scholarly journals Screening and Identification of Differentially Expressed and Adipose Growth-Related Protein-Coding Genes During the Deposition of Perirenal Adipose Tissue in Rabbits

2020 ◽  
Vol Volume 13 ◽  
pp. 4669-4680
Author(s):  
Guoze Wang ◽  
Kun Du ◽  
Zhenjian Xie ◽  
Renyong Tang ◽  
Xianbo Jia ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Differentially Expressed ◽  
Related Protein ◽  
Protein Coding ◽  
Perirenal Adipose Tissue ◽  
Protein Coding Genes ◽  
Screening And Identification

scholarly journals Genome-wide identification and comparison of differentially expressed profiles of miRNAs and lncRNAs with associated ceRNA networks in the gonads of Chinese soft-shelled turtle, Pelodiscus sinensis

2020 ◽  
Author(s):  
Xiao Ma ◽  
Shuangshuang Cen ◽  
Luming Wang ◽  
Chao Zhang ◽  
Limin Wu ◽  
...  
Keyword(s):  
Messenger Rna ◽  
Target Genes ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Pelodiscus Sinensis ◽  
Specific Expression ◽  
Protein Coding ◽  
Reproductive Regulation ◽  
Protein Coding Genes

Abstract Background: The gonad is the major factor affecting animal reproduction. The regulatory mechanism of the expression of protein-coding genes involved in reproduction still remains to be elucidated. Increasing evidence has shown that ncRNAs play key regulatory roles in gene expression in many life processes. The roles of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in reproduction have been investigated in some species. However, the regulatory patterns of miRNA and lncRNA in the sex biased expression of protein coding genes remains to be elucidated. In this study, we performed an integrated analysis of miRNA, messenger RNA (mRNA), and lncRNA expression profiles to explore their regulatory patterns in the female ovary and male testis of Chinese soft-shelled turtle, Pelodiscus sinensis.Results: We identified 10 446 mature miRNAs, 20 414 mRNAs and 28 500 lncRNAs in the ovaries and testes, and 633 miRNAs, 11 319 mRNAs, and 10 495 lncRNAs showed differential expression. A total of 2 814 target genes were identified for miRNAs. The predicted target genes of these differentially expressed (DE) miRNAs and lncRNAs included abundant genes related to reproductive regulation. Furthermore, we found that 189 DEmiRNAs and 5 408 DElncRNAs showed sex-specific expression. Of these, 3 DEmiRNAs and 917 DElncRNAs were testis-specific, and 186 DEmiRNAs and 4 491 DElncRNAs were ovary-specific. We further constructed complete endogenous lncRNA-miRNA-mRNA networks using bioinformatics, including 103 DEmiRNAs, 636 DEmRNAs, and 1 622 DElncRNAs. The target genes for the differentially expressed miRNAs and lncRNAs included abundant genes involved in gonadal development, including Wt1, Creb3l2, Gata4, Wnt2, Nr5a1, Hsd17, Igf2r, H2afz, Lin52, Trim71, Zar1, and Jazf1.Conclusions: In animals, miRNA and lncRNA as master regulators regulate reproductive processes by controlling the expression of mRNAs. Considering their importance, the identified miRNAs, lncRNAs, and their targets in P. sinensis might be useful for studying the molecular processes involved in sexual reproduction and genome editing to produce higher quality aquaculture animals. A thorough understanding of ncRNA-based cellular regulatory networks will aid in the improvement of P. sinensis reproductive traits for aquaculture.

scholarly journals Transcriptome-wide map of m6A circRNAs identified in a rat model of hypoxia mediated pulmonary hypertension

2020 ◽  
Author(s):  
Hua Su ◽  
Guowen Wang ◽  
Lingfang Wu ◽  
Xiuqing Ma ◽  
Kejing Ying ◽  
...  
Keyword(s):  
Pulmonary Hypertension ◽  
Key Words ◽  
Clinical Significance ◽  
Rat Model ◽  
Physiological Process ◽  
Effective Therapy ◽  
Differentially Expressed ◽  
Protein Coding ◽  
Protein Coding Genes

