Dataset Information

SRAssembler: Selective Recursive local Assembly of homologous genomic regions.

ABSTRACT: BACKGROUND:The falling cost of next-generation sequencing technology has allowed deep sequencing across related species and of individuals within species. Whole genome assemblies from these data remain high time- and resource-consuming computational tasks, particularly if best solutions are sought using different assembly strategies and parameter sets. However, in many cases, the underlying research questions are not genome-wide but rather target specific genes or sets of genes. We describe a novel assembly tool, SRAssembler, that efficiently assembles only contigs containing potential homologs of a gene or protein query, thus enabling gene-specific genome studies over large numbers of short read samples. RESULTS:We demonstrate the functionality of SRAssembler with examples largely drawn from plant genomics. The workflow implements a recursive strategy by which relevant reads are successively pulled from the input sets based on overlapping significant matches, resulting in virtual chromosome walking. The typical workflow behavior is illustrated with assembly of simulated reads. Applications to real data show that SRAssembler produces homologous contigs of equivalent quality to whole genome assemblies. Settings can be chosen to not only assemble presumed orthologs but also paralogous gene loci in distinct contigs. A key application is assembly of the same locus in many individuals from population genome data, which provides assessment of structural variation beyond what can be inferred from read mapping to a reference genome alone. SRAssembler can be used on modest computing resources or used in parallel on high performance computing clusters (most easily by invoking a dedicated Singularity image). CONCLUSIONS:SRAssembler offers an efficient tool to complement whole genome assembly software. It can be used to solve gene-specific research questions based on large genomic read samples from multiple sources and would be an expedient choice when whole genome assembly from the reads is either not feasible, too costly, or unnecessary. The program can also aid decision making on the depth of sequencing in an ongoing novel genome sequencing project or with respect to ultimate whole genome assembly strategies.

SUBMITTER: McCarthy TW

PROVIDER: S-EPMC6604332 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

SRAssembler: Selective Recursive local Assembly of homologous genomic regions.

McCarthy Thomas W TW Chou Hsien-Chao HC Brendel Volker P VP

BMC bioinformatics 20190702 1

<h4>Background</h4>The falling cost of next-generation sequencing technology has allowed deep sequencing across related species and of individuals within species. Whole genome assemblies from these data remain high time- and resource-consuming computational tasks, particularly if best solutions are sought using different assembly strategies and parameter sets. However, in many cases, the underlying research questions are not genome-wide but rather target specific genes or sets of genes. We descr ...[more]

PMID: 31266441

Similar Datasets

Project description:GRAbB (Genomic Region Assembly by Baiting) is a new program that is dedicated to assemble specific genomic regions from NGS data. This approach is especially useful when dealing with multi copy regions, such as mitochondrial genome and the rDNA repeat region, parts of the genome that are often neglected or poorly assembled, although they contain interesting information from phylogenetic or epidemiologic perspectives, but also single copy regions can be assembled. The program is capable of targeting multiple regions within a single run. Furthermore, GRAbB can be used to extract specific loci from NGS data, based on homology, like sequences that are used for barcoding. To make the assembly specific, a known part of the region, such as the sequence of a PCR amplicon or a homologous sequence from a related species must be specified. By assembling only the region of interest, the assembly process is computationally much less demanding and may lead to assemblies of better quality. In this study the different applications and functionalities of the program are demonstrated such as: exhaustive assembly (rDNA region and mitochondrial genome), extracting homologous regions or genes (IGS, RPB1, RPB2 and TEF1a), as well as extracting multiple regions within a single run. The program is also compared with MITObim, which is meant for the exhaustive assembly of a single target based on a similar query sequence. GRAbB is shown to be more efficient than MITObim in terms of speed, memory and disk usage. The other functionalities (handling multiple targets simultaneously and extracting homologous regions) of the new program are not matched by other programs. The program is available with explanatory documentation at https://github.com/b-brankovics/grabb. GRAbB has been tested on Ubuntu (12.04 and 14.04), Fedora (23), CentOS (7.1.1503) and Mac OS X (10.7). Furthermore, GRAbB is available as a docker repository: brankovics/grabb (https://hub.docker.com/r/brankovics/grabb/).

