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Wijayanti D, Zhang S, Bai Y, Pan C, Chen H, Qu L, Guo Z, Lan X. Investigation on mRNA expression and genetic variation within goat SMAD2 gene and its association with litter size. Anim Biotechnol 2023; 34:2111-2119. [PMID: 35584800 DOI: 10.1080/10495398.2022.2077214] [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] [Indexed: 11/01/2022]
Abstract
The SMAD family member 2 (SMAD2), a member of the TGF-beta superfamily, executes a significant part in the oogenesis and ovulation process. A genome-wide selective sweep analysis also found SMAD2 was different in the fertility groups of Laoshan dairy goats; whether this gene was linked to litter size was unknown. Therefore, SMAD2 was chosen to study its effects on Shaanbei white cashmere goat reproduction and mRNA expression profile. Herein, the mRNA expression level of SMAD2 was firstly determined in female goat tissues, revealing significant differences in mRNA levels of different tissues (p < 0.05), including ovary tissue, indicating a potential role for SMAD2 in goat prolificacy. Then, using six pairs of primers, only one indel locus (P3-Del-12-bp) was found to be polymorphic in goat SMAD2 (n = 501). ANOVA also revealed that a P3-Del-12-bp deletion was significantly related to first-born litter size (p = 0.037). The Chi-square (χ2) test revealed that the ID genotype was significantly more prevalent in mothers with multiple lambs (p = 0.01), indicating that heterozygous individuals (ID) are more likely to produce multiple lambs. Our findings suggest that the SMAD2 gene's P3-Del-12-bp deletion could be used to improve goat breeds by assisting with litter size selection.
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Affiliation(s)
- Dwi Wijayanti
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
- Department of Animal Science, Perjuangan University of Tasikmalaya, Tasikmalaya, West Java, Indonesia
| | - Sihuan Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Yangyang Bai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Chuanying Pan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Hong Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Lei Qu
- Shaanxi Provincial Engineering and Technology Research Center of Cashmere Goats, Yulin University, Yulin, Shaanxi, PR China; Life Science Research Center, Yulin University, Yulin, Shaanxi, PR China
| | - Zhengang Guo
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
- Institute of Animal Husbandry and Veterinary Science of Bijie City, Guizhou, China
| | - Xianyong Lan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
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Demir E, Moravčíková N, Kaya S, Kasarda R, Doğru H, Bilginer Ü, Balcioğlu MS, Karsli T. Genome-wide genetic variation and population structure of native and cosmopolitan cattle breeds reared in Türkiye. Anim Biotechnol 2023; 34:3877-3886. [PMID: 37471206 DOI: 10.1080/10495398.2023.2235600] [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] [Indexed: 07/22/2023]
Abstract
This is the first comprehensive study to reveal genetic variation and population structure at genome level in six Anatolian (Anatolian Black, East Anatolian Red, South Anatolian Red, South Anatolian Yellow, Turkish Grey Steppe, and Zavot) and two cosmopolitan (Brown Swiss and Holstein Friesian) cattle breeds reared in Türkiye. Being 20 samples from each population, a total of 160 blood samples retrieved from representative herds were utilized to generate genomic libraries by ddRADseq method. Genomic libraries sequenced by Illumina HiSeq X Ten instrument revealed a total of 211,119 bi-allelic SNPs with high call rate. Compared to cosmopolitan cattle breeds, a higher genetic variation was observed in native Turkish cattle with an average of 0.380 observed heterozygosity. Genetic distances were comparatively low between native cattle breeds, whereas the highest genetic distance (0.064) was detected between South Anatolian Yellow and Brown Swiss. Population structure analyses showed that the native Turkish and cosmopolitan cattle breeds were clearly different from each other according to their phylogenetic origin. Besides, a high level of genetic admixture was detected among Anatolian Black, Turkish Grey Steppe, South Anatolian Red, and South Anatolian Yellow, whereas East Anatolian Red and Zavot were distinct from the other native and cosmopolitan cattle breeds. TreeMix algorithm under the assumption of one and two migration events revealed a migration route from Anatolian clade to Anatolian Black, while a second migration edge was drawn from Brown Swiss to East Anatolian Red. This study demonstrates the importance of national conservation studies in the native breeds whose population size has dramatically decreased. In addition, SNP arrays and next-generation sequencing platforms are recommended for future studies to reveal the genetic variation of other local Turkish livestock species to arrange effective conservation programs.
