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Beiki H, Murdoch BM, Park CA, Kern C, Kontechy D, Becker G, Rincon G, Jiang H, Zhou H, Thorne J, Koltes JE, Michal JJ, Davenport K, Rijnkels M, Ross PJ, Hu R, Corum S, McKay S, Smith TPL, Liu W, Ma W, Zhang X, Xu X, Han X, Jiang Z, Hu ZL, Reecy JM. Enhanced bovine genome annotation through integration of transcriptomics and epi-transcriptomics datasets facilitates genomic biology. Gigascience 2024; 13:giae019. [PMID: 38626724 PMCID: PMC11020238 DOI: 10.1093/gigascience/giae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 07/29/2023] [Accepted: 03/27/2024] [Indexed: 04/18/2024] Open
Abstract
BACKGROUND The accurate identification of the functional elements in the bovine genome is a fundamental requirement for high-quality analysis of data informing both genome biology and genomic selection. Functional annotation of the bovine genome was performed to identify a more complete catalog of transcript isoforms across bovine tissues. RESULTS A total of 160,820 unique transcripts (50% protein coding) representing 34,882 unique genes (60% protein coding) were identified across tissues. Among them, 118,563 transcripts (73% of the total) were structurally validated by independent datasets (PacBio isoform sequencing data, Oxford Nanopore Technologies sequencing data, de novo assembled transcripts from RNA sequencing data) and comparison with Ensembl and NCBI gene sets. In addition, all transcripts were supported by extensive data from different technologies such as whole transcriptome termini site sequencing, RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression, chromatin immunoprecipitation sequencing, and assay for transposase-accessible chromatin using sequencing. A large proportion of identified transcripts (69%) were unannotated, of which 86% were produced by annotated genes and 14% by unannotated genes. A median of two 5' untranslated regions were expressed per gene. Around 50% of protein-coding genes in each tissue were bifunctional and transcribed both coding and noncoding isoforms. Furthermore, we identified 3,744 genes that functioned as noncoding genes in fetal tissues but as protein-coding genes in adult tissues. Our new bovine genome annotation extended more than 11,000 annotated gene borders compared to Ensembl or NCBI annotations. The resulting bovine transcriptome was integrated with publicly available quantitative trait loci data to study tissue-tissue interconnection involved in different traits and construct the first bovine trait similarity network. CONCLUSIONS These validated results show significant improvement over current bovine genome annotations.
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Affiliation(s)
- Hamid Beiki
- Department of Animal Science, Iowa State University, Ames, IA 50011, USA
| | - Brenda M Murdoch
- Department of Animal and Veterinary and Food Science, University of Idaho, ID 83844, USA
| | - Carissa A Park
- Department of Animal Science, Iowa State University, Ames, IA 50011, USA
| | - Chandlar Kern
- Department of Animal Science, Pennsylvania State University, PA 16802, USA
| | - Denise Kontechy
- Department of Animal and Veterinary and Food Science, University of Idaho, ID 83844, USA
| | - Gabrielle Becker
- Department of Animal and Veterinary and Food Science, University of Idaho, ID 83844, USA
| | | | - Honglin Jiang
- Department of Animal and Poultry Sciences, Virginia Tech, VA 24060, USA
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, CA 95616, USA
| | - Jacob Thorne
- Department of Animal and Veterinary and Food Science, University of Idaho, ID 83844, USA
| | - James E Koltes
- Department of Animal Science, Iowa State University, Ames, IA 50011, USA
| | - Jennifer J Michal
- Department of Animal Science, Washington State University, WA 99164, USA
| | - Kimberly Davenport
- Department of Animal and Veterinary and Food Science, University of Idaho, ID 83844, USA
| | - Monique Rijnkels
- Department of Veterinary Integrative Biosciences, Texas A&M University, TX 77843, USA
| | - Pablo J Ross
- Department of Animal Science, University of California, Davis, CA 95616, USA
| | - Rui Hu
- Department of Animal and Poultry Sciences, Virginia Tech, VA 24060, USA
| | - Sarah Corum
- Zoetis, Parsippany-Troy Hills, NJ 07054, USA
| | | | | | - Wansheng Liu
- Department of Animal Science, Pennsylvania State University, PA 16802, USA
| | - Wenzhi Ma
- Department of Animal Science, Pennsylvania State University, PA 16802, USA
| | - Xiaohui Zhang
- Department of Animal Science, Washington State University, WA 99164, USA
| | - Xiaoqing Xu
- Department of Animal Science, University of California, Davis, CA 95616, USA
| | - Xuelei Han
- Department of Animal Science, Washington State University, WA 99164, USA
| | - Zhihua Jiang
- Department of Animal Science, Washington State University, WA 99164, USA
| | - Zhi-Liang Hu
- Department of Animal Science, Iowa State University, Ames, IA 50011, USA
| | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA 50011, USA
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2
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Hu ZL, Park CA, Reecy JM. A combinatorial approach implementing new database structures to facilitate practical data curation management of QTL, association, correlation and heritability data on trait variants. Database (Oxford) 2023; 2023:7135870. [PMID: 37084387 PMCID: PMC10121204 DOI: 10.1093/database/baad024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 02/28/2023] [Accepted: 03/27/2023] [Indexed: 04/23/2023]
Abstract
A precise description of traits is essential in genetics and genomics studies to facilitate comparative genetics and meta-analyses. It is an ongoing challenge in research and production environments to unambiguously and consistently compare traits of interest from data collected under various conditions. Despite previous efforts to standardize trait nomenclature, it remains a challenge to fully and accurately capture trait nomenclature granularity in a way that ensures long-term data sustainability in terms of the data curation processes, data management logistics and the ability to make meaningful comparisons across studies. In the Animal Quantitative Trait Loci Database and the Animal Trait Correlation Database, we have recently introduced a new method to extend livestock trait ontologies by using trait modifiers and qualifiers to define traits that differ slightly in how they are measured, examined or combined with other traits or factors. Here, we describe the implementation of a system in which the extended trait data, with modifiers, are managed at the experiment level as 'trait variants'. This has helped us to streamline the management and curation of such trait information in our database environment. Database URL https://www.animalgenome.org/PGNET/.
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Affiliation(s)
- Zhi-Liang Hu
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, 806 Stange Road, Ames, IA 50011-3150, USA
| | - Carissa A Park
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, 806 Stange Road, Ames, IA 50011-3150, USA
| | - James M Reecy
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, 806 Stange Road, Ames, IA 50011-3150, USA
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3
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Andrade BGN, Bressani FA, Cuadrat RRC, Cardoso TF, Malheiros JM, de Oliveira PSN, Petrini J, Mourão GB, Coutinho LL, Reecy JM, Koltes JE, Neto AZ, R de Medeiros S, Berndt A, Palhares JCP, Afli H, Regitano LCA. Stool and Ruminal Microbiome Components Associated With Methane Emission and Feed Efficiency in Nelore Beef Cattle. Front Genet 2022; 13:812828. [PMID: 35656319 PMCID: PMC9152269 DOI: 10.3389/fgene.2022.812828] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 03/02/2022] [Indexed: 12/27/2022] Open
Abstract
Background: The impact of extreme changes in weather patterns on the economy and human welfare is one of the biggest challenges our civilization faces. From anthropogenic contributions to climate change, reducing the impact of farming activities is a priority since it is responsible for up to 18% of global greenhouse gas emissions. To this end, we tested whether ruminal and stool microbiome components could be used as biomarkers for methane emission and feed efficiency in bovine by studying 52 Brazilian Nelore bulls belonging to two feed intervention treatment groups, that is, conventional and by-product-based diets. Results: We identified a total of 5,693 amplicon sequence variants (ASVs) in the Nelore bulls’ microbiomes. A Differential abundance analysis with the ANCOM approach identified 30 bacterial and 15 archaeal ASVs as differentially abundant (DA) among treatment groups. An association analysis using Maaslin2 software and a linear mixed model indicated that bacterial ASVs are linked to the host’s residual methane emission (RCH4) and residual feed intake (RFI) phenotype variation, suggesting their potential as targets for interventions or biomarkers. Conclusion: The feed composition induced significant differences in both abundance and richness of ruminal and stool microbial populations in ruminants of the Nelore breed. The industrial by-product-based dietary treatment applied to our experimental groups influenced the microbiome diversity of bacteria and archaea but not of protozoa. ASVs were associated with RCH4 emission and RFI in ruminal and stool microbiomes. While ruminal ASVs were expected to influence CH4 emission and RFI, the relationship of stool taxa, such as Alistipes and Rikenellaceae (gut group RC9), with these traits was not reported before and might be associated with host health due to their link to anti-inflammatory compounds. Overall, the ASVs associated here have the potential to be used as biomarkers for these complex phenotypes.
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Affiliation(s)
- Bruno G N Andrade
- Embrapa Southeast Livestock, São Carlos, Brazil.,Department of Computer Science, Munster Technological University, MTU/ADAPT, Cork, Ireland
| | | | - Rafael R C Cuadrat
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke (DIfE), Nuthetal, Germany
| | | | | | | | - Juliana Petrini
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, Brazil
| | - Gerson B Mourão
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, Brazil
| | - Luiz L Coutinho
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, Brazil
| | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - James E Koltes
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | | | | | | | | | - Haithem Afli
- Department of Computer Science, Munster Technological University, MTU/ADAPT, Cork, Ireland
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Lawrence-Dill CJ, Allscheid RL, Boaitey A, Bauman T, Buckler ES, Clarke JL, Cullis C, Dekkers J, Dorius CJ, Dorius SF, Ertl D, Homann M, Hu G, Losch M, Lyons E, Murdoch B, Navabi ZK, Punnuri S, Rafiq F, Reecy JM, Schnable PS, Scott NM, Sheehan M, Sirault X, Staton M, Tuggle CK, Van Eenennaam A, Voas R. Ten simple rules to ruin a collaborative environment. PLoS Comput Biol 2022; 18:e1009957. [PMID: 35421080 PMCID: PMC9009642 DOI: 10.1371/journal.pcbi.1009957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Affiliation(s)
- Carolyn J. Lawrence-Dill
- Department of Agronomy, Iowa State University, Ames, Iowa, United States of America
- Department of Genetics, Development and Cell Biology, Iowa State University, Ames, Iowa, United States of America
- * E-mail:
| | - Robyn L. Allscheid
- Research, National Corn Growers Association, Chesterfield, Missouri, United States of America
| | - Albert Boaitey
- Department of Agricultural Economics, University of Wisconsin, River Falls, Wisconsin, United States of America
| | - Todd Bauman
- Filament, St. Louis, Missouri, United States of America
| | - Edward S. Buckler
- Plant Soil and Nutrition Research Unit, USDA Agricultural Research Service, Ithaca, New York, United States of America
| | - Jennifer L. Clarke
- Department of Statistics, University of Nebraska, Lincoln, Nebraska, United States of America
- Department of Food Science and Technology, University of Nebraska, Lincoln, Nebraska, United States of America
| | - Christopher Cullis
- Department of Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Jack Dekkers
- Department of Animal Science, Iowa State University, Ames, Iowa, United States of America
| | - Cassandra J. Dorius
- Department of Human Development and Family Studies, Iowa State University, Ames, Iowa, United States of America
| | - Shawn F. Dorius
- Department of Sociology and Criminal Justice, Iowa State University, Ames, Iowa, United States of America
| | - David Ertl
- Research and Business Development, Iowa Corn Promotion Board, Johnston, Iowa, United States of America
| | | | - Guiping Hu
- Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, Iowa, United States of America
| | - Mary Losch
- Department of Psychology, University of Northern Iowa, Cedar Falls, Iowa, United States of America
| | - Eric Lyons
- School of Plant Sciences, University of Arizona, Tucson, Arizona, United States of America
| | - Brenda Murdoch
- Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, Idaho, United States of America
| | | | - Somashekhar Punnuri
- Agricultural Research Station, Fort Valley State University, Fort Falley, Georgia, United States of America
| | - Fahad Rafiq
- Department of Animal Science, University of Florida, Gainesville, Florida, United States of America
| | - James M. Reecy
- Department of Animal Science, Iowa State University, Ames, Iowa, United States of America
| | - Patrick S. Schnable
- Department of Agronomy, Iowa State University, Ames, Iowa, United States of America
| | - Nicole M. Scott
- Department of Agronomy, Iowa State University, Ames, Iowa, United States of America
| | - Moira Sheehan
- Institute of Biotechnology, Cornell University, Ithaca, New York, United States of America
| | | | - Margaret Staton
- Institute of Agriculture, University of Tennessee, Knoxville, Tennessee, United States of America
| | - Christopher K. Tuggle
- Department of Animal Science, Iowa State University, Ames, Iowa, United States of America
| | - Alison Van Eenennaam
- Department of Animal Science, University of California-Davis, Davis, California, United States of America
| | - Rachael Voas
- Department of Human Development and Family Studies, Iowa State University, Ames, Iowa, United States of America
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5
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Sharifi S, Lotfi Shahreza M, Pakdel A, Reecy JM, Ghadiri N, Atashi H, Motamedi M, Ebrahimie E. Systems Biology–Derived Genetic Signatures of Mastitis in Dairy Cattle: A New Avenue for Drug Repurposing. Animals (Basel) 2021; 12:ani12010029. [PMID: 35011134 PMCID: PMC8749881 DOI: 10.3390/ani12010029] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 11/21/2021] [Accepted: 12/17/2021] [Indexed: 02/07/2023] Open
Abstract
Simple Summary Therapeutic success of bovine mastitis depends mainly on accurately diagnosing the type of pathogen involved. Despite the development prospects for bovine mastitis diagnosis, including new biomarker discovery to target specific pathogens with high sensitivity and specificity, treatment studies have shown controversial results, and the most efficient, safe, and economical treatments for mastitis are still topics of scientific debate. The goal of this research is the integration of different levels of systems biology data to predict candidate drugs for the control and management of E. coli mastitis. We propose that the novel drugs could be used by pharmaceutical scientists or veterinarians to find commercially efficacious medicines. Abstract Mastitis, a disease with high incidence worldwide, is the most prevalent and costly disease in the dairy industry. Gram-negative bacteria such as Escherichia coli (E. coli) are assumed to be among the leading agents causing acute severe infection with clinical signs. E. Coli, environmental mastitis pathogens, are the primary etiological agents of bovine mastitis in well-managed dairy farms. Response to E. Coli infection has a complex pattern affected by genetic and environmental parameters. On the other hand, the efficacy of antibiotics and/or anti-inflammatory treatment in E. coli mastitis is still a topic of scientific debate, and studies on the treatment of clinical cases show conflicting results. Unraveling the bio-signature of mastitis in dairy cattle can open new avenues for drug repurposing. In the current research, a novel, semi-supervised heterogeneous label propagation algorithm named Heter-LP, which applies both local and global network features for data integration, was used to potentially identify novel therapeutic avenues for the treatment of E. coli mastitis. Online data repositories relevant to known diseases, drugs, and gene targets, along with other specialized biological information for E. coli mastitis, including critical genes with robust bio-signatures, drugs, and related disorders, were used as input data for analysis with the Heter-LP algorithm. Our research identified novel drugs such as Glibenclamide, Ipratropium, Salbutamol, and Carbidopa as possible therapeutics that could be used against E. coli mastitis. Predicted relationships can be used by pharmaceutical scientists or veterinarians to find commercially efficacious medicines or a combination of two or more active compounds to treat this infectious disease.
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Affiliation(s)
- Somayeh Sharifi
- Department of Animal Sciences, College of Agriculture, Isfahan University of Technology, Isfahan 84156-83111, Iran;
- Department of Animal Science, Iowa State University, Ames, IA 50011, USA;
- Correspondence: (S.S.); (E.E.)
| | - Maryam Lotfi Shahreza
- Department of Computer Engineering, Shahreza Campus, University of Isfahan, Isfahan 86149-56841, Iran;
| | - Abbas Pakdel
- Department of Animal Sciences, College of Agriculture, Isfahan University of Technology, Isfahan 84156-83111, Iran;
| | - James M. Reecy
- Department of Animal Science, Iowa State University, Ames, IA 50011, USA;
| | - Nasser Ghadiri
- Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran;
| | - Hadi Atashi
- Department of Animal Science, Shiraz University, Shiraz 71946-84334, Iran;
| | - Mahmood Motamedi
- Department of Animal Sciences, University of Tehran, Tehran 1417935840, Iran;
| | - Esmaeil Ebrahimie
- Genomics Research Platform, School of Life Sciences, College of Science, Health and Engineering, La Trobe University, Melbourne, VIC 3086, Australia
- School of Animal and Veterinary Sciences, The University of Adelaide, Adelaide, SA 5371, Australia
- School of BioSciences, The University of Melbourne, Melbourne, VIC 3010, Australia
- Correspondence: (S.S.); (E.E.)
