human gene expression
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2022 ◽  
Vol 12 ◽  
Author(s):  
Moldir Myrzabekova ◽  
Siegfried Labeit ◽  
Raigul Niyazova ◽  
Aigul Akimniyazova ◽  
Anatoliy Ivashchenko

Milk and other products from large mammals have emerged during human evolution as an important source of nutrition. Recently, it has been recognized that exogenous miRNAs (mRNA inhibited RNA) contained in milk and other tissues of the mammalian body can enter the human body, which in turn have the ability to potentially regulate human metabolism by affecting gene expression. We studied for exogenous miRNAs from Bos taurus that are potentially contain miRNAs from milk and that could act postprandially as regulators of human gene expression. The interaction of 17,508 human genes with 1025 bta-miRNAs, including 245 raw milk miRNAs was studied. The milk bta-miR-151-5p, bta-miR-151-3p, bta-miRNA-320 each have 11 BSs (binding sites), and bta-miRNA-345-5p, bta-miRNA-614, bta-miRNA-1296b and bta-miRNA-149 has 12, 14, 15 and 26 BSs, respectively. The bta-miR-574-5p from cow’s milk had 209 human genes in mRNAs from one to 25 repeating BSs. We found 15 bta-miRNAs that have 100% complementarity to the mRNA of 13 human target genes. Another 12 miRNAs have BSs in the mRNA of 19 human genes with 98% complementarity. The bta-miR-11975, bta-miR-11976, and bta-miR-2885 BSs are located with the overlap of nucleotide sequences in the mRNA of human genes. Nucleotide sequences of BSs of these miRNAs in 5′UTR mRNA of human genes consisted of GCC repeats with a total length of 18 nucleotides (nt) in 18 genes, 21 nt in 11 genes, 24 nt in 14 genes, and 27–48 nt in nine genes. Nucleotide sequences of BSs of bta-miR-11975, bta-miR-11976, and bta-miR-2885 in CDS mRNA of human genes consisted of GCC repeats with a total length of 18 nt in 33 genes, 21 nt in 13 genes, 24 nt in nine genes, and 27–36 nt in 11 genes. These BSs encoded polyA or polyP peptides. In only one case, the polyR (SLC24A3 gene) was encoded. The possibility of regulating the expression of human genes by exogenous bovine miRNAs is discussed.


2021 ◽  
Author(s):  
Phillip J Dexheimer ◽  
Mario Pujato ◽  
Krishna Roskin ◽  
Matthew T Weirauch

AbstractMotivationHuman viruses cause significant mortality, morbidity, and economic disruption worldwide. The human gene expression response to viral infection can yield important insights into the detrimental effects to the host. To date, hundreds of studies have performed genome-scale profiling of the effect of viral infection on human gene expression. However, no resource exists that aggregates human expression results across multiple studies, viruses, and tissue types.ResultsWe developed the Virus Expression Database (VExD), a comprehensive curated resource of transcriptomic studies of viral infection in human cells. We have processed all studies within VExD in a uniform manner, allowing users to easily compare human gene expression changes across conditions.Availability and ImplementationVExD is freely accessible at https://vexd.cchmc.org for all modern web browsers. An Application Programming Interface (API) for VExD is also available. The source code is available at https://github.com/pdexheimer/[email protected], [email protected]


BMC Biology ◽  
2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Ryuichi Kumata ◽  
Jumpei Ito ◽  
Kenta Takahashi ◽  
Tadaki Suzuki ◽  
Kei Sato

Abstract Background Human-resident microbes can influence both health and disease. Investigating the microbiome using next-generation sequencing technology has revealed examples of mutualism and conflict between microbes and humans. Comparing to bacteria, the viral component of the microbiome (i.e., the “virome”) is understudied. Somatic tissues of healthy individuals are usually inaccessible for the virome sampling; therefore, there is limited understanding of the presence and distribution of viruses in tissues in healthy individuals and how virus infection associates with human gene expression and perturbs immunological homeostasis. Results To characterize the human virome in a tissue-specific manner, here we performed meta-transcriptomic analysis using the RNA-sequencing dataset from the Genotype-Tissue Expression (GTEx) Project. We analyzed the 8991 RNA-sequencing data obtained from 51 somatic tissues from 547 individuals and successfully detected 39 viral species in at least one tissue. We then investigated associations between virus infection and human gene expression and human disease onset. We detected some expected relationships; for instance, hepatitis C virus infection in the liver was strongly associated with interferon-stimulated gene upregulation and pathological findings of chronic hepatitis. The presence of herpes simplex virus type 1 in one subject’s brain strongly associated with immune gene expression. While torque teno virus was detected in a broad range of human tissues, it was not associated with interferon responses. Being notable in light of its association with lymphoproliferative disorders, Epstein-Barr virus infection in the spleen and blood was associated with an increase in plasma cells in healthy subjects. Human herpesvirus 7 was often detected in the stomach; intriguingly, it associated with the proportion of human leukocytes in the stomach as well as digestive gene expression. Moreover, virus infections in the local tissues associated with systemic immune responses in circulating blood. Conclusions To our knowledge, this study is the first comprehensive investigation of the human virome in a variety of tissues in healthy individuals through meta-transcriptomic analysis. Further investigation of the associations described here, and application of this analytical pipeline to additional datasets, will be useful to reveal the impact of viral infections on human health.


2020 ◽  
Author(s):  
Yuzhou Wang ◽  
Yu Zhang ◽  
Jiazhen Gong ◽  
Jianqiang Bao ◽  
Shisong Ma

ABSTRACTTranscription factors (TF) regulate cellular activities via controlling gene expression, but a predictive model describing how TFs quantitatively modulate human transcriptomes was lacking. We constructed a universal human gene expression predictor and utilized it to decode transcriptional regulation. Using 1613 TFs’ expression, the predictor reconstituted highly accurate transcriptomes for samples derived from a wide range of tissues and conditions. The predictor’s broad applicability indicated it had recapitulated the quantitative relationships between TFs and target genes ubiquitous across tissues. Significant interacting TF-target gene pairs were then extracted from the predictor and enabled downstream inference of TF regulators for diverse pathways involved in development, immunity, metabolism, and stress response. Thus, we present a novel approach to study human transcriptional regulation following the “understanding by modeling” principle.


Virus Genes ◽  
2020 ◽  
Vol 56 (3) ◽  
pp. 386-389 ◽  
Author(s):  
Ryuichi Kumata ◽  
Jumpei Ito ◽  
Kei Sato

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