Nimbus: a design-driven analyses suite for amplicon-based NGS data.

Motivation: PCR-based DNA enrichment followed by massively parallel sequencing is a straightforward and cost effective method to sequence genes up to high depth. The full potential of amplicon-based sequencing assays is currently not achieved as analysis methods do not take into account the source amplicons of the detected variants. Tracking the source amplicons has the potential to identify systematic biases, enhance variant calling and improve the designs of future assays. Results: We present Nimbus, a software suite for the analysis of amplicon-based sequencing data. Nimbus includes tools for data pre-processing, alignment, single nucleotide polymorphism (SNP), insertion and deletion calling, quality control and visualization. Nimbus can detect SNPs in its alignment seeds and reduces alignment issues by the usage of decoy amplicons. Tracking the amplicons throughout analysis allows easy and fast design optimization by amplicon performance comparison. It enables detection of probable false positive variants present in a single amplicon from real variants present in multiple amplicons and provides multiple sample visualization. Nimbus was tested using HaloPlex Exome datasets and outperforms other callers for low-frequency variants. The variants called by Nimbus were highly concordant between twin samples and SNP-arrays. The Nimbus suite provides an end-to-end solution for variant calling, design optimization and visualization of amplicon-derived next-generation sequencing datasets. Availability and implementation: https://github.com/erasmus-center-for-biomics/Nimbus. Supplementary information: Supplementary data are available at Bioinformatics online.

A rare missense variant in RCL1 segregates with depression in extended families.

Depression is the most prevalent psychiatric disorder with a complex and elusive etiology that is moderately heritable. Identification of genes would greatly facilitate the elucidation of the biological mechanisms underlying depression, however, its complex etiology has proved to be a major bottleneck in the identification of its genetic risk factors, especially in genome-wide association-like studies. In this study, we exploit the properties of a genetic isolate and its family-based structure to explore whether relatively rare exonic variants influence the burden of depressive symptoms in families. Using a multistep approach involving linkage and haplotype analyses followed by exome sequencing in the Erasmus Rucphen Family (ERF) study, we identified a rare (minor allele frequency (MAF)=1%) missense c.1114C>T mutation (rs115482041) in the RCL1 gene segregating with depression across multiple generations. Rs115482041 showed significant association with depressive symptoms (N=2393, ßT-allele=2.33, P-value=1 × 10-4) and explained 2.9% of the estimated genetic variance of depressive symptoms (22%) in ERF. Despite being twice as rare (MAF<0.5%), c.1114C>T showed similar effect and significant association with depressive symptoms in samples from the independent population-based Rotterdam study (N=1604, ßT-allele=3.60, P-value=3 × 10-2). A comparison of RCL1 expression in human and mouse brain revealed a striking co-localization of RCL1 with the layer 1 interlaminar subclass of astrocytes found exclusively in higher-order primates. Our findings identify RCL1 as a novel candidate gene for depression and offer insights into mechanisms through which RCL1 may be relevant for depression.

NARWHAL, a primary analysis pipeline for NGS data.

UNLABELLED: The NARWHAL software pipeline has been developed to automate the primary analysis of Illumina sequencing data. This pipeline combines a new and flexible de-multiplexing tool with open-source aligners and automated quality assessment. The entire pipeline can be run using only one simple sample-sheet for diverse sequencing applications. NARWHAL creates a sample-oriented data structure and outperforms existing tools in speed. AVAILABILITY: https://trac.nbic.nl/narwhal/.