Mouse Fscn3 Conditional Knockout Project (CRISPR/Cas9)
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Ovarian Gene Expression in the Absence of FIGLA, an Oocyte
BMC Developmental Biology BioMed Central Research article Open Access Ovarian gene expression in the absence of FIGLA, an oocyte-specific transcription factor Saurabh Joshi*1, Holly Davies1, Lauren Porter Sims2, Shawn E Levy2 and Jurrien Dean1 Address: 1Laboratory of Cellular and Developmental Biology, NIDDK, National Institutes of Health, Bethesda, MD 20892, USA and 2Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA Email: Saurabh Joshi* - [email protected]; Holly Davies - [email protected]; Lauren Porter Sims - [email protected]; Shawn E Levy - [email protected]; Jurrien Dean - [email protected] * Corresponding author Published: 13 June 2007 Received: 11 December 2006 Accepted: 13 June 2007 BMC Developmental Biology 2007, 7:67 doi:10.1186/1471-213X-7-67 This article is available from: http://www.biomedcentral.com/1471-213X/7/67 © 2007 Joshi et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: Ovarian folliculogenesis in mammals is a complex process involving interactions between germ and somatic cells. Carefully orchestrated expression of transcription factors, cell adhesion molecules and growth factors are required for success. We have identified a germ-cell specific, basic helix-loop-helix transcription factor, FIGLA (Factor In the GermLine, Alpha) and demonstrated its involvement in two independent developmental processes: formation of the primordial follicle and coordinate expression of zona pellucida genes. Results: Taking advantage of Figla null mouse lines, we have used a combined approach of microarray and Serial Analysis of Gene Expression (SAGE) to identify potential downstream target genes. -
Protein Interaction Network of Alternatively Spliced Isoforms from Brain Links Genetic Risk Factors for Autism
ARTICLE Received 24 Aug 2013 | Accepted 14 Mar 2014 | Published 11 Apr 2014 DOI: 10.1038/ncomms4650 OPEN Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism Roser Corominas1,*, Xinping Yang2,3,*, Guan Ning Lin1,*, Shuli Kang1,*, Yun Shen2,3, Lila Ghamsari2,3,w, Martin Broly2,3, Maria Rodriguez2,3, Stanley Tam2,3, Shelly A. Trigg2,3,w, Changyu Fan2,3, Song Yi2,3, Murat Tasan4, Irma Lemmens5, Xingyan Kuang6, Nan Zhao6, Dheeraj Malhotra7, Jacob J. Michaelson7,w, Vladimir Vacic8, Michael A. Calderwood2,3, Frederick P. Roth2,3,4, Jan Tavernier5, Steve Horvath9, Kourosh Salehi-Ashtiani2,3,w, Dmitry Korkin6, Jonathan Sebat7, David E. Hill2,3, Tong Hao2,3, Marc Vidal2,3 & Lilia M. Iakoucheva1 Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases. -
Mammalian Male Germ Cells Are Fertile Ground for Expression Profiling Of
REPRODUCTIONREVIEW Mammalian male germ cells are fertile ground for expression profiling of sexual reproduction Gunnar Wrobel and Michael Primig Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland Correspondence should be addressed to Michael Primig; Email: [email protected] Abstract Recent large-scale transcriptional profiling experiments of mammalian spermatogenesis using rodent model systems and different types of microarrays have yielded insight into the expression program of male germ cells. These studies revealed that an astonishingly large number of loci are differentially expressed during spermatogenesis. Among them are several hundred transcripts that appear to be specific for meiotic and post-meiotic germ cells. This group includes many genes that were pre- viously implicated in spermatogenesis and/or fertility and others that are as yet poorly characterized. Profiling experiments thus reveal candidates for regulation of spermatogenesis and fertility as well as targets for innovative contraceptives that act on gene products absent in somatic tissues. In this review, consolidated high density oligonucleotide microarray data from rodent total testis and purified germ cell samples are analyzed and their impact on our understanding of the transcriptional program governing male germ cell differentiation is discussed. Reproduction (2005) 129 1–7 Introduction 2002, Sadate-Ngatchou et al. 2003) and the absence of cAMP responsive-element modulator (Crem) and deleted During mammalian male -
Associated Marks Are Enriched in Imprinted Gene Regions and Predict Allele-Specific Modification
Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press Methods Overlapping euchromatin/heterochromatin- associated marks are enriched in imprinted gene regions and predict allele-specific modification Bo Wen,1,4 Hao Wu,2,4 Hans Bjornsson,1 Roland D. Green,3 Rafael Irizarry,2 and Andrew P. Feinberg1,5 1Department of Medicine and Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA; 2Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA; 3NimbleGen Systems, Inc., Madison, Wisconsin 53711, USA Most genome-level analysis treats the two parental alleles equivalently, yet diploid genomes contain two parental genomes that are often epigenetically distinct. While single nucleotide polymorphisms (SNPs) can be used to distinguish these genomes, it would be useful to develop a generalized strategy for identifying candidate genes or regions showing allele-specific differences, independent of SNPs. We have explored this problem by looking for overlapping marks in the genome related to both euchromatin (histone H3 dimethyl lysine-4 [H3K4Me2]) and heterochromatin (DNA methylation [DNAm]). “Double hits” were defined by the intersection of H3K4Me2 and DNAm. For the top 5% of marks, defined by a sliding window, imprinted gene regions were enriched for double hits 5.4-fold. When the location information of CTCF binding sites were integrated, the “triple hits” were enriched 76-fold for known imprinted genes in the regions studied. The double hits in imprinted genes were found to occur usually at the site of alternative or antisense transcripts. In addition, four of four imprinted genes tested showing double hits also showed allele-specific methylation. -
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). -
Supplementary Data
Supplementary Fig. 1 A B Responder_Xenograft_ Responder_Xenograft_ NON- NON- Lu7336, Vehicle vs Lu7466, Vehicle vs Responder_Xenograft_ Responder_Xenograft_ Sagopilone, Welch- Sagopilone, Welch- Lu7187, Vehicle vs Lu7406, Vehicle vs Test: 638 Test: 600 Sagopilone, Welch- Sagopilone, Welch- Test: 468 Test: 482 Responder_Xenograft_ NON- Lu7860, Vehicle vs Responder_Xenograft_ Sagopilone, Welch - Lu7558, Vehicle vs Test: 605 Sagopilone, Welch- Test: 333 Supplementary Fig. 2 Supplementary Fig. 3 Supplementary Figure S1. Venn diagrams comparing probe sets regulated by Sagopilone treatment (10mg/kg for 24h) between individual models (Welsh Test ellipse p-value<0.001 or 5-fold change). A Sagopilone responder models, B Sagopilone non-responder models. Supplementary Figure S2. Pathway analysis of genes regulated by Sagopilone treatment in responder xenograft models 24h after Sagopilone treatment by GeneGo Metacore; the most significant pathway map representing cell cycle/spindle assembly and chromosome separation is shown, genes upregulated by Sagopilone treatment are marked with red thermometers. Supplementary Figure S3. GeneGo Metacore pathway analysis of genes differentially expressed between Sagopilone Responder and Non-Responder models displaying –log(p-Values) of most significant pathway maps. Supplementary Tables Supplementary Table 1. Response and activity in 22 non-small-cell lung cancer (NSCLC) xenograft models after treatment with Sagopilone and other cytotoxic agents commonly used in the management of NSCLC Tumor Model Response type -
