Spliced genes in muscle from Nelore Cattle and their association with carcass and meat quality.
ABSTRACT: Transcript data obtained by RNA-Seq were used to identify differentially expressed alternatively spliced genes in ribeye muscle tissue between Nelore cattle that differed in their ribeye area (REA) or intramuscular fat content (IF). A total of 166 alternatively spliced transcripts from 125 genes were significantly differentially expressed in ribeye muscle between the highest and lowest REA groups (p???0.05). For animals selected on their IF content, 269 alternatively spliced transcripts from 219 genes were differentially expressed in ribeye muscle between the highest and lowest IF animals. Cassette exons and alternative 3' splice sites were the most frequently found alternatively spliced transcripts for REA and IF content. For both traits, some differentially expressed alternatively spliced transcripts belonged to myosin and myotilin gene families. The hub transcripts were identified for REA (LRRFIP1, RCAN1 and RHOBTB1) and IF (TRIP12, HSPE1 and MAP2K6) have an important role to play in muscle cell degradation, development and motility. In general, transcripts were found for both traits with biological process GO terms that were involved in pathways related to protein ubiquitination, muscle differentiation, lipids and hormonal systems. Our results reinforce the biological importance of these known processes but also reveal new insights into the complexity of the whole cell muscle mRNA of Nelore cattle.
Project description:BACKGROUND:Positively correlated with carcass weight and animal growth, the ribeye area (REA) and the backfat thickness (BFT) are economic important carcass traits, which impact directly on producer's payment. The selection of these traits has not been satisfactory since they are expressed later in the animal's life and multigene regulated. So, next-generation technologies have been applied in this area to improve animal's selection and better understand the molecular mechanisms involved in the development of these traits. Correlation network analysis, performed by tools like WGCNA (Weighted Correlation Network Analysis), has been used to explore gene-gene interactions and gene-phenotype correlations. Thus, this study aimed to identify putative candidate genes and metabolic pathways that regulate REA and BFT by constructing a gene co-expression network using WGCNA and RNA sequencing data, to better understand genetic and molecular variations behind these complex traits in Nelore cattle. RESULTS:The gene co-expression network analysis, using WGCNA, were built using RNA-sequencing data normalized by transcript per million (TPM) from 43 Nelore steers. Forty-six gene clusters were constructed, between them, three were positively correlated (p-value<?0.1) to the BFT (Green Yellow, Ivory, and Light Yellow modules) and, one cluster was negatively correlated (p-value<?0.1) with REA (Salmon module). The enrichment analysis performed by DAVID and WebGestalt (FDR 5%) identified eight Gene Ontology (GO) terms and three KEGG pathways in the Green Yellow module, mostly associated with immune response and inflammatory mechanisms. The enrichment of the Salmon module demonstrated 19 GO terms and 21 KEGG pathways, related to muscle energy metabolism, lipid metabolism, muscle degradation, and oxidative stress diseases. The Ivory and Light yellow modules have not shown significant results in the enrichment analysis. CONCLUSION:With this study, we verified that inflammation and immune response pathways modulate the BFT trait. Energy and lipid metabolism pathways, highlighting fatty acid metabolism, were the central pathways associated with REA. Some genes, as RSAD2, EIF2AK2, ACAT1, and ACSL1 were considered as putative candidate related to these traits. Altogether these results allow us to a better comprehension of the molecular mechanisms that lead to muscle and fat deposition in bovine.
Project description:Commercial cuts yield is an important trait for beef production, which affects the final value of the products, but its direct determination is a challenging procedure to be implemented in practice. The measurement of ribeye area (REA) and backfat thickness (BFT) can be used as indirect measures of meat yield. REA and BFT are important traits studied in beef cattle due to their strong implication in technological (carcass yield) and nutritional characteristics of meat products, like the degree of muscularity and total body fat. Thus, the aim of this work was to study the Longissimus dorsi muscle transcriptome of Nellore cattle, associated with REA and BFT, to find differentially expressed (DE) genes, metabolic pathways, and biological processes that may regulate these traits.By comparing the gene expression level between groups with extreme genomic estimated breeding values (GEBV), 101 DE genes for REA and 18 for BFT (false discovery rate, FDR 10%) were identified. Functional enrichment analysis for REA identified two KEGG pathways, MAPK (Mitogen-Activated Protein Kinase) signaling pathway and endocytosis pathway, and three biological processes, response to endoplasmic reticulum stress, cellular protein modification process, and macromolecule modification. The MAPK pathway is responsible for fundamental cellular processes, such as growth, differentiation, and hypertrophy. For BFT, 18 biological processes were found to be altered and grouped into 8 clusters of semantically similar terms. The DE genes identified in the biological processes for BFT were ACHE, SRD5A1, RSAD2 and RSPO3. RSAD2 has been previously shown to be associated with lipid droplet content and lipid biosynthesis.In this study, we identified genes, metabolic pathways, and biological processes, involved in differentiation, proliferation, protein turnover, hypertrophy, as well as adipogenesis and lipid biosynthesis related to REA and BFT. These results enlighten some of the molecular processes involved in muscle and fat deposition, which are economically important carcass traits for beef production.
