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Qiu Z, Cai W, Liu Q, Liu K, Liu C, Yang H, Huang R, Li P, Zhao Q. Unravelling novel and pleiotropic genes for cannon bone circumference and bone mineral density in Yorkshire pigs. J Anim Sci 2024; 102:skae036. [PMID: 38330300 PMCID: PMC10914368 DOI: 10.1093/jas/skae036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 02/03/2024] [Indexed: 02/10/2024] Open
Abstract
Leg weakness is a prevalent health condition in pig farms. The augmentation of cannon bone circumference and bone mineral density can effectively improve limb strength in pigs and alleviate leg weakness. This study measured forelimb cannon bone circumference (fCBC) and rear limb cannon bone circumference (rCBC) using an inelastic tapeline and rear limb metatarsal area bone mineral density (raBMD) using a dual-energy X-ray absorptiometry bone density scanner. The samples of Yorkshire castrated boars were genotyped using a 50K single-nucleotide polymorphism (SNP) array. The SNP-chip data were imputed to the level of whole-genome sequencing data (iWGS). This study used iWGS data to perform genome-wide association studies and identified novel significant SNPs associated with fCBC on SSC6, SSC12, and SSC13, rCBC on SSC12 and SSC14, and raBMD on SSC7. Based on the high phenotypic and genetic correlations between CBC and raBMD, multi-trait meta-analysis was performed to identify pleiotropic SNPs. A significant potential pleiotropic quantitative trait locus (QTL) regulating both CBC and raBMD was identified on SSC15. Bayes fine mapping was used to establish the confidence intervals for these novel QTLs with the most refined confidence interval narrowed down to 56 kb (15.11 to 15.17 Mb on SSC12 for fCBC). Furthermore, the confidence interval for the potential pleiotropic QTL on SSC15 in the meta-analysis was narrowed down to 7.45 kb (137.55 to137.56 Mb on SSC15). Based on the biological functions of genes, the following genes were identified as novel regulatory candidates for different phenotypes: DDX42, MYSM1, FTSJ3, and MECOM for fCBC; SMURF2, and STC1 for rCBC; RGMA for raBMD. Additionally, RAMP1, which was determined to be located 23.68 kb upstream of the confidence interval of the QTL on SSC15 in the meta-analysis, was identified as a potential pleiotropic candidate gene regulating both CBC and raBMD. These findings offered valuable insights for identifying pathogenic genes and elucidating the genetic mechanisms underlying CBC and BMD.
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Affiliation(s)
- Zijian Qiu
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Wenwu Cai
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Qian Liu
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Kaiyue Liu
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Chenxi Liu
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Huilong Yang
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
| | - Ruihua Huang
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
- Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - Pinghua Li
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
- Huaian Academy, Nanjing Agricultural University, Huaian 223005, China
| | - Qingbo Zhao
- Key Laboratory in Nanjing for Evaluation and Utilization of Pigs Resources, Ministry of Agriculture and Rural Areas of China, Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China
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Nan JH, Yin LL, Tang ZS, Xiang T, Ma GJ, Li XY, Liu XL, Zhao SH, Liu XD. Identification of novel variants and candidate genes associated with porcine bone mineral density using genome-wide association study. J Anim Sci 2020; 98:5736012. [PMID: 32055823 PMCID: PMC7166125 DOI: 10.1093/jas/skaa052] [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: 08/14/2019] [Accepted: 02/12/2020] [Indexed: 11/13/2022] Open
Abstract
Pig leg weakness not only causes huge economic losses for producers but also affects animal welfare. However, genes with large effects on pig leg weakness have not been identified and suitable methods to study porcine leg weakness are urgently needed. Bone mineral density (BMD) is an important indicator for determining leg soundness in pigs. Increasing pig BMD is likely to improve pig leg soundness. In this study, porcine BMD was measured using an ultrasound bone densitometer in a population with 212 Danish Landrace pigs and 537 Danish Yorkshires. After genotyping all the individuals using GeneSeek Porcine 50K SNP chip, genetic parameter estimation was performed to evaluate the heritability of BMD. Genome-wide association study and haplotype analysis were also performed to identify the variants and candidate genes associated with porcine BMD. The results showed that the heritability of BMD was 0.21 in Landrace and 0.31 in Yorkshire. Five single-nucleotide polymorphisms on chromosome 6 identified were associated with porcine BMD at suggestive significance level. Two candidate quantitative trait loci (74.47 to 75.33 Mb; 80.20 to 83.83 Mb) and three potential candidate genes (ZBTB40, CNR2, and Lin28a) of porcine BMD were detected in this study.
