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Farhangi S, Gòdia M, Derks MFL, Harlizius B, Dibbits B, González-Prendes R, Crooijmans RPMA, Madsen O, Groenen MAM. Expression genome-wide association study identifies key regulatory variants enriched with metabolic and immune functions in four porcine tissues. BMC Genomics 2024; 25:684. [PMID: 38992576 PMCID: PMC11238464 DOI: 10.1186/s12864-024-10583-w] [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: 02/02/2024] [Accepted: 07/01/2024] [Indexed: 07/13/2024] Open
Abstract
BACKGROUND Integration of high throughput DNA genotyping and RNA-sequencing data enables the discovery of genomic regions that regulate gene expression, known as expression quantitative trait loci (eQTL). In pigs, efforts to date have been mainly focused on purebred lines for traits with commercial relevance as such growth and meat quality. However, little is known on genetic variants and mechanisms associated with the robustness of an animal, thus its overall health status. Here, the liver, lung, spleen, and muscle transcriptomes of 100 three-way crossbred female finishers were studied, with the aim of identifying novel eQTL regulatory regions and transcription factors (TFs) associated with regulation of porcine metabolism and health-related traits. RESULTS An expression genome-wide association study with 535,896 genotypes and the expression of 12,680 genes in liver, 13,310 genes in lung, 12,650 genes in spleen, and 12,595 genes in muscle resulted in 4,293, 10,630, 4,533, and 6,871 eQTL regions for each of these tissues, respectively. Although only a small fraction of the eQTLs were annotated as cis-eQTLs, these presented a higher number of polymorphisms per region and significantly stronger associations with their target gene compared to trans-eQTLs. Between 20 and 115 eQTL hotspots were identified across the four tissues. Interestingly, these were all enriched for immune-related biological processes. In spleen, two TFs were identified: ERF and ZNF45, with key roles in regulation of gene expression. CONCLUSIONS This study provides a comprehensive analysis with more than 26,000 eQTL regions identified that are now publicly available. The genomic regions and their variants were mostly associated with tissue-specific regulatory roles. However, some shared regions provide new insights into the complex regulation of genes and their interactions that are involved with important traits related to metabolism and immunity.
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Affiliation(s)
- Samin Farhangi
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Marta Gòdia
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands.
| | - Martijn F L Derks
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
- Topigs Norsvin Research Center, 's-Hertogenbosch, The Netherlands
| | | | - Bert Dibbits
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Rayner González-Prendes
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
- Ausnutria BV, Zwolle, The Netherlands
| | | | - Ole Madsen
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Martien A M Groenen
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
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Zhao J, Liu Z, Wang X, Xin X, Du L, Zhao H, An Q, Ding X, Zhang Z, Wang E, Xu Z, Huang Y. The Identification of Goat KCNJ15 Gene Copy Number Variation and Its Association with Growth Traits. Genes (Basel) 2024; 15:250. [PMID: 38397239 PMCID: PMC10888278 DOI: 10.3390/genes15020250] [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: 12/21/2023] [Revised: 02/06/2024] [Accepted: 02/13/2024] [Indexed: 02/25/2024] Open
Abstract
(1) Background: Copy number variation (CNV) is a critical component of genome structural variation and has garnered significant attention. High-throughput screening of the KCNJ15 gene has revealed a correlation between the CNV region and the growth traits of goats. We aimed to identify the CNV of the KCNJ15 gene in five goat breeds and analyze its association with growth characteristics. (2) Methods: We utilized 706 goats from five breeds: Guizhou black goat (GZB), Guizhou white goat (GZW), Bohuai goat (BH), Huai goat (HH), and Taihang goat (TH). To evaluate the number of copies of the KCNJ15 gene using qPCR, we analyzed the correlation between the CNV and growth characteristics and then used a universal linear model. The findings revealed variations in the distribution of different copy number types among the different goat breeds. (3) Results: Association analysis revealed a positive influence of the CNV in the KCNJ15 gene on goat growth. In GZB, individuals with duplication types exhibited superior performance in terms of cannon bone circumference (p < 0.05). In HH, individuals with duplication types exhibited superior performance in terms of body slanting length (p < 0.05). Conversely, normal TH demonstrated better body height and body weight (p < 0.05), while in GZW, when CN = 3, it performed better than other types in terms of body weight and chest circumference (p < 0.05). However, in BH, it had no significant effect on growth traits. (4) Conclusions: We confirmed that the CNV in the KCNJ15 gene significantly influences the growth characteristics of four distinct goat breeds. The correlation between KCNJ15 gene CNVs and goat growth traits offers valuable insights to breeders, enabling them to employ precise and efficient breeding methods that enhance livestock welfare, productivity, and overall economic benefits in the industry.
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Affiliation(s)
- Jiahao Zhao
- College of Animal Science and Technology, Northwest A&F University, Xianyang 712100, China; (J.Z.); (Z.L.); (L.D.); (H.Z.); (X.D.)
| | - Zhe Liu
- College of Animal Science and Technology, Northwest A&F University, Xianyang 712100, China; (J.Z.); (Z.L.); (L.D.); (H.Z.); (X.D.)
| | - Xianwei Wang
- Henan Provincial Animal Husbandry General Station, Zhengzhou 450008, China;
| | - Xiaoling Xin
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China; (X.X.); (Z.Z.); (E.W.)
| | - Lei Du
- College of Animal Science and Technology, Northwest A&F University, Xianyang 712100, China; (J.Z.); (Z.L.); (L.D.); (H.Z.); (X.D.)
| | - Huangqing Zhao
- College of Animal Science and Technology, Northwest A&F University, Xianyang 712100, China; (J.Z.); (Z.L.); (L.D.); (H.Z.); (X.D.)
| | - Qingming An
- College of Agriculture and Forestry Engineering, Tongren University, Tongren 554300, China;
| | - Xiaoting Ding
- College of Animal Science and Technology, Northwest A&F University, Xianyang 712100, China; (J.Z.); (Z.L.); (L.D.); (H.Z.); (X.D.)
| | - Zijing Zhang
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China; (X.X.); (Z.Z.); (E.W.)
| | - Eryao Wang
- Institute of Animal Husbandry and Veterinary Science, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China; (X.X.); (Z.Z.); (E.W.)
| | - Zejun Xu
- Henan Provincial Animal Husbandry General Station, Zhengzhou 450008, China;
| | - Yongzhen Huang
- College of Animal Science and Technology, Northwest A&F University, Xianyang 712100, China; (J.Z.); (Z.L.); (L.D.); (H.Z.); (X.D.)
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3
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Zhu Z, Chen X, Zhang S, Yu R, Qi C, Cheng L, Zhang X. Leveraging molecular quantitative trait loci to comprehend complex diseases/traits from the omics perspective. Hum Genet 2023; 142:1543-1560. [PMID: 37755483 DOI: 10.1007/s00439-023-02602-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 09/14/2023] [Indexed: 09/28/2023]
Abstract
Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms. Herein, we reviewed molQTLs with the corresponding resource from the omics perspective and further discussed the integrative strategy of GWAS-molQTL to infer their causal effects. Subsequently, we described the opportunities and challenges encountered by molQTL. The case studies showed that molQTL is essential for complex diseases and traits, whether single- or multi-omics QTLs. Overall, we highlighted the functional significance of genetic variants to employ the discovery of molQTL in complex diseases and traits.
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Affiliation(s)
- Zijun Zhu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Xinyu Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Sainan Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Rui Yu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Changlu Qi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Liang Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China.
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150028, Heilongjiang, China.
| | - Xue Zhang
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150028, Heilongjiang, China
- McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China
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4
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Jiang Q, Xie C, Chen L, Xiao H, Xie Z, Zhu X, Ma L, Yan X. Identification of gut microbes associated with feed efficiency by daily-phase feeding strategy in growing-finishing pigs. ANIMAL NUTRITION (ZHONGGUO XU MU SHOU YI XUE HUI) 2023; 12:42-53. [PMID: 36381065 PMCID: PMC9647424 DOI: 10.1016/j.aninu.2022.09.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 09/03/2022] [Accepted: 09/15/2022] [Indexed: 06/08/2023]
Abstract
Feed efficiency is one of the most important issues for sustainable pig production. Daily-phase feeding (DPF) is a form of precision feeding that could improve feed efficiency in pigs. Gut microbiota can regulate host nutrient digestion, absorption, and metabolism. However, which key microbes may play a vital role in improving the feed efficiency during DPF remains unclear. In the present study, we used a DPF program compared to a three-phase feeding (TPF) program in growing-finishing pigs to investigate the effects of gut microbiota on feed efficiency. A total of 204 Landrace × Yorkshire pigs (75 d) were randomly assigned into 2 treatments. Each treatment was replicated 8 times with 13 to 15 pigs per replicate pen. Pigs in the TPF group were fed with a commercial feeding program that supplied fixed feed for phases I, II, and III, starting at 81, 101, and 132 d of age, respectively, and pigs in the DPF group were fed a blend of adjacent phase feed from 81 to 155 d at a gradual daily ratio and phase III feed from 155 to 180 d of age. Daily feed intake and body weight were recorded by a computerized device in the feeders. Feces and blood samples were collected from 1 pig per replicate at 155 and 180 d of age. The results showed that the DPF program remarkably improved the feed efficiency at 155 d (P < 0.001) and 180 d of age (P < 0.001), with a significant reduction of the intake of crude protein (P < 0.01), net energy (P < 0.001), crude fiber (P < 0.001), ether extract (P < 0.01), and ash (P < 0.001). The daily-phase feeding program increased the abundance of Prevotella copri (P < 0.05) and Paraprevotella clara (P < 0.05), while it decreased the abundance of Ocilibacter (P < 0.05) at 155 d of age. The results of correlation analysis indicated that the differentially abundant microbiota communities were closely associated with 20 metabolites which enriched amino acid and phenylalanine metabolism. Our results suggest that 2 key microbes may contribute to feed efficiency during daily-phase feeding strategies in pigs.
