Genome-Wide Association Scan Identifies New Variants Associated
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Whole-Genome Microarray Detects Deletions and Loss of Heterozygosity of Chromosome 3 Occurring Exclusively in Metastasizing Uveal Melanoma
Anatomy and Pathology Whole-Genome Microarray Detects Deletions and Loss of Heterozygosity of Chromosome 3 Occurring Exclusively in Metastasizing Uveal Melanoma Sarah L. Lake,1 Sarah E. Coupland,1 Azzam F. G. Taktak,2 and Bertil E. Damato3 PURPOSE. To detect deletions and loss of heterozygosity of disease is fatal in 92% of patients within 2 years of diagnosis. chromosome 3 in a rare subset of fatal, disomy 3 uveal mela- Clinical and histopathologic risk factors for UM metastasis noma (UM), undetectable by fluorescence in situ hybridization include large basal tumor diameter (LBD), ciliary body involve- (FISH). ment, epithelioid cytomorphology, extracellular matrix peri- ϩ ETHODS odic acid-Schiff-positive (PAS ) loops, and high mitotic M . Multiplex ligation-dependent probe amplification 3,4 5 (MLPA) with the P027 UM assay was performed on formalin- count. Prescher et al. showed that a nonrandom genetic fixed, paraffin-embedded (FFPE) whole tumor sections from 19 change, monosomy 3, correlates strongly with metastatic death, and the correlation has since been confirmed by several disomy 3 metastasizing UMs. Whole-genome microarray analy- 3,6–10 ses using a single-nucleotide polymorphism microarray (aSNP) groups. Consequently, fluorescence in situ hybridization were performed on frozen tissue samples from four fatal dis- (FISH) detection of chromosome 3 using a centromeric probe omy 3 metastasizing UMs and three disomy 3 tumors with Ͼ5 became routine practice for UM prognostication; however, 5% years’ metastasis-free survival. to 20% of disomy 3 UM patients unexpectedly develop metas- tases.11 Attempts have therefore been made to identify the RESULTS. Two metastasizing UMs that had been classified as minimal region(s) of deletion on chromosome 3.12–15 Despite disomy 3 by FISH analysis of a small tumor sample were found these studies, little progress has been made in defining the key on MLPA analysis to show monosomy 3. -
C2orf3 (GCFC2) (NM 001201334) Human Tagged ORF Clone Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for RG234563 C2orf3 (GCFC2) (NM_001201334) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: C2orf3 (GCFC2) (NM_001201334) Human Tagged ORF Clone Tag: TurboGFP Symbol: GCFC2 Synonyms: C2orf3; DNABF; GCF; TCF9 Vector: pCMV6-AC-GFP (PS100010) E. coli Selection: Ampicillin (100 ug/mL) Cell Selection: Neomycin This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 4 C2orf3 (GCFC2) (NM_001201334) Human Tagged ORF Clone – RG234563 ORF Nucleotide >RG234563 representing NM_001201334 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGAAGAGAGAGAGCGAAGATGACCCTGAGAGTGAGCCTGATGACCATGAAAAGAGAATACCATTTACTC TAAGACCTCAAACACTTAGACAAAGGATGGCTGAGGAATCAATAAGCAGAAATGAAGAAACAAGTGAAGA AAGTCAGGAAGATGAAAAGCAAGATACTTGGGAACAACAGCAAATGAGGAAAGCAGTTAAAATCATAGAG GAAAGAGACATAGATCTTTCCTGTGGCAATGGATCTTCAAAAGTGAAGAAATTTGATACTTCCATTTCAT TTCCGCCAGTAAATTTAGAAATTATAAAGAAGCAATTAAATACTAGATTAACATTACTACAGGAAACTCA CCGCTCACACCTGAGGGAGTATGAAAAATACGTACAAGATGTCAAAAGCTCAAAGAGTACCATCCAGAAC CTAGAGAGTTCATCAAATCAAGCTCTAAATTGTAAATTCTATAAAAGCATGAAAATTTATGTGGAAAATT TAATTGACTGCCTTAATGAAAAGATTATCAACATCCAAGAAATAGAATCATCCATGCATGCACTCCTTTT -
Table SI. Genes Upregulated ≥ 2-Fold by MIH 2.4Bl Treatment Affymetrix ID