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6
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Hu ZL, Park CA, Reecy JM. Bringing the Animal QTLdb and CorrDB into the future: meeting new challenges and providing updated services. Nucleic Acids Res 2021; 50:D956-D961. [PMID: 34850103 PMCID: PMC8728226 DOI: 10.1093/nar/gkab1116] [Citation(s) in RCA: 90] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 10/21/2021] [Accepted: 10/22/2021] [Indexed: 11/25/2022] Open
Abstract
The Animal QTLdb (https://www.animalgenome.org/QTLdb) and CorrDB (https://www.animalgenome.org/CorrDB) are unique resources for livestock animal genetics and genomics research which have been used extensively by the international livestock genome research community. This is largely due to the active development of the databases over the years to keep up with the rapid advancement of genome sciences. The ongoing development has ensured that these databases provide researchers not only with continually updated data but also with new web tools to disseminate the data. Through our continued efforts, the databases have evolved from the original Pig QTLdb for cross-experiment QTL data comparisons to an Animal QTLdb hosting 220 401 QTL, SNP association and eQTL data linking phenotype to genotype for 2210 traits. In addition, there are 23 552 correlations for 866 traits and 4273 heritability data on 1069 traits in CorrDB. All these data were curated from 3157 publications that cover seven livestock species. Along with the continued data curation, new species, additional genome builds, and new functions and features have been built into the databases as well. Standardized procedures to support data mapping on multiple species/genome builds and the ability to browse data based on linked ontology terms are highlights of the recent developments.
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Affiliation(s)
- Zhi-Liang Hu
- To whom correspondence should be addressed. Tel: +1 901 212 2820; Fax: +1 515 294 2401;
| | - Carissa A Park
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, USA
| | - James M Reecy
- Correspondence may also be addressed to James M. Reecy. Tel: +1 515 294 9269; Fax: +1 515 294 2401;
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7
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Dong Q, Lunney JK, Lim KS, Nguyen Y, Hess AS, Beiki H, Rowland RRR, Walker K, Reecy JM, Tuggle CK, Dekkers JCM. Gene expression in tonsils in swine following infection with porcine reproductive and respiratory syndrome virus. BMC Vet Res 2021; 17:88. [PMID: 33618723 PMCID: PMC7901068 DOI: 10.1186/s12917-021-02785-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Accepted: 02/02/2021] [Indexed: 12/18/2022] Open
Abstract
Background Porcine reproductive and respiratory syndrome (PRRS) is a threat to pig production worldwide. Our objective was to understand mechanisms of persistence of PRRS virus (PRRSV) in tonsil. Transcriptome data from tonsil samples collected at 42 days post infection (dpi) were generated by RNA-seq and NanoString on 51 pigs that were selected to contrast the two PRRSV isolates used, NVSL and KS06, high and low tonsil viral level at 42 dpi, and the favorable and unfavorable genotypes at a genetic marker (WUR) for the putative PRRSV resistance gene GBP5. Results The number of differentially expressed genes (DEGs) differed markedly between models with and without accounting for cell-type enrichments (CE) in the samples that were predicted from the RNA-seq data. This indicates that differences in cell composition in tissues that consist of multiple cell types, such as tonsil, can have a large impact on observed differences in gene expression. Based on both the NanoString and the RNA-seq data, KS06-infected pigs showed greater activation, or less inhibition, of immune response in tonsils at 42 dpi than NVSL-infected pigs, with and without accounting for CE. This suggests that the NVSL virus may be better than the KS06 virus at evading host immune response and persists in tonsils by weakening, or preventing, host immune responses. Pigs with high viral levels showed larger CE of immune cells than low viral level pigs, potentially to trigger stronger immune responses. Presence of high tonsil virus was associated with a stronger immune response, especially innate immune response through interferon signaling, but these differences were not significant when accounting for CE. Genotype at WUR was associated with different effects on immune response in tonsils of pigs during the persistence stage, depending on viral isolate and tonsil viral level. Conclusions Results of this study provide insights into the effects of PRRSV isolate, tonsil viral level, and WUR genotype on host immune response and into potential mechanisms of PRRSV persistence in tonsils that could be targeted to improve strategies to reduce viral rebreaks. Finally, to understand transcriptome responses in tissues that consist of multiple cell types, it is important to consider differences in cell composition. Supplementary Information The online version contains supplementary material available at 10.1186/s12917-021-02785-1.
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Affiliation(s)
- Qian Dong
- Department of Animal Science, Iowa State University, Ames, Iowa, 50011, USA
| | | | - Kyu-Sang Lim
- Department of Animal Science, Iowa State University, Ames, Iowa, 50011, USA
| | - Yet Nguyen
- Department of Statistics, Iowa State University, Ames, Iowa, 50011, USA
| | - Andrew S Hess
- Department of Animal Science, Iowa State University, Ames, Iowa, 50011, USA
| | - Hamid Beiki
- Department of Animal Science, Iowa State University, Ames, Iowa, 50011, USA
| | - Raymond R R Rowland
- College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, 61802, USA
| | | | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, Iowa, 50011, USA
| | | | - Jack C M Dekkers
- Department of Animal Science, Iowa State University, Ames, Iowa, 50011, USA.
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Clark EL, Archibald AL, Daetwyler HD, Groenen MAM, Harrison PW, Houston RD, Kühn C, Lien S, Macqueen DJ, Reecy JM, Robledo D, Watson M, Tuggle CK, Giuffra E. From FAANG to fork: application of highly annotated genomes to improve farmed animal production. Genome Biol 2020; 21:285. [PMID: 33234160 PMCID: PMC7686664 DOI: 10.1186/s13059-020-02197-8] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 11/05/2020] [Indexed: 12/27/2022] Open
Affiliation(s)
- Emily L Clark
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, EH25 9RG, UK.
| | - Alan L Archibald
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, EH25 9RG, UK
| | - Hans D Daetwyler
- Agriculture Victoria, AgriBio Centre for AgriBioscience, Bundoora, Victoria, 3083, Australia.,School of Applied Systems Biology, La Trobe University, Bundoora, Victoria, 3083, Australia
| | - Martien A M Groenen
- Animal Breeding and Genomics Centre, Wageningen University and Research, 6708 PB, Wageningen, The Netherlands
| | - Peter W Harrison
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Ross D Houston
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, EH25 9RG, UK
| | - Christa Kühn
- Leibniz Institute for Farm Animal Biology (FBN), Institute of Genome Biology, Genome Physiology Unit, Wilhelm-Stahl-Allee 2, 18196, Dummerstorf, Germany.,Faculty of Agricultural and Environmental Sciences, University Rostock, Justus-von-Liebig-Weg 6, 18059, Rostock, Germany
| | - Sigbjørn Lien
- Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, NO-1432, Ås, Norway
| | - Daniel J Macqueen
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, EH25 9RG, UK
| | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Diego Robledo
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, EH25 9RG, UK
| | - Mick Watson
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, EH25 9RG, UK
| | | | - Elisabetta Giuffra
- Université Paris Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France
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9
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Leal-Gutiérrez JD, Rezende FM, Reecy JM, Kramer LM, Peñagaricano F, Mateescu RG. Whole Genome Sequence Data Provides Novel Insights Into the Genetic Architecture of Meat Quality Traits in Beef. Front Genet 2020; 11:538640. [PMID: 33101375 PMCID: PMC7500205 DOI: 10.3389/fgene.2020.538640] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 08/12/2020] [Indexed: 12/12/2022] Open
Abstract
Tenderness is a major quality attribute for fresh beef steaks in the United States, and meat quality traits in general are suitable candidates for genomic research. The objectives of the present analysis were to (1) perform genome-wide association (GWA) analysis for marbling, Warner-Bratzler shear force (WBSF), tenderness, and connective tissue using whole-genome data in an Angus population, (2) identify enriched pathways in each GWA analysis; (3) construct a protein-protein interaction network using the associated genes and (4) perform a μ-calpain proteolysis assessment for associated structural proteins. An Angus-sired population of 2,285 individuals was assessed. Animals were transported to a commercial packing plant and harvested at an average age of 457 ± 46 days. After 48 h postmortem, marbling was recorded by graders' visual appraisal. Two 2.54-cm steaks were sampled from each muscle for recording of WBSF, and tenderness, and connective tissue by a sensory panel. The relevance of additive effects on marbling, WBSF, tenderness, and connective tissue was evaluated on a genome-wide scale using a two-step mixed model-based approach in single-trait analysis. A tissue-restricted gene enrichment was performed for each GWA where all polymorphisms with an association p-value lower than 1 × 10-3 were included. The genes identified as associated were included in a protein-protein interaction network and a candidate structural protein assessment of proteolysis analyses. A total of 1,867, 3,181, 3,926, and 3,678 polymorphisms were significantly associated with marbling, WBSF, tenderness, and connective tissue, respectively. The associate region on BTA29 (36,432,655-44,313,046 bp) harbors 13 highly significant markers for meat quality traits. Enrichment for the GO term GO:0005634 (Nucleus), which includes transcription factors, was evident. The final protein-protein network included 431 interations between 349 genes. The 42 most important genes based on significance that encode structural proteins were included in a proteolysis analysis, and 81% of these proteins were potential μ-Calpain substrates. Overall, this comprehensive study unraveled genetic variants, genes and mechanisms of action responsible for the variation in meat quality traits. Our findings can provide opportunities for improving meat quality in beef cattle via marker-assisted selection.
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Affiliation(s)
| | - Fernanda M. Rezende
- Department of Animal Sciences, University of Florida, Gainesville, FL, United States
- Faculdade de Medicina Veterinária, Universidade Federal de Uberlândia, Uberlândia, Brazil
| | - James M. Reecy
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Luke M. Kramer
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Francisco Peñagaricano
- Department of Animal Sciences, University of Florida, Gainesville, FL, United States
- University of Florida Genetics Institute, University of Florida, Gainesville, FL, United States
| | - Raluca G. Mateescu
- Department of Animal Sciences, University of Florida, Gainesville, FL, United States
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10
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Hu ZL, Park CA, Reecy JM. Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB. Nucleic Acids Res 2020; 47:D701-D710. [PMID: 30407520 PMCID: PMC6323967 DOI: 10.1093/nar/gky1084] [Citation(s) in RCA: 211] [Impact Index Per Article: 52.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 10/18/2018] [Indexed: 12/27/2022] Open
Abstract
Successful development of biological databases requires accommodation of the burgeoning amounts of data from high-throughput genomics pipelines. As the volume of curated data in Animal QTLdb (https://www.animalgenome.org/QTLdb) increases exponentially, the resulting challenges must be met with rapid infrastructure development to effectively accommodate abundant data curation and make metadata analysis more powerful. The development of Animal QTLdb and CorrDB for the past 15 years has provided valuable tools for researchers to utilize a wealth of phenotype/genotype data to study the genetic architecture of livestock traits. We have focused our efforts on data curation, improved data quality maintenance, new tool developments, and database co-developments, in order to provide convenient platforms for users to query and analyze data. The database currently has 158 499 QTL/associations, 10 482 correlations and 1977 heritability data as a result of an average 32% data increase per year. In addition, we have made >14 functional improvements or new tool implementations since our last report. Our ultimate goals of database development are to provide infrastructure for data collection, curation, and annotation, and more importantly, to support innovated data structure for new types of data mining, data reanalysis, and networked genetic analysis that lead to the generation of new knowledge.
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Affiliation(s)
- Zhi-Liang Hu
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, USA
| | - Carissa A Park
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, USA
| | - James M Reecy
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, USA
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11
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Zhang H, Shen LY, Xu ZC, Kramer LM, Yu JQ, Zhang XY, Na W, Yang LL, Cao ZP, Luan P, Reecy JM, Li H. Haplotype-based genome-wide association studies for carcass and growth traits in chicken. Poult Sci 2020; 99:2349-2361. [PMID: 32359570 PMCID: PMC7597553 DOI: 10.1016/j.psj.2020.01.009] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 01/20/2020] [Accepted: 01/20/2020] [Indexed: 12/15/2022] Open
Abstract
There have been several genome-wide association study (GWAS) reported for carcass, growth, and meat traits in chickens. Most of these studies have been based on single SNPs GWAS. In contrast, haplotype-based GWAS reports have been limited. In the present study, 2 Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF) and genotyped with the chicken 60K SNP chip were used to perform a haplotype-based GWAS. The lean and fat chicken lines were selected for abdominal fat content for 11 yr. Abdominal fat weight was significantly different between the 2 lines; however, there was no difference for body weight between the lean and fat lines. A total of 132 haplotype windows were significantly associated with abdominal fat weight. These significantly associated haplotype windows were primarily located on chromosomes 2, 4, 8, 10, and 26. Seven candidate genes, including SHH, LMBR1, FGF7, IL16, PLIN1, IGF1R, and SLC16A1, were located within these associated regions. These genes may play important roles in the control of abdominal fat content. Two regions on chromosomes 3 and 10 were significantly associated with testis weight. These 2 regions were previously detected by the single SNP GWAS using this same resource population. TCF21 on chromosome 3 was identified as a potentially important candidate gene for testis growth and development based on gene expression analysis and the reported function of this gene. TCF12, which was previously detected in our SNP by SNP interaction analysis, was located in a region on chromosome 10 that was significantly associated with testis weight. Six candidate genes, including TNFRSF1B, PLOD1, NPPC, MTHFR, EPHB2, and SLC35A3, on chromosome 21 may play important roles in bone development based on the known function of these genes. In addition, several regions were significantly associated with other carcass and growth traits, but no candidate genes were identified. The results of the present study may be helpful in understanding the genetic mechanisms of carcass and growth traits in chickens.
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Affiliation(s)
- Hui Zhang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - Lin-Yong Shen
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - Zi-Chun Xu
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - Luke M Kramer
- Department of Animal Science, Iowa State University, Ames, IA 50011, USA
| | - Jia-Qiang Yu
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - Xin-Yang Zhang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - Wei Na
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - Li-Li Yang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - Zhi-Ping Cao
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - Peng Luan
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China
| | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA 50011, USA.
| | - Hui Li
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs, Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province, College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, PR China.
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12
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Andrade BGN, Bressani FA, Cuadrat RRC, Tizioto PC, de Oliveira PSN, Mourão GB, Coutinho LL, Reecy JM, Koltes JE, Walsh P, Berndt A, Palhares JCP, Regitano LCA. The structure of microbial populations in Nelore GIT reveals inter-dependency of methanogens in feces and rumen. J Anim Sci Biotechnol 2020; 11:6. [PMID: 32123563 PMCID: PMC7038601 DOI: 10.1186/s40104-019-0422-x] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Accepted: 12/23/2019] [Indexed: 12/18/2022] Open
Abstract
Background The success of different species of ruminants in the colonization of a diverse range of environments is due to their ability to digest and absorb nutrients from cellulose, a complex polysaccharide found in leaves and grass. Ruminants rely on a complex and diverse microbial community, or microbiota, in a unique compartment known as the rumen to break down this polysaccharide. Changes in microbial populations of the rumen can affect the host’s development, health, and productivity. However, accessing the rumen is stressful for the animal. Therefore, the development and use of alternative sampling methods are needed if this technique is to be routinely used in cattle breeding. To this end, we tested if the fecal microbiome could be used as a proxy for the rumen microbiome due to its accessibility. We investigated the taxonomic composition, diversity and inter-relations of two different GIT compartments, rumen and feces, of 26 Nelore (Bos indicus) bulls, using Next Generation Sequencing (NGS) metabarcoding of bacteria, archaea and ciliate protozoa. Results We identified 4265 Amplicon Sequence Variants (ASVs) from bacteria, 571 from archaea, and 107 from protozoa, of which 143 (96 bacteria and 47 archaea) were found common between both microbiomes. The most prominent bacterial phyla identified were Bacteroidetes (41.48%) and Firmicutes (56.86%) in the ruminal and fecal microbiomes, respectively, with Prevotella and Ruminococcaceae UCG-005 the most relatively abundant genera identified in each microbiome. The most abundant archaeal phylum identified was Euryarchaeota, of which Methanobrevibacter gottschalkii, a methanogen, was the prevalent archaeal species identified in both microbiomes. Protozoa were found exclusively identified in the rumen with Bozasella/Triplumaria being the most frequent genus identified. Co-occurrence among ruminal and fecal ASVs reinforces the relationship of microorganisms within a biological niche. Furthermore, the co-occurrence of shared archaeal ASVs between microbiomes indicates a dependency of the predominant fecal methanogen population on the rumen population. Conclusions Co-occurring microorganisms were identified within the rumen and fecal microbiomes, which revealed a strong association and inter-dependency between bacterial, archaeal and protozoan populations of the same microbiome. The archaeal ASVs identified as co-occurring between GIT compartments corresponded to the methanogenic genera Methanobrevibacter and Methanosphaera and represented 26.34% of the overall archaeal sequencesdiversity in the rumen and 42.73% in feces. Considering that these archaeal ASVs corresponded to a significant part of the overall diversity of both microbiomes, which is much higher if one includes the interactions of these co-occurring with other rumen archaea ASVs, we suggest that fecal methanogens could be used as a proxy of ruminal methanogens.
