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C

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The Project MinE databrowser: bringing large-scale whole-genome sequencing in ALS to researchers and the public.

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive fatal neurodegenerative disease affecting 1 in 350 people. The aim of Project MinE is to elucidate the pathophysiology of ALS through whole-genome sequencing at least 15,000 ALS patients and 7,500 controls at 30X coverage. Here, we present the Project MinE data browser (databrowser.projectmine.com). a unique and intuitive one-stop, open-access server that provides detailed information on genetic variation analyzed in a new and still growing set of 4,366 ALS cases and 1,832 matched controls. Through its visual components and interactive design, the browser specifically aims to be a resource to those without a biostatistics background and allow clinicians and preclinical researchers to integrate Project MinE data into their own research. The browser allows users to query a transcript and immediately access a unique combination of detailed (meta)data, annotations and association statistics that would otherwise require analytic expertise and visits to scattered resources.

genomics

Disease variants alter transcription factor levels and methylation of their binding sites

Most disease associated genetic risk factors are non-coding, making it challenging to design experiments to understand their functional consequences1,2. Identification of expression quantitative trait loci (eQTLs) has been a powerful approach to infer downstream effects of disease variants but the large majority remains unexplained.3,4. The analysis of DNA methylation, a key component of the epigenome5, offers highly complementary data on the regulatory potential of genomic regions6,7. However, a large-scale, combined analysis of methylome and transcriptome data to infer downstream effects of disease variants is lacking. Here, we show that disease variants have wide-spread effects on DNA methylation in trans that likely reflect the downstream effects on binding sites of cis-regulated transcription factors. Using data on 3,841 Dutch samples, we detected 272,037 independent cis-meQTLs (FDR < 0.05) and identified 1,907 trait-associated SNPs that affect methylation levels of 10,141 different CpG sites in trans (FDR < 0.05), an eight-fold increase in the number of downstream effects that was known from trans-eQTL studies3,8,9. Trans-meQTL CpG sites are enriched for active regulatory regions, being correlated with gene expression and overlap with Hi-C determined interchromosomal contacts10,11. We detected many trans-meQTL SNPs that affect expression levels of nearby transcription factors (including NFKB1, CTCF and NKX2-3), while the corresponding trans-meQTL CpG sites frequently coincide with its respective binding site. Trans-meQTL mapping therefore provides a strategy for identifying and better understanding downstream functional effects of many disease-associated variants.

Genomics