Project description:Structure comparison tools can be used to align related protein structures to identify structurally conserved and variable regions and to infer functional and evolutionary relationships. While the conserved regions often superimpose well, the variable regions appear non superimposable. Differences in homologous protein structures are thought to be due to evolutionary plasticity to accommodate diverged sequences during evolution. One of the kinds of differences between 3-D structures of homologous proteins is rigid body displacement. A glaring example is not well superimposed equivalent regions of homologous proteins corresponding to ?-helical conformation with different spatial orientations. In a rigid body superimposition, these regions would appear variable although they may contain local similarity. Also, due to high spatial deviation in the variable region, one-to-one correspondence at the residue level cannot be determined accurately. Another kind of difference is conformational variability and the most common example is topologically equivalent loops of two homologues but with different conformations. In the current study, we present a refined view of the "structurally variable" regions which may contain local similarity obscured in global alignment of homologous protein structures. As structural alphabet is able to describe local structures of proteins precisely through Protein Blocks approach, conformational similarity has been identified in a substantial number of 'variable' regions in a large data set of protein structural alignments; optimal residue-residue equivalences could be achieved on the basis of Protein Blocks which led to improved local alignments. Also, through an example, we have demonstrated how the additional information on local backbone structures through protein blocks can aid in comparative modeling of a loop region. In addition, understanding on sequence-structure relationships can be enhanced through our approach. This has been illustrated through examples where the equivalent regions in homologous protein structures share sequence similarity to varied extent but do not preserve local structure.

Project description:BackgroundEmploying genomic DNA clones to characterise gene attributes has several advantages over the use of cDNA clones, including the presence of native transcription and translation regulatory sequences as well as a representation of the complete repertoire of potential splice variants encoded by the gene. However, working with genomic DNA clones has traditionally been tedious due to their large size relative to cDNA clones and the presence, absence or position of particular restriction enzyme sites that may complicate conventional in vitro cloning procedures.ResultsTo enable efficient cloning and manipulation of genomic DNA fragments for the purposes of gene expression and reporter-gene studies we have combined aspects of the Gateway system and a bacteriophage-based homologous recombination (i.e. recombineering) system. To apply the method for characterising plant genes we developed novel Gateway and plant transformation vectors that are of small size and incorporate selectable markers which enable efficient identification of recombinant clones. We demonstrate that the genomic coding region of a gene can be directly cloned into a Gateway Entry vector by recombineering enabling its subsequent transfer to Gateway Expression vectors. We also demonstrate how the coding and regulatory regions of a gene can be directly cloned into a plant transformation vector by recombineering. This construct was then rapidly converted into a novel Gateway Expression vector incorporating cognate 5' and 3' regulatory regions by using recombineering to replace the intervening coding region with the Gateway Destination cassette. Such expression vectors can be applied to characterise gene regulatory regions through development of reporter-gene fusions, using the Gateway Entry clones of GUS and GFP described here, or for ectopic expression of a coding region cloned into a Gateway Entry vector. We exemplify the utility of this approach with the Arabidopsis PAP85 gene and demonstrate that the expression profile of a PAP85::GUS transgene highly corresponds with native PAP85 expression.ConclusionWe describe a novel combination of the favourable attributes of the Gateway and recombineering systems to enable efficient cloning and manipulation of genomic DNA clones for more effective characterisation of gene function. Although the system and plasmid vectors described here were developed for applications in plants, the general approach is broadly applicable to gene characterisation studies in many biological systems.

Dataset Information

SRAssembler: Selective Recursive local Assembly of homologous genomic regions.

Publications

SRAssembler: Selective Recursive local Assembly of homologous genomic regions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets