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.

BackgroundThe process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly.ResultsIn Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies.ConclusionsMany current genome assemblers produced useful assemblies, containing a significant representation of their genes and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another.

Transcriptome and genome data from twenty stony coral species and a selection of reference bilaterians were studied to elucidate coral evolutionary history. We identified genes that encode the proteins responsible for the precipitation and aggregation of the aragonite skeleton on which the organisms live, and revealed a network of environmental sensors that coordinate responses of the host animals to temperature, light, and pH. Furthermore, we describe a variety of stress-related pathways, including apoptotic pathways that allow the host animals to detoxify reactive oxygen and nitrogen species that are generated by their intracellular photosynthetic symbionts, and determine the fate of corals under environmental stress. Some of these genes arose through horizontal gene transfer and comprise at least 0.2% of the animal gene inventory. Our analysis elucidates the evolutionary strategies that have allowed symbiotic corals to adapt and thrive for hundreds of millions of years.DOI: http://dx.doi.org/10.7554/eLife.13288.001

Natural history collections are unparalleled repositories of geographical and temporal variation in faunal conditions. Molecular studies offer an opportunity to uncover much of this variation; however, genetic studies of historical museum specimens typically rely on extracting highly degraded and chemically modified DNA samples from skins, skulls or other dried samples. Despite this limitation, obtaining short fragments of DNA sequences using traditional PCR amplification of DNA has been the primary method for genetic study of historical specimens. Few laboratories have succeeded in obtaining genome-scale sequences from historical specimens and then only with considerable effort and cost. Here, we describe a low-cost approach using high-throughput next-generation sequencing to obtain reliable genome-scale sequence data from a traditionally preserved mammal skin and skull using a simple extraction protocol. We show that single-nucleotide polymorphisms (SNPs) from the genome sequences obtained independently from the skin and from the skull are highly repeatable compared to a reference genome.