Next-gen sequencing identifies non-coding variation disrupting miRNA-binding sites in neurological disorders

Understanding the genetic factors underlying neurodevelopmental and neuropsychiatric disorders is a major challenge given their prevalence and potential severity for quality of life. While large-scale genomic screens have made major advances in this area, for many disorders the genetic underpinnings are complex and poorly understood. To date the field has focused predominantly on protein coding variation, but given the importance of tightly controlled gene expression for normal brain development and disorder, variation that affects non-coding regulatory regions of the genome is likely to play an important role in these phenotypes. Herein we show the importance of 3 prime untranslated region (3'UTR) non-coding regulatory variants across neurodevelopmental and neuropsychiatric disorders. We devised a pipeline for identifying and functionally validating putatively pathogenic variants from next generation sequencing (NGS) data. We applied this pipeline to a cohort of children with severe specific language impairment (SLI) and identified a functional, SLI-associated variant affecting gene regulation in cells and post-mortem human brain. This variant and the affected gene (ARHGEF39) represent new putative risk factors for SLI. Furthermore, we identified 3'UTR regulatory variants across autism, schizophrenia and bipolar disorder NGS cohorts demonstrating their impact on neurodevelopmental and neuropsychiatric disorders. Our findings show the importance of investigating non-coding regulatory variants when determining risk factors contributing to neurodevelopmental and neuropsychiatric disorders. In the future, integration of such regulatory variation with protein coding changes will be essential for uncovering the genetic causes of complex neurological disorders and the fundamental mechanisms underlying health and disease

Genome-wide characterization of genetic variants and putative regions under selection in meat and egg-type chicken lines

Abstract\ud \ud Background\ud Meat and egg-type chickens have been selected for several generations for different traits. Artificial and natural selection for different phenotypes can change frequency of genetic variants, leaving particular genomic footprints throghtout the genome. Thus, the aims of this study were to sequence 28 chickens from two Brazilian lines (meat and white egg-type) and use this information to characterize genome-wide genetic variations, identify putative regions under selection using Fst method, and find putative pathways under selection.\ud \ud \ud Results\ud A total of 13.93 million SNPs and 1.36 million INDELs were identified, with more variants detected from the broiler (meat-type) line. Although most were located in non-coding regions, we identified 7255 intolerant non-synonymous SNPs, 512 stopgain/loss SNPs, 1381 frameshift and 1094 non-frameshift INDELs that may alter protein functions. Genes harboring intolerant non-synonymous SNPs affected metabolic pathways related mainly to reproduction and endocrine systems in the white-egg layer line, and lipid metabolism and metabolic diseases in the broiler line. Fst analysis in sliding windows, using SNPs and INDELs separately, identified over 300 putative regions of selection overlapping with more than 250 genes. For the first time in chicken, INDEL variants were considered for selection signature analysis, showing high level of correlation in results between SNP and INDEL data. The putative regions of selection signatures revealed interesting candidate genes and pathways related to important phenotypic traits in chicken, such as lipid metabolism, growth, reproduction, and cardiac development.\ud \ud \ud Conclusions\ud In this study, Fst method was applied to identify high confidence putative regions under selection, providing novel insights into selection footprints that can help elucidate the functional mechanisms underlying different phenotypic traits relevant to meat and egg-type chicken lines. In addition, we generated a large catalog of line-specific and common genetic variants from a Brazilian broiler and a white egg layer line that can be used for genomic studies involving association analysis with phenotypes of economic interest to the poultry industry.CB received a fellowship from the program Science Without Borders - National Council for Scientific and Technological Development (CNPq, grant 370620/2013–5). GCMM and TFG received fellowships from São Paulo Research Foundation (FAPESP, grants 14/21380–9 and 15/00616–7). LLC is recipient of productivity fellowship from CNPq. This project was funded by São Paulo Research Foundation (FAPESP) - thematic project (2014/08704–0)

An Unbiased Method for Detection of Genome-Wide Off-Target Effects in Cell Lines Treated with Zinc Finger Nucleases

We describe a method for detecting and validating genomic aberrations arising from cell lines exposed to zinc finger nucleases (ZFNs), an important reagent used for targeted genome modifications. This method makes use of cloned cell lines, an approach that adds power when testing variables that may affect gene correction efficiency and evaluating potential side effects on a genome-wide scale. After cell treatment, the genomic DNA isolation method, as described, is ideal for high-resolution array comparative genomic hybridization (aCGH) and quantitative PCR. Guidelines for aCGH analysis and calling significant copy number variations (CNVs) for validation by qPCR are also discussed. Using this method, we describe a novel ZFN-associated chromosome 4 copy number variation (CNV) attributable to a predicted ZFN off-target cleavage site found within the CNV