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Qadri QR, Lai X, Zhao W, Zhang Z, Zhao Q, Ma P, Pan Y, Wang Q. Exploring the Interplay between the Hologenome and Complex Traits in Bovine and Porcine Animals Using Genome-Wide Association Analysis. Int J Mol Sci 2024; 25:6234. [PMID: 38892420 PMCID: PMC11172659 DOI: 10.3390/ijms25116234] [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: 03/15/2024] [Revised: 05/25/2024] [Accepted: 05/29/2024] [Indexed: 06/21/2024] Open
Abstract
Genome-wide association studies (GWAS) significantly enhance our ability to identify trait-associated genomic variants by considering the host genome. Moreover, the hologenome refers to the host organism's collective genetic material and its associated microbiome. In this study, we utilized the hologenome framework, called Hologenome-wide association studies (HWAS), to dissect the architecture of complex traits, including milk yield, methane emissions, rumen physiology in cattle, and gut microbial composition in pigs. We employed four statistical models: (1) GWAS, (2) Microbial GWAS (M-GWAS), (3) HWAS-CG (hologenome interaction estimated using COvariance between Random Effects Genome-based restricted maximum likelihood (CORE-GREML)), and (4) HWAS-H (hologenome interaction estimated using the Hadamard product method). We applied Bonferroni correction to interpret the significant associations in the complex traits. The GWAS and M-GWAS detected one and sixteen significant SNPs for milk yield traits, respectively, whereas the HWAS-CG and HWAS-H each identified eight SNPs. Moreover, HWAS-CG revealed four, and the remaining models identified three SNPs each for methane emissions traits. The GWAS and HWAS-CG detected one and three SNPs for rumen physiology traits, respectively. For the pigs' gut microbial composition traits, the GWAS, M-GWAS, HWAS-CG, and HWAS-H identified 14, 16, 13, and 12 SNPs, respectively. We further explored these associations through SNP annotation and by analyzing biological processes and functional pathways. Additionally, we integrated our GWA results with expression quantitative trait locus (eQTL) data using transcriptome-wide association studies (TWAS) and summary-based Mendelian randomization (SMR) methods for a more comprehensive understanding of SNP-trait associations. Our study revealed hologenomic variability in agriculturally important traits, enhancing our understanding of host-microbiome interactions.
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Affiliation(s)
- Qamar Raza Qadri
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China; (Q.R.Q.); (P.M.)
| | - Xueshuang Lai
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Science, Zhejiang University, Hangzhou 310030, China; (X.L.); (W.Z.); (Z.Z.); (Y.P.)
| | - Wei Zhao
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Science, Zhejiang University, Hangzhou 310030, China; (X.L.); (W.Z.); (Z.Z.); (Y.P.)
| | - Zhenyang Zhang
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Science, Zhejiang University, Hangzhou 310030, China; (X.L.); (W.Z.); (Z.Z.); (Y.P.)
| | - Qingbo Zhao
- Institute of Swine Science, Nanjing Agricultural University, Nanjing 210095, China;
| | - Peipei Ma
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China; (Q.R.Q.); (P.M.)
| | - Yuchun Pan
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Science, Zhejiang University, Hangzhou 310030, China; (X.L.); (W.Z.); (Z.Z.); (Y.P.)
- Hainan Institute, Zhejiang University, Yongyou Industry Park, Yazhou Bay Sci-Tech City, Sanya 572000, China
| | - Qishan Wang
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Science, Zhejiang University, Hangzhou 310030, China; (X.L.); (W.Z.); (Z.Z.); (Y.P.)
