scholarly journals Transcriptome Analysis Reveals the Profile of Long Non-coding RNAs During Chicken Muscle Development

2021 ◽  
Vol 12 ◽  
Author(s):  
Jie Liu ◽  
Yan Zhou ◽  
Xin Hu ◽  
Jingchao Yang ◽  
Qiuxia Lei ◽  
...  
Keyword(s):  
Gene Expression ◽  
Muscle Development ◽  
Differentially Expressed ◽  
Chicken Breast ◽  
Regulation Of Transcription ◽  
Rna Seq ◽  
Regulatory Interactions ◽  
Chicken Muscle ◽  
Non Coding Rnas

The developmental complexity of muscle arises from elaborate gene regulation. Long non-coding RNAs (lncRNAs) play critical roles in muscle development through the regulation of transcription and post-transcriptional gene expression. In chickens, previous studies have focused on the lncRNA profile during the embryonic periods, but there are no studies that explore the profile from the embryonic to post-hatching period. Here, we reconstructed 14,793 lncRNA transcripts and identified 2,858 differentially expressed lncRNA transcripts and 4,282 mRNAs from 12-day embryos (E12), 17-day embryos (E17), 1-day post-hatch chicks (D1), 14-day post-hatch chicks (D14), 56-day post-hatch chicks (D56), and 98-day post-hatch chicks (D98), based on our published RNA-seq datasets. We performed co-expression analysis for the differentially expressed lncRNAs and mRNAs, using STEM, and identified two profiles with opposite expression trends: profile 4 with a downregulated pattern and profile 21 with an upregulated pattern. The cis- and trans-regulatory interactions between the lncRNAs and mRNAs were predicted within each profile. Functional analysis of the lncRNA targets showed that lncRNAs in profile 4 contributed to the cell proliferation process, while lncRNAs in profile 21 were mainly involved in metabolism. Our work highlights the lncRNA profiles involved in the development of chicken breast muscle and provides a foundation for further experiments on the role of lncRNAs in the regulation of muscle development.

scholarly journals Microsatellites as Agents of Adaptive Change: An RNA-seq based Comparative Study of Transcriptomes from Five Helianthus Species

2021 ◽  
Author(s):  
Chathurani Ranathunge ◽  
Sreepriya Pramod ◽  
Sébastien Renaut ◽  
Gregory Wheeler ◽  
Andy Perkins ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed ◽  
Regulation Of Transcription ◽  
Expression Divergence ◽  
Rna Seq ◽  
Gene Expression Divergence ◽  
Coding Regions ◽  
Regulatory Mutations ◽  
Helianthus Species

Mutations that provide environment dependent selective advantages drive adaptive divergence among species. Many phenotypic differences among related species are more likely to result from gene expression divergence rather than from non-synonymous mutations. In this regard, cis-regulatory mutations play an important part in generating functionally significant variation. Some proposed mechanisms that explore the role of cis-regulatory mutations in gene expression divergence involve microsatellites. Microsatellites exhibit high mutation rates and are abundant in both coding and non-coding regions and could influence gene function and products. Here we tested the hypothesis that microsatellites contribute to gene expression divergence among species with 50 individuals from nine closely related Helianthus species using an RNA-seq approach. Differential expression analyses of the transcriptomes revealed that genes containing microsatellites in non-coding regions (UTRs and introns) are more likely to be differentially expressed among species when compared to genes with microsatellites in the coding regions and transcripts lacking microsatellites. We detected a greater proportion of shared microsatellites in 5’UTRs and coding regions compared to 3’UTRs and non-coding transcripts among Helianthus spp. Further, allele frequency differences measured by pairwise FST at single nucleotide polymorphisms (SNPs), indicate greater genetic divergence in transcripts containing microsatellites compared to those lacking microsatellites. A gene ontology (GO) analysis revealed that microsatellite-containing differentially expressed genes are significantly enriched for GO terms associated with regulation of transcription and transcription factor activity. Collectively, our study provides compelling evidence to support the role of microsatellites in gene expression divergence.

scholarly journals Microsatellites as Agents of Adaptive Change: An RNA-Seq-Based Comparative Study of Transcriptomes from Five Helianthus Species