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Affiliation(s)
- Eymen Demir
- Department of Animal Science, Faculty of Agriculture, Akdeniz University, Antalya, Republic of Türkiye
| | - Nina Moravčíková
- Institute of Nutrition and Genomics, Faculty of Agrobiology and Food Resources, Slovak University of Agriculture in Nitra, Slovak Republic
| | - Sarp Kaya
- Department of Medical Services and Techniques, Vocational School of Burdur Health Services, Burdur Mehmet Akif Ersoy University, Burdur, Republic of Türkiye
| | - Radovan Kasarda
- Institute of Nutrition and Genomics, Faculty of Agrobiology and Food Resources, Slovak University of Agriculture in Nitra, Slovak Republic
| | - Huriye Doğru
- Department of Medical Services and Techniques, Vocational School of Burdur Health Services, Burdur Mehmet Akif Ersoy University, Burdur, Republic of Türkiye
| | - Ümit Bilginer
- Department of Animal Science, Faculty of Agriculture, Akdeniz University, Antalya, Republic of Türkiye
| | - Murat Soner Balcioğlu
- Department of Animal Science, Faculty of Agriculture, Akdeniz University, Antalya, Republic of Türkiye
| | - Taki Karsli
- Department of Animal Science, Faculty of Agriculture, Eskisehir Osmangazi University, Eskisehir, Republic of Türkiye
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Zhang K, Wang G, Wang L, Wen B, Fu X, Liu N, Yu Z, Jian W, Guo X, Liu H, Chen SY. A genome-wide association study of coat color in Chinese Rex rabbits. Front Vet Sci 2023; 10:1184764. [PMID: 37655262 PMCID: PMC10467280 DOI: 10.3389/fvets.2023.1184764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 07/31/2023] [Indexed: 09/02/2023] Open
Abstract
Coat color is an important phenotypic characteristic of the domestic rabbit (Oryctolagus cuniculus) and has specific economic importance in the Rex rabbit industry. Coat color varies considerably among different populations of rabbits, and several causal genes for this variation have been thoroughly studied. Nevertheless, the candidate genes affecting coat color variation in Chinese Rex rabbits remained to be investigated. In this study, we collected blood samples from 250 Chinese Rex rabbits with six different coat colors. We performed genome sequencing using a restriction site-associated DNA sequencing approach. A total of 91,546 single nucleotide polymorphisms (SNPs), evenly distributed among 21 autosomes, were identified. Genome-wide association studies (GWAS) were performed using a mixed linear model, in which the individual polygenic effect was fitted as a random effect. We detected a total of 24 significant SNPs that were located within a genomic region on chromosome 4 (OCU4). After re-fitting the most significant SNP (OCU4:13,434,448, p = 1.31e-12) as a covariate, another near-significant SNP (OCU4:11,344,946, p = 7.03e-07) was still present. Hence, we conclude that the 2.1-Mb genomic region located between these two significant SNPs is significantly associated with coat color in Chinese Rex rabbits. The well-studied coat-color-associated agouti signaling protein (ASIP) gene is located within this region. Furthermore, low genetic differentiation was also observed among the six coat color varieties. In conclusion, our results confirmed that ASIP is a putative causal gene affecting coat color variation in Chinese Rex rabbits.
