Source code and user manual are available at http://sourceforge.net/projects/soapdenovotrans/.

The advent of next generation sequencing (NGS) has enabled investigations of the gut microbiome with unprecedented resolution and throughput. This has stimulated the development of sophisticated bioinformatics tools to analyze the massive amounts of data generated. Researchers therefore need a clear understanding of the key concepts required for the design, execution and interpretation of NGS experiments on microbiomes. We conducted a literature review and used our own data to determine which approaches work best. The two main approaches for analyzing the microbiome, 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics, are illustrated with analyses of libraries designed to highlight their strengths and weaknesses. Several methods for taxonomic classification of bacterial sequences are discussed. We present simulations to assess the number of sequences that are required to perform reliable appraisals of bacterial community structure. To the extent that fluctuations in the diversity of gut bacterial populations correlate with health and disease, we emphasize various techniques for the analysis of bacterial communities within samples (α-diversity) and between samples (β-diversity). Finally, we demonstrate techniques to infer the metabolic capabilities of a bacteria community from these 16S and shotgun data.

clinicaltrials.gov Identifier: NCT02254811.

Next-generation sequencing plays a central role in the characterization and quantification of transcriptomes. Although numerous metrics are purported to quantify the quality of RNA, there have been no large-scale empirical evaluations of the major determinants of sequencing success. We used a combination of existing and newly developed methods to isolate total RNA from 1115 samples from 695 plant species in 324 families, which represents >900 million years of phylogenetic diversity from green algae through flowering plants, including many plants of economic importance. We then sequenced 629 of these samples on Illumina GAIIx and HiSeq platforms and performed a large comparative analysis to identify predictors of RNA quality and the diversity of putative genes (scaffolds) expressed within samples. Tissue types (e.g., leaf vs. flower) varied in RNA quality, sequencing depth and the number of scaffolds. Tissue age also influenced RNA quality but not the number of scaffolds ≥1000 bp. Overall, 36% of the variation in the number of scaffolds was explained by metrics of RNA integrity (RIN score), RNA purity (OD 260/230), sequencing platform (GAIIx vs HiSeq) and the amount of total RNA used for sequencing. However, our results show that the most commonly used measures of RNA quality (e.g., RIN) are weak predictors of the number of scaffolds because Illumina sequencing is robust to variation in RNA quality. These results provide novel insight into the methods that are most important in isolating high quality RNA for sequencing and assembling plant transcriptomes. The methods and recommendations provided here could increase the efficiency and decrease the cost of RNA sequencing for individual labs and genome centers.

Article first published online 29 April 2015.

Mycosis fungoides (MF), the most common type of cutaneous T-cell lymphoma, is believed to represent a clonal expansion of a transformed skin-resident memory T cell. T-cell receptor (TCR) clonality (ie, identical sequences of rearranged TCRα, TCRβ, and TCRγ), the key premise of this hypothesis, has been difficult to document conclusively because malignant cells are not readily distinguishable from the tumor-infiltrating reactive lymphocytes that contribute to the TCR clonotypic repertoire of MF. Here, we have successfully adopted targeted whole-exome sequencing (WES) to identify the repertoire of rearranged TCR genes in tumor-enriched samples from patients with MF. Although some of the investigated MF biopsies had the expected frequency of monoclonal rearrangements of TCRγ corresponding to that of tumor cells, the majority of the samples presented multiple TCRγ, TCRα, and TCRβ clonotypes by WES. Our findings are compatible with the model in which the initial malignant transformation in MF does not occur in mature memory T cells but rather at the level of T-lymphocyte progenitors before TCRβ or TCRα rearrangements. We have also shown that WES can be combined with whole-transcriptome sequencing in the same sample, which enables comprehensive characterization of the TCR repertoire in relation to tumor content. WES/whole-transcriptome sequencing might be applicable to other types of T-cell lymphomas to determine clonal dominance and clonotypic heterogeneity in these malignancies.

Mycosis fungoides (MF) is a slowly progressive cutaneous T-cell lymphoma (CTCL) for which there is no cure. In the early plaque stage the disease is indolent, but development of tumors heralds an increased risk of metastasis and death. Previous research into the genomic landscape of CTCL revealed a complex pattern of >50 driver mutations implicated in more than a dozen of signaling pathways. However, the genomic mechanisms governing disease progression and treatment resistance remain unknown. Building on our previous discovery of the clonotypic heterogeneity of MF, we hypothesized that this lymphoma does not progress in a linear fashion as currently thought, but comprises heterogeneous mutational subclones. We sequenced exomes of 49 cases of MF and identified 28 previously unreported putative driver genes. MF exhibited extensive intratumoral heterogeneity (ITH) of a median of six subclones showing branched pattern of phylogenetic relationships. Stage progression was correlated with an increase in ITH and redistribution of mutations from the stem to the clades. The pattern of clonal driver mutations was highly variable with no consistent mutations between patients. A similar intratumoral heterogeneity was detected in leukemic CTCL (Sézary syndrome). Based on these findings we propose a model of the pathogenesis of MF comprising neutral, divergent evolution of cancer subclones and discuss how ITH impacts the efficacy of targeted drug therapies and immunotherapies of CTCL.

Iyer and colleagues used deep sequencing of T-cell receptor genes to demonstrate clonal heterogeneity of mycosis fungoides, with repeated seeding of disparate clones from the blood.