Table SI. Genes upregulated 2-fold by MIH 2.4Bl treatment Fold UniGene ID Description Affymetrix ID Entrez Gene Change 1558048_x_at 28.84 Hs.551290 231597_x_at 17.02 Hs.720692 238825_at 10.19 93953 Hs.135167 acidic repeat containing (ACRC) 203821_at 9.82 1839 Hs.799 heparin binding EGF like growth factor (HBEGF) 1559509_at 9.41 Hs.656636 202957_at 9.06 3059 Hs.14601 hematopoietic cell-specific Lyn substrate 1 (HCLS1) 202388_at 8.11 5997 Hs.78944 regulator of G-protein signaling 2 (RGS2) 213649_at 7.9 6432 Hs.309090 serine and arginine rich splicing factor 7 (SRSF7) 228262_at 7.83 256714 Hs.127951 MAP7 domain containing 2 (MAP7D2) 38037_at 7.75 1839 Hs.799 heparin binding EGF like growth factor (HBEGF) 224549_x_at 7.6 202672_s_at 7.53 467 Hs.460 activating transcription factor 3 (ATF3) 243581_at 6.94 Hs.659284 239203_at 6.9 286006 Hs.396189 leucine rich single-pass membrane protein 1 (LSMEM1) 210800_at 6.7 1678 translocase of inner mitochondrial membrane 8 homolog A (yeast) (TIMM8A) 238956_at 6.48 1943 Hs.741510 ephrin A2 (EFNA2) 242918_at 6.22 4678 Hs.319334 nuclear autoantigenic sperm protein (NASP) 224254_x_at 6.06 243509_at 6 236832_at 5.89 221442 Hs.374076 adenylate cyclase 10, soluble pseudogene 1 (ADCY10P1) 234562_x_at 5.89 Hs.675414 214093_s_at 5.88 8880 Hs.567380; far upstream element binding protein 1 (FUBP1) Hs.707742 223774_at 5.59 677825 Hs.632377 small nucleolar RNA, H/ACA box 44 (SNORA44) 234723_x_at 5.48 Hs.677287 226419_s_at 5.41 6426 Hs.710026; serine and arginine rich splicing factor 1 (SRSF1) Hs.744140 228967_at 5.37 -
Speech Sound Disorder Influenced by a Locus in 15Q14 Region
Behav Genet DOI 10.1007/s10519-006-9090-7 ORIGINAL PAPER Speech Sound Disorder Influenced by a Locus in 15q14 Region Catherine M. Stein Æ Christopher Millard Æ Amy Kluge Æ Lara E. Miscimarra Æ Kevin C. Cartier Æ Lisa A. Freebairn Æ Amy J. Hansen Æ Lawrence D. Shriberg Æ H. Gerry Taylor Æ Barbara A. Lewis Æ Sudha K. Iyengar Received: 27 September 2005 / Accepted: 23 May 2006 Ó Springer Science+Business Media, Inc. 2006 Abstract Despite a growing body of evidence in- phonological memory, and that linkage at D15S118 was dicating that speech sound disorder (SSD) has an un- potentially influenced by a parent-of-origin effect derlying genetic etiology, researchers have not yet (LOD score increase from 0.97 to 2.17, P = 0.0633). identified specific genes predisposing to this condition. These results suggest shared genetic determinants in The speech and language deficits associated with SSD this chromosomal region for SSD, autism, and PWS/AS. are shared with several other disorders, including dys- lexia, autism, Prader-Willi Syndrome (PWS), and An- Keywords Phonology Æ Speech Æ Language Æ gelman’s Syndrome (AS), raising the possibility of gene Parent-of-origin Æ Allele-sharing sharing. Furthermore, we previously demonstrated that dyslexia and SSD share genetic susceptibility loci. The present study assesses the hypothesis that SSD also Introduction shares susceptibility loci with autism and PWS. To test this hypothesis, we examined linkage between SSD Speech–sound disorder (SSD) is a common communi- phenotypes and microsatellite markers on the chromo- cation disorder of unknown etiology with an estimated some 15q14–21 region, which has been associated with prevalence of 15.2% in children at age 3, persisting in autism, PWS/AS, and dyslexia. -
Structural Variant Calling by Assembly in Whole Human Genomes: Applications in Hypoplastic Left Heart Syndrome by Matthew Kendzi