- Hainan Institute, Zhejiang University, Yongyou Industry Park, Yazhou Bay Sci-Tech City, Sanya 572000, China
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Devailly G, Fève K, Saci S, Sarry J, Valière S, Lluch J, Bouchez O, Ravon L, Billon Y, Gilbert H, Riquet J, Beaumont M, Demars J. Divergent selection for feed efficiency in pigs altered the duodenum transcriptomic response to feed intake and its DNA methylation profiles. Physiol Genomics 2024; 56:397-408. [PMID: 38497119 DOI: 10.1152/physiolgenomics.00123.2023] [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: 10/20/2023] [Revised: 03/01/2024] [Accepted: 03/10/2024] [Indexed: 03/19/2024] Open
Abstract
Feed efficiency is a trait of interest in pigs as it contributes to lowering the ecological and economical costs of pig production. A divergent genetic selection experiment from a Large White pig population was performed for 10 generations, leading to pig lines with relatively low- (LRFI) and high- (HRFI) residual feed intake (RFI). Feeding behavior and metabolic differences have been previously reported between the two lines. We hypothesized that part of these differences could be related to differential sensing and absorption of nutrients in the proximal intestine. We investigated the duodenum transcriptome and DNA methylation profiles comparing overnight fasting with ad libitum feeding in LRFI and HRFI pigs (n = 24). We identified 1,106 differentially expressed genes between the two lines, notably affecting pathways of the transmembrane transport activity and related to mitosis or chromosome separation. The LRFI line showed a greater transcriptomic response to feed intake than the HRFI line. Feed intake affected genes from both anabolic and catabolic pathways in the pig duodenum, such as rRNA production and autophagy. Several nutrient transporter and tight junction genes were differentially expressed between lines and/or by short-term feed intake. We also identified 409 differentially methylated regions in the duodenum mucosa between the two lines, while this epigenetic mark was less affected by feeding. Our findings highlighted that the genetic selection for feed efficiency in pigs changed the transcriptome profiles of the duodenum, and notably its response to feed intake, suggesting key roles for this proximal gut segment in mechanisms underlying feed efficiency.NEW & NOTEWORTHY The duodenum is a key organ for the hunger/satiety loop and nutrient sensing. We investigated how the duodenum transcriptome and DNA methylation profiles are affected by feed intakes in pigs. We observed thousands of changes in gene expression levels between overnight-fasted and fed pigs in high-feed efficiency pig lines, but almost none in the related low-feed efficiency pig line.
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Affiliation(s)
| | - Katia Fève
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
| | - Safia Saci
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
| | - Julien Sarry
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
| | - Sophie Valière
- INRAE, US 1426, GeT-PlaGe, Genotoul, Castanet-Tolosan, France
| | - Jérôme Lluch
- INRAE, US 1426, GeT-PlaGe, Genotoul, Castanet-Tolosan, France
| | - Olivier Bouchez
- INRAE, US 1426, GeT-PlaGe, Genotoul, Castanet-Tolosan, France
| | - Laure Ravon
- Pig Phenotyping and Innovative Breeding Facility, GenESI, UE1372, INRAE, Surgères, France
| | - Yvon Billon
- Pig Phenotyping and Innovative Breeding Facility, GenESI, UE1372, INRAE, Surgères, France
| | - Hélène Gilbert
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
| | - Juliette Riquet
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
| | - Martin Beaumont
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
| | - Julie Demars
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France
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Atrian-Afiani F, Berger B, Draxl C, Sölkner J, Mészáros G. Selective Sweeps in the Austrian Turopolje and Other Commercial Pig Populations. Animals (Basel) 2023; 13:3749. [PMID: 38136787 PMCID: PMC10741191 DOI: 10.3390/ani13243749] [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: 10/16/2023] [Revised: 11/30/2023] [Accepted: 11/30/2023] [Indexed: 12/24/2023] Open
Abstract
The goal of our study was to identify signatures of selection in the Turopolje pigs and other commercial pig breeds. We conducted a comprehensive analysis of five datasets, including one local pig breed (Turopolje) and four commercial pig breeds (Large White, Landrace, Pietrain, and Duroc), using strict quality control measures. Our final dataset consisted of 485 individuals and 54,075 single nucleotide polymorphisms (SNPs). To detect selection signatures within these pig breeds, we utilized the XP-EHH and XP-nSL methodologies, which allowed us to identify candidate genes that have been subject to positive selection. Our analysis consistently highlighted the PTBP2 and DPYD genes as commonly targeted by selection in the Turopolje breed. DPYD is associated with muscular development in pigs and other species and PTBP2 emerges as one of the potential genes linked to seminal characteristics. Furthermore, in the Large White breed, a number of genes were detected with the two methods, such as ATP1A1, CASQ2, CD2, IGSF3, MAB21L3, NHLH2, SLC22A15, VANGL1. In the Duroc breed, a different set of genes was detected, such as ARSB, BHMT, BHMT2, DMGDH, JMY. The function of these genes was related to body weight, production efficiency and meat quality, average daily gain, and other similar traits. Overall, our results have identified a number of genomic regions that are under selective pressure between local and commercial pig breeds. This information can help to improve our understanding of the mechanisms underlying pig breeding, and ultimately contribute to the development of more efficient and sustainable pig production practices. Our study highlights the power of using multiple genomic methodologies to detect genetic signatures of selection, and provides important insights into the genetic diversity of pig breeds.