Abstract Background: Hypoxia mediated pulmonary hypertension (HPH) is a lethal disease and lacks effective therapy. CircRNAs play significant roles in physiological process. Recently, circRNAs are found to be m 6 A-modified. The abundance of circRNAs was influenced by m 6 A. Furthermore, the significance of m 6 A circRNAs has not been elucidated in HPH yet. Here we aim to investigate the transcriptome-wide map of m 6 A circRNAs in HPH. Results: Differentially expressed m 6 A abundance was detected in lungs of HPH rats. M 6 A abundance in circRNAs was significantly reduced in hypoxia in vitro . M 6 A circRNAs were mainly from protein-coding genes spanned single exons in control and HPH groups. Moreover, m 6 A influenced the circRNA–miRNA–mRNA co-expression network in hypoxia. M 6 A circXpo6 and m 6 A circTmtc3 were firstly identified to be downregulated in HPH. Conclusion: Our study firstly identified the transcriptome-wide map of m 6 A circRNAs in HPH. M 6 A can influence circRNA–miRNA–mRNA network. Furthermore, we firstly identified two HPH-associated m 6 A circRNAs: circXpo6 and circTmtc3. However, the clinical significance of m 6 A circRNAs for HPH should be further validated. Key words: m 6 A circRNAs; hypoxia mediated pulmonary hypertension; m 6 A circXpo6; m 6 A circTmtc3

Gene Expression Profile in Responsive and Non-Responsive Chronic Myeloid Leukemia Patients Treated with Dasatinib.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 3260-3260
Author(s):  
Rosana A Silveira ◽  
Angela A Fachel ◽  
Yuri B Moreira ◽  
Marcia T Delamain ◽  
Carmino Antonio De Souza ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Genome ◽  
Mononuclear Cells ◽  
Cytogenetic Response ◽  
Post Treatment ◽  
Differentially Expressed ◽  
Regulation Of Transcription ◽  
Protein Coding ◽  
Altered Expression ◽  
Protein Coding Genes

Abstract Abstract 3260 Poster Board III-1 Background: CML treatment with tyrosine kinase inhibitors induces high and durable rates of complete cytogenetic response. Despite treatment efficacy, a significant proportion of patients develop resistance to these drugs. We measured gene expression profiles in an attempt to identify gene pathways that may be associated with dasatinib resistance. Patients and Methods: Mononuclear cells were separated from peripheral blood samples from seven CML patients resistant to imatinib, collected prior and after dasatinib treatment. Three patients who achieved partial cytogenetic response (Ph-positive cells: 1% - 35%) within twelve months were considered responders (R), whereas four patients who failed to achieve PCyR within 12 months of treatment were classified as non-responders. RNA samples prepared from peripheral mononuclear cells were hybridized to Agilent Technologies 4×44K Whole Human Genome Microarrays (WHGM) and 4×44K intronic-exonic custom oligoarrays. The latter was developed by Verjovski-Almeida's group (Nakaya et al, Genome Biology 2007, 8:R43) and contains sense and antisense probes that map to intronic regions in the human genome representing totally (TIN) and partially (PIN) intronic non-coding RNAs (ncRNAs), in addition to probes for the corresponding protein-coding genes of the same loci. Raw microarray data were normalized by the Affy package in statistical R language implemented in the Bioconductor platform. Each sample was labeled in replicate with Cy3 or Cy5 and the two were considered technical replicates. Two independent statistical approaches SAM (Significance Analysis of Microarrays) and Golub's discrimination score (SNR, Signal to Noise Ratio, with permutations) were performed to identify differentially expressed transcripts between responder and non-responder patients. For the intronic-exonic platform, the analysis parameters were FDR 10%, SNR>1.5 and p<0.01, and for WHGM platform parameters were FDR 5%, SNR>1.5 and p<0.001. For this latter platform, we also performed a patient leave-one-out analysis. Functions of transcripts differentially expressed were annotated and compared using GO Biological Process categories (www.genetools.microarray.ntu.no/egon). Results: We identified 34 ncRNAs with altered expression (26 over and 8 underexpressed in responders) in pre-treatment samples and 33 ncRNAs (20 over and 13 underexpressed in responders) in post-treatment samples. Functions associated with protein-coding genes from the same genomic loci as those of the intronic differentially expressed ncRNAs were: regulation of transcription (PRMT5, SOD2, SSBP3, BCL7A, MLL), signal transduction (PRKCB1, RASGRP2, NF1, PXN) and apoptosis (BCL2, PCSK6, TNFAIP8, EIF4G2). WHGM platform data analysis showed 63 and 250 protein-coding genes differentially expressed in pre and post-treatment samples, respectively. We observed a higher number of protein-coding genes with altered expression after treatment in the following functions: cell communication, immune response and metabolic process (p<0.02). Conclusions: Overall, these findings indicate that protein-coding genes and intronic ncRNAs may be related to dasatinib resistance and response to treatment. In particular, altered expression of ncRNAs transcribed from the introns of ‘regulation of transcription' genes could be part of an important alternative mechanism of gene expression control during emergence of resistance.Support: FAPESP (2005/60266-8) Disclosures: No relevant conflicts of interest to declare.