STRUCTURAL VARIANT CALLING BY ASSEMBLY IN WHOLE HUMAN GENOMES: APPLICATIONS IN HYPOPLASTIC LEFT HEART SYNDROME BY MATTHEW KENDZIOR THESIS Submitted in partial FulFillment oF tHe requirements for the degree of Master of Science in BioinFormatics witH a concentration in Crop Sciences in the Graduate College of the University oF Illinois at Urbana-Champaign, 2019 Urbana, Illinois Master’s Committee: ProFessor MattHew Hudson, CHair ResearcH Assistant ProFessor Liudmila Mainzer ProFessor SaurabH SinHa ABSTRACT Variant discovery in medical researcH typically involves alignment oF sHort sequencing reads to the human reference genome. SNPs and small indels (variants less than 50 nucleotides) are the most common types oF variants detected From alignments. Structural variation can be more diFFicult to detect From short-read alignments, and thus many software applications aimed at detecting structural variants From short read alignments have been developed. However, these almost all detect the presence of variation in a sample using expected mate-pair distances From read data, making them unable to determine the precise sequence of the variant genome at the speciFied locus. Also, reads from a structural variant allele migHt not even map to the reference, and will thus be lost during variant discovery From read alignment. A variant calling by assembly approacH was used witH tHe soFtware Cortex-var for variant discovery in Hypoplastic Left Heart Syndrome (HLHS). THis method circumvents many of the limitations oF variants called From a reFerence alignment: unmapped reads will be included in a sample’s assembly, and variants up to thousands of nucleotides can be detected, with the Full sample variant allele sequence predicted. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Molecular Genetics of Dyslexia: an Overview
DYSLEXIA Published online in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/dys.1464 ■ Molecular Genetics of Dyslexia: An Overview Amaia Carrion-Castillo1*, Barbara Franke2 and Simon E. Fisher1,2 1Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands 2Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Netherlands Dyslexia is a highly heritable learning disorder with a complex underlying genetic architecture. Over the past decade, researchers have pinpointed a number of candidate genes that may con- tribute to dyslexia susceptibility. Here, we provide an overview of the state of the art, describing how studies have moved from mapping potential risk loci, through identification of associated gene variants, to characterization of gene function in cellular and animal model systems. Work thus far has highlighted some intriguing mechanistic pathways, such as neuronal migration, axon guidance, and ciliary biology, but it is clear that we still have much to learn about the molecular networks that are involved. We end the review by highlighting the past, present, and future contributions of the Dutch Dyslexia Programme to studies of genetic factors. In particular, we emphasize the importance of relating genetic information to intermediate neurobiological measures, as well as the value of incorporating longitudinal and developmental data into molecular designs. Copyright © 2013 John Wiley & Sons, Ltd. Keywords: molecular genetics; dyslexia; review INTRODUCTION Over the past decade or so, advances in molecular technologies have enabled researchers to begin pinpointing potential genetic risk factors implicated in human neurodevelopmental disorders (Graham & Fisher, 2013). A significant amount of work has focused on developmental dyslexia (specific reading disability). -
A Chromosome Level Genome of Astyanax Mexicanus Surface Fish for Comparing Population
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.06.189654; this version posted July 6, 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. 1 Title 2 A chromosome level genome of Astyanax mexicanus surface fish for comparing population- 3 specific genetic differences contributing to trait evolution. 