Identification of Candidate Genes in Regulation of Spermatogenesis In
Animal Reproduction Science 205 (2019) 52–61 Contents lists available at ScienceDirect Animal Reproduction Science journal homepage: www.elsevier.com/locate/anireprosci Identification of candidate genes in regulation of spermatogenesis in sheep testis following dietary vitamin E supplementation T Yang-Hua Qua,1, Lu-Yang Jiana,1, Ce Liua, Yong Maa, Chen-Chen Xua, Yue-Feng Gaoa, ⁎ Zoltan Machatyb, Hai-Ling Luoa, a State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing 100193, PR China b Purdue University, Department of Animal Sciences, West Lafayette, IN, 47907, USA ARTICLE INFO ABSTRACT Keywords: Dietary vitamin E supplementation is beneficial to semen quality in different sheep and goat Vitamin E breeds. The aim of this research was to further investigate the effect of vitamin E in sheep on Spermatogenesis spermatogenesis and its regulatory mechanisms using RNA-seq. Thirty male Hu lambs were Male Hu lamb randomly divided into three groups. The animals received 0, 200 or 2000 IU/day vitamin E RNA-seq dietary supplementation for 105 days, and its effects were subsequently evaluated. The results indicate vitamin E supplementation increased the number of germ cells in the testes and epidi- dymides. The positive effects were reduced, however, in animals that received 2000 IU/d vitamin E. Using the RNA-seq procedure, there was detection of a number of differentially expressed genes such as NDRG1, FSCN3 and CYP26B1 with these genes being mainly related to the reg- ulation of spermatogenesis. Supplementation with 2000 IU/d vitamin E supplementation resulted in a lesser abundance of skeleton-related transcripts such as TUBB, VIM and different subtypes of collagen, and there was also an effect on the ECM-receptor interaction pathway. -
The R109H Variant of Fascin-2, a Developmentally Regulated Actin Crosslinker in Hair-Cell Stereocilia, Underlies Early-Onset Hearing Loss of DBA/2J Mice
The Journal of Neuroscience, July 21, 2010 • 30(29):9683–9694 • 9683 Cellular/Molecular The R109H Variant of Fascin-2, a Developmentally Regulated Actin Crosslinker in Hair-Cell Stereocilia, Underlies Early-Onset Hearing Loss of DBA/2J Mice Jung-Bum Shin,1,2 Chantal M. Longo-Guess,5 Leona H. Gagnon,5 Katherine W. Saylor,1,2 Rachel A. Dumont,1,2 Kateri J. Spinelli,1,2 James M. Pagana,1,2 Phillip A. Wilmarth,3,4 Larry L. David,3,4 Peter G. Gillespie,1,2 and Kenneth R. Johnson5 1Oregon Hearing Research Center, 2Vollum Institute, 3Proteomics Shared Resource, and 4Department of Biochemistry, Oregon Health & Science University, Portland, Oregon 97239, and 5The Jackson Laboratory, Bar Harbor, Maine 04609 The quantitative trait locus ahl8 is a key contributor to the early-onset, age-related hearing loss of DBA/2J mice. A nonsynonymous nucleotide substitution in the mouse fascin-2 gene (Fscn2) is responsible for this phenotype, confirmed by wild-type BAC transgene rescue of hearing loss in DBA/2J mice. In chickens and mice, FSCN2 protein is abundant in hair-cell stereocilia, the actin-rich structures comprising the mechanically sensitive hair bundle, and is concentrated toward stereocilia tips of the bundle’s longest stereocilia. FSCN2 expression increases when these stereocilia differentially elongate, suggesting that FSCN2 controls filament growth, stiffens exposed stereocilia, or both. Because ahl8 accelerates hearing loss only in the presence of mutant cadherin 23, a component of hair-cell tip links, mechanotransduction and actin crosslinking must be functionally interrelated. Introduction espin, has very short stereocilia, and is profoundly deaf (Zheng et Hair cells of the inner ear detect and transduce mechanical dis- al., 2000). -