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Affiliation(s)
- Qin Jiang
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
- The Cooperative Innovation Center of Sustainable Pig Production, Wuhan, Hubei 430070, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, Hubei 430070, China
| | - Chunlin Xie
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
- The Cooperative Innovation Center of Sustainable Pig Production, Wuhan, Hubei 430070, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, Hubei 430070, China
| | - Lingli Chen
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
- The Cooperative Innovation Center of Sustainable Pig Production, Wuhan, Hubei 430070, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, Hubei 430070, China
| | - Hongli Xiao
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
- The Cooperative Innovation Center of Sustainable Pig Production, Wuhan, Hubei 430070, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, Hubei 430070, China
| | - Zhilian Xie
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
- The Cooperative Innovation Center of Sustainable Pig Production, Wuhan, Hubei 430070, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, Hubei 430070, China
| | - Xiaoyan Zhu
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
- The Cooperative Innovation Center of Sustainable Pig Production, Wuhan, Hubei 430070, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, Hubei 430070, China
| | - Libao Ma
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
- The Cooperative Innovation Center of Sustainable Pig Production, Wuhan, Hubei 430070, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, Hubei 430070, China
| | - Xianghua Yan
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Frontiers Science Center for Animal Breeding and Sustainable Production, College of Animal Sciences and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
- The Cooperative Innovation Center of Sustainable Pig Production, Wuhan, Hubei 430070, China
- Hubei Provincial Engineering Laboratory for Pig Precision Feeding and Feed Safety Technology, Wuhan, Hubei 430070, China
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5
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Ding R, Zhuang Z, Qiu Y, Wang X, Wu J, Zhou S, Ruan D, Xu C, Hong L, Gu T, Zheng E, Cai G, Huang W, Wu Z, Yang J. A composite strategy of genome-wide association study and copy number variation analysis for carcass traits in a Duroc pig population. BMC Genomics 2022; 23:590. [PMID: 35964005 PMCID: PMC9375371 DOI: 10.1186/s12864-022-08804-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 07/31/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Carcass traits are important in pig breeding programs for improving pork production. Understanding the genetic variants underlies complex phenotypes can help explain trait variation in pigs. In this study, we integrated a weighted single-step genome-wide association study (wssGWAS) and copy number variation (CNV) analyses to map genetic variations and genes associated with loin muscle area (LMA), loin muscle depth (LMD) and lean meat percentage (LMP) in Duroc pigs. RESULTS Firstly, we performed a genome-wide analysis for CNV detection using GeneSeek Porcine SNP50 Bead chip data of 3770 pigs. A total of 11,100 CNVs were detected, which were aggregated by overlapping 695 CNV regions (CNVRs). Next, we investigated CNVs of pigs from the same population by whole-genome resequencing. A genome-wide analysis of 21 pigs revealed 23,856 CNVRs that were further divided into three categories (851 gain, 22,279 loss, and 726 mixed), which covered 190.8 Mb (~ 8.42%) of the pig autosomal genome. Further, the identified CNVRs were used to determine an overall validation rate of 68.5% for the CNV detection accuracy of chip data. CNVR association analyses identified one CNVR associated with LMA, one with LMD and eight with LMP after applying stringent Bonferroni correction. The wssGWAS identified eight, six and five regions explaining more than 1% of the additive genetic variance for LMA, LMD and LMP, respectively. The CNVR analyses and wssGWAS identified five common regions, of which three regions were associated with LMA and two with LMP. Four genes (DOK7, ARAP1, ELMO2 and SLC13A3) were highlighted as promising candidates according to their function. CONCLUSIONS We determined an overall validation rate for the CNV detection accuracy of low-density chip data and constructed a genomic CNV map for Duroc pigs using resequencing, thereby proving a value genetic variation resource for pig genome research. Furthermore, our study utilized a composite genetic strategy for complex traits in pigs, which will contribute to the study for elucidating the genetic architecture that may be influenced and regulated by multiple forms of variations.
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Affiliation(s)
- Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Guangdong Wens Breeding Swine Technology Co., Ltd, Guangdong, 527439, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Xingwang Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Cineng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Linjun Hong
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Ting Gu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China
| | - Wen Huang
- Department of Animal Science, Michigan State University, East Lansing, MI, USA
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China. .,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China.
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangdong, 510642, P.R. China. .,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, China.
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Malgwi IH, Halas V, Grünvald P, Schiavon S, Jócsák I. Genes Related to Fat Metabolism in Pigs and Intramuscular Fat Content of Pork: A Focus on Nutrigenetics and Nutrigenomics. Animals (Basel) 2022; 12:ani12020150. [PMID: 35049772 PMCID: PMC8772548 DOI: 10.3390/ani12020150] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 12/29/2021] [Accepted: 01/05/2022] [Indexed: 02/04/2023] Open
Abstract
Simple Summary The intramuscular fat (IMF) or marbling is an essential pork sensory quality that influences the preference of the consumers and premiums for pork. IMF is the streak of visible fat intermixed with the lean within a muscle fibre and determines sensorial qualities of pork such as flavour, tenderness and juiciness. Fat metabolism and IMF development are controlled by dietary nutrients, genes, and their metabolic pathways in the pig. Nutrigenetics explains how the genetic make-up of an individual pig influences the pig’s response to dietary nutrient intake. Differently, nutrigenomics is the analysis of how the entire genome of an individual pig is affected by dietary nutrient intake. The knowledge of nutrigenetics and nutrigenomics, when harmonized, is a powerful tool in estimating nutrient requirements for swine and programming dietary nutrient supply according to an individual pig’s genetic make-up. The current paper aimed to highlight the roles of nutrigenetics and nutrigenomics in elucidating the underlying mechanisms of fat metabolism and IMF deposition in pigs. This knowledge is essential in redefining nutritional intervention for swine production and the improvement of some economically important traits such as growth performance, backfat thickness, IMF accretion, disease resistance etc., in animals. Abstract Fat metabolism and intramuscular fat (IMF) are qualitative traits in pigs whose development are influenced by several genes and metabolic pathways. Nutrigenetics and nutrigenomics offer prospects in estimating nutrients required by a pig. Application of these emerging fields in nutritional science provides an opportunity for matching nutrients based on the genetic make-up of the pig for trait improvements. Today, integration of high throughput “omics” technologies into nutritional genomic research has revealed many quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs) for the mutation(s) of key genes directly or indirectly involved in fat metabolism and IMF deposition in pigs. Nutrient–gene interaction and the underlying molecular mechanisms involved in fatty acid synthesis and marbling in pigs is difficult to unravel. While existing knowledge on QTLs and SNPs of genes related to fat metabolism and IMF development is yet to be harmonized, the scientific explanations behind the nature of the existing correlation between the nutrients, the genes and the environment remain unclear, being inconclusive or lacking precision. This paper aimed to: (1) discuss nutrigenetics, nutrigenomics and epigenetic mechanisms controlling fat metabolism and IMF accretion in pigs; (2) highlight the potentials of these concepts in pig nutritional programming and research.
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Affiliation(s)
- Isaac Hyeladi Malgwi
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padua, Viale dell’ Università 16, 35020 Padova, Italy;
- Correspondence: ; Tel.: +39-33-17566768
| | - Veronika Halas
- Department of Farm Animal Nutrition, Kaposvár Campus, Hungarian University of Agriculture and Life Sciences, Guba Sándor Utca 40, 7400 Kaposvár, Hungary; (V.H.); (P.G.)
| | - Petra Grünvald
- Department of Farm Animal Nutrition, Kaposvár Campus, Hungarian University of Agriculture and Life Sciences, Guba Sándor Utca 40, 7400 Kaposvár, Hungary; (V.H.); (P.G.)
| | - Stefano Schiavon
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padua, Viale dell’ Università 16, 35020 Padova, Italy;
| | - Ildikó Jócsák
- Institute of Agronomy, Kaposvár Campus, Hungarian University of Agriculture and Life Sciences, Guba Sándor Utca 40, 7400 Kaposvár, Hungary;
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7
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Shen L, Gan M, Chen L, Zhao Y, Niu L, Tang G, Jiang Y, Zhang T, Zhang S, Zhu L. miR-152 targets pyruvate kinase to regulate the glycolytic activity of pig skeletal muscles and affects pork quality. Meat Sci 2021; 185:108707. [PMID: 35032684 DOI: 10.1016/j.meatsci.2021.108707] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/04/2021] [Accepted: 11/08/2021] [Indexed: 11/30/2022]
Abstract
As a type of non-coding RNA, microRNAs are widely involved in the biological processes of animals. In the present study, the expression of miR-152 in glycolytic muscle fibers (Longissimus thoracis, LT) was lower than that of oxidative muscle fibers (Psoas major, PM). Using dual luciferase assay, miR-152 was shown to target muscle pyruvate kinase (PKM) to perform biological functions. Moreover, overexpression of miR-152 in primary porcine cells inhibited PKM gene expression and reduced lactic acid production in cells, whereas inhibition of miR-152 expression promoted PKM gene expression and increased lactic acid production. Correlation analysis showed that the expression of miR-152 was significantly positively correlated with the ultimate pH of LT after slaughter, while the expression of the PKM gene was significantly negatively correlated with the final pH of LT. In vivo and in vitro experiments discussed herein suggest that miR-152 may affect muscle pH by targeting the expression of the PKM gene. Our findings enrich the understanding of the genetic regulatory network that influences pork quality.
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Affiliation(s)
- Linyuan Shen
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan 611130, China; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan 611130, China
| | - Mailin Gan
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan 611130, China; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan 611130, China
| | - Lei Chen
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan 611130, China; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan 611130, China
| | - Ye Zhao
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan 611130, China; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan 611130, China
| | - Lili Niu
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan 611130, China; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan 611130, China
| | - Guoqing Tang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan 611130, China; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan 611130, China
| | - Yanzhi Jiang
- College of Life Science, Sichuan Agricultural University, Ya'an, Sichuan 625014, China
| | - Tinghuan Zhang
- Chongqing Academy of Animal Science, Rongchang County, Chongqing 402460, China
| | - Shunhua Zhang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan 611130, China; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan 611130, China.
| | - Li Zhu
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, Sichuan 611130, China; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan 611130, China.
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8
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Johnsson M, Jungnickel MK. Evidence for and localization of proposed causative variants in cattle and pig genomes. Genet Sel Evol 2021; 53:67. [PMID: 34461824 PMCID: PMC8404348 DOI: 10.1186/s12711-021-00662-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 08/20/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND This paper reviews the localization of published potential causative variants in contemporary pig and cattle reference genomes, and the evidence for their causality. In spite of the difficulties inherent to the identification of causative variants from genetic mapping and genome-wide association studies, researchers in animal genetics have proposed putative causative variants for several traits relevant to livestock breeding. RESULTS For this review, we read the literature that supports potential causative variants in 13 genes (ABCG2, DGAT1, GHR, IGF2, MC4R, MSTN, NR6A1, PHGK1, PRKAG3, PLRL, RYR1, SYNGR2 and VRTN) in cattle and pigs, and localized them in contemporary reference genomes. We review the evidence for their causality, by aiming to separate the evidence for the locus, the proposed causative gene and the proposed causative variant, and report the bioinformatic searches and tactics needed to localize the sequence variants in the cattle or pig genome. CONCLUSIONS Taken together, there is usually good evidence for the association at the locus level, some evidence for a specific causative gene at eight of the loci, and some experimental evidence for a specific causative variant at six of the loci. We recommend that researchers who report new potential causative variants use referenced coordinate systems, show local sequence context, and submit variants to repositories.
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Affiliation(s)
- Martin Johnsson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 750 07 Uppsala, Sweden
| | - Melissa K. Jungnickel
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG Scotland, UK
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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: 17] [Impact Index Per Article: 5.7] [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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10
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Траспов АА, Костюнина ОВ, Белоус АА, Карпушкина ТВ, Свеженцева НА, Зиновьева НА. [Whole-genome association studies of distribution of developmental abnormalities and other breeding-valuable qualitative traits in offspring of the Russian large-white boars]. Vavilovskii Zhurnal Genet Selektsii 2021; 24:185-190. [PMID: 33659798 PMCID: PMC7716570 DOI: 10.18699/vj20.612] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Выявление областей генома, прямо или опосредованно связанных с признаками пороков развития у домашних свиней, может способствовать идентификации генетических мишеней, используемых в качестве биомаркеров индивидуальных особенностей формирования экстерьера, их метаболического статуса,
а также подверженности генетическим заболеваниям. Такие исследования напрямую связаны с повышением
экономической эффективности, поскольку позволяют выявлять и исключать из селекционного процесса животных-носителей нежелательных генов, фенотип которых может не проявляться. В данной работе проведен
поиск подобных целевых генов и геномных регионов с помощью полногеномных ассоциативных исследований
(GWAS) с использованием ДНК-чипов PorcineSNP60K BeadChips (Illumina, San Diego, USA). Проанализировано
48 хряков свиней крупной белой породы селекционно-гибридного центра «Знаменский» Орловской области
по 21 недостатку экстерьера и дефектам развития у 39 153 их потомков. Расчеты производили по линейной модели смешанного типа в программном пакете GEMMA. Из изначального сета в 61 000 SNP были отобраны 36 704
полиморфных SNP, в которых найдены 24 полиморфизма, входящих в 11 генов (P < 0.1), статистически значимо
коррелирующих с признаками аномалий развития в геноме свиней, такими как атрезия анального отверстия
(ARMC7, FANCC, RND3, ENSSSCG00000017216), проблемы с конечностями (PAWR, NTM, OPCML, ENSSSCG00000040250,
ENSSSCG00000017018) и тремор поросят (RIC3, ENSSSCG00000032665). Также была выявлена коэкспрессия генов
NTM, OPCML и RND3, участвующих в регуляции клеточной адгезии. Проведенная работа подтвердила актуальность применения подобного подхода в полногеномно-ассоциативных исследованиях для детектирования
единичных SNP, связанных с отдельными признаками, даже для небольших выборок.