4 5 Authors 6 Wesley C. Warren1, Tyler E. Boggs2, Richard Borowsky3, Brian M. Carlson4, Estephany 7 Ferrufino5, Joshua B. Gross2, LaDeana Hillier6, Zhilian Hu7, Alex C. Keene8, Alexander Kenzior9, 8 Johanna E. Kowalko5, Chad Tomlinson10, Milinn Kremitzki10, Madeleine E. Lemieux11, Tina 9 Graves-Lindsay10, Suzanne E. McGaugh12, Jeff T. Miller12, Mathilda Mommersteeg7, Rachel L. 10 Moran12, Robert Peuß9, Edward Rice1, Misty R. Riddle13, Itzel Sifuentes-Romero5, Bethany A. 11 Stanhope5,8, Clifford J. Tabin13, Sunishka Thakur5, Yamamoto Yoshiyuki14, Nicolas Rohner9,15 12 13 Authors for correspondence: Wesley C. Warren ([email protected]), Nicolas Rohner 14 ([email protected]) 15 16 Affiliation 17 1Department of Animal Sciences, Department of Surgery, Institute for Data Science and 18 Informatics, University of Missouri, Bond Life Sciences Center, Columbia, MO 19 2 Department of Biological Sciences, University of Cincinnati, Cincinnati, OH 20 3 Department of Biology, New York University, New York, NY 21 4 Department of Biology, The College of Wooster, Wooster, OH 22 5 Harriet L. Wilkes Honors College, Florida Atlantic University, Jupiter FL 23 6 Department of Genome Sciences, University of Washington, Seattle, WA 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.07.06.189654; this version posted July 6, 2020. -
GCF (H-87): Sc-366876
SAN TA C RUZ BI OTEC HNOL OG Y, INC . GCF (H-87): sc-366876 BACKGROUND APPLICATIONS GCF (GC-rich sequence DNA-binding factor), also known as C2orf3 (chro - GCF (H-87) is recommended for detection of GCF of mouse, rat and human mosome 2 open reading frame 3), transcription factor 9 (TCF-9) or DNABF, origin by Western Blotting (starting dilution 1:200, dilution range 1:100- is a 781 amino acid nuclear protein that belongs to the GCF family. Widely 1:1000), immunoprecipitation [1-2 µg per 100-500 µg of total protein (1 ml expressed, GCF binds the GC-rich sequences of β-Actin, EGFR and calcium- of cell lysate)], immunofluorescence (starting dilution 1:50, dilution range dependent protease (CANP) promoters. GCF contains multiple phosphoser - 1:50-1:500) and solid phase ELISA (starting dilution 1:30, dilution range ine and phosphothreonine residues, and two GCF isoforms are produced 1:30- 1:3000). due to alternative splicing events. GCF is considered a candidate for sus - GCF (H-87) is also recommended for detection of GCF in additional species, ceptibility to dyslexia (DYX3) as both genes reside in close proximity on including equine, canine and porcine. human chromosome 2. Chromosome 2 is the second largest human chro - mosome and consists of 237 million bases, encodes over 1,400 genes and Suitable for use as control antibody for GCF siRNA (h): sc-94282, GCF siRNA makes up approximately 8% of the human genome. (m): sc-141404, GCF shRNA Plasmid (h): sc-94282-SH, GCF shRNA Plasmid (m): sc-141404-SH, GCF shRNA (h) Lentiviral Particles: sc-94282-V and GCF REFERENCES shRNA (m) Lentiviral Particles: sc-141404-V. -
MOCHI Enables Discovery of Heterogeneous Interactome Modules in 3D Nucleome
Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press MOCHI enables discovery of heterogeneous interactome modules in 3D nucleome Dechao Tian1,# , Ruochi Zhang1,# , Yang Zhang1, Xiaopeng Zhu1, and Jian Ma1,* 1Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA #These two authors contributed equally *Correspondence: [email protected] Contact To whom correspondence should be addressed: Jian Ma School of Computer Science Carnegie Mellon University 7705 Gates-Hillman Complex 5000 Forbes Avenue Pittsburgh, PA 15213 Phone: +1 (412) 268-2776 Email: [email protected] 1 Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press Abstract The composition of the cell nucleus is highly heterogeneous, with different constituents forming complex interactomes. However, the global patterns of these interwoven heterogeneous interactomes remain poorly understood. Here we focus on two different interactomes, chromatin interaction network and gene regulatory network, as a proof-of-principle, to identify heterogeneous