scholarly journals Gene expression patterns of novel visual and non-visual opsin families in immature and mature Japanese eel males

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8326
Author(s):  
Jun-Hwan Byun ◽  
Ji-Yeon Hyeon ◽  
Eun-Su Kim ◽  
Byeong-Hoon Kim ◽  
Hiroshi Miyanishi ◽  
...  

This study was carried out to identify and estimate physiological function of a new type of opsin subfamily present in the retina and whole brain tissues of Japanese eel using RNA–Seq transcriptome method. A total of 18 opsin subfamilies were identified through RNA–seq. The visual opsin family included Rh2, SWS2, FWO, DSO, and Exo-Rhod. The non-visual opsin family included four types of melanopsin subfamily (Opn4x1, Opn4x2, Opn4m1, and Opn4m2), peropsin, two types of neuropsin subfamily (Opn5-like, Opn5), Opn3, three types of TMT opsin subfamily (TMT1, 2, 3), VA-opsin, and parapinopsin. In terms of changes in photoreceptor gene expression in the retina of sexually mature and immature male eels, DSO mRNA increased in the maturation group. Analysis of expression of opsin family gene in male eel brain before and after maturation revealed that DSO and SWS2 expression in terms of visual opsin mRNA increased in the sexually mature group. In terms of non-visual opsin mRNA, parapinopsin mRNA increased whereas that of TMT2 decreased in the fore-brain of the sexually mature group. The mRNA for parapinopsin increased in the mid-brain of the sexually mature group, whereas those of TMT1 and TMT3 increased in the hind-brain of the sexually mature group. DSO mRNA also increased in the retina after sexual maturation, and DSO and SWS2 mRNA increased in whole brain part, suggesting that DSO and SWS2 are closely related to sexual maturation.


2014 ◽  
Vol 221 (3) ◽  
pp. 429-440 ◽  
Author(s):  
Wenxia He ◽  
Xiangyan Dai ◽  
Xiaowen Chen ◽  
Jiangyan He ◽  
Zhan Yin

Sexual maturation and somatic growth cessation are associated with adolescent development, which is precisely controlled by interconnected neuroendocrine regulatory pathways in the endogenous endocrine system. The pituitary gland is one of the key regulators of the endocrine system. By analyzing the RNA sequencing (RNA-seq) transcriptome before and after sexual maturation, in this study, we characterized the global gene expression patterns in zebrafish pituitaries at 45 and 90 days post-fertilization (dpf). A total of 15 043 annotated genes were expressed in the pituitary tissue, 3072 of which were differentially expressed with a greater than or equal to twofold change between pituitaries at 45 and 90 dpf. In the pituitary transcriptome, the most abundant transcript was gh. The expression levels of gh remained high even after sexual maturation at 90 dpf. Among the eight major pituitary hormone genes, lhb was the only gene that exhibited a significant change in its expression levels between 45 and 90 dpf. Significant changes in the pituitary transcripts included genes involved in the regulation of immune responses, bone metabolism, and hormone secretion processes during the juvenile–sexual maturity transition. Real-time quantitative PCR analysis was carried out to verify the RNA-seq transcriptome results and demonstrated that the expression patterns of the eight major pituitary hormone genes did not exhibit a significant gender difference at 90 dpf. For the first time, we report the quantitative global gene expression patterns at the juvenile and sexual maturity stages. These expression patterns may account for the dynamic neuroendocrine regulation observed in body metabolism.



2020 ◽  
Author(s):  
Hiroto Yamamoto ◽  
Yutaro Uchida ◽  
Tomoki Chiba ◽  
Ryota Kurimoto ◽  
Takahide Matsushima ◽  
...  

AbstractBackgroundsSevoflurane is a most frequently used volatile anaesthetics, but its molecular mechanisms of action remain unclear. We hypothesized that specific genes play regulatory roles in whole brain exposed to sevoflurane. Thus, we aimed to evaluate the effects of sevoflurane inhalation and identify potential regulatory genes by RNA-seq analysis.MethodsEight-week old mice were exposed to sevoflurane. RNA from four medial prefrontal cortex, striatum, hypothalamus, and hippocampus were analysed using RNA-seq. Differently expressed genes were extracted. Their gene ontology terms and the transcriptome array data of the cerebral cortex of sleeping mice were analysed using Metascape, and the gene expression patterns were compared. Finally, the activities of transcription factors were evaluated using a weighted parametric gene set analysis (wPGSA). JASPAR was used to confirm the existence of binding motifs in the upstream sequences of the differently expressed genes.ResultsThe gene ontology term enrichment analysis result suggests that sevoflurane inhalation upregulated angiogenesis and downregulated neural differentiation in the whole brain. The comparison with the brains of sleeping mice showed that the gene expression changes were specific to anaesthetized mice. Sevoflurane induced Klf4 upregulation in the whole brain. The transcriptional analysis result suggests that KLF4 is a potential transcriptional regulator of angiogenesis and neural development.ConclusionsKlf4 was upregulated by sevoflurane inhalation in whole brain. KLF4 might promote angiogenesis and cause the appearance of undifferentiated neural cells by transcriptional regulation. The roles of KLF4 might be key to elucidating the mechanisms of sevoflurane induced functional modification in the brain.



Foods ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 360
Author(s):  
Guodong Rao ◽  
Jianguo Zhang ◽  
Xiaoxia Liu ◽  
Xue Li ◽  
Chenhe Wang

Olive oil has been favored as high-quality edible oil because it contains balanced fatty acids (FAs) and high levels of minor components. The contents of FAs and minor components are variable in olive fruits of different color at harvest time, which render it difficult to determine the optimal harvest strategy for olive oil producing. Here, we combined metabolome, Pacbio Iso-seq, and Illumina RNA-seq transcriptome to investigate the association between metabolites and gene expression of olive fruits at harvest time. A total of 34 FAs, 12 minor components, and 181 other metabolites (including organic acids, polyols, amino acids, and sugars) were identified in this study. Moreover, we proposed optimal olive harvesting strategy models based on different production purposes. In addition, we used the combined Pacbio Iso-seq and Illumina RNA-seq gene expression data to identify genes related to the biosynthetic pathways of hydroxytyrosol and oleuropein. These data lay the foundation for future investigations of olive fruit metabolism and gene expression patterns, and provide a method to obtain olive harvesting strategies for different production purposes.



2020 ◽  
pp. 160-170
Author(s):  
John Vivian ◽  
Jordan M. Eizenga ◽  
Holly C. Beale ◽  
Olena M. Vaske ◽  
Benedict Paten

PURPOSE Many antineoplastics are designed to target upregulated genes, but quantifying upregulation in a single patient sample requires an appropriate set of samples for comparison. In cancer, the most natural comparison set is unaffected samples from the matching tissue, but there are often too few available unaffected samples to overcome high intersample variance. Moreover, some cancer samples have misidentified tissues of origin or even composite-tissue phenotypes. Even if an appropriate comparison set can be identified, most differential expression tools are not designed to accommodate comparisons to a single patient sample. METHODS We propose a Bayesian statistical framework for gene expression outlier detection in single samples. Our method uses all available data to produce a consensus background distribution for each gene of interest without requiring the researcher to manually select a comparison set. The consensus distribution can then be used to quantify over- and underexpression. RESULTS We demonstrate this method on both simulated and real gene expression data. We show that it can robustly quantify overexpression, even when the set of comparison samples lacks ideally matched tissue samples. Furthermore, our results show that the method can identify appropriate comparison sets from samples of mixed lineage and rediscover numerous known gene-cancer expression patterns. CONCLUSION This exploratory method is suitable for identifying expression outliers from comparative RNA sequencing (RNA-seq) analysis for individual samples, and Treehouse, a pediatric precision medicine group that leverages RNA-seq to identify potential therapeutic leads for patients, plans to explore this method for processing its pediatric cohort.



2015 ◽  
Vol 33 (6) ◽  
pp. 1634-1649 ◽  
Author(s):  
Ho-Youn Kim ◽  
Prasenjit Saha ◽  
Macarena Farcuh ◽  
Bosheng Li ◽  
Avi Sadka ◽  
...  