Symmetry ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 933
Author(s):  
Chathurani Ranathunge ◽  
Sreepriya Pramod ◽  
Sébastien Renaut ◽  
Gregory L. Wheeler ◽  
Andy D. Perkins ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed ◽  
Regulation Of Transcription ◽  
Expression Divergence ◽  
Rna Seq ◽  
Gene Expression Divergence ◽  
Coding Regions ◽  
Regulatory Mutations ◽  
Helianthus Species

Mutations that provide environment-dependent selective advantages drive adaptive divergence among species. Many phenotypic differences among related species are more likely to result from gene expression divergence rather than from non-synonymous mutations. In this regard, cis-regulatory mutations play an important part in generating functionally significant variation. Some proposed mechanisms that explore the role of cis-regulatory mutations in gene expression divergence involve microsatellites. Microsatellites exhibit high mutation rates achieved through symmetric or asymmetric mutation processes and are abundant in both coding and non-coding regions in positions that could influence gene function and products. Here we tested the hypothesis that microsatellites contribute to gene expression divergence among species with 50 individuals from five closely related Helianthus species using an RNA-seq approach. Differential expression analyses of the transcriptomes revealed that genes containing microsatellites in non-coding regions (UTRs and introns) are more likely to be differentially expressed among species when compared to genes with microsatellites in the coding regions and transcripts lacking microsatellites. We detected a greater proportion of shared microsatellites in 5′UTRs and coding regions compared to 3′UTRs and non-coding transcripts among Helianthus spp. Furthermore, allele frequency differences measured by pairwise FST at single nucleotide polymorphisms (SNPs), indicate greater genetic divergence in transcripts containing microsatellites compared to those lacking microsatellites. A gene ontology (GO) analysis revealed that microsatellite-containing differentially expressed genes are significantly enriched for GO terms associated with regulation of transcription and transcription factor activity. Collectively, our study provides compelling evidence to support the role of microsatellites in gene expression divergence.

Abstract 286: Long Noncoding RNAs Are Differentially Expressed in Heart Failure

2012 ◽  
Vol 111 (suppl_1) ◽  
Author(s):  
Emma L Robinson ◽  
Syed Haider ◽  
Hillary Hei ◽  
Richard T Lee ◽  
Roger S Foo
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Significant Proportion ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Control Of Gene Expression ◽  
Failing Heart ◽  
Novel Transcripts ◽  
Non Coding Rnas

Heart failure comprises of clinically distinct inciting causes but a consistent pattern of change in myocardial gene expression supports the hypothesis that unifying biochemical mechanisms underlie disease progression. The recent RNA-seq revolution has enabled whole transcriptome profiling, using deep-sequencing technologies. Up to 70% of the genome is now known to be transcribed into RNA, a significant proportion of which is long non-coding RNAs (lncRNAs), defined as polyribonucleotides of ≥200 nucleotides. This project aims to discover whether the myocardium expression of lncRNAs changes in the failing heart. Paired end RNA-seq from a 300-400bp library of ‘stretched’ mouse myocyte total RNA was carried out to generate 76-mer sequence reads. Mechanically stretching myocytes with equibiaxial stretch apparatus mimics pathological hypertrophy in the heart. Transcripts were assembled and aligned to reference genome mm9 (UCSC), abundance determined and differential expression of novel transcripts and alternative splice variants were compared with that of control (non-stretched) mouse myocytes. Five novel transcripts have been identified in our RNA-seq that are differentially expressed in stretched myocytes compared with non-stretched. These are regions of the genome that are currently unannotated and potentially are transcribed into non-coding RNAs. Roles of known lncRNAs include control of gene expression, either by direct interaction with complementary regions of the genome or association with chromatin remodelling complexes which act on the epigenome.Changes in expression of genes which contribute to the deterioration of the failing heart could be due to the actions of these novel lncRNAs, immediately suggesting a target for new pharmaceuticals. Changes in the expression of these novel transcripts will be validated in a larger sample size of stretched myocytes vs non-stretched myocytes as well as in the hearts of transverse aortic constriction (TAC) mice vs Sham (surgical procedure without the aortic banding). In vivo investigations will then be carried out, using siLNA antisense technology to silence novel lncRNAs in mice.

