:e105867. [PMID: 25158056 PMCID: PMC4144910 DOI: 10.1371/journal.pone.0105867] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2014] [Accepted: 07/29/2014] [Indexed: 12/31/2022] Open
Abstract
Dominance has been suggested as one of the genetic mechanisms explaining heterosis. However, using traditional quantitative genetic methods it is difficult to obtain accurate estimates of dominance effects. With the availability of dense SNP (Single Nucleotide Polymorphism) panels, we now have new opportunities for the detection and use of dominance at individual loci. Thus, the aim of this study was to detect additive and dominance effects on number of teats (NT), specifically to investigate the importance of dominance in a Landrace-based population of pigs. In total, 1,550 animals, genotyped for 32,911 SNPs, were used in single SNP analysis. SNPs with a significant genetic effect were tested for their mode of gene action being additive, dominant or a combination. In total, 21 SNPs were associated with NT, located in three regions with additive (SSC6, 7 and 12) and one region with dominant effects (SSC4). Estimates of additive effects ranged from 0.24 to 0.29 teats. The dominance effect of the QTL located on SSC4 was negative (−0.26 teats). The additive variance of the four QTLs together explained 7.37% of the total phenotypic variance. The dominance variance of the four QTLs together explained 1.82% of the total phenotypic variance, which corresponds to one-fourth of the variance explained by additive effects. The results suggest that dominance effects play a relevant role in the genetic architecture of NT. The QTL region on SSC7 contains the most promising candidate gene: VRTN. This gene has been suggested to be related to the number of vertebrae, a trait correlated with NT.
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Affiliation(s)
- Marcos S. Lopes
- TOPIGS Research Center IPG B.V., Beuningen, the Netherlands
- Wageningen University, Animal Breeding and Genomics Centre, Wageningen, the Netherlands
- * E-mail:
| | | | | | - Egbert F. Knol
- TOPIGS Research Center IPG B.V., Beuningen, the Netherlands
| | - Henk Bovenhuis
- Wageningen University, Animal Breeding and Genomics Centre, Wageningen, the Netherlands
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27
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Kadarmideen HN. Genomics to systems biology in animal and veterinary sciences: Progress, lessons and opportunities. Livest Sci 2014. [DOI: 10.1016/j.livsci.2014.04.028] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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28
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Pena RN, Quintanilla R, Manunza A, Gallardo D, Casellas J, Amills M. Application of the microarray technology to the transcriptional analysis of muscle phenotypes in pigs. Anim Genet 2014; 45:311-21. [DOI: 10.1111/age.12146] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/05/2014] [Indexed: 01/09/2023]
Affiliation(s)
- R. N. Pena
- Department of Animal Production; University of Lleida-Agrotecnio Center; 25198 Lleida Spain
| | | | - A. Manunza
- Department of Animal Genetics; Center for Research in Agricultural Genomics (CSIC-IRTA-UAB-UB); Universitat Autònoma de Barcelona; 08193 Bellaterra Spain
| | - D. Gallardo
- Departament de Ciència Animal i dels Aliments; Facultat de Veterinària; Universitat Autònoma de Barcelona; 08193 Bellaterra Spain
| | - J. Casellas
- Departament de Ciència Animal i dels Aliments; Facultat de Veterinària; Universitat Autònoma de Barcelona; 08193 Bellaterra Spain
| | - M. Amills
- Department of Animal Genetics; Center for Research in Agricultural Genomics (CSIC-IRTA-UAB-UB); Universitat Autònoma de Barcelona; 08193 Bellaterra Spain
- Departament de Ciència Animal i dels Aliments; Facultat de Veterinària; Universitat Autònoma de Barcelona; 08193 Bellaterra Spain
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29
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Xiao D, Wang H, Basnet RK, Zhao J, Lin K, Hou X, Bonnema G. Genetic dissection of leaf development in Brassica rapa using a genetical genomics approach. PLANT PHYSIOLOGY 2014; 164:1309-25. [PMID: 24394778 PMCID: PMC3938622 DOI: 10.1104/pp.113.227348] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2013] [Accepted: 01/01/2014] [Indexed: 05/20/2023]
Abstract
