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Current efforts in cellular disease modeling and regenerative medicine are limited by the paucity of cell types that can be generated in the laboratory. A new study introduces a computational framework, Mogrify, that uses network biology to predict combinations of transcription factors necessary for direct conversion between human cell types to ameliorate this issue.
The migration of cancer genomics data to cloud computing is a great encouragement for data reuse and integration by bioinformaticians and other data symbionts. Because the cloud allows rapid, transparent and reproducible research on large data sets, we are keen to consider articles and analyses submitted to the journal that provide peer referee access to their constituent cloud projects.
The integration of large, well-sampled collections of bacterial isolates with genomics and experimental methods provides opportunities for 'top-down' discovery of the genetic basis of phenotypes of interest. In a new report, the authors apply this approach to investigate the heterogeneity in manifestations of disease caused by Listeria monocytogenes and demonstrate that a previously uncharacterized cellobiose PTS system is involved in central nervous system infection.
David Solit and colleagues report that inactivating CDH1 mutations are found in 84% of plasmacytoid bladder cancer samples tested and are not found in other bladder cancer subtypes. CRISPR/Cas9-mediated knockout of CDH1 in cell lines leads to enhanced cellular migration.
Steven McCarroll and colleagues present a detailed study of copy number variation of exons within the human HP (haptoglobin) gene. They show that HP exons undergo recurring deletions that, together with local SNP variation, influence LDL and total cholesterol levels in human populations.
Andy Dahl and colleagues present a method for imputing missing phenotype data in genetic studies with multiple correlated phenotypes where samples can have any level of relatedness. They apply their method to simulated and real data sets and show that it improves the sensitivity to detect association signals.
David Bertioli and colleagues report the genomes of Arachis duranensis and Arachis ipaensis, the diploid ancestors of cultivated peanut, Arachis hypogaea. Their analyses are a first step in understanding the evolution of the peanut's tetraploid genome.
Jun Yang and colleagues perform targeted sequencing of NUDT15 and identify loss-of-function variants associated with thiopurine intolerance. Functionally, they show that NUDT15 inactivates thiopurine metabolites, providing a mechanism to explain the association between NUDT15 loss-of-function variants and thiopurine toxicity.
Friedhelm Hildebrandt and colleagues identify mutations in NUP93, NUP205 or XPO5 in patients with steroid-resistant nephrotic syndrome. They show that NUP93 and XPO5 interact with SMAD4 and that NUP93 mutations interfere with BMP7-SMAD4 signaling in podocytes.
Varun Aggarwala and Benjamin Voight analyze human polymorphism data and develop an expanded sequence context model that explains >81% of variability in substitution probabilities, highlighting mutation-promoting motifs. Using their model, they present substitution intolerance scores for genes and a new intolerance score for amino acids, and demonstrate clinical use of the model in neuropsychiatric diseases.
Daniel Gudbjartsson, Kari Stefansson and colleagues propose a new weighted Bonferroni approach for determining significance thresholds for human genome-wide association studies (GWAS). They demonstrate that the weighted approach, which is based on sequence annotation enrichments, improves power over standard GWAS methods.
Alexander Gusev, Bogdan Pasaniuc and colleagues present a strategy that integrates gene expression measurements with summary statistics from large-scale genome-wide association studies to identify genes whose cis-regulated expression is associated with complex traits. They identify 69 new genes significantly associated with obesity-related traits and illustrate how this approach can provide insights into the genetic basis of complex traits.
Justin Crocker, Garth Ilsley and David Stern use engineered transcription factors to regulate enhancers in a quantitatively predictable manner in Drosophila embryos. Their models of enhancer function provide a framework for the quantitative control of enhancers in vivo.
Taisei Kikuchi, Mark Viney, Matthew Berriman and colleagues report the genome sequences of six species of nematodes from the Strongyloides clade of nematodes, including human and animal pathogens, facultative parasites and a free-living species. They find that expansions of the astacin and SCP/TAPS gene families are associated with parasitism in these species.
José Luis Gómez-Skarmeta, Hector Escrivá, Ignacio Maeso, Damien Devos and colleagues perform 4C-seq profiling of the Hox cluster in amphioxus embryos and find that, unlike in vertebrate embryos, the cluster is organized into a single chromatin interaction domain. They suggest that the vertebrate Hox bipartite regulatory system is an evolutionary novelty.
Keith Ligon, Adam Resnick, Rameen Beroukhim and colleagues identify MYB-QKI fusions in angiocentric gliomas and show that these rearrangements promote tumorigenesis through activation of MYB by truncation, enhancer translocation driving aberrant MYB-QKI expression and hemizygous loss of QKI.
Bradley Bernstein, Birgit Knoechel and colleagues identify super-enhancer translocations that drive overexpression of MYB in adenoid cystic carcinoma (ACC). They find that MYB binds to the translocated enhancers and to other active enhancers that drive different regulatory programs in alternate cell lineages in ACC.
Ingileif Jonsdottir, Kari Stefansson and colleagues show that variants in the HLA class II region contribute to tuberculosis risk in populations of European ancestry. They propose that the associated variants influence disease risk by altering expression of HLA class II molecules presenting protective M. tuberculosis antigens to T cells.
Marc Lecuit, Sylvain Brisse and colleagues combine Listeria monocytogenes population genomic data with human epidemiological and clinical data to study human listeriosis. They report new putative virulence factors and demonstrate that some clones are hypervirulent in a humanized mouse model of listeriosis and have enhanced neural and placental tropism.