Nº Ref Uniprot Proteína Péptidos Identificados Por MS/MS 1 P01024
Document downloaded from http://www.elsevier.es, day 26/09/2021. This copy is for personal use. Any transmission of this document by any media or format is strictly prohibited. Nº Ref Uniprot Proteína Péptidos identificados 1 P01024 CO3_HUMAN Complement C3 OS=Homo sapiens GN=C3 PE=1 SV=2 por 162MS/MS 2 P02751 FINC_HUMAN Fibronectin OS=Homo sapiens GN=FN1 PE=1 SV=4 131 3 P01023 A2MG_HUMAN Alpha-2-macroglobulin OS=Homo sapiens GN=A2M PE=1 SV=3 128 4 P0C0L4 CO4A_HUMAN Complement C4-A OS=Homo sapiens GN=C4A PE=1 SV=1 95 5 P04275 VWF_HUMAN von Willebrand factor OS=Homo sapiens GN=VWF PE=1 SV=4 81 6 P02675 FIBB_HUMAN Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 78 7 P01031 CO5_HUMAN Complement C5 OS=Homo sapiens GN=C5 PE=1 SV=4 66 8 P02768 ALBU_HUMAN Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 66 9 P00450 CERU_HUMAN Ceruloplasmin OS=Homo sapiens GN=CP PE=1 SV=1 64 10 P02671 FIBA_HUMAN Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 58 11 P08603 CFAH_HUMAN Complement factor H OS=Homo sapiens GN=CFH PE=1 SV=4 56 12 P02787 TRFE_HUMAN Serotransferrin OS=Homo sapiens GN=TF PE=1 SV=3 54 13 P00747 PLMN_HUMAN Plasminogen OS=Homo sapiens GN=PLG PE=1 SV=2 48 14 P02679 FIBG_HUMAN Fibrinogen gamma chain OS=Homo sapiens GN=FGG PE=1 SV=3 47 15 P01871 IGHM_HUMAN Ig mu chain C region OS=Homo sapiens GN=IGHM PE=1 SV=3 41 16 P04003 C4BPA_HUMAN C4b-binding protein alpha chain OS=Homo sapiens GN=C4BPA PE=1 SV=2 37 17 Q9Y6R7 FCGBP_HUMAN IgGFc-binding protein OS=Homo sapiens GN=FCGBP PE=1 SV=3 30 18 O43866 CD5L_HUMAN CD5 antigen-like OS=Homo -
An Atlas of Human Gene Expression from Massively Parallel Signature Sequencing (MPSS)
Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Resource An atlas of human gene expression from massively parallel signature sequencing (MPSS) C. Victor Jongeneel,1,6 Mauro Delorenzi,2 Christian Iseli,1 Daixing Zhou,4 Christian D. Haudenschild,4 Irina Khrebtukova,4 Dmitry Kuznetsov,1 Brian J. Stevenson,1 Robert L. Strausberg,5 Andrew J.G. Simpson,3 and Thomas J. Vasicek4 1Office of Information Technology, Ludwig Institute for Cancer Research, and Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; 2National Center for Competence in Research in Molecular Oncology, Swiss Institute for Experimental Cancer Research (ISREC) and Swiss Institute of Bioinformatics, 1066 Epalinges, Switzerland; 3Ludwig Institute for Cancer Research, New York, New York 10012, USA; 4Solexa, Inc., Hayward, California 94545, USA; 5The J. Craig Venter Institute, Rockville, Maryland 20850, USA We have used massively parallel signature sequencing (MPSS) to sample the transcriptomes of 32 normal human tissues to an unprecedented depth, thus documenting the patterns of expression of almost 20,000 genes with high sensitivity and specificity. The data confirm the widely held belief that differences in gene expression between cell and tissue types are largely determined by transcripts derived from a limited number of tissue-specific genes, rather than by combinations of more promiscuously expressed genes. Expression of a little more than half of all known human genes seems to account for both the common requirements and the specific functions of the tissues sampled. A classification of tissues based on patterns of gene expression largely reproduces classifications based on anatomical and biochemical properties. -
Prognostic Significance of FSCN Family in Multiple Myeloma
Journal of Cancer 2021, Vol. 12 1936 Ivyspring International Publisher Journal of Cancer 2021; 12(7): 1936-1944. doi: 10.7150/jca.53675 Research Paper Prognostic significance of FSCN family in multiple myeloma Cong Deng1*, Chaozeng Si2*, Xu Ye3, Qiang Zhou1, Tiansheng Zeng3,4,5, Zeyong Huang3,4,5, Wenhui Huang3,4,5, Pei Zhu3,4,5, Qingfu Zhong3,4,5, Zhihua Wu3,4,5, Huoyan Zhu3,4,5, Qing Lin3,4,5, Wenjuan Zhang3,4,5, Lin Fu3,4,5,6,7, Yongjiang Zheng8, Tingting Qian3,4,5 1. Department of Clinical laboratory, The Second Affiliated Hospital, Guangzhou Medical University, 510260 Guangzhou, China. 2. Department of Information Center, China-Japan Friendship Hospital, 100029 Beijing, China. 3. Department of Hematology, The Second Affiliated Hospital, Guangzhou Medical University, 510260 Guangzhou, China. 4. Translational Medicine Center, State Key Laboratory of Respiratory Disease, The Second Affiliated Hospital of Guangzhou Medical University, 510260 Guangzhou, China. 5. Guangdong Provincial Education Department Key Laboratory of Nano-Immunoregulation Tumor Microenvironment, The Second Affiliated Hospital of Guangzhou Medical University, 510260 Guangzhou, China. 6. Translational Medicine Center, Huaihe Hospital of Henan University, 475000 Kaifeng, China. 7. Department of Hematology, Huaihe Hospital of Henan University, 475000 Kaifeng, China. 8. Department of Hematology, Institute of Hematology, The Third Affiliated Hospital of Sun Yat-Sen University, 510630 Guangzhou, China. * These authors contributed equally to this work: Cong Deng, Chaozeng Si. Corresponding author: Lin Fu, MD. PhD. E-mail: [email protected]; Yongjiang Zheng, MD. PhD. E-mail: [email protected]; Tingting Qian. E-mail: [email protected]. © The author(s). -
(12) Patent Application Publication (10) Pub. No.: US 2016/0002733 A1 Chu (43) Pub
US 2016.0002733A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2016/0002733 A1 Chu (43) Pub. Date: Jan. 7, 2016 (54) ASSESSING RISK FORENCEPHALOPATHY Related U.S. Application Data INDUCED BYS-FLUOROURACL, OR (60) Provisional application No. 61/772,949, filed on Mar. CAPECTABINE 5, 2013. Publication Classification (71) Applicant: THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNOR (51) Int. C. UNIVERSITY, Palo Alto, CA (US) CI2O I/68 (2006.01) (52) U.S. C. (72) Inventor: Gilbert Chu, Stanford, CA (US) CPC ........ CI2O I/6886 (2013.01); C12O 2600/156 (2013.01); C12O 2600/106 (2013.01); C12O (21) Appl. No.: 14/769,961 2600/142 (2013.01) (22) PCT Fled: Feb. 26, 2014 (57) ABSTRACT Methods and systems are provided for determining Suscepti (86) PCT NO.: PCT/US14/18739 bility to 5-fluorouracil (5-FU) or capecitabine toxicity. Meth ods are provided for treating a human Subject based on a S371 (c)(1), determined susceptibility to 5-fluorouracil (5-FU) or capecit (2) Date: Aug. 24, 2015 abine toxicity. Patent Application Publication Jan. 7, 2016 Sheet 1 of 17 US 2016/0002733 A1 Figure 1A urea cycle pyrimidine synthesis -- - - - - - - - - - - - Glin / WPA H al-NAGS NH 3. NH3CPSIDcarbamoyl-P Glu->NAG->|CPS Ca rbamyl-Asp: carbamoyl-P OHO : P. Orotate ornithine citruline s --AlORNT - Y - - - OMPwY Ornithine citruline UDP am UMP as UTP RR urea { UDP in OSuccinat A. 5-FUTP arginine 8 gypsuccina e CUMP i. cycleRECTS-5-FdUMP4-5-FU dTMP Figure IB /a-ketoglutarate pyruvate Asp PD PC 4-acetyl-CoA Glu oxaloacetate malate isocitrate Krebs cycle NH3 fumarate a-ketoglutarate Glu succinate succinyl-CoA methylmalonyl-CoA r a fatty acid proponyi-UOE.