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Genetic Diversity and Identification of Homozygosity-Rich Genomic Regions in Seven Italian Heritage Turkey ( Meleagris gallopavo) Breeds. Genes (Basel) 2021; 12:genes12091342. [PMID: 34573324 PMCID: PMC8470100 DOI: 10.3390/genes12091342] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 08/24/2021] [Accepted: 08/26/2021] [Indexed: 01/10/2023] Open
Abstract
Italian autochthonous turkey breeds are an important reservoir of genetic biodiversity that should be maintained with an in vivo approach. The aim of this study, part of the TuBAvI national project on biodiversity, was to use run of homozygosity (ROH), together with others statistical approaches (e.g., Wright's F-statistics, principal component analysis, ADMIXTURE analysis), to investigate the genomic diversity in several heritage turkey breeds. We performed a genome-wide characterization of ROH-rich regions in seven autochthonous turkey breeds, i.e., Brianzolo (Brzl), Bronzato Comune Italiano (BrCI), Bronzato dei Colli Euganei (CoEu), Parma e Piacenza (PrPc), Nero d'Italia (NeIt), Ermellinato di Rovigo (ErRo) and Romagnolo (Roma). ROHs were detected based on a 650K SNP genotyping. ROH_islands were identified as homozygous ROH regions shared by at least 75% of birds (within breed). Annotation of genes was performed with DAVID. The admixture analyses revealed that six breeds are unique populations while the Roma breed consists in an admixture of founder populations. Effective population size estimated on genomic data shows a numeric contraction. ROH_islands harbour genes that may be interesting for target selection in commercial populations also. Among them the PTGS2 and PLA2G4A genes on chr10 were related to reproduction efficiency. This is the first study mapping genetic variation in autochthonous turkey populations. Breeds were genetically different among them, with the Roma breed proving to be a mixture of the other breeds. The ROH_islands identified harboured genes peculiar to the selection that occurred in heritage breeds. Finally, this study releases previously undisclosed information on existing genetic variation in the turkey species.
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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] [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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Strillacci MG, Marelli SP, Martinez-Velazquez G. Hybrid Versus Autochthonous Turkey Populations: Homozygous Genomic Regions Occurrences Due to Artificial and Natural Selection. Animals (Basel) 2020; 10:ani10081318. [PMID: 32751760 PMCID: PMC7460020 DOI: 10.3390/ani10081318] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 07/27/2020] [Accepted: 07/28/2020] [Indexed: 12/28/2022] Open
Abstract
Simple Summary In this study we investigate the genomic differentiation of traditional Mexican turkey breeds and commercial hybrid strains. The analysis aimed to identify the effects of different types of selection on the birds’ genome structure. Mexican turkeys are characterized by an adaptive selection to their specific original environment; on the other hand, commercial hybrid strains are directionally selected to maximize productive traits and to reduce production costs. The Mexican turkeys were grouped in two geographic subpopulations, while high genomic homogeneity was found in hybrid birds. Traditional breeds and commercial strains are clearly differentiated from a genetic point of view. Inbreeding coefficients were here calculated with different approaches. A clear effect of selection for productive traits was recorded. Abstract The Mexican turkey population is considered to be the descendant of the original domesticated wild turkey and it is distinct from hybrid strains obtained by the intense artificial selection activity that has occurred during the last 40 years. In this study 30 Mexican turkeys were genomically compared to 38 commercial hybrids using 327,342 SNP markers in order to elucidate the differences in genome variability resulting from different types of selection, i.e., only adaptive for Mexican turkey, and strongly directional for hybrids. Runs of homozygosity (ROH) were detected and the two inbreeding coefficients (F and FROH) based on genomic information were calculated. Principal component and admixture analyses revealed two different clusters for Mexican turkeys (MEX_cl_1 and MEX_cl_2) showing genetic differentiation from hybrids (HYB) (FST equal 0.168 and 0.167, respectively). A total of 3602 ROH were found in the genome of the all turkeys populations. ROH resulted mainly short in length and the ROH_island identified in HYB (n = 9), MEX_cl_1 (n = 1), and MEX_cl_2 (n = 2) include annotated genes related to production traits: abdominal fat (percentage and weight) and egg characteristics (egg shell color and yolk weight). F and FROH resulted correlated to each other only for Mexican populations. Mexican turkey genomic variability allows us to separate the birds into two subgroups according to the geographical origin of samples, while the genomic homogeneity of hybrid birds reflected the strong directional selection occurring in this population.
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Affiliation(s)
- Maria Giuseppina Strillacci
- Department of Veterinary Medicine, University of Milan, Via Festa del Perdono, 7, 20122 Milano, Italy;
- Correspondence: ; Tel.: +39-025-033-4582
| | - Stefano Paolo Marelli
- Department of Veterinary Medicine, University of Milan, Via Festa del Perdono, 7, 20122 Milano, Italy;
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Use of gene expression profile to identify potentially relevant transcripts to myofibrillar fragmentation index trait. Funct Integr Genomics 2020; 20:609-619. [PMID: 32285226 DOI: 10.1007/s10142-020-00738-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 03/14/2020] [Accepted: 03/17/2020] [Indexed: 12/22/2022]
Abstract
The myofibrillar fragmentation index (MFI) is an indicative trait for meat tenderness. Longissimus thoracis muscle samples from the 20 most extreme bulls (out of 80 bulls set) for MFI (high (n = 10) and low (n = 10) groups) trait were used to perform transcriptomic analysis, using RNA Sequencing (RNA-Seq). An average of 24.616 genes was expressed in the Nellore muscle transcriptome analysis. A total of 96 genes were differentially expressed (p value ≤ 0.001) between the two groups of divergent bulls for MFI. The HEBP2 and BDH1 genes were overexpressed in animals with high MFI. The MYBPH and MYL6, myosin encoders, were identified. The differentially expressed genes were related to increase mitochondria efficiency, especially in cells under oxidative stress conditions, and these also were related to zinc and calcium binding, membrane transport, and muscle constituent proteins, such as actin and myosin. Most of those genes were involved in metabolic pathways of oxidation-reduction, transport of lactate in the plasma membrane, and muscle contraction. This is the first study applying MFI phenotypes in transcriptomic studies to identify and understand differentially expressed genes for beef tenderness. These results suggest that differences detected in gene expression between high and low MFI animals are related to reactive mechanisms and structural components of oxidative fibers under the condition of cellular stress. Some genes may be selected as positional candidate genes to beef tenderness, MYL6, MYBPH, TRIM63, TRIM55, TRIOBP, and CHRNG genes. The use of MFI phenotypes could enhance results of meat tenderness studies.
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Leal-Gutiérrez JD, Mateescu RG. Genetic basis of improving the palatability of beef cattle: current insights. FOOD BIOTECHNOL 2019. [DOI: 10.1080/08905436.2019.1616299] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Leal-Gutiérrez JD, Elzo MA, Johnson DD, Hamblen H, Mateescu RG. Genome wide association and gene enrichment analysis reveal membrane anchoring and structural proteins associated with meat quality in beef. BMC Genomics 2019; 20:151. [PMID: 30791866 PMCID: PMC6385435 DOI: 10.1186/s12864-019-5518-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Accepted: 02/07/2019] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Meat quality related phenotypes are difficult and expensive to measure and predict but are ideal candidates for genomic selection if genetic markers that account for a worthwhile proportion of the phenotypic variation can be identified. The objectives of this study were: 1) to perform genome wide association analyses for Warner-Bratzler Shear Force (WBSF), marbling, cooking loss, tenderness, juiciness, connective tissue and flavor; 2) to determine enriched pathways present in each genome wide association analysis; and 3) to identify potential candidate genes with multiple quantitative trait loci (QTL) associated with meat quality. RESULTS The WBSF, marbling and cooking loss traits were measured in longissimus dorsi muscle from 672 steers. Out of these, 495 animals were used to measure tenderness, juiciness, connective tissue and flavor by a sensory panel. All animals were genotyped for 221,077 markers and included in a genome wide association analysis. A total number of 68 genomic regions covering 52 genes were identified using the whole genome association approach; 48% of these genes encode transmembrane proteins or membrane associated molecules. Two enrichment analysis were performed: a tissue restricted gene enrichment applying a correlation analysis between raw associated single nucleotide polymorphisms (SNPs) by trait, and a functional classification analysis performed using the DAVID Bioinformatic Resources 6.8 server. The tissue restricted gene enrichment approach identified eleven pathways including "Endoplasmic reticulum membrane" that influenced multiple traits simultaneously. The DAVID functional classification analysis uncovered eleven clusters related to transmembrane or structural proteins. A gene network was constructed where the number of raw associated uncorrelated SNPs for each gene across all traits was used as a weight. A multiple SNP association analysis was performed for the top five most connected genes in the gene-trait network. The gene network identified the EVC2, ANXA10 and PKHD1 genes as potentially harboring multiple QTLs. Polymorphisms identified in structural proteins can modulate two different processes with direct effect on meat quality: in vivo myocyte cytoskeletal organization and postmortem proteolysis. CONCLUSION The main result from the present analysis is the uncovering of several candidate genes associated with meat quality that have structural function in the skeletal muscle.
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Affiliation(s)
| | - Mauricio A. Elzo
- Department of Animal Sciences, University of Florida, Gainesville, FL USA
| | - D. Dwain Johnson
- Department of Animal Sciences, University of Florida, Gainesville, FL USA
| | - Heather Hamblen
- Department of Animal Sciences, University of Florida, Gainesville, FL USA
| | - Raluca G. Mateescu
- Department of Animal Sciences, University of Florida, Gainesville, FL USA
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Leal-Gutiérrez JD, Rezende FM, Elzo MA, Johnson D, Peñagaricano F, Mateescu RG. Structural Equation Modeling and Whole-Genome Scans Uncover Chromosome Regions and Enriched Pathways for Carcass and Meat Quality in Beef. Front Genet 2018; 9:532. [PMID: 30555508 PMCID: PMC6282042 DOI: 10.3389/fgene.2018.00532] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Accepted: 10/22/2018] [Indexed: 12/11/2022] Open
Abstract
Structural equation models involving latent variables are useful tools for formulating hypothesized models defined by theoretical variables and causal links between these variables. The objectives of this study were: (1) to identify latent variables underlying carcass and meat quality traits and (2) to perform whole-genome scans for these latent variables in order to identify genomic regions and individual genes with both direct and indirect effects. A total of 726 steers from an Angus-Brahman multibreed population with records for 22 phenotypes were used. A total of 480 animals were genotyped with the GGP Bovine F-250. The single-step genomic best linear unbiased prediction method was used to estimate the amount of genetic variance explained for each latent variable by chromosome regions of 20 adjacent SNP-windows across the genome. Three types of genetic effects were considered: (1) direct effects on a single latent phenotype; (2) direct effects on two latent phenotypes simultaneously; and (3) indirect effects. The final structural model included carcass quality as an independent latent variable and meat quality as a dependent latent variable. Carcass quality was defined by quality grade, fat over the ribeye and marbling, while the meat quality was described by juiciness, tenderness and connective tissue, all of them measured through a taste panel. From 571 associated genomic regions (643 genes), each one explaining at least 0.05% of the additive variance, 159 regions (179 genes) were associated with carcass quality, 106 regions (114 genes) were associated with both carcass and meat quality, 242 regions (266 genes) were associated with meat quality, and 64 regions (84 genes) were associated with carcass quality, having an indirect effect on meat quality. Three biological mechanisms emerged from these findings: postmortem proteolysis of structural proteins and cellular compartmentalization, cellular proliferation and differentiation of adipocytes, and fat deposition.
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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
| | - Mauricio A. Elzo
- Department of Animal Sciences, University of Florida, Gainesville, FL, United States
| | - Dwain Johnson
- Department of Animal Sciences, University of Florida, Gainesville, FL, 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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