scholarly journals Long non-coding RNAs as pan-cancer master gene regulators of associated protein-coding genes: a systems biology approach

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6388 ◽  
Author(s):  
Asanigari Saleembhasha ◽  
Seema Mishra
Keyword(s):  
Gene Expression ◽  
Gene Expression Pattern ◽  
Differentially Expressed ◽  
Regulation Of Transcription ◽  
Biological Processes ◽  
Lncrna Gene ◽  
Cancer Types ◽  
Non Coding Rnas ◽  
Rna Interaction ◽  
Pan Cancer

Despite years of research, we are still unraveling crucial stages of gene expression regulation in cancer. On the basis of major biological hallmarks, we hypothesized that there must be a uniform gene expression pattern and regulation across cancer types. Among non-coding genes, long non-coding RNAs (lncRNAs) are emerging as key gene regulators playing powerful roles in cancer. Using TCGA RNAseq data, we analyzed coding (mRNA) and non-coding (lncRNA) gene expression across 15 and 9 common cancer types, respectively. 70 significantly differentially expressed genes common to all 15 cancer types were enlisted. Correlating with protein expression levels from Human Protein Atlas, we observed 34 positively correlated gene sets which are enriched in gene expression, transcription from RNA Pol-II, regulation of transcription and mitotic cell cycle biological processes. Further, 24 lncRNAs were among common significantly differentially expressed non-coding genes. Using guilt-by-association method, we predicted lncRNAs to be involved in same biological processes. Combining RNA-RNA interaction prediction and transcription regulatory networks, we identified E2F1, FOXM1 and PVT1 regulatory path as recurring pan-cancer regulatory entity. PVT1 is predicted to interact with SYNE1 at 3′-UTR; DNAJC9, RNPS1 at 5′-UTR and ATXN2L, ALAD, FOXM1 and IRAK1 at CDS sites. The key findings are that through E2F1, FOXM1 and PVT1 regulatory axis and possible interactions with different coding genes, PVT1 may be playing a prominent role in pan-cancer development and progression.

Genome-wide identification and characterization of long non-coding RNAs in Longissimus dorsi skeletal muscle of Shandong black cattle and Luxi cattle

2020 ◽  
Author(s):  
Ruili Liu ◽  
Xianxun Liu ◽  
Kun Yu ◽  
Xuejin Bai ◽  
Yajuan Dong
Keyword(s):  
Skeletal Muscle ◽  
Cell Differentiation ◽  
Muscle Cell ◽  
Muscle Development ◽  
Differentially Expressed ◽  
Luciferase Reporter ◽  
Longissimus Dorsi ◽  
Protein Coding ◽  
Non Coding Rnas

Abstract Background There is increasing understanding of the possible regulatory role of long non-coding RNAs (LncRNA). Studies on livestock have mainly focused on the regulation of cell differentiation, fat synthesis, and embryonic development. However, there has been little study of skeletal muscle of domestic animals and the potential role of lncRNA. Results RNA samples were collected from longissimus dorsi muscle samples of Shandong black cattle and Luxi cattle and libraries were constructed and sequenced. A total of 1415 transcripts (of which 480 were LncRNAs) were differentially expressed (P < 0.05) in the different breeds, and fourteen of these RNAs were randomly selected and validated by qPCR. We found that the most differentially expressed LncRNAs were found on chromosome 9, with 1164 within 50 kb of a protein-coding gene. In addition, Pearson's correlation coefficients of co-expression levels indicated a potential trans regulatory relationship between the differentially expressed LncRNAs and 43844 mRNAs (r > 0.9). The identified co-expressed mRNAs (MYORG, Dll1, EFNB2, SOX6, MYOCD, and MYLK3) are related to the formation of muscle structure, and enriched in muscle system process, strained muscle cell differentiation, muscle cell development, striated muscle tissue development, calcium signaling, and AMPK signaling. Additionally, we also found that some LncRNAs (LOC112444238, LOC101903367, LOC104975788, LOC112441863, LOC112449549, and LOC101907194) may interact with miRNAs related to cattle muscle growth and development. Based on this, we constructed a LncRNAs-miRNA-mRNA interaction network as the putative basis for biological regulation in cattle skeletal muscle. Interestingly, a candidate differential LncRNA (LOC104975788) and a protein-coding gene (Pax7) contain miR-133a binding sites and binding was confirmed by luciferase reporter assay. LOC104975788 may bind miR-133a competitively with Pax7, thus relieving the inhibitory effect of miR-133a on Pax7 to regulate skeletal muscle development. These results will provide the theoretical basis for further study of LncRNA regulation and activity in different cattle breeds. Conclusions The data obtained in this study were used to predict muscle-related LncRNAs-miRNA-mRNA interaction networks, which can help elucidate the molecular mechanism of cattle muscle development. These results can be used to facilitate livestock breeding and improve livestock production.