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Affiliation(s)
- А А Траспов
- Федеральный научный центр животноводства - ВИЖ им. академика Л.К. Эрнста, пос. Дубровицы, Подольский городской округ, Московская область, Россия
| | - О В Костюнина
- Федеральный научный центр животноводства - ВИЖ им. академика Л.К. Эрнста, пос. Дубровицы, Подольский городской округ, Московская область, Россия
| | - А А Белоус
- Федеральный научный центр животноводства - ВИЖ им. академика Л.К. Эрнста, пос. Дубровицы, Подольский городской округ, Московская область, Россия
| | - Т В Карпушкина
- Федеральный научный центр животноводства - ВИЖ им. академика Л.К. Эрнста, пос. Дубровицы, Подольский городской округ, Московская область, Россия
| | - Н А Свеженцева
- Федеральный научный центр животноводства - ВИЖ им. академика Л.К. Эрнста, пос. Дубровицы, Подольский городской округ, Московская область, Россия
| | - Н А Зиновьева
- Федеральный научный центр животноводства - ВИЖ им. академика Л.К. Эрнста, пос. Дубровицы, Подольский городской округ, Московская область, Россия
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11
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He Y, Zhou X, Zheng R, Jiang Y, Yao Z, Wang X, Zhang Z, Zhang H, Li J, Yuan X. The Association of an SNP in the EXOC4 Gene and Reproductive Traits Suggests Its Use as a Breeding Marker in Pigs. Animals (Basel) 2021; 11:ani11020521. [PMID: 33671441 PMCID: PMC7921996 DOI: 10.3390/ani11020521] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 02/07/2021] [Accepted: 02/10/2021] [Indexed: 02/07/2023] Open
Abstract
In mammals, the exocyst complex component 4 (EXOC4) gene has often been reported to be involved in vesicle transport. The SNP rs81471943 (C/T) is located in the intron of porcine EXOC4, while six quantitative trait loci (QTL) within 5-10 Mb around EXOC4 are associated with ovary weight, teat number, total offspring born alive, and corpus luteum number. However, the molecular mechanisms between EXOC4 and the reproductive performance of pigs remains to be elucidated. In this study, rs81471943 was genotyped from a total of 994 Duroc sows, and the genotype and allele frequency of SNP rs81471943 (C/T) were statistically analyzed. Then, the associations between SNP rs81471943 and four reproductive traits, including number of piglets born alive (NBA), litter weight at birth (LWB), number of piglets weaned (NW), and litter weight at weaning (LWW), were determined. Sanger sequencing and PCR restriction fragment length polymorphism (PCR-RFLP) were utilized to identify the rs81471943 genotype. We found that the genotype frequency of CC was significantly higher than that of CT and TT, and CC was the most frequent genotype for NBA, LWB, NW, and LWW. Moreover, 5'-deletion and luciferase assays identified a positive transcription regulatory element in the EXOC4 promoter. After exploring the EXOC4 promoter, SNP -1781G/A linked with SNP rs81471943 (C/T) were identified by analysis of the transcription activity of the haplotypes, and SNP -1781 G/A may influence the potential binding of P53, E26 transformation specific sequence -like 1 transcription factor (ELK1), and myeloid zinc finger 1 (MZF1). These findings provide useful information for identifying a molecular marker of EXOC4-assisted selection in pig breeding.
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Affiliation(s)
- Yingting He
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
| | - Xiaofeng Zhou
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
| | - Rongrong Zheng
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
| | - Yao Jiang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
| | - Zhixiang Yao
- Guangdong Dexing Food Co., Ltd., Shantou 515100, China;
| | - Xilong Wang
- Guangdong Provincial Key Laboratory of Laboratory Animals, Guangdong Laboratory Animals Monitoring Institute, Guangzhou 510260, China;
| | - Zhe Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
| | - Hao Zhang
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
| | - Jiaqi Li
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
- Correspondence: (J.L.); (X.Y.)
| | - Xiaolong Yuan
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (Y.H.); (X.Z.); (R.Z.); (Y.J.); (Z.Z.); (H.Z.)
- Guangdong Provincial Key Laboratory of Laboratory Animals, Guangdong Laboratory Animals Monitoring Institute, Guangzhou 510260, China;
- Correspondence: (J.L.); (X.Y.)
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12
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Wang B, Xu CC, Liu C, Qu YH, Zhang H, Luo HL. The Effect of Dietary Lycopene Supplementation on Drip Loss during Storage of Lamb Meat by iTRAQ Analysis. Antioxidants (Basel) 2021; 10:198. [PMID: 33573002 PMCID: PMC7911479 DOI: 10.3390/antiox10020198] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 01/26/2021] [Accepted: 01/26/2021] [Indexed: 12/16/2022] Open
Abstract
This study was designed to investigate the impact of dietary lycopene (antioxidant extracted from tomato) supplementation on postmortem antioxidant capacity, drip loss and protein expression profiles of lamb meat during storage. Thirty male Hu lambs were randomly divided into three treatment groups and housed in individual pens and received 0, 200 or 400 mg·kg-1 lycopene in their diet, respectively. All lambs were slaughtered after 3 months of fattening, and the longissimus thoracis (LT) muscle was collected for analyses. The results indicated that drip loss of LT muscle increased with storage days (P < 0.05). After storage for 7 days, significantly lower drip loss of meat was found in fed the lycopene-supplemented diet (P < 0.05). Dietary lycopene supplementation increased the activity of antioxidant enzymes (total antioxidant capacity (T-AOC), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), catalase (CAT)) (P < 0.05) and decreased the thiobarbituric acid reactive substance (TBARS) and carbonyl contents (P < 0.05). During the storage period (days 0, 5 and 7), a number of differentially abundant proteins (DAPs), including oxidases, metabolic enzymes, calcium channels and structural proteins, were identified based on iTRAQ data, with roles predominantly in carbon metabolism, oxidative phosphorylation, cardiac muscle contraction and proteasome pathways, and which contribute to decreased drip loss of lamb meat during storage. It can be concluded that dietary lycopene supplementation increased antioxidant capacity after slaughter, and the decreased drip loss during postmortem storage might occur by changing the expression of proteins related to enzyme activity and cellular structure in lamb muscle.
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Affiliation(s)
- Bo Wang
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, NO.2 Yuanmingyuan West Road, Haidian, Beijing 100193, China; (B.W.); (C.-c.X.); (C.L.); (Y.-h.Q.)
| | - Chen-chen Xu
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, NO.2 Yuanmingyuan West Road, Haidian, Beijing 100193, China; (B.W.); (C.-c.X.); (C.L.); (Y.-h.Q.)
| | - Ce Liu
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, NO.2 Yuanmingyuan West Road, Haidian, Beijing 100193, China; (B.W.); (C.-c.X.); (C.L.); (Y.-h.Q.)
| | - Yang-hua Qu
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, NO.2 Yuanmingyuan West Road, Haidian, Beijing 100193, China; (B.W.); (C.-c.X.); (C.L.); (Y.-h.Q.)
| | - Hao Zhang
- Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Food Science and Nutritional Engineering, China Agricultural University, No.17 Qinghua East Road, Haidian, Beijing 100083, China;
| | - Hai-ling Luo
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, NO.2 Yuanmingyuan West Road, Haidian, Beijing 100193, China; (B.W.); (C.-c.X.); (C.L.); (Y.-h.Q.)
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13
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Fonseca PAS, Suárez-Vega A, Marras G, Cánovas Á. GALLO: An R package for genomic annotation and integration of multiple data sources in livestock for positional candidate loci. Gigascience 2020; 9:giaa149. [PMID: 33377911 PMCID: PMC7772745 DOI: 10.1093/gigascience/giaa149] [Citation(s) in RCA: 86] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 10/26/2020] [Accepted: 11/24/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The development of high-throughput sequencing and genotyping methodologies has enabled the identification of thousands of genomic regions associated with several complex traits. The integration of multiple sources of biological information is a crucial step required to better understand patterns regulating the development of these traits. FINDINGS Genomic Annotation in Livestock for positional candidate LOci (GALLO) is an R package developed for the accurate annotation of genes and quantitative trait loci (QTLs) located in regions identified in common genomic analyses performed in livestock, such as genome-wide association studies and transcriptomics using RNA sequencing. Moreover, GALLO allows the graphical visualization of gene and QTL annotation results, data comparison among different grouping factors (e.g., methods, breeds, tissues, statistical models, studies), and QTL enrichment in different livestock species such as cattle, pigs, sheep, and chickens. CONCLUSIONS Consequently, GALLO is a useful package for annotation, identification of hidden patterns across datasets, and data mining previously reported associations, as well as the efficient examination of the genetic architecture of complex traits in livestock.
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Affiliation(s)
- Pablo A S Fonseca
- University of Guelph, Department of Animal Biosciences, Centre for Genetic Improvement of Livestock, 50 Stone Rd E, Guelph N1G 2W1, ONT, Canada
| | - Aroa Suárez-Vega
- University of Guelph, Department of Animal Biosciences, Centre for Genetic Improvement of Livestock, 50 Stone Rd E, Guelph N1G 2W1, ONT, Canada
| | - Gabriele Marras
- University of Guelph, Department of Animal Biosciences, Centre for Genetic Improvement of Livestock, 50 Stone Rd E, Guelph N1G 2W1, ONT, Canada
- The Semex Alliance, 5653 ON-6, Guelph N1G 3Z2, ONT, Canada
| | - Ángela Cánovas
- University of Guelph, Department of Animal Biosciences, Centre for Genetic Improvement of Livestock, 50 Stone Rd E, Guelph N1G 2W1, ONT, Canada
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14
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Genetic parameters and associated genomic regions for global immunocompetence and other health-related traits in pigs. Sci Rep 2020; 10:18462. [PMID: 33116177 PMCID: PMC7595139 DOI: 10.1038/s41598-020-75417-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 10/15/2020] [Indexed: 12/16/2022] Open
Abstract
The inclusion of health-related traits, or functionally associated genetic markers, in pig breeding programs could contribute to produce more robust and disease resistant animals. The aim of the present work was to study the genetic determinism and genomic regions associated to global immunocompetence and health in a Duroc pig population. For this purpose, a set of 30 health-related traits covering immune (mainly innate), haematological, and stress parameters were measured in 432 healthy Duroc piglets aged 8 weeks. Moderate to high heritabilities were obtained for most traits and significant genetic correlations among them were observed. A genome wide association study pointed out 31 significantly associated SNPs at whole-genome level, located in six chromosomal regions on pig chromosomes SSC4, SSC6, SSC17 and SSCX, for IgG, γδ T-cells, C-reactive protein, lymphocytes phagocytic capacity, total number of lymphocytes, mean corpuscular volume and mean corpuscular haemoglobin. A total of 16 promising functionally-related candidate genes, including CRP, NFATC2, PRDX1, SLA, ST3GAL1, and VPS4A, have been proposed to explain the variation of immune and haematological traits. Our results enhance the knowledge of the genetic control of traits related with immunity and support the possibility of applying effective selection programs to improve immunocompetence in pigs.
