Regulatory Genes in the Ancestral Chordate Genomes
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Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
Transcription Factors SOHLH1 and SOHLH2 Coordinate Oocyte Differentiation Without Affecting Meiosis I
Transcription factors SOHLH1 and SOHLH2 coordinate oocyte differentiation without affecting meiosis I Yong-Hyun Shin, … , Vasil Mico, Aleksandar Rajkovic J Clin Invest. 2017;127(6):2106-2117. https://doi.org/10.1172/JCI90281. Research Article Development Reproductive biology Following migration of primordial germ cells to the genital ridge, oogonia undergo several rounds of mitotic division and enter meiosis at approximately E13.5. Most oocytes arrest in the dictyate (diplotene) stage of meiosis circa E18.5. The genes necessary to drive oocyte differentiation in parallel with meiosis are unknown. Here, we have investigated whether expression of spermatogenesis and oogenesis bHLH transcription factor 1 (Sohlh1) and Sohlh2 coordinates oocyte differentiation within the embryonic ovary. We found that SOHLH2 protein was expressed in the mouse germline as early as E12.5 and preceded SOHLH1 protein expression, which occurred circa E15.5. SOHLH1 protein appearance at E15.5 correlated with SOHLH2 translocation from the cytoplasm into the nucleus and was dependent on SOHLH1 expression. NOBOX oogenesis homeobox (NOBOX) and LIM homeobox protein 8 (LHX8), two important regulators of postnatal oogenesis, were coexpressed with SOHLH1. Single deficiency of Sohlh1 or Sohlh2 disrupted the expression of LHX8 and NOBOX in the embryonic gonad without affecting meiosis. Sohlh1-KO infertility was rescued by conditional expression of the Sohlh1 transgene after the onset of meiosis. However, Sohlh1 or Sohlh2 transgene expression could not rescue Sohlh2-KO infertility due to a lack of Sohlh1 or Sohlh2 expression in rescued mice. Our results indicate that Sohlh1 and Sohlh2 are essential regulators of oocyte differentiation but do not affect meiosis I. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Concomitant DNA Methylation and Transcriptome Signatures Define
www.nature.com/scientificreports OPEN Concomitant DNA methylation and transcriptome signatures defne epidermal responses to acute solar UV radiation Nicholas Holzscheck 1,2*, Jörn Söhle 1, Torsten Schläger1, Cassandra Falckenhayn 1, Elke Grönniger 1, Ludger Kolbe 1, Horst Wenck 1, Lara Terstegen1, Lars Kaderali 2, Marc Winnefeld 1 & Katharina Gorges1* The simultaneous analysis of diferent regulatory levels of biological phenomena by means of multi-omics data integration has proven an invaluable tool in modern precision medicine, yet many processes ultimately paving the way towards disease manifestation remain elusive and have not been studied in this regard. Here we investigated the early molecular events following repetitive UV irradiation of in vivo healthy human skin in depth on transcriptomic and epigenetic level. Our results provide frst hints towards an immediate acquisition of epigenetic memories related to aging and cancer and demonstrate signifcantly correlated epigenetic and transcriptomic responses to irradiation stress. The data allowed the precise prediction of inter-individual UV sensitivity, and molecular subtyping on the integrated post-irradiation multi-omics data established the existence of three latent molecular phototypes. Importantly, further analysis suggested a form of melanin-independent DNA damage protection in subjects with higher innate UV resilience. This work establishes a high- resolution molecular landscape of the acute epidermal UV response and demonstrates the potential of integrative analyses to untangle complex and heterogeneous biological responses. Solar UV irradiation has complex and ambivalent efects on the human organism. Benefcial efects of sun expo- sure are thought to be mainly mediated by vitamin D, which is synthesized in the skin through a photosynthetic reaction triggered by exposure to UVB. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Transcriptome Analysis of Human Diabetic Kidney Disease
