De novo assembly of RNA-Seq data allows us to study transcriptomes without the need for a genome sequence, such as in non-model organisms of ecological and evolutionary importance, cancer samples, or the microbiome. In this protocol, we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-Seq data in non-model organisms. We also present Trinity’s supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples, and approaches to identify protein coding genes. In an included tutorial we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http://trinityrnaseq.sf.net.

Comprehensive, high-quality reference genomes are required for functional characterization and taxonomic assignment of the human gut microbiota. We present the Unified Human Gastrointestinal Genome (UHGG) collection, comprising 204,938 nonredundant genomes from 4,644 gut prokaryotes. These genomes encode >170 million protein sequences, which we collated in the Unified Human Gastrointestinal Protein (UHGP) catalog. The UHGP more than doubles the number of gut proteins in comparison to those present in the Integrated Gene Catalog. More than 70% of the UHGG species lack cultured representatives, and 40% of the UHGP lack functional annotations. Intraspecies genomic variation analyses revealed a large reservoir of accessory genes and single-nucleotide variants, many of which are specific to individual human populations. The UHGG and UHGP collections will enable studies linking genotypes to phenotypes in the human gut microbiome.

A 1000-cow study across four European countries was undertaken to understand to what extent ruminant microbiomes can be controlled by the host animal and to identify characteristics of the host rumen microbiome axis that determine productivity and methane emissions. A core rumen microbiome, phylogenetically linked and with a preserved hierarchical structure, was identified. A 39-member subset of the core formed hubs in co-occurrence networks linking microbiome structure to host genetics and phenotype (methane emissions, rumen and blood metabolites, and milk production efficiency). These phenotypes can be predicted from the core microbiome using machine learning algorithms. The heritable core microbes, therefore, present primary targets for rumen manipulation toward sustainable and environmentally friendly agriculture.

Methane emissions from ruminant livestock contribute significantly to the large environmental footprint of agriculture. The rumen is the principal source of methane, and certain features of the microbiome are associated with low/high methane phenotypes. Despite their primary role in methanogenesis, the abundance of archaea has only a weak correlation with methane emissions from individual animals. The composition of the archaeal community appears to have a stronger effect, with animals harbouring the Methanobrevibacter gottschalkii clade tending to be associated with greater methane emissions. Ciliate protozoa produce abundant H2, the main substrate for methanogenesis in the rumen, and their removal (defaunation) results in an average 11% lower methane emissions in vivo, but the results are not consistent. Different protozoal genera seem to result in greater methane emissions, though community types (A, AB, B and O) did not differ. Within the bacteria, three different ‘ruminotypes’ have been identified, two of which predispose animals to have lower methane emissions. The two low-methane ruminotypes are generally characterized by less abundant H2-producing bacteria. A lower abundance of Proteobacteria and differences in certain Bacteroidetes and anaerobic fungi seem to be associated with high methane emissions. Rumen anaerobic fungi produce abundant H2 and formate, and their abundance generally corresponds to the level of methane emissions. Thus, microbiome analysis is consistent with known pathways for H2 production and methanogenesis, but not yet in a predictive manner. The production and utilisation of formate by the ruminal microbiota is poorly understood and may be a source of variability between animals.

Background Among asymptomatic patients with severe carotid artery stenosis but no recent stroke or transient cerebral ischaemia, either carotid artery stenting (CAS) or carotid endarterectomy (CEA) can restore patency and reduce long-term stroke risks. However, from recent national registry data, each option causes about 1% procedural risk of disabling stroke or death. Comparison of their long-term protective effects requires large-scale randomised evidence.Methods ACST-2 is an international multicentre randomised trial of CAS versus CEA among asymptomatic patients with severe stenosis thought to require intervention, interpreted with all other relevant trials. Patients were eligible if they had severe unilateral or bilateral carotid artery stenosis and both doctor and patient agreed that a carotid procedure should be undertaken, but they were substantially uncertain which one to choose. Patients were randomly allocated to CAS or CEA and followed up at 1 month and then annually, for a mean 5 years. Procedural events were those within 30 days of the intervention. Intention-to-treat analyses are provided. Analyses including procedural hazards use tabular methods. Analyses and meta-analyses of non-procedural strokes use Kaplan-Meier and log-rank methods. The trial is registered with the ISRCTN registry, ISRCTN21144362.