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15
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Phenotyping of the Visceral Adipose Tissue Using Dual Energy X-Ray Absorptiometry (DXA) and Magnetic Resonance Imaging (MRI) in Pigs. Animals (Basel) 2020; 10:ani10071165. [PMID: 32660013 PMCID: PMC7401593 DOI: 10.3390/ani10071165] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 06/22/2020] [Accepted: 07/06/2020] [Indexed: 02/07/2023] Open
Abstract
The objective of this study was to phenotype visceral adipose tissue (VAT) in pigs. In this context, the ability to detect VAT by using the DXA CoreScan mode within the enCORE software, version 17 (GE Healthcare) was evaluated in comparison with MRI measurements (Siemens Magnetom C!) of the same body region. A number of 120 crossbred pigs of the F1 and F2 generation, with the parental breeds Large White, Landrace, Piétrain, and Duroc, were examined at an age of 150 days. A whole-body scan in two different modes ("thick", "standard") was carried out by a GE Lunar iDXA scanner. Very strong relationships (R2 = 0.95, RMSE = 175cm3) were found for VAT between the two DXA modes. The comparison of VAT measured by MRI and DXA shows high linear relationships ("thick": R2 = 0.76, RMSE = 399.25cm3/"standard": R2 = 0.71, RMSE = 443.42cm3), but is biased, according to the Bland-Altman analysis. A variance analysis of VAT shows significant differences for both DXA modes and for MRI between male and female pigs, as well as between F1 and F2. In conclusion, DXA "CoreScan" has the ability to estimate VAT in pigs with a close relationship to MRI but needs bias correction.
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16
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Zhuang Z, Ding R, Peng L, Wu J, Ye Y, Zhou S, Wang X, Quan J, Zheng E, Cai G, Huang W, Yang J, Wu Z. Genome-wide association analyses identify known and novel loci for teat number in Duroc pigs using single-locus and multi-locus models. BMC Genomics 2020; 21:344. [PMID: 32380955 PMCID: PMC7204245 DOI: 10.1186/s12864-020-6742-6] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Accepted: 04/16/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND More teats are necessary for sows to nurse larger litters to provide immunity and nutrient for piglets prior to weaning. Previous studies have reported the strong effect of an insertion mutation in the Vertebrae Development Associated (VRTN) gene on Sus scrofa chromosome 7 (SSC7) that increased the number of thoracic vertebrae and teat number in pigs. We used genome-wide association studies (GWAS) to map genetic markers and genes associated with teat number in two Duroc pig populations with different genetic backgrounds. A single marker method and several multi-locus methods were utilized. A meta-analysis that combined the effects and P-values of 34,681 single nucleotide polymorphisms (SNPs) that were common in the results of single marker GWAS of American and Canadian Duroc pigs was conducted. We also performed association tests between the VRTN insertion and teat number in the same populations. RESULTS A total of 97 SNPs were found to be associated with teat number. Among these, six, eight and seven SNPs were consistently detected with two, three and four multi-locus methods, respectively. Seven SNPs were concordantly identified between single marker and multi-locus methods. Moreover, 26 SNPs were newly found by multi-locus methods to be associated with teat number. Notably, we detected one consistent quantitative trait locus (QTL) on SSC7 for teat number using single-locus and meta-analysis of GWAS and the top SNP (rs692640845) explained 8.68% phenotypic variance of teat number in the Canadian Duroc pigs. The associations between the VRTN insertion and teat number in two Duroc pig populations were substantially weaker. Further analysis revealed that the effect of VRTN on teat number may be mediated by its LD with the true causal mutation. CONCLUSIONS Our study suggested that VRTN insertion may not be a strong or the only candidate causal mutation for the QTL on SSC7 for teat number in the analyzed Duroc pig populations. The combination of single-locus and multi-locus GWAS detected additional SNPs that were absent using only one model. The identified SNPs will be useful for the genetic improvement of teat number in pigs by assigning higher weights to associated SNPs in genomic selection.
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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, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Longlong Peng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Yong Ye
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Xingwang Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Wen Huang
- Department of animal science, Michigan State University, East Lansing, MI, USA
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China.
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China.
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17
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Luan MW, Chen W, Xing JF, Xiao CL, Chen Y, Xie SQ. DNA N6-Methyladenosine modification role in transmitted variations from genomic DNA to RNA in Herrania umbratica. BMC Genomics 2019; 20:508. [PMID: 31215402 PMCID: PMC6582544 DOI: 10.1186/s12864-019-5776-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 05/07/2019] [Indexed: 11/16/2022] Open
Abstract
Background DNA methylation is an important epigenetic modification. Recently the developed single-molecule real-time (SMRT) sequencing technology provided an efficient way to detect DNA N6-methyladenine (6mA) modification that played an important role in epigenetic and positively regulated gene expression. In addition, the gene expression was also regulated by genetic variation. However, the relationship between DNA 6mA modification and variation is still unknown. Results We collected the SMRT long-reads DNA, Illumina short reads DNA and RNA datasets from the young leaves of Herrania umbratica, and used them to detect 35,654 6mA modification sites, 829,894 DNA variations and 60,672 RNA variations respectively, among which, there are 303 DNA variations and 19 RNA variations with 6mA modification, and 57,468 transmitted genetic variations from DNA to RNA. The results illustrated that the genes with 6mA modification were significant disadvantage to mutate than those genes without modification (p-value< 4.9e-08). And result from the linear regression model showed the 6mA densities of genes were associated with the transmitted variations type 0/1 to 1/1 (p-value < 0.001). Conclusions The variations of DNA and RNA in genes with 6mA modification were significant less than those in unmodified genes. Furthermore, the variations in 6mA modified genes were easily transmitted from DNA to RNA, especially the transmitted variation from DNA heterozygote to RNA homozygote. Electronic supplementary material The online version of this article (10.1186/s12864-019-5776-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Mei-Wei Luan
- Research Center for Terrestrial Biodiversity of the South China Sea, Hainan Key Laboratory for Biology of Tropical Ornamental Plant Germplasm, Natural Rubber Cooperative Innovation Centre of Hainan Province & Ministry of Education of China, Hainan University, Haikou, 570228, China
| | - Wei Chen
- Research Center for Terrestrial Biodiversity of the South China Sea, Hainan Key Laboratory for Biology of Tropical Ornamental Plant Germplasm, Natural Rubber Cooperative Innovation Centre of Hainan Province & Ministry of Education of China, Hainan University, Haikou, 570228, China
| | - Jian-Feng Xing
- Research Center for Terrestrial Biodiversity of the South China Sea, Hainan Key Laboratory for Biology of Tropical Ornamental Plant Germplasm, Natural Rubber Cooperative Innovation Centre of Hainan Province & Ministry of Education of China, Hainan University, Haikou, 570228, China
| | - Chuan-Le Xiao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, 510060, China
| | - Ying Chen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, 510060, China.
| | - Shang-Qian Xie
- Research Center for Terrestrial Biodiversity of the South China Sea, Hainan Key Laboratory for Biology of Tropical Ornamental Plant Germplasm, Natural Rubber Cooperative Innovation Centre of Hainan Province & Ministry of Education of China, Hainan University, Haikou, 570228, China.
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18
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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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19
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20
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Genome-wide association studies and meta-analysis uncovers new candidate genes for growth and carcass traits in pigs. PLoS One 2018; 13:e0205576. [PMID: 30308042 PMCID: PMC6181390 DOI: 10.1371/journal.pone.0205576] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Accepted: 09/27/2018] [Indexed: 11/19/2022] Open
Abstract
Genome-wide association studies (GWAS) have been widely used in the genetic dissection of complex traits. As more genomic data is being generated within different commercial or resource pig populations, the challenge which arises is how to collectively investigate the data with the purpose to increase sample size and implicitly the statistical power. This study performs an individual population GWAS, a joint population GWAS and a meta-analysis in three pig F2 populations. D1 is derived from European type breeds (Piétrain, Large White and Landrace), D2 is obtained from an Asian breed (Meishan) and Piétrain, and D3 stems from a European Wild Boar and Piétrain, which is the common founder breed. The traits investigated are average daily gain, backfat thickness, meat to fat ratio and carcass length. The joint and the meta-analysis did not identify additional genomic clusters besides the ones discovered via the individual population GWAS. However, the benefit was an increased mapping resolution which pinpointed to narrower clusters harboring causative variants. The joint analysis identified a higher number of clusters as compared to the meta-analysis; nevertheless, the significance levels and the number of significant variants in the meta-analysis were generally higher. Both types of analysis had similar outputs suggesting that the two strategies can complement each other and that the meta-analysis approach can be a valuable tool whenever access to raw datasets is limited. Overall, a total of 20 genomic clusters that predominantly overlapped at various extents, were identified on chromosomes 2, 7 and 17, many confirming previously identified quantitative trait loci. Several new candidate genes are being proposed and, among them, a strong candidate gene to be taken into account for subsequent analysis is BMP2 (bone morphogenetic protein 2).
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21
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Li Z, Kemppainen P, Rastas P, Merilä J. Linkage disequilibrium clustering‐based approach for association mapping with tightly linked genomewide data. Mol Ecol Resour 2018; 18:809-824. [DOI: 10.1111/1755-0998.12893] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2017] [Revised: 04/05/2018] [Accepted: 04/06/2018] [Indexed: 02/05/2023]
Affiliation(s)
- Zitong Li
- Ecological Genetics Research Unit Research Programme in Organismal and Evolutionary Biology Faculty of Biological and Environmental Sciences Department of Biosciences University of Helsinki Helsinki Finland
| | - Petri Kemppainen
- Ecological Genetics Research Unit Research Programme in Organismal and Evolutionary Biology Faculty of Biological and Environmental Sciences Department of Biosciences University of Helsinki Helsinki Finland
| | - Pasi Rastas
- Ecological Genetics Research Unit Research Programme in Organismal and Evolutionary Biology Faculty of Biological and Environmental Sciences Department of Biosciences University of Helsinki Helsinki Finland
| | - Juha Merilä
- Ecological Genetics Research Unit Research Programme in Organismal and Evolutionary Biology Faculty of Biological and Environmental Sciences Department of Biosciences University of Helsinki Helsinki Finland
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22
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The effect of QTL-rich region polymorphisms identified by targeted DNA-seq on pig production traits. Mol Biol Rep 2018; 45:361-371. [PMID: 29623566 PMCID: PMC5966500 DOI: 10.1007/s11033-018-4170-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Accepted: 03/24/2018] [Indexed: 12/27/2022]
Abstract
The aim of the present study was to analyse the effect of PLCD4, PECR, FN1 and PNKD mutations on pig productive traits and tested the usefulness of targeted enrichment DNA sequencing method as tool for preselection of genetic markers. The potential genetic markers for pig productive traits were identified by using targeted enrichment DNA sequencing of chromosome 15 region that is QTL-rich. The selected mutations were genotyped by using HRM, Sanger sequencing and PCR-ACRS methods. The association study was performed by using GLM model in SAS program and included over 500 pigs of 5 populations maintained in Poland. The variation (C/T) of PLCD4 gene affected feed conversion, intramuscular fat and water exudation. The PNKD mutations were associated with texture parameters measured after cooking. In turn, the variation rs792423408 (C/T) in the FN1 gene influenced toughness measured in semimembranosus muscle and growth traits that was observed particularly in Duroc breed. Summarizing, the investigated gene variants delivered valuable information that could be used during developing SNP microarray for genomic estimated breeding value procedure in pigs. Moreover, the study showed that the TEDNA-seq method could be used to preselect the molecular markers associated with pig traits. However, the further association study that included large number animal populations is necessary.