The paleohexaploid crop Brassica rapa harbors an enormous reservoir of morphological variation, encompassing leafy vegetables, vegetable and fodder turnips (Brassica rapa, ssp. campestris), and oil crops, with different crops having very different leaf morphologies. In the triplicated B. rapa genome, many genes have multiple paralogs that may be regulated differentially and contribute to phenotypic variation. Using a genetical genomics approach, phenotypic data from a segregating doubled haploid population derived from a cross between cultivar Yellow sarson (oil type) and cultivar Pak choi (vegetable type) were used to identify loci controlling leaf development. Twenty-five colocalized phenotypic quantitative trait loci (QTLs) contributing to natural variation for leaf morphological traits, leaf number, plant architecture, and flowering time were identified. Genetic analysis showed that four colocalized phenotypic QTLs colocalized with flowering time and leaf trait candidate genes, with their cis-expression QTLs and cis- or trans-expression QTLs for homologs of genes playing a role in leaf development in Arabidopsis (Arabidopsis thaliana). The leaf gene Brassica rapa KIP-related protein2_A03 colocalized with QTLs for leaf shape and plant height; Brassica rapa Erecta_A09 colocalized with QTLs for leaf color and leaf shape; Brassica rapa Longifolia1_A10 colocalized with QTLs for leaf size, leaf color, plant branching, and flowering time; while the major flowering time gene, Brassica rapa flowering locus C_A02, colocalized with QTLs explaining variation in flowering time, plant architectural traits, and leaf size. Colocalization of these QTLs points to pleiotropic regulation of leaf development and plant architectural traits in B. rapa.
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30
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Muñoz M, Rodríguez MC, Alves E, Folch JM, Ibañez-Escriche N, Silió L, Fernández AI. Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data. BMC Genomics 2013; 14:845. [PMID: 24295214 PMCID: PMC4046688 DOI: 10.1186/1471-2164-14-845] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2013] [Accepted: 11/25/2013] [Indexed: 01/15/2023] Open
Abstract
Background Porcine fatty acid composition is a key factor for quality and nutritive value of pork. Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the fat deposits. Those studies have been conducted using simple approaches and most of them focused on one single tissue. The first objective of the present study was to identify tissue-specific and tissue-consistent QTLs for fatty acid composition in backfat and intramuscular fat, combining linkage mapping and GWAS approaches and conducted under single and multitrait models. A second aim was to identify powerful candidate genes for these tissue-consistent QTLs, using microarray gene expression data and following a targeted genetical genomics approach. Results The single model analyses, linkage and GWAS, revealed over 30 and 20 chromosomal regions, 24 of them identified here for the first time, specifically associated to the content of diverse fatty acids in BF and IMF, respectively. The analyses with multitrait models allowed identifying for the first time with a formal statistical approach seven different regions with pleiotropic effects on particular fatty acids in both fat deposits. The most relevant were found on SSC8 for C16:0 and C16:1(n-7) fatty acids, detected by both linkage and GWAS approaches. Other detected pleiotropic regions included one on SSC1 for C16:0, two on SSC4 for C16:0 and C18:2, one on SSC11 for C20:3 and the last one on SSC17 for C16:0. Finally, a targeted eQTL scan focused on regions showing tissue-consistent effects was conducted with Longissimus and fat gene expression data. Some powerful candidate genes and regions were identified such as the PBX1, RGS4, TRIB3 and a transcription regulatory element close to ELOVL6 gene to be further studied. Conclusions Complementary genome scans have confirmed several chromosome regions previously associated to fatty acid composition in backfat and intramuscular fat, but even more, to identify new ones. Although most of the detected regions were tissue-specific, supporting the hypothesis that the major part of genes affecting fatty acid composition differs among tissues, seven chromosomal regions showed tissue-consistent effects. Additional gene expression analyses have revealed powerful target regions to carry the mutation responsible for the pleiotropic effects. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-14-845) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- María Muñoz
- INIA, Mejora Genética Animal, 28040 Madrid, Spain.