ORIGINAL ARTICLE Transcriptome Analysis of Human Diabetic Kidney Disease Karolina I. Woroniecka,1 Ae Seo Deok Park,1 Davoud Mohtat,2 David B. Thomas,3 James M. Pullman,4 and Katalin Susztak1,5 OBJECTIVE—Diabetic kidney disease (DKD) is the single cases, mild and then moderate mesangial expansion can be leading cause of kidney failure in the U.S., for which a cure has observed. In general, diabetic kidney disease (DKD) is not yet been found. The aim of our study was to provide an considered a nonimmune-mediated degenerative disease unbiased catalog of gene-expression changes in human diabetic of the glomerulus; however, it has long been noted that kidney biopsy samples. complement and immunoglobulins sometimes can be de- — tected in diseased glomeruli, although their role and sig- RESEARCH DESIGN AND METHODS Affymetrix expression fi arrays were used to identify differentially regulated transcripts in ni cance is not clear (4). 44 microdissected human kidney samples. The DKD samples were The understanding of DKD has been challenged by multi- significant for their racial diversity and decreased glomerular ple issues. First, the diagnosis of DKD usually is made using filtration rate (~20–30 mL/min). Stringent statistical analysis, using clinical criteria, and kidney biopsy often is not performed. the Benjamini-Hochberg corrected two-tailed t test, was used to According to current clinical practice, the development of identify differentially expressed transcripts in control and diseased albuminuria in patients with diabetes is sufficient to make the glomeruli and tubuli. Two different Web-based algorithms were fi diagnosis of DKD (5). We do not understand the correlation used to de ne differentially regulated pathways. -
The Genetics of Non-Syndromic Primary Ovarian Insufficiency: a Systematic Review
Systematic Review The Genetics of Non-Syndromic Primary Ovarian Insufficiency: A Systematic Review Roberta Venturella, M.D.1, Valentino De Vivo, M.D.2, Annunziata Carlea, M.D.2, Pietro D’Alessandro, M.D.2, Gabriele Saccone, M.D.2*, Bruno Arduino, M.D.2, Francesco Paolo Improda, M.D.2, Daniela Lico, M.D.1, Erika Rania, M.D.1, Carmela De Marco, M.D.3, Giuseppe Viglietto, M.D.3, Fulvio Zullo, M.D.1 1. Department of Obstetrics and Gynaecology, Magna Graecia University of Catanzaro, Catanzaro, Italy 2. Department of Neuroscience, Reproductive Sciences and Dentistry, School of Medicine, University of Naples Federico II, Naples, Italy 3. Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy Abstract Several causes for primary ovarian insufficiency (POI) have been described, including iatrogenic and environmental factor, viral infections, chronic disease as well as genetic alterations. The aim of this review was to collect all the ge- netic mutations associated with non-syndromic POI. All studies, including gene screening, genome-wide study and as- sessing genetic mutations associated with POI, were included and analyzed in this systematic review. Syndromic POI and chromosomal abnormalities were not evaluated. Single gene perturbations, including genes on the X chromosome (such as BMP15, PGRMC1 and FMR1) and genes on autosomal chromosomes (such as GDF9, FIGLA, NOBOX, ESR1, FSHR and NANOS3) have a positive correlation with non-syndromic POI. Future strategies include linkage analysis of families with multiple affected members, array comparative genomic hybridization (CGH) for analysis of copy number variations, next generation sequencing technology and genome-wide data analysis. -
Bioinformatic Analyses of Zinc-Activated Transcription Factor