Long Intergenic Non-Coding RNAs (lincRNA) Impacts Biology and Clinical Outcome in Multiple Myeloma

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 642-642
Author(s):  
Mehmet Kemal Samur ◽  
Naim Rashid ◽  
Alice Cleynen ◽  
Mariateresa Fulciniti ◽  
Adam Sperling ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Regression Model ◽  
Cox Regression ◽  
Differentially Expressed ◽  
P Value ◽  
Relapse Free Survival ◽  
Protein Coding ◽  
Free Survival ◽  
Protein Coding Genes ◽  
Regulatory Functions

Abstract RNA has a diverse sets of regulatory functions besides being a messenger between DNA and protein. Recent analysis of RNA repertoire has identified a large numbers of non-coding transcripts. One of which, long intergenic non-coding RNA (lincRNA) with transcripts longer than 200 nucleotides, are located between the protein coding genes and do not overlap exons of either protein-coding or other non-lincRNA genes. lincRNAs have been considered to provide regulatory functions, however, their precise role in cellular biology remains unclear. Here, we have evaluated the lincRNA profile and their clinical role in MM. We performed RNA-seq on CD138+ MM cells from 320 patients and 18 normal bone marrow plasma cells (NBM) and analyzed for lincRNA. Data from Unstranded 50 bp paired-end RNAseq reads were mapped to the human genome and evaluated for frequency and type of lncRNA. Patient data for MM characteristics, cytogenetic and FISH as well as clinical survival outcomes were also analyzed and correlated with lncRNA data. We compared differentially expressed lincRNAs and protein coding genes in MM versus NBM samples. lincRNA and protein coding genes that have more than 2 reads/million reads for at least 50 samples (~15%) were included in the analysis. We identified 192 significantly expressed lincRNA (adj p value <0.05). We evaluated neighborhood protein coding genes for lincRNA within 500kb up/down stream and identified 298 genes within the region, 134 of these also differentially expressed between MM and NBM. Gene enrichment analysis to recognize possible biological processes that may be affected by lincRNAs and genes enriched by several Gene Ontology(GO) terms identified DNA binding, transcription, cell proliferation, and regulation of lymphocyte function. We applied unsupervised clustering method to the differentially expressed lincRNA that are neighbor of these 134 protein-coding genes. We identified four distinct clusters which are being investigated for correlation with clinical subtypes of MM. Finally we checked correlation between lincRNAs and clinical outcome including response and relapse free survival. We compared differentially expressed lincRNA between patients achieving complete response (CR) versus others and identified 16 lincRNAs with significantly different expression values (p value < 0.05). Using univariate cox regression model, 26 lincRNAs were identified as having significant correlation (cox p value < 0.05) with event-free survival (EFS). Three of these lincRNAs were also related with response prediction suggesting high level of functional and biological importance. We have developed a multivariate cox regression model utilizing these individually significant lincRNAs able to predict relapse free survival (Overall Wald test p value = 6.736e-07). Using a training set of 171 patients, we developed a cox regression multivariate survival model and created a risk score. The high and low risk based on lincRNA was validated using this model in 85 independent patients (log-rank p = 0.04). We are in the process of now integrating the gene expression data with lincRNA data to develop an integrated survival model. In summary, we report the first differential lincRNA expression in MM showing a significant role in disease biology as well as clinical outcome. lincRNAs are still functionally poorly characterized and our ongoing integrative approach will provide a link between lincRNAs and protein coding genes in MM. Disclosures Anderson: Celgene: Consultancy; Sanofi-Aventis: Consultancy; Onyx: Consultancy; Acetylon: Scientific Founder, Scientific Founder Other; Oncoprep: Scientific Founder Other; Gilead Sciences: Consultancy.

Differentially Expressed and Prognostically Significant Lincrnas May Impact Immune System and Tumor Progression in Multiple Myeloma (MM)

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2989-2989 ◽  
Author(s):  
Mehmet K Samur ◽  
Annamaria Gulla ◽  
Alice Cleynen ◽  
Florence Magrangeas ◽  
Stephane Minvielle ◽  
...  
Keyword(s):  
Immune System ◽  
Board Of Directors ◽  
Differentially Expressed ◽  
Support Vector ◽  
Strongly Correlated ◽  
Advisory Committees ◽  
Protein Coding ◽  
Free Survival ◽  
Protein Coding Genes ◽  
Highly Correlated

Abstract Long intergenic non-coding RNA (lincRNA) are transcripts longer than 200 nucleotides which have a diverse sets of regulatory functions but do not get translated into protein. lincRNAs are located between the protein coding genes and do not overlap exons of either protein-coding or other non-lincRNA. However precise role of individual lincRNA in disease biology remains unclear. Here, we have evaluated the lincRNA expression and their potential biological functions in MM. We performed RNA-seq on CD138+ MM cells from 296 newly diagnosed patients and 16 normal bone marrow plasma cells (NBM) and analyzed for lincRNA expression. Data from paired-end RNAseq reads were mapped to the latest human genome, differentially expressed lincRNAs were identified and for each expressed lincRNA event free survival was examined with univariate cox regression model and support vector machine. Finally, we identified protein coding genes that are strongly correlated (cor > 0.5) with lincRNAs with significant altered expression in MM and impact on EFS to identify their biological role. lincRNA and protein coding genes that have more than 10 reads/million reads for at least 15 normal samples or 62 MM samples (20% all MM samples) were included in the analysis. We identified 60 differentially expressed lincRNA (adj p value <0.05), 51 of those had at least 1.5 fold change difference. The differentially expressed lncRNAs were in close proximity of Ig-related genes, genome stability related genes, hosting miRNAs such as mir222 and mir22 and previously reported for other cancers (PVT and TTY15). We evaluated relation of these lincRNAs with event free survival (EFS) and observed 6 lincRNAs associated with shorter EFS. We have developed multivariate signature model to predict EFS by using these 6 lincRNAs. We divided our dataset into training (n=99) and test (n=156) dataset and we utilized support vector machine classification to divide samples into 2 groups using six lincRNAs. This model was able to predict good and poor survival groups in training dataset (p val < 0.001) as well as test dataset (p val = 0.002) (Figure). We examined genome wide correlation between these six differentially expressed and prognostically significant lincRNAs to expressed protein coding genes to identify their biological functions in MM. Four of these lincRNAs strongly correlated with 47 to 504 genes (abs(cor) > 0.5), affecting immune system pathways and pathways in cancer including Jak-STAT signaling pathway. We also found that these lincRNAs are also highly correlated with tumor development genes such as TNFRSF1B,FGR,TP53BP2,TNF and T or B cells related genes PIK3CD, BCL6. In addition, two of these lincRNAs (LINC00936 and CTB-61M7.2) were found highly correlated with their protein coding neighbor genes ATP2B1(cor = 0.45) and FCAR (cor = 0.95) respectively and MIR22HG was host gene for mir22 which may indicate lincRNAs are using different machinery in MM to regulate protein coding genes. In summary, we report that lincRNA is differentially expressed and prognostically significant in myeloma and may function through their impact on immune system and tumor progression. Our ongoing integrative approach will provide further evidence of their regulatory role in MM with potential therapeutic application. Figure 1. Figure 1. Disclosures Anderson: acetylon pharmaceuticals: Equity Ownership; Celgene Corporation: Consultancy; Gilead: Consultancy; Oncocorp: Equity Ownership; Millennium: Consultancy; BMS: Consultancy. Munshi:onyx: Membership on an entity's Board of Directors or advisory committees; celgene: Membership on an entity's Board of Directors or advisory committees; novartis: Membership on an entity's Board of Directors or advisory committees; millenium: Membership on an entity's Board of Directors or advisory committees.

scholarly journals Alternative splicing at NAGNAG acceptors in Arabidopsis thaliana SR and SR-related protein-coding genes

BMC Genomics ◽  
2008 ◽  
Vol 9 (1) ◽  
pp. 159 ◽  
Author(s):  
Stefanie Schindler ◽  
Karol Szafranski ◽  
Michael Hiller ◽  
Gul Ali ◽  
Saiprasad G Palusa ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Alternative Splicing ◽  
Related Protein ◽  
Protein Coding ◽  
Protein Coding Genes

scholarly journals RNA-Seq Implies Divergent Regulation Patterns of LincRNA on Spermatogenesis and Testis Growth in Goats

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 625
Author(s):  
Dongdong Bo ◽  
Xunping Jiang ◽  
Guiqiong Liu ◽  
Ruixue Hu ◽  
Yuqing Chong
Keyword(s):  
Target Genes ◽  
Expression Patterns ◽  
Testicular Development ◽  
Related Protein ◽  
Rna Seq ◽  
Down Regulation ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Regulation Of Growth ◽  
Fresh Insight

Long intergenic non-coding RNAs (lincRNAs) regulate testicular development by acting on protein-coding genes. However, little is known about whether lincRNAs and protein-coding genes exhibit the same expression pattern in the same phase of postnatal testicular development in goats. Therefore, this study aimed to demonstrate the expression patterns and roles of lincRNAs during the postnatal development of the goat testis. Herein, the testes of Yiling goats with average ages of 0, 30, 60, 90, 120, 150, and 180 days postnatal (DP) were used for RNA-seq. In total, 20,269 lincRNAs were identified, including 16,931 novel lincRNAs. We identified seven time-specifically diverse lincRNA modules and six mRNA modules by weighted gene co-expression network analysis (WGCNA). Interestingly, the down-regulation of growth-related lincRNAs was nearly one month earlier than the up-regulation of spermatogenesis-related lincRNAs, while the down-regulation of growth-related protein-coding genes and the correspondent up-regulation of spermatogenesis-related protein-coding genes occurred at the same age. Then, potential lincRNA target genes were predicted. Moreover, the co-expression network of lincRNAs demonstrated that ENSCHIT00000000777, ENSCHIT00000002069, and ENSCHIT00000005076 were the key lincRNAs in the process of testis development. Our study discovered the divergent regulation patterns of lincRNA on spermatogenesis and testis growth, providing a fresh insight into age-biased changes in lincRNA expression in the goat testis.

scholarly journals Comprehensive analysis of differential expression profiles via transcriptome sequencing in SH-SY5Y cells infected with CV-A16

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0241174
Author(s):  
Yajie Hu ◽  
Zhen Yang ◽  
Shenglan Wang ◽  
Danxiong Sun ◽  
Mingmei Zhong ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Transcriptome Sequencing ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Transcriptome Profiling ◽  
Differentially Expressed ◽  
Control Group ◽  
Protein Coding ◽  
Qrt Pcr ◽  
Protein Coding Genes

Coxsackievirus A16 (CV-A16) is one of the viruses that is most frequently associated with hand-foot-and-mouth disease (HFMD). Previous studies have shown that CV-A16 infections are mostly self-limiting, but in recent years, it has been gradually found that CV-A16 infections can also induce neurological complications and eventually cause death in children with HFMD. Moreover, no curative drugs or preventative vaccines have been developed for CV-A16 infection. Therefore, it is particularly important to investigate the mechanism of CV-A16 infection-induced neuropathy. In the current study, transcriptome sequencing technology was used to identify changes in the transcriptome of SH-SY5Y cells infected with CV-A16, which might hide the mechanism of CV-A16-induced neuropathology. The transcriptome profiling showed that 82,406,974, 108,652,260 and 97,753,565 clean reads were obtained in the Control, CV-A16-12 h and CV-A16-24 h groups, respectively. And it was further detected that a total of 136 and 161 differentially expressed genes in CV-A16-12 h and CV-A16-24 h groups, respectively, when compared with Control group. Then, to explore the mechanism of CV-A16 infection, we focused on the common differentially expressed genes at different time points of CV-A16 infection and found that there were 34 differentially expressed genes based on which clustering analysis and functional category enrichment analysis were performed. The results indicated that changes in oxidation levels were particularly evident in the GO term analysis, while only the “Gonadotropin-releasing hormone receptor pathway” was enriched in the KEGG pathway analysis, which might be closely related to the neurotoxicity caused by CV-A16 infection. Meanwhile, the ID2 closely related to nervous system has been demonstrated to be increased during CV-A16 infection. Additionally, the data on differentially expressed non-protein-coding genes of different types within the transcriptome sequencing results were analyzed, and it was speculated that these dysregulated non-protein-coding genes played a pivotal role in CV-A16 infection. Ultimately, qRT-PCR was utilized to validate the transcriptome sequencing findings, and the results of qRT-PCR were in agreement with the transcriptome sequencing data. In conclusion, transcriptome profiling was carried out to analyze response of SH-SY5Y cells to CV-A16 infection. And our findings provide important information to elucidate the possible molecular mechanisms which were linked to the neuropathogenesis of CV-A16 infection.

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