Bemisia tabaci has long been considered a complex species. It rose to global prominence in the 1980s owing to the global invasion by the commonly named B biotype. Since then, the concomitant eruption of a group of plant viruses known as begomoviruses has created considerable management problems in many countries. However, an enduring set of questions remains: Is B. tabaci a complex species or a species complex, what are Bemisia biotypes, and how did all the genetic variability arise? This review considers these issues and concludes that there is now sufficient evidence to state that B. tabaci is not made up of biotypes and that the use of biotype in this context is erroneous and misleading. Instead, B. tabaci is a complex of 11 well-defined high-level groups containing at least 24 morphologically indistinguishable species.

Background: Herbaria are valuable sources of extensive curated plant material that are now accessible to genetic studies because of advances in high-throughput, next-generation sequencing methods. As an applied assessment of large-scale recovery of plastid and ribosomal genome sequences from herbarium material for plant identification and phylogenomics, we sequenced 672 samples covering 21 families, 142 genera and 530 named and proposed named species. We explored the impact of parameters such as sample age, DNA concentration and quality, read depth and fragment length on plastid assembly error. We also tested the efficacy of DNA sequence information for identifying plant samples using 45 specimens recently collected in the Pilbara.Results: Genome skimming was effective at producing genomic information at large scale. Substantial sequence information on the chloroplast genome was obtained from 96.1% of samples, and complete or near-complete sequences of the nuclear ribosomal RNA gene repeat were obtained from 93.3% of samples. We were able to extract sequences for the core DNA barcode regionsrbcLandmatKfrom 96 to 93.3% of samples, respectively. Read quality and DNA fragment length had significant effects on sequencing outcomes and error correction of reads proved essential. Assembly problems were specific to certain taxa with low GC and high repeat content (Goodenia,Scaevola,Cyperus,Bulbostylis,Fimbristylis) suggesting biological rather than technical explanations. The structure of related genomes was needed to guide the assembly of repeats that exceeded the read length. DNA-based matching proved highly effective and showed that the efficacy for species identification declined in the order cpDNA >> rDNA > matK >> rbcL.Conclusions: We showed that a large-scale approach to genome sequencing using herbarium specimens produces high-quality complete cpDNA and rDNA sequences as a source of data for DNA barcoding and phylogenomics.

Motivation: The hepatitis C virus (HCV) is a significant threat to public health worldwide. The virus is highly variable and evolves rapidly, making it an elusive target for the immune system and for vaccine and drug design. At present, some 30 000 HCV sequences have been published. A central website that provides annotated sequences and analysis tools will be helpful to HCV scientists worldwide. Results: The HCV sequence database collects and annotates sequence data and provides them to the public via a website that contains a user-friendly search interface and a large number of sequence analysis tools, based on the model of the highly regarded Los Alamos HIV database. The HCV sequence database was officially launched in September 2003. Since then, its usage has steadily increased and is now at an average of ∼280 visits per day from distinct IP addresses. Availability: The HCV website can be accessed via http://hcv.lanl.gov and http://hcv-db.org Contact:hcv-info@lanl.gov

Summary: 1. DNA barcoding studies use Kimura's two‐parameter substitution model (K2P) as thede factostandard for constructing genetic distance matrices. Distances generated under this model then provide the basis for most downstream analyses, but uncertainty in model choice is rarely explored and could potentially affect how reliably DNA barcodes discriminate species.2. Using information‐theoretic approaches for a data set comprising 14 472 DNA barcodes from 14 published studies, we tested whether the K2P model was a good fit at the species level and whether applying a better fitting model biased error rates or changed overall identification success.3. We report that the K2P was a poorly fitting model at the species level; it was never selected as the best model and very rarely selected as a credible alternative model. Despite the lack of support for the K2P model, differences in distance between best model and K2P model estimates were usually minimal, and importantly, identification success rates were largely unaffected by model choice even when interspecific threshold values were reassessed.4. Although these conclusions may justify using the K2P model for specimen identification purposes, we found simpler metrics such aspdistance performed equally well, perhaps obviating the requirement for model correction in DNA barcoding. Conversely, when incorporating genetic distance data into taxonomic studies, we advocate a more thorough examination of model uncertainty.