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A genetical genomics approach reveals new candidates and confirms known candidate genes for drip loss in a porcine resource population. Mamm Genome 2013; 24:416-26. [PMID: 24026665 DOI: 10.1007/s00335-013-9473-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2013] [Accepted: 08/05/2013] [Indexed: 10/26/2022]
Abstract
In this study lean meat water-holding capacity (WHC) of a Duroc × Pietrain (DuPi) resource population with corresponding genotypes and transcriptomes was investigated using genetical genomics. WHC was characterized by drip loss measured in M. longissimus dorsi. The 60K Illumina SNP chips identified genotypes of 169 F2 DuPi animals. Whole-genome transcriptomes of muscle samples were available for 132 F2 animals using the Affymetrix 24K GeneChip® Porcine Genome Array. Performing genome-wide association studies of transcriptional profiles, which are correlated with phenotypes, allows elucidation of cis- and trans-regulation. Expression levels of 1,228 genes were significantly correlated with drip loss and were further analyzed for enrichment of functional annotation groups as defined by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. A hypergeometric gene set enrichment test was performed and revealed glycolysis/glyconeogenesis, pentose phosphate pathway, and pyruvate metabolism as the most promising pathways. For 267 selected transcripts, expression quantitative trait loci (eQTL) analysis was performed and revealed a total of 1,541 significant associations. Because of positional accordance of the gene underlying transcript and the eQTL location, it was possible to identify eight eQTL that can be assumed to be cis-regulated. Comparing the results of gene set enrichment and the eQTL detection tests, molecular networks and potential candidate genes, which seemed to play key roles in the expression of WHC, were detected. The α-1-microglobulin/bikunin precursor (AMBP) gene was assumed to be cis-regulated and was part of the glycolysis pathway. This approach supports the identification of trait-associated SNPs and the further biological understanding of complex traits.
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Molecular advances in QTL discovery and application in pig breeding. Trends Genet 2013; 29:215-24. [DOI: 10.1016/j.tig.2013.02.002] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2012] [Revised: 02/12/2013] [Accepted: 02/13/2013] [Indexed: 11/21/2022]
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Cánovas A, Pena RN, Gallardo D, Ramírez O, Amills M, Quintanilla R. Segregation of regulatory polymorphisms with effects on the gluteus medius transcriptome in a purebred pig population. PLoS One 2012; 7:e35583. [PMID: 22545120 PMCID: PMC3335821 DOI: 10.1371/journal.pone.0035583] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2012] [Accepted: 03/19/2012] [Indexed: 01/21/2023] Open
Abstract
Background The main goal of the present study was to analyse the genetic architecture of mRNA expression in muscle, a tissue with an outmost economic importance for pig breeders. Previous studies have used F2 crosses to detect porcine expression QTL (eQTL), so they contributed with data that mostly represents the between-breed component of eQTL variation. Herewith, we have analysed eQTL segregation in an outbred Duroc population using two groups of animals with divergent fatness profiles. This approach is particularly suitable to analyse the within-breed component of eQTL variation, with a special emphasis on loci involved in lipid metabolism. Methodology/Principal Findings GeneChip Porcine Genome arrays (Affymetrix) were used to determine the mRNA expression levels of gluteus medius samples from 105 Duroc barrows. A whole-genome eQTL scan was carried out with a panel of 116 microsatellites. Results allowed us to detect 613 genome-wide significant eQTL unevenly distributed across the pig genome. A clear predominance of trans- over cis-eQTL, was observed. Moreover, 11 trans-regulatory hotspots affecting the expression levels of four to 16 genes were identified. A Gene Ontology study showed that regulatory polymorphisms affected the expression of muscle development and lipid metabolism genes. A number of positional concordances between eQTL and lipid trait QTL were also found, whereas limited evidence of a linear relationship between muscle fat deposition and mRNA levels of eQTL regulated genes was obtained. Conclusions/Significance Our data provide substantial evidence that there is a remarkable amount of within-breed genetic variation affecting muscle mRNA expression. Most of this variation acts in trans and influences biological processes related with muscle development, lipid deposition and energy balance. The identification of the underlying causal mutations and the ascertainment of their effects on phenotypes would allow gaining a fundamental perspective about how complex traits are built at the molecular level.
