aTRAM - automated target restricted assembly method: a fast method for assembling loci across divergent taxa from next-generation sequencing data

Abstract

BackgroundAssembling genes from next-generation sequencing data is not only time consuming but computationally difficult, particularly for taxa without a closely related reference genome. Assembling even a draft genome using de novo approaches can take days, even on a powerful computer, and these assemblies typically require data from a variety of genomic libraries. Here we describe software that will alleviate these issues by rapidly assembling genes from distantly related taxa using a single library of paired-end reads: aTRAM, automated Target Restricted Assembly Method. The aTRAM pipeline uses a reference sequence, BLAST, and an iterative approach to target and locally assemble the genes of interest.ResultsOur results demonstrate that aTRAM rapidly assembles genes across distantly related taxa. In comparative tests with a closely related taxon, aTRAM assembled the same sequence as reference-based and de novo approaches taking on average < 1 min per gene. As a test case with divergent sequences, we assembled >1,000 genes from six taxa ranging from 25 – 110 million years divergent from the reference taxon. The gene recovery was between 97 – 99% from each taxon.ConclusionsaTRAM can quickly assemble genes across distantly-related taxa, obviating the need for draft genome assembly of all taxa of interest. Because aTRAM uses a targeted approach, loci can be assembled in minutes depending on the size of the target. Our results suggest that this software will be useful in rapidly assembling genes for phylogenomic projects covering a wide taxonomic range, as well as other applications. The software is freely available http://www.github.com/juliema/aTRAM.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0515-2) contains supplementary material, which is available to authorized users.

Genomic sequence capture of haemosporidian parasites: Methods and prospects for enhanced study of host–parasite evolution

“…These settings include trimming reads with lengths <40 (MINLEN:40), bases at the start of a read with quality scores <5 (LEADING:5), bases at the end of a read with scores <15 (TRAILING:15) and bases in a sliding window where four consecutive bases have an average quality <15 (SLIDINGWINDOW:4:15). We then used the automated Target Restricted Assembly Method, atram 2.0 (Allen et al, ; http://www.github.com/juliema/aTRAM) to assemble haemosporidian parasite genes using the 498 reference Haemoproteus gene sequences. This approach uses local blast searches and an iterative approach to produce assemblies for genes of interest from cleaned read data.…”

“…We also describe our bioinformatics pipeline using atram 2.0 (Allen, Huang, Cronk, & Johnson, 2015;Allen, LaFrance, Folk, Johnson, & Guralnick, 2018) for locus assembly and phyluce (Faircloth, 2015) and custom PERL and Python scripts for downstream processing.…”

Integrating phylogenomic and population genomic patterns in avian lice provides a more complete picture of parasite evolution

“…First, we used aTRAM (Allen et al. ) to assemble exons for the Physconelloides emersoni library sequenced at a higher depth. Of the three higher coverage libraries, this sample had the highest predicted depth after quality control (Sample 1, Table S1).…”

“…To obtain orthologous sequences for downstream analysis, we developed a novel approach to assemble and map the cleaned genomic data. First, we used aTRAM (Allen et al 2015) to assemble exons for the Physconelloides emersoni library sequenced at a higher depth. Of the three higher coverage libraries, this sample had the highest predicted depth after quality control (Sample 1, Table S1).…”

Applying evolutionary genetics to developmental toxicology and risk assessment

“…The National Center for Biotechnology Information (NCBI) Taxonomy Browser organizes DNA sequences from multiple databases into a taxonomy tree, covering about 10% of all known eukaryotic species (Acland et al 2014). If the species of interest has not been covered in NCBI, then gene identification and annotation can be done using next-generation sequencing and sequence alignment software (Allen et al 2015). These bioinformatics tools are invaluable in developing novel models of morphogenesis and developmental toxicity.…”