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Affiliation(s)
- Jiuhong-H Nan
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, P.R. China
| | - Lilin-L Yin
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, P.R. China
| | - Zhenshuang-S Tang
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, P.R. China
| | - Tao Xiang
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, P.R. China
| | - Guanjun-J Ma
- Key Lab of Swine Healthy Breeding of Ministry of Agriculture and Rural Affairs, Guangxi Yangxiang Co., Ltd., Guigang, Guangxi, P.R. China
| | - Xinyun-Y Li
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, P.R. China
| | - Xiaolei-L Liu
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, P.R. China
| | - Shuhong-H Zhao
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, P.R. China
| | - Xiangdong-D Liu
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, P.R. China.,Key Lab of Swine Healthy Breeding of Ministry of Agriculture and Rural Affairs, Guangxi Yangxiang Co., Ltd., Guigang, Guangxi, P.R. China
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Suwannasing R, Duangjinda M, Boonkum W, Taharnklaew R, Tuangsithtanon K. The identification of novel regions for reproduction trait in Landrace and Large White pigs using a single step genome-wide association study. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2018; 31:1852-1862. [PMID: 29879826 PMCID: PMC6212738 DOI: 10.5713/ajas.18.0072] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Accepted: 05/15/2018] [Indexed: 01/09/2023]
Abstract
OBJECTIVE The purpose of this study was to investigate a single step genome-wide association study (ssGWAS) for identifying genomic regions affecting reproductive traits in Landrace and Large White pigs. METHODS The traits included the number of pigs weaned per sow per year (PWSY), the number of litters per sow per year (LSY), pigs weaned per litters (PWL), born alive per litters (BAL), non-productive day (NPD) and wean to conception interval per litters (W2CL). A total of 321 animals (140 Landrace and 181 Large White pigs) were genotyped with the Illumina Porcine SNP 60k BeadChip, containing 61,177 single nucleotide polymorphisms (SNPs), while multiple traits single-step genomic BLUP method was used to calculate variances of 5 SNP windows for 11,048 Landrace and 13,985 Large White data records. RESULTS The outcome of ssGWAS on the reproductive traits identified twenty-five and twenty-two SNPs associated with reproductive traits in Landrace and Large White, respectively. Three known genes were identified to be candidate genes in Landrace pigs including retinol binding protein 7, and ubiquitination factor E4B genes for PWL, BAL, W2CL, and PWSY and one gene, solute carrier organic anion transporter family member 6A1, for LSY and NPD. Meanwhile, five genes were identified to be candidate genes in Large White, two of which, aldehyde dehydrogenase 1 family member A3 and leucine rich repeat kinase 1, associated with all of six reproduction traits and three genes; retrotransposon Gag like 4, transient receptor potential cation channel subfamily C member 5, and LHFPL tetraspan subfamily member 1 for five traits except W2CL. CONCLUSION The genomic regions identified in this study provided a start-up point for marker assisted selection and estimating genomic breeding values for improving reproductive traits in commercial pig populations.
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Affiliation(s)
- Rattikan Suwannasing
- Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Monchai Duangjinda
- Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Wuttigrai Boonkum
- Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand
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Guo Y, Qiu H, Xiao S, Wu Z, Yang M, Yang J, Ren J, Huang L. A genome-wide association study identifies genomic loci associated with backfat thickness, carcass weight, and body weight in two commercial pig populations. J Appl Genet 2017; 58:499-508. [DOI: 10.1007/s13353-017-0405-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Revised: 08/17/2017] [Accepted: 08/18/2017] [Indexed: 12/30/2022]
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Guo Y, Huang Y, Hou L, Ma J, Chen C, Ai H, Huang L, Ren J. Genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches. Genet Sel Evol 2017; 49:21. [PMID: 28196480 PMCID: PMC5307927 DOI: 10.1186/s12711-017-0295-4] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2015] [Accepted: 02/06/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) have been extensively used to identify genomic regions associated with a variety of phenotypic traits in pigs. Until now, most GWAS have explored single-trait association models. Here, we conducted both single- and multi-trait GWAS and a meta-analysis for nine fatness and growth traits on 2004 pigs from four diverse populations, including a White Duroc × Erhualian F2 intercross population and Chinese Sutai, Laiwu and Erhualian populations. RESULTS We identified 44 chromosomal regions that were associated with the nine traits, including four genome-wide significant single nucleotide polymorphisms (SNPs) on SSC2 (SSC for Sus scrofa chromosome), 4, 7 and X. Compared to the single-population GWAS, the meta-analysis was less powerful for the identification of SNPs with population-specific effects but more powerful for the detection of SNPs with population-shared effects. Multiple-trait analysis reduced the power to detect trait-specific SNPs but significantly enhanced the power to identify common SNPs across traits. The SNP on SSC7 had pleiotropic effects on the nine traits in the F2 and Erhualian populations. Another pleiotropic SNP was observed on SSCX for these traits in the F2 and Sutai populations. Both population-specific and shared SNPs were identified in this study, thus reflecting the complex genetic architecture of pig growth and fatness traits. CONCLUSIONS We demonstrate that the multi-trait method and the meta-analysis on multiple populations can be used to increase the power of GWAS. The two significant SNPs on SSC7 and X had pleiotropic effects in the F2, Erhualian and Sutai populations.
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Affiliation(s)
- Yuanmei Guo
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Yixuan Huang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Lijuan Hou
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Junwu Ma
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Congying Chen
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Huashui Ai
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Lusheng Huang
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China
| | - Jun Ren
- State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
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Sato S, Uemoto Y, Kikuchi T, Egawa S, Kohira K, Saito T, Sakuma H, Miyashita S, Arata S, Kojima T, Suzuki K. SNP- and haplotype-based genome-wide association studies for growth, carcass, and meat quality traits in a Duroc multigenerational population. BMC Genet 2016; 17:60. [PMID: 27094516 PMCID: PMC4837538 DOI: 10.1186/s12863-016-0368-3] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Accepted: 04/15/2016] [Indexed: 12/21/2022] Open
Abstract
Background The aim of the present study was to compare the power of single nucleotide polymorphism (SNP)-based genome-wide association study (GWAS) and haplotype-based GWAS for quantitative trait loci (QTL) detection, and to detect novel candidate genes affecting economically important traits in a purebred Duroc population comprising seven-generation pedigree. First, we performed a simulation analysis using real genotype data of this population to compare the power (based on the null hypothesis) of the two methods. We then performed GWAS using both methods and real phenotype data comprising 52 traits, which included growth, carcass, and meat quality traits. Results In total, 836 animals were genotyped using the Illumina PorcineSNP60 BeadChip and 14 customized SNPs from regions of known candidate genes related to the traits of interest. The power of SNP-based GWAS was greater than that of haplotype-based GWAS in a simulation analysis. In real data analysis, a larger number of significant regions was obtained by SNP-based GWAS than by haplotype-based GWAS. For SNP-based GWAS, 23 genome-wide significant SNP regions were detected for 17 traits, and 120 genome-wide suggestive SNP regions were detected for 27 traits. For haplotype-based GWAS, 6 genome-wide significant SNP regions were detected for four traits, and 11 genome-wide suggestive SNP regions were detected for eight traits. All genome-wide significant SNP regions detected by haplotype-based GWAS were located in regions also detected by SNP-based GWAS. Four regions detected by SNP-based GWAS were significantly associated with multiple traits: on Sus scrofa chromosome (SSC) 1 at 304 Mb; and on SSC7 at 35–39 Mb, 41–42 Mb, and 103 Mb. The vertnin gene (VRTN) in particular, was located on SSC7 at 103 Mb and was significantly associated with vertebrae number and carcass lengths. Mapped QTL regions contain some candidate genes involved in skeletal formation (FUBP3; far upstream element binding protein 3) and fat deposition (METTL3; methyltransferase like 3). Conclusion Our results show that a multigenerational pig population is useful for detecting QTL, which are typically segregated in a purebred population. In addition, a novel significant region could be detected by SNP-based GWAS as opposed to haplotype-based GWAS. Electronic supplementary material The online version of this article (doi:10.1186/s12863-016-0368-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Shuji Sato
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan.
