A software pipeline for processing and identification of fungal ITS sequences

<p>Abstract</p> <p>Background</p> <p>Fungi from environmental samples are typically identified to species level through DNA sequencing of the nuclear ribosomal internal transcribed spacer (<it>ITS</it>) region for use in BLAST-based similarity searches in the International Nucleotide Sequence Databases. These searches are time-consuming and regularly require a significant amount of manual intervention and complementary analyses. We here present software – in the form of an identification pipeline for large sets of fungal <it>ITS </it>sequences – developed to automate the BLAST process and several additional analysis steps. The performance of the pipeline was evaluated on a dataset of 350 <it>ITS </it>sequences from fungi growing as epiphytes on building material.</p> <p>Results</p> <p>The pipeline was written in Perl and uses a local installation of NCBI-BLAST for the similarity searches of the query sequences. The variable subregion <it>ITS2 </it>of the <it>ITS </it>region is extracted from the sequences and used for additional searches of higher sensitivity. Multiple alignments of each query sequence and its closest matches are computed, and query sequences sharing at least 50% of their best matches are clustered to facilitate the evaluation of hypothetically conspecific groups. The pipeline proved to speed up the processing, as well as enhance the resolution, of the evaluation dataset considerably, and the fungi were found to belong chiefly to the <it>Ascomycota</it>, with <it>Penicillium </it>and <it>Aspergillus </it>as the two most common genera. The <it>ITS2 </it>was found to indicate a different taxonomic affiliation than did the complete <it>ITS </it>region for 10% of the query sequences, though this figure is likely to vary with the taxonomic scope of the query sequences.</p> <p>Conclusion</p> <p>The present software readily assigns large sets of fungal query sequences to their respective best matches in the international sequence databases and places them in a larger biological context. The output is highly structured to be easy to process, although it still needs to be inspected and possibly corrected for the impact of the incomplete and sometimes erroneously annotated fungal entries in these databases. The open source pipeline is available for UNIX-type platforms, and updated releases of the target database are made available biweekly. The pipeline is easily modified to operate on other molecular regions and organism groups.</p

Novel copy-number variations in pharmacogenes contribute to interindividual differences in drug pharmacokinetics

PurposeVariability in pharmacokinetics and drug response is shaped by single-nucleotide variants (SNVs) as well as copy-number variants (CNVs) in genes with importance for drug absorption, distribution, metabolism, and excretion (ADME). While SNVs have been extensively studied, a systematic assessment of the CNV landscape in ADME genes is lacking.MethodsWe integrated data from 2,504 whole genomes from the 1000 Genomes Project and 59,898 exomes from the Exome Aggregation Consortium to identify CNVs in 208 relevant pharmacogenes.ResultsWe describe novel exonic deletions and duplications in 201 (97%) of the pharmacogenes analyzed. The deletions are population-specific and frequencies range from singletons up to 1%, accounting for >5% of all loss-of-function alleles in up to 42% of the genes studied. We experimentally confirmed novel deletions in CYP2C19, CYP4F2, and SLCO1B3 by Sanger sequencing and validated their allelic frequencies in selected populations.ConclusionCNVs are an additional source of pharmacogenetic variability with important implications for drug response and personalized therapy. This, together with the important contribution of rare alleles to the variability of pharmacogenes, emphasizes the necessity of comprehensive next-generation sequencing-based genotype identification for an accurate prediction of the genetic variability of drug pharmacokinetics.This work was supported by the Spanish Ministry of Economy and Competiveness (grant SAF2015-64850-R), by the European Union's Horizon 2020 research and innovation program U-PGx under grant agreement 668353, and by the Swedish Research Council (grant agreements 2015-02760, 2016-01153, and 2016-01154)N