MsatAllele_1.0: An R package to visualize the binning of microsatellite Alleles

MsatAllele is a computer package built on R to visualize and bin the raw microsatellite allele size distributions. The method is based on the creation of an R database with exported files from the open-source electropherogram peak-reading program STRAND. Contrary to other binning programs, in this program, the bin limits are not fixed and are automatically defined by the data stored in the database. Data manipulation and graphical functions allow to 1) visualize raw allele size variation, allowing the detection of potential scoring errors, strange bin distributions, and unexpected spacing between the bins; 2) bin raw fragment sizes and write bin summary statistics for each locus; and 3) export genotype files with the resulting binned data.Fundacao para a Ciencia e Tecnologia [SFRH/BPD/14945/2004]; MEGIKELP [PTDC/MAR/65461/2006]info:eu-repo/semantics/publishedVersio

Prey Preference of Snow Leopard (Panthera uncia) in South Gobi, Mongolia

International audienceAccurate information about the diet of large carnivores that are elusive and inhabit inaccessible terrain, is required to properly design conservation strategies. Predation on livestock and retaliatory killing of predators have become serious issues throughout the range of the snow leopard. Several feeding ecology studies of snow leopards have been conducted using classical approaches. These techniques have inherent limitations in their ability to properly identify both snow leopard feces and prey taxa. To examine the frequency of livestