DOCSLIB.ORG

Sporadic Autism Exomes Reveal a Highly Interconnected Protein Network of De Novo Mutations

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Sporadic Autism Exomes Reveal a Highly Interconnected Protein Network of De Novo Mutations LETTER doi:10.1038/nature10989 Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations Brian J. O’Roak1,LauraVives1, Santhosh Girirajan1,EmreKarakoc1, Niklas Krumm1,BradleyP.Coe1,RoieLevy1,ArthurKo1,CholiLee1, Joshua D. Smith1, Emily H. Turner1, Ian B. Stanaway1, Benjamin Vernot1, Maika Malig1, Carl Baker1, Beau Reilly2,JoshuaM.Akey1, Elhanan Borenstein1,3,4,MarkJ.Rieder1, Deborah A. Nickerson1, Raphael Bernier2, Jay Shendure1 &EvanE.Eichler1,5 It is well established that autism spectrum disorders (ASD) have a per generation, in close agreement with our previous observations4, strong genetic component; however, for at least 70% of cases, the yet in general, higher than previous studies, indicating increased underlying genetic cause is unknown1. Under the hypothesis that sensitivity (Supplementary Table 2 and Supplementary Table 4)7. de novo mutations underlie a substantial fraction of the risk for We also observed complex classes of de novo mutation including: five developing ASD in families with no previous history of ASD or cases of multiple mutations in close proximity; two events consistent related phenotypes—so-called sporadic or simplex families2,3—we with paternal germline mosaicism (that is, where both siblings con- sequenced all coding regions of the genome (the exome) for tained a de novo event observed in neither parent); and nine events parent–child trios exhibiting sporadic ASD, including 189 new showing a weak minor allele profile consistent with somatic mosaicism trios and 20 that were previously reported4. Additionally, we also (Supplementary Table 3 and Supplementary Figs 2 and 3). sequenced the exomes of 50 unaffected siblings corresponding to Of the severe de novo events, 28% (33 of 120) are predicted to these new (n 5 31) and previously reported trios (n 5 19)4, for a truncate the protein. The distribution of synonymous, missense and total of 677 individual exomes from 209 families. Here we show nonsense changes corresponds well with a random mutation model7 that de novo point mutations are overwhelmingly paternal in (Supplementary Fig. 4 and Supplementary Table 2). However, the origin (4:1 bias) and positively correlated with paternal age, con- difference in nonsense rates between de novo and rare singleton events sistent with the modest increased risk for children of older fathers (not present in 1,779 other exomes) is striking (4:1) and suggests to develop ASD5. Moreover, 39% (49 of 126) of the most severe or strong selection against new nonsense events (Fisher’s exact test, disruptive de novo mutations map to a highly interconnected P , 0.0001). In contrast with a recent report8, we find no significant b-catenin/chromatin remodelling protein network ranked signifi- difference in mutation rate between affected and unaffected indivi- cantly for autism candidate genes. In proband exomes, recurrent duals; however, we do observe a trend towards increased non- protein-altering mutations were observed in two genes: CHD8 and synonymous rates in probands, consistent with the findings of ref. 9 NTNG1. Mutation screening of six candidate genes in 1,703 ASD (Supplementary Tables 1 and 2). probands identified additional de novo, protein-altering muta- Given the association of ASD with increased paternal age5 and our tions in GRIN2B, LAMC3 and SCN1A. Combined with copy previous observations4, we used molecular cloning, read-pair informa- number variant (CNV) data, these results indicate extreme locus tion, and obligate carrier status to identify informative markers linked heterogeneity but also provide a target for future discovery, to 51 de novo events and observed a marked paternal bias (41:10; diagnostics and therapeutics. binomial P , 1.4 3 1025; Fig. 1a and Supplementary Tables 3 and 5). We selected 189 autism trios from the Simons Simplex Collection This provides strong direct evidence that the germline mutation rate in (SSC)6, which included males significantly impaired with autism and protein-coding regions is, on average, substantially higher in males. A intellectual disability (n 5 47), a female sample set (n 5 56) of which similar finding was recently reported for de novo CNVs10. In addition, 26 were cognitively impaired, and samples chosen at random from the