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23
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Wei W, Li B, Liu K, Jiang A, Dong C, Jia C, Chen J, Liu H, Wu W. Identification of key microRNAs affecting drip loss in porcine longissimus dorsi by RNA-Seq. Gene 2018; 647:276-282. [DOI: 10.1016/j.gene.2018.01.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Revised: 09/28/2017] [Accepted: 01/02/2018] [Indexed: 12/27/2022]
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24
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Drag M, Hansen MB, Kadarmideen HN. Systems genomics study reveals expression quantitative trait loci, regulator genes and pathways associated with boar taint in pigs. PLoS One 2018; 13:e0192673. [PMID: 29438444 PMCID: PMC5811030 DOI: 10.1371/journal.pone.0192673] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Accepted: 01/29/2018] [Indexed: 01/14/2023] Open
Abstract
Boar taint is an offensive odour and/or taste from a proportion of non-castrated male pigs caused by skatole and androstenone accumulation during sexual maturity. Castration is widely used to avoid boar taint but is currently under debate because of animal welfare concerns. This study aimed to identify expression quantitative trait loci (eQTLs) with potential effects on boar taint compounds to improve breeding possibilities for reduced boar taint. Danish Landrace male boars with low, medium and high genetic merit for skatole and human nose score (HNS) were slaughtered at ~100 kg. Gene expression profiles were obtained by RNA-Seq, and genotype data were obtained by an Illumina 60K Porcine SNP chip. Following quality control and filtering, 10,545 and 12,731 genes from liver and testis were included in the eQTL analysis, together with 20,827 SNP variants. A total of 205 and 109 single-tissue eQTLs associated with 102 and 58 unique genes were identified in liver and testis, respectively. By employing a multivariate Bayesian hierarchical model, 26 eQTLs were identified as significant multi-tissue eQTLs. The highest densities of eQTLs were found on pig chromosomes SSC12, SSC1, SSC13, SSC9 and SSC14. Functional characterisation of eQTLs revealed functions within regulation of androgen and the intracellular steroid hormone receptor signalling pathway and of xenobiotic metabolism by cytochrome P450 system and cellular response to oestradiol. A QTL enrichment test revealed 89 QTL traits curated by the Animal Genome PigQTL database to be significantly overlapped by the genomic coordinates of cis-acting eQTLs. Finally, a subset of 35 cis-acting eQTLs overlapped with known boar taint QTL traits. These eQTLs could be useful in the development of a DNA test for boar taint but careful monitoring of other overlapping QTL traits should be performed to avoid any negative consequences of selection.
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Affiliation(s)
- Markus Drag
- Section of Anatomy, Biochemistry and Physiology, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark
| | - Mathias B. Hansen
- Section of Anatomy, Biochemistry and Physiology, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark
| | - Haja N. Kadarmideen
- Section of Anatomy, Biochemistry and Physiology, Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark
- Section of Systems Genomics, Department of Bio and Health Informatics, Technical University of Denmark, Kemitorvet, Lyngby, Denmark
- * E-mail:
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25
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Ha J, Kwon S, Hwang JH, Park DH, Kim TW, Kang DG, Yu GE, Park HC, An SM, Kim CW. Squalene epoxidase plays a critical role in determining pig meat quality by regulating adipogenesis, myogenesis, and ROS scavengers. Sci Rep 2017; 7:16740. [PMID: 29196684 PMCID: PMC5711910 DOI: 10.1038/s41598-017-16979-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Accepted: 11/20/2017] [Indexed: 11/17/2022] Open
Abstract
In mammals, Squalene epoxidase (SQLE) is an enzyme that converts squalene to 2,3-oxidosqualene, in the early stage of cholesterol generation. Here, we identified single nucleotide polymorphisms (SNPs) in the SQLE gene (c.2565 G > T) by RNA Sequencing from the liver tissue of Berkshire pigs. Furthermore, we found that homozygous GG pigs expressed more SQLE mRNA than GT heterozygous and TT homozygous pigs in longissimus dorsi tissue. Next, we showed that the SNP in the SQLE gene was associated with several meat quality traits including backfat thickness, carcass weight, meat colour (yellowness), fat composition, and water-holding capacity. Rates of myogenesis and adipogenesis induced in C2C12 cells and 3T3-L1 cells, respectively, were decreased by Sqle knockdown. Additionally, the expression of myogenic marker genes (Myog, Myod, and Myh4) and adipogenic marker genes (Pparg, Cebpa, and Adipoq) was substantially downregulated in cells transfected with Sqle siRNA. Moreover, mRNA expression levels of ROS scavengers, which affect meat quality by altering protein oxidation processes, were significantly downregulated by Sqle knockdown. Taken together, our results suggest the molecular mechanism by which SNPs in the SQLE gene can affect meat quality.
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Affiliation(s)
- Jeongim Ha
- Swine Science and Technology Center, Gyeongnam National University of Science & Technology, Jinju, South Korea
| | - Seulgi Kwon
- Swine Science and Technology Center, Gyeongnam National University of Science & Technology, Jinju, South Korea
| | - Jung Hye Hwang
- Swine Science and Technology Center, Gyeongnam National University of Science & Technology, Jinju, South Korea
| | - Da Hye Park
- Swine Science and Technology Center, Gyeongnam National University of Science & Technology, Jinju, South Korea
| | - Tae Wan Kim
- Swine Science and Technology Center, Gyeongnam National University of Science & Technology, Jinju, South Korea
| | - Deok Gyeong Kang
- Swine Science and Technology Center, Gyeongnam National University of Science & Technology, Jinju, South Korea
| | - Go Eun Yu
- Swine Science and Technology Center, Gyeongnam National University of Science & Technology, Jinju, South Korea
| | | | - Sang Mi An
- Swine Science and Technology Center, Gyeongnam National University of Science & Technology, Jinju, South Korea
| | - Chul Wook Kim
- Swine Science and Technology Center, Gyeongnam National University of Science & Technology, Jinju, South Korea.
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26
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Hai T, Cao C, Shang H, Guo W, Mu Y, Yang S, Zhang Y, Zheng Q, Zhang T, Wang X, Liu Y, Kong Q, Li K, Wang D, Qi M, Hong Q, Zhang R, Wang X, Jia Q, Wang X, Qin G, Li Y, Luo A, Jin W, Yao J, Huang J, Zhang H, Li M, Xie X, Zheng X, Guo K, Wang Q, Zhang S, Li L, Xie F, Zhang Y, Weng X, Yin Z, Hu K, Cong Y, Zheng P, Zou H, Xin L, Xia J, Ruan J, Li H, Zhao W, Yuan J, Liu Z, Gu W, Li M, Wang Y, Wang H, Yang S, Liu Z, Wei H, Zhao J, Zhou Q, Meng A. Pilot study of large-scale production of mutant pigs by ENU mutagenesis. eLife 2017. [PMID: 28639938 PMCID: PMC5505698 DOI: 10.7554/elife.26248] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
N-ethyl-N-nitrosourea (ENU) mutagenesis is a powerful tool to generate mutants on a large scale efficiently, and to discover genes with novel functions at the whole-genome level in Caenorhabditis elegans, flies, zebrafish and mice, but it has never been tried in large model animals. We describe a successful systematic three-generation ENU mutagenesis screening in pigs with the establishment of the Chinese Swine Mutagenesis Consortium. A total of 6,770 G1 and 6,800 G3 pigs were screened, 36 dominant and 91 recessive novel pig families with various phenotypes were established. The causative mutations in 10 mutant families were further mapped. As examples, the mutation of SOX10 (R109W) in pig causes inner ear malfunctions and mimics human Mondini dysplasia, and upregulated expression of FBXO32 is associated with congenital splay legs. This study demonstrates the feasibility of artificial random mutagenesis in pigs and opens an avenue for generating a reservoir of mutants for agricultural production and biomedical research. DOI:http://dx.doi.org/10.7554/eLife.26248.001
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Affiliation(s)
- Tang Hai
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Chunwei Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Haitao Shang
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Department of Laboratory Animal Science, College of Basic Medicine, Third Military Medical University, Chongqing, China
| | - Weiwei Guo
- Department of Otolaryngology-Head and Neck Surgery, Institute of Otolaryngology, Chinese PLA General Hospital, Beijing, China
| | - Yanshuang Mu
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,College of Life Science, Northeast Agricultural University of China, Harbin, China
| | - Shulin Yang
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Ying Zhang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Qiantao Zheng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Tao Zhang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Xianlong Wang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Yu Liu
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Department of Laboratory Animal Science, College of Basic Medicine, Third Military Medical University, Chongqing, China
| | - Qingran Kong
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,College of Life Science, Northeast Agricultural University of China, Harbin, China
| | - Kui Li
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Dayu Wang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Meng Qi
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Qianlong Hong
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Rui Zhang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Xiupeng Wang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Qitao Jia
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Xiao Wang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Guosong Qin
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Yongshun Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Ailing Luo
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Weiwu Jin
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Jing Yao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Jiaojiao Huang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Hongyong Zhang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Menghua Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Xiangmo Xie
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Xuejuan Zheng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Kenan Guo
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Department of Laboratory Animal Science, College of Basic Medicine, Third Military Medical University, Chongqing, China
| | - Qinghua Wang
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Department of Laboratory Animal Science, College of Basic Medicine, Third Military Medical University, Chongqing, China
| | - Shibin Zhang
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Department of Laboratory Animal Science, College of Basic Medicine, Third Military Medical University, Chongqing, China
| | - Liang Li
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Department of Laboratory Animal Science, College of Basic Medicine, Third Military Medical University, Chongqing, China
| | - Fei Xie
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Department of Laboratory Animal Science, College of Basic Medicine, Third Military Medical University, Chongqing, China
| | - Yu Zhang
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,College of Life Science, Northeast Agricultural University of China, Harbin, China
| | - Xiaogang Weng
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,College of Life Science, Northeast Agricultural University of China, Harbin, China
| | - Zhi Yin
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,College of Life Science, Northeast Agricultural University of China, Harbin, China
| | - Kui Hu
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,College of Life Science, Northeast Agricultural University of China, Harbin, China
| | - Yimei Cong
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,College of Life Science, Northeast Agricultural University of China, Harbin, China
| | - Peng Zheng
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,College of Life Science, Northeast Agricultural University of China, Harbin, China
| | - Hailong Zou
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,College of Life Science, Northeast Agricultural University of China, Harbin, China
| | - Leilei Xin
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jihan Xia
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jinxue Ruan
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hegang Li
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Weiming Zhao
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jing Yuan
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zizhan Liu
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Weiwang Gu
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Pearl Laboratory Animal Sci. & Tech. Co. Ltd, Guangzhou, China
| | - Ming Li
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Pearl Laboratory Animal Sci. & Tech. Co. Ltd, Guangzhou, China
| | - Yong Wang
- Chinese Swine Mutagenesis Consortium Working Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,Department of Laboratory Animal Science, College of Basic Medicine, Third Military Medical University, Chongqing, China
| | - Hongmei Wang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Guide Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Shiming Yang
- Department of Otolaryngology-Head and Neck Surgery, Institute of Otolaryngology, Chinese PLA General Hospital, Beijing, China.,Chinese Swine Mutagenesis Consortium Guide Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Zhonghua Liu
- College of Life Science, Northeast Agricultural University of China, Harbin, China.,Chinese Swine Mutagenesis Consortium Guide Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Hong Wei
- Department of Laboratory Animal Science, College of Basic Medicine, Third Military Medical University, Chongqing, China.,Chinese Swine Mutagenesis Consortium Guide Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Jianguo Zhao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Guide Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Qi Zhou
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.,Chinese Swine Mutagenesis Consortium Guide Group, Chinese Swine Mutagenesis Consortium, Beijing, China
| | - Anming Meng
- Chinese Swine Mutagenesis Consortium Guide Group, Chinese Swine Mutagenesis Consortium, Beijing, China.,School of Life Sciences, Tsinghua University, Beijing, China
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27
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Li Z, Guo B, Yang J, Herczeg G, Gonda A, Balázs G, Shikano T, Calboli FCF, Merilä J. Deciphering the genomic architecture of the stickleback brain with a novel multilocus gene-mapping approach. Mol Ecol 2017; 26:1557-1575. [DOI: 10.1111/mec.14005] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2016] [Revised: 11/11/2016] [Accepted: 11/14/2016] [Indexed: 12/24/2022]
Affiliation(s)
- Zitong Li
- Ecological Genetics Research Unit; Department of Biosciences; University of Helsinki; P.O. Box 65 FI-00014 Helsinki Finland
| | - Baocheng Guo
- Ecological Genetics Research Unit; Department of Biosciences; University of Helsinki; P.O. Box 65 FI-00014 Helsinki Finland
| | - Jing Yang
- Ecological Genetics Research Unit; Department of Biosciences; University of Helsinki; P.O. Box 65 FI-00014 Helsinki Finland
| | - Gábor Herczeg
- Ecological Genetics Research Unit; Department of Biosciences; University of Helsinki; P.O. Box 65 FI-00014 Helsinki Finland
- Behavioural Ecology Group; Department of Systematic Zoology and Ecology; Eötvös Loránd University; Pázmány Péter sétány1/C 1117 Budapest Hungary
| | - Abigél Gonda
- Ecological Genetics Research Unit; Department of Biosciences; University of Helsinki; P.O. Box 65 FI-00014 Helsinki Finland
| | - Gergely Balázs
- Behavioural Ecology Group; Department of Systematic Zoology and Ecology; Eötvös Loránd University; Pázmány Péter sétány1/C 1117 Budapest Hungary
| | - Takahito Shikano
- Ecological Genetics Research Unit; Department of Biosciences; University of Helsinki; P.O. Box 65 FI-00014 Helsinki Finland
| | - Federico C. F. Calboli
- Ecological Genetics Research Unit; Department of Biosciences; University of Helsinki; P.O. Box 65 FI-00014 Helsinki Finland
| | - Juha Merilä
- Ecological Genetics Research Unit; Department of Biosciences; University of Helsinki; P.O. Box 65 FI-00014 Helsinki Finland
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28
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González-Prendes R, Quintanilla R, Cánovas A, Manunza A, Figueiredo Cardoso T, Jordana J, Noguera JL, Pena RN, Amills M. Joint QTL mapping and gene expression analysis identify positional candidate genes influencing pork quality traits. Sci Rep 2017; 7:39830. [PMID: 28054563 PMCID: PMC5215505 DOI: 10.1038/srep39830] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2016] [Accepted: 11/29/2016] [Indexed: 12/28/2022] Open
Abstract
Meat quality traits have an increasing importance in the pig industry because of their strong impact on consumer acceptance. Herewith, we have combined phenotypic and microarray expression data to map loci with potential effects on five meat quality traits recorded in the longissimus dorsi (LD) and gluteus medius (GM) muscles of 350 Duroc pigs, i.e. pH at 24 hours post-mortem (pH24), electric conductivity (CE) and muscle redness (a*), lightness (L*) and yellowness (b*). We have found significant genome-wide associations for CE of LD on SSC4 (~104 Mb), SSC5 (~15 Mb) and SSC13 (~137 Mb), while several additional regions were significantly associated with meat quality traits at the chromosome-wide level. There was a low positional concordance between the associations found for LD and GM traits, a feature that reflects the existence of differences in the genetic determinism of meat quality phenotypes in these two muscles. The performance of an eQTL search for SNPs mapping to the regions associated with meat quality traits demonstrated that the GM a* SSC3 and pH24 SSC17 QTL display positional concordance with cis-eQTL regulating the expression of several genes with a potential role on muscle metabolism.