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Affiliation(s)
- Kai Zhang
- Sichuan Academy of Grassland Sciences, Chengdu, Sichuan, China
| | - Guozhi Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan, China
| | - Lihuan Wang
- Sichuan Academy of Grassland Sciences, Chengdu, Sichuan, China
| | - Bin Wen
- Sichuan Academy of Grassland Sciences, Chengdu, Sichuan, China
| | - Xiangchao Fu
- Sichuan Academy of Grassland Sciences, Chengdu, Sichuan, China
| | - Ning Liu
- Sichuan Academy of Grassland Sciences, Chengdu, Sichuan, China
| | - Zhiju Yu
- Sichuan Academy of Grassland Sciences, Chengdu, Sichuan, China
| | - Wensu Jian
- Sichuan Academy of Grassland Sciences, Chengdu, Sichuan, China
| | - Xiaolin Guo
- Sichuan Academy of Grassland Sciences, Chengdu, Sichuan, China
| | - Hanzhong Liu
- Sichuan Academy of Grassland Sciences, Chengdu, Sichuan, China
| | - Shi-Yi Chen
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan, China
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Zhang R, Zhang Y, Liu T, Jiang B, Li Z, Qu Y, Chen Y, Li Z. Utilizing Variants Identified with Multiple Genome-Wide Association Study Methods Optimizes Genomic Selection for Growth Traits in Pigs. Animals (Basel) 2023; 13:ani13040722. [PMID: 36830509 PMCID: PMC9952664 DOI: 10.3390/ani13040722] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Revised: 02/09/2023] [Accepted: 02/15/2023] [Indexed: 02/22/2023] Open
Abstract
Improving the prediction accuracies of economically important traits in genomic selection (GS) is a main objective for researchers and breeders in the livestock industry. This study aims at utilizing potentially functional SNPs and QTLs identified with various genome-wide association study (GWAS) models in GS of pig growth traits. We used three well-established GWAS methods, including the mixed linear model, Bayesian model and meta-analysis, as well as 60K SNP-chip and whole genome sequence (WGS) data from 1734 Yorkshire and 1123 Landrace pigs to detect SNPs related to four growth traits: average daily gain, backfat thickness, body weight and birth weight. A total of 1485 significant loci and 24 candidate genes which are involved in skeletal muscle development, fatty deposition, lipid metabolism and insulin resistance were identified. Compared with using all SNP-chip data, GS with the pre-selected functional SNPs in the standard genomic best linear unbiased prediction (GBLUP), and a two-kernel based GBLUP model yielded average gains in accuracy by 4 to 46% (from 0.19 ± 0.07 to 0.56 ± 0.07) and 5 to 27% (from 0.16 ± 0.06 to 0.57 ± 0.05) for the four traits, respectively, suggesting that the prioritization of preselected functional markers in GS models had the potential to improve prediction accuracies for certain traits in livestock breeding.
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Affiliation(s)
- Ruifeng Zhang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou 510006, China
| | - Yi Zhang
- Institute of Neuroscience, Panzhihua University, Panzhihua 617000, China
| | - Tongni Liu
- Genetic Data Center, Faculty of Forestry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Bo Jiang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou 510006, China
| | - Zhenyang Li
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou 510006, China
| | - Youping Qu
- Guangdong IPIG Technology Co., Ltd., Guangzhou 510006, China
| | - Yaosheng Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou 510006, China
| | - Zhengcao Li
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou 510006, China
- Correspondence:
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Yuan Y, Yang B, He Y, Zhang W, E G. Genome-Wide Selection Signal Analysis of Australian Boer Goat by Insertion/Deletion Variants. RUSS J GENET+ 2022. [DOI: 10.1134/s1022795422120158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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Heidaritabar M, Huisman A, Krivushin K, Stothard P, Dervishi E, Charagu P, Bink MCAM, Plastow GS. Imputation to whole-genome sequence and its use in genome-wide association studies for pork colour traits in crossbred and purebred pigs. Front Genet 2022; 13:1022681. [PMID: 36303553 PMCID: PMC9593086 DOI: 10.3389/fgene.2022.1022681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 09/22/2022] [Indexed: 11/16/2022] Open
Abstract
