A Galaxy-based training resource for single-cell RNA-sequencing quality control and analyses.

BACKGROUND: It is not a trivial step to move from single-cell RNA-sequencing (scRNA-seq) data production to data analysis. There is a lack of intuitive training materials and easy-to-use analysis tools, and researchers can find it difficult to master the basics of scRNA-seq quality control and the later analysis. RESULTS: We have developed a range of practical scripts, together with their corresponding Galaxy wrappers, that make scRNA-seq training and quality control accessible to researchers previously daunted by the prospect of scRNA-seq analysis. We implement a "visualize-filter-visualize" paradigm through simple command line tools that use the Loom format to exchange data between the tools. The point-and-click nature of Galaxy makes it easy to assess, visualize, and filter scRNA-seq data from short-read sequencing data. CONCLUSION: We have developed a suite of scRNA-seq tools that can be used for both training and more in-depth analyses.

A quantitative framework for characterizing the evolutionary history of mammalian gene expression.

The evolutionary history of a gene helps predict its function and relationship to phenotypic traits. Although sequence conservation is commonly used to decipher gene function and assess medical relevance, methods for functional inference from comparative expression data are lacking. Here, we use RNA-seq across seven tissues from 17 mammalian species to show that expression evolution across mammals is accurately modeled by the Ornstein-Uhlenbeck process, a commonly proposed model of continuous trait evolution. We apply this model to identify expression pathways under neutral, stabilizing, and directional selection. We further demonstrate novel applications of this model to quantify the extent of stabilizing selection on a gene's expression, parameterize the distribution of each gene's optimal expression level, and detect deleterious expression levels in expression data from individual patients. Our work provides a statistical framework for interpreting expression data across species and in disease.

An improved assembly and annotation of the allohexaploid wheat genome identifies complete families of agronomic genes and provides genomic evidence for chromosomal translocations.

Advances in genome sequencing and assembly technologies are generating many high-quality genome sequences, but assemblies of large, repeat-rich polyploid genomes, such as that of bread wheat, remain fragmented and incomplete. We have generated a new wheat whole-genome shotgun sequence assembly using a combination of optimized data types and an assembly algorithm designed to deal with large and complex genomes. The new assembly represents >78% of the genome with a scaffold N50 of 88.8 kb that has a high fidelity to the input data. Our new annotation combines strand-specific Illumina RNA-seq and Pacific Biosciences (PacBio) full-length cDNAs to identify 104,091 high-confidence protein-coding genes and 10,156 noncoding RNA genes. We confirmed three known and identified one novel genome rearrangements. Our approach enables the rapid and scalable assembly of wheat genomes, the identification of structural variants, and the definition of complete gene models, all powerful resources for trait analysis and breeding of this key global crop.

Exome sequencing of lymphomas from three dog breeds reveals somatic mutation patterns reflecting genetic background.

Lymphoma is the most common hematological malignancy in developed countries. Outcome is strongly determined by molecular subtype, reflecting a need for new and improved treatment options. Dogs spontaneously develop lymphoma, and the predisposition of certain breeds indicates genetic risk factors. Using the dog breed structure, we selected three lymphoma predisposed breeds developing primarily T-cell (boxer), primarily B-cell (cocker spaniel), and with equal distribution of B- and T-cell lymphoma (golden retriever), respectively. We investigated the somatic mutations in B- and T-cell lymphomas from these breeds by exome sequencing of tumor and normal pairs. Strong similarities were evident between B-cell lymphomas from golden retrievers and cocker spaniels, with recurrent mutations in TRAF3-MAP3K14 (28% of all cases), FBXW7 (25%), and POT1 (17%). The FBXW7 mutations recurrently occur in a specific codon; the corresponding codon is recurrently mutated in human cancer. In contrast, T-cell lymphomas from the predisposed breeds, boxers and golden retrievers, show little overlap in their mutation pattern, sharing only one of their 15 most recurrently mutated genes. Boxers, which develop aggressive T-cell lymphomas, are typically mutated in the PTEN-mTOR pathway. T-cell lymphomas in golden retrievers are often less aggressive, and their tumors typically showed mutations in genes involved in cellular metabolism. We identify genes with known involvement in human lymphoma and leukemia, genes implicated in other human cancers, as well as novel genes that could allow new therapeutic options.