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Garcia IS, Silva-Vignato B, Cesar ASM, Petrini J, da Silva VH, Morosini NS, Goes CP, Afonso J, da Silva TR, Lima BD, Clemente LG, Regitano LCDA, Mourão GB, Coutinho LL. Novel putative causal mutations associated with fat traits in Nellore cattle uncovered by eQTLs located in open chromatin regions. Sci Rep 2024; 14:10094. [PMID: 38698200 PMCID: PMC11066111 DOI: 10.1038/s41598-024-60703-5] [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: 10/19/2023] [Accepted: 04/26/2024] [Indexed: 05/05/2024] Open
Abstract
Intramuscular fat (IMF) and backfat thickness (BFT) are critical economic traits impacting meat quality. However, the genetic variants controlling these traits need to be better understood. To advance knowledge in this area, we integrated RNA-seq and single nucleotide polymorphisms (SNPs) identified in genomic and transcriptomic data to generate a linkage disequilibrium filtered panel of 553,581 variants. Expression quantitative trait loci (eQTL) analysis revealed 36,916 cis-eQTLs and 14,408 trans-eQTLs. Association analysis resulted in three eQTLs associated with BFT and 24 with IMF. Functional enrichment analysis of genes regulated by these 27 eQTLs revealed noteworthy pathways that can play a fundamental role in lipid metabolism and fat deposition, such as immune response, cytoskeleton remodeling, iron transport, and phospholipid metabolism. We next used ATAC-Seq assay to identify and overlap eQTL and open chromatin regions. Six eQTLs were in regulatory regions, four in predicted insulators and possible CCCTC-binding factor DNA binding sites, one in an active enhancer region, and the last in a low signal region. Our results provided novel insights into the transcriptional regulation of IMF and BFT, unraveling putative regulatory variants.
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Affiliation(s)
- Ingrid Soares Garcia
- Department of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil
| | - Bárbara Silva-Vignato
- Department of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil
| | - Aline Silva Mello Cesar
- Department of Agroindustry, Food and Nutrition, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil
| | - Juliana Petrini
- Department of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil
| | - Vinicius Henrique da Silva
- Department of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil
| | - Natália Silva Morosini
- Department of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil
| | - Carolina Purcell Goes
- Department of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil
| | | | - Thaís Ribeiro da Silva
- Department of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil
| | - Beatriz Delcarme Lima
- Department of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil
| | - Luan Gaspar Clemente
- Department of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil
| | | | - Gerson Barreto Mourão
- Department of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil
| | - Luiz Lehmann Coutinho
- Department of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil.
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Corrêa MSL, Silva EN, Dos Santos TCF, Simielli Fonseca LF, Magalhães AFB, Verardo LL, de Albuquerque LG, Silva DBDS. A network-based approach to understanding gene-biological processes affecting economically important traits of Nelore cattle. Anim Genet 2024; 55:55-65. [PMID: 38112158 DOI: 10.1111/age.13389] [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: 10/07/2023] [Revised: 10/07/2023] [Accepted: 11/29/2023] [Indexed: 12/20/2023]
Abstract
This study aimed to build gene-biological process networks with differentially expressed genes associated with economically important traits of Nelore cattle from 17 previous studies. The genes were clustered into three groups by evaluated traits: group 1, production traits; group 2, carcass traits; and group 3, meat quality traits. For each group, a gene-biological process network analysis was performed with the differentially expressed genes in common. For production traits, 37 genes were found in common, of which 13 genes were enriched for six Gene Ontology (GO) terms; these terms were not functionally grouped. However, the enriched GO terms were related to homeostasis, the development of muscles and the immune system. For carcass traits, four genes were found in common. Thus, it was not possible to functionally group these genes into a network. For meat quality traits, the analysis revealed 222 genes in common. CSRP3 was the only gene differentially expressed in all three groups. Non-redundant biological terms for clusters of genes were functionally grouped networks, reflecting the cross-talk between all biological processes and genes involved. Many biological processes and pathways related to muscles, the immune system and lipid metabolism were enriched, such as striated muscle cell development and triglyceride metabolic processes. This study provides insights into the genetic mechanisms of production, carcass and meat quality traits of Nelore cattle. This information is fundamental for a better understanding of the complex traits and could help in planning strategies for the production and selection systems of Nelore cattle.