| | - Yoshinobu Uemoto
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan
| | - Takashi Kikuchi
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan
| | - Sachiko Egawa
- Miyazaki Branch of National Livestock Breeding Center, Kobayashi, Miyazaki, 886-0004, Japan
| | - Kimiko Kohira
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan
| | - Tomomi Saito
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan
| | - Hironori Sakuma
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan
| | - Satoshi Miyashita
- Miyazaki Branch of National Livestock Breeding Center, Kobayashi, Miyazaki, 886-0004, Japan
| | - Shinji Arata
- Miyazaki Branch of National Livestock Breeding Center, Kobayashi, Miyazaki, 886-0004, Japan
| | - Takatoshi Kojima
- National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan
| | - Keiichi Suzuki
- Graduate School of Agricultural Science, Tohoku University, Sendai, Miyagi, 981-8555, Japan
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Guo YM, Zhang ZY, Ma JW, Ai HS, Ren J, Huang LS. A genomewide association study of feed efficiency and feeding behaviors at two fattening stages in a White Duroc × Erhualian F population. J Anim Sci 2016; 93:1481-9. [PMID: 26020169 DOI: 10.2527/jas.2014-8655] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Feeding efficiency is a multifactorial and economically important trait in pigs. Genetic improvement of feeding efficiency will greatly benefit the pig industry. In the past decades, the hog market weight has increased worldwide. However, whether the genetic architecture of feeding efficiency is same or not at early and late fattening periods is unclear. To map genomic regions for feed efficiency and feeding behavior traits at early (n ≥ 384) and late (n ≥ 334) growth stages in pigs, we performed genomewide association studies for feed to gain ratio (FCR), residual feed intake (RFI), daily feed intake, daily visit times, daily feeding time (DFT), feed intake per second (FIPS), and feed intake per visit during 3 periods (2 stages and overall) in a White Duroc × Erhualian F2 intercross population. Six chromosomal regions showed significant association with these traits, of which 4 loci were reported for the first time. Our results confirmed the QTL of FCR around 34 Mb on SSC7 and RFI around 134 Mb on SSC12. Of note, 2 regions were associated with more than 1 trait. One was around 36 Mb on SSC7, and there were 47 and 67 SNP associated with FCR from 120 to 210 and from 120 to 240 d, respectively. The top SNP is located in a 2.88-Mb linkage disequilibrium (LD) block that harbors 44 genes. We propose the high mobility group AT-hook 1 gene as a plausible candidate gene in this region. The other was evidenced around 53 Mb on SSC12, which had multiple association signals for DFT and FIPS. The top SNP is located in a 211-kb LD block that harbors only 1 annotated gene, WSCD1, which encodes a protein with sulfotransferase activity and involves the glucose metabolism and, therefore, appears to be a plausible candidate gene. Except the region on SSC12 associated with DFT at both stages, the rest of the regions associated with the traits at only 1 stage, so the genetic architectures of the 2 stages are not same.
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Guo Y, Hou L, Zhang X, Huang M, Mao H, Chen H, Ma J, Chen C, Ai H, Ren J, Huang L. A meta analysis of genome-wide association studies for limb bone lengths in four pig populations. BMC Genet 2015. [PMID: 26219668 PMCID: PMC4518597 DOI: 10.1186/s12863-015-0257-1] [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] [Indexed: 12/30/2022] Open
Abstract
Background Limb bone length is an economically important trait in pigs, because it is negatively correlated with backfat thickness, and is also a determinant to the yield of hip and loin. Moreover, abnormal growth of the limb bone leads to leg structural weakness. Until now, the genetic architecture of the pig lime bone length remains poorly understood. The object of this study was to map genomic loci for limb bone length by genome-wide association study (GWAS) on 4 pig populations. Results We measured the lengths of five limb bones including scapula, humerus, ulna, femur and tibia that were dissected from the right-side carcass of 925, 331, 314 and 434 animals from White Duroc × Erhualian F2 intercross, Erhualian, Laiwu and Sutai populations, respectively. We genotyped the 2004 pigs for 62,163 single nucleotide polymorphisms (SNPs) on the Porcine SNP60 BeadChip, and performed GWAS and a GWAS meta analysis in the 4 populations. In total, we identified 12 and 4 loci associated with the limb bone lengths at suggestive and genome-wide significant levels respectively, of which 4 loci were reported for the first time. The most prominent locus was identified in a 924-kb (kilo base pairs) linkage disequilibrium block on Sus Scrofa chromosome (SSC) 7, and High Mobility Group AT-hook 1 (HMGA1) appears to be a strong candidate