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Affiliation(s)
- Rayner González-Prendes
- Center for Research in Agricultural Genomics (CSIC-IRTA-UAB-UB), Campus Universitat Autònoma de Barcelona, Bellaterra 08193, Spain
| | - Raquel Quintanilla
- Animal Breeding and Genetics Program, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Torre Marimon, Caldes de Montbui 08140, Spain
| | - Angela Cánovas
- Center for Research in Agricultural Genomics (CSIC-IRTA-UAB-UB), Campus Universitat Autònoma de Barcelona, Bellaterra 08193, Spain
| | - Arianna Manunza
- Center for Research in Agricultural Genomics (CSIC-IRTA-UAB-UB), Campus Universitat Autònoma de Barcelona, Bellaterra 08193, Spain
| | - Tainã Figueiredo Cardoso
- Center for Research in Agricultural Genomics (CSIC-IRTA-UAB-UB), Campus Universitat Autònoma de Barcelona, Bellaterra 08193, Spain.,CAPES Foundation, Ministry of Education of Brazil, Brasilia D. F., Zip Code 70.040-020, Brazil
| | - Jordi Jordana
- Departament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain
| | - José Luis Noguera
- Animal Breeding and Genetics Program, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Torre Marimon, Caldes de Montbui 08140, Spain
| | - Ramona N Pena
- Department of Animal Science, University of Lleida - Agrotecnio Center, Lleida 25198, Spain
| | - Marcel Amills
- Center for Research in Agricultural Genomics (CSIC-IRTA-UAB-UB), Campus Universitat Autònoma de Barcelona, Bellaterra 08193, Spain
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29
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Lim KS, Lee KT, Lee SW, Chai HH, Jang G, Hong KC, Kim TH. Genomic structure, expression and association study of the porcine FSD2. Mol Biol Rep 2016; 43:1011-8. [PMID: 27350214 DOI: 10.1007/s11033-016-4029-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Accepted: 06/13/2016] [Indexed: 10/21/2022]
Abstract
The fibronectin type III and SPRY domain containing 2 (FSD2) on porcine chromosome 7 is considered a candidate gene for pork quality, since its two domains, which were present in fibronectin and ryanodine receptor. The fibronectin type III and SPRY domains were first identified in fibronectin and ryanodine receptor, respectively, which are candidate genes for meat quality. The aim of this study was to elucidate the genomic structure of FSD2 and functions of single nucleotide polymorphisms (SNPs) within FSD2 that are related to meat quality in pigs. Using a bacterial artificial chromosome clone sequence, we revealed that porcine FSD2 consisted of 13 exons encoding 750 amino acids. In addition, FSD2 was expressed in heart, longissimus dorsi muscle, psoas muscle, and tendon among 23 kinds of porcine tissues tested. A total of ten SNPs, including four missense mutations, were identified in the exonic region of FSD2, and two major haplotypes were obtained based on the SNP genotypes of 633 Berkshire pigs. Both haplotypes were associated significantly with intramuscular fat content (IMF, P < 0.020) and moisture percentage (MP, P < 0.002). Moreover, haplotype 2 was associated with meat color, affecting yellowness (P = 0.002). These haplotype effects were further supported by the alteration of putative protein structures with amino acid substitutions. Taken together, our results suggest that FSD2 haplotypes are involved in regulating meat quality including IMF, MP, and meat color in pigs, and may be used as meaningful molecular makers to identify pigs with preferable pork quality.
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Affiliation(s)
- Kyu-Sang Lim
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, 1500 Kongjwipatjwi, Iseo, Wanju, 565-851, Korea.,College of Life Science and Biotechnology, Korea University, Seoul, 136-713, Korea
| | - Kyung-Tai Lee
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, 1500 Kongjwipatjwi, Iseo, Wanju, 565-851, Korea
| | - Si-Woo Lee
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, 1500 Kongjwipatjwi, Iseo, Wanju, 565-851, Korea
| | - Han-Ha Chai
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, 1500 Kongjwipatjwi, Iseo, Wanju, 565-851, Korea
| | - Gulwon Jang
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, 1500 Kongjwipatjwi, Iseo, Wanju, 565-851, Korea
| | - Ki-Chang Hong
- College of Life Science and Biotechnology, Korea University, Seoul, 136-713, Korea
| | - Tae-Hun Kim
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, 1500 Kongjwipatjwi, Iseo, Wanju, 565-851, Korea.
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30
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Samorè AB, Fontanesi L. Genomic selection in pigs: state of the art and perspectives. ITALIAN JOURNAL OF ANIMAL SCIENCE 2016. [DOI: 10.1080/1828051x.2016.1172034] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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31
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Maimari N, Pedrigi RM, Russo A, Broda K, Krams R. Integration of flow studies for robust selection of mechanoresponsive genes. Thromb Haemost 2016; 115:474-83. [PMID: 26842798 DOI: 10.1160/th15-09-0704] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2015] [Accepted: 11/13/2015] [Indexed: 11/05/2022]
Abstract
Blood flow is an essential contributor to plaque growth, composition and initiation. It is sensed by endothelial cells, which react to blood flow by expressing > 1000 genes. The sheer number of genes implies that one needs genomic techniques to unravel their response in disease. Individual genomic studies have been performed but lack sufficient power to identify subtle changes in gene expression. In this study, we investigated whether a systematic meta-analysis of available microarray studies can improve their consistency. We identified 17 studies using microarrays, of which six were performed in vivo and 11 in vitro. The in vivo studies were disregarded due to the lack of the shear profile. Of the in vitro studies, a cross-platform integration of human studies (HUVECs in flow cells) showed high concordance (> 90 %). The human data set identified > 1600 genes to be shear responsive, more than any other study and in this gene set all known mechanosensitive genes and pathways were present. A detailed network analysis indicated a power distribution (e. g. the presence of hubs), without a hierarchical organisation. The average cluster coefficient was high and further analysis indicated an aggregation of 3 and 4 element motifs, indicating a high prevalence of feedback and feed forward loops, similar to prokaryotic cells. In conclusion, this initial study presented a novel method to integrate human-based mechanosensitive studies to increase its power. The robust network was large, contained all known mechanosensitive pathways and its structure revealed hubs, and a large aggregate of feedback and feed forward loops.
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Affiliation(s)
| | | | | | | | - Rob Krams
- Prof. Rob Krams, Chair in Molecular Bioengineering, Dept. Bioengineering, Imperial College London, Room 3.15, Royal School of Mines, Exhibition Road, SW7 2AZ London, UK, Tel.:+44 2075941473, E-mail:
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32
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Howard JT, O’Nan AT, Maltecca C, Baynes RE, Ashwell MS. Differential Gene Expression across Breed and Sex in Commercial Pigs Administered Fenbendazole and Flunixin Meglumine. PLoS One 2015; 10:e0137830. [PMID: 26366864 PMCID: PMC4569569 DOI: 10.1371/journal.pone.0137830] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2015] [Accepted: 08/24/2015] [Indexed: 11/19/2022] Open
Abstract
Characterizing the variability in transcript levels across breeds and sex in swine for genes that play a role in drug metabolism may shed light on breed and sex differences in drug metabolism. The objective of the study is to determine if there is heterogeneity between swine breeds and sex in transcript levels for genes previously shown to play a role in drug metabolism for animals administered flunixin meglumine or fenbendazole. Crossbred nursery female and castrated male pigs (n = 169) spread across 5 groups were utilized. Sires (n = 15) of the pigs were purebred Duroc, Landrace, Yorkshire or Hampshire boars mated to a common sow population. Animals were randomly placed into the following treatments: no drug (control), flunixin meglumine, or fenbendazole. One hour after the second dosing, animals were sacrificed and liver samples collected. Quantitative Real-Time PCR was used to measure liver gene expression of the following genes: SULT1A1, ABCB1, CYP1A2, CYP2E1, CYP3A22 and CYP3A29. The control animals were used to investigate baseline transcript level differences across breed and sex. Post drug administration transcript differences across breed and sex were investigated by comparing animals administered the drug to the controls. Contrasts to determine fold change were constructed from a model that included fixed and random effects within each drug. Significant (P-value <0.007) basal transcript differences were found across breeds for SULT1A1, CYP3A29 and CYP3A22. Across drugs, significant (P-value <0.0038) transcript differences existed between animals given a drug and controls across breeds and sex for ABCB1, PS and CYP1A2. Significant (P <0.0038) transcript differences across breeds were found for CYP2E1 and SULT1A1 for flunixin meglumine and fenbendazole, respectively. The current analysis found transcript level differences across swine breeds and sex for multiple genes, which provides greater insight into the relationship between flunixin meglumine and fenbendazole and known drug metabolizing genes.
