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Genetic variants in the transcription regulatory region of MEGF10 are associated with autism in Chinese Han population.

Scientific reports | 2017

Multiple epidermal growth factor-like-domains 10 (MEGF10), a critical member of the apoptotic engulfment pathway, mediates axon pruning and synapse elimination during brain development. Previous studies indicated that synaptic pruning deficit was associated with autism-related phenotypes. However, the relationship between MEGF10 and autism remains poorly understood. Disease-associated variants are significantly enriched in the transcription regulatory regions. These include the transcription start site (TSS) and its cis-regulatory elements. To investigate the role of MEGF10 variants with putative transcription regulatory function in the etiology of autism, we performed a family-based association study in 410 Chinese Han trios. Our results indicate that three single nucleotide polymorphisms (SNPs), rs4836316, rs2194079 and rs4836317 near the TSS are significantly associated with autism following Bonferroni correction (p = 0.0011, p = 0.0088, and p = 0.0023, respectively). Haplotype T-A-G (rs4836316-rs2194079-rs4836317) was preferentially transmitted from parents to affected offspring (p permutation = 0.0055). Consistently, functional exploration further verified that the risk allele and haplotype might influence its binding with transcription factors, resulting in decreased transcriptional activity of MEGF10. Our findings indicated that the risk alleles and haplotype near the MEGF10 TSS might modulate transcriptional activity and increase the susceptibility to autism.

Pubmed ID: 28536440 RIS Download

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dbSNP (tool)

RRID:SCR_002338

Database as central repository for both single base nucleotide substitutions and short deletion and insertion polymorphisms. Distinguishes report of how to assay SNP from use of that SNP with individuals and populations. This separation simplifies some issues of data representation. However, these initial reports describing how to assay SNP will often be accompanied by SNP experiments measuring allele occurrence in individuals and populations. Community can contribute to this resource.

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Haploview (tool)

RRID:SCR_003076

A Java based software tool designed to simplify and expedite the process of haplotype analysis by providing a common interface to several tasks relating to such analyses. Haploview currently allows users to examine block structures, generate haplotypes in these blocks, run association tests, and save the data in a number of formats. All functionalities are highly customizable. (entry from Genetic Analysis Software) * LD & haplotype block analysis * haplotype population frequency estimation * single SNP and haplotype association tests * permutation testing for association significance * implementation of Paul de Bakker's Tagger tag SNP selection algorithm. * automatic download of phased genotype data from HapMap * visualization and plotting of PLINK whole genome association results including advanced filtering options Haploview is fully compatible with data dumps from the HapMap project and the Perlegen Genotype Browser. It can analyze thousands of SNPs (tens of thousands in command line mode) in thousands of individuals. Note: Haploview is currently on a development and support freeze. The team is currently looking at a variety of options in order to provide support for the software. Haploview is an open source project hosted by SourceForge. The source can be downloaded at the SourceForge project site.

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Applied Biosystems (tool)

RRID:SCR_005039

An Antibody supplier

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HaploReg (tool)

RRID:SCR_006796

HaploReg is a tool for exploring annotations of the noncoding genome at variants on haplotype blocks, such as candidate regulatory SNPs at disease-associated loci. Using linkage disequilibrium (LD) information from the 1000 Genomes Project, linked SNPs and small indels can be visualized along with their predicted chromatin state in nine cell types, conservation across mammals, and their effect on regulatory motifs. HaploReg is designed for researchers developing mechanistic hypotheses of the impact of non-coding variants on clinical phenotypes and normal variation.

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