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Affiliation(s)
| | | | - Rafael R C Cuadrat
- 2Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke (DIfE), Nuthetal, Germany
| | | | | | - Gerson B Mourão
- 4Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, Brazil
| | - Luiz L Coutinho
- 4Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, Brazil
| | - James M Reecy
- 5Department of Animal Science, Iowa State University, Ames, IA USA
| | - James E Koltes
- 5Department of Animal Science, Iowa State University, Ames, IA USA
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13
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Koltes JE, Cole JB, Clemmens R, Dilger RN, Kramer LM, Lunney JK, McCue ME, McKay SD, Mateescu RG, Murdoch BM, Reuter R, Rexroad CE, Rosa GJM, Serão NVL, White SN, Woodward-Greene MJ, Worku M, Zhang H, Reecy JM. A Vision for Development and Utilization of High-Throughput Phenotyping and Big Data Analytics in Livestock. Front Genet 2019; 10:1197. [PMID: 31921279 PMCID: PMC6934059 DOI: 10.3389/fgene.2019.01197] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Accepted: 10/29/2019] [Indexed: 01/28/2023] Open
Abstract
Automated high-throughput phenotyping with sensors, imaging, and other on-farm technologies has resulted in a flood of data that are largely under-utilized. Drastic cost reductions in sequencing and other omics technology have also facilitated the ability for deep phenotyping of livestock at the molecular level. These advances have brought the animal sciences to a cross-roads in data science where increased training is needed to manage, record, and analyze data to generate knowledge and advances in Agriscience related disciplines. This paper describes the opportunities and challenges in using high-throughput phenotyping, “big data,” analytics, and related technologies in the livestock industry based on discussions at the Livestock High-Throughput Phenotyping and Big Data Analytics meeting, held in November 2017 (see: https://www.animalgenome.org/bioinfo/community/workshops/2017/). Critical needs for investments in infrastructure for people (e.g., “big data” training), data (e.g., data transfer, management, and analytics), and technology (e.g., development of low cost sensors) were defined by this group. Though some subgroups of animal science have extensive experience in predictive modeling, cross-training in computer science, statistics, and related disciplines are needed to use big data for diverse applications in the field. Extensive opportunities exist for public and private entities to harness big data to develop valuable research knowledge and products to the benefit of society under the increased demands for food in a rapidly growing population.
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Affiliation(s)
- James E Koltes
- Department of Animal Science, College of Agriculture and Life Sciences, Iowa State University, Ames, IA, United States
| | - John B Cole
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, United States
| | - Roxanne Clemmens
- College of Agriculture and Life Sciences, Iowa State University, Ames, IA, United States
| | - Ryan N Dilger
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Luke M Kramer
- Department of Animal Science, College of Agriculture and Life Sciences, Iowa State University, Ames, IA, United States
| | - Joan K Lunney
- Animal Parasitic Diseases Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, MD, United States
| | - Molly E McCue
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, United States
| | - Stephanie D McKay
- Department of Animal and Veterinary Sciences, College of Agriculture and Life Sciences, University of Vermont, Burlington, VT, United States
| | - Raluca G Mateescu
- Department of Animal Sciences, University of Florida, Gainesville, FL, United States
| | - Brenda M Murdoch
- Department of Animal and Veterinary Science, University of Idaho, Moscow, ID, United States
| | - Ryan Reuter
- Department of Animal and Food Sciences, College of Agricultural Sciences and Natural Resources, Oklahoma State University, Stillwater, OK, United States
| | - Caird E Rexroad
- Agricultural Research Service, United States Department of Agriculture, Washington D.C., DC, United States
| | - Guilherme J M Rosa
- Department of Dairy Science, University of Wisconsin-Madison, Madison, WI, United States
| | - Nick V L Serão
- Department of Animal Science, College of Agriculture and Life Sciences, Iowa State University, Ames, IA, United States
| | - Stephen N White
- Animal Disease Research Unit, Agricultural Research Service, United States Department of Agriculture, Pullman, WA, United States.,Department of Veterinary Microbiology and Pathology, College of Veterinary Medicine, Washington State University, Pullman, WA, United States.,Center for Reproductive Biology, College of Veterinary Medicine, Washington State University, Pullman, WA, United States
| | - M Jennifer Woodward-Greene
- Agricultural Research Service, United States Department of Agriculture, Washington D.C., DC, United States
| | - Millie Worku
- Department of Animal Sciences, North Carolina Agricultural and Technical State University, Greensboro, NC, United States
| | - Hongwei Zhang
- Department of Electrical and Computer Engineering, College of Engineering, Iowa State University, Ames, IA, United States
| | - James M Reecy
- Department of Animal Science, College of Agriculture and Life Sciences, Iowa State University, Ames, IA, United States
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14
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Moreira GCM, Poleti MD, Pértille F, Boschiero C, Cesar ASM, Godoy TF, Ledur MC, Reecy JM, Garrick DJ, Coutinho LL. Unraveling genomic associations with feed efficiency and body weight traits in chickens through an integrative approach. BMC Genet 2019; 20:83. [PMID: 31694549 PMCID: PMC6836328 DOI: 10.1186/s12863-019-0783-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Accepted: 10/11/2019] [Indexed: 12/25/2022] Open
Abstract
Background Feed efficiency and growth rate have been targets for selection to improve chicken production. The incorporation of genomic tools may help to accelerate selection. We genotyped 529 individuals using a high-density SNP chip (600 K, Affymetrix®) to estimate genomic heritability of performance traits and to identify genomic regions and their positional candidate genes associated with performance traits in a Brazilian F2 Chicken Resource population. Regions exhibiting selection signatures and a SNP dataset from resequencing were integrated with the genomic regions identified using the chip to refine the list of positional candidate genes and identify potential causative mutations. Results Feed intake (FI), feed conversion ratio (FC), feed efficiency (FE) and weight gain (WG) exhibited low genomic heritability values (i.e. from 0.0002 to 0.13), while body weight at hatch (BW1), 35 days-of-age (BW35), and 41 days-of-age (BW41) exhibited high genomic heritability values (i.e. from 0.60 to 0.73) in this F2 population. Twenty unique 1-Mb genomic windows were associated with BW1, BW35 or BW41, located on GGA1–4, 6–7, 10, 14, 24, 27 and 28. Thirty-eight positional candidate genes were identified within these windows, and three of them overlapped with selection signature regions. Thirteen predicted deleterious and three high impact sequence SNPs in these QTL regions were annotated in 11 positional candidate genes related to osteogenesis, skeletal muscle development, growth, energy metabolism and lipid metabolism, which may be associated with body weight in chickens. Conclusions The use of a high-density SNP array to identify QTL which were integrated with whole genome sequence signatures of selection allowed the identification of candidate genes and candidate causal variants. One novel QTL was detected providing additional information to understand the genetic architecture of body weight traits. We identified QTL for body weight traits, which were also associated with fatness in the same population. Our findings form a basis for further functional studies to elucidate the role of specific genes in regulating body weight and fat deposition in chickens, generating useful information for poultry breeding programs.
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Affiliation(s)
| | - Mirele Daiana Poleti
- University of São Paulo (USP) / College of Animal Science and Food Engineering (FZEA), Pirassununga, São Paulo, Brazil
| | - Fábio Pértille
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | - Clarissa Boschiero
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | | | - Thaís Fernanda Godoy
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | | | - James M Reecy
- Department of Animal Science, Iowa State University (ISU), Ames, Iowa, USA
| | - Dorian J Garrick
- School of Agriculture, Massey University, Ruakura, Hamilton, New Zealand
| | - Luiz Lehmann Coutinho
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil.
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15
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Moreira GCM, Salvian M, Boschiero C, Cesar ASM, Reecy JM, Godoy TF, Ledur MC, Garrick D, Mourão GB, Coutinho LL. Genome-wide association scan for QTL and their positional candidate genes associated with internal organ traits in chickens. BMC Genomics 2019; 20:669. [PMID: 31438838 PMCID: PMC6704653 DOI: 10.1186/s12864-019-6040-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 08/16/2019] [Indexed: 02/07/2023] Open
Abstract
Background Poultry breeding programs have been focused on improvement of growth and carcass traits, however, this has resulted in correlated changes in internal organ weights and increased incidence of metabolic disorders. These disorders can affect feed efficiency or even cause death. We used a high density SNP array (600 K, Affymetrix) to estimate genomic heritability, perform genome-wide association analysis, and identify genomic regions and positional candidate genes (PCGs) associated with internal organ traits in an F2 chicken population. We integrated knowledge of haplotype blocks, selection signature regions and sequencing data to refine the list of PCGs. Results Estimated genomic heritability for internal organ traits in chickens ranged from low (LUNGWT, 0.06) to high (GIZZWT, 0.45). A total of 20 unique 1 Mb windows identified on GGA1, 2, 4, 7, 12, 15, 18, 19, 21, 27 and 28 were significantly associated with intestine length, and weights or percentages of liver, gizzard or lungs. Within these windows, 14 PCGs were identified based on their biological functions: TNFSF11, GTF2F2, SPERT, KCTD4, HTR2A, RB1, PCDH7, LCORL, LDB2, NR4A2, GPD2, PTPN11, ITGB4 and SLC6A4. From those genes, two were located within haplotype blocks and three overlapped with selection signature regions. A total of 13,748 annotated sequence SNPs were in the 14 PCGs, including 156 SNPs in coding regions (124 synonymous, 26 non-synonymous, and 6 splice variants). Seven deleterious SNPs were identified in TNFSF11, NR4A2 or ITGB4 genes. Conclusions The results from this study provide novel insights to understand the genetic architecture of internal organ traits in chickens. The QTL detection performed using a high density SNP array covered the whole genome allowing the discovery of novel QTL associated with organ traits. We identified PCGs within the QTL involved in biological processes that may regulate internal organ growth and development. Potential functional genetic variations were identified generating crucial information that, after validation, might be used in poultry breeding programs to reduce the occurrence of metabolic disorders. Electronic supplementary material The online version of this article (10.1186/s12864-019-6040-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - Mayara Salvian
- University of São Paulo (USP), Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Clarissa Boschiero
- University of São Paulo (USP), Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Aline Silva Mello Cesar
- University of São Paulo (USP), Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - James M Reecy
- Department of Animal Science, Iowa State University (ISU), Ames, Iowa, USA
| | - Thaís Fernanda Godoy
- University of São Paulo (USP), Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | | | - Dorian Garrick
- School of Agriculture, Massey University, Ruakura, Hamilton, New Zealand
| | - Gerson Barreto Mourão
- University of São Paulo (USP), Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Luiz L Coutinho
- University of São Paulo (USP), Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil.
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16
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de Oliveira PSN, Coutinho LL, Cesar ASM, Diniz WJDS, de Souza MM, Andrade BG, Koltes JE, Mourão GB, Zerlotini A, Reecy JM, Regitano LCA. Co-Expression Networks Reveal Potential Regulatory Roles of miRNAs in Fatty Acid Composition of Nelore Cattle. Front Genet 2019; 10:651. [PMID: 31354792 PMCID: PMC6637853 DOI: 10.3389/fgene.2019.00651] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Accepted: 06/19/2019] [Indexed: 12/15/2022] Open
Abstract
Fatty acid (FA) content affects the sensorial and nutritional value of meat and plays a significant role in biological processes such as adipogenesis and immune response. It is well known that, in beef, the main FAs associated with these biological processes are oleic acid (C18:1 cis9, OA) and conjugated linoleic acid (CLA-c9t11), which may have beneficial effects on metabolic diseases such as type 2 diabetes and obesity. Here, we performed differential expression and co-expression analyses, weighted gene co-expression network analysis (WGCNA) and partial correlation with information theory (PCIT), to uncover the complex interactions between miRNAs and mRNAs expressed in skeletal muscle associated with FA content. miRNA and mRNA expression data were obtained from skeletal muscle of Nelore cattle that had extreme genomic breeding values for OA and CLA. Insulin and MAPK signaling pathways were identified by WGCNA as central pathways associated with both of these fatty acids. Co-expression network analysis identified bta-miR-33a/b, bta-miR-100, bta-miR-204, bta-miR-365-5p, bta-miR-660, bta-miR-411a, bta-miR-136, bta-miR-30-5p, bta-miR-146b, bta-let-7a-5p, bta-let-7f, bta-let-7, bta-miR 339, bta-miR-10b, bta-miR 486, and the genes ACTA1 and ALDOA as potential regulators of fatty acid synthesis. This study provides evidence and insights into the molecular mechanisms and potential target genes involved in fatty acid content differences in Nelore beef cattle, revealing new candidate pathways of phenotype modulation that could positively benefit beef production and human consumption.
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Affiliation(s)
| | - Luiz L Coutinho
- Department of Animal Science, University of São Paulo, Piracicaba, Brazil
| | - Aline S M Cesar
- Department of Agroindustry, Food and Nutrition, University of São Paulo, Piracicaba, Brazil
| | | | - Marcela M de Souza
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Bruno G Andrade
- Embrapa Pecuária Sudeste, Empresa Brasileira de Pesquisa Agropecuária, São Carlos, Brazil
| | - James E Koltes
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Gerson B Mourão
- Department of Agroindustry, Food and Nutrition, University of São Paulo, Piracicaba, Brazil
| | | | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - Luciana C A Regitano
- Embrapa Pecuária Sudeste, Empresa Brasileira de Pesquisa Agropecuária, São Carlos, Brazil
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17
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Sharifi S, Pakdel A, Ebrahimie E, Aryan Y, Ghaderi Zefrehee M, Reecy JM. Prediction of key regulators and downstream targets of E. coli induced mastitis. J Appl Genet 2019; 60:367-373. [DOI: 10.1007/s13353-019-00499-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Revised: 04/02/2019] [Accepted: 05/21/2019] [Indexed: 01/04/2023]
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18
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Beiki H, Liu H, Huang J, Manchanda N, Nonneman D, Smith TPL, Reecy JM, Tuggle CK. Improved annotation of the domestic pig genome through integration of Iso-Seq and RNA-seq data. BMC Genomics 2019; 20:344. [PMID: 31064321 PMCID: PMC6505119 DOI: 10.1186/s12864-019-5709-y] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 04/17/2019] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Our understanding of the pig transcriptome is limited. RNA transcript diversity among nine tissues was assessed using poly(A) selected single-molecule long-read isoform sequencing (Iso-seq) and Illumina RNA sequencing (RNA-seq) from a single White cross-bred pig. RESULTS Across tissues, a total of 67,746 unique transcripts were observed, including 60.5% predicted protein-coding, 36.2% long non-coding RNA and 3.3% nonsense-mediated decay transcripts. On average, 90% of the splice junctions were supported by RNA-seq within tissue. A large proportion (80%) represented novel transcripts, mostly produced by known protein-coding genes (70%), while 17% corresponded to novel genes. On average, four transcripts per known gene (tpg) were identified; an increase over current EBI (1.9 tpg) and NCBI (2.9 tpg) annotations and closer to the number reported in human genome (4.2 tpg). Our new pig genome annotation extended more than 6000 known gene borders (5' end extension, 3' end extension, or both) compared to EBI or NCBI annotations. We validated a large proportion of these extensions by independent pig poly(A) selected 3'-RNA-seq data, or human FANTOM5 Cap Analysis of Gene Expression data. Further, we detected 10,465 novel genes (81% non-coding) not reported in current pig genome annotations. More than 80% of these novel genes had transcripts detected in > 1 tissue. In addition, more than 80% of novel intergenic genes with at least one transcript detected in liver tissue had H3K4me3 or H3K36me3 peaks mapping to their promoter and gene body, respectively, in independent liver chromatin immunoprecipitation data. CONCLUSIONS These validated results show significant improvement over current pig genome annotations.
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Affiliation(s)
- H Beiki
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA
| | - H Liu
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA
| | - J Huang
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.,College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang, Jiangxi, People's Republic of China
| | - N Manchanda
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, 819 Wallace Road, Ames, IA, 50011, USA
| | - D Nonneman
- USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA
| | - T P L Smith
- USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, 68933, USA
| | - J M Reecy
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA
| | - C K Tuggle
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
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19
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Kramer LM, Mayes MS, Downey ED, Tait RG, Woolums A, Chase C, Reecy JM. Genome-wide association study for response to vaccination in Angus calves 1. BMC Genet 2019; 20:6. [PMID: 30621575 PMCID: PMC6325805 DOI: 10.1186/s12863-018-0709-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 12/21/2018] [Indexed: 11/24/2022] Open
Abstract
Background Bovine respiratory disease complex (BRDC) is one of the most important sources of loss within the beef cattle industry in the USA. Steps have been taken to reduce the incidence of BRDC through vaccination. Despite the effectiveness of vaccines, large proportions of cattle still experience morbidity and mortality. Identification of genomic regions that are associated with variation in response to vaccination would allow for the selection of individuals genetically predisposed to respond to vaccination based on specific markers, while heritability and accuracy estimates would help facilitate genomic selection. This in turn may lead to selection for beef cattle herds that may have lower incidence rate of BRDC after vaccination. This study utilizes an Angus herd of more than 2000 head of cattle to identify these regions of association. Results Genome wide association studies were performed for viral neutralization antibody level and response to vaccination traits against four different viruses associated with BRDC: bovine viral diarrhea virus 1 and 2 (BVDV1 and BVDV2), bovine respiratory syncytial virus (BRSV), and bovine herpesvirus (BHV1). A total of six 1-Mb windows were associated with greater than 1% of the genetic variance for the analyzed vaccination response traits. Heritabilities ranged from 0.08 to 0.21 and prediction accuracy ranged from 0.01 to 0.33 across 7 different vaccination traits. Conclusions Although six 1-Mb windows were identified as associated with 1% or greater genetic variance for viral neutralization antibody level and response to vaccination traits, few genes around these windows could readily be considered candidates. This indicates the need for further functional genomic annotation, as these regions appear to be gene deserts. Traits ranged from lowly to moderately heritable, which indicated the potential for selection of individuals that are genetically pre-disposed to respond to vaccination. The relatively low amount of genetic variance accounted for by any 1-Mb window indicated that viral neutralization antibody level and response to vaccination traits are polygenic in nature. Selection for these traits is possible, but likely to be slow due to the low heritabilities and absence of markers with high genetic variation associated with them.
