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A well-defined risk factor and precursor for cutaneous melanoma is the dysplastic nevus. These benign tumors represent clonal hyperproliferation of melanocytes that are in a senescent-like state, but with occasional malignant transformation events. To portray the mutational repertoire of dysplastic nevi in patients with the dysplastic nevus syndrome and to determine the discriminatory profiles of melanocytic nevi (including dysplastic nevi) from melanoma, we sequenced exomes of melanocytic nevi including dysplastic nevi (n = 19), followed by a targeted gene panel (785 genes) characterization of melanocytic nevi (n = 46) and primary melanomas (n = 42). Exome sequencing revealed that dysplastic nevi harbored a substantially lower mutational load than melanomas (21 protein-changing mutations versus >100). Known "driver" mutations in genes for melanoma, including CDKN2A, TP53, NF1, RAC1, and PTEN, were not found among any melanocytic nevi sequenced. Additionally, melanocytic nevi including dysplastic nevi showed a significantly lower frequency and a different UV-associated mutational signature. These results show that although melanocytic nevi and dysplastic nevi harbor stable genomes with relatively few alterations, progression into melanomas requires additional mutational processes affecting key tumor suppressors. This study identifies molecular parameters that could be useful for diagnostic platforms., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Meiotic recombination is a fundamental evolutionary process driving diversity in eukaryotes. In mammals, recombination is known to occur preferentially at specific genomic regions. Using topological data analysis (TDA), a branch of applied topology that extracts global features from large data sets, we developed an efficient method for mapping recombination at fine scales. When compared to standard linkage-based methods, TDA can deal with a larger number of SNPs and genomes without incurring prohibitive computational costs. We applied TDA to 1,000 Genomes Project data and constructed high-resolution whole-genome recombination maps of seven human populations. Our analysis shows that recombination is generally under-represented within transcription start sites. However, the binding sites of specific transcription factors are enriched for sites of recombination. These include transcription factors that regulate the expression of meiosis- and gametogenesis-specific genes, cell cycle progression, and differentiation blockage. Additionally, our analysis identifies an enrichment for sites of recombination at repeat-derived loci matched by piwi-interacting RNAs., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Despite large-scale cancer genomics studies, key somatic mutations driving cancer, and their functional roles, remain elusive. Here, we propose that analysis of comorbidities of Mendelian diseases with cancers provides a novel, systematic way to discover new cancer genes. If germline genetic variation in Mendelian loci predisposes bearers to common cancers, the same loci may harbour cancer-associated somatic variation. Compilations of clinical records spanning over 100 million patients provide an unprecedented opportunity to assess clinical associations between Mendelian diseases and cancers. We systematically compare these comorbidities against recurrent somatic mutations from more than 5,000 patients across many cancers. Using multiple measures of genetic similarity, we show that a Mendelian disease and comorbid cancer indeed have genetic alterations of significant functional similarity. This result provides a basis to identify candidate drivers in cancers including melanoma and glioblastoma. Some Mendelian diseases demonstrate 'pan-cancer' comorbidity and shared genetics across cancers.

Nanopore sequencing promises long read-lengths and single-molecule resolution, but the stochastic motion of the DNA molecule inside the pore is, as of this writing, a barrier to high accuracy reads. We develop a method of statistical inference that explicitly accounts for this error, and demonstrate that high accuracy (>99%) sequence inference is feasible even under highly diffusive motion by using a hidden Markov model to jointly analyze multiple stochastic reads. Using this model, we place bounds on achievable inference accuracy under a range of experimental parameters., (Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Background: Viral outbreaks, such as the 2014 ebolavirus, can spread rapidly and have complex evolutionary dynamics, including coinfection and bulk transmission of multiple viral populations. Genomic surveillance can be hindered when the spread of the outbreak exceeds the evolutionary rate, in which case consensus approaches will have limited resolution. Deep sequencing of infected patients can identify genomic variants present in intrahost populations at subclonal frequencies (i.e. <50%). Shared subclonal variants (SSVs) can provide additional phylogenetic resolution and inform about disease transmission patterns., Methods: We use metrics from population genetics to analyze data from the 2014 ebolavirus outbreak in Sierra Leone and identify phylogenetic signal arising from SSVs. We use methods derived from information theory to measure a lower bound on transmission bottleneck size., Results and Conclusions: We identify several SSV that shed light on phylogenetic relationships not captured by consensus-based analyses. We find that transmission bottleneck size is larger than one founder population, yet significantly smaller than the intrahost effective population. Our results demonstrate the important role of shared subclonal variants in genomic surveillance.

The eukaryotic initiation factor 4F (eIF4F) is thought to be the first factor to bind mRNA during 7-methylguanosine (m7G) cap-dependent translation initiation. The multipartite eIF4F contains the cap-binding protein eIF4E, and it is assumed that eIF4F binds mRNAs primarily at the 5' m7G cap structure. We have analyzed equilibrium binding of rabbit eIF4F to a series of diverse RNAs and found no impact of the 5'-cap on the stability of eIF4F-RNA complexes. However, eIF4F preferentially and cooperatively binds to RNAs with a minimum length of approximately 60 nucleotides in vitro. Furthermore, translation activity in rabbit reticulocyte lysate is strongly inhibited by RNAs exceeding this length, but not by shorter ones, consistent with the notion that eIF4F in its physiological environment preferentially binds longer RNAs, too. Collectively, our results indicate that intrinsic RNA binding by eIF4F depends on a minimal RNA length, rather than on cap recognition. The nonetheless essential m7G cap may either function at steps subsequent to eIF4F-RNA binding, or other factors facilitate preferential binding of eIF4F to the m7G cap.