Fungal high-throughput taxonomic identification tool for use with next-generation sequencing (FHiTINGS).

Improvements in DNA sequencing technology provide unprecedented opportunities to explore fungal diversity, but also present challenges in data analysis due to the large number of sequences generated. Here, we describe an open source software program "FHiTINGS" that utilizes the output of a BLASTn (blastall) search to rapidly identify, classify, and parse internal transcribed spacer (ITS) DNA sequences produced in fungal ecology studies that utilize next-generation DNA sequencing. This tool was designed for use with 454 pyrosequencing and is also appropriate for use with any sequencing platform that allows for BLAST searches against the indicated ITS database. For each sequence, FHiTINGS uses the lowest common ancestor method (LCA) to produce a single identification from BLAST output results, and then assigns taxonomic ranks from species through kingdom when possible for each sequence based on the Index Fungorum database. The program then sums and sorts this data into tabular form to enable rapid analysis of the sample, including α-diversity measures or richness. In silico testing demonstrates the time required to analyze and classify 1000 sequences is reduced from over 2 h by manual sorting to <1 min of computational time when using FHiTINGS, and that the classification output from the software is consistent with that derived from manual sorting of the data.

Optimization of de novo transcriptome assembly from high-throughput short read sequencing data improves functional annotation for non-model organisms.

BACKGROUND: The k-mer hash length is a key factor affecting the output of de novo transcriptome assembly packages using de Bruijn graph algorithms. Assemblies constructed with varying single k-mer choices might result in the loss of unique contiguous sequences (contigs) and relevant biological information. A common solution to this problem is the clustering of single k-mer assemblies. Even though annotation is one of the primary goals of a transcriptome assembly, the success of assembly strategies does not consider the impact of k-mer selection on the annotation output. This study provides an in-depth k-mer selection analysis that is focused on the degree of functional annotation achieved for a non-model organism where no reference genome information is available. Individual k-mers and clustered assemblies (CA) were considered using three representative software packages. Pair-wise comparison analyses (between individual k-mers and CAs) were produced to reveal missing Kyoto Encyclopedia of Genes and Genomes (KEGG) ortholog identifiers (KOIs), and to determine a strategy that maximizes the recovery of biological information in a de novo transcriptome assembly. RESULTS: Analyses of single k-mer assemblies resulted in the generation of various quantities of contigs and functional annotations within the selection window of k-mers (k-19 to k-63). For each k-mer in this window, generated assemblies contained certain unique contigs and KOIs that were not present in the other k-mer assemblies. Producing a non-redundant CA of k-mers 19 to 63 resulted in a more complete functional annotation than any single k-mer assembly. However, a fraction of unique annotations remained (~0.19 to 0.27% of total KOIs) in the assemblies of individual k-mers (k-19 to k-63) that were not present in the non-redundant CA. A workflow to recover these unique annotations is presented. CONCLUSIONS: This study demonstrated that different k-mer choices result in various quantities of unique contigs per single k-mer assembly which affects biological information that is retrievable from the transcriptome. This undesirable effect can be minimized, but not eliminated, with clustering of multi-k assemblies with redundancy removal. The complete extraction of biological information in de novo transcriptomics studies requires both the production of a CA and efforts to identify unique contigs that are present in individual k-mer assemblies but not in the CA.

The mitogenome of the bed bug Cimex lectularius (Hemiptera: Cimicidae).

We report the extraction of a bed bug mitogenome from high-throughput sequencing projects originally focused on the nuclear genome of Cimex lectularius. The assembled mitogenome has a similar AT nucleotide composition bias found in other insects. Phylogenetic analysis of all protein-coding genes indicates that C. lectularius is clearly a member of a paraphyletic Cimicomorpha clade within the Order Hemiptera.

Genome assembly and geospatial phylogenomics of the bed bug Cimex lectularius.

The common bed bug (Cimex lectularius) has been a persistent pest of humans for thousands of years, yet the genetic basis of the bed bug's basic biology and adaptation to dense human environments is largely unknown. Here we report the assembly, annotation and phylogenetic mapping of the 697.9-Mb Cimex lectularius genome, with an N50 of 971 kb, using both long and short read technologies. A RNA-seq time course across all five developmental stages and male and female adults generated 36,985 coding and noncoding gene models. The most pronounced change in gene expression during the life cycle occurs after feeding on human blood and included genes from the Wolbachia endosymbiont, which shows a simultaneous and coordinated host/commensal response to haematophagous activity. These data provide a rich genetic resource for mapping activity and density of C. lectularius across human hosts and cities, which can help track, manage and control bed bug infestations.

Geospatial Resolution of Human and Bacterial Diversity with City-Scale Metagenomics.

The panoply of microorganisms and other species present in our environment influence human health and disease, especially in cities, but have not been profiled with metagenomics at a city-wide scale. We sequenced DNA from surfaces across the entire New York City (NYC) subway system, the Gowanus Canal, and public parks. Nearly half of the DNA (48%) does not match any known organism; identified organisms spanned 1,688 bacterial, viral, archaeal, and eukaryotic taxa, which were enriched for harmless genera associated with skin (e.g., Acinetobacter). Predicted ancestry of human DNA left on subway surfaces can recapitulate U.S. Census demographic data, and bacterial signatures can reveal a station's history, such as marine-associated bacteria in a hurricane-flooded station. Some evidence of pathogens was found (Bacillus anthracis), but a lack of reported cases in NYC suggests that the pathogens represent a normal, urban microbiome. This baseline metagenomic map of NYC could help long-term disease surveillance, bioterrorism threat mitigation, and health management in the built environment of cities.

A genome sequence resource for the aye-aye (Daubentonia madagascariensis), a nocturnal lemur from Madagascar.

We present a high-coverage draft genome assembly of the aye-aye (Daubentonia madagascariensis), a highly unusual nocturnal primate from Madagascar. Our assembly totals ~3.0 billion bp (3.0 Gb), roughly the size of the human genome, comprised of ~2.6 million scaffolds (N50 scaffold size = 13,597 bp) based on short paired-end sequencing reads. We compared the aye-aye genome sequence data with four other published primate genomes (human, chimpanzee, orangutan, and rhesus macaque) as well as with the mouse and dog genomes as nonprimate outgroups. Unexpectedly, we observed strong evidence for a relatively slow substitution rate in the aye-aye lineage compared with these and other primates. In fact, the aye-aye branch length is estimated to be ~10% shorter than that of the human lineage, which is known for its low substitution rate. This finding may be explained, in part, by the protracted aye-aye life-history pattern, including late weaning and age of first reproduction relative to other lemurs. Additionally, the availability of this draft lemur genome sequence allowed us to polarize nucleotide and protein sequence changes to the ancestral primate lineage-a critical period in primate evolution, for which the relevant fossil record is sparse. Finally, we identified 293,800 high-confidence single nucleotide polymorphisms in the donor individual for our aye-aye genome sequence, a captive-born individual from two wild-born parents. The resulting heterozygosity estimate of 0.051% is the lowest of any primate studied to date, which is understandable considering the aye-aye's extensive home-range size and relatively low population densities. Yet this level of genetic diversity also suggests that conservation efforts benefiting this unusual species should be prioritized, especially in the face of the accelerating degradation and fragmentation of Madagascar's forests.