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Affiliation(s)
- L M Kramer
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA
| | - M S Mayes
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA
| | - E D Downey
- Elanco Animal Health, Larchwood, IA, 51241, USA
| | - R G Tait
- Neogen GeneSeek Operations, Lincoln, NE, 68504, USA
| | - A Woolums
- Department of Pathobiology and Population Medicine, Mississippi State University, Mississippi State, MS, 39762, USA
| | - C Chase
- Department of Veterinary and Biomedical Sciences, South Dakota State University, Brookings, SD, 57006, USA
| | - J M Reecy
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
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20
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De Oliveira PSN, Coutinho LL, Tizioto PC, Cesar ASM, de Oliveira GB, Diniz WJDS, De Lima AO, Reecy JM, Mourão GB, Zerlotini A, Regitano LCA. An integrative transcriptome analysis indicates regulatory mRNA-miRNA networks for residual feed intake in Nelore cattle. Sci Rep 2018; 8:17072. [PMID: 30459456 PMCID: PMC6244318 DOI: 10.1038/s41598-018-35315-5] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 10/30/2018] [Indexed: 12/21/2022] Open
Abstract
Residual Feed Intake (RFI) is an economically relevant trait in beef cattle. Among the molecular regulatory mechanisms, microRNAs (miRNAs) are an important dimension in post-transcriptional regulation and have been associated with different biological pathways. Here, we performed differential miRNAs expression and weighted gene co-expression network analyses (WGCNA) to better understand the complex interactions between miRNAs and mRNAs expressed in bovine skeletal muscle and liver. MiRNA and mRNA expression data were obtained from Nelore steers that were genetically divergent for RFI (N = 10 [low RFI or feed efficient]; N = 10 [high RFI or feed inefficient]). Differentially expressed and hub miRNAs such as bta-miR-486, bta-miR-7, bta-miR15a, bta-miR-21, bta-miR 29, bta- miR-30b, bta-miR-106b, bta-miR-199a-3p, bta-miR-204, and bta-miR 296 may have a potential role in variation of RFI. Functional enrichment analysis of differentially expressed (DE) miRNA's target genes and miRNA-mRNA correlated modules revealed that insulin, lipid, immune system, oxidative stress and muscle development signaling pathways might potentially be involved in RFI in this population. Our study identified DE miRNAs, miRNA - mRNA regulatory networks and hub miRNAs related to RFI. These findings suggest a possible role of miRNAs in regulation of RFI, providing new insights into the potential molecular mechanisms that control feed efficiency in Nelore cattle.
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Affiliation(s)
| | - Luiz L Coutinho
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | | | - Aline S M Cesar
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | | | - Wellison J da S Diniz
- Department of Genetics and Evolution, Federal University of São Carlos, São Carlos, SP, 13565-905, Brazil
| | - Andressa O De Lima
- Department of Genetics and Evolution, Federal University of São Carlos, São Carlos, SP, 13565-905, Brazil
| | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Gerson B Mourão
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
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21
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Moreira GCM, Boschiero C, Cesar ASM, Reecy JM, Godoy TF, Pértille F, Ledur MC, Moura ASAMT, Garrick DJ, Coutinho LL. Integration of genome wide association studies and whole genome sequencing provides novel insights into fat deposition in chicken. Sci Rep 2018; 8:16222. [PMID: 30385857 PMCID: PMC6212401 DOI: 10.1038/s41598-018-34364-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Accepted: 10/12/2018] [Indexed: 02/07/2023] Open
Abstract
Excessive fat deposition is a negative factor for poultry production because it reduces feed efficiency, increases the cost of meat production and is a health concern for consumers. We genotyped 497 birds from a Brazilian F2 Chicken Resource Population, using a high-density SNP array (600 K), to estimate the genomic heritability of fat deposition related traits and to identify genomic regions and positional candidate genes (PCGs) associated with these traits. Selection signature regions, haplotype blocks and SNP data from a previous whole genome sequencing study in the founders of this chicken F2 population were used to refine the list of PCGs and to identify potential causative SNPs. We obtained high genomic heritabilities (0.43-0.56) and identified 22 unique QTLs for abdominal fat and carcass fat content traits. These QTLs harbored 26 PCGs involved in biological processes such as fat cell differentiation, insulin and triglyceride levels, and lipid biosynthetic process. Three of these 26 PCGs were located within haplotype blocks there were associated with fat traits, five overlapped with selection signature regions, and 12 contained predicted deleterious variants. The identified QTLs, PCGs and potentially causative SNPs provide new insights into the genetic control of fat deposition and can lead to improved accuracy of selection to reduce excessive fat deposition in chickens.
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Affiliation(s)
| | - Clarissa Boschiero
- Department of Animal Science, University of São Paulo, Piracicaba, SP, Brazil
| | | | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | | | - Fábio Pértille
- Department of Animal Science, University of São Paulo, Piracicaba, SP, Brazil
| | | | | | - Dorian J Garrick
- School of Agriculture, Massey University, Ruakura, Hamilton, New Zealand
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22
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Gonçalves TM, de Almeida Regitano LC, Koltes JE, Cesar ASM, da Silva Andrade SC, Mourão GB, Gasparin G, Moreira GCM, Fritz-Waters E, Reecy JM, Coutinho LL. Gene Co-expression Analysis Indicates Potential Pathways and Regulators of Beef Tenderness in Nellore Cattle. Front Genet 2018; 9:441. [PMID: 30344530 PMCID: PMC6182065 DOI: 10.3389/fgene.2018.00441] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 09/14/2018] [Indexed: 12/13/2022] Open
Abstract
Beef tenderness, a complex trait affected by many factors, is economically important to beef quality, industry, and consumer’s palatability. In this study, RNA-Seq was used in network analysis to better understand the biological processes that lead to differences in beef tenderness. Skeletal muscle transcriptional profiles from 24 Nellore steers, selected by extreme estimated breeding values (EBVs) for shear force after 14 days of aging, were analyzed and 22 differentially expressed transcripts were identified. Among these were genes encoding ribosomal proteins, glutathione transporter ATP-binding cassette, sub-family C (CFTR/MRP), member 4 (ABCC4), and synaptotagmin IV (SYT4). Complementary co-expression analyses using Partial Correlation with Information Theory (PCIT), Phenotypic Impact Factor (PIF) and the Regulatory Impact Factor (RIF) methods identified candidate regulators and related pathways. The PCIT analysis identified ubiquitin specific peptidase 2 (USP2), growth factor receptor-bound protein 10 (GBR10), anoctamin 1 (ANO1), and transmembrane BAX inhibitor motif containing 4 (TMBIM4) as the most differentially hubbed (DH) transcripts. The transcripts that had a significant correlation with USP2, GBR10, ANO1, and TMBIM4 enriched for proteasome KEGG pathway. RIF analysis identified microRNAs as candidate regulators of variation in tenderness, including bta-mir-133a-2 and bta-mir-22. Both microRNAs have target genes present in the calcium signaling pathway and apoptosis. PIF analysis identified myoglobin (MB), enolase 3 (ENO3), and carbonic anhydrase 3 (CA3) as potentially having fundamental roles in tenderness. Pathways identified in our study impacted in beef tenderness included: calcium signaling, apoptosis, and proteolysis. These findings underscore some of the complex molecular mechanisms that control beef tenderness in Nellore cattle.
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Affiliation(s)
| | | | - James E Koltes
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | | | - Sónia Cristina da Silva Andrade
- Department of Animal Science, University of São Paulo, Piracicaba, Brazil.,Department of Genetics and Evolutionary Biology, University of São Paulo, São Paulo, Brazil
| | | | - Gustavo Gasparin
- Department of Animal Science, University of São Paulo, Piracicaba, Brazil
| | | | - Elyn Fritz-Waters
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, United States
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23
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Cesar ASM, Regitano LCA, Reecy JM, Poleti MD, Oliveira PSN, de Oliveira GB, Moreira GCM, Mudadu MA, Tizioto PC, Koltes JE, Fritz-Waters E, Kramer L, Garrick D, Beiki H, Geistlinger L, Mourão GB, Zerlotini A, Coutinho LL. Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits. BMC Genomics 2018; 19:499. [PMID: 29945546 PMCID: PMC6020320 DOI: 10.1186/s12864-018-4871-y] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Accepted: 06/14/2018] [Indexed: 12/21/2022] Open
Abstract
Background Integration of high throughput DNA genotyping and RNA-sequencing data allows for the identification of genomic regions that control gene expression, known as expression quantitative trait loci (eQTL), on a whole genome scale. Intramuscular fat (IMF) content and carcass composition play important roles in metabolic and physiological processes in mammals because they influence insulin sensitivity and consequently prevalence of metabolic diseases such as obesity and type 2 diabetes. However, limited information is available on the genetic variants and mechanisms associated with IMF deposition in mammals. Thus, our hypothesis was that eQTL analyses could identify putative regulatory regions and transcription factors (TFs) associated with intramuscular fat (IMF) content traits. Results We performed an integrative eQTL study in skeletal muscle to identify putative regulatory regions and factors associated with intramuscular fat content traits. Data obtained from skeletal muscle samples of 192 animals was used for association analysis between 461,466 SNPs and the transcription level of 11,808 genes. This yielded 1268 cis- and 10,334 trans-eQTLs, among which we identified nine hotspot regions that each affected the expression of > 119 genes. These putative regulatory regions overlapped with previously identified QTLs for IMF content. Three of the hotspots respectively harbored the transcription factors USF1, EGR4 and RUNX1T1, which are known to play important roles in lipid metabolism. From co-expression network analysis, we further identified modules significantly correlated with IMF content and associated with relevant processes such as fatty acid metabolism, carbohydrate metabolism and lipid metabolism. Conclusion This study provides novel insights into the link between genotype and IMF content as evident from the expression level. It thereby identifies genomic regions of particular importance and associated regulatory factors. These new findings provide new knowledge about the biological processes associated with genetic variants and mechanisms associated with IMF deposition in mammals. Electronic supplementary material The online version of this article (10.1186/s12864-018-4871-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Aline S M Cesar
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil.,Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | | | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Mirele D Poleti
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | | | | | - Gabriel C M Moreira
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | | | - Polyana C Tizioto
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | - James E Koltes
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Elyn Fritz-Waters
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Luke Kramer
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Dorian Garrick
- School of Agriculture, Massey University, Ruakura, Hamilton, New Zealand
| | - Hamid Beiki
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | | | - Gerson B Mourão
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | | | - Luiz L Coutinho
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil.
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24
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Moreira GCM, Boschiero C, Cesar ASM, Reecy JM, Godoy TF, Trevisoli PA, Cantão ME, Ledur MC, Ibelli AMG, Peixoto JDO, Moura ASAMT, Garrick D, Coutinho LL. A genome-wide association study reveals novel genomic regions and positional candidate genes for fat deposition in broiler chickens. BMC Genomics 2018; 19:374. [PMID: 29783939 PMCID: PMC5963092 DOI: 10.1186/s12864-018-4779-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 05/10/2018] [Indexed: 12/21/2022] Open
Abstract
Background Excess fat content in chickens has a negative impact on poultry production. The discovery of QTL associated with fat deposition in the carcass allows the identification of positional candidate genes (PCGs) that might regulate fat deposition and be useful for selection against excess fat content in chicken’s carcass. This study aimed to estimate genomic heritability coefficients and to identify QTLs and PCGs for abdominal fat (ABF) and skin (SKIN) traits in a broiler chicken population, originated from the White Plymouth Rock and White Cornish breeds. Results ABF and SKIN are moderately heritable traits in our broiler population with estimates ranging from 0.23 to 0.33. Using a high density SNP panel (355,027 informative SNPs), we detected nine unique QTLs that were associated with these fat traits. Among these, four QTL were novel, while five have been previously reported in the literature. Thirteen PCGs were identified that might regulate fat deposition in these QTL regions: JDP2, PLCG1, HNF4A, FITM2, ADIPOR1, PTPN11, MVK, APOA1, APOA4, APOA5, ENSGALG00000000477, ENSGALG00000000483, and ENSGALG00000005043. We used sequence information from founder animals to detect 4843 SNPs in the 13 PCGs. Among those, two were classified as potentially deleterious and two as high impact SNPs. Conclusions This study generated novel results that can contribute to a better understanding of fat deposition in chickens. The use of high density array of SNPs increases genome coverage and improves QTL resolution than would have been achieved with low density. The identified PCGs were involved in many biological processes that regulate lipid storage. The SNPs identified in the PCGs, especially those predicted as potentially deleterious and high impact, may affect fat deposition. Validation should be undertaken before using these SNPs for selection against carcass fat accumulation and to improve feed efficiency in broiler chicken production. Electronic supplementary material The online version of this article (10.1186/s12864-018-4779-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Gabriel Costa Monteiro Moreira
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, 13418-900, Brazil
| | - Clarissa Boschiero
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, 13418-900, Brazil
| | - Aline Silva Mello Cesar
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, 13418-900, Brazil
| | - James M Reecy
- Department of Animal Science, Iowa State University (ISU), Ames, Iowa, USA
| | - Thaís Fernanda Godoy
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, 13418-900, Brazil
| | - Priscila Anchieta Trevisoli
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, 13418-900, Brazil
| | | | | | | | | | | | - Dorian Garrick
- School of Agriculture, Massey University, Ruakura, Hamilton, New Zealand
| | - Luiz Lehmann Coutinho
- Department of Animal Science, University of São Paulo (USP) / Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, 13418-900, Brazil.
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25
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Kramer LM, Mayes MS, Fritz-Waters E, Williams JL, Downey ED, Tait RG, Woolums A, Chase C, Reecy JM. Evaluation of responses to vaccination of Angus cattle for four viruses that contribute to bovine respiratory disease complex. J Anim Sci 2018; 95:4820-4834. [PMID: 29293723 DOI: 10.2527/jas2017.1793] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Although vaccination is an effective measure in reducing the risk of bovine respiratory disease complex (BRDC) in cattle, BRDC losses remain significant. Increasing the efficacy of vaccination depends on elucidating the protective immune response to different antigens included in vaccines, determining the best timing for vaccination, and understanding the impact of the age of the calf on vaccination. This study measured the serum antibodies present in calves following vaccination against 4 viruses commonly associated with BRDC: bovine viral diarrhea virus type 1 and 2 (BVDV1 and BVDV2), bovine respiratory syncytial virus (BRSV), and bovine herpesvirus 1 (BHV1). Serum antibody titers were measured in more than 1,600 calves at 3-wk intervals starting at the time of the first vaccination. This first vaccination occurred at weaning for approximately half of the individuals and 3 wk before weaning for the other half. Dam age (years), time of weaning (initial vaccination or booster vaccination), and age of calf within year-season (days within year-season) classification all were found to have a significant effect on measured traits such as the initial titer and overall response. An increased initial titer was negatively correlated with each response trait (initial, booster, and overall response). Calves that were weaned at initial vaccination had greater overall antibody response to BVDV1 and BVDV2 compared with calves weaned 3 wk before initial vaccination. In contrast, calves given their initial vaccination 3 wk before weaning had greater overall antibody response to BRSV and BHV1 compared with calves that were vaccinated at weaning. Furthermore, the circulating antibody titer at which each virus needed to be below for an individual calf to positively respond to vaccination was determined (log titer of 0.38 for BVDV1, 1.5 for BVDV2, 3.88 for BRSV, and 1.5 for BHV1). This information can be used to improve vaccination protocols to allow for a greater response rate of individuals to vaccination and, hopefully, improved protection.