we observe that the number of de novo events is positively correlated remaining males in the collection (n 5 86) (Supplementary Table 1 with increasing paternal age (Spearman’s rank correlation 5 0.19; and Supplementary Fig. 1). In general, we excluded samples known to P , 0.008; Fig. 1b). Together, these observations are consistent with carry large de novo CNVs2. Exome sequencing was performed as the hypothesis that the modest increased risk for children of older described previously4, but with an expanded target definition (see fathers to develop ASD5 is the result of an increased mutation rate. Methods). We achieved sufficient coverage for both parents and child Using sequence read-depth methods in 122 of the 189 families, we to call genotypes for, on average, 29.5 megabases (Mb) of haploid scanned ASD probands for either de novo CNVs or rare (,1% of exome coding sequence (Supplementary Table 1). In addition, we controls), inherited CNVs. Individual events were validated by either performed copy number analysis on 122 of these families, using a array CGH or genotyping array (see Methods). We identified 76 events combination of the exome data, array comparative genomic hybrid- in 53 individuals, including six de novo (median size 467 kilobases ization (CGH), and genotyping arrays, thereby providing a more com- (kb)) and 70 inherited (median size 155 kb) CNVs (Supplementary prehensive view of rare variation. Table 6). These include disruptions of EHMT1 (Kleefstra’s syndrome, In the 189 new probands, we validated 248 de novo events, 225 single Online Mendelian Inheritance in Man (OMIM) accession 610253), nucleotide variants (SNVs), 17 small insertions/deletions (indels), and CNTNAP4 (reported in children with developmental delay and aut- six CNVs (Supplementary Table 2). These included 181 non- ism11) and the 16p11.2 duplication (OMIM 611913) associated with synonymous changes, of which 120 were classified as severe based developmental delay, bipolar disorder and schizophrenia. on sequence conservation and/or biochemical properties (Methods We performed a multivariate analysis on non-verbal IQ (NVIQ), and Supplementary Table 3). The observed point mutation rate in verbal IQ (VIQ) and the load of ‘extreme’ de novo mutations—where coding sequence was ,1.3 events per trio or 2.17 3 1028 per base extreme is defined as point mutations that truncate proteins, intersect 1Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA. 2Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington 98195, USA. 3Department of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, USA. 4Santa Fe Institute, Santa Fe, New Mexico 87501, USA. 5Howard Hughes Medical Institute, Seattle, Washington 98195, USA. 00 MONTH 2012 | VOL 000 | NATURE | 1 ©2012 Macmillan Publishers Limited. All rights reserved RESEARCH LETTER a b c 140 120 A A T T 80 100 T T 41 10 Non-verbal IQ A G paternal maternal 40 60 Paternal age (months) A G events events 250 350 450 550 T 012 3+ 20 012+ Number of de novo coding mutations Number of extreme de novo mutations d Chr18: 40000000 40500000 41000000 41500000 Cases Controls 18q12.3 SETBP1 SLC14A2 EPG5 SLC14A1 SIGLEC15 Figure 1 | De novo mutation events in autism spectrum disorder. mutation events (0, n 5 138; 1, n 5 41; 21, n 5 10), both with and without a, Haplotype phasing using informative markers shows a strong parent-of- CNVs (Supplementary Discussion). d, Browser images showing CNVs origin bias with 41 of 51 de novo events occurring on the paternally inherited identified in the del(18)(q12.2q21.1) syndrome region. The truncating point haplotype. Arrows represent sequence reads from paternal (blue) or maternal mutation in SETBP1 occurs within the critical region, identifying the likely (red) haplotypes. b, c, Box and whisker plots for 189 SSC probands. b,The causative locus. Each red (deletion) and green (duplication) line represents an paternal estimated age at conception versus the number of observed de novo identified CNV in cases (solid lines) versus controls (dashed lines), with point mutations (0, n 5 53; 1, n 5 65; 2, n 5 44; 31, n 5 27). c, Decreased non- arrowheads showing point mutation. verbal IQ is significantly associated with an increasing number of extreme Mendelian or ASD loci (n 5 57), or de novo CNVs that intersect genes The de novo mutations included truncating events in syndromic (n 5 5) (Fig. 1c and Supplementary Discussion). NVIQ, but not VIQ, intellectual disability genes (MBD5 (mental retardation, autosomal decreased significantly (P , 0.01) with increased number of events. dominant 1, OMIM 156200), RPS6KA3 (Coffin–Lowry syndrome, Covariant analysis of the samples with CNV data showed that this OMIM 303600) and DYRK1A (the Down’s syndrome candidate finding was strengthened, but not exclusively driven, by the presence gene, OMIM 600855)), and missense variants in loci associated with of either de novo or rare CNVs (Supplementary Fig. 5). syndromic ASD, including CHD7, PTEN (macrocephaly/autism Among the de novo events, we identified 62 top ASD risk con- syndrome, OMIM 605309) and TSC2 (tuberous sclerosis complex, tributing mutations based on the deleteriousness of the
Load more

Recommended publications
  • Histone Isoform H2A1H Promotes Attainment of Distinct Physiological
    Bhattacharya et al. Epigenetics & Chromatin (2017) 10:48 DOI 10.1186/s13072-017-0155-z Epigenetics & Chromatin RESEARCH Open Access Histone isoform H2A1H promotes attainment of distinct physiological states by altering chromatin dynamics Saikat Bhattacharya1,4,6, Divya Reddy1,4, Vinod Jani5†, Nikhil Gadewal3†, Sanket Shah1,4, Raja Reddy2,4, Kakoli Bose2,4, Uddhavesh Sonavane5, Rajendra Joshi5 and Sanjay Gupta1,4* Abstract Background: The distinct functional efects of the replication-dependent histone H2A isoforms have been dem- onstrated; however, the mechanistic basis of the non-redundancy remains unclear. Here, we have investigated the specifc functional contribution of the histone H2A isoform H2A1H, which difers from another isoform H2A2A3 in the identity of only three amino acids. Results: H2A1H exhibits varied expression levels in diferent normal tissues and human cancer cell lines (H2A1C in humans). It also promotes cell proliferation in a context-dependent manner when exogenously overexpressed. To uncover the molecular basis of the non-redundancy, equilibrium unfolding of recombinant H2A1H-H2B dimer was performed. We found that the M51L alteration at the H2A–H2B dimer interface decreases the temperature of melting of H2A1H-H2B by ~ 3 °C as compared to the H2A2A3-H2B dimer. This diference in the dimer stability is also refected in the chromatin dynamics as H2A1H-containing nucleosomes are more stable owing to M51L and K99R substitu- tions. Molecular dynamic simulations suggest that these substitutions increase the number of hydrogen bonds and hydrophobic interactions of H2A1H, enabling it to form more stable nucleosomes. Conclusion: We show that the M51L and K99R substitutions, besides altering the stability of histone–histone and histone–DNA complexes, have the most prominent efect on cell proliferation, suggesting that the nucleosome sta- bility is intimately linked with the physiological efects observed.
    [Show full text]
  • Genetic Variation Across the Human Olfactory Receptor Repertoire Alters Odor Perception
    bioRxiv preprint doi: https://doi.org/10.1101/212431; this version posted November 1, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Genetic variation across the human olfactory receptor repertoire alters odor perception Casey Trimmer1,*, Andreas Keller2, Nicolle R. Murphy1, Lindsey L. Snyder1, Jason R. Willer3, Maira Nagai4,5, Nicholas Katsanis3, Leslie B. Vosshall2,6,7, Hiroaki Matsunami4,8, and Joel D. Mainland1,9 1Monell Chemical Senses Center, Philadelphia, Pennsylvania, USA 2Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, New York, USA 3Center for Human Disease Modeling, Duke University Medical Center, Durham, North Carolina, USA 4Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, North Carolina, USA 5Department of Biochemistry, University of Sao Paulo, Sao Paulo, Brazil 6Howard Hughes Medical Institute, New York, New York, USA 7Kavli Neural Systems Institute, New York, New York, USA 8Department of Neurobiology and Duke Institute for Brain Sciences, Duke University Medical Center, Durham, North Carolina, USA 9Department of Neuroscience, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA *[email protected] ABSTRACT The human olfactory receptor repertoire is characterized by an abundance of genetic variation that affects receptor response, but the perceptual effects of this variation are unclear. To address this issue, we sequenced the OR repertoire in 332 individuals and examined the relationship between genetic variation and 276 olfactory phenotypes, including the perceived intensity and pleasantness of 68 odorants at two concentrations, detection thresholds of three odorants, and general olfactory acuity.