Imputed whole-genome sequence (WGS) has been proposed to improve genome-wide association studies (GWAS), since all causative mutations responsible for phenotypic variation are expected to be present in the data. This approach was applied on a large number of purebred (PB) and crossbred (CB) pigs for 18 pork color traits to evaluate the impact of using imputed WGS relative to medium-density marker panels. The traits included Minolta A*, B*, and L* for fat (FCOL), quadriceps femoris muscle (QFCOL), thawed loin muscle (TMCOL), fresh ham gluteus medius (GMCOL), ham iliopsoas muscle (ICOL), and longissimus dorsi muscle on the fresh loin (FMCOL). Sequence variants were imputed from a medium-density marker panel (61K for CBs and 50K for PBs) in all genotyped pigs using BeagleV5.0. We obtained high imputation accuracy (average of 0.97 for PBs and 0.91 for CBs). GWAS were conducted for three datasets: 954 CBs and 891 PBs, and the combined CBs and PBs. For most traits, no significant associations were detected, regardless of panel density or population type. However, quantitative trait loci (QTL) regions were only found for a few traits including TMCOL Minolta A* and GMCOL Minolta B* (CBs), FMCOL Minolta B*, FMCOL Minolta L*, and ICOL Minolta B* (PBs) and FMCOL Minolta A*, FMCOL Minolta B*, GMCOL Minolta B*, and ICOL Minolta B* (Combined dataset). More QTL regions were identified with WGS (n = 58) relative to medium-density marker panels (n = 22). Most of the QTL were linked to previously reported QTLs or candidate genes that have been previously reported to be associated with meat quality, pH and pork color; e.g., VIL1, PRKAG3, TTLL4, and SLC11A1, USP37. CTDSP1 gene on SSC15 has not been previously associated with meat color traits in pigs. The findings suggest any added value of WGS was only for detecting novel QTL regions when the sample size is sufficiently large as with the Combined dataset in this study. The percentage of phenotypic variance explained by the most significant SNPs also increased with WGS compared with medium-density panels. The results provide additional insights into identification of a number of candidate regions and genes for pork color traits in different pig populations.
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Affiliation(s)
- Marzieh Heidaritabar
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
- *Correspondence: Marzieh Heidaritabar,
| | - Abe Huisman
- Hendrix Genetics Research, Boxmeer, Netherlands
| | - Kirill Krivushin
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Paul Stothard
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Elda Dervishi
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | | | | | - Graham S. Plastow
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
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Salavati M, Woolley SA, Cortés Araya Y, Halstead MM, Stenhouse C, Johnsson M, Ashworth CJ, Archibald AL, Donadeu FX, Hassan MA, Clark EL. Profiling of open chromatin in developing pig (Sus scrofa) muscle to identify regulatory regions. G3 (BETHESDA, MD.) 2022; 12:6460335. [PMID: 34897420 PMCID: PMC9210303 DOI: 10.1093/g3journal/jkab424] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 12/03/2021] [Indexed: 06/14/2023]
Abstract
There is very little information about how the genome is regulated in domestic pigs (Sus scrofa). This lack of knowledge hinders efforts to define and predict the effects of genetic variants in pig breeding programs. To address this knowledge gap, we need to identify regulatory sequences in the pig genome starting with regions of open chromatin. We used the "Improved Protocol for the Assay for Transposase-Accessible Chromatin (Omni-ATAC-Seq)" to identify putative regulatory regions in flash-frozen semitendinosus muscle from 24 male piglets. We collected samples from the smallest-, average-, and largest-sized male piglets from each litter through five developmental time points. Of the 4661 ATAC-Seq peaks identified that represent regions of open chromatin, >50% were within 1 kb of known transcription start sites. Differential read count analysis revealed 377 ATAC-Seq defined genomic regions where chromatin accessibility differed significantly across developmental time points. We found regions of open chromatin associated with downregulation of genes involved in muscle development that were present in small-sized fetal piglets but absent in large-sized fetal piglets at day 90 of gestation. The dataset that we have generated provides a resource for studies of genome regulation in pigs and contributes valuable functional annotation information to filter genetic variants for use in genomic selection in pig breeding programs.
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Affiliation(s)
- Mazdak Salavati
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK
- Centre for Tropical Livestock Genetics and Health (CTLGH), Roslin Institute, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Shernae A Woolley
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Yennifer Cortés Araya
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Michelle M Halstead
- Department of Animal Science, University of California Davis, Davis, CA 95616, USA
| | - Claire Stenhouse
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK
- Department of Animal Science, Texas A&M University, College Station, TX 77843, USA
| | - Martin Johnsson
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala 750 07, Sweden
| | - Cheryl J Ashworth
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Alan L Archibald
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Francesc X Donadeu
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Musa A Hassan
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK
- Centre for Tropical Livestock Genetics and Health (CTLGH), Roslin Institute, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Emily L Clark
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK
- Centre for Tropical Livestock Genetics and Health (CTLGH), Roslin Institute, University of Edinburgh, Edinburgh EH25 9RG, UK
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Kim S, Lim B, Cho J, Lee S, Dang CG, Jeon JH, Kim JM, Lee J. Genome-Wide Identification of Candidate Genes for Milk Production Traits in Korean Holstein Cattle. Animals (Basel) 2021; 11:ani11051392. [PMID: 34068321 PMCID: PMC8153329 DOI: 10.3390/ani11051392] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 05/07/2021] [Accepted: 05/11/2021] [Indexed: 12/12/2022] Open
Abstract
Simple Summary Milk production traits that are economically important in the dairy industry have been considered the main selection criteria for breeding. The present genome-wide association study was performed to identify chromosomal loci and candidate genes with potential effects on milk production phenotypes in a Korean Holstein population. A total of eight significant quantitative trait locus regions were identified for milk yield (Bos taurus autosome (BTA) 7 and 14), adjusted 305-d fat yield (BTA 3, 5, and 14), adjusted 305-d protein yield (BTA 8), and somatic cell score (BTA 8 and 23) of milk production traits. Furthermore, we discovered three main candidate genes (diacylglycerol O-acyltransferase 1 (DGAT1), phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) through bioinformatics analysis. These genes may help to understand better the underlying genetic and molecular mechanisms for milk production phenotypes in the Korean Holstein population. Abstract We performed a genome-wide association study and fine mapping using two methods (single marker regression: frequentist approach and Bayesian C (BayesC): fitting selected single nucleotide polymorphisms (SNPs) in a Bayesian framework) through three high-density SNP chip platforms to analyze milk production phenotypes in Korean Holstein cattle (n = 2780). We identified four significant SNPs for each phenotype in the single marker regression model: AX-311625843 and AX-115099068 on Bos taurus autosome (BTA) 14 for milk yield (MY) and adjusted 305-d fat yield (FY), respectively, AX-428357234 on BTA 18 for adjusted 305-d protein yield (PY), and AX-185120896 on BTA 5 for somatic cell score (SCS). Using the BayesC model, we discovered significant 1-Mb window regions that harbored over 0.5% of the additive genetic variance effects for four milk production phenotypes. The concordant significant SNPs and 1-Mb window regions were characterized into quantitative trait loci (QTL). Among the QTL regions, we focused on a well-known gene (diacylglycerol O-acyltransferase 1 (DGAT1)) and newly identified genes (phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) for MY and FY, and observed that DGAT1 is involved in glycerolipid metabolism, fat digestion and absorption, metabolic pathways, and retinol metabolism, and PDE4B is involved in cAMP signaling. Our findings suggest that the candidate genes in QTL are strongly related to physiological mechanisms related to the fat production and consequent total MY in Korean Holstein cattle.