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26
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Reecy JM. 30 Beef Cattle Metagenomics: Predicting Traits from the inside out. J Anim Sci 2018. [DOI: 10.1093/jas/sky073.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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27
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Sharifi S, Pakdel A, Ebrahimi M, Reecy JM, Fazeli Farsani S, Ebrahimie E. Integration of machine learning and meta-analysis identifies the transcriptomic bio-signature of mastitis disease in cattle. PLoS One 2018; 13:e0191227. [PMID: 29470489 PMCID: PMC5823400 DOI: 10.1371/journal.pone.0191227] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Accepted: 12/29/2017] [Indexed: 12/14/2022] Open
Abstract
Gram-negative bacteria such as Escherichia coli (E. coli) are assumed to be among the main agents that cause severe mastitis disease with clinical signs in dairy cattle. Rapid detection of this disease is so important in order to prevent transmission to other cows and helps to reduce inappropriate use of antibiotics. With the rapid progress in high-throughput technologies, and accumulation of various kinds of '-omics' data in public repositories, there is an opportunity to retrieve, integrate, and reanalyze these resources to improve the diagnosis and treatment of different diseases and to provide mechanistic insights into host resistance in an efficient way. Meta-analysis is a relatively inexpensive option with good potential to increase the statistical power and generalizability of single-study analysis. In the current meta-analysis research, six microarray-based studies that investigate the transcriptome profile of mammary gland tissue after induced mastitis by E. coli infection were used. This meta-analysis not only reinforced the findings in individual studies, but also several novel terms including responses to hypoxia, response to drug, anti-apoptosis and positive regulation of transcription from RNA polymerase II promoter enriched by up-regulated genes. Finally, in order to identify the small sets of genes that are sufficiently informative in E. coli mastitis, the differentially expressed gene introduced by meta-analysis were prioritized by using ten different attribute weighting algorithms. Twelve meta-genes were detected by the majority of attribute weighting algorithms (with weight above 0.7) as most informative genes including CXCL8 (IL8), NFKBIZ, HP, ZC3H12A, PDE4B, CASP4, CXCL2, CCL20, GRO1(CXCL1), CFB, S100A9, and S100A8. Interestingly, the results have been demonstrated that all of these genes are the key genes in the immune response, inflammation or mastitis. The Decision tree models efficiently discovered the best combination of the meta-genes as bio-signature and confirmed that some of the top-ranked genes -ZC3H12A, CXCL2, GRO, CFB- as biomarkers for E. coli mastitis (with the accuracy 83% in average). This research properly indicated that by combination of two novel data mining tools, meta-analysis and machine learning, increased power to detect most informative genes that can help to improve the diagnosis and treatment strategies for E. coli associated with mastitis in cattle.
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Affiliation(s)
- Somayeh Sharifi
- Department of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan, Iran
- Department of Animal Science, Iowa State University, Ames, Iowa, United States of America
| | - Abbas Pakdel
- Department of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan, Iran
| | | | - James M. Reecy
- Department of Animal Science, Iowa State University, Ames, Iowa, United States of America
| | | | - Esmaeil Ebrahimie
- School of Medicine, The University of Adelaide, Adelaide, Australia
- Institute of Biotechnology, Shiraz University, Shiraz, Iran
- Division of Information Technology, Engineering and the Environment, School of Information Technology and Mathematical Sciences, University of South Australia, Adelaide, South Australia, Australia
- School of Biological Sciences, Faculty of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
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Oliveira GB, Regitano LCA, Cesar ASM, Reecy JM, Degaki KY, Poleti MD, Felício AM, Koltes JE, Coutinho LL. Integrative analysis of microRNAs and mRNAs revealed regulation of composition and metabolism in Nelore cattle. BMC Genomics 2018; 19:126. [PMID: 29415651 PMCID: PMC5804041 DOI: 10.1186/s12864-018-4514-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2016] [Accepted: 01/31/2018] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND The amount of intramuscular fat can influence the sensory characteristics and nutritional value of beef, thus the selection of animals with adequate fat deposition is important to the consumer. There is growing knowledge about the genes and pathways that control the biological processes involved in fat deposition in muscle. MicroRNAs (miRNAs) belong to a well-conserved class of non-coding small RNAs that modulate gene expression across a range of biological functions in animal development and physiology. The aim of this study was to identify differentially expressed (DE) miRNAs, regulatory candidate genes and co-expression networks related to intramuscular fat (IMF) deposition. To achieve this, we used mRNA and miRNA expression data from the Longissimus dorsi muscle of 30 Nelore steers with high (H) and low (L) genomic estimated breeding values (GEBV) for IMF deposition. RESULTS Differential miRNA expression analysis between animals with extreme GEBV values for IMF identified six DE miRNAs (FDR 10%). Functional annotation of the target genes for these microRNAs indicated that the PPARs signaling pathway is involved with IMF deposition. Candidate regulatory genes such as SDHAF4, FBXO17, ALDOA and PKM were identified by partial correlation with information theory (PCIT), phenotypic impact factor (PIF) and regulatory impact factor (RIF) co-expression approaches from integrated miRNA-mRNA expression data. Two DE miRNAs (FDR 10%), bta-miR-143 and bta-miR-146b, which were upregulated in the Low IMF group, were correlated with regulatory candidate genes, which were functionally enriched for fatty acid oxidation GO terms. Co-expression patterns obtained by weighted correlation network analysis (WGCNA), which showed possible interaction and regulation between mRNAs and miRNAs, identified several modules related to immune system function, protein metabolism, energy metabolism and glucose catabolism according to in silico analysis performed herein. CONCLUSION In this study, several genes and miRNAs were identified as candidate regulators of IMF by analyzing DE miRNAs using two different miRNA-mRNA co-expression network methods. This study contributes to the understanding of potential regulatory mechanisms of gene signaling networks involved in fat deposition processes measured in muscle. Glucose metabolism and inflammation processes were the main pathways found in silico to influence intramuscular fat deposition in beef cattle in the integrative mRNA-miRNA co-expression analysis.
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Affiliation(s)
- Gabriella B. Oliveira
- Department of Animal Science, University of São Paulo, Piracicaba, SP 13418-900 Brazil
| | | | - Aline S. M. Cesar
- Department of Animal Science, University of São Paulo, Piracicaba, SP 13418-900 Brazil
| | - James M. Reecy
- Department of Animal Science, Iowa State University, Ames, IA 50011 USA
| | - Karina Y. Degaki
- Department of Animal Science, University of São Paulo, Piracicaba, SP 13418-900 Brazil
| | - Mirele D. Poleti
- Department of Animal Science, University of São Paulo, Piracicaba, SP 13418-900 Brazil
| | - Andrezza M. Felício
- Department of Animal Science, University of São Paulo, Piracicaba, SP 13418-900 Brazil
| | - James E. Koltes
- Department of Animal Science, University of Arkansas, Fayetteville, AR 72701 USA
| | - Luiz L. Coutinho
- Department of Animal Science, University of São Paulo, Piracicaba, SP 13418-900 Brazil
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Beiki H, Pakdel A, Javaremi AN, Masoudi-Nejad A, Reecy JM. Cattle infection response network and its functional modules. BMC Immunol 2018; 19:2. [PMID: 29301495 PMCID: PMC5755453 DOI: 10.1186/s12865-017-0238-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Accepted: 12/18/2017] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Weighted Gene Co-expression Network analysis, a powerful technique used to extract co-expressed gene pattern from mRNA expression data, was constructed to infer common immune strategies used by cattle in response to five different bacterial species (Escherichia coli, Mycobacterium avium, Mycobacterium bovis, Salmonella and Staphylococcus aureus) and a protozoa (Trypanosoma Congolense) using 604 publicly available gene expression microarrays from 12 cattle infection experiments. RESULTS A total of 14,999 transcripts that were differentially expressed (DE) in at least three different infection experiments were consolidated into 15 modules that contained between 43 and 4441 transcripts. The high number of shared DE transcripts between the different types of infections indicated that there were potentially common immune strategies used in response to these infections. The number of transcripts in the identified modules varied in response to different infections. Fourteen modules showed a strong functional enrichment for specific GO/pathway terms related to "immune system process" (71%), "metabolic process" (71%), "growth and developmental process" (64%) and "signaling pathways" (50%), which demonstrated the close interconnection between these biological pathways in response to different infections. The largest module in the network had several over-represented GO/pathway terms related to different aspects of lipid metabolism and genes in this module were down-regulated for the most part during various infections. Significant negative correlations between this module's eigengene values, three immune related modules in the network, and close interconnection between their hub genes, might indicate the potential co-regulation of these modules during different infections in bovine. In addition, the potential function of 93 genes with no functional annotation was inferred based on neighbor analysis and functional uniformity among associated genes. Several hypothetical genes were differentially expressed during experimental infections, which might indicate their important role in cattle response to different infections. CONCLUSIONS We identified several biological pathways involved in immune response to different infections in cattle. These findings provide rich information for experimental biologists to design experiments, interpret experimental results, and develop novel hypothesis on immune response to different infections in cattle.
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Affiliation(s)
- Hamid Beiki
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Abbas Pakdel
- Department of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan, 84156-83111, Iran.
| | - Ardeshir Nejati Javaremi
- Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, 31587-11167, Iran
| | - Ali Masoudi-Nejad
- Laboratory of Systems Biology and Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, 31587-11167, Iran
| | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
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30
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Mateescu RG, Garrick DJ, Reecy JM. Network Analysis Reveals Putative Genes Affecting Meat Quality in Angus Cattle. Front Genet 2017; 8:171. [PMID: 29163638 PMCID: PMC5681485 DOI: 10.3389/fgene.2017.00171] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Accepted: 10/23/2017] [Indexed: 11/13/2022] Open
Abstract
Improvements in eating satisfaction will benefit consumers and should increase beef demand which is of interest to the beef industry. Tenderness, juiciness, and flavor are major determinants of the palatability of beef and are often used to reflect eating satisfaction. Carcass qualities are used as indicator traits for meat quality, with higher quality grade carcasses expected to relate to more tender and palatable meat. However, meat quality is a complex concept determined by many component traits making interpretation of genome-wide association studies (GWAS) on any one component challenging to interpret. Recent approaches combining traditional GWAS with gene network interactions theory could be more efficient in dissecting the genetic architecture of complex traits. Phenotypic measures of 23 traits reflecting carcass characteristics, components of meat quality, along with mineral and peptide concentrations were used along with Illumina 54k bovine SNP genotypes to derive an annotated gene network associated with meat quality in 2,110 Angus beef cattle. The efficient mixed model association (EMMAX) approach in combination with a genomic relationship matrix was used to directly estimate the associations between 54k SNP genotypes and each of the 23 component traits. Genomic correlated regions were identified by partial correlations which were further used along with an information theory algorithm to derive gene network clusters. Correlated SNP across 23 component traits were subjected to network scoring and visualization software to identify significant SNP. Significant pathways implicated in the meat quality complex through GO term enrichment analysis included angiogenesis, inflammation, transmembrane transporter activity, and receptor activity. These results suggest that network analysis using partial correlations and annotation of significant SNP can reveal the genetic architecture of complex traits and provide novel information regarding biological mechanisms and genes that lead to complex phenotypes, like meat quality, and the nutritional and healthfulness value of beef. Improvements in genome annotation and knowledge of gene function will contribute to more comprehensive analyses that will advance our ability to dissect the complex architecture of complex traits.
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Affiliation(s)
- Raluca G Mateescu
- Department of Animal Sciences, University of Florida, Gainesville, FL, United States
| | - Dorian J Garrick
- Department of Animal Science, Iowa State University, Ames, IA, United States
| | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, United States
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Iamartino D, Nicolazzi EL, Van Tassell CP, Reecy JM, Fritz-Waters ER, Koltes JE, Biffani S, Sonstegard TS, Schroeder SG, Ajmone-Marsan P, Negrini R, Pasquariello R, Ramelli P, Coletta A, Garcia JF, Ali A, Ramunno L, Cosenza G, de Oliveira DAA, Drummond MG, Bastianetto E, Davassi A, Pirani A, Brew F, Williams JL. Design and validation of a 90K SNP genotyping assay for the water buffalo (Bubalus bubalis). PLoS One 2017; 12:e0185220. [PMID: 28981529 PMCID: PMC5628821 DOI: 10.1371/journal.pone.0185220] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2016] [Accepted: 09/10/2017] [Indexed: 11/28/2022] Open
Abstract
Background The availability of the bovine genome sequence and SNP panels has improved various genomic analyses, from exploring genetic diversity to aiding genetic selection. However, few of the SNP on the bovine chips are polymorphic in buffalo, therefore a panel of single nucleotide DNA markers exclusive for buffalo was necessary for molecular genetic analyses and to develop genomic selection approaches for water buffalo. The creation of a 90K SNP panel for river buffalo and testing in a genome wide association study for milk production is described here. Methods The genomes of 73 buffaloes of 4 different breeds were sequenced and aligned against the bovine genome, which facilitated the identification of 22 million of sequence variants among the buffalo genomes. Based on frequencies of variants within and among buffalo breeds, and their distribution across the genome, inferred from the bovine genome sequence, 90,000 putative single nucleotide polymorphisms were selected to create an Axiom® Buffalo Genotyping Array 90K. Results This 90K “SNP-Chip” was tested in several river buffalo populations and found to have ∼70% high quality and polymorphic SNPs. Of the 90K SNPs about 24K were also found to be polymorphic in swamp buffalo. The SNP chip was used to investigate the structure of buffalo populations, and could distinguish buffalo from different farms. A Genome Wide Association Study identified genomic regions on 5 chromosomes putatively involved in milk production. Conclusion The 90K buffalo SNP chip described here is suitable for the analysis of the genomes of river buffalo breeds, and could be used for genetic diversity studies and potentially as a starting point for genome-assisted selection programmes. This SNP Chip could also be used to analyse swamp buffalo, but many loci are not informative and creation of a revised SNP set specific for swamp buffalo would be advised.
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Affiliation(s)
- Daniela Iamartino
- AIA-LGS Associazione Italiana Allevatori–Laboratorio Genetica e Servizi, Cremona, Italy
- Fondazione Parco Tecnologico Padano, Lodi, Italy
- * E-mail:
| | | | - Curtis P. Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland, United States of America
| | - James M. Reecy
- Department of Animal Science, Iowa State University, Ames, IA, United States of America
| | - Eric R. Fritz-Waters
- Department of Animal Science, Iowa State University, Ames, IA, United States of America
| | - James E. Koltes
- Department of Animal Science, Iowa State University, Ames, IA, United States of America
| | | | - Tad S. Sonstegard
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland, United States of America
| | - Steven G. Schroeder
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland, United States of America
| | - Paolo Ajmone-Marsan
- Institute of Zootechnics, Università Cattolica del S. Cuore, Piacenza, Italy
| | - Riccardo Negrini
- AIA-LGS Associazione Italiana Allevatori–Laboratorio Genetica e Servizi, Cremona, Italy
- Institute of Zootechnics, Università Cattolica del S. Cuore, Piacenza, Italy
| | | | | | - Angelo Coletta
- ANASB-Associazione Nazionale Allevatori Specie Bufalina, Centurano—Caserta, Italy
| | - José F. Garcia
- Universidade Estadual Paulista (UNESP), Câmpus de Araçatuba, Sao Paulo, Brazil
| | - Ahmad Ali
- COMSATS Institute of Information Technology, Sahiwal, Pakistan
| | - Luigi Ramunno
- Dipartimento di Scienze Zootecniche ed Ispezione degli Alimenti, Facoltà di Agraria, Università degli Studi di Napoli Federico II, Portici (NA), Italy
| | - Gianfranco Cosenza
- Dipartimento di Scienze Zootecniche ed Ispezione degli Alimenti, Facoltà di Agraria, Università degli Studi di Napoli Federico II, Portici (NA), Italy
| | | | | | | | | | - Ali Pirani
- Affymetrix UK Ltd, High Wycombe, United Kingdom
| | - Fiona Brew
- Affymetrix UK Ltd, High Wycombe, United Kingdom
| | - John L. Williams
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, Australia
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Walker K, Hong L, Reecy JM, Fritz-Waters E, Dong Q, Rowland RRR, Ireland DD, Verthelyi D, Tuggle CK, Dekkers JC, Lunney JK. Probing host immune response to porcine reproductive and respiratory syndrome virus (PRRSV) infection using 3′RNAseq and NanoString arrays. The Journal of Immunology 2017. [DOI: 10.4049/jimmunol.198.supp.226.15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Abstract
Porcine reproductive and respiratory syndrome (PRRS) is economically the most important disease of pigs worldwide and, when combined with porcine circovirus (PCV2) coinfection, increases severity of disease. Our goal is to assess the role of host genetics in determining efficacy of PRRS vaccine responses and on resistance/susceptibility to coinfection challenge. We performed 3′RNA-seq and NanoString analyses to explore the blood transcriptome and identify mechanisms and biomarkers involved. We used a nursery pig model in which 50% of 200 pigs received a PRRS vaccination (Vx); after 28 days all were challenged with PRRSV and PCV2. Each pig was genotyped (80K SNP chip) and deeply phenotyped, including repeated blood sampling for viremia level (VL), and immune proteins, and weight gain (WG). Blood RNA was analyzed to identify differentially expressed (DE) genes associated with anti-viral response phenotypes. Previous work identified a PRRS resistance marker on swine chromosome 4 (SSC4) so, for these studies, samples from 7 sib sets (AA or AB for SSC4 marker; with/without Vx; 28 pigs total) were used for RNA preparation from Tempus tube-preserved blood samples collected following vaccination (4, 7, 11, 14, 21 days) and challenge (0, 4, 7, 11, 14, 21, 28 days). Samples were subjected to 3′RNA-seq and swine immune-focused, 220 gene NanoString codeset analyses. Data will be presented on DE gene expression, and particularly on immune related genes, that may contribute to controlling PRRS vaccination and PRRSV and PCV2 challenge responses. Further studies are aimed at identifying genes and biomarkers that regulate anti-viral response phenotypes. Funding: USDA ARS, USDA NIFA grant # 2013-68004-20362.
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Affiliation(s)
- Kristen Walker
- 1USDA-ARS, BARC, APDL, Building 1040, Beltsville 20705, MD, USA
| | - Linjun Hong
- 1USDA-ARS, BARC, APDL, Building 1040, Beltsville 20705, MD, USA
| | - James M. Reecy
- 2Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames 50011, IA, USA
| | - Elyn Fritz-Waters
- 2Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames 50011, IA, USA
| | - Qian Dong
- 2Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames 50011, IA, USA
| | - Robert R. R. Rowland
- 3College of Veterinary Medicine, Kansas State University, K-231 Mosier Hall, Manhattan 66506, KS, USA
| | - Derek D.C. Ireland
- 4Laboratory of Immunology, DBRRIII, OBP, CDER, FDA, Building 52, Silver Spring, MD 20993
| | - Daniela Verthelyi
- 4Laboratory of Immunology, DBRRIII, OBP, CDER, FDA, Building 52, Silver Spring, MD 20993
| | - Christopher K. Tuggle
- 2Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames 50011, IA, USA
| | - Jack C.M. Dekkers
- 2Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames 50011, IA, USA
| | - Joan K. Lunney
- 1USDA-ARS, BARC, APDL, Building 1040, Beltsville 20705, MD, USA
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Kommadath A, Bao H, Choi I, Reecy JM, Koltes JE, Fritz-Waters E, Eisley CJ, Grant JR, Rowland RRR, Tuggle CK, Dekkers JCM, Lunney JK, Guan LL, Stothard P, Plastow GS. Genetic architecture of gene expression underlying variation in host response to porcine reproductive and respiratory syndrome virus infection. Sci Rep 2017; 7:46203. [PMID: 28393889 PMCID: PMC5385538 DOI: 10.1038/srep46203] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Accepted: 03/13/2017] [Indexed: 01/21/2023] Open
Abstract
It has been shown that inter-individual variation in host response to porcine reproductive and respiratory syndrome (PRRS) has a heritable component, yet little is known about the underlying genetic architecture of gene expression in response to PRRS virus (PRRSV) infection. Here, we integrated genome-wide genotype, gene expression, viremia level, and weight gain data to identify genetic polymorphisms that are associated with variation in inter-individual gene expression and response to PRRSV infection in pigs. RNA-seq analysis of peripheral blood samples collected just prior to experimental challenge (day 0) and at 4, 7, 11 and 14 days post infection from 44 pigs revealed 6,430 differentially expressed genes at one or more time points post infection compared to the day 0 baseline. We mapped genetic polymorphisms that were associated with inter-individual differences in expression at each day and found evidence of cis-acting expression quantitative trait loci (cis-eQTL) for 869 expressed genes (qval < 0.05). Associations between cis-eQTL markers and host response phenotypes using 383 pigs suggest that host genotype-dependent differences in expression of GBP5, GBP6, CCHCR1 and CMPK2 affect viremia levels or weight gain in response to PRRSV infection.
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Affiliation(s)
- Arun Kommadath
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton T6G 2P5, AB, Canada
| | - Hua Bao
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton T6G 2P5, AB, Canada
- Department of Research and Development, Geneseeq Technology Inc., Toronto M5G 1L7, ON, Canada
| | - Igseo Choi
- USDA-ARS, BARC, APDL, Building1040, Beltsville 20705, MD, USA
| | - James M. Reecy
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames 50011, IA, USA
| | - James E. Koltes
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames 50011, IA, USA
- Department of Animal Science, University of Arkansas, AFLS B106D, Fayetteville, AR, 72703, USA
| | - Elyn Fritz-Waters
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames 50011, IA, USA
| | - Chris J. Eisley
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames 50011, IA, USA
- Department of Statistics, Iowa State University, 1121 Snedecor Hall, Ames, IA 50011, USA
| | - Jason R. Grant
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton T6G 2P5, AB, Canada
| | - Robert R. R. Rowland
- College of Veterinary Medicine, Kansas State University, K-231 Mosier Hall, Manhattan 66506, KS, USA
| | - Christopher K. Tuggle
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames 50011, IA, USA
| | - Jack C. M. Dekkers
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames 50011, IA, USA
| | - Joan K. Lunney
- USDA-ARS, BARC, APDL, Building1040, Beltsville 20705, MD, USA
| | - Le Luo Guan
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton T6G 2P5, AB, Canada
| | - Paul Stothard
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton T6G 2P5, AB, Canada
| | - Graham S. Plastow
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton T6G 2P5, AB, Canada
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Cesar ASM, Regitano LCA, Poleti MD, Andrade SCS, Tizioto PC, Oliveira PSN, Felício AM, do Nascimento ML, Chaves AS, Lanna DPD, Tullio RR, Nassu RT, Koltes JE, Fritz-Waters E, Mourão GB, Zerlotini-Neto A, Reecy JM, Coutinho LL. Differences in the skeletal muscle transcriptome profile associated with extreme values of fatty acids content. BMC Genomics 2016; 17:961. [PMID: 27875996 PMCID: PMC5120530 DOI: 10.1186/s12864-016-3306-x] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2016] [Accepted: 11/17/2016] [Indexed: 12/19/2022] Open
Abstract
Background Lipids are a class of molecules that play an important role in cellular structure and metabolism in all cell types. In the last few decades, it has been reported that long-chain fatty acids (FAs) are involved in several biological functions from transcriptional regulation to physiological processes. Several fatty acids have been both positively and negatively implicated in different biological processes in skeletal muscle and other tissues. To gain insight into biological processes associated with fatty acid content in skeletal muscle, the aim of the present study was to identify differentially expressed genes (DEGs) and functional pathways related to gene expression regulation associated with FA content in cattle. Results Skeletal muscle transcriptome analysis of 164 Nellore steers revealed no differentially expressed genes (DEGs, FDR 10%) for samples with extreme values for linoleic acid (LA) or stearic acid (SA), and only a few DEGs for eicosapentaenoic acid (EPA, 5 DEGs), docosahexaenoic acid (DHA, 4 DEGs) and palmitic acid (PA, 123 DEGs), while large numbers of DEGs were associated with oleic acid (OA, 1134 DEGs) and conjugated linoleic acid cis9 trans11 (CLA-c9t11, 872 DEGs). Functional annotation and functional enrichment from OA DEGs identified important genes, canonical pathways and upstream regulators such as SCD, PLIN5, UCP3, CPT1, CPT1B, oxidative phosphorylation mitochondrial dysfunction, PPARGC1A, and FOXO1. Two important genes associated with lipid metabolism, gene expression and cancer were identified as DEGs between animals with high and low CLA-c9t11, specifically, epidermal growth factor receptor (EGFR) and RNPS. Conclusion Only two out of seven classes of molecules of FA studied were associated with large changes in the expression profile of skeletal muscle. OA and CLA-c9t11 content had significant effects on the expression level of genes related to important biological processes associated with oxidative phosphorylation, and cell growth, survival, and migration. These results contribute to our understanding of how some FAs modulate metabolism and may have protective health function. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3306-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Aline S M Cesar
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil.,Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | | | - Mirele D Poleti
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | - Sónia C S Andrade
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil.,Departament of Genetics and Evolutionary Biology-IB, USP, São Paulo, SP, 05508-090, Brazil
| | | | | | - Andrezza M Felício
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | | | - Amália S Chaves
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | - Dante P D Lanna
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | - Rymer R Tullio
- Embrapa Pecuária Sudeste, São Carlos, SP, 13560-970, Brazil
| | - Renata T Nassu
- Embrapa Pecuária Sudeste, São Carlos, SP, 13560-970, Brazil
| | - James E Koltes
- Department of Animal Science, University of Arkansas, Fayetteville, AR, 72701, USA
| | - Eric Fritz-Waters
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Gerson B Mourão
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | | | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Luiz L Coutinho
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418-900, Brazil.
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35
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Kramer LM, Ghaffar MAA, Koltes JE, Fritz-Waters ER, Mayes MS, Sewell AD, Weeks NT, Garrick DJ, Fernando RL, Ma L, Reecy JM. Epistatic interactions associated with fatty acid concentrations of beef from angus sired beef cattle. BMC Genomics 2016; 17:891. [PMID: 27821053 PMCID: PMC5100273 DOI: 10.1186/s12864-016-3235-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Accepted: 11/01/2016] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Consumers are becoming increasingly conscientious about the nutritional value of their food. Consumption of some fatty acids has been associated with human health traits such as blood pressure and cardiovascular disease. Therefore, it is important to investigate genetic variation in content of fatty acids present in meat. Previously publications reported regions of the cattle genome that are additively associated with variation in fatty acid content. This study evaluated epistatic interactions, which could account for additional genetic variation in fatty acid content. RESULTS Epistatic interactions for 44 fatty acid traits in a population of Angus beef cattle were evaluated with EpiSNPmpi. False discovery rate (FDR) was controlled at 5 % and was limited to well-represented genotypic combinations. Epistatic interactions were detected for 37 triacylglyceride (TAG), 36 phospholipid (PL) fatty acid traits, and three weight traits. A total of 6,181, 7,168, and 0 significant epistatic interactions (FDR < 0.05, 50-animals per genotype combination) were associated with Triacylglyceride fatty acids, Phospholipid fatty acids, and weight traits respectively and most were additive-by-additive interactions. A large number of interactions occurred in potential regions of regulatory control along the chromosomes where genes related to fatty acid metabolism reside. CONCLUSIONS Many fatty acids were associated with epistatic interactions. Despite a large number of significant interactions, there are a limited number of genomic locations that harbored these interactions. While larger population sizes are needed to accurately validate and quantify these epistatic interactions, the current findings point towards additional genetic variance that can be accounted for within these fatty acid traits.
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Affiliation(s)
- L M Kramer
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA
| | - M A Abdel Ghaffar
- Department of Animal & Poultry Production/Faculty of Environmental Agricultural Science, Arish University, North Sinai, 45516, Egypt
| | - J E Koltes
- Department of Animal Science, University of Arkansas, Fayetteville, AR, 72701, USA
| | - E R Fritz-Waters
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA
| | - M S Mayes
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA
| | | | - N T Weeks
- Department of Mathematics, Iowa State University, Ames, IA, 50011, USA
| | - D J Garrick
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA
| | - R L Fernando
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA
| | - L Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, USA
| | - J M Reecy
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
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36
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Beiki H, Nejati-Javaremi A, Pakdel A, Masoudi-Nejad A, Hu ZL, Reecy JM. Large-scale gene co-expression network as a source of functional annotation for cattle genes. BMC Genomics 2016; 17:846. [PMID: 27806696 PMCID: PMC5094014 DOI: 10.1186/s12864-016-3176-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2016] [Accepted: 10/18/2016] [Indexed: 11/15/2022] Open
Abstract
Background Genome sequencing and subsequent gene annotation of genomes has led to the elucidation of many genes, but in vertebrates the actual number of protein coding genes are very consistent across species (~20,000). Seven years after sequencing the cattle genome, there are still genes that have limited annotation and the function of many genes are still not understood, or partly understood at best. Based on the assumption that genes with similar patterns of expression across a vast array of tissues and experimental conditions are likely to encode proteins with related functions or participate within a given pathway, we constructed a genome-wide Cattle Gene Co-expression Network (CGCN) using 72 microarray datasets that contained a total of 1470 Affymetrix Genechip Bovine Genome Arrays that were retrieved from either NCBI GEO or EBI ArrayExpress. Results The total of 16,607 probe sets, which represented 11,397 genes, with unique Entrez ID were consolidated into 32 co-expression modules that contained between 29 and 2569 probe sets. All of the identified modules showed strong functional enrichment for gene ontology (GO) terms and Reactome pathways. For example, modules with important biological functions such as response to virus, response to bacteria, energy metabolism, cell signaling and cell cycle have been identified. Moreover, gene co-expression networks using “guilt-by-association” principle have been used to predict the potential function of 132 genes with no functional annotation. Four unknown Hub genes were identified in modules highly enriched for GO terms related to leukocyte activation (LOC509513), RNA processing (LOC100848208), nucleic acid metabolic process (LOC100850151) and organic-acid metabolic process (MGC137211). Such highly connected genes should be investigated more closely as they likely to have key regulatory roles. Conclusions We have demonstrated that the CGCN and its corresponding regulons provides rich information for experimental biologists to design experiments, interpret experimental results, and develop novel hypothesis on gene function in this poorly annotated genome. The network is publicly accessible at http://www.animalgenome.org/cgi-bin/host/reecylab/d. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3176-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Hamid Beiki
- Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, 31587-11167, Iran.,Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - Ardeshir Nejati-Javaremi
- Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj, 31587-11167, Iran.
| | - Abbas Pakdel
- Department of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan, 84156-83111, Iran
| | - Ali Masoudi-Nejad
- Laboratory of Systems Biology and Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, 31587-11167, Iran
| | - Zhi-Liang Hu
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
| | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, 50011, USA
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Fleming DS, Koltes JE, Fritz-Waters ER, Rothschild MF, Schmidt CJ, Ashwell CM, Persia ME, Reecy JM, Lamont SJ. Single nucleotide variant discovery of highly inbred Leghorn and Fayoumi chicken breeds using pooled whole genome resequencing data reveals insights into phenotype differences. BMC Genomics 2016; 17:812. [PMID: 27760519 PMCID: PMC5070165 DOI: 10.1186/s12864-016-3147-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2015] [Accepted: 10/05/2016] [Indexed: 11/22/2022] Open
Abstract
Background Analyses of sequence variants of two distinct and highly inbred chicken lines allowed characterization of genomic variation that may be associated with phenotypic differences between breeds. These lines were the Leghorn, the major contributing breed to commercial white-egg production lines, and the Fayoumi, representative of an outbred indigenous and robust breed. Unique within- and between-line genetic diversity was used to define the genetic differences of the two breeds through the use of variant discovery and functional annotation. Results Downstream fixation test (FST) analysis and subsequent gene ontology (GO) enrichment analysis elucidated major differences between the two lines. The genes with high FST values for both breeds were used to identify enriched gene ontology terms. Over-enriched GO annotations were uncovered for functions indicative of breed-related traits of pathogen resistance and reproductive ability for Fayoumi and Leghorn, respectively. Conclusions Variant analysis elucidated GO functions indicative of breed-predominant phenotypes related to genomic variation in the lines, showing a possible link between the genetic variants and breed traits. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3147-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - J E Koltes
- Iowa State University, Ames, IA, USA.,Department of Animal Science, University of Arkansas, Fayetteville, AR, 72701, USA
| | | | | | | | - C M Ashwell
- North Carolina State University, Raleigh, NC, USA
| | - M E Persia
- Virginia Polytechnic and State University, Blacksburg, VA, USA
| | - J M Reecy
- Iowa State University, Ames, IA, USA
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38
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Tuggle CK, Giuffra E, White SN, Clarke L, Zhou H, Ross PJ, Acloque H, Reecy JM, Archibald A, Bellone RR, Boichard M, Chamberlain A, Cheng H, Crooijmans RPMA, Delany ME, Finno CJ, Groenen MAM, Hayes B, Lunney JK, Petersen JL, Plastow GS, Schmidt CJ, Song J, Watson M. GO-FAANG meeting: a Gathering On Functional Annotation of Animal Genomes. Anim Genet 2016; 47:528-33. [PMID: 27453069 PMCID: PMC5082551 DOI: 10.1111/age.12466] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/21/2016] [Indexed: 12/18/2022]
Abstract
The Functional Annotation of Animal Genomes (FAANG) Consortium recently held a Gathering On FAANG (GO‐FAANG) Workshop in Washington, DC on October 7–8, 2015. This consortium is a grass‐roots organization formed to advance the annotation of newly assembled genomes of domesticated and non‐model organisms (www.faang.org). The workshop gathered together from around the world a group of 100+ genome scientists, administrators, representatives of funding agencies and commodity groups to discuss the latest advancements of the consortium, new perspectives, next steps and implementation plans. The workshop was streamed live and recorded, and all talks, along with speaker slide presentations, are available at www.faang.org. In this report, we describe the major activities and outcomes of this meeting. We also provide updates on ongoing efforts to implement discussions and decisions taken at GO‐FAANG to guide future FAANG activities. In summary, reference datasets are being established under pilot projects; plans for tissue sets, morphological classification and methods of sample collection for different tissues were organized; and core assays and data and meta‐data analysis standards were established.