    [Show full text]
  • Supplementary Information Integrative Analyses of Splicing in the Aging Brain: Role in Susceptibility to Alzheimer’S Disease
    Supplementary Information Integrative analyses of splicing in the aging brain: role in susceptibility to Alzheimer’s Disease Contents 1. Supplementary Notes 1.1. Religious Orders Study and Memory and Aging Project 1.2. Mount Sinai Brain Bank Alzheimer’s Disease 1.3. CommonMind Consortium 1.4. Data Availability 2. Supplementary Tables 3. Supplementary Figures Note: Supplementary Tables are provided as separate Excel files. 1. Supplementary Notes 1.1. Religious Orders Study and Memory and Aging Project Gene expression data1. Gene expression data were generated using RNA- sequencing from Dorsolateral Prefrontal Cortex (DLPFC) of 540 individuals, at an average sequence depth of 90M reads. Detailed description of data generation and processing was previously described2 (Mostafavi, Gaiteri et al., under review). Samples were submitted to the Broad Institute’s Genomics Platform for transcriptome analysis following the dUTP protocol with Poly(A) selection developed by Levin and colleagues3. All samples were chosen to pass two initial quality filters: RNA integrity (RIN) score >5 and quantity threshold of 5 ug (and were selected from a larger set of 724 samples). Sequencing was performed on the Illumina HiSeq with 101bp paired-end reads and achieved coverage of 150M reads of the first 12 samples. These 12 samples will serve as a deep coverage reference and included 2 males and 2 females of nonimpaired, mild cognitive impaired, and Alzheimer's cases. The remaining samples were sequenced with target coverage of 50M reads; the mean coverage for the samples passing QC is 95 million reads (median 90 million reads). The libraries were constructed and pooled according to the RIN scores such that similar RIN scores would be pooled together.
    [Show full text]
  • Zhou Et Al POLQ Inhibitor.Docx
    bioRxiv preprint doi: https://doi.org/10.1101/2020.05.23.111658; this version posted May 26, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Polymerase Theta Inhibition Kills Homologous Recombination Deficient Tumors Jia Zhou1, Camille Gelot2, Constantia Pantelidou3, Adam Li1, Hatice Yücel2, Rachel E. Davis4, Anniina Farkkila1, Bose Kochupurakkal1, Aleem Syed5, Geoffrey I. Shapiro3,6, John A. Tainer5, Brian S. J. Blagg4, Raphael Ceccaldi2,7* and Alan D. D’Andrea1,6,7* 1Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA. 2Inserm U830, PSL Research University, Institut Curie, 75005, Paris, France. 3Department of Medical Oncology, Dana-Farber Cancer Institute and Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA. 4Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA. 5Departments of Cancer Biology and of Molecular and Cellular Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 6Center for DNA Damage and Repair, Dana-Farber Cancer Institute, Boston, MA, USA. 7Co-senior authors. * Co-corresponding authors. * Corresponding authors: Alan D. D’Andrea, M.D. Director, Susan F. Smith Center for Women’s Cancers (SFSCWC) Director, Center for DNA Damage and Repair Dana-Farber Cancer Institute The Fuller-American Cancer Society Professor Harvard Medical School Phone: 617-632-2080 Email: [email protected] Raphael Ceccaldi Institut Curie, 75005, Paris, France Phone: +33 (0)1 56 24 69 49 Email: [email protected] Key Words: Novobiocin, Polymerase theta (POLθ), Homologous Recombination, PARP inhibitor resistance.
    [Show full text]
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2
    Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491
    [Show full text]
  • Differences for Ectopic Versus Eutopic Cells
    556 RBMO VOLUME 39 ISSUE 4 2019 ARTICLE Chemosensitivity and chemoresistance in endometriosis – differences for ectopic versus eutopic cells BIOGRAPHY Andres Salumets is Professor of Reproductive Medicine at the University of Tartu, and Scientific Head at the Competence Centre on Health Technologies, Tartu, Estonia. He has been involved in assisted reproduction for 20 years, first as an embryologist and later as a researcher. His major interests are endometriosis, endometrial biology and implantation. Darja Lavogina1,2,*, Külli Samuel1, Arina Lavrits1,3, Alvin Meltsov1, Deniss Sõritsa1,4,5, Ülle Kadastik6, Maire Peters1,4, Ago Rinken2, Andres Salumets1,4,7, 8 KEY MESSAGE Akt/PKB inhibitor GSK690693, CK2 inhibitor ARC-775, MAPK pathway inhibitor sorafenib, proteasome inhibitor bortezomib, and microtubule-depolymerizing toxin MMAE showed higher cytotoxicity in eutopic cells. In contrast, 10 µmol/l of the anthracycline toxin doxorubicin caused cellular death in ectopic cells more effectively than in eutopic cells, underlining the potential of doxorubicin in endometriosis research. ABSTRACT Research question: Endometriosis is a common gynaecological disease defined by the presence of endometrium-like tissue outside the uterus. This complex disease, often accompanied by severe pain and infertility, causes a significant medical and socioeconomic burden; hence, novel strategies are being sought for the treatment of endometriosis. Here, we set out to explore the cytotoxic effects of a panel of compounds to find toxins with different efficiency in eutopic versus ectopic cells, thus highlighting alterations in the corresponding molecular pathways. Design: The effect on cellular viability of 14 compounds was established in a cohort of paired eutopic and ectopic endometrial stromal cell samples from 11 patients.
    [Show full text]
  • Supplementary Table S2
    1-high in cerebrotropic Gene P-value patients Definition BCHE 2.00E-04 1 Butyrylcholinesterase PLCB2 2.00E-04 -1 Phospholipase C, beta 2 SF3B1 2.00E-04 -1 Splicing factor 3b, subunit 1 BCHE 0.00022 1 Butyrylcholinesterase ZNF721 0.00028 -1 Zinc finger protein 721 GNAI1 0.00044 1 Guanine nucleotide binding protein (G protein), alpha inhibiting activity polypeptide 1 GNAI1 0.00049 1 Guanine nucleotide binding protein (G protein), alpha inhibiting activity polypeptide 1 PDE1B 0.00069 -1 Phosphodiesterase 1B, calmodulin-dependent MCOLN2 0.00085 -1 Mucolipin 2 PGCP 0.00116 1 Plasma glutamate carboxypeptidase TMX4 0.00116 1 Thioredoxin-related transmembrane protein 4 C10orf11 0.00142 1 Chromosome 10 open reading frame 11 TRIM14 0.00156 -1 Tripartite motif-containing 14 APOBEC3D 0.00173 -1 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3D ANXA6 0.00185 -1 Annexin A6 NOS3 0.00209 -1 Nitric oxide synthase 3 SELI 0.00209 -1 Selenoprotein I NYNRIN 0.0023 -1 NYN domain and retroviral integrase containing ANKFY1 0.00253 -1 Ankyrin repeat and FYVE domain containing 1 APOBEC3F 0.00278 -1 Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3F EBI2 0.00278 -1 Epstein-Barr virus induced gene 2 ETHE1 0.00278 1 Ethylmalonic encephalopathy 1 PDE7A 0.00278 -1 Phosphodiesterase 7A HLA-DOA 0.00305 -1 Major histocompatibility complex, class II, DO alpha SOX13 0.00305 1 SRY (sex determining region Y)-box 13 ABHD2 3.34E-03 1 Abhydrolase domain containing 2 MOCS2 0.00334 1 Molybdenum cofactor synthesis 2 TTLL6 0.00365 -1 Tubulin tyrosine ligase-like family, member 6 SHANK3 0.00394 -1 SH3 and multiple ankyrin repeat domains 3 ADCY4 0.004 -1 Adenylate cyclase 4 CD3D 0.004 -1 CD3d molecule, delta (CD3-TCR complex) (CD3D), transcript variant 1, mRNA.
    [Show full text]
  • Supplementary Table 9. Functional Annotation Clustering Results for the Union (GS3) of the Top Genes from the SNP-Level and Gene-Based Analyses (See ST4)
    Supplementary Table 9. Functional Annotation Clustering Results for the union (GS3) of the top genes from the SNP-level and Gene-based analyses (see ST4) Column Header Key Annotation Cluster Name of cluster, sorted by descending Enrichment score Enrichment Score EASE enrichment score for functional annotation cluster Category Pathway Database Term Pathway name/Identifier Count Number of genes in the submitted list in the specified term % Percentage of identified genes in the submitted list associated with the specified term PValue Significance level associated with the EASE enrichment score for the term Genes List of genes present in the term List Total Number of genes from the submitted list present in the category Pop Hits Number of genes involved in the specified term (category-specific) Pop Total Number of genes in the human genome background (category-specific) Fold Enrichment Ratio of the proportion of count to list total and population hits to population total Bonferroni Bonferroni adjustment of p-value Benjamini Benjamini adjustment of p-value FDR False Discovery Rate of p-value (percent form) Annotation Cluster 1 Enrichment Score: 3.8978262119731335 Category Term Count % PValue Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR GOTERM_CC_DIRECT GO:0005886~plasma membrane 383 24.33290978 5.74E-05 SLC9A9, XRCC5, HRAS, CHMP3, ATP1B2, EFNA1, OSMR, SLC9A3, EFNA3, UTRN, SYT6, ZNRF2, APP, AT1425 4121 18224 1.18857065 0.038655922 0.038655922 0.086284383 UP_KEYWORDS Membrane 626 39.77128335 1.53E-04 SLC9A9, HRAS,
    [Show full text]
  • An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors
    Ecology and Evolutionary Biology 2021; 6(3): 53-77 http://www.sciencepublishinggroup.com/j/eeb doi: 10.11648/j.eeb.20210603.11 ISSN: 2575-3789 (Print); ISSN: 2575-3762 (Online) An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors Miguel Angel Fuertes*, Carlos Alonso Department of Microbiology, Centre for Molecular Biology “Severo Ochoa”, Spanish National Research Council and Autonomous University, Madrid, Spain Email address: *Corresponding author To cite this article: Miguel Angel Fuertes, Carlos Alonso. An Evolutionary Based Strategy for Predicting Rational Mutations in G Protein-Coupled Receptors. Ecology and Evolutionary Biology. Vol. 6, No. 3, 2021, pp. 53-77. doi: 10.11648/j.eeb.20210603.11 Received: April 24, 2021; Accepted: May 11, 2021; Published: July 13, 2021 Abstract: Capturing conserved patterns in genes and proteins is important for inferring phenotype prediction and evolutionary analysis. The study is focused on the conserved patterns of the G protein-coupled receptors, an important superfamily of receptors. Olfactory receptors represent more than 2% of our genome and constitute the largest family of G protein-coupled receptors, a key class of drug targets. As no crystallographic structures are available, mechanistic studies rely on the use of molecular dynamic modelling combined with site-directed mutagenesis data. In this paper, we hypothesized that human-mouse orthologs coding for G protein-coupled receptors maintain, at speciation events, shared compositional structures independent, to some extent, of their percent identity as reveals a method based in the categorization of nucleotide triplets by their gross composition. The data support the consistency of the hypothesis, showing in ortholog G protein-coupled receptors the presence of emergent shared compositional structures preserved at speciation events.
    [Show full text]
  • Research Article Clinic-Genomic Association Mining for Colorectal Cancer Using Publicly Available Datasets
    Hindawi Publishing Corporation BioMed Research International Volume 2014, Article ID 170289, 10 pages http://dx.doi.org/10.1155/2014/170289 Research Article Clinic-Genomic Association Mining for Colorectal Cancer Using Publicly Available Datasets Fang Liu,1 Yaning Feng,1 Zhenye Li,2 Chao Pan,1 Yuncong Su,1 Rui Yang,1 Liying Song,1 Huilong Duan,1 and Ning Deng1 1 Department of Biomedical Engineering, Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou 310027, China 2 General Hospital of Ningxia Medical University, Yinchuan 750004, China Correspondence should be addressed to Ning Deng; [email protected] Received 30 March 2014; Accepted 12 May 2014; Published 2 June 2014 Academic Editor: Degui Zhi Copyright © 2014 Fang Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In recent years, a growing number of researchers began to focus on how to establish associations between clinical and genomic data. However, up to now, there is lack of research mining clinic-genomic associations by comprehensively analysing available gene expression data for a single disease. Colorectal cancer is one of the malignant tumours. A number of genetic syndromes have been proven to be associated with colorectal cancer. This paper presents our research on mining clinic-genomic associations for colorectal cancer under biomedical big data environment. The proposed method is engineered with multiple technologies, including extracting clinical concepts using the unified medical language system (UMLS), extracting genes through the literature mining, and mining clinic-genomic associations through statistical analysis.
    [Show full text]
  • Identification of Candidate Biomarkers and Pathways Associated with Type 1 Diabetes Mellitus Using Bioinformatics Analysis
    bioRxiv preprint doi: https://doi.org/10.1101/2021.06.08.447531; this version posted June 9, 2021. 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. Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2021.06.08.447531; this version posted June 9, 2021. 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 Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were then performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway.
    [Show full text]