Transcriptome profiling of muscle by RNA-Seq reveals significant differences in digital gene expression profiling between Angus and Luxi cattle

2015 ◽  
Vol 55 (9) ◽  
pp. 1172 ◽  
Author(s):  
G. F. Liu ◽  
H. J. Cheng ◽  
W. You ◽  
E. L. Song ◽  
X. M. Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Beef Cattle ◽  
Growth And Development ◽  
Massively Parallel Sequencing ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Digital Gene Expression ◽  
Transcriptome Profiling ◽  
Rna Seq ◽  
Angus Cattle

The development of massively parallel sequencing technologies enables the sequencing of total cDNA to identify unigene expression and to discover novel regions of transcription. Here, we report the first use of RNA sequencing (RNA-Seq) to find the digital gene expression profiles (DGEs) associated with the growth and development of muscle in Chinese Luxi and Angus beef cattle. More than 9 243 921 clean reads were found in samples of muscle tissue. We found 232 DGEs between Luxi cattle and Angus cattle (false discovery ratio ≤0.001 and |log2 ratio| ≥1). Among the DGEs, we determined that 147 genes were downregulated and 85 genes were upregulated. Gene Ontology and KEGG Pathway analyses were performed to analyse the biological role of the DGEs and determine their contribution to the differences seen in muscle growth and development between local Chinese Luxi cattle and the introduced Angus cattle. The results suggest that RNA-Seq is a useful tool for predicting differences in gene expression between Luxi and Angus beef cattle; moreover, our results provides unprecedented resolution of mRNAs that are expressed across the two breeds.

scholarly journals A tensor decomposition-based integrated analysis applicable to multiple gene expression profiles without sample matching

2021 ◽  
Author(s):  
Taguchi Y-h. ◽  
Turki Turki
Keyword(s):  
Gene Expression ◽  
Learning Strategies ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Tensor Decomposition ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Prior Learning ◽  
Multiple Gene ◽  
Machine Learning Applications

Abstract The integrated analysis of multiple gene expression profiles measured in distinct studies is always problematic. Especially, missing sample matching and missing common labeling between distinct studies prevent the integration of multiple studies in fully data-driven and unsupervised manner. In this study, we propose a strategy enabling the integration of multiple gene expression profiles among multiple independent studies without either labeling or sample matching, using tensor decomposition-based unsupervised feature extraction. As an example, we applied this strategy to Alzheimer’s disease (AD)-related gene expression profiles that lack exact correspondence among samples as well as AD single-cell RNA-seq (scRNA-seq) data. We found that we could select biologically reasonable genes with integrated analysis. Overall, integrated gene expression profiles can function analogously to prior learning and/or transfer learning strategies in other machine learning applications. For scRNA-seq, the proposed approach was able to drastically reduce the required computational memory.

scholarly journals High resolution spatial transcriptome analysis by photo-isolation chemistry

2020 ◽  
Author(s):  
Mizuki Honda ◽  
Shinya Oki ◽  
Akihito Harada ◽  
Kazumitsu Maehara ◽  
Kaori Tanaka ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptome Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Transcriptome Profiling ◽  
Tissue Sections ◽  
Complex Functions ◽  
Multicellular Organisms

ABSTRACTIn multicellular organisms, individual cells are characterized by their gene expression profiles and the spatial interactions among cells enable the elaboration of complex functions. Expression profiling in spatially defined regions is crucial to elucidate cell interactions and functions. Here, we established a transcriptome profiling method coupled with photo-isolation chemistry (PIC) that allows the determination of expression profiles specifically from photo-irradiated regions of whole tissues. PIC uses photo-caged oligodeoxynucleotides for in situ reverse transcription. After photo-irradiation of limited areas, gene expression was detected from at least 10 cells in the tissue sections. PIC transcriptome analysis detected genes specifically expressed in small distinct areas of the mouse embryo. Thus, PIC enables transcriptome profiles to be determined from limited regions at a spatial resolution up to the diffraction limit.

The characteristics of mesenteric adipose tissue attached to different intestinal segments and their roles in immune regulation

2022 ◽  
Author(s):  
Haowei Zhang ◽  
Yujin Ding ◽  
Qin Zeng ◽  
Dandan Wang ◽  
Ganglei Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Adipose Tissue ◽  
Immune Regulation ◽  
Expression Profiles ◽  
Critical Role ◽  
Gene Expression Profiles ◽  
Rna Seq ◽  
Mesenteric Adipose Tissue ◽  
Cell Components ◽  
Subsequent Effect

Background: Mesenteric adipose tissue (MAT) plays a critical role in the intestinal physiological ecosystems. Small and large intestines have evidently intrinsic and distinct characteristics. However, whether there exist any mesenteric differences adjacent to the small and large intestines (SMAT and LMAT) has not been properly characterized. We studied the important facets of these differences, such as morphology, gene expression, cell components and immune regulation of MATs, to characterize the mesenteric differences. Methods: The SMAT and LMAT of mice were utilized for comparison of tissue morphology. Paired mesenteric samples were analyzed by RNA-seq to clarify gene expression profiles. MAT partial excision models were constructed to illustrate the immune regulation roles of MATs, and 16S-seq was applied to detect the subsequent effect on microbiota. Results: Our data show that different segments of mesenteries have different morphological structures. SMAT not only has smaller adipocytes but also contains more fat-associated lymphoid clusters than LMAT. The gene expression profile is also discrepant between these two MATs in mice. B-cell markers were abundantly expressed in SMAT, while development-related genes were highly expressed in LMAT. Adipose-derived stem cells of LMAT exhibited higher adipogenic potential and lower proliferation rates than those of SMAT. In addition, SMAT and LMAT play different roles in immune regulation and subsequently affect microbiota components. Finally, our data clarified the described differences between SMAT and LMAT in humans. Conclusions: There were significant differences in cell morphology, gene expression profiles, cell components, biological characteristics, and immune and microbiota regulation roles between regional MATs.

scholarly journals The Significance of Digital Gene Expression Profiles

1997 ◽  
Vol 7 (10) ◽  
pp. 986-995 ◽  
Author(s):  
Stéphane Audic ◽  
Jean-Michel Claverie
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Digital Gene Expression

scholarly journals Comparative Transcriptome Analysis of Different Dendrobium Species Reveals Active Ingredients-Related Genes and Pathways

2020 ◽  
Vol 21 (3) ◽  
pp. 861 ◽  
Author(s):  
Yingdan Yuan ◽  
Bo Zhang ◽  
Xinggang Tang ◽  
Jinchi Zhang ◽  
Jie Lin
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Rna Seq ◽  
Active Ingredients ◽  
Hub Genes ◽  
Transcriptome Database ◽  
Gene Modules ◽  
Functional Investigation ◽  
First Time

Dendrobium is widely used in traditional Chinese medicine, which contains many kinds of active ingredients. In recent years, many Dendrobium transcriptomes have been sequenced. Hence, weighted gene co-expression network analysis (WGCNA) was used with the gene expression profiles of active ingredients to identify the modules and genes that may associate with particular species and tissues. Three kinds of Dendrobium species and three tissues were sampled for RNA-seq to generate a high-quality, full-length transcriptome database. Based on significant changes in gene expression, we constructed co-expression networks and revealed 19 gene modules. Among them, four modules with properties correlating to active ingredients regulation and biosynthesis, and several hub genes were selected for further functional investigation. This is the first time the WGCNA method has been used to analyze Dendrobium transcriptome data. Further excavation of the gene module information will help us to further study the role and significance of key genes, key signaling pathways, and regulatory mechanisms between genes on the occurrence and development of medicinal components of Dendrobium.

scholarly journals Interferon-regulated genetic programs and JAK/STAT pathway activate the intronic promoter of the short ACE2 isoform in renal proximal tubules

2021 ◽  
Author(s):  
Jakub Jankowski ◽  
Hye Kyung Lee ◽  
Julia Wilflingseder ◽  
Lothar Hennighausen
Keyword(s):  
Gene Expression ◽  
Proximal Tubule ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Regulatory Elements ◽  
Rna Seq ◽  
Angiotensin Converting Enzyme 2 ◽  
Genome Wide ◽  
Cytokine Stimulation

SummaryRecently, a short, interferon-inducible isoform of Angiotensin-Converting Enzyme 2 (ACE2), dACE2 was identified. ACE2 is a SARS-Cov-2 receptor and changes in its renal expression have been linked to several human nephropathies. These changes were never analyzed in context of dACE2, as its expression was not investigated in the kidney. We used Human Primary Proximal Tubule (HPPT) cells to show genome-wide gene expression patterns after cytokine stimulation, with emphasis on the ACE2/dACE2 locus. Putative regulatory elements controlling dACE2 expression were identified using ChIP-seq and RNA-seq. qRT-PCR differentiating between ACE2 and dACE2 revealed 300- and 600-fold upregulation of dACE2 by IFNα and IFNβ, respectively, while full length ACE2 expression was almost unchanged. JAK inhibitor ruxolitinib ablated STAT1 and dACE2 expression after interferon treatment. Finally, with RNA-seq, we identified a set of genes, largely immune-related, induced by cytokine treatment. These gene expression profiles provide new insights into cytokine response of proximal tubule cells.

scholarly journals De novo characterization of the Lycium ruthenicum transcriptome and analysis of its digital gene expression profiles during fruit development and ripening

2017 ◽  
Vol 69 (1) ◽  
pp. 181-190 ◽  
Author(s):  
Yong Peng ◽  
Huiqin Ma ◽  
Shangwu Chen
Keyword(s):  
Gene Expression ◽  
Developmental Stages ◽  
De Novo ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Digital Gene Expression ◽  
Orthologous Group ◽  
Functional Studies ◽  
Lycium Ruthenicum

Lycium ruthenicum Murr., which belongs to the family Solanaceae, is a resource plant for Chinese traditional medicine and nutraceutical foods. In this study, RNA sequencing was applied to obtain raw reads of L. ruthenicum fruit at different stages of ripening, and a de novo assembly of its sequence was performed. Approximately 52.45 million 100-bp paired-end raw reads were generated from the samples by deep RNA-seq analysis. These short reads were assembled to obtain 164814 contigs, and the contigs were assembled into 84968 non-redundant unigenes using the Trinity method. Assembled sequences were annotated with gene descriptions, gene ontology, clusters of orthologous group and KEGG (Kyoto Encyclopedia of Genes and Genomes)pathway terms. Digital gene expression analysis was applied to compare gene-expression patterns at different fruit developmental stages. These results contribute to existing sequence resources for Lycium spp. during the fruit-ripening stages, which is valuable for further functional studies of genes involved in L. ruthenicum fruit nutraceutical quality.

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