2018 ◽  
Vol 50 (3) ◽  
pp. 144-157 ◽  
Author(s):  
Katherine Chen ◽  
Alice Jih ◽  
Olivia Osborn ◽  
Sarah T. Kavaler ◽  
Wenxian Fu ◽  
...  

Highly inbred C57BL/6 mice show wide variation in their degree of insulin resistance in response to diet-induced obesity even though they are almost genetically identical. Here we employed transcriptional profiling by RNA sequencing (RNA-Seq) of visceral adipose tissue (VAT) and liver in young mice to determine how gene expression patterns correlate with the later development of high-fat diet (HFD)-induced insulin resistance in adulthood. To accomplish this goal, we partially removed and banked tissues from pubertal mice. Mice subsequently received HFD followed by metabolic phenotyping to identify two well-defined groups of mice with either severe or mild insulin resistance. The remaining tissues were collected at study termination. We then applied RNA-Seq to generate transcriptome profiles associated with worsened insulin resistance before and after the initiation of HFD. We found 244 up- and 109 downregulated genes in VAT of the most insulin-resistant mice even before HFD exposure. Downregulated genes included serine protease inhibitor, major urinary protein, and complement genes; upregulated genes represented mostly muscle constituents. These gene families were also differentially expressed in VAT of mice with high or low insulin resistance after HFD. Inflammatory genes predicted insulin resistance in liver, but not in VAT. In contrast, when we compared VAT of all mice before and after HFD, differentially expressed genes were predominantly composed of immune response genes. These data show a distinct set of gene transcripts in young mice correlates with the severity of insulin resistance in adulthood, providing insight into the pathogenesis of insulin resistance in early life.



2015 ◽  
Author(s):  
Carl J Schmdt ◽  
Elizabeth M Pritchett ◽  
Liang Sun ◽  
Richard V.N. Davis ◽  
Allen Hubbard ◽  
...  

Transcriptome analysis by RNA-seq has emerged as a high-throughput, cost-effective means to evaluate the expression pattern of genes in organisms. Unlike other methods, such as microarrays or quantitative PCR, RNA-seq is a target free method that permits analysis of essentially any RNA that can be amplified from a cell or tissue. At its most basic, RNA-seq can determine individual gene expression levels by counting the number of times a particular transcript was found in the sequence data. Transcript levels can be compared across multiple samples to identify differentially expressed genes and infer differences in biological states between the samples. We have used this approach to examine gene expression patterns in chicken and human cells, with particular interest in determining response to heat stress.



2021 ◽  
Author(s):  
Jakub Jankowski ◽  
Hye Kyung Lee ◽  
Julia Wilflingseder ◽  
Lothar Hennighausen

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.



Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2404-2404
Author(s):  
Shouguo Gao ◽  
Zhijie Wu ◽  
Carrie Diamond ◽  
Bradley Arnold ◽  
Valentina Giudice ◽  
...  

Abstract Introduction . T-cell large granular lymphocytosis (T-LGL) is a low grade lymphoproliferative disorder, often clinically manifest as bone marrow failure. Treatment with immunosuppressive therapies is effective, but the dominant clone may persist even in responding patients. The pathogenesis of T-LGL has not been fully elucidated. In this study, we performed single cell RNA sequencing (sc-RNA seq) and V(D)J profiling to discern clonotypes and gene expression patterns of T lymphocytes from T-LGL patients who were sampled before and after treatment. Methods. Blood was obtained from patients participating in a phase 2 protocol of alemtuzumab as second line therapy (NCT00345345; Dumitriu B et al, Lancet Haematol 2016). Leukapheresis was performed in 13 patients (M/F 7/6; median age 51 years, range 26-85) before and after 3-6 months alemtuzumab administration and in 7 age-matched healthy donors. Cryopreserved blood was enriched for T cells with the EasySep Human T cell Isolation Kit (Stem cell). sc-RNA seq was performed on the 10XGenomics Chromium Single Cell V(D)J + 5' Gene Expression platform, and sequencing obtained on the HiSeq3000 Platform. Barcode assignment, alignment, unique molecular index counting and T cell receptor sequence assembly were performed using Cell Ranger 2.1.1. Results. Four hundred fifty thousand cells from 13 patients and 107,000 cells from 7 healthy donors were profiled. We measured productive TCR chains (which fully span the V and J regions, with a recognizable start codon in the V region and lacking a stop codon in the V-J region, thus potentially generating a protein). We detected at least one productive TCR α-chain in 50%, one productive TCR β-chain in 69% and paired productive αβ-chains in 47% of all cells. There was loss of TCR repertoire diversity in patients which was quantified by Simpson's diversity index; most patients showed oligoclonal or, less frequently, monoclonal expansion of the TCR repertoire (Fig. A). Regardless of clinical response, alemtuzumab treatment did not correct the low TCR repertoire diversity. TCR repertoires can be classified as "public", when they express identical TCR sequences across multiple individuals, or "private", when each individual displays distinct TCR clonotypes. No TCRA or TCRB CDR3 homology among patients was observed: most TCR clonotypes appeared to be private. Our data suggests that T-LGL is etiologically heterogenous disease, consistent with T cell expansion in response to a variety antigens, in diverse HLA contexts, or randomly. Despite differences of TCR among patients and healthy donors, and the presence of large clones in patients, distribution of TCR diversity followed the power law distribution in healthy donors and patients (Fig. B, showing the negative linear relationship between logarithmic expression of clone frequency and clone size). The observed distribution is consistent with a somatic evolution model, in which cell fitness depends on cellular receptor response to specific antigens and stimulation of cells by cytokine and other signals from the environment; fitted clones have higher birth-death ratios and thus expand (Desponds J et al, PNAS 2016). CD4 and CD8 T cells can be virtually separated by imputation from their transcriptomes (Fig. C). Comparison of gene expression between patients and healthy donors showed dysregulation of genes involved in pathways related to the immune response and cell apoptosis, consistent with a pathophysiology of T cell clonal expansion. We used diffusion mapping, which localizes datapoints to their eigen components in low-dimesional space, to characterize sources contributing to the gene expression phenotype: the first component was mainly from T cell activation and the second was associated with TCR expression. In LGL the T cell transcriptome appeared to be shaped by both lineage development and TCR rearrangement. Conclusion. We describe at the single cell level T clonal expansion profiles in T-LGL, pre- and post-treatment. Single cell analysis allows accurate recovery of paired α and β chains in the same cell and demonstrates a continuum of cell lineage differentiation. We found a range of differences in transcriptome and TCR repertoires across patients. Transcriptome data, coupled with detailed TCR-based lineage information, provides a rich resource for understanding of the pathology of T-LGL and has implications for prognosis, treatment, and monitoring in the clinic. Figure. Figure. Disclosures Young: GlaxoSmithKline: Research Funding; CRADA with Novartis: Research Funding; National Institute of Health: Research Funding.



2017 ◽  
Author(s):  
John M Bryan ◽  
Temesgen D Fufa ◽  
Kapil Bharti ◽  
Brian P Brooks ◽  
Robert B Hufnagel ◽  
...  

AbstractThe human eye is built from several specialized tissues which direct, capture, and pre-process information to provide vision. The gene expression of the different eye tissues has been extensively profiled with RNA-seq across numerous studies. Large consortium projects have also used RNA-seq to study gene expression patterning across many different human tissues, minus the eye. There has not been an integrated study of expression patterns from multiple eye tissues compared to other human body tissues. We have collated all publicly available healthy human eye RNA-seq datasets as well as dozens of other tissues. We use this fully integrated dataset to probe the biological processes and pan expression relationships between the cornea, retina, RPE-choroid complex, and the rest of the human tissues with differential expression, clustering, and GO term enrichment tools. We also leverage our large collection of retina and RPE-choroid tissues to build the first human weighted gene correlation networks and use them to highlight known biological pathways and eye gene disease enrichment. We also have integrated publicly available single cell RNA-seq data from mouse retina into our framework for validation and discovery. Finally, we make all these data, analyses, and visualizations available via a powerful interactive web application (https://eyeintegration.nei.nih.gov/).



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