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Affiliation(s)
- Sangwook Kim
- Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Gyeonggi-do, Korea; (S.K.); (B.L.)
| | - Byeonghwi Lim
- Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Gyeonggi-do, Korea; (S.K.); (B.L.)
| | - Joohyeon Cho
- Dairy Cattle Genetic Improvement Center, Nonghyup, Goyang 10292, Gyeonggi-do, Korea; (J.C.); (S.L.)
| | - Seokhyun Lee
- Dairy Cattle Genetic Improvement Center, Nonghyup, Goyang 10292, Gyeonggi-do, Korea; (J.C.); (S.L.)
| | - Chang-Gwon Dang
- Animal Genetics and Breeding Division, National Institute of Animal Science, RDA, Cheonan 31000, Chungcheongnam-do, Korea;
| | - Jung-Hwan Jeon
- Animal Welfare Research Team, National Institute of Animal Science, RDA, Wanju 55365, Jeollabuk-do, Korea;
| | - Jun-Mo Kim
- Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Gyeonggi-do, Korea; (S.K.); (B.L.)
- Correspondence: (J.-M.K.); (J.L.); Tel.: +82-31-670-3263 (J.-M.K. & J.L.); Fax: +82-31-675-3108 (J.-M.K. & J.L.)
| | - Jungjae Lee
- Department of Animal Science and Technology, Chung-Ang University, Anseong 17546, Gyeonggi-do, Korea; (S.K.); (B.L.)
- Correspondence: (J.-M.K.); (J.L.); Tel.: +82-31-670-3263 (J.-M.K. & J.L.); Fax: +82-31-675-3108 (J.-M.K. & J.L.)
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Estimation of Variance Components and Genomic Prediction for Individual Birth Weight Using Three Different Genome-Wide SNP Platforms in Yorkshire Pigs. Animals (Basel) 2020; 10:ani10122219. [PMID: 33256056 PMCID: PMC7761447 DOI: 10.3390/ani10122219] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 11/20/2020] [Accepted: 11/23/2020] [Indexed: 11/17/2022] Open
Abstract
Simple Summary The individual birth weight (IBW) of pigs is an important trait regarding its relevance to mortality at weaning, sow prolificacy, and growth performance. This study investigates the variance component estimation, informative window regions, and the efficiency of genomic predictions associated with IBW traits in Yorkshire pigs. The low heritability (0.13) is estimated on the basis of a full model including individual genetic, sow genetic, and common environmental effects. Two common window regions of the genome are identified under three different genotyping platforms found within the ARAP2 and TSN genes concerning the IBW trait. The genomic prediction ability is improved using deregressed estimated breeding values including parental information as a response variable despite Bayesian methods and genotyping platforms for the IBW trait in Korean Yorkshire pigs. Abstract This study estimates the individual birth weight (IBW) trait heritability and investigates the genomic prediction efficiency using three types of high-density single nucleotide polymorphism (SNP) genotyping panels in Korean Yorkshire pigs. We use 38,864 IBW phenotypic records to identify a suitable model for statistical genetics, where 698 genotypes match our phenotypic records. During our genomic analysis, the deregressed estimated breeding values (DEBVs) and their reliabilities are used as derived response variables from the estimated breeding values (EBVs). Bayesian methods identify the informative regions and perform the genomic prediction using the IBW trait, in which two common significant window regions (SSC8 27 Mb and SSC15 29 Mb) are identified using the three genotyping platforms. Higher prediction ability is observed using the DEBV-including parent average as a response variable, regardless of the SNP genotyping panels and the Bayesian methods, relative to the DEBV-excluding parent average. Hence, we suggest that fine-mapping studies targeting the identified informative regions in this study are necessary to find the causal mutations to improve the IBW trait’s prediction ability. Furthermore, studying the IBW trait using a genomic prediction model with a larger genomic dataset may improve the genomic prediction accuracy in Korean Yorkshire pigs.
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