Project description:BACKGROUND:The aim of this study was to use transcriptome RNA-Seq data from longissimus thoracis muscle of uncastrated Nelore males to identify hub genes based on co-expression network obtained from differentially expressed genes (DEGs) associated with intramuscular fat content. RESULTS:A total of 30 transcriptomics datasets (RNA-Seq) obtained from longissimus thoracis muscle were selected based on the phenotypic value of divergent intramuscular fat content: 15 with the highest intramuscular fat content (HIF) and 15 with the lowest intramuscular fat content (LIF). The transcriptomics datasets were aligned with a reference genome and 65 differentially expressed genes (DEGs) were identified, including 21 upregulated and 44 downregulated genes in HIF animals. The normalized count data from DEGs was then used for co-expression network construction. From the co-expression network, four modules were identified. The topological properties of the network were analyzed; those genes engaging in the most interactions (maximal clique centrality method) with other DEGs were predicted to be hub genes (PDE4D, KLHL30 and IL1RAP), which consequently may play a role in cellular and/or systemic lipid biology in Nelore cattle. Top modules screened from the gene co-expression network were identify. The two candidate modules had clear associated biological pathways related to fat development, cell adhesion, and muscle differentiation, immune system, among others. The hub genes belonged in top modules and were downregulated in HIF animals. PDE4D and IL1RAP have known effects on lipid metabolism and the immune system through the regulation of cAMP signaling. Given that cAMP is known to play a role in lipid systems, PDE4D and IL1RAP downregulation may contribute to increased levels of intracellular cAMP and thus may have effects on IF content differences in Nelore cattle. KLHL30 may have effects on muscle metabolism. Klhl protein families play a role in protein degradation. However, the downregulation of this gene and its role in lipid metabolism has not yet been clarified. CONCLUSIONS:The results reported in this study indicate candidate genes and molecular mechanisms involved in IF content difference in Nelore cattle.
Project description:Dystrophin transcripts were shown to be alternatively spliced in a pattern characteristic of both tissue type and developmental stage. Multiple novel spliced forms of dystrophin mRNA were identified in murine brain tissue, skeletal and cardiac muscle, diaphragm, and human cardiac Purkinje fibers. The transcript diversity was greatest in adult, non-skeletal muscle tissues. Sequence analysis revealed that four tandem exons of the murine gene are differentially spliced in at least 11 separate patterns to generate distinct isoforms. Two of these forms were observed in all tissues examined, while several others were uniquely observed in cardiac muscle and brain. Cardiac Purkinje fibers express an isoform primarily observed in brain tissue. Several spliced transcripts were observed only in postnatal development. Differential utilization of a fifth exon results in two mRNA splice forms that encode separate embryonic and adult C-termini of dystrophin. Comparison of murine with human dystrophin mRNAs showed that similar isoform expression patterns exist across species. These observations suggest that functionally distinct isoforms of the dystrophin protein are expressed in separate tissues and at different stages of development. These isoforms may be of significance in understanding the various tissue-specific effects produced by dystrophin gene mutations in Duchenne and Becker muscular dystrophy patients.
