HiPR: High-throughput probabilistic RNA structure inference.

Recent high-throughput structure-sensitive genome-wide sequencing-based assays have enabled large-scale studies of RNA structure, and robust transcriptome-wide computational prediction of individual RNA structures across RNA classes from these assays has potential to further improve the prediction accuracy. Here, we describe HiPR, a novel method for RNA structure prediction at single-nucleotide resolution that combines high-throughput structure probing data (DMS-seq, DMS-MaPseq) with a novel probabilistic folding algorithm. On validation data spanning a variety of RNA classes, HiPR often increases accuracy for predicting RNA structures, giving researchers new tools to study RNA structure.

LRP10 variants in progressive supranuclear palsy.

The aim of this study was to explore whether variants in LRP10, recently associated with Parkinson's disease and dementia with Lewy bodies, are observed in 2 large cohorts (discovery and validation cohort) of patients with progressive supranuclear palsy (PSP). A total of 950 patients with PSP were enrolled: 246 patients with PSP (n = 85 possible (35%), n = 128 probable (52%), n = 33 definite (13%)) in the discovery cohort and 704 patients with definite PSP in the validation cohort. Sanger sequencing of all LRP10 exons and exon-intron boundaries was performed in the discovery cohort, and whole-exome sequencing was performed in the validation cohort.

SparkINFERNO: a scalable high-throughput pipeline for inferring molecular mechanisms of non-coding genetic variants.

Summary: We report Spark-based INFERence of the molecular mechanisms of NOn-coding genetic variants (SparkINFERNO), a scalable bioinformatics pipeline characterizing non-coding genome-wide association study (GWAS) association findings. SparkINFERNO prioritizes causal variants underlying GWAS association signals and reports relevant regulatory elements, tissue contexts and plausible target genes they affect. To achieve this, the SparkINFERNO algorithm integrates GWAS summary statistics with large-scale collection of functional genomics datasets spanning enhancer activity, transcription factor binding, expression quantitative trait loci and other functional datasets across more than 400 tissues and cell types.

HIPPIE2: a method for fine-scale identification of physically interacting chromatin regions.

Most regulatory chromatin interactions are mediated by various transcription factors (TFs) and involve physically interacting elements such as enhancers, insulators or promoters. To map these elements and interactions at a fine scale, we developed HIPPIE2 that analyzes raw reads from high-throughput chromosome conformation (Hi-C) experiments to identify precise loci of DNA physically interacting regions (PIRs). Unlike standard genome binning approaches (e.

Transmission of tauopathy strains is independent of their isoform composition.

The deposition of pathological tau is a common feature in several neurodegenerative tauopathies. Although equal ratios of tau isoforms with 3 (3R) and 4 (4R) microtubule-binding repeats are expressed in the adult human brain, the pathological tau from different tauopathies have distinct isoform compositions and cell type specificities. The underlying mechanisms of tauopathies are unknown, partially due to the lack of proper models.

Inferring the Molecular Mechanisms of Noncoding Alzheimer's Disease-Associated Genetic Variants.

Most of the loci identified by genome-wide association studies (GWAS) for late-onset Alzheimer's disease (LOAD) are in strong linkage disequilibrium (LD) with nearby variants all of which could be the actual functional variants, often in non-protein-coding regions and implicating underlying gene regulatory mechanisms. We set out to characterize the causal variants, regulatory mechanisms, tissue contexts, and target genes underlying these associations. We applied our INFERNO algorithm to the top 19 non-APOE loci from the IGAP GWAS study.

C9orf72 intermediate repeats are associated with corticobasal degeneration, increased C9orf72 expression and disruption of autophagy.

Microsatellite repeat expansion disease loci can exhibit pleiotropic clinical and biological effects depending on repeat length. Large expansions in C9orf72 (100s-1000s of units) are the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). However, whether intermediate expansions also contribute to neurodegenerative disease is not well understood.

DASHR 2.0: integrated database of human small non-coding RNA genes and mature products.

Motivation: Small non-coding RNAs (sncRNAs, <100 nts) are highly abundant RNAs that regulate diverse and often tissue-specific cellular processes by associating with transcription factor complexes or binding to mRNAs. While thousands of sncRNA genes exist in the human genome, no single resource provides searchable, unified annotation, expression and processing information for full sncRNA transcripts and mature RNA products derived from these larger RNAs.

Results: Our goal is to establish a complete catalog of annotation, expression, processing, conservation, tissue-specificity and other biological features for all human sncRNA genes and mature products derived from all major RNA classes.

Ancestral origin of ApoE ε4 Alzheimer disease risk in Puerto Rican and African American populations.

The ApoE ε4 allele is the most significant genetic risk factor for late-onset Alzheimer disease. The risk conferred by ε4, however, differs across populations, with populations of African ancestry showing lower ε4 risk compared to those of European or Asian ancestry. The cause of this heterogeneity in risk effect is currently unknown; it may be due to environmental or cultural factors correlated with ancestry, or it may be due to genetic variation local to the ApoE region that differs among populations.

INFERNO: inferring the molecular mechanisms of noncoding genetic variants.

The majority of variants identified by genome-wide association studies (GWAS) reside in the noncoding genome, affecting regulatory elements including transcriptional enhancers. However, characterizing their effects requires the integration of GWAS results with context-specific regulatory activity and linkage disequilibrium annotations to identify causal variants underlying noncoding association signals and the regulatory elements, tissue contexts, and target genes they affect. We propose INFERNO, a novel method which integrates hundreds of functional genomics datasets spanning enhancer activity, transcription factor binding sites, and expression quantitative trait loci with GWAS summary statistics.

Replication of progressive supranuclear palsy genome-wide association study identifies SLCO1A2 and DUSP10 as new susceptibility loci.

Background: Progressive supranuclear palsy (PSP) is a parkinsonian neurodegenerative tauopathy affecting brain regions involved in motor function, including the basal ganglia, diencephalon and brainstem. While PSP is largely considered to be a sporadic disorder, cases with suspected familial inheritance have been identified and the common MAPT H1haplotype is a major genetic risk factor. Due to the relatively low prevalence of PSP, large sample sizes can be difficult to achieve, and this has limited the ability to detect true genetic risk factors at the genome-wide statistical threshold for significance in GWAS data.

SPAR: small RNA-seq portal for analysis of sequencing experiments.

The introduction of new high-throughput small RNA sequencing protocols that generate large-scale genomics datasets along with increasing evidence of the significant regulatory roles of small non-coding RNAs (sncRNAs) have highlighted the urgent need for tools to analyze and interpret large amounts of small RNA sequencing data. However, it remains challenging to systematically and comprehensively discover and characterize sncRNA genes and specifically-processed sncRNA products from these datasets. To fill this gap, we present Small RNA-seq Portal for Analysis of sequencing expeRiments (SPAR), a user-friendly web server for interactive processing, analysis, annotation and visualization of small RNA sequencing data.

Identification of seven novel loci associated with amino acid levels using single-variant and gene-based tests in 8545 Finnish men from the METSIM study.

Comprehensive metabolite profiling captures many highly heritable traits, including amino acid levels, which are potentially sensitive biomarkers for disease pathogenesis. To better understand the contribution of genetic variation to amino acid levels, we performed single variant and gene-based tests of association between nine serum amino acids (alanine, glutamine, glycine, histidine, isoleucine, leucine, phenylalanine, tyrosine, and valine) and 16.6 million genotyped and imputed variants in 8545 non-diabetic Finnish men from the METabolic Syndrome In Men (METSIM) study with replication in Northern Finland Birth Cohort (NFBC1966).