BIOINFORMATIC ANALYSES OF ZINC-ACTIVATED TRANSCRIPTION FACTOR BINDING SITES by MICHAEL FRANCIS (Under the Direction of Arthur Grider) ABSTRACT In humans, the zinc (Zn)-activated transcription factors (TFs) metal response element- binding transcription factor 1 (MTF-1) and ZNF658 regulate gene expression by binding to their associated DNA motifs, the metal regulatory element (MRE) and the zinc transcriptional regulatory element (ZTRE), respectively, upon activation by cellular Zn. Genome-wide bioinformatic analyses were performed to better understand how these motifs may affect TF binding. The effects of the number of MREs and their distance from transcriptional start sites (TSSs) were examined in a secondary analysis of gene expression. MTF-1 is also predicted to form complex regulatory networks with miRNAs via the MRE in the promoters of miRNAs and their target genes. ZNF658 may be responsible for a global Zn deficiency response by binding selectively to ZTRE permutations that occur closer to transcriptional start sites (ex: ZTRE-E) versus others (ex: ZTRE-A) under varied Zn concentrations. INDEX WORDS: Metal response element-binding transcription factor 1 (MTF-1), ZNF658, zinc, microRNAs (miRNAs), transcriptional regulation, nutrigenomics, bioinformatics BIOINFORMATIC ANALYSES OF ZINC-ACTIVATED TRANSCRIPTION FACTOR BINDING SITES by MICHAEL FRANCIS B.S., State University of New York College of Environmental Science and Forestry, 2014 A Thesis Submitted to the Graduate Faculty of The University of Georgia in Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE ATHENS, GEORGIA 2019 © 2019 Michael Francis All Rights Reserved BIOINFORMATIC ANALYSES OF ZINC-ACTIVATED TRANSCRIPTION FACTOR BINDING SITES by MICHAEL FRANCIS Major Professor: Arthur Grider Committee: Hea Jin Park Robert Pazdro Electronic Version Approved: Suzanne Barbour Dean of the Graduate School The University of Georgia August 2019 DEDICATION To Dolores Inserra, who believed in me, and to Stephen Marotta, an American patriot, and to Barclay Powers. -
Engineered Type 1 Regulatory T Cells Designed for Clinical Use Kill Primary
ARTICLE Acute Myeloid Leukemia Engineered type 1 regulatory T cells designed Ferrata Storti Foundation for clinical use kill primary pediatric acute myeloid leukemia cells Brandon Cieniewicz,1* Molly Javier Uyeda,1,2* Ping (Pauline) Chen,1 Ece Canan Sayitoglu,1 Jeffrey Mao-Hwa Liu,1 Grazia Andolfi,3 Katharine Greenthal,1 Alice Bertaina,1,4 Silvia Gregori,3 Rosa Bacchetta,1,4 Norman James Lacayo,1 Alma-Martina Cepika1,4# and Maria Grazia Roncarolo1,2,4# Haematologica 2021 Volume 106(10):2588-2597 1Department of Pediatrics, Division of Stem Cell Transplantation and Regenerative Medicine, Stanford School of Medicine, Stanford, CA, USA; 2Stanford Institute for Stem Cell Biology and Regenerative Medicine, Stanford School of Medicine, Stanford, CA, USA; 3San Raffaele Telethon Institute for Gene Therapy, Milan, Italy and 4Center for Definitive and Curative Medicine, Stanford School of Medicine, Stanford, CA, USA *BC and MJU contributed equally as co-first authors #AMC and MGR contributed equally as co-senior authors ABSTRACT ype 1 regulatory (Tr1) T cells induced by enforced expression of interleukin-10 (LV-10) are being developed as a novel treatment for Tchemotherapy-resistant myeloid leukemias. In vivo, LV-10 cells do not cause graft-versus-host disease while mediating graft-versus-leukemia effect against adult acute myeloid leukemia (AML). Since pediatric AML (pAML) and adult AML are different on a genetic and epigenetic level, we investigate herein whether LV-10 cells also efficiently kill pAML cells. We show that the majority of primary pAML are killed by LV-10 cells, with different levels of sensitivity to killing. Transcriptionally, pAML sensitive to LV-10 killing expressed a myeloid maturation signature. -
NOBOX (D-3): Sc-390016
SANTA CRUZ BIOTECHNOLOGY, INC. NOBOX (D-3): sc-390016 BACKGROUND APPLICATIONS Early ovarian folliculogenesis is characterized by the breakdown of germ cell NOBOX (D-3) is recommended for detection of NOBOX of mouse, rat and clusters and formation of primordial follicles. The cessation of ovarian function human origin by Western Blotting (starting dilution 1:100, dilution range under the age of 40 years results in premature ovarian failure (POF) and is 1:100-1:1000), immunoprecipitation [1-2 µg per 100-500 µg of total protein accompanied by amenorrhea, hypoestrogenism and elevated serum gonado- (1 ml of cell lysate)], immunofluorescence (starting dilution 1:50, dilution tropin concentrations. 1% of all women are affected by POF, and mutations in range 1:50-1:500) and solid phase ELISA (starting dilution 1:30, dilution a few genes, including inhibina, fsh receptor and the LH/choriogonadotropin range 1:30-1:3000). receptor have been linked to POF. In addition, several germ cell specific genes Suitable for use as control antibody for NOBOX siRNA (h): sc-89594, and downstream transcription factors are thought to play and important role NOBOX siRNA (m): sc-150015, NOBOX shRNA Plasmid (h): sc-89594-SH, in human oogenesis. NOBOX (newborn ovary homeobox gene), an ooctye-spe- NOBOX shRNA Plasmid (m): sc-150015-SH, NOBOX shRNA (h) Lentiviral cific homeobox gene, is a critical protein involved in early folliculogenesis. Particles: sc-89594-V and NOBOX shRNA (m) Lentiviral Particles: Missense mutations have been shown to cause nonsyndromic ovarian failure sc-150015-V. by disrupting the NOBOX proteins ability to bind to NOBOX DNA-binding ele- ment (NBE), and thereby inhibiting its regulation of Pou5f1 and GDF-9. -
Combined GWAS and 'Guilt by Association'-Based Prioritization Analysis Identifies Functional Candidate Genes for Body Size
Combined GWAS and ‘guilt by association’-based prioritization analysis identifies functional candidate genes for body size in sheep Antonios Kominakis, Ariadne L. Hager-Theodorides, Evangelos Zoidis, Aggeliki Saridaki, George Antonakos, George Tsiamis To cite this version: Antonios Kominakis, Ariadne L. Hager-Theodorides, Evangelos Zoidis, Aggeliki Saridaki, George An- tonakos, et al.. Combined GWAS and ‘guilt by association’-based prioritization analysis identifies functional candidate genes for body size in sheep. Genetics Selection Evolution, BioMed Central, 2017, 49 (1), pp.41. 10.1186/s12711-017-0316-3. hal-01516195 HAL Id: hal-01516195 https://hal.archives-ouvertes.fr/hal-01516195 Submitted on 28 Apr 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Kominakis et al. Genet Sel Evol (2017) 49:41 DOI 10.1186/s12711-017-0316-3 Genetics Selection Evolution RESEARCH ARTICLE Open Access Combined GWAS and ‘guilt by association’‑based prioritization analysis identifes functional candidate genes for body size in sheep Antonios Kominakis1, Ariadne L. Hager‑Theodorides1*, Evangelos Zoidis1, Aggeliki Saridaki2, George Antonakos3 and George Tsiamis2 Abstract Background: Body size in sheep is an important indicator of productivity, growth and health as well as of environmen‑ tal adaptation. -
Common Variants in Signaling Transcription-Factor-Binding Sites Drive Phenotypic Variability in Red Blood Cell Traits
ARTICLES https://doi.org/10.1038/s41588-020-00738-2 Common variants in signaling transcription-factor-binding sites drive phenotypic variability in red blood cell traits Avik Choudhuri1,2,24, Eirini Trompouki 2,3,4,24, Brian J. Abraham 5,6,24, Leandro M. Colli7,8, Kian Hong Kock9,10, William Mallard 1,11, Min-Lee Yang12, Divya S. Vinjamur 13, Alireza Ghamari14, Audrey Sporrij1, Karen Hoi1, Barbara Hummel3, Sonja Boatman2, Victoria Chan1, Sierra Tseng1, Satish K. Nandakumar 13, Song Yang2, Asher Lichtig2, Michael Superdock 2, Seraj N. Grimes9,15, Teresa V. Bowman2,16, Yi Zhou2, Shinichiro Takahashi17, Roby Joehanes18,19, Alan B. Cantor14, Daniel E. Bauer 13, Santhi K. Ganesh12, John Rinn1,20, Paul S. Albert7, Martha L. Bulyk9,10,11,15,21, Stephen J. Chanock 7, Richard A. Young 5,22 and Leonard I. Zon 1,23 ✉ Genome-wide association studies identify genomic variants associated with human traits and diseases. Most trait-associated variants are located within cell-type-specific enhancers, but the molecular mechanisms governing phenotypic variation are less well understood. Here, we show that many enhancer variants associated with red blood cell (RBC) traits map to enhancers that are co-bound by lineage-specific master transcription factors (MTFs) and signaling transcription factors (STFs) responsive to extra- cellular signals. The majority of enhancer variants reside on STF and not MTF motifs, perturbing DNA binding by various STFs (BMP/TGF-β-directed SMADs or WNT-induced TCFs) and affecting target gene expression. Analyses of engineered human blood cells and expression quantitative trait loci verify that disrupted STF binding leads to altered gene expression.