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Affiliation(s)
- Farzad Atrian-Afiani
- Institute of Livestock Sciences (NUWI), University of Natural Resources and Life Sciences, Vienna, 1180 Vienna, Austria; (F.A.-A.); (J.S.)
| | - Beate Berger
- Institut für Biologische Landwirtschaft und Biodiversität der Nutztiere, HBLFA Raumberg-Gumpenstein 2, 4600 Thalheim bei Wels, Austria;
| | - Christian Draxl
- Österreichische Schweineprüfanstalt GmbH, 2004 Streitdorf, Austria;
| | - Johann Sölkner
- Institute of Livestock Sciences (NUWI), University of Natural Resources and Life Sciences, Vienna, 1180 Vienna, Austria; (F.A.-A.); (J.S.)
| | - Gábor Mészáros
- Institute of Livestock Sciences (NUWI), University of Natural Resources and Life Sciences, Vienna, 1180 Vienna, Austria; (F.A.-A.); (J.S.)
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Zhou GL, Xu FJ, Qiao JK, Che ZX, Xiang T, Liu XL, Li XY, Zhao SH, Zhu MJ. E-GWAS: an ensemble-like GWAS strategy that provides effective control over false positive rates without decreasing true positives. Genet Sel Evol 2023; 55:46. [PMID: 37407918 DOI: 10.1186/s12711-023-00820-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 06/23/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) are an effective way to explore genotype-phenotype associations in humans, animals, and plants. Various GWAS methods have been developed based on different genetic or statistical assumptions. However, no single method is optimal for all traits and, for many traits, the putative single nucleotide polymorphisms (SNPs) that are detected by the different methods do not entirely overlap due to the diversity of the genetic architecture of complex traits. Therefore, multi-tool-based GWAS strategies that combine different methods have been increasingly employed. To take this one step further, we propose an ensemble-like GWAS strategy (E-GWAS) that statistically integrates GWAS results from different single GWAS methods. RESULTS E-GWAS was compared with various single GWAS methods using simulated phenotype traits with different genetic architectures. E-GWAS performed stably across traits with different genetic architectures and effectively controlled the number of false positive genetic variants detected without decreasing the number of true positive variants. In addition, its performance could be further improved by using a bin-merged strategy and the addition of more distinct single GWAS methods. Our results show that the numbers of true and false positive SNPs detected by the E-GWAS strategy slightly increased and decreased, respectively, with increasing bin size and when the number and the diversity of individual GWAS methods that were integrated in E-GWAS increased, the latter being more effective than the bin-merged strategy. The E-GWAS strategy was also applied to a real dataset to study backfat thickness in a pig population, and 10 candidate genes related to this trait and expressed in adipose-associated tissues were identified. CONCLUSIONS Using both simulated and real datasets, we show that E-GWAS is a reliable and robust strategy that effectively integrates the GWAS results of different methods and reduces the number of false positive SNPs without decreasing that of true positive SNPs.
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Affiliation(s)
- Guang-Liang Zhou
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
| | - Fang-Jun Xu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
| | - Jia-Kun Qiao
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
| | - Zhao-Xuan Che
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
| | - Tao Xiang
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, 430070, China
| | - Xiao-Lei Liu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, 430070, China
| | - Xin-Yun Li
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, 430070, China
| | - Shu-Hong Zhao
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, 430070, China
| | - Meng-Jin Zhu
- Key Lab of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China.
- The Cooperative Innovation Center for Sustainable Pig Production, Huazhong Agricultural University, Wuhan, 430070, China.
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Wang H, Li Q, Xu R, Su Y, Zhu W. Time-restricted feeding affects colonic nutrient substrates and modulates the diurnal fluctuation of microbiota in pigs. Front Microbiol 2023; 14:1162482. [PMID: 37275162 PMCID: PMC10235616 DOI: 10.3389/fmicb.2023.1162482] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 05/09/2023] [Indexed: 06/07/2023] Open
Abstract
Introduction Studies demonstrate that time-restricted feeding (TRF) can regulate gut microbiota composition. However, it is unclear whether TRF could affect the gut microbial rhythmicity in growing pigs. Therefore, the present study aimed to explore the effects of TRF on the dynamic fluctuation of the gut microbiota. Methods A total of 10 healthy growing pigs equipped with T cannula were employed. Pigs were randomly allotted to the free access (FA) and the TRF groups with 5 replicates (1 pig/replicates). Pigs in the FA group were fed free access during the whole experimental period, whereas pigs in the TRF group were fed free access three times per day within limited times (7:00-8:00, 12:00-13:00, 17:00-18:00). The experiment lasted for 15 days, at 06:00 a.m. of the day 16, colonic digesta were collected at a 6-h interval for consecutive 24 h marked as T06 (06:00), T12 (12:00), T18 (18:00), T24 (24:00), T30 (06:00), respectively. Results Results showed that TRF altered the distribution of feed intake without changing the total feed intake within a day (p = 0.870). TRF decreased the overall concentration of colonic cellulose and altered their oscillating patterns. All alpha-diversity indexes of different time points showed significant differences regardless of feeding pattern with a trough at T18 or T24. TRF shifted the trough of the alpha-diversity index Simpson and Invsimpson. TRF lost the rhythmicity of Prevotellaceae, Ruminococcaceae, Bacteroidales_S24-7_group, and Peptococcaceae and gained the rhythmicity of Pasteurellaceae, Clostridiaceae_1, Veillonellaceae, and Peptostreptococcaceae. Also, TRF altered the interaction pattern by increasing the microbes involved in the co-occurrence network and their crosstalk, especially at T24. Interestingly, the microbial variation at T24 could largely explained by colonic substrates starch (R2 = 0.369; p = 0.001), cellulose (R2 = 0.235; p = 0.009) and NH4-N (R2 = 0.489; p = 0.001). Conclusion In conclusion, TRF has changed the concentrates of cellulose and the relative abundance of specific microbes and certain microbial metabolites. In addition, TRF has more powerful effects on the fluctuation modes of these nutrient substrates, microbes, and metabolites by shifting their peaks or troughs. This knowledge facilitates the development of precision regulation targeting gut microbial rhythmicity.
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Affiliation(s)
- Hongyu Wang
- Laboratory of Gastrointestinal Microbiology, Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
- National Center for International Research on Animal Gut Nutrition, Nanjing Agricultural University, Nanjing, China
| | - Qiuke Li
- Laboratory of Gastrointestinal Microbiology, Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
- National Center for International Research on Animal Gut Nutrition, Nanjing Agricultural University, Nanjing, China
| | - Rongying Xu
- Laboratory of Gastrointestinal Microbiology, Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
- National Center for International Research on Animal Gut Nutrition, Nanjing Agricultural University, Nanjing, China
| | - Yong Su
- Laboratory of Gastrointestinal Microbiology, Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
- National Center for International Research on Animal Gut Nutrition, Nanjing Agricultural University, Nanjing, China
| | - Weiyun Zhu
- Laboratory of Gastrointestinal Microbiology, Jiangsu Key Laboratory of Gastrointestinal Nutrition and Animal Health, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
- National Center for International Research on Animal Gut Nutrition, Nanjing Agricultural University, Nanjing, China
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Blaj I, Tetens J, Bennewitz J, Thaller G, Falker-Gieske C. Structural variants and tandem repeats in the founder individuals of four F 2 pig crosses and implications to F 2 GWAS results. BMC Genomics 2022; 23:631. [PMID: 36057580 PMCID: PMC9440560 DOI: 10.1186/s12864-022-08716-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 06/23/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Structural variants and tandem repeats are relevant sources of genomic variation that are not routinely analyzed in genome wide association studies mainly due to challenging identification and genotyping. Here, we profiled these variants via state-of-the-art strategies in the founder animals of four F2 pig crosses using whole-genome sequence data (20x coverage). The variants were compared at a founder level with the commonly screened SNPs and small indels. At the F2 level, we carried out an association study using imputed structural variants and tandem repeats with four growth and carcass traits followed by a comparison with a previously conducted SNPs and small indels based association study. RESULTS A total of 13,201 high confidence structural variants and 103,730 polymorphic tandem repeats (with a repeat length of 2-20 bp) were profiled in the founders. We observed a moderate to high (r from 0.48 to 0.57) level of co-localization between SNPs or small indels and structural variants or tandem repeats. In the association step 56.56% of the significant variants were not in high LD with significantly associated SNPs and small indels identified for the same traits in the earlier study and thus presumably not tagged in case of a standard association study. For the four growth and carcass traits investigated, many of the already proposed candidate genes in our previous studies were confirmed and additional ones were identified. Interestingly, a common pattern on how structural variants or tandem repeats regulate the phenotypic traits emerged. Many of the significant variants were embedded or nearby long non-coding RNAs drawing attention to their functional importance. Through which specific mechanisms the identified long non-coding RNAs and their associated structural variants or tandem repeats contribute to quantitative trait variation will need further investigation. CONCLUSIONS The current study provides insights into the characteristics of structural variants and tandem repeats and their role in association studies. A systematic incorporation of these variants into genome wide association studies is advised. While not of immediate interest for genomic prediction purposes, this will be particularly beneficial for elucidating biological mechanisms driving the complex trait variation.
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Affiliation(s)
- Iulia Blaj
- Institute of Animal Breeding and Husbandry, Kiel University, Kiel, Germany.
| | - Jens Tetens
- Department of Animal Sciences, Georg-August-University, Göttingen, Germany
- Center for Integrated Breeding Research, Georg-August-University, Göttingen, Germany
| | - Jörn Bennewitz
- Institute of Animal Husbandry and Breeding, University of Hohenheim, Stuttgart, Germany
| | - Georg Thaller
- Institute of Animal Breeding and Husbandry, Kiel University, Kiel, Germany
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