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Affiliation(s)
- Jeremy T. Howard
- Department of Animal Science, College of Agriculture and Life Sciences, North Carolina State University, Raleigh, NC, United States of America
| | - Audrey T. O’Nan
- Department of Animal Science, College of Agriculture and Life Sciences, North Carolina State University, Raleigh, NC, United States of America
| | - Christian Maltecca
- Department of Animal Science, College of Agriculture and Life Sciences, North Carolina State University, Raleigh, NC, United States of America
| | - Ronald E. Baynes
- Department of Population Health and Pathobiology, Center for Chemical Toxicology and Research Pharmacokinetics, College of Veterinary Medicine, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Melissa S. Ashwell
- Department of Animal Science, College of Agriculture and Life Sciences, North Carolina State University, Raleigh, NC, United States of America
- * E-mail:
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33
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Copy number variation-based genome wide association study reveals additional variants contributing to meat quality in Swine. Sci Rep 2015; 5:12535. [PMID: 26234186 PMCID: PMC4522650 DOI: 10.1038/srep12535] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2015] [Accepted: 07/02/2015] [Indexed: 01/26/2023] Open
Abstract
Pork quality is important both to the meat processing industry and consumers' purchasing attitude. Copy number variation (CNV) is a burgeoning kind of variants that may influence meat quality. In this study, a genome-wide association study (GWAS) was performed between CNVs and meat quality traits in swine. After false discovery rate (FDR) correction, a total of 8 CNVs on 6 chromosomes were identified to be significantly associated with at least one meat quality trait. All of the 8 CNVs were verified by next generation sequencing and six of them were verified by qPCR. Only the haplotype block containing CNV12 is adjacent to significant SNPs associated with meat quality, suggesting the effects of those CNVs were not likely captured by tag SNPs. The DNA dosage and EST expression of CNV12, which overlap with an obesity related gene Netrin-1 (Ntn1), were consistent with Ntn1 RNA expression, suggesting the CNV12 might be involved in the expression regulation of Ntn1 and finally influence meat quality. We concluded that CNVs may contribute to the genetic variations of meat quality beyond SNPs, and several candidate CNVs were worth further exploration.
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34
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Beynon SE, Slavov GT, Farré M, Sunduimijid B, Waddams K, Davies B, Haresign W, Kijas J, MacLeod IM, Newbold CJ, Davies L, Larkin DM. Population structure and history of the Welsh sheep breeds determined by whole genome genotyping. BMC Genet 2015; 16:65. [PMID: 26091804 PMCID: PMC4474581 DOI: 10.1186/s12863-015-0216-x] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2014] [Accepted: 05/13/2015] [Indexed: 11/10/2022] Open
Abstract
Background One of the most economically important areas within the Welsh agricultural sector is sheep farming, contributing around £230 million to the UK economy annually. Phenotypic selection over several centuries has generated a number of native sheep breeds, which are presumably adapted to the diverse and challenging landscape of Wales. Little is known about the history, genetic diversity and relationships of these breeds with other European breeds. We genotyped 353 individuals from 18 native Welsh sheep breeds using the Illumina OvineSNP50 array and characterised the genetic structure of these breeds. Our genotyping data were then combined with, and compared to, those from a set of 74 worldwide breeds, previously collected during the International Sheep Genome Consortium HapMap project. Results Model based clustering of the Welsh and European breeds indicated shared ancestry. This finding was supported by multidimensional scaling analysis (MDS), which revealed separation of the European, African and Asian breeds. As expected, the commercial Texel and Merino breeds appeared to have extensive co-ancestry with most European breeds. Consistently high levels of haplotype sharing were observed between native Welsh and other European breeds. The Welsh breeds did not, however, form a genetically homogeneous group, with pairwise FST between breeds averaging 0.107 and ranging between 0.020 and 0.201. Four subpopulations were identified within the 18 native breeds, with high homogeneity observed amongst the majority of mountain breeds. Recent effective population sizes estimated from linkage disequilibrium ranged from 88 to 825. Conclusions Welsh breeds are highly diverse with low to moderate effective population sizes and form at least four distinct genetic groups. Our data suggest common ancestry between the native Welsh and European breeds. These findings provide the basis for future genome-wide association studies and a first step towards developing genomics assisted breeding strategies in the UK. Electronic supplementary material The online version of this article (doi:10.1186/s12863-015-0216-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sarah E Beynon
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Penglais, Aberystwyth, Ceredigion, SY23 3DA, UK.
| | - Gancho T Slavov
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Penglais, Aberystwyth, Ceredigion, SY23 3DA, UK.
| | - Marta Farré
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Penglais, Aberystwyth, Ceredigion, SY23 3DA, UK. .,Royal Veterinary College, University of London, Royal College Street, London, NW1 0TU, UK.
| | - Bolormaa Sunduimijid
- Victorian Department of Environment and Primary Industries, Bundoora, VIC, 3083, Australia.
| | - Kate Waddams
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Penglais, Aberystwyth, Ceredigion, SY23 3DA, UK.
| | - Brian Davies
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Penglais, Aberystwyth, Ceredigion, SY23 3DA, UK.
| | - William Haresign
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Penglais, Aberystwyth, Ceredigion, SY23 3DA, UK.
| | - James Kijas
- Commonwealth Scientific and Industrial Research Organisation (CSIRO), 306 Carmody Road, St Lucia, QLD, 4067, Australia.
| | - Iona M MacLeod
- Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, VIC, 3010, Australia.
| | - C Jamie Newbold
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Penglais, Aberystwyth, Ceredigion, SY23 3DA, UK.
| | - Lynfa Davies
- Hybu Cig Cymru, Meat Promotion Wales, Tŷ Rheidol, Parc Merlin, Aberystwyth, SY23 3FF, UK.
| | - Denis M Larkin
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Penglais, Aberystwyth, Ceredigion, SY23 3DA, UK. .,Royal Veterinary College, University of London, Royal College Street, London, NW1 0TU, UK.
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35
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Zhang R, Große-Brinkhaus C, Heidt H, Uddin MJ, Cinar MU, Tesfaye D, Tholen E, Looft C, Schellander K, Neuhoff C. Polymorphisms and expression analysis of SOX-6 in relation to porcine growth, carcass, and meat quality traits. Meat Sci 2015; 107:26-32. [PMID: 25935846 DOI: 10.1016/j.meatsci.2015.04.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2014] [Revised: 03/16/2015] [Accepted: 04/13/2015] [Indexed: 11/24/2022]
Abstract
The aim of the study was to investigate single nucleotide polymorphisms (SNPs) and expression of SOX-6 to support its candidacy for growth, carcass, and meat quality traits in pigs. The first SNP, rs81358375, was associated with pH 45 min post mortem in loin (pH1L), the thickness of backfat and side fat, and carcass length in Pietrain (Pi) population, and related with backfat thickness and daily gain in Duroc × Pietrain F2 (DuPi) population. The other SNP, rs321666676, was associated with meat colour in Pi population. In DuPi population, the protein, not mRNA, level of SOX-6 in high pH1L pigs was significantly less abundant compared with low pH1L pigs, where microRNAs targeting SOX-6 were also differently regulated. This paper shows that SOX-6 could be a potential candidate gene for porcine growth, carcass, and meat quality traits based on genetic association and gene expression.
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Affiliation(s)
- Rui Zhang
- Institute of Animal Science, Animal Breeding and Husbandry Group, University of Bonn, 53115 Bonn, Germany.
| | - Christine Große-Brinkhaus
- Institute of Animal Science, Animal Breeding and Husbandry Group, University of Bonn, 53115 Bonn, Germany.
| | - Hanna Heidt
- Institute of Animal Science, Animal Breeding and Husbandry Group, University of Bonn, 53115 Bonn, Germany.
| | - Muhammad Jasim Uddin
- Institute of Animal Science, Animal Breeding and Husbandry Group, University of Bonn, 53115 Bonn, Germany; Department of Medicine, Faculty of Veterinary Science, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh.
| | - Mehmet Ulas Cinar
- Institute of Animal Science, Animal Breeding and Husbandry Group, University of Bonn, 53115 Bonn, Germany; Faculty of Agriculture, Department of Animal Science, Erciyes University, 38039 Kayseri, Turkey.
| | - Dawit Tesfaye
- Institute of Animal Science, Animal Breeding and Husbandry Group, University of Bonn, 53115 Bonn, Germany.
| | - Ernst Tholen
- Institute of Animal Science, Animal Breeding and Husbandry Group, University of Bonn, 53115 Bonn, Germany.
| | - Christian Looft
- Institute of Animal Science, Animal Breeding and Husbandry Group, University of Bonn, 53115 Bonn, Germany.
| | - Karl Schellander
- Institute of Animal Science, Animal Breeding and Husbandry Group, University of Bonn, 53115 Bonn, Germany.
| | - Christiane Neuhoff
- Institute of Animal Science, Animal Breeding and Husbandry Group, University of Bonn, 53115 Bonn, Germany.
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36
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Cho HR, Ha J, Kwon SG, Hwang JH, Park DH, Kim TW, Lee HK, Song KD, Kim SW, Kim CW. Single-Nucleotide Polymorphisms in Pig EPHX1 Gene are Associated with Pork Quality Traits. Anim Biotechnol 2015; 26:237-42. [PMID: 25927171 DOI: 10.1080/10495398.2015.1005215] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Epoxide hydrolase 1 (EPHX1) plays an important role in both the activation and detoxification of exogenous chemicals. Reverse transcription-polymerase chain reaction (RT-PCR) analysis showed that the highest level of EPHX1 expression occurred in Berkshire liver, which is an organ that plays a key role in detoxification. We examined EPHX1 SNPs to analyze effect on increased expression of EPHX1 gene in Berkshire liver by total of 192 pigs of a pure Berkshire line (males = 97; females = 95). As a result, two nonsynonymous SNPs (nsSNPs) of EPHX1 were found from c.685T>G and c.776C > T, and located in 5th and 6th exons, respectively, which constitute the A/b hydrolase 1 domain of epoxide hydrolase. The nsSNP c.685T > G was significant differences in meat color, protein content, collagen content, and pH24 hr. Especially, T and G alleles of the nsSNP c.685T > G were significantly associated with CIE a*/CIE b* and protein content/pH24 hr, respectively. The nsSNP c.776C > T was significant differences in drip loss and protein content. Among meat quality traits to associate with SNPs, the protein content was only significantly associated with sex. Therefore, it is suggested that nsSNP c.685T > G in EPHX1 gene is a potential to apply as appropriate DNA markers for improvement of porcine economic traits.
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Affiliation(s)
- Hwak Rae Cho
- a Swine Science and Technology Center , Gyeongnam National University of Science & Technology , Jinju , South Korea
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Revay T, Quach AT, Maignel L, Sullivan B, King WA. Copy number variations in high and low fertility breeding boars. BMC Genomics 2015; 16:280. [PMID: 25888238 PMCID: PMC4404230 DOI: 10.1186/s12864-015-1473-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2014] [Accepted: 03/20/2015] [Indexed: 01/17/2023] Open
Abstract
Background In this study we applied the extreme groups/selective genotyping approach for identifying copy number variations in high and low fertility breeding boars. The fertility indicator was the calculated Direct Boar Effect on litter size (DBE) that was obtained as a by-product of the national genetic evaluation for litter size (BLUP). The two groups of animals had DBE values at the upper (high fertility) and lower (low fertility) end of the distribution from a population of more than 38,000 boars. Animals from these two diverse phenotypes were genotyped with the Porcine SNP60K chip and compared by several approaches in order to prove the feasibility of our CNV analysis and to identify putative markers of fertility. Results We have identified 35 CNVRs covering 36.5 Mb or ~1.3% of the porcine genome. Among these 35 CNVRs, 14 were specific to the high fertility group, while 19 CNVRs were specific to the low fertility group which overlap with 137 QTLs of various reproductive traits. The identified 35 CNVRs encompassed 50 genes, among them 40 were specific to the low fertility group, seven to the high fertility group, while three were found in regions that were present in both groups but with opposite gain/loss status. A functional analysis of several databases revealed that the genes found in CNVRs from the low fertility group have been significantly enriched in members of the innate immune system, Toll-like receptor and RIG-I-like receptor signaling and fatty acid oxidation pathways. Conclusions We have demonstrated that our analysis pipeline could identify putative CNV markers of fertility, especially in case of low fertility boars. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1473-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Tamas Revay
- University of Guelph, Ontario Veterinary College, Department of Biomedical Sciences, 50 Stone Rd E, Guelph, ON, N1G 2W1, Canada.
| | - Anh T Quach
- University of Guelph, Ontario Veterinary College, Department of Biomedical Sciences, 50 Stone Rd E, Guelph, ON, N1G 2W1, Canada.
| | - Laurence Maignel
- Canadian Centre for Swine Improvement Inc. (CCSI), Central Experimental Farm, Building #75, 960 Carling Avenue, Ottawa, ON, K1A 0C6, Canada.
| | - Brian Sullivan
- Canadian Centre for Swine Improvement Inc. (CCSI), Central Experimental Farm, Building #75, 960 Carling Avenue, Ottawa, ON, K1A 0C6, Canada.
| | - W Allan King
- University of Guelph, Ontario Veterinary College, Department of Biomedical Sciences, 50 Stone Rd E, Guelph, ON, N1G 2W1, Canada.
