Individuals with 22q11.2 microdeletions show behavioral and cognitive deficits and are at high risk of developing schizophrenia. We analyzed an engineered mouse strain carrying a chromosomal deficiency spanning a segment syntenic to the human 22q11.2 locus. We uncovered a previously unknown alteration in the biogenesis of microRNAs (miRNAs) and identified a subset of brain miRNAs affected by the microdeletion. We provide evidence that the abnormal miRNA biogenesis emerges because of haploinsufficiency of the Dgcr8 gene, which encodes an RNA-binding moiety of the 'microprocessor' complex and contributes to the behavioral and neuronal deficits associated with the 22q11.2 microdeletion.
Schizophrenia is an etiologically heterogeneous psychiatric disease, which exists in familial and nonfamilial (sporadic) forms. Here, we examine the possibility that rare de novo copy number (CN) mutations with relatively high penetrance contribute to the genetic component of schizophrenia. We carried out a whole-genome scan and implemented a number of steps for finding and confirming CN mutations. Confirmed de novo mutations were significantly associated with schizophrenia (P = 0.00078) and were collectively approximately 8 times more frequent in sporadic (but not familial) cases with schizophrenia than in unaffected controls. In comparison, rare inherited CN mutations were only modestly enriched in sporadic cases. Our results suggest that rare de novo germline mutations contribute to schizophrenia vulnerability in sporadic cases and that rare genetic lesions at many different loci can account, at least in part, for the genetic heterogeneity of this disease.
Over the past few years, substantial effort has been put into the functional annotation of variation in human genome sequence. Such annotations can play a critical role in identifying putatively causal variants among the abundant natural variation that occurs at a locus of interest. The main challenges in using these various annotations include their large numbers, and their diversity. Here we develop an unsupervised approach to integrate these different annotations into one measure of functional importance (Eigen), that, unlike most existing methods, is not based on any labeled training data. We show that the resulting meta-score has better discriminatory ability using disease associated and putatively benign variants from published studies (in both coding and noncoding regions) compared with the recently proposed CADD score. Across varied scenarios, the Eigen score performs generally better than any single individual annotation, representing a powerful single functional score that can be incorporated in fine-mapping studies.
To evaluate evidence for de novo etiologies in schizophrenia, we sequenced at high coverage the exomes of families recruited from two populations with distinct demographic structure and history. We sequenced a total of 795 exomes from 231 parent-proband trios enriched for sporadic schizophrenia cases, as well as 34 unaffected trios. We observed in cases an excess of non-synonymous single nucleotide variants as well as a higher prevalence of gene-disruptive de novo mutations. We found four genes (LAMA2, DPYD, TRRAP and VPS39) affected by recurrent de novo events within or across the two populations, a finding unlikely to have occurred by chance. We show that de novo mutations affect genes with diverse functions and developmental profiles but we also find a substantial contribution of mutations in genes with higher expression in early fetal life. Our results help define the pattern of genomic and neural architecture of schizophrenia.
Despite high heritability, a large fraction of cases with schizophrenia do not have a family history of the disease (sporadic cases). Here, we examine the possibility that rare de novo protein-altering mutations contribute to the genetic component of schizophrenia by sequencing the exome of 53 sporadic cases, 22 unaffected controls and their parents. We identified 40 de novo mutations in 27 patients affecting 40 genes including a potentially disruptive mutation in DGCR2, a gene removed Users may view, print, copy, download and text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms * Correspondence should be addressed to Maria Karayiorgou (mk2758@columbia.edu) or Joseph A. Gogos (jag90@columbia.edu). URLs: Picard (http://picard.sourceforge.net/) SAM tools (http://samtools.sourceforge.net/) PolyPhen-2 (http://genetics.bwh.harvard.edu/pph2/) UCSC Table Browser (http://genome.ucsc.edu/cgi-bin/hgTables) The Human Splicing Finder (HSF, Version 2.4.1) software (http://www.umd.be/HSF/) R (www.r-project.org/) dbSNP v132 (ftp://ftp.ncbi.nlm.nih.gov/snp/organisms/human_9606/VCF/v4.0/00-All.vcf.gz) GATK