Project description:T cell activation leads to dramatic changes in cellular phenotype. We used CD3/CD28-activated human CD4 T cells to study how RNA binding proteins define the post-transcriptional landscape. Using RIPseq, we identified the RNA interactome of U2AF2 and show at the global level that U2AF2 binds the majority of transcripts that are differentially expressed and/or alternatively spliced during CD4 T cell activation. A unique protein interactome centered on U2AF2 is assembled in response to activation. Knocking down specific U2AF2 interacting partners (U2AF1, SYNCRIP, SRRM2, ILF2) selectively affects cytokine secretion and expression of activation markers. Furthermore, the expression and/or alternative splicing of transcripts important for immune cell function are also affected by knocking down these U2AF2 interacting proteins. U2AF1 and SYNCRIP knockdowns affect the proteins and transcripts bound to U2AF2, altering the transcriptome. Our work highlights the importance of RNA binding protein complexes in regulating the differential expression and alternative splicing that defines T cell activation. HTA 2.0 microarray results of total from a primary CD4 T cell culture after treatment with siRNAs (Control, U2AF1, SRRM2, SYNCRIP, and ILF2) and 24 hours after anti-CD3/CD28 bead activation Please note that the Series supplementary 'TotalRNA_HTA2_all_siRNA_100414.xslx' file has multiple worksheets containing: 1) Differentially expressed genes in ctrl siRNA vs. U2AF1 siRNA; 2) Differntially spliced genes in ctrl siRNA vs. U2AF1 siRNA; 3) Differentially spliced exons in ctrl siRNA vs. U2AF1 siRNA; 4) Differentially expressed genes in ctrl siRNA vs. SRRM2 siRNA; 5) Differntially spliced genes in ctrl siRNA vs. SRRM2 siRNA; 6) Differentially spliced exons in ctrl siRNA vs. SRRM2 siRNA; 7) Differentially expressed genes in ctrl siRNA vs. SYNCRIP siRNA; 8) Differntially spliced genes in ctrl siRNA vs. SYNCRIP siRNA; 9) Differentially spliced exons in ctrl siRNA vs. SYNCRIP siRNA; 10) Differentially expressed genes in ctrl siRNA vs. ILF2 siRNA; 11) Differntially spliced genes in ctrl siRNA vs. ILF2 siRNA; 12) Differentially spliced exons in ctrl siRNA vs. ILF2 siRNA
Project description:BACKGROUND:The time required to analyse RNA-seq data varies considerably, due to discrete steps for computational assembly, quantification of gene expression and splicing analysis. Recent fast non-alignment tools such as Kallisto and Salmon overcome these problems, but these tools require a high quality, comprehensive reference transcripts dataset (RTD), which are rarely available in plants. RESULTS:A high-quality, non-redundant barley gene RTD and database (Barley Reference Transcripts - BaRTv1.0) has been generated. BaRTv1.0, was constructed from a range of tissues, cultivars and abiotic treatments and transcripts assembled and aligned to the barley cv. Morex reference genome (Mascher et al. Nature; 544: 427-433, 2017). Full-length cDNAs from the barley variety Haruna nijo (Matsumoto et al. Plant Physiol; 156: 20-28, 2011) determined transcript coverage, and high-resolution RT-PCR validated alternatively spliced (AS) transcripts of 86 genes in five different organs and tissue. These methods were used as benchmarks to select an optimal barley RTD. BaRTv1.0-Quantification of Alternatively Spliced Isoforms (QUASI) was also made to overcome inaccurate quantification due to variation in 5' and 3' UTR ends of transcripts. BaRTv1.0-QUASI was used for accurate transcript quantification of RNA-seq data of five barley organs/tissues. This analysis identified 20,972 significant differentially expressed genes, 2791 differentially alternatively spliced genes and 2768 transcripts with differential transcript usage. CONCLUSION:A high confidence barley reference transcript dataset consisting of 60,444 genes with 177,240 transcripts has been generated. Compared to current barley transcripts, BaRTv1.0 transcripts are generally longer, have less fragmentation and improved gene models that are well supported by splice junction reads. Precise transcript quantification using BaRTv1.0 allows routine analysis of gene expression and AS.
Project description:Splicing and alternative splicing (AS) are widespread co- and post-transcriptional regulatory processes in plants. Recently, we characterized genome-wide AS landscapes and virus-induced AS patterns in Brachypodium distachyon (Brachypodium), a C3 model grass. Brachypodium plants infected with Panicum mosaic virus (PMV) alone or in mixed infections with its satellite virus (SPMV) were used for high-throughput, paired-end RNA sequencing. Here, using gene attributes of ?5,655 intronless genes, ?13,302 constitutively spliced, and ?7,564 alternatively spliced genes, we analyzed the influence of genomic features on splicing incidence and AS frequency. In Brachypodium, gene length, coding sequence length, and exon and intron number were positively correlated to splicing incidence and AS frequency. In contrast, exon length and the percentage composition of GC (%GC) content were inversely correlated with splicing incidence and AS frequency. Although gene expression status had little correlation with splicing occurrence per se, it negatively correlated to AS frequency: i.e., genes with ?5 alternatively spliced transcripts were significantly less expressed compared to genes encoding <5 alternative transcripts. Further gene set enrichment analysis uncovered unique functional relationships among nonspliced, constitutively spliced and alternatively spliced genes.
Project description:BACKGROUND: Standard 3' Affymetrix gene expression arrays have contributed a significantly higher volume of existing gene expression data than other microarray platforms. These arrays were designed to identify differentially expressed genes, but not their alternatively spliced transcript forms. No resource can currently identify expression pattern of specific mRNA forms using these microarray data, even though it is possible to do this. RESULTS: We report a web server for expression profiling of alternatively spliced transcripts using microarray data sets from 31 standard 3' Affymetrix arrays for human, mouse and rat species. The tool has been experimentally validated for mRNAs transcribed or not-detected in a human disease condition (non-obstructive azoospermia, a male infertility condition). About 4000 gene expression datasets were downloaded from a public repository. 'Good probes' with complete coverage and identity to latest reference transcript sequences were first identified. Using them, 'Transcript specific probe-clusters' were derived for each platform and used to identify expression status of possible transcripts. The web server can lead the user to datasets corresponding to specific tissues, conditions via identifiers of the microarray studies or hybridizations, keywords, official gene symbols or reference transcript identifiers. It can identify, in the tissues and conditions of interest, about 40% of known transcripts as 'transcribed', 'not-detected' or 'differentially regulated'. Corresponding additional information for probes, genes, transcripts and proteins can be viewed too. We identified the expression of transcripts in a specific clinical condition and validated a few of these transcripts by experiments (using reverse transcription followed by polymerase chain reaction). The experimental observations indicated higher agreements with the web server results, than contradictions. The tool is accessible at http://resource.ibab.ac.in/TIPMaP. CONCLUSION: The newly developed online tool forms a reliable means for identification of alternatively spliced transcript-isoforms that may be differentially expressed in various tissues, cell types or physiological conditions. Thus, by making better use of existing data, TIPMaP avoids the dependence on precious tissue-samples, in experiments with a goal to establish expression profiles of alternative splice forms--at least in some cases.
Project description:Messenger RNAs containing premature stop codons are generally targeted for degradation through nonsense-mediated mRNA decay (NMD). This mechanism degrades aberrant transcripts derived from mutant genes containing nonsense or frameshift mutations. Wild-type genes also give rise to transcripts targeted by NMD. For example, some wild-type genes give rise to alternatively spliced transcripts that are targeted for decay by NMD. In Caenorhabditis elegans, the ribosomal protein (rp) L12 gene generates a nonsense codon-bearing alternatively spliced transcript that is induced in an autoregulatory manner by the rpL12 protein. By pharmacologically blocking the NMD pathway, we identified alternatively spliced mRNA transcripts derived from the human rpL3 and rpL12 genes that are natural targets of NMD. The deduced protein sequence of these alternatively spliced transcripts suggests that they are unlikely to encode functional ribosomal proteins. Overexpression of rpL3 increased the level of the alternatively spliced rpL3 mRNA and decreased the normally expressed rpL3. This indicates that rpL3 regulates its own production by a negative feedback loop and suggests the possibility that NMD participates in this regulatory loop by degrading the non-functional alternatively spliced transcript.
Project description:T cell activation leads to dramatic changes in cellular phenotype. We used CD3/CD28-activated human CD4 T cells to study how RNA binding proteins define the post-transcriptional landscape. Using RIPseq, we identified the RNA interactome of U2AF2 and show at the global level that U2AF2 binds the majority of transcripts that are differentially expressed and/or alternatively spliced during CD4 T cell activation. A unique protein interactome centered on U2AF2 is assembled in response to activation. Knocking down specific U2AF2 interacting partners (U2AF1, SYNCRIP, SRRM2, ILF2) selectively affects cytokine secretion and expression of activation markers. Furthermore, the expression and/or alternative splicing of transcripts important for immune cell function are also affected by knocking down these U2AF2 interacting proteins. U2AF1 and SYNCRIP knockdowns affect the proteins and transcripts bound to U2AF2, altering the transcriptome. Our work highlights the importance of RNA binding protein complexes in regulating the differential expression and alternative splicing that defines T cell activation. HTA 2.0 microarray results of U2AF2 RIP RNA from a primary CD4 T cell culture after treatment with siRNAs (Control, U2AF1, and SYNCRIP) and 24 hours after anti-CD3/CD28 bead activation Please note that the Series supplementary 'U2AF2RIP_HTA2_all_siRNA_100414.xlsx' file includes multiple worksheets containing: 1) Differentially expressed genes in ctrl siRNA vs. U2AF1 siRNA; 2) Differntially spliced genes in ctrl siRNA vs. U2AF1 siRNA; 3) Differentially spliced exons in ctrl siRNA vs. U2AF1 siRNA; 4) Differentially expressed genes in ctrl siRNA vs. SYNCRIP siRNA; 5) Differntially spliced genes in ctrl siRNA vs. SYNCRIP siRNA; 6) Differentially spliced exons in ctrl siRNA vs. SYNCRIP siRNA