interactome modules (HIMs), each of which represents a cluster of gene loci that are in spatial contact more frequently than expected and that are regulated by the same group of transcription factors. HIM integrates transcription factor binding and 3D genome structure to reflect “transcriptional niche” in the nucleus. We develop a new algorithm MOCHI to facilitate the discovery of HIMs based on network motif clustering in heterogeneous interactomes. By applying MOCHI to five different cell types, we found that HIMs have strong spatial preference within the nucleus and exhibit distinct functional properties. Through integrative analysis, this work demonstrates the utility of MOCHI to identify HIMs, which may provide new perspectives on the interplay between transcriptional regulation and 3D genome organization. -
Evolutionary Diversification of DYX1C1 Transcripts Via an HERV-H LTR Integration Event
Genes Genet. Syst. (2011) 86, p. 277–284 Evolutionary diversification of DYX1C1 transcripts via an HERV-H LTR integration event Yun-Ji Kim1, Jae-Won Huh2, Dae-Soo Kim3, Kyudong Han4, Hwan-Mook Kim5 and Heui-Soo Kim1* 1Department of Biological Sciences, College of Natural Sciences, Pusan National University, Busan 609-735, Republic of Korea 2National Primate Research Center (NPRC), KRIBB, Ochang, Chungbuk 363-883, Republic of Korea 3Korean BioInformation Center, KRIBB, Daejeon 305-806, Republic of Korea 4Department of Nanobiomedical Science & WCU Research Center, Dankook University, Cheonan 330-714, Republic of Korea 5Department of Pharmacy, College of Pharmacy, Gachon University of Medicine and Science, Incheon 406-799, Republic of Korea (Received 21 May 2011, accepted 13 August 2011) DYX1C1 is a candidate gene for developmental dyslexia and has three alterna- tive pre-mRNA spliced forms in the human genome. One of the transcripts con- tains an HERV-H LTR that could affect the expression level of DYX1C1. We speculate that the HERV-H LTR integrated into the DYX1C1 locus in the catar- rhine lineage after its divergence from the platyrrhine lineage. Reverse tran- scription-PCR of the HERV-H LTR-related transcript produced four alternative forms from several human tissues. All of alternative forms were also identified in various rhesus macaque tissues. Through sequencing analysis of various pri- mate DNA samples, we found that a part of the HERV-H LTR sequence was dupli- cated within the DYX1C1 exon 9 only in catarrhines. However, the duplication event did not cause frameshift mutation of the DYX1C1 transcript. Taken together, this HERV-H LTR insertion into DYX1C1 has contributed to transcript diversification of DYX1C1 during primate evolution. -
Mouse Gcfc2 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Gcfc2 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Gcfc2 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Gcfc2 gene (NCBI Reference Sequence: NM_177884 ; Ensembl: ENSMUSG00000035125 ) is located on Mouse chromosome 6. 17 exons are identified, with the ATG start codon in exon 1 and the TGA stop codon in exon 17 (Transcript: ENSMUST00000043195). Exon 5 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Gcfc2 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-442L23 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 5 starts from about 29.69% of the coding region. The knockout of Exon 5 will result in frameshift of the gene. The size of intron 4 for 5'-loxP site insertion: 2994 bp, and the size of intron 5 for 3'-loxP site insertion: 3358 bp. The size of effective cKO region: ~616 bp. The cKO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 5 17 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Gcfc2 Homology arm cKO region loxP site Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats.