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 Identification of sheep lncRNAs related to the immune response to vaccines and aluminium adjuvants

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Martin Bilbao-Arribas ◽  
Endika Varela-Martínez ◽  
Naiara Abendaño ◽  
Damián de Andrés ◽  
Lluís Luján ◽  
...  
Keyword(s):  
Immune Response ◽  
Expression Analysis ◽  
Expression Patterns ◽  
Differential Expression Analysis ◽  
Rna Seq ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Livestock Species ◽  
Non Coding Rnas ◽  
Aluminium Adjuvant

Abstract Background Long non-coding RNAs (lncRNAs) are involved in several immune processes, including the immune response to vaccination, but most of them remain uncharacterised in livestock species. The mechanism of action of aluminium adjuvants as vaccine components is neither not fully understood. Results We built a transcriptome from sheep PBMCs RNA-seq data in order to identify unannotated lncRNAs and analysed their expression patterns along protein coding genes. We found 2284 novel lncRNAs and assessed their conservation in terms of sequence and synteny. Differential expression analysis performed between animals inoculated with commercial vaccines or aluminium adjuvant alone and the co-expression analysis revealed lncRNAs related to the immune response to vaccines and adjuvants. A group of co-expressed genes enriched in cytokine signalling and production highlighted the differences between different treatments. A number of differentially expressed lncRNAs were correlated with a divergently located protein-coding gene, such as the OSM cytokine. Other lncRNAs were predicted to act as sponges of miRNAs involved in immune response regulation. Conclusions This work enlarges the lncRNA catalogue in sheep and puts an accent on their involvement in the immune response to repetitive vaccination, providing a basis for further characterisation of the non-coding sheep transcriptome within different immune cells.

scholarly journals Comparison of human and mouse tissues with focus on genes with no 1-to-1 homology

2021 ◽  
Author(s):  
Jieun Jeong ◽  
Manolis Kellis
Keyword(s):  
Immune Response ◽  
Target Genes ◽  
Expression Patterns ◽  
Adaptive Immune Response ◽  
Mouse Skin ◽  
Rna Seq ◽  
Therapy Targets ◽  
Mouse Tissues ◽  
Tissues Expression ◽  
Human And Mouse

We assembled a panel of 28 tissue pairs of human and mouse with RNA-Seq data on gene expression. We focused on genes with no 1-to-1 homology, because they pose special challenges. In this way, we identified expression patterns that identify and explain differences between the two species and suggest target genes for therapeutic applications. Here we mention three examples. One pattern is observed by defining the aggregate expression of immunoglobulin genes (which have no homology) as a measure of different levels of an immune response. In Lung, we used this statistic to find genes that have significantly higher expression in low/moderate response, and thus they may be therapy targets: increasing their expression or mimicking their function with medications may help in recovery from inflammation in the lungs. Some of the observed associations are common to human and mouse; other associations involve genes involved in cell-to-cell signaling or in regeneration but were not known to be important in Lung. Second pattern is that in the Small Intestine, mouse expresses much less antimicrobial defensins, while it has much higher expression of enzymes that are found to improve adaptive immune response. Such enzymes may be tested if they improve probiotic supplements that help in gut inflammation and other diseases. Another pattern involves a many-to-many homology group of defensins that did not have a described function. In human tissues, expression of its genes was found only in a study of a disease of hair covered skin, but several of its genes are highly expressed in two tissues of our panel: mouse Skin and to a lesser degree mouse Vagina. This suggests that those genes or their homologs in other species may provide non-antibiotic medications for hair covered skin and other tissues with microbiome that includes fungi.

scholarly journals Alterations of Growth and Focal Adhesion Molecules in Human Breast Cancer Cells Exposed to the Random Positioning Machine

2021 ◽  
Vol 9 ◽  
Author(s):  
Jayashree Sahana ◽  
Thomas J. Corydon ◽  
Markus Wehland ◽  
Marcus Krüger ◽  
Sascha Kopp ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Target Genes ◽  
Interaction Analysis ◽  
Expression Patterns ◽  
Focal Adhesions ◽  
Multicellular Spheroids ◽  
Down Regulation ◽  
Random Positioning Machine ◽  
Mcf 7

In this study, we evaluated changes in focal adhesions (FAs) in two types of breast cancer cell (BCC) lines (differentiated MCF-7 and the triple-negative MDA-MB-231 cell line) exposed to simulated microgravity (s-μg) created by a random positioning machine (RPM) for 24 h. After exposure, the BCC changed their growth behavior and exhibited two phenotypes in RPM samples: one portion of the cells grew as a normal two-dimensional monolayer [adherent (AD) BCC], while the other portion formed three-dimensional (3D) multicellular spheroids (MCS). After 1 h and 30 min (MDA-MB-231) and 1 h 40 min (MCF-7), the MCS adhered completely to the slide flask bottom. After 2 h, MDA-MB-231 MCS cells started to migrate, and after 6 h, a large number of the cells had left the MCS and continued to grow in a scattered pattern, whereas MCF-7 cells were growing as a confluent monolayer after 6 h and 24 h. We investigated the genes associated with the cytoskeleton, the extracellular matrix and FAs. ACTB, TUBB, FN1, FAK1, and PXN gene expression patterns were not significantly changed in MDA-MB-231 cells, but we observed a down-regulation of LAMA3, ITGB1 mRNAs in AD cells and of ITGB1, TLN1 and VCL mRNAs in MDA-MB-231 MCS. RPM-exposed MCF-7 cells revealed a down-regulation in the gene expression of FAK1, PXN, TLN1, VCL and CDH1 in AD cells and PXN, TLN and CDH1 in MCS. An interaction analysis of the examined genes involved in 3D growth and adhesion indicated a central role of fibronectin, vinculin, and E-cadherin. Live cell imaging of eGFP-vinculin in MCF-7 cells confirmed these findings. β-catenin-transfected MCF-7 cells revealed a nuclear expression in 1g and RPM-AD cells. The target genes BCL9, MYC and JUN of the Wnt/β-catenin signaling pathway were differentially expressed in RPM-exposed MCF-7 cells. These findings suggest that vinculin and β-catenin are key mediators of BCC to form MCS during 24 h of RPM-exposure.

scholarly journals Identifying inaccuracies in gene expression estimates from unstranded RNA-seq data

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Mikhail Pomaznoy ◽  
Ashu Sethi ◽  
Jason Greenbaum ◽  
Bjoern Peters
Keyword(s):  
Gene Expression ◽  
Differential Expression Analysis ◽  
Cell Types ◽  
Library Preparation ◽  
Rna Seq ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Machine Learning Model ◽  
Specific Manner ◽  
Library Preparation Protocol

Abstract RNA-seq methods are widely utilized for transcriptomic profiling of biological samples. However, there are known caveats of this technology which can skew the gene expression estimates. Specifically, if the library preparation protocol does not retain RNA strand information then some genes can be erroneously quantitated. Although strand-specific protocols have been established, a significant portion of RNA-seq data is generated in non-strand-specific manner. We used a comprehensive stranded RNA-seq dataset of 15 blood cell types to identify genes for which expression would be erroneously estimated if strand information was not available. We found that about 10% of all genes and 2.5% of protein coding genes have a two-fold or higher difference in estimated expression when strand information of the reads was ignored. We used parameters of read alignments of these genes to construct a machine learning model that can identify which genes in an unstranded dataset might have incorrect expression estimates and which ones do not. We also show that differential expression analysis of genes with biased expression estimates in unstranded read data can be recovered by limiting the reads considered to those which span exonic boundaries. The resulting approach is implemented as a package available at https://github.com/mikpom/uslcount.

scholarly journals Emerging Roles of Estrogen-Regulated Enhancer and Long Non-Coding RNAs

2020 ◽  
Vol 21 (10) ◽  
pp. 3711
Author(s):  
Melina J. Sedano ◽  
Alana L. Harrison ◽  
Mina Zilaie ◽  
Chandrima Das ◽  
Ramesh Choudhari ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Expression Patterns ◽  
Biological Significance ◽  
Rna Seq ◽  
Biological Functions ◽  
Protein Coding ◽  
Rna Molecules ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Non Coding Rnas

Genome-wide RNA sequencing has shown that only a small fraction of the human genome is transcribed into protein-coding mRNAs. While once thought to be “junk” DNA, recent findings indicate that the rest of the genome encodes many types of non-coding RNA molecules with a myriad of functions still being determined. Among the non-coding RNAs, long non-coding RNAs (lncRNA) and enhancer RNAs (eRNA) are found to be most copious. While their exact biological functions and mechanisms of action are currently unknown, technologies such as next-generation RNA sequencing (RNA-seq) and global nuclear run-on sequencing (GRO-seq) have begun deciphering their expression patterns and biological significance. In addition to their identification, it has been shown that the expression of long non-coding RNAs and enhancer RNAs can vary due to spatial, temporal, developmental, or hormonal variations. In this review, we explore newly reported information on estrogen-regulated eRNAs and lncRNAs and their associated biological functions to help outline their markedly prominent roles in estrogen-dependent signaling.

scholarly journals TSEBRA: transcript selector for BRAKER

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Lars Gabriel ◽  
Katharina J. Hoff ◽  
Tomáš Brůna ◽  
Mark Borodovsky ◽  
Mario Stanke
Keyword(s):  
Statistical Models ◽  
Gene Prediction ◽  
Software Tool ◽  
Genome Project ◽  
Rna Seq ◽  
Protein Coding ◽  
Homologous Protein ◽  
Protein Coding Genes ◽  
Overlapping Transcripts ◽  
Eukaryotic Genomes

Abstract Background BRAKER is a suite of automatic pipelines, BRAKER1 and BRAKER2, for the accurate annotation of protein-coding genes in eukaryotic genomes. Each pipeline trains statistical models of protein-coding genes based on provided evidence and, then predicts protein-coding genes in genomic sequences using both the extrinsic evidence and statistical models. For training and prediction, BRAKER1 and BRAKER2 incorporate complementary extrinsic evidence: BRAKER1 uses only RNA-seq data while BRAKER2 uses only a database of cross-species proteins. The BRAKER suite has so far not been able to reliably exceed the accuracy of BRAKER1 and BRAKER2 when incorporating both types of evidence simultaneously. Currently, for a novel genome project where both RNA-seq and protein data are available, the best option is to run both pipelines independently, and to pick one, likely better output. Therefore, one or another type of the extrinsic evidence would remain unexploited. Results We present TSEBRA, a software that selects gene predictions (transcripts) from the sets generated by BRAKER1 and BRAKER2. TSEBRA uses a set of rules to compare scores of overlapping transcripts based on their support by RNA-seq and homologous protein evidence. We show in computational experiments on genomes of 11 species that TSEBRA achieves higher accuracy than either BRAKER1 or BRAKER2 running alone and that TSEBRA compares favorably with the combiner tool EVidenceModeler. Conclusion TSEBRA is an easy-to-use and fast software tool. It can be used in concert with the BRAKER pipeline to generate a gene prediction set supported by both RNA-seq and homologous protein evidence.

scholarly journals Comparative transcriptomic analysis of gonadal development and renewal in the ovoviviparous black rockfish (Sebastes schlegelii)

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jianshuang Li ◽  
Likang Lyu ◽  
Haishen Wen ◽  
Yun Li ◽  
Xiaojie Wang ◽  
...  
Keyword(s):  
Expression Patterns ◽  
Gonadal Development ◽  
Mature Stage ◽  
Reproductive Pattern ◽  
Cell Renewal ◽  
Rna Seq ◽  
Intercellular Interaction ◽  
Down Regulation ◽  
Black Rockfish ◽  
Sebastes Schlegelii

Abstract Background The black rockfish (Sebastes schlegelii) has an ovoviviparous reproductive pattern and long-term sperm storage, resulting in asynchronous gonadal development between the sexes. However, the comprehensive understanding of gonadal development in black rockfish has not yet been achieved. Here, we studied gonadal development and germ cell renewal using histology and RNA-seq. Results In this study, RNA-seq was performed on testes and ovaries to characterize key pathways and genes that are active during development and gamete maturation in black rockfish. Differentially expressed genes (DEGs) were identified and annotated in 4 comparisons (F_III vs. F_IV, F_IV vs. F_V, M_III vs. M_IV and M_IV vs. M_V). Based on analysis of DEGs enriched in the testis, 11 and 14 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were mapped to the M_III vs. M_IV group and the M_IV vs. M_V group, respectively. DEGs in ovarian development were also classified into 10 groups according to their biological functions. The expression patterns of the selected genes determined by qPCR were significantly correlated with the RNA-Seq results, supporting the reliability and accuracy of the RNA-Seq analysis. E2 levels showed down regulation from previtellogenesis to mature stage in female and T level showed down regulation from spermatogenesis to regressed stage in the male. Conclusions The categories “intercellular interaction and cytoskeleton”, “molecule amplification” and “repair in the cell cycle” were revealed to be crucial in testis development and spermatogenesis, as was the biosynthesis of a series of metabolites. Our results provide comprehensive insight into black rockfish gonadal development and provide a basis for further study of reproductive physiology and molecular biology in ovoviviparity teleosts.

scholarly journals Long Noncoding RNA Derived from LncRNA–mRNA Co-expression Networks Modulates the Locust Phase Change

2020 ◽  
Author(s):  
Ting Li ◽  
Bing Chen ◽  
Pengcheng Yang ◽  
Depin Wang ◽  
Baozhen Du ◽  
...  
Keyword(s):  
Phase Change ◽  
Animal Behavior ◽  
Noncoding Rna ◽  
Time Course ◽  
Empirical Studies ◽  
Expression Patterns ◽  
Rna Seq ◽  
Protein Coding ◽  
Migratory Locust ◽  
Functional Annotations

AbstractLong noncoding RNAs (lncRNAs) regulate various biological processes from gene expression to animal behavior. Although protein-coding genes, microRNAs, and neuropeptides play important roles in the regulation of phenotypic plasticity in migratory locust, empirical studies on the function of lncRNAs in the process remain limited. Here, we applied high-throughput RNA-seq to characterize the expression patterns of lncRNAs and mRNAs in the time course of the locust phase change. LncRNAs displayed more rapid response at the early stages of the time-course treatments than mRNA expression. Functional annotations demonstrated that early changed lncRNAs employed different pathways in isolation and crowding processes to cope up with the changes in population density. Finally, two overlapping hub lncRNA loci in the crowding and isolation networks were screened to be functionally verified. Experimental validation indicated that LNC1010057 could act as a potential regulator to modulate the locust phase change. This work offers new insights into the mechanism underlying the locust phase change and expands the scope of lncRNA functions in animal behavior.

scholarly journals Integrated sRNAome and RNA-Seq Analysis Reveals miRNA Effects on Betalain Biosynthesis in Pitaya

2020 ◽  
Author(s):  
Canbin Chen ◽  
Fangfang Xie ◽  
Qingzhu Hua ◽  
Noemi Tel Zur ◽  
Lulu Zhang ◽  
...  
Keyword(s):  
Transient Expression ◽  
Plant Species ◽  
Negative Correlation ◽  
Target Genes ◽  
Regulatory Mechanism ◽  
Expression System ◽  
Expression Patterns ◽  
Rna Seq ◽  
Chlorophyll Accumulation ◽  
Regulatory Functions

Abstract Background: MicroRNAs (miRNAs) and their regulatory functions in anthocyanin, carotenoid, and chlorophyll accumulation have been extensively characterized in many plant species. However, the miRNA regulatory mechanism in betalain biosynthesis remains mostly unknown. Results: In this study, 126 conserved miRNAs and 41 novel miRNAs were first isolated from Hylocereus monacanthus, among which 95 conserved miRNAs belonged to 53 miRNA families. 34 candidate miRNAs related to betalain biosynthesis were found to be differentially expressed. The expression patterns of those differential expressed miRNAs were analyzed in various tissues of the pitaya by RT-qPCR. A significantly negative correlation was detected between the expression levels of half those miRNAs and corresponding target genes. Target genes of miRNAs i.e. aly-miR157d-5p_L+1_1ss4AC-comp25631_c0, aau-miR160_L-4R+ 1-comp36993_c0_seq3, nta-miR6020b-comp234190_c0, PC-5p-192_7269-comp29967_c0, PC-5p-23845_39-comp28219_c0, mdm-miR828a_1ss22AT-comp24967_c0, mdm-miR858- comp15143_c0, mdm-miR858-comp24362_c0 and mdm-miR858-comp403340_c0 were verified by 5′RACE and transient expression system in tobacco.Conclusions: aly-miR157d-5p_L+1_1ss4AC, aau-miR160_L-4R+1, nta-miR6020b PC-5p-192_7269, PC-5p-23845_39, mdm-miR828a_1ss22AT and mdm-miR858 may play important roles in pitaya fruit coloration and betalain accumulation. Our findings provide insights into the roles of miRNAs and their target genes of regulatory functions involved in betalain biosynthesis of pitaya.

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