scholarly journals An exon-intron split framework to prioritize transcriptional and post-transcriptional regulatory signals and its application to study energy homeostasis in pigs

2021 ◽  
Author(s):  
Emilio Marmol-Sanchez ◽  
Susanna Cirera ◽  
Laura Zingaretti ◽  
Mette Juul Jacobsen ◽  
Yuliaxis Ramayo-Caldas ◽  
...  
Keyword(s):  
Gene Expression ◽  
Binding Sites ◽  
Muscle Development ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Enhancer Activity ◽  
Protein Coding ◽  
Transcriptional Regulatory ◽  
Mrna Transcripts

Bulk sequencing of RNA transcripts has typically been used to quantify gene expression levels in different experimental systems. However, linking differentially expressed (DE) mRNA transcripts to gene expression regulators, such as miRNAs or transcription factors (TFs), remains challenging, as in silico or experimental interactions are commonly identified post hoc after selecting differentially expressed genes of interest, thus biasing the interpretation of underlying gene regulatory mechanisms. In this study, we performed an exon-intron split analysis (EISA) to muscle and fat RNA-seq data from two Duroc pig populations subjected to fasting-feeding conditions and with divergent fatness profiles, respectively. We compared the number of reads from exonic and intronic regions for all expressed protein-coding genes and divided their expression profiles into transcriptional and post-transcriptional components, considering intronic and exonic fractions as estimates of the abundance of pre-mRNA and mature mRNA transcripts, respectively. In this way, we obtained a prioritized list of genes showing significant transcriptional and post-transcriptional regulatory signals. After running EISA analyses, protein-coding mRNA genes with downregulated exonic fractions and high post-transcriptional signals were significantly enriched for binding sites of upregulated DE miRNAs. Moreover, these genes showed an increased expression covariation for the exonic fraction compared to that of the intronic fraction. On the contrary, they did not show enrichment for binding sites of highly expressed and/or downregulated DE miRNAs. Among the set of loci displaying miRNA-driven post-transcriptional regulatory signals, we observed genes related to glucose homeostasis (PDK4, NR4A3, CHRNA1 and DKK2), cell differentiation (MYO9A, KLF5 and BACH2) or adipocytes metabolism (LEP, SERPINE2, RNF157, OSBPL10 and PRSS23). Besides, genes showing upregulated intronic fractions with a lack of exonic fractions were significantly enriched for TF-enhancer activity while depleted for miRNA targets, thus suggesting a transient transcription activation regulating skeletal muscle development. Our results highlight an efficient framework to classify mRNA genes showing transcriptional and post-transcriptional signals linked to transient transcription and miRNA-driven downregulation by using exonic and intronic fractions of RNA-seq datasets from muscle and adipose tissues in pigs.

scholarly journals OP0021 IDENTIFICATION OF DIFFERENTIALLY EXPRESSED GENES IN EARLY RHEUMATOID ARTHRITIS PATIENTS RESPONDING TO TOCILIZUMAB

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 12.2-12
Author(s):  
I. Muller ◽  
M. Verhoeven ◽  
H. Gosselt ◽  
M. Lin ◽  
T. De Jong ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
T Cells ◽  
Gene Ontology ◽  
Regulatory T Cells ◽  
Early Rheumatoid Arthritis ◽  
Whole Blood ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Double Blind

