VIP Barcoding: Composition vector-based software for rapid species identification based on DNA barcoding

Species identification based on short sequences of DNA markers, that is, DNA barcoding, has emerged as an integral part of modern taxonomy. However, software for the analysis of large and multilocus barcoding data sets is scarce. The Basic Local Alignment Search Tool (BLAST) is currently the fastest tool capable of handling large databases (e.g. >5000 sequences), but its accuracy is a concern and has been criticized for its local optimization. However, current more accurate software requires sequence alignment or complex calculations, which are time-consuming when dealing with large data sets during data preprocessing or during the search stage. Therefore, it is imperative to develop a practical program for both accurate and scalable species identification for DNA barcoding. In this context, we present VIP Barcoding: a user-friendly software in graphical user interface for rapid DNA barcoding. It adopts a hybrid, two-stage algorithm. First, an alignment-free composition vector (CV) method is utilized to reduce searching space by screening a reference database. The alignment-based K2P distance nearest-neighbour method is then employed to analyse the smaller data set generated in the first stage. In comparison with other software, we demonstrate that VIP Barcoding has (i) higher accuracy than Blastn and several alignment-free methods and (ii) higher scalability than alignment-based distance methods and character-based methods. These results suggest that this platform is able to deal with both large-scale and multilocus barcoding data with accuracy and can contribute to DNA barcoding for modern taxonomy. VIP Barcoding is free and available at http://msl.sls.cuhk.edu.hk/vipbarcoding/.

Energy and nutrient intakes among Sri Lankan adults

Introduction The epidemic of nutrition related non-communicable diseases such as type 2 diabetes mellitus and obesity has reached to epidemic portion in the Sri Lanka. However, to date, detailed data on food consumption in the Sri Lankan population is limited. The aim of this study is to identify energy and major nutrient intake among Sri Lankan adults. Methods A nationally-representative sample of adults was selected using a multi-stage random cluster sampling technique. Results Data from 463 participants (166 Males, 297 Females) were analyzed. Total energy intake was significantly higher in males (1913 ± 567 kcal/d) than females (1514 ± 458 kcal/d). However, there was no significant gender differences in the percentage of energy from carbohydrate (Male: 72.8 ± 6.4%, Female: 73.9 ± 6.7%), fat (Male: 19.9 ± 6.1%, Female: 18.5 ± 5.7%) and proteins (Male: 10.6 ± 2.1%, Female: 10.9 ± 5.6%). Conclusion The present study provides the first national estimates of energy and nutrient intake of the Sri Lankan adult population.

PolyPatEx : an R package for paternity exclusion in autopolyploids

Microsatellite markers have demonstrated their value for performing paternity exclusion and hence exploring mating patterns in plants and animals. Methodology is well established for diploid species, and several software packages exist for elucidating paternity in diploids; however, these issues are not so readily addressed in polyploids due to the increased complexity of the exclusion problem and a lack of available software. We introduce polypatex, an r package for paternity exclusion analysis using microsatellite data in autopolyploid, monoecious or dioecious/bisexual species with a ploidy of 4n, 6n or 8n. Given marker data for a set of offspring, their mothers and a set of candidate fathers, polypatex uses allele matching to exclude candidates whose marker alleles are incompatible with the alleles in each offspring–mother pair. polypatex can analyse marker data sets in which allele copy numbers are known (genotype data) or unknown (allelic phenotype data) – for data sets in which allele copy numbers are unknown, comparisons are made taking into account all possible genotypes that could arise from the compared allele sets. polypatex is a software tool that provides population geneticists with the ability to investigate the mating patterns of autopolyploids using paternity exclusion analysis on data from codominant markers having multiple alleles per locus.