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Affiliation(s)
- Christopher K Tuggle
- Department of Animal Science, Iowa State University, 806 Stange Road, Ames, IA, 50011, USA.
| | - Elisabetta Giuffra
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France.
| | - Stephen N White
- USDA-ARS Animal Disease Research Unit, Pullman, WA, 99164, USA.,Department of Veterinary Microbiology & Pathology, Washington State University, Pullman, WA, 99164, USA.,Center for Reproductive Biology, Washington State University, Pullman, WA, 99164, USA
| | - Laura Clarke
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, CA, 95616, USA
| | - Pablo J Ross
- Department of Animal Science, University of California, Davis, CA, 95616, USA
| | - Hervé Acloque
- INRA, UMR1388 Génétique, Physiologie et Systèmes d'Elevage, F-31326, Castanet Tolosan, France
| | - James M Reecy
- Department of Animal Science, Iowa State University, 806 Stange Road, Ames, IA, 50011, USA
| | - Alan Archibald
- The Roslin Institute and Royal(Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Edinburgh, EH29 9RG, UK
| | - Rebecca R Bellone
- Department of Population Health and Reproduction, Veterinary Genetics Laboratory, School of Veterinary Medicine, University of California-Davis, Davis, CA, USA
| | - Michèle Boichard
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France
| | - Amanda Chamberlain
- Department of Economic Development, Jobs, Transport and Resources, Agribiosciences Building, Bundoora, Australia
| | - Hans Cheng
- Avian Disease and Oncology Laboratory, USDA, ARS, East Lansing, MI, 48823, USA
| | - Richard P M A Crooijmans
- Animal Breeding and Genomics Centre, Wageningen University, PO Box 338, 6700, AH Wageningen, The Netherlands
| | - Mary E Delany
- Department of Animal Science, University of California, Davis, CA, 95616, USA
| | - Carrie J Finno
- Department of Population Health and Reproduction, University of California, Davis, CA, 95616, USA
| | - Martien A M Groenen
- Animal Breeding and Genomics Centre, Wageningen University, PO Box 338, 6700, AH Wageningen, The Netherlands
| | - Ben Hayes
- Queensland Alliance for Agriculture and Food Innovation, Centre for Animal Science, The University of Queensland, St. Lucia, 4072, Queensland, Australia
| | - Joan K Lunney
- Animal Parasitic Diseases Laboratory, BARC, ARS, USDA, Beltsville, MD, 20705, USA
| | - Jessica L Petersen
- 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
| | - Carl J Schmidt
- Department of Animal and Food Sciences, University of Delaware, Newark, DE, 19716, USA
| | - Jiuzhou Song
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Mick Watson
- The Roslin Institute and Royal(Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Edinburgh, EH29 9RG, UK
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Buchanan JW, Reecy JM, Garrick DJ, Duan Q, Beitz DC, Koltes JE, Saatchi M, Koesterke L, Mateescu RG. Deriving Gene Networks from SNP Associated with Triacylglycerol and Phospholipid Fatty Acid Fractions from Ribeyes of Angus Cattle. Front Genet 2016; 7:116. [PMID: 27379164 PMCID: PMC4913692 DOI: 10.3389/fgene.2016.00116] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Accepted: 06/06/2016] [Indexed: 11/20/2022] Open
Abstract
The fatty acid profile of beef is a complex trait that can benefit from gene-interaction network analysis to understand relationships among loci that contribute to phenotypic variation. Phenotypic measures of fatty acid profile from triacylglycerol and phospholipid fractions of longissimus muscle, pedigree information, and Illumina 54 k bovine SNP genotypes were utilized to derive an annotated gene network associated with fatty acid composition in 1,833 Angus beef cattle. The Bayes-B statistical model was utilized to perform a genome wide association study to estimate associations between 54 k SNP genotypes and 39 individual fatty acid phenotypes within each fraction. Posterior means of the effects were estimated for each of the 54 k SNP and for the collective effects of all the SNP in every 1-Mb genomic window in terms of the proportion of genetic variance explained by the window. Windows that explained the largest proportions of genetic variance for individual lipids were found in the triacylglycerol fraction. There was almost no overlap in the genomic regions explaining variance between the triacylglycerol and phospholipid fractions. Partial correlations were used to identify correlated regions of the genome for the set of largest 1 Mb windows that explained up to 35% genetic variation in either fatty acid fraction. SNP were allocated to windows based on the bovine UMD3.1 assembly. Gene network clusters were generated utilizing a partial correlation and information theory algorithm. Results were used in conjunction with network scoring and visualization software to analyze correlated SNP across 39 fatty acid phenotypes to identify SNP of significance. Significant pathways implicated in fatty acid metabolism through GO term enrichment analysis included homeostasis of number of cells, homeostatic process, coenzyme/cofactor activity, and immunoglobulin. These results suggest different metabolic pathways regulate the development of different types of lipids found in bovine muscle tissues. Network analysis using partial correlations and annotation of significant SNPs can yield information about the genetic architecture of complex traits.
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Affiliation(s)
- Justin W Buchanan
- Department of Animal Science, University of California, Davis, Davis CA, USA
| | - James M Reecy
- Department of Animal Science, Iowa State University, Ames IA, USA
| | - Dorian J Garrick
- Department of Animal Science, Iowa State University, Ames IA, USA
| | - Qing Duan
- Department of Animal Science, Iowa State University, Ames IA, USA
| | - Don C Beitz
- Department of Animal Science, Iowa State University, Ames IA, USA
| | - James E Koltes
- Department of Animal Science, University of Arkansas, Fayetteville AR, USA
| | - Mahdi Saatchi
- Department of Animal Science, Iowa State University, Ames IA, USA
| | - Lars Koesterke
- Texas Advanced Computing Center, University of Texas at Austin Austin, TX, USA
| | - Raluca G Mateescu
- Department of Animal Sciences, University of Florida, Gainesville FL, USA
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40
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Fleming DS, Koltes JE, Markey AD, Schmidt CJ, Ashwell CM, Rothschild MF, Persia ME, Reecy JM, Lamont SJ. Genomic analysis of Ugandan and Rwandan chicken ecotypes using a 600 k genotyping array. BMC Genomics 2016; 17:407. [PMID: 27230772 PMCID: PMC4882793 DOI: 10.1186/s12864-016-2711-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2016] [Accepted: 05/06/2016] [Indexed: 02/07/2023] Open
Abstract
Background Indigenous populations of animals have developed unique adaptations to their local environments, which may include factors such as response to thermal stress, drought, pathogens and suboptimal nutrition. The survival and subsequent evolution within these local environments can be the result of both natural and artificial selection driving the acquisition of favorable traits, which over time leave genomic signatures in a population. This study’s goals are to characterize genomic diversity and identify selection signatures in chickens from equatorial Africa to identify genomic regions that may confer adaptive advantages of these ecotypes to their environments. Results Indigenous chickens from Uganda (n = 72) and Rwanda (n = 100), plus Kuroilers (n = 24, an Indian breed imported to Africa), were genotyped using the Axiom® 600 k Chicken Genotyping Array. Indigenous ecotypes were defined based upon location of sampling within Africa. The results revealed the presence of admixture among the Ugandan, Rwandan, and Kuroiler populations. Genes within runs of homozygosity consensus regions are linked to gene ontology (GO) terms related to lipid metabolism, immune functions and stress-mediated responses (FDR < 0.15). The genes within regions of signatures of selection are enriched for GO terms related to health and oxidative stress processes. Key genes in these regions had anti-oxidant, apoptosis, and inflammation functions. Conclusions The study suggests that these populations have alleles under selective pressure from their environment, which may aid in adaptation to harsh environments. The correspondence in gene ontology terms connected to stress-mediated processes across the populations could be related to the similarity of environments or an artifact of the detected admixture. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2711-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - J E Koltes
- Iowa State University, Ames, IA, USA.,University of Arkansas, Fayetteville, AR, USA
| | | | | | - C M Ashwell
- North Carolina State University, Raleigh, NC, USA
| | | | - M E Persia
- Virginia Polytechnic University, Blacksburg, VA, USA
| | - J M Reecy
- Iowa State University, Ames, IA, USA
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41
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Schroyen M, Eisley C, Koltes JE, Fritz-Waters E, Choi I, Plastow GS, Guan L, Stothard P, Bao H, Kommadath A, Reecy JM, Lunney JK, Rowland RRR, Dekkers JCM, Tuggle CK. Bioinformatic analyses in early host response to Porcine Reproductive and Respiratory Syndrome virus (PRRSV) reveals pathway differences between pigs with alternate genotypes for a major host response QTL. BMC Genomics 2016; 17:196. [PMID: 26951612 PMCID: PMC4782518 DOI: 10.1186/s12864-016-2547-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2015] [Accepted: 02/26/2016] [Indexed: 01/01/2023] Open
Abstract
Background A region on Sus scrofa chromosome 4 (SSC4) surrounding single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) has been reported to be strongly associated with both weight gain and serum viremia in pigs after infection with PRRS virus (PRRSV). A proposed causal mutation in the guanylate binding protein 5 gene (GBP5) is predicted to truncate the encoded protein. To investigate transcriptional differences between WUR genotypes in early host response to PRRSV infection, an RNA-seq experiment was performed on globin depleted whole blood RNA collected on 0, 4, 7, 10 and 14 days post-infection (dpi) from eight littermate pairs with one AB (favorable) and one AA (unfavorable) WUR genotype animal per litter. Results Gene Ontology (GO) enrichment analysis of transcripts that were differentially expressed (DE) between dpi across both genotypes revealed an inflammatory response for all dpi when compared to day 0. However, at the early time points of 4 and 7dpi, several GO terms had higher enrichment scores compared to later dpi, including inflammatory response (p < 10-7), specifically regulation of NFkappaB (p < 0.01), cytokine, and chemokine activity (p < 0.01). At 10 and 14dpi, GO term enrichment indicated a switch to DNA damage response, cell cycle checkpoints, and DNA replication. Few transcripts were DE between WUR genotypes on individual dpi or averaged over all dpi, and little enrichment of any GO term was found. However, there were differences in expression patterns over time between AA and AB animals, which was confirmed by genotype-specific expression patterns of several modules that were identified in weighted gene co-expression network analyses (WGCNA). Minor differences between AA and AB animals were observed in immune response and DNA damage response (p = 0.64 and p = 0.11, respectively), but a significant effect between genotypes pointed to a difference in ion transport/homeostasis and the participation of G-coupled protein receptors (p = 8e-4), which was reinforced by results from regulatory and phenotypic impact factor analyses between genotypes. Conclusion We propose these pathway differences between WUR genotypes are the result of the inability of the truncated GBP5 of the AA genotyped pigs to inhibit viral entry and replication as quickly as the intact GBP5 protein of the AB genotyped pigs. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2547-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Martine Schroyen
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | - Christopher Eisley
- Department of Statistics, Iowa State University, 1121 Snedecor Hall, Ames, IA, 50011, USA.
| | - James E Koltes
- Department of Animal Science, University of Arkansas, AFLS B106D, Fayetteville, AR, 72701, USA.
| | - Eric Fritz-Waters
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | - Igseo Choi
- USDA-ARS, BARC, APDL, Bldg.1040, Beltsville, MD, 20705, USA.
| | - Graham S Plastow
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
| | - Leluo Guan
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
| | - Paul Stothard
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
| | - Hua Bao
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
| | - Arun Kommadath
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
| | - James M Reecy
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | - Joan K Lunney
- USDA-ARS, BARC, APDL, Bldg.1040, Beltsville, MD, 20705, USA.
| | - Robert R R Rowland
- College of Veterinary Medicine, Kansas State University, K-231 Mosier Hall, Manhattan, KS, 66506, USA.
| | - Jack C M Dekkers
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | - Christopher K Tuggle
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
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42
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Buchanan JW, Reecy JM, Garrick DJ, Duan Q, Beitz DC, Mateescu RG. Genetic parameters and genetic correlations among triacylglycerol and phospholipid fractions in Angus cattle. J Anim Sci 2016; 93:522-8. [PMID: 26020741 DOI: 10.2527/jas.2014-8418] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
The objective of this study was to estimate genetic parameters for intramuscular fatty acids from triacylglycerol (TAG) and phospholipid (PL) fractions in beef LM tissue. Longissimus muscle samples were obtained from 1,833 Angus cattle to determine the intramuscular fatty acid composition for 31 lipids and lipid classes from TAG and PL fractions and were classified by structure into saturated (SFA), monounsaturated (MUFA), polyunsaturated (PUFA), omega-3 (n-3), and omega-6 (n-6) fatty acids. An atherogenic index (AI) was also determined as a measure of the unsaturated fatty acid to SFA ratio. Restricted maximum likelihood methods combined with pedigree data were used to estimate variance components with the WOMBAT software package. Heritability estimates ranged from 0.00 to 0.63 for the major classes of fatty acids. Heritability estimates differed between the TAG and PL fractions, with higher estimates for TAG up to 0.64 and lower estimates for PL that ranged from 0.00 to 0.14. Phenotypic and genetic correlations among individual fatty acids were determined for the TAG fraction as well as among carcass traits, including rib eye area, numerical marbling score, yield grade, ether fat, and Warner-Bratzler shear force value. Strong negative or positive genetic correlations were observed among individual fatty acids in the TAG fraction, which ranged from -0.99 to 0.97 ( < 0.05). Moderate correlations between carcass traits and fatty acids from the TAG fraction ranged from -0.43 to 0.32 ( < 0.05). These results indicate that fatty acids prominent in beef tissues show significant genetic variation as well as genetic relationships with carcass traits.
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Hu ZL, Park CA, Reecy JM. Developmental progress and current status of the Animal QTLdb. Nucleic Acids Res 2015; 44:D827-33. [PMID: 26602686 PMCID: PMC4702873 DOI: 10.1093/nar/gkv1233] [Citation(s) in RCA: 188] [Impact Index Per Article: 20.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2015] [Accepted: 10/30/2015] [Indexed: 11/14/2022] Open
Abstract
The Animal QTL Database (QTLdb; http://www.animalgenome.org/QTLdb) has undergone dramatic growth in recent years in terms of new data curated, data downloads and new functions and tools. We have focused our development efforts to cope with challenges arising from rapid growth of newly published data and end users' data demands, and to optimize data retrieval and analysis to facilitate users' research. Evidenced by the 27 releases in the past 11 years, the growth of the QTLdb has been phenomenal. Here we report our recent progress which is highlighted by addition of one new species, four new data types, four new user tools, a new API tool set, numerous new functions and capabilities added to the curator tool set, expansion of our data alliance partners and more than 20 other improvements. In this paper we present a summary of our progress to date and an outlook regarding future directions.
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Affiliation(s)
- Zhi-Liang Hu
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, USA
| | - Carissa A Park
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, USA
| | - James M Reecy
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, USA
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Schroyen M, Steibel JP, Koltes JE, Choi I, Raney NE, Eisley C, Fritz-Waters E, Reecy JM, Dekkers JCM, Rowland RRR, Lunney JK, Ernst CW, Tuggle CK. Whole blood microarray analysis of pigs showing extreme phenotypes after a porcine reproductive and respiratory syndrome virus infection. BMC Genomics 2015; 16:516. [PMID: 26159815 PMCID: PMC4496889 DOI: 10.1186/s12864-015-1741-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2015] [Accepted: 06/30/2015] [Indexed: 12/18/2022] Open
Abstract
Background The presence of variability in the response of pigs to Porcine Reproductive and Respiratory Syndrome virus (PRRSv) infection, and recent demonstration of significant genetic control of such responses, leads us to believe that selection towards more disease resistant pigs could be a valid strategy to reduce its economic impact on the swine industry. To find underlying molecular differences in PRRS susceptible versus more resistant pigs, 100 animals with extremely different growth rates and viremia levels after PRRSv infection were selected from a total of 600 infected pigs. A microarray experiment was conducted on whole blood RNA samples taken at 0, 4 and 7 days post infection (dpi) from these pigs. From these data, we examined associations of gene expression with weight gain and viral load phenotypes. The single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) on the porcine 60 K SNP chip was shown to be associated with viral load and weight gain after PRRSv infection, and so the effect of the WUR10000125 (WUR) genotype on expression in whole blood was also examined. Results Limited information was obtained through linear modeling of blood gene differential expression (DE) that contrasted pigs with extreme phenotypes, for growth or viral load or between animals with different WUR genotype. However, using network-based approaches, molecular pathway differences between extreme phenotypic classes could be identified. Several gene clusters of interest were found when Weighted Gene Co-expression Network Analysis (WGCNA) was applied to 4dpi contrasted with 0dpi data. The expression pattern of one such cluster of genes correlated with weight gain and WUR genotype, contained numerous immune response genes such as cytokines, chemokines, interferon type I stimulated genes, apoptotic genes and genes regulating complement activation. In addition, Partial Correlation and Information Theory (PCIT) identified differentially hubbed (DH) genes between the phenotypically divergent groups. GO enrichment revealed that the target genes of these DH genes are enriched in adaptive immune pathways. Conclusion There are molecular differences in blood RNA patterns between pigs with extreme phenotypes or with a different WUR genotype in early responses to PRRSv infection, though they can be quite subtle and more difficult to discover with conventional DE expression analyses. Co-expression analyses such as WGCNA and PCIT can be used to reveal network differences between such extreme response groups. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1741-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Martine Schroyen
- Department of Animal Science, Iowa State University, Ames, IA, USA.
| | - Juan P Steibel
- Department of Animal Science, Michigan State University, East Lansing, MI, USA. .,Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA.
| | - James E Koltes
- Department of Animal Science, Iowa State University, Ames, IA, USA.
| | - Igseo Choi
- APDL, BARC, ARS, USDA, Beltsville, MD, USA.
| | - Nancy E Raney
- Department of Animal Science, Michigan State University, East Lansing, MI, USA.
| | | | | | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, USA.
| | - Jack C M Dekkers
- Department of Animal Science, Iowa State University, Ames, IA, USA.
| | - Robert R R Rowland
- Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA.
| | | | - Catherine W Ernst
- Department of Animal Science, Michigan State University, East Lansing, MI, USA.
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Cesar ASM, Regitano LCA, Koltes JE, Fritz-Waters ER, Lanna DPD, Gasparin G, Mourão GB, Oliveira PSN, Reecy JM, Coutinho LL. Putative regulatory factors associated with intramuscular fat content. PLoS One 2015; 10:e0128350. [PMID: 26042666 PMCID: PMC4456163 DOI: 10.1371/journal.pone.0128350] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2014] [Accepted: 04/26/2015] [Indexed: 01/12/2023] Open
Abstract
Intramuscular fat (IMF) content is related to insulin resistance, which is an important prediction factor for disorders, such as cardiovascular disease, obesity and type 2 diabetes in human. At the same time, it is an economically important trait, which influences the sensorial and nutritional value of meat. The deposition of IMF is influenced by many factors such as sex, age, nutrition, and genetics. In this study Nellore steers (Bos taurus indicus subspecies) were used to better understand the molecular mechanisms involved in IMF content. This was accomplished by identifying differentially expressed genes (DEG), biological pathways and putative regulatory factors. Animals included in this study had extreme genomic estimated breeding value (GEBV) for IMF. RNA-seq analysis, gene set enrichment analysis (GSEA) and co-expression network methods, such as partial correlation coefficient with information theory (PCIT), regulatory impact factor (RIF) and phenotypic impact factor (PIF) were utilized to better understand intramuscular adipogenesis. A total of 16,101 genes were analyzed in both groups (high (H) and low (L) GEBV) and 77 DEG (FDR 10%) were identified between the two groups. Pathway Studio software identified 13 significantly over-represented pathways, functional classes and small molecule signaling pathways within the DEG list. PCIT analyses identified genes with a difference in the number of gene-gene correlations between H and L group and detected putative regulatory factors involved in IMF content. Candidate genes identified by PCIT include: ANKRD26, HOXC5 and PPAPDC2. RIF and PIF analyses identified several candidate genes: GLI2 and IGF2 (RIF1), MPC1 and UBL5 (RIF2) and a host of small RNAs, including miR-1281 (PIF). These findings contribute to a better understanding of the molecular mechanisms that underlie fat content and energy balance in muscle and provide important information for the production of healthier beef for human consumption.
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Affiliation(s)
- Aline S. M. Cesar
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418–900, Brazil
| | | | - James E. Koltes
- Department of Animal Science, Iowa State University, Ames, IA, 50011, United States of America
| | - Eric R. Fritz-Waters
- Department of Animal Science, Iowa State University, Ames, IA, 50011, United States of America
| | - Dante P. D. Lanna
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418–900, Brazil
| | - Gustavo Gasparin
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418–900, Brazil
| | - Gerson B. Mourão
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418–900, Brazil
| | - Priscila S. N. Oliveira
- Department of Genetics and Evolution, Federal University of São Carlos, São Carlos, SP, 13565–905, Brazil
| | - James M. Reecy
- Department of Animal Science, Iowa State University, Ames, IA, 50011, United States of America
| | - Luiz L. Coutinho
- Department of Animal Science, University of São Paulo, Piracicaba, SP, 13418–900, Brazil
- * E-mail:
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Koltes JE, Fritz-Waters E, Eisley CJ, Choi I, Bao H, Kommadath A, Serão NVL, Boddicker NJ, Abrams SM, Schroyen M, Loyd H, Tuggle CK, Plastow GS, Guan L, Stothard P, Lunney JK, Liu P, Carpenter S, Rowland RRR, Dekkers JCM, Reecy JM. Identification of a putative quantitative trait nucleotide in guanylate binding protein 5 for host response to PRRS virus infection. BMC Genomics 2015; 16:412. [PMID: 26016888 PMCID: PMC4446061 DOI: 10.1186/s12864-015-1635-9] [Citation(s) in RCA: 67] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2015] [Accepted: 05/18/2015] [Indexed: 12/16/2022] Open
Abstract
Background Previously, we identified a major quantitative trait locus (QTL) for host response to Porcine Respiratory and Reproductive Syndrome virus (PRRSV) infection in high linkage disequilibrium (LD) with SNP rs80800372 on Sus scrofa chromosome 4 (SSC4). Results Within this QTL, guanylate binding protein 5 (GBP5) was differentially expressed (DE) (p < 0.05) in blood from AA versus AB rs80800372 genotyped pigs at 7,11, and 14 days post PRRSV infection. All variants within the GBP5 transcript in LD with rs80800372 exhibited allele specific expression (ASE) in AB individuals (p < 0.0001). A transcript re-assembly revealed three alternatively spliced transcripts for GBP5. An intronic SNP in GBP5, rs340943904, introduces a splice acceptor site that inserts five nucleotides into the transcript. Individuals homozygous for the unfavorable AA genotype predominantly produced this transcript, with a shifted reading frame and early stop codon that truncates the 88 C-terminal amino acids of the protein. RNA-seq analysis confirmed this SNP was associated with differential splicing by QTL genotype (p < 0.0001) and this was validated by quantitative capillary electrophoresis (p < 0.0001). The wild-type transcript was expressed at a higher level in AB versus AA individuals, whereas the five-nucleotide insertion transcript was the dominant form in AA individuals. Splicing and ASE results are consistent with the observed dominant nature of the favorable QTL allele. The rs340943904 SNP was also 100 % concordant with rs80800372 in a validation population that possessed an alternate form of the favorable B QTL haplotype. Conclusions GBP5 is known to play a role in inflammasome assembly during immune response. However, the role of GBP5 host genetic variation in viral immunity is novel. These findings demonstrate that rs340943904 is a strong candidate causal mutation for the SSC4 QTL that controls variation in host response to PRRSV. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1635-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- James E Koltes
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | - Eric Fritz-Waters
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | - Chris J Eisley
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA. .,Department of Statistics, Iowa State University, 1121 Snedecor Hall, Ames, IA, 50011, USA.
| | - Igseo Choi
- USDA-ARS, BARC, APDL, Building1040, Beltsville, MD, 20705, USA.
| | - Hua Bao
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
| | - Arun Kommadath
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
| | - Nick V L Serão
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | | | - Sam M Abrams
- USDA-ARS, BARC, APDL, Building1040, Beltsville, MD, 20705, USA.
| | - Martine Schroyen
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | - Hyelee Loyd
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | - Chris K Tuggle
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | - Graham S Plastow
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
| | - Leluo Guan
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
| | - Paul Stothard
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
| | - Joan K Lunney
- USDA-ARS, BARC, APDL, Building1040, Beltsville, MD, 20705, USA.
| | - Peng Liu
- Department of Statistics, Iowa State University, 1121 Snedecor Hall, Ames, IA, 50011, USA.
| | - Susan Carpenter
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | - Robert R R Rowland
- College of Veterinary Medicine, Kansas State University, K-231 Mosier Hall, Manhattan, KS, 66506, USA.
| | - Jack C M Dekkers
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | - James M Reecy
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
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Koltes JE, Kumar D, Kataria RS, Cooper V, Reecy JM. Transcriptional profiling of PRKG2-null growth plate identifies putative down-stream targets of PRKG2. BMC Res Notes 2015; 8:177. [PMID: 25924610 PMCID: PMC4419418 DOI: 10.1186/s13104-015-1136-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2014] [Accepted: 04/22/2015] [Indexed: 11/16/2022] Open
Abstract
Background Kinase activity of cGMP-dependent, type II, protein kinase (PRKG2) is required for the proliferative to hypertrophic transition of growth plate chondrocytes during endochondral ossification. Loss of PRKG2 function in rodent and bovine models results in dwarfism. The objective of this study was to identify pathways regulated or impacted by PRKG2 loss of function that may be responsible for disproportionate dwarfism at the molecular level. Methods Microarray technology was used to compare growth plate cartilage gene expression in dwarf versus unaffected Angus cattle to identify putative downstream targets of PRGK2. Results Pathway enrichment of 1284 transcripts (nominal p < 0.05) was used to identify candidate pathways consistent with the molecular phenotype of disproportionate dwarfism. Analysis with the DAVID pathway suite identified differentially expressed genes that clustered in the MHC, cytochrome B, WNT, and Muc1 pathways. A second analysis with pathway studio software identified differentially expressed genes in a host of pathways (e.g. CREB1, P21, CTNNB1, EGFR, EP300, JUN, P53, RHOA, and SRC). As a proof of concept, we validated the differential expression of five genes regulated by P53, including CEBPA, BRCA1, BUB1, CD58, and VDR by real-time PCR (p < 0.05). Conclusions Known and novel targets of PRKG2 were identified as enriched pathways in this study. This study indicates that loss of PRKG2 function results in differential expression of P53 regulated genes as well as additional pathways consistent with increased proliferation and apoptosis in the growth plate due to achondroplastic dwarfism. Electronic supplementary material The online version of this article (doi:10.1186/s13104-015-1136-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- James E Koltes
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
| | - Dinesh Kumar
- National Bureau of Animal Genetic Resources, Karnal, 132001, Haryana, India. .,Current address: Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi, 110012, India.
| | - Ranjit S Kataria
- National Bureau of Animal Genetic Resources, Karnal, 132001, Haryana, India.
| | - Vickie Cooper
- Veterinary Diagnostics and Production Animal Medicine, Iowa State University College of Veterinary Medicine, Ames, IA, 50011-3150, USA.
| | - James M Reecy
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA, 50011, USA.
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Duan Q, Tait RG, Schneider MJ, Beitz DC, Wheeler TL, Shackelford SD, Cundiff LV, Reecy JM. Sire breed effect on beef longissimus mineral concentrations and their relationships with carcass and palatability traits. Meat Sci 2015; 106:25-30. [PMID: 25866932 DOI: 10.1016/j.meatsci.2015.03.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2014] [Revised: 12/10/2014] [Accepted: 03/20/2015] [Indexed: 11/19/2022]
Abstract
The objective of this study was to evaluate sire breed effect on mineral concentration in beef longissimus thoracis (LT) and investigate the correlations between beef mineral concentrations and carcass and palatability traits. Steer progeny (N=246) from the Germplasm Evaluation project-Cycle VIII were used in this study. In addition to carcass traits, LT was evaluated for mineral concentrations, Warner-Bratzler shear force, and palatability traits. A mixed linear model estimated breed effects on mineral concentrations. No significant sire breed (P≥0.43) or dam breed (P≥0.20) effects were identified for mineral concentrations. Pearson correlation coefficients were calculated among mineral concentrations, carcass, and sensory traits. Zinc concentration was positively correlated (P≤0.05) with total iron (r=0.14), heme iron (r=0.13), and magnesium (r=0.19). Significant (P<0.05) correlations were identified between non-heme or heme iron and most traits in this study. Magnesium concentration was correlated with all carcass and palatability traits.
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Affiliation(s)
- Q Duan
- Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, 313 Kildee Hall, Ames, IA 50011, United States.
| | - R G Tait
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, United States; USDA, ARS, U.S. Meat Animal Research Center, P.O. Box 166, Clay Center, NE 68933, United States.
| | - M J Schneider
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, United States.
| | - D C Beitz
- Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, 313 Kildee Hall, Ames, IA 50011, United States; Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, United States.
| | - T L Wheeler
- USDA, ARS, U.S. Meat Animal Research Center, P.O. Box 166, Clay Center, NE 68933, United States.
| | - S D Shackelford
- USDA, ARS, U.S. Meat Animal Research Center, P.O. Box 166, Clay Center, NE 68933, United States.
| | - L V Cundiff
- USDA, ARS, U.S. Meat Animal Research Center, P.O. Box 166, Clay Center, NE 68933, United States.
| | - J M Reecy
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, United States.
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Andersson L, Archibald AL, Bottema CD, Brauning R, Burgess SC, Burt DW, Casas E, Cheng HH, Clarke L, Couldrey C, Dalrymple BP, Elsik CG, Foissac S, Giuffra E, Groenen MA, Hayes BJ, Huang LS, Khatib H, Kijas JW, Kim H, Lunney JK, McCarthy FM, McEwan JC, Moore S, Nanduri B, Notredame C, Palti Y, Plastow GS, Reecy JM, Rohrer GA, Sarropoulou E, Schmidt CJ, Silverstein J, Tellam RL, Tixier-Boichard M, Tosser-Klopp G, Tuggle CK, Vilkki J, White SN, Zhao S, Zhou H. Coordinated international action to accelerate genome-to-phenome with FAANG, the Functional Annotation of Animal Genomes project. Genome Biol 2015; 16:57. [PMID: 25854118 PMCID: PMC4373242 DOI: 10.1186/s13059-015-0622-4] [Citation(s) in RCA: 225] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
We describe the organization of a nascent international effort, the Functional Annotation of Animal Genomes (FAANG) project, whose aim is to produce comprehensive maps of functional elements in the genomes of domesticated animal species.
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50
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Tizioto PC, Taylor JF, Decker JE, Gromboni CF, Mudadu MA, Schnabel RD, Coutinho LL, Mourão GB, Oliveira PSN, Souza MM, Reecy JM, Nassu RT, Bressani FA, Tholon P, Sonstegard TS, Alencar MM, Tullio RR, Nogueira ARA, Regitano LCA. Detection of quantitative trait loci for mineral content of Nelore longissimus dorsi muscle. Genet Sel Evol 2015; 47:15. [PMID: 25880074 PMCID: PMC4355494 DOI: 10.1186/s12711-014-0083-3] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2014] [Accepted: 12/12/2014] [Indexed: 01/04/2023] Open
Abstract
Background Beef cattle require dietary minerals for optimal health, production and reproduction. Concentrations of minerals in tissues are at least partly genetically determined. Mapping genomic regions that affect the mineral content of bovine longissimus dorsi muscle can contribute to the identification of genes that control mineral balance, transportation, absorption and excretion and that could be associated to metabolic disorders. Methods We applied a genome-wide association strategy and genotyped 373 Nelore steers from 34 half-sib families with the Illumina BovineHD BeadChip. Genome-wide association analysis was performed for mineral content of longissimus dorsi muscle using a Bayesian approach implemented in the GenSel software. Results Muscle mineral content in Bos indicus cattle was moderately heritable, with estimates ranging from 0.29 to 0.36. Our results suggest that variation in mineral content is influenced by numerous small-effect QTL (quantitative trait loci) but a large-effect QTL that explained 6.5% of the additive genetic variance in iron content was detected at 72 Mb on bovine chromosome 12. Most of the candidate genes present in the QTL regions for mineral content were involved in signal transduction, signaling pathways via integral (also called intrinsic) membrane proteins, transcription regulation or metal ion binding. Conclusions This study identified QTL and candidate genes that affect the mineral content of skeletal muscle. Our findings provide the first step towards understanding the molecular basis of mineral balance in bovine muscle and can also serve as a basis for the study of mineral balance in other organisms. Electronic supplementary material The online version of this article (doi:10.1186/s12711-014-0083-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Polyana C Tizioto
- Department of Genetics and Evolution, Federal University of Sao Carlos, São Carlos, SP, Brazil. .,Division of Animal Sciences, University of Missouri, Columbia, MO, USA.
| | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA.
| | - Jared E Decker
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA.
| | - Caio F Gromboni
- Federal Institute of Education, Bahia Science and Technology, Valença, BA, Brazil.
| | | | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA.
| | - Luiz L Coutinho
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, SP, Brazil.
| | - Gerson B Mourão
- Department of Animal Science, University of São Paulo/ESALQ, Piracicaba, SP, Brazil.
| | - Priscila S N Oliveira
- Department of Genetics and Evolution, Federal University of Sao Carlos, São Carlos, SP, Brazil.
| | - Marcela M Souza
- Department of Genetics and Evolution, Federal University of Sao Carlos, São Carlos, SP, Brazil.
| | - James M Reecy
- Department of Animal Science, Iowa State University, Ames, IA, USA.
| | | | | | | | - Tad S Sonstegard
- United States Department of Agriculture (USDA), Agricultural Research Service, Beltsville, MD, USA.
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