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Lipka AE, Kandianis CB, Hudson ME, Yu J, Drnevich J, Bradbury PJ, Gore MA. From association to prediction: statistical methods for the dissection and selection of complex traits in plants. CURRENT OPINION IN PLANT BIOLOGY 2015; 24:110-8. [PMID: 25795170 DOI: 10.1016/j.pbi.2015.02.010] [Citation(s) in RCA: 82] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2014] [Revised: 02/24/2015] [Accepted: 02/27/2015] [Indexed: 05/02/2023]
Abstract
Quantification of genotype-to-phenotype associations is central to many scientific investigations, yet the ability to obtain consistent results may be thwarted without appropriate statistical analyses. Models for association can consider confounding effects in the materials and complex genetic interactions. Selecting optimal models enables accurate evaluation of associations between marker loci and numerous phenotypes including gene expression. Significant improvements in QTL discovery via association mapping and acceleration of breeding cycles through genomic selection are two successful applications of models using genome-wide markers. Given recent advances in genotyping and phenotyping technologies, further refinement of these approaches is needed to model genetic architecture more accurately and run analyses in a computationally efficient manner, all while accounting for false positives and maximizing statistical power.
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Affiliation(s)
- Alexander E Lipka
- University of Illinois, Department of Crop Sciences, Urbana, IL 61801, USA.
| | - Catherine B Kandianis
- Michigan State University, Department of Biochemistry and Molecular Biology, East Lansing, MI 48824, USA; Cornell University, Plant Breeding and Genetics Section, School of Integrative Plant Science, Ithaca, NY 14853, USA
| | - Matthew E Hudson
- University of Illinois, Department of Crop Sciences, Urbana, IL 61801, USA
| | - Jianming Yu
- Iowa State University, Department of Agronomy, Ames, IA 50011, USA
| | - Jenny Drnevich
- University of Illinois, High Performance Biological Computing Group and the Carver Biotechnology Center, Urbana, IL 61801, USA
| | - Peter J Bradbury
- United States Department of Agriculture (USDA) - Agricultural Research Service (ARS), Robert W. Holley Center for Agriculture and Health, Ithaca, NY 14853, USA
| | - Michael A Gore
- Cornell University, Plant Breeding and Genetics Section, School of Integrative Plant Science, Ithaca, NY 14853, USA
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Fontanesi L, Schiavo G, Scotti E, Galimberti G, Calò DG, Samorè AB, Gallo M, Russo V, Buttazzoni L. A retrospective analysis of allele frequency changes of major genes during 20 years of selection in the Italian Large White pig breed. J Anim Breed Genet 2015; 132:239-46. [PMID: 25727360 DOI: 10.1111/jbg.12127] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2014] [Accepted: 10/01/2014] [Indexed: 12/01/2022]
Abstract
In this study, we investigated whether a selection programme based on boar genetic evaluation obtained with a classical BLUP animal model can change allele frequencies in a pig population. All Italian Large White boars born from 1992 to 2012 with estimated breeding value reliability >0.85 (n = 200) were selected among all boars of this breed. Boars were genotyped with markers in major genes (IGF2 intron3-g.3072G>A, MC4R p.D298N, VRTN PRE1 insertion, PRKAG3 p.I199V and FTO g.276T>G). Genotyping data were analysed grouping boars in eight classes according to their year of birth. To evaluate the influence of time on allele frequencies of the genotyped markers, multinomial logistic regression models were computed. Four of five polymorphic sites (IGF2, MC4R, VRTN and FTO) showed significant (p < 0.01) changes in allele frequencies over time due to a progressive and continuous increase of one allele (associated with higher lean meat content, higher average daily gain and favourable feed: gain ratio) and, consequently, decrease of the other one, following the directional selection of the selection programme of this pig breed. The retrospective analysis that was carried out in Italian Large White boars suggests that selection based on methodologies assuming the infinitesimal model is able to modify in a quite short period of time allele frequencies in major genes, increasing the frequency of alleles explaining a relevant (non-infinitesimal) fraction of the overall genetic variability for production traits.
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Affiliation(s)
- L Fontanesi
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Bologna, Italy
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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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Jiao S, Maltecca C, Gray KA, Cassady JP. Feed intake, average daily gain, feed efficiency, and real-time ultrasound traits in Duroc pigs: II. Genomewide association. J Anim Sci 2015; 92:2846-60. [PMID: 24962532 DOI: 10.2527/jas.2014-7337] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Efficient use of feed resources has become a clear challenge for the U.S. pork industry as feed costs continue to be the largest variable expense. The availability of the Illumina Porcine60K BeadChip has greatly facilitated whole-genome association studies to identify chromosomal regions harboring genes influencing those traits. The current study aimed at identifying genomic regions associated with variation in feed efficiency and several production traits in a Duroc terminal sire population, including ADFI, ADG, feed conversion ratio, residual feed intake (RFI), real-time ultrasound back fat thickness (BF), ultrasound muscle depth, intramuscular fat content (IMF), birth weight (BW at birth), and weaning weight (BW at weaning). Single trait association analyses were performed using Bayes B models with 35,140 SNP on 18 autosomes after quality control. Significance of nonoverlapping 1-Mb length windows (n = 2,380) were tested across 3 QTL inference methods: posterior distribution of windows variances from Monte Carlo Markov Chain, naive Bayes factor, and nonparametric bootstrapping. Genes within the informative QTL regions for the traits were annotated. A region ranging from166 to 140 Mb (4-Mb length) on SSC 1, approximately 8 Mb upstream of the MC4R gene, was significantly associated with ADFI, ADG, and BF, where SOCS6 and DOK6 are proposed as the most likely candidate genes. Another region affecting BW at weaning was identified on SSC 4 (84-85 Mb), harboring genes previously found to influence both human and cattle height: PLAG1, CHCHD7, RDHE2 (or SDR16C5), MOS, RPS20, LYN, and PENK. No QTL were identified for RFI, IMF, and BW at birth. In conclusion, we have identified several genomic regions associated with traits affecting nutrient utilization that could be considered for future genomic prediction to improve feed utilization.
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Affiliation(s)
- S Jiao
- Department of Animal Science, North Carolina State University, Raleigh 27695
| | - C Maltecca
- Department of Animal Science, North Carolina State University, Raleigh 27695
| | - K A Gray
- Smithfield Premium Genetics, Rose Hill, NC 28458
| | - J P Cassady
- Department of Animal Science, North Carolina State University, Raleigh 27695
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Rothammer S, Kremer PV, Bernau M, Fernandez-Figares I, Pfister-Schär J, Medugorac I, Scholz AM. Genome-wide QTL mapping of nine body composition and bone mineral density traits in pigs. Genet Sel Evol 2014; 46:68. [PMID: 25359100 PMCID: PMC4210560 DOI: 10.1186/s12711-014-0068-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2014] [Accepted: 09/19/2014] [Indexed: 12/20/2022] Open
Abstract
Background Since the pig is one of the most important livestock animals worldwide, mapping loci that are associated with economically important traits and/or traits that influence animal welfare is extremely relevant for efficient future pig breeding. Therefore, the purpose of this study was a genome-wide mapping of quantitative trait loci (QTL) associated with nine body composition and bone mineral traits: absolute (Fat, Lean) and percentage (FatPC, LeanPC) fat and lean mass, live weight (Weight), soft tissue X-ray attenuation coefficient (R), absolute (BMC) and percentage (BMCPC) bone mineral content and bone mineral density (BMD). Methods Data on the nine traits investigated were obtained by Dual-energy X-ray absorptiometry for 551 pigs that were between 160 and 200 days old. In addition, all pigs were genotyped using Illumina’s PorcineSNP60 Genotyping BeadChip. Based on these data, a genome-wide combined linkage and linkage disequilibrium analysis was conducted. Thus, we used 44 611 sliding windows that each consisted of 20 adjacent single nucleotide polymorphisms (SNPs). For the middle of each sliding window a variance component analysis was carried out using ASReml. The underlying mixed linear model included random QTL and polygenic effects, with fixed effects of sex, housing, season and age. Results Using a Bonferroni-corrected genome-wide significance threshold of P < 0.001, significant peaks were identified for all traits except BMCPC. Overall, we identified 72 QTL on 16 chromosomes, of which 24 were significantly associated with one trait only and the remaining with more than one trait. For example, a QTL on chromosome 2 included the highest peak across the genome for four traits (Fat, FatPC, LeanPC and R). The nearby gene, ZNF608, is known to be associated with body mass index in humans and involved in starvation in Drosophila, which makes it an extremely good candidate gene for this QTL. Conclusions Our QTL mapping approach identified 72 QTL, some of which confirmed results of previous studies in pigs. However, we also detected significant associations that have not been published before and were able to identify a number of new and promising candidate genes, such as ZNF608. Electronic supplementary material The online version of this article (doi:10.1186/s12711-014-0068-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | | | | | | | | | - Ivica Medugorac
- Chair of Animal Genetics and Husbandry, Ludwig-Maximilians-University Munich, Veterinärstrasse 13, Munich, 80539, Germany.
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Du ZQ, Eisley CJ, Onteru SK, Madsen O, Groenen MAM, Ross JW, Rothschild MF. Identification of species-specific novel transcripts in pig reproductive tissues using RNA-seq. Anim Genet 2014; 45:198-204. [PMID: 24450499 DOI: 10.1111/age.12124] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/14/2013] [Indexed: 02/04/2023]
Abstract
Although structural properties of the porcine reproductive system are shared by many placental mammals, some combination of these properties is unique to pigs. To explore whether genomic elements specific to pigs could potentially underlie this uniqueness, we made the first step to identify novel transcripts in two representative pig reproductive tissues by the technique of massively parallel sequencing. To automate the whole process, we built a computational pipeline, which can also be easily extended for similar studies in other species. In total, 5516 and 9061 novel transcripts were found, and 159 and 252 novel transcripts appear to be specific to pigs for the placenta and testis respectively. Furthermore, these novel transcripts were found to be enriched in quantitative trait loci (QTL) regions for reproduction traits in pigs. We validated eight of these novel transcripts by quantitative real-time PCR. With respect to their genomic organization and their functional relationship to reproduction, these transcripts need to be further validated and explored in various pig breeds to better comprehend the relevant aspects of pig physiology that contribute to reproductive performance.
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Affiliation(s)
- Z-Q Du
- Department of Animal Science and Center for Integrated Animal Genomics, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA
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Kang K, Seo DW, Lee JB, Jung EJ, Park HB, Cho IC, Lim HT, Lee JH. Identification of SNPs Affecting Porcine Carcass Weight with the 60K SNP Chip. JOURNAL OF ANIMAL SCIENCE AND TECHNOLOGY 2013. [DOI: 10.5187/jast.2013.55.4.231] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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