Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

Integrative Genomics Viewer

https://www.cell.com/neuron/pdf/S0896-6273(15)00773-4.pdf

Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci.

Autism spectrum disorder is a construct used to describe individuals with a specific combination of impairments in social communication and repetitive behaviours, highly restricted interests and/or sensory behaviours beginning early in life. The worldwide prevalence of autism is just under 1%, but estimates are higher in high-income countries. Although gross brain pathology is not characteristic of autism, subtle anatomical and functional differences have been observed in post-mortem, neuroimaging and electrophysiological studies. Initially, it was hoped that accurate measurement of behavioural phenotypes would lead to specific genetic subtypes, but genetic findings have mainly applied to heterogeneous groups that are not specific to autism. Psychosocial interventions in children can improve specific behaviours, such as joint attention, language and social engagement, that may affect further development and could reduce symptom severity. However, further research is necessary to identify the long-term needs of people with autism, and treatments and the mechanisms behind them that could result in improved independence and quality of life over time. Families are often the major source of support for people with autism throughout much of life and need to be considered, along with the perspectives of autistic individuals, in both research and practice.

/pdf/autism-spectrum-disorder-55g4bscnxz.pdf

Autism spectrum disorder

To assess the relative impact of inherited and de novo variants on autism risk, we generated a comprehensive set of exonic single-nucleotide variants (SNVs) and copy number variants (CNVs) from 2,377 families with autism. We find that private, inherited truncating SNVs in conserved genes are enriched in probands (odds ratio = 1.14, P = 0.0002) in comparison to unaffected siblings, an effect involving significant maternal transmission bias to sons. We also observe a bias for inherited CNVs, specifically for small (<100 kb), maternally inherited events (P = 0.01) that are enriched in CHD8 target genes (P = 7.4 × 10(-3)). Using a logistic regression model, we show that private truncating SNVs and rare, inherited CNVs are statistically independent risk factors for autism, with odds ratios of 1.11 (P = 0.0002) and 1.23 (P = 0.01), respectively. This analysis identifies a second class of candidate genes (for example, RIMS1, CUL7 and LZTR1) where transmitted mutations may create a sensitized background but are unlikely to be completely penetrant.

Excess of rare, inherited truncating mutations in autism.

Over the past few years, substantial effort has been put into the functional annotation of variation in human genome sequences. Such annotations can have a critical role in identifying putatively causal variants for a disease or trait among the abundant natural variation that occurs at a locus of interest. The main challenges in using these various annotations include their large numbers and their diversity. Here we develop an unsupervised approach to integrate these different annotations into one measure of functional importance (Eigen) that, unlike most existing methods, is not based on any labeled training data. We show that the resulting meta-score has better discriminatory ability using disease-associated and putatively benign variants from published studies (in both coding and noncoding regions) than the recently proposed CADD score. Across varied scenarios, the Eigen score performs generally better than any single individual annotation, representing a powerful single functional score that can be incorporated in fine-mapping studies.

/pdf/a-spectral-approach-integrating-functional-genomic-3dhgo49hb7.pdf

A spectral approach integrating functional genomic annotations for coding and noncoding variants

http://d-scholarship.pitt.edu/24720/1/1%2Ds2.0%2DS2211124714007608%2Dmain.pdf

De Novo Insertions and Deletions of Predominantly Paternal Origin Are Associated with Autism Spectrum Disorder

Abstract Background Melanoma, the deadliest of skin cancers, has a high propensity to form brain metastases that are associated with a markedly worsened prognosis. In spite of recent therapeutic advances, melanoma brain lesions remain a clinical challenge, biomarkers predicting brain dissemination are not clear and differences with other metastatic sites are poorly understood. Methods We examined a genetically diverse panel of human-derived melanoma brain metastasis (MBM) and extracranial cell lines using targeted sequencing, a Reverse Phase Protein Array, protein expression analyses, and functional studies in vitro and in vivo. Results Brain-specific genetic alterations were not detected; however, MBM cells in vitro displayed lower proliferation rates and MBM-specific protein expression patterns associated with proliferation, DNA damage, adhesion, and migration. MBM lines displayed higher levels of RAC1 expression, involving a distinct RAC1-PAK1-JNK1 signaling network. RAC1 knockdown or treatment with small molecule inhibitors contributed to a less aggressive MBM phenotype in vitro, while RAC1 knockdown in vivo led to reduced tumor volumes and delayed tumor appearance. Proliferation, adhesion, and migration were higher in MBM vs nonMBM lines in the presence of insulin or brain-derived factors and were affected by RAC1 levels. Conclusions Our findings indicate that despite their genetic variability, MBM engage specific molecular processes such as RAC1 signaling to adapt to the brain microenvironment and this can be used for the molecular characterization and treatment of brain metastases.

/pdf/a-distinct-pattern-of-growth-and-rac1-signaling-in-melanoma-36owjq99.pdf

Sinem M. Sertel

Papers

De Novo Insertions and Deletions of Predominantly Paternal Origin Are Associated with Autism Spectrum Disorder

A distinct pattern of growth and RAC1 signaling in melanoma brain metastasis cells