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Affiliation(s)
| | - Evandro Neves Silva
- Professor Edson Antônio Velano University (UNIFENAS), Alfenas, Minas Gerais, Brazil
- Federal University of Alfenas (UNIFAL), Alfenas, Minas Gerais, Brazil
| | - Thaís Cristina Ferreira Dos Santos
- Professor Edson Antônio Velano University (UNIFENAS), Alfenas, Minas Gerais, Brazil
- National Center for Research in Energy and Materials (CNPEM), Campinas, São Paulo, Brazil
| | | | - Ana Fabrícia Braga Magalhães
- Department of Animal Science, Federal University of Vales do Jequitinhonha e Mucuri (UFVJM), Diamantina, Minas Gerais, Brazil
| | - Lucas Lima Verardo
- Department of Animal Science, Federal University of Vales do Jequitinhonha e Mucuri (UFVJM), Diamantina, Minas Gerais, Brazil
| | - Lucia Galvão de Albuquerque
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Jaboticabal, São Paulo, Brazil
| | - Danielly Beraldo Dos Santos Silva
- Professor Edson Antônio Velano University (UNIFENAS), Alfenas, Minas Gerais, Brazil
- School of Agricultural and Veterinarian Sciences, São Paulo State University (UNESP), Jaboticabal, São Paulo, Brazil
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Use of a graph neural network to the weighted gene co-expression network analysis of Korean native cattle. Sci Rep 2022; 12:9854. [PMID: 35701465 PMCID: PMC9197844 DOI: 10.1038/s41598-022-13796-9] [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: 11/09/2021] [Accepted: 05/27/2022] [Indexed: 11/25/2022] Open
Abstract
In the general framework of the weighted gene co-expression network analysis (WGCNA), a hierarchical clustering algorithm is commonly used to module definition. However, hierarchical clustering depends strongly on the topological overlap measure. In other words, this algorithm may assign two genes with low topological overlap to different modules even though their expression patterns are similar. Here, a novel gene module clustering algorithm for WGCNA is proposed. We develop a gene module clustering network (gmcNet), which simultaneously addresses single-level expression and topological overlap measure. The proposed gmcNet includes a “co-expression pattern recognizer” (CEPR) and “module classifier”. The CEPR incorporates expression features of single genes into the topological features of co-expressed ones. Given this CEPR-embedded feature, the module classifier computes module assignment probabilities. We validated gmcNet performance using 4,976 genes from 20 native Korean cattle. We observed that the CEPR generates more robust features than single-level expression or topological overlap measure. Given the CEPR-embedded feature, gmcNet achieved the best performance in terms of modularity (0.261) and the differentially expressed signal (27.739) compared with other clustering methods tested. Furthermore, gmcNet detected some interesting biological functionalities for carcass weight, backfat thickness, intramuscular fat, and beef tenderness of Korean native cattle. Therefore, gmcNet is a useful framework for WGCNA module clustering.
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Overlapping haplotype blocks indicate shared genomic regions between a composite beef cattle breed and its founder breeds. Livest Sci 2021. [DOI: 10.1016/j.livsci.2021.104747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Liu D, Chen Z, Zhao W, Guo L, Sun H, Zhu K, Liu G, Shen X, Zhao X, Wang Q, Ma P, Pan Y. Genome-wide selection signatures detection in Shanghai Holstein cattle population identified genes related to adaption, health and reproduction traits. BMC Genomics 2021; 22:747. [PMID: 34654366 PMCID: PMC8520274 DOI: 10.1186/s12864-021-08042-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 09/28/2021] [Indexed: 12/26/2022] Open
Abstract
Background Over several decades, a wide range of natural and artificial selection events in response to subtropical environments, intensive pasture and intensive feedlot systems have greatly changed the customary behaviour, appearance, and important economic traits of Shanghai Holstein cattle. In particular, the longevity of the Shanghai Holstein cattle population is generally short, approximately the 2nd to 3rd lactation. In this study, two complementary approaches, integrated haplotype score (iHS) and runs of homozygosity (ROH), were applied for the detection of selection signatures within the genome using genotyping by genome-reduced sequence data from 1092 cows. Results In total, 101 significant iHS genomic regions containing selection signatures encompassing a total of 256 candidate genes were detected. There were 27 significant |iHS| genomic regions with a mean |iHS| score > 2. The average number of ROH per individual was 42.15 ± 25.47, with an average size of 2.95 Mb. The length of 78 % of the detected ROH was within the range of 1–2 MB and 2–4 MB, and 99 % were shorter than 8 Mb. A total of 168 genes were detected in 18 ROH islands (top 1 %) across 16 autosomes, in which each SNP showed a percentage of occurrence > 30 %. There were 160 and 167 genes associated with the 52 candidate regions within health-related QTL intervals and 59 candidate regions within reproduction-related QTL intervals, respectively. Annotation of the regions harbouring clustered |iHS| signals and candidate regions for ROH revealed a panel of interesting candidate genes associated with adaptation and economic traits, such as IL22RA1, CALHM3, ITGA9, NDUFB3, RGS3, SOD2, SNRPA1, ST3GAL4, ALAD, EXOSC10, and MASP2. In a further step, a total of 1472 SNPs in 256 genes were matched with 352 cis-eQTLs in 21 tissues and 27 trans-eQTLs in 6 tissues. For SNPs located in candidate regions for ROH, a total of 108 cis-eQTLs in 13 tissues and 4 trans-eQTLs were found for 1092 SNPs. Eighty-one eGenes were significantly expressed in at least one tissue relevant to a trait (P value < 0.05) and matched the 256 genes detected by iHS. For the 168 significant genes detected by ROH, 47 gene-tissue pairs were significantly associated with at least one of the 37 traits. Conclusions We provide a comprehensive overview of selection signatures in Shanghai Holstein cattle genomes by combining iHS and ROH. Our study provides a list of genes associated with immunity, reproduction and adaptation. For functional annotation, the cGTEx resource was used to interpret SNP-trait associations. The results may facilitate the identification of genes relevant to important economic traits and can help us better understand the biological processes and mechanisms affected by strong ongoing natural or artificial selection in livestock populations. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-08042-x.
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Affiliation(s)
- Dengying Liu
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, 200240, Shanghai, PR China
| | - Zhenliang Chen
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, 200240, Shanghai, PR China
| | - Wei Zhao
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, 200240, Shanghai, PR China
| | - Longyu Guo
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, 200240, Shanghai, PR China
| | - Hao Sun
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, 200240, Shanghai, PR China
| | - Kai Zhu
- Shanghai Dairy Cattle Breeding Centre Co., Ltd, 201901, Shanghai, P.R. China
| | - Guanglei Liu
- Shanghai Dairy Cattle Breeding Centre Co., Ltd, 201901, Shanghai, P.R. China
| | - Xiuping Shen
- Shanghai Agricultural Development Promotion Center, 200335, Shanghai, PR China
| | - Xiaoduo Zhao
- Shanghai Dairy Cattle Breeding Centre Co., Ltd, 201901, Shanghai, P.R. China
| | - Qishan Wang
- Department of Animal Breeding and Reproduction, College of Animal Science, Zhejiang University, 310058, Hangzhou, PR China
| | - Peipei Ma
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, 200240, Shanghai, PR China.
| | - Yuchun Pan
- Department of Animal Breeding and Reproduction, College of Animal Science, Zhejiang University, 310058, Hangzhou, PR China.
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