De novo assembly of Dekkera bruxellensis: a multi technology approach using short and long-read sequencing and optical mapping.

Olsen RA, Bunikis I, Tiukova I, Holmberg K, Lötstedt B, Pettersson OV, Passoth V, Käller M, Vezzi F

Gigascience 4 (-) 56 [2015-11-26; online 2015-11-26]

It remains a challenge to perform de novo assembly using next-generation sequencing (NGS). Despite the availability of multiple sequencing technologies and tools (e.g., assemblers) it is still difficult to assemble new genomes at chromosome resolution (i.e., one sequence per chromosome). Obtaining high quality draft assemblies is extremely important in the case of yeast genomes to better characterise major events in their evolutionary history. The aim of this work is two-fold: on the one hand we want to show how combining different and somewhat complementary technologies is key to improving assembly quality and correctness, and on the other hand we present a de novo assembly pipeline we believe to be beneficial to core facility bioinformaticians. To demonstrate both the effectiveness of combining technologies and the simplicity of the pipeline, here we present the results obtained using the Dekkera bruxellensis genome. In this work we used short-read Illumina data and long-read PacBio data combined with the extreme long-range information from OpGen optical maps in the task of de novo genome assembly and finishing. Moreover, we developed NouGAT, a semi-automated pipeline for read-preprocessing, de novo assembly and assembly evaluation, which was instrumental for this work. We obtained a high quality draft assembly of a yeast genome, resolved on a chromosomal level. Furthermore, this assembly was corrected for mis-assembly errors as demonstrated by resolving a large collapsed repeat and by receiving higher scores by assembly evaluation tools. With the inclusion of PacBio data we were able to fill about 5 % of the optical mapped genome not covered by the Illumina data.

NGI Stockholm (Genomics Applications)

NGI Stockholm (Genomics Production)

NGI Uppsala (Uppsala Genome Center)

National Genomics Infrastructure

PubMed 26617983

DOI 10.1186/s13742-015-0094-1

Crossref 10.1186/s13742-015-0094-1

pii: 94
pmc: PMC4661999