Short-read sequencing for genomic analysis of the brown rot fungus Fibroporia radiculosa

Appl Environ Microbiol. 2012 Apr;78(7):2272-81. doi: 10.1128/AEM.06745-11. Epub 2012 Jan 13.

Abstract

The feasibility of short-read sequencing for genomic analysis was demonstrated for Fibroporia radiculosa, a copper-tolerant fungus that causes brown rot decay of wood. The effect of read quality on genomic assembly was assessed by filtering Illumina GAIIx reads from a single run of a paired-end library (75-nucleotide read length and 300-bp fragment size) at three different stringency levels and then assembling each data set with Velvet. A simple approach was devised to determine which filter stringency was "best." Venn diagrams identified the regions containing reads that were used in an assembly but were of a low-enough quality to be removed by a filter. By plotting base quality histograms of reads in this region, we judged whether a filter was too stringent or not stringent enough. Our best assembly had a genome size of 33.6 Mb, an N50 of 65.8 kb for a k-mer of 51, and a maximum contig length of 347 kb. Using GeneMark, 9,262 genes were predicted. TargetP and SignalP analyses showed that among the 1,213 genes with secreted products, 986 had motifs for signal peptides and 227 had motifs for signal anchors. Blast2GO analysis provided functional annotation for 5,407 genes. We identified 29 genes with putative roles in copper tolerance and 73 genes for lignocellulose degradation. A search for homologs of these 102 genes showed that F. radiculosa exhibited more similarity to Postia placenta than Serpula lacrymans. Notable differences were found, however, and their involvements in copper tolerance and wood decay are discussed.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Computational Biology / methods
  • Copper / metabolism
  • Copper / pharmacology
  • Fungal Proteins / genetics*
  • Fungal Proteins / metabolism
  • Gene Expression Profiling
  • Genome Size
  • Genome, Fungal / genetics*
  • Genomics / methods*
  • Lignin / metabolism
  • Polyporaceae / drug effects
  • Polyporaceae / genetics*
  • Sequence Analysis, DNA / methods*
  • Wood / metabolism
  • Wood / microbiology*

Substances

  • Fungal Proteins
  • lignocellulose
  • Copper
  • Lignin