gene in this region. Another promising locus is located in the middle of SSC4, and Pleiomorphic Adenoma Gene 1 (PLAG1) is a functionally plausible candidate gene underlying the locus. Because the lengths of the 5 limb bones are highly correlated to each other, most of significant loci were associated with all of the 5 traits; however, several loci showed specific effect on the length of one limb bone, such as the locus at the proximal end of SSC2 associated with only the scapula length. Conclusion To our knowledge, this study was the first GWAS meta analysis for limb bone lengths in pigs. As expected, the meta analysis is more powerful to identify genomic loci. A total of 16 loci were identified in this study, including four novel loci. HMGA1 and PLAG1 are two appearing candidate genes for pig limb bone lengths, which warrant further investigations. Electronic supplementary material The online version of this article (doi:10.1186/s12863-015-0257-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yuanmei Guo
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Lijuan Hou
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Xufei Zhang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China. .,Current address: Wenzhou Medical University, WenZhou, 325000, China.
| | - Min Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Huirong Mao
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Hao Chen
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Junwu Ma
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Congying Chen
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Huashui Ai
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Jun Ren
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
| | - Lusheng Huang
- State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
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Zhu J, Chen C, Yang B, Guo Y, Ai H, Ren J, Peng Z, Tu Z, Yang X, Meng Q, Friend S, Huang L. A systems genetics study of swine illustrates mechanisms underlying human phenotypic traits. BMC Genomics 2015; 16:88. [PMID: 25765547 PMCID: PMC4336704 DOI: 10.1186/s12864-015-1240-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2014] [Accepted: 01/13/2015] [Indexed: 12/20/2022] Open
Abstract
Background The pig, which shares greater similarities with human than with mouse, is important for agriculture and for studying human diseases. However, similarities in the genetic architecture and molecular regulations underlying phenotypic variations in humans and swine have not been systematically assessed. Results We systematically surveyed ~500 F2 pigs genetically and phenotypically. By comparing candidates for anemia traits identified in swine genome-wide SNP association and human genome-wide association studies (GWAS), we showed that both sets of candidates are related to the biological process “cellular lipid metabolism” in liver. Human height is a complex heritable trait; by integrating genome-wide SNP data and human adipose Bayesian causal network, which closely represents bone transcriptional regulations, we identified PLAG1 as a causal gene for limb bone length. This finding is consistent with GWAS findings for human height and supports the common genetic architecture between swine and humans. By leveraging a human protein-protein interaction network, we identified two putative candidate causal genes TGFB3 and DAB2IP and the known regulators MESP1 and MESP2 as responsible for the variation in rib number and identified the potential underlying molecular mechanisms. In mice, knockout of Tgfb3 and Tgfb2 together decreases rib number. Conclusion Our findings show that integrative network analyses reveal causal regulators underlying the genetic association of complex traits in swine and that these causal regulators have similar effects in humans. Thus, swine are a potentially good animal model for studying some complex human traits that are not under intense selection. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1240-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jun Zhu
- Jiangxi Agricultural University, Nanchang, Jiangxi, China. .,Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| | - Congying Chen
- Jiangxi Agricultural University, Nanchang, Jiangxi, China.
| | - Bin Yang
- Jiangxi Agricultural University, Nanchang, Jiangxi, China.
| | - Yuanmei Guo
- Jiangxi Agricultural University, Nanchang, Jiangxi, China.
| | - Huashui Ai
- Jiangxi Agricultural University, Nanchang, Jiangxi, China.
| | - Jun Ren
- Jiangxi Agricultural University, Nanchang, Jiangxi, China.
| | | | - Zhidong Tu
- Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California at Los Angeles, Los Angeles, CA, USA.
| | - Qingying Meng
- Department of Integrative Biology and Physiology, University of California at Los Angeles, Los Angeles, CA, USA.
| | | | - Lusheng Huang
- Jiangxi Agricultural University, Nanchang, Jiangxi, China.
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