Background:Tocilizumab (TCZ) is a monoclonal antibody that binds to the interleukin 6 receptor (IL-6R), inhibiting IL-6R signal transduction to downstream inflammatory mediators. TCZ has shown to be effective as monotherapy in early rheumatoid arthritis (RA) patients (1). However, approximately one third of patients inadequately respond to therapy and the biological mechanisms underlying lack of efficacy for TCZ remain elusive (1). Here we report gene expression differences, in both whole blood and peripheral blood mononuclear cells (PBMC) RNA samples between early RA patients, categorized by clinical TCZ response (reaching DAS28 < 3.2 at 6 months). These findings could lead to identification of predictive biomarkers for TCZ response and improve RA treatment strategies.Objectives:To identify potential baseline gene expression markers for TCZ response in early RA patients using an RNA-sequencing approach.Methods:Two cohorts of RA patients were included and blood was collected at baseline, before initiating TCZ treatment (8 mg/kg every 4 weeks, intravenously). DAS28-ESR scores were calculated at baseline and clinical response to TCZ was defined as DAS28 < 3.2 at 6 months of treatment. In the first cohort (n=21 patients, previously treated with DMARDs), RNA-sequencing (RNA-seq) was performed on baseline whole blood PAXgene RNA (Illumina TruSeq mRNA Stranded) and differential gene expression (DGE) profiles were measured between responders (n=14) and non-responders (n=7). For external replication, in a second cohort (n=95 therapy-naïve patients receiving TCZ monotherapy), RNA-seq was conducted on baseline PBMC RNA (SMARTer Stranded Total RNA-Seq Kit, Takara Bio) from the 2-year, multicenter, double-blind, placebo-controlled, randomized U-Act-Early trial (ClinicalTrials.gov identifier: NCT01034137) and DGE was analyzed between 84 responders and 11 non-responders.Results:Whole blood DGE analysis showed two significantly higher expressed genes in TCZ non-responders (False Discovery Rate, FDR < 0.05): urotensin 2 (UTS2) and caveolin-1 (CAV1). Subsequent analysis of U-Act-Early PBMC DGE showed nine differentially expressed genes (FDR < 0.05) of which expression in clinical TCZ non-responders was significantly higher for eight genes (MTCOP12, ZNF774, UTS2, SLC4A1, FECH, IFIT1B, AHSP, and SPTB) and significantly lower for one gene (TND2P28M). Both analyses were corrected for baseline DAS28-ESR, age and gender. Expression of UTS2, with a proposed function in regulatory T-cells (2), was significantly higher in TCZ non-responders in both cohorts. Furthermore, gene ontology enrichment analysis revealed no distinct gene ontology or IL-6 related pathway(s) that were significantly different between TCZ-responders and non-responders.Conclusion:Several genes are differentially expressed at baseline between responders and non-responders to TCZ therapy at 6 months. Most notably, UTS2 expression is significantly higher in TCZ non-responders in both whole blood as well as PBMC cohorts. UTS2 could be a promising target for further analyses as a potential predictive biomarker for TCZ response in RA patients in combination with clinical parameters (3).References:[1]Bijlsma JWJ, Welsing PMJ, Woodworth TG, et al. Early rheumatoid arthritis treated with tocilizumab, methotrexate, or their combination (U-Act-Early): a multicentre, randomised, double-blind, double-dummy, strategy trial. Lancet. 2016;388(10042):343-55.[2]Bhairavabhotla R, Kim YC, Glass DD, et al. Transcriptome profiling of human FoxP3+ regulatory T cells. Human Immunology. 2016;77(2):201-13.[3]Gosselt HR, Verhoeven MMA, Bulatovic-Calasan M, et al. Complex machine-learning algorithms and multivariable logistic regression on par in the prediction of insufficient clinical response to methotrexate in rheumatoid arthritis. Journal of Personalized Medicine. 2021;11(1).Disclosure of Interests:None declared

scholarly journals High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Weitong Cui ◽  
Huaru Xue ◽  
Lei Wei ◽  
Jinghua Jin ◽  
Xuewen Tian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Small Sample ◽  
Differentially Expressed ◽  
Cancer Type ◽  
Rna Seq ◽  
Sample Sizes ◽  
Large Sample ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract Background RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible. Results Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis. Conclusions High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.