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Affiliation(s)
| | - Ramona N. Pena
- IRTA, Genètica i Millora Animal, Lleida, Spain
- * E-mail: (RQ); (RP)
| | - David Gallardo
- Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, Spain
| | - Oscar Ramírez
- Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, Spain
| | - Marcel Amills
- Departament de Genètica Animal, Centre de Recerca en Agrigenòmica (CRAG), Universitat Autònoma de Barcelona, Bellaterra, Barcelona, Spain
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Liaubet L, Lobjois V, Faraut T, Tircazes A, Benne F, Iannuccelli N, Pires J, Glénisson J, Robic A, Le Roy P, Sancristobal M, Cherel P. Genetic variability of transcript abundance in pig peri-mortem skeletal muscle: eQTL localized genes involved in stress response, cell death, muscle disorders and metabolism. BMC Genomics 2011; 12:548. [PMID: 22053791 PMCID: PMC3239847 DOI: 10.1186/1471-2164-12-548] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2011] [Accepted: 11/04/2011] [Indexed: 01/03/2023] Open
Abstract
Background The genetics of transcript-level variation is an exciting field that has recently given rise to many studies. Genetical genomics studies have mainly focused on cell lines, blood cells or adipose tissues, from human clinical samples or mice inbred lines. Few eQTL studies have focused on animal tissues sampled from outbred populations to reflect natural genetic variation of gene expression levels in animals. In this work, we analyzed gene expression in a whole tissue, pig skeletal muscle sampled from individuals from a half sib F2 family shortly after slaughtering. Results QTL detection on transcriptome measurements was performed on a family structured population. The analysis identified 335 eQTLs affecting the expression of 272 transcripts. The ontologic annotation of these eQTLs revealed an over-representation of genes encoding proteins involved in processes that are expected to be induced during muscle development and metabolism, cell morphology, assembly and organization and also in stress response and apoptosis. A gene functional network approach was used to evidence existing biological relationships between all the genes whose expression levels are influenced by eQTLs. eQTLs localization revealed a significant clustered organization of about half the genes located on segments of chromosome 1, 2, 10, 13, 16, and 18. Finally, the combined expression and genetic approaches pointed to putative cis-drivers of gene expression programs in skeletal muscle as COQ4 (SSC1), LOC100513192 (SSC18) where both the gene transcription unit and the eQTL affecting its expression level were shown to be localized in the same genomic region. This suggests cis-causing genetic polymorphims affecting gene expression levels, with (e.g. COQ4) or without (e.g. LOC100513192) potential pleiotropic effects that affect the expression of other genes (cluster of trans-eQTLs). Conclusion Genetic analysis of transcription levels revealed dependence among molecular phenotypes as being affected by variation at the same loci. We observed the genetic variation of molecular phenotypes in a specific situation of cellular stress thus contributing to a better description of muscle physiologic response. In turn, this suggests that large amounts of genetic variation, mediated through transcriptional networks, can drive transient cell response phenotypes and contribute to organismal adaptative potential.
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Affiliation(s)
- Laurence Liaubet
- Laboratoire de Génétique Cellulaire, INRA UMR444, Chemin de Borde Rouge, F-31326 Castanet-Tolosan, France.
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Nie Q, Fang M, Jia X, Zhang W, Zhou X, He X, Zhang X. Analysis of muscle and ovary transcriptome of Sus scrofa: assembly, annotation and marker discovery. DNA Res 2011; 18:343-51. [PMID: 21729922 PMCID: PMC3190955 DOI: 10.1093/dnares/dsr021] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Pig (Sus scrofa) is an important organism for both agricultural and medical purpose. This study aims to investigate the S. scrofa transcriptome by the use of Roche 454 pyrosequencing. We obtained a total of 558 743 and 528 260 reads for the back-leg muscle and ovary tissue each. The overall 1 087 003 reads give rise to 421 767 341 bp total residues averaging 388 bp per read. The de novo assemblies yielded 11 057 contigs and 60 270 singletons for the back-leg muscle, 12 204 contigs and 70 192 singletons for the ovary and 18 938 contigs and 102 361 singletons for combined tissues. The overall GC content of S. scrofa transcriptome is 42.3% for assembled contigs. Alternative splicing was found within 4394 contigs, giving rise to 1267 isogroups or genes. A total of 56 589 transcripts are involved in molecular function (40 916), biological process (38 563), cellular component (35 787) by further gene ontology analyses. Comparison analyses showed that 336 and 553 genes had significant higher expression in the back-leg muscle and ovary each. In addition, we obtained a total of 24 214 single-nucleotide polymorphisms and 11 928 simple sequence repeats. These results contribute to the understanding of the genetic makeup of S. scrofa transcriptome and provide useful information for functional genomic research in future.
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Affiliation(s)
- Qinghua Nie
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong 510642, People's Republic of China
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