Enabling large‐scale next‐generation sequence assembly with Blacklight

A variety of extremely challenging biological sequence analyses were conducted on the XSEDE large shared memory resource Blacklight, using current bioinformatics tools and encompassing a wide range of scientific applications. These include genomic sequence assembly [6,12], very large metagenomic sequence assembly, transcriptome assembly [3], and sequencing error correction. The datasets used in these analyses included uncategorized fungal species, reference microbial data, very large soil and human gut microbiome sequence data, and primate transcriptomes, comprised of both short- and long-read sequence data. A new parallel command execution program was developed on the Blacklight resource to handle some of these analyses. These results represent significant advances for their respective scientific communities. The breadth and depth of the results achieved demonstrate the ease of use, versatility, and unique capabilities of the Blacklight XSEDE resource for scientific analysis of genomic and transcriptomic sequence data, and the power of these resources, together with XSEDE support, in meeting the most challenging scientific problems.

[1]  Jean Thierry-Mieg,et al.  The non-human primate reference transcriptome resource (NHPRTR) for comparative functional genomics , 2012, Nucleic Acids Res..

[2]  Xin Chen,et al.  dbCAN: a web resource for automated carbohydrate-active enzyme annotation , 2012, Nucleic Acids Res..

[3]  Sean R. Eddy,et al.  Profile hidden Markov models , 1998, Bioinform..

[4]  M. Borodovsky,et al.  Ab initio gene identification in metagenomic sequences , 2010, Nucleic acids research.

[5]  Brandi L. Cantarel,et al.  The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics , 2008, Nucleic Acids Res..

[6]  Katharine Sanderson,et al.  Lignocellulose: A chewy problem , 2011, Nature.

[7]  Eugene W. Myers,et al.  A whole-genome assembly of Drosophila. , 2000, Science.

[8]  Craig A. Stewart,et al.  Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond , 2012 .

[9]  Robert L. Grossman,et al.  The Case for Cloud Computing , 2009, IT Professional.

[10]  Shashikant Kulkarni,et al.  Assuring the quality of next-generation sequencing in clinical laboratory practice , 2012, Nature Biotechnology.

[11]  M. B. Couger,et al.  The Genome of the Anaerobic Fungus Orpinomyces sp. Strain C1A Reveals the Unique Evolutionary History of a Remarkable Plant Biomass Degrader , 2013, Applied and Environmental Microbiology.

[12]  Chrystala Constantinidou,et al.  Genome sequencing in clinical microbiology , 2012, Nature Biotechnology.

[13]  N. Friedman,et al.  Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data , 2011, Nature Biotechnology.

[14]  J. Mattick,et al.  Long non-coding RNAs: insights into functions , 2009, Nature Reviews Genetics.

[15]  James Taylor,et al.  Next-generation sequencing data interpretation: enhancing reproducibility and accessibility , 2012, Nature Reviews Genetics.

[16]  E. Birney,et al.  Velvet: algorithms for de novo short read assembly using de Bruijn graphs. , 2008, Genome research.

[17]  Andreas Wilke,et al.  phylogenetic and functional analysis of metagenomes , 2022 .

[18]  S. Tringe,et al.  Metagenomic Discovery of Biomass-Degrading Genes and Genomes from Cow Rumen , 2011, Science.

[19]  Le-Shin Wu,et al.  Trinity RNA-Seq assembler performance optimization , 2012, XSEDE '12.

[20]  A G Brownlee,et al.  Remarkably AT-rich genomic DNA from the anaerobic fungus Neocallimastix. , 1989, Nucleic acids research.