P1058
A Comparison of Assemblers and Strategies for Complex Large Genome Sequencing with PacBio® Long Reads

Date: Monday, January 13, 2014
Room: Grand Exhibit Hall
Jenny Gu , Pacific Biosciences, Menlo Park, CA
Richard Hall , Pacific Biosciences, Menlo Park, CA
Cheryl Heiner , Pacific Biosciences, Menlo Park, CA
Brian Sogoloff , Broad Institute of MIT & Harvard, Cambridge, MA
James Meldrim , Broad Institute of MIT & Harvard, Cambridge, MA
Kristen Connolly , Broad Institute of MIT & Harvard, Cambridge, MA
Terrance Shea , Broad Institute of MIT & Harvard, Cambridge, MA
Carsten Russ , Broad Institute, Cambridge, MA
Christina Cuomo , Broad Institute of MIT & Harvard, Cambridge, MA
Les J. Szabo , USDA-ARS, University of Minnesota, St. Paul, MN
PacBio® sequencing holds promise for addressing large genome complexities, such as long, highly repetitive, low complexity regions and duplication events that are difficult to resolve with short-read technologies.  Several strategies, with varying outcomes, are available for de novo sequencing and assembling of larger genomes.  Using a diploid fungal genome, estimated to be ~80 Mb in size, as the basis dataset for comparison, we highlight assembly options when using only PacBio sequencing or a combined strategy leveraging multiple sequencing technology data sets.  Comparisons of results generated from different assemblers available for large genome assembly using data generated from SMRT® Sequencing will be shown.  These include results generated with HGAP, Celera, MIRA, PBJelly, and other assembly tools currently in development.  Improvements observed include a near 50% reduction in the number of contigs coupled with a doubling of contig N50 size, at the minimum, in genome assemblies incorporating SMRT®sequencing data.  We further show how incorporating long reads also highlights new challenges and missed insights of short read assemblies arising from heterozygosity inherent in multiploid genomes.
Handouts
  • Comparison of Assemblers and Strategies for Complex Large Genomes.pdf (823.3 kB)