VCF annotation file for hg19 (ftp://gatk-ftp:PH5UH7Pa@ftp.broadinstitute.org/refGene/refGene-big-table-hg19.txt.gz) Accession codes: Reference sequences are available from NCBI under the following accession codes: PLCL2, NM_001144382; WDR11, NM_018117; DPYD, NM_000110; OR4C46, NM_001004703; UGT1A3, NM_019093; FAM3D, NM_138805; KLF12, NM_007249; ADCY7, NM_001114; GPR153, NM_207370; PML, NM_002675; SLC26A8, NM_052961; CCDC108, NM_152389; TRAK1, NM_001042646; FASTKD5, NM_021826; DGCR2, NM_005137; ACOT6, NM_001037162; PITPNM1, NM_001130848; NPRL2, NM_006545; MAGEC1, NM_005462; TRRAP, NM_003496; COL3A1, NM_000090; GIF, NM_005142; TEKT5, NM_144674; THBS1, NM_003246; PAG1, NM_018440; RGS12, NM_002926; SAP30BP, NM_013260; ZNF530, NM_020880; MTOR, NM_004958; INPP5A, NM_005539; EDEM2, NM_001145025; CELF2, NM_001083591; SLC26A7, NM_134266; VPS35, NM_018206; ADAMTS3, NM_014243; GPR115, NM_153838; SPATA5, NM_145207; RB1CC1, NM_014781; LAMA2, NM_000426; ESAM, NM_138961 AUTHOR CONTRIBUTIONS BX, JAG and MK designed the study, interpreted the data and prepared the manuscript; BX developed the analysis pipeline and had the primary role in analysis and validation of sequence data; JLR collected the samples and was the primary clinician on the project; SL and BP performed exome library construction, capture and sequencing; PD contributed to the analysis of the data; BB contributed to the primary sequence data analysis; SL supervised the sequencing project at HudsonAlpha Institute and contributed to the manuscript. COMPETING FINANCIAL INTERESTSThe authors declare no competing financial interests. 8,9 . Pilot studies in patients with SCZ focusing on specific synaptic genes identified a small number of putative de novo mutations 10 . However, the full contribution of rare de novo SNVs and in/d...
Peroxisome proliferator-activated receptor-γ (PPARγ) is a master transcriptional regulator of adipogenesis. Hence, the identification of PPARγ coactivators should help reveal mechanisms controlling gene expression in adipose tissue development and physiology. We show that the non-coding RNA, Steroid receptor RNA Activator (SRA), associates with PPARγ and coactivates PPARγ-dependent reporter gene expression. Overexpression of SRA in ST2 mesenchymal precursor cells promotes their differentiation into adipocytes. Conversely, knockdown of endogenous SRA inhibits 3T3-L1 preadipocyte differentiation. Microarray analysis reveals hundreds of SRA-responsive genes in adipocytes, including genes involved in the cell cycle, and insulin and TNFα signaling pathways. Some functions of SRA may involve mechanisms other than coactivation of PPARγ. SRA in adipocytes increases both glucose uptake and phosphorylation of Akt and FOXO1 in response to insulin. SRA promotes S-phase entry during mitotic clonal expansion, decreases expression of the cyclin-dependent kinase inhibitors p21Cip1 and p27Kip1, and increases phosphorylation of Cdk1/Cdc2. SRA also inhibits the expression of adipocyte-related inflammatory genes and TNFα-induced phosphorylation of c-Jun NH2-terminal kinase. In conclusion, SRA enhances adipogenesis and adipocyte function through multiple pathways.
Highlights d Integrated analysis provides insight into the molecular classification in NKTCL d EBV lytic genes play an important role on NKTCL pathogenesis d Genomic alteration-based molecular subtypes associate with clinical outcomes d MYC, histone acetylation, and PD-L1/2 are potential therapeutic targets of NKTCL
Despite the successful identification of several relevant genomic loci, the underlying molecular mechanisms of schizophrenia remain largely unclear. We developed a computational approach (NETBAG+) that allows an integrated analysis of diverse disease-related genetic data using a unified statistical framework. The application of this approach to schizophrenia-associated genetic variations, obtained using unbiased whole-genome methods, allowed us to identify several cohesive gene networks related to axon guidance, neuronal cell mobility, synaptic function and chromosomal remodeling. The genes forming the networks are highly expressed in the brain, with higher brain expression during prenatal development. The identified networks are functionally related to genes previously implicated in schizophrenia, autism and intellectual disability. A comparative analysis of copy number variants associated with autism and schizophrenia suggests that although the molecular networks implicated in these distinct disorders may be related, the mutations associated with each disease are likely to lead, at least on average, to different functional consequences.
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