Hepatic Transcriptome Analysis Reveals Genes, Polymorphisms, and Molecules Related to Lamb Tenderness

Simple Summary Tenderness influences repurchase decisions of sheep meat because it is a significant factor contributing to eating satisfaction and consumer acceptance. This study analyzed the transcriptome of five high- and five low-lamb tenderness samples. The result showed potential candidate hepatic genes and polymorphisms affecting lamb tenderness. These potential candidate genes and genetic markers could be used in lamb tenderness selection programs. Abstract Tenderness is a key meat quality trait that determines the public acceptance of lamb consumption, so genetic improvement toward lamb with higher tenderness is pivotal for a sustainable sheep industry. However, unravelling the genomics controlling the tenderness is the first step. Therefore, this study aimed to identify the transcriptome signatures and polymorphisms related to divergent lamb tenderness using RNA deep sequencing. Since the molecules and enzymes that control muscle growth and tenderness are metabolized and synthesized in the liver, hepatic tissues of ten sheep with divergent phenotypes: five high- and five low-lamb tenderness samples were applied for deep sequencing. Sequence analysis identified the number of reads ranged from 21.37 to 25.37 million bases with a mean value of 22.90 million bases. In total, 328 genes are detected as differentially expressed (DEGs) including 110 and 218 genes that were up- and down-regulated, respectively. Pathway analysis showed steroid hormone biosynthesis as the dominant pathway behind the lamb tenderness. Gene expression analysis identified the top high (such as TP53INP1, CYP2E1, HSD17B13, ADH1C, and LPIN1) and low (such as ANGPTL2, IGFBP7, FABP5, OLFML3, and THOC5) expressed candidate genes. Polymorphism and association analysis revealed that mutation in OLFML3, ANGPTL2, and THOC5 genes could be potential candidate markers for tenderness in sheep. The genes and pathways identified in this study cause variation in tenderness, thus could be potential genetic markers to improve meat quality in sheep. However, further validation is needed to confirm the effect of these markers in different sheep populations so that these could be used in a selection program for lamb with high tenderness.

[1]  M. J. Uddin,et al.  Association study and expression analysis of olfactomedin like 3 gene related to meat quality, carcass characteristics, retail meat cut, and fatty acid composition in sheep , 2022, Animal bioscience.

[2]  Jakaria,et al.  Hepatic transcriptome analysis identifies genes, polymorphisms and pathways involved in the fatty acids metabolism in sheep , 2021, PloS one.

[3]  S. Sudarshan,et al.  Muscle transcriptome provides the first insight into the dynamics of gene expression with progression of age in sheep , 2021, Scientific Reports.

[4]  Joseph T. Glessner,et al.  Genome-Wide Detection of Copy Number Variations and Their Association With Distinct Phenotypes in the World’s Sheep , 2021, Frontiers in Genetics.

[5]  Huijiang Gao,et al.  Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle , 2021, Animals : an open access journal from MDPI.

[6]  Yasuyo Yamaoka,et al.  Caenorhabditis elegans Lipin 1 moderates the lifespan‐shortening effects of dietary glucose by maintaining ω‐6 polyunsaturated fatty acids , 2020, Aging cell.

[7]  N. Schreurs,et al.  The Role of MicroRNAs in Muscle Tissue Development in Beef Cattle , 2020, Genes.

[8]  Quanwei Zhang,et al.  Comparative Transcriptome Analysis Identifying the Different Molecular Genetic Markers Related to Production Performance and Meat Quality in Longissimus Dorsi Tissues of MG × STH and STH Sheep , 2020, Genes.

[9]  B. Picard,et al.  Meta-proteomics for the discovery of protein biomarkers of beef tenderness: An overview of integrated studies. , 2020, Food research international.

[10]  Zhongchang Hu,et al.  IGFBP7 downregulation or overexpression effect on bovine preadipocyte differentiation , 2019, Animal biotechnology.

[11]  M. Elzo,et al.  Genome wide association and gene enrichment analysis reveal membrane anchoring and structural proteins associated with meat quality in beef , 2019, BMC Genomics.

[12]  R. Carvalheiro,et al.  Sliding window haplotype approaches overcome single SNP analysis limitations in identifying genes for meat tenderness in Nelore cattle , 2019, BMC Genetics.

[13]  J. Jakaria,et al.  Identification of Single Nucleotide Polymorphism and Pathway Analysis of Apolipoprotein A5 (APOA5) Related to Fatty Acid Traits in Indonesian Sheep , 2018, Tropical Animal Science Journal.

[14]  J. Jakaria,et al.  Association and Expression of CYP2A6 and KIF12 Genes Related to Lamb Flavour and Odour , 2018, Tropical Animal Science Journal.

[15]  F. Peñagaricano,et al.  Comparison of transcriptomic landscapes of different lamb muscles using RNA-Seq. , 2018, PloS one.

[16]  A. Sánchez,et al.  Expression patterns and genetic variation of the ovine skeletal muscle transcriptome of sheep from five Spanish meat breeds , 2018, Scientific Reports.

[17]  Jakaria,et al.  Transcriptome signature of liver tissue with divergent mutton odour and flavour using RNA deep sequencing. , 2018, Gene.

[18]  Esti Yeger Lotem,et al.  The DifferentialNet database of differential protein–protein interactions in human tissues , 2017, Nucleic Acids Res..

[19]  Cheng Zhang,et al.  TCSBN: a database of tissue and cancer specific biological networks , 2017, Nucleic Acids Res..

[20]  S. Joo,et al.  Meat Tenderness Characteristics of Ten Major Muscles from Hanwoo Steers according to Quality Grades of Carcasses , 2017, Korean journal for food science of animal resources.

[21]  S. Bornstein,et al.  A-FABP mediates adaptive thermogenesis by promoting intracellular activation of thyroid hormones in brown adipocytes , 2017, Nature Communications.

[22]  Y. Baek,et al.  Effect of alcohol dehydrogenase 1C (ADH1C) genotype on vitamin A restriction and marbling in Korean native steers , 2017, Asian-Australasian journal of animal sciences.

[23]  C. Kim,et al.  Association between a non-synonymous HSD17B4 single nucleotide polymorphism and meat-quality traits in Berkshire pigs. , 2016, Genetics and molecular research : GMR.

[24]  A. Wierzbicka,et al.  Influence of post-mortem muscle glycogen content on the quality of beef during aging , 2016 .

[25]  D. Gerrard,et al.  Excess glycogen does not resolve high ultimate pH of oxidative muscle. , 2016, Meat science.

[26]  J. Shim,et al.  Proteomic Assessment of the Relevant Factors Affecting Pork Meat Quality Associated with Longissimus dorsi Muscles in Duroc Pigs , 2016, Asian-Australasian journal of animal sciences.

[27]  A. Law,et al.  Genome-wide association reveals QTL for growth, bone and in vivo carcass traits as assessed by computed tomography in Scottish Blackface lambs , 2016, Genetics Selection Evolution.

[28]  Daniel J. Gaffney,et al.  A survey of best practices for RNA-seq data analysis , 2016, Genome Biology.

[29]  T. Nishimura.  Role of extracellular matrix in development of skeletal muscle and postmortem aging of meat. , 2015, Meat science.

[30]  Jiangang Gao,et al.  Loss of lysyl oxidase-like 3 causes cleft palate and spinal deformity in mice , 2015, Human molecular genetics.

[31]  Yong-Min Cho,et al.  Gene Expression Patterns Associated with Peroxisome Proliferator-activated Receptor (PPAR) Signaling in the Longissimus dorsi of Hanwoo (Korean Cattle) , 2015, Asian-Australasian Journal of Animal Sciences.

[32]  C. Óvilo,et al.  Longissimus dorsi transcriptome analysis of purebred and crossbred Iberian pigs differing in muscle characteristics , 2014, BMC Genomics.

[33]  Robert E. W. Hancock,et al.  NetworkAnalyst - integrative approaches for protein–protein interaction network analysis and visual exploration , 2014, Nucleic Acids Res..

[34]  J. E. Edwards,et al.  Genetic parameters for meat quality traits of Australian lamb meat. , 2014, Meat science.

[35]  A. P. Del Vesco,et al.  Expression of calpastatin and myostatin genes associated with lamb meat quality. , 2013, Genetics and molecular research : GMR.

[36]  S. Joo,et al.  Control of fresh meat quality through manipulation of muscle fiber characteristics. , 2013, Meat science.

[37]  A. Ouali,et al.  Biomarkers of meat tenderness: present knowledge and perspectives in regards to our current understanding of the mechanisms involved. , 2013, Meat science.

[38]  D. Tesfaye,et al.  Identification of the Novel Candidate Genes and Variants in Boar Liver Tissues with Divergent Skatole Levels Using RNA Deep Sequencing , 2013, PloS one.

[39]  D. Mörlein,et al.  A single nucleotide polymorphism in the CYP2E1 gene promoter affects skatole content in backfat of boars of two commercial Duroc-sired crossbred populations. , 2012, Meat science.

[40]  D. Tesfaye,et al.  Association and expression quantitative trait loci (eQTL) analysis of porcine AMBP, GC and PPP1R3B genes with meat quality traits , 2012, Molecular Biology Reports.

[41]  Kui Li,et al.  OLFML3 Expression is Decreased during Prenatal Muscle Development and Regulated by MicroRNA-155 in Pigs , 2012, International journal of biological sciences.

[42]  Jing Zhu,et al.  GO-function: deriving biologically relevant functions from statistically significant functions , 2012, Briefings Bioinform..

[43]  Chaeyoung Lee,et al.  Association of bovine carcass phenotypes with genes in an adaptive thermogenesis pathway , 2012, Molecular Biology Reports.

[44]  J. VandeBerg,et al.  Genomics and proteomics of vertebrate cholesterol ester lipase (LIPA) and cholesterol 25-hydroxylase (CH25H) , 2011, 3 Biotech.

[45]  L. MacNeil,et al.  Gene regulatory networks and the role of robustness and stochasticity in the control of gene expression. , 2011, Genome research.

[46]  L. Bünger,et al.  The effect of conditioning period on loin muscle tenderness in crossbred lambs with or without the Texel muscling QTL (TM-QTL). , 2010, Meat science.

[47]  Roger J. Davis,et al.  Differential activation of p38MAPK isoforms by MKK6 and MKK3. , 2010, Cellular signalling.

[48]  Tae-Hun Kim,et al.  Transcriptional alteration of p53 related processes as a key factor for skeletal muscle characteristics in Sus scrofa , 2009, Molecules and cells.

[49]  Davis J. McCarthy,et al.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data , 2009, Bioinform..

[50]  Gonçalo R. Abecasis,et al.  The Sequence Alignment/Map format and SAMtools , 2009, Bioinform..

[51]  B. C. Kim,et al.  The relation between glycogen, lactate content and muscle fiber type composition, and their influence on postmortem glycolytic rate and pork quality. , 2008, Meat science.

[52]  Yoshihiro Yamanishi,et al.  KEGG for linking genomes to life and the environment , 2007, Nucleic Acids Res..

[53]  R. Durbin,et al.  GeneWise and Genomewise. , 2004, Genome research.

[54]  Charlotte Maltin,et al.  Determinants of meat quality: tenderness , 2003, Proceedings of the Nutrition Society.

[55]  Ana M Soto,et al.  Mammalian development in a changing environment: exposure to endocrine disruptors reveals the developmental plasticity of steroid‐hormone target organs , 2003, Evolution & development.

[56]  M. Ruusunen,et al.  Some effects of residual glycogen concentration on the physical and sensory quality of normal pH beef. , 2000, Meat science.

[57]  J. B. Morgan,et al.  IDENTIFICATION OF THRESHOLD LEVELS FOR WARNER-BRATZLER SHEAR FORCE IN BEEF TOP LOIN STEAKS , 1991 .

[58]  P. Warriss,et al.  The relationships between glycogen stores and muscle ultimate pH in commercially slaughtered pigs. , 1989, The British veterinary journal.

[59]  P. Warriss,et al.  Liver glycogen in slaughtered pigs and estimated time of fasting before slaughter. , 1987, The British veterinary journal.

[60]  R. M. Koch,et al.  Heritabilities and Genetic, Environmental and Phenotypic Correlations of Carcass Traits in a Population of Diverse Biological Types and their Implications in Selection Programs , 1982 .

[61]  E. N. Bergman,et al.  Glucose metabolism in ruminants: comparison of whole-body turnover with production by gut, liver, and kidneys. , 1974, Federation proceedings.

[62]  S. Suman,et al.  PROTEOMIC TECHNOLOGIES AND THEIR APPLICATIONS IN THE MEAT INDUSTRY , 2014 .

[63]  R. R. Noor,et al.  Carcass and physical meat characteristics of thin tail sheep (TTS) based on calpastatin gene (CAST) (Locus intron 5 – exon 6) genotypes variation , 2012 .

[64]  M. Gerstein,et al.  RNA-Seq: a revolutionary tool for transcriptomics , 2009, Nature Reviews Genetics.

[65]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[66]  I. I. Arief,et al.  Correlation and Categories of Meat Tenderness Based on Equipment and Panelist Test , 2008 .

[67]  Dinh T. Tran,et al.  MEAT QUALITY: UNDERSTANDING OF MEAT TENDERNESS AND INFLUENCE OF FAT CONTENT ON MEAT FLAVOR , 2006 .

[68]  Subandriyo,et al.  Relative Superiority Analysis of Garut Dam and Its Crossbred , 2005 .

[69]  J. Berger,et al.  The mechanisms of action of PPARs. , 2002, Annual review of medicine.

[70]  S Rozen,et al.  Primer3 on the WWW for general users and for biologist programmers. , 2000, Methods in molecular biology.

[71]  B. McEwen.  Steroid hormones: effect on brain development and function. , 1992, Hormone research.