scholarly journals Long Intergenic Non-Coding RNAs in the Mammary Parenchyma and Fat Pad of Pre-Weaning Heifer Calves: Identification and Functional Analysis

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1268
Author(s):  
Shengchao Zhang ◽  
Sibtain Ahmad ◽  
Yuxia Zhang ◽  
Guohua Hua ◽  
Jianming Yi
Keyword(s):  
Mammary Gland ◽  
Crude Protein ◽  
Regulatory Mechanism ◽  
Differentially Expressed ◽  
Milk Replacer ◽  
Rna Seq ◽  
Fat Pad ◽  
Mammary Fat Pad ◽  
Non Coding Rnas ◽  
Gland Development

Enhanced plane of nutrition at pre-weaning stage can promote the development of mammary gland especially heifer calves. Although several genes are involved in this process, long intergenic non-coding RNAs (lincRNAs) are regarded as key regulators in the regulated network and are still largely unknown. We identified and characterized 534 putative lincRNAs based on the published RNA-seq data, including heifer calves in two groups: fed enhanced milk replacer (EH, 1.13 kg/day, including 28% crude protein, 25% fat) group and fed restricted milk replacer (R, 0.45 kg/day, including 20% crude protein, 20% fat) group. Sub-samples from the mammary parenchyma (PAR) and mammary fat pad (MFP) were harvested from heifer calves. According to the information of these lincRNAs’ quantitative trait loci (QTLs), the neighboring and co-expression genes were used to predict their function. By comparing EH vs R, 79 lincRNAs (61 upregulated, 18 downregulated) and 86 lincRNAs (54 upregulated, 32 downregulated) were differentially expressed in MFP and PAR, respectively. In MFP, some differentially expressed lincRNAs (DELs) are involved in lipid metabolism pathways, while, in PAR, among of DELs are involved in cell proliferation pathways. Taken together, this study explored the potential regulatory mechanism of lincRNAs in the mammary gland development of calves under different planes of nutrition.

scholarly journals Transcriptome Analysis of Differentially Expressed mRNA Related to Pigeon Muscle Development

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2311
Author(s):  
Hao Ding ◽  
Yueyue Lin ◽  
Tao Zhang ◽  
Lan Chen ◽  
Genxi Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Differentially Expressed Genes ◽  
Growth And Development ◽  
Muscle Development ◽  
Expression Patterns ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Growth Stages ◽  
Gene Expression And Regulation

The mechanisms behind the gene expression and regulation that modulate the development and growth of pigeon skeletal muscle remain largely unknown. In this study, we performed gene expression analysis on skeletal muscle samples at different developmental and growth stages using RNA sequencing (RNA−Seq). The differentially expressed genes (DEGs) were identified using edgeR software. Weighted gene co−expression network analysis (WGCNA) was used to identify the gene modules related to the growth and development of pigeon skeletal muscle based on DEGs. A total of 11,311 DEGs were identified. WGCNA aggregated 11,311 DEGs into 12 modules. Black and brown modules were significantly correlated with the 1st and 10th day of skeletal muscle growth, while turquoise and cyan modules were significantly correlated with the 8th and 13th days of skeletal muscle embryonic development. Four mRNA−mRNA regulatory networks corresponding to the four significant modules were constructed and visualised using Cytoscape software. Twenty candidate mRNAs were identified based on their connectivity degrees in the networks, including Abca8b, TCONS−00004461, VWF, OGDH, TGIF1, DKK3, Gfpt1 and RFC5, etc. A KEGG pathway enrichment analysis showed that many pathways were related to the growth and development of pigeon skeletal muscle, including PI3K/AKT/mTOR, AMPK, FAK, and thyroid hormone pathways. Five differentially expressed genes (LAST2, MYPN, DKK3, B4GALT6 and OGDH) in the network were selected, and their expression patterns were quantified by qRT−PCR. The results were consistent with our sequencing results. These findings could enhance our understanding of the gene expression and regulation in the development and growth of pigeon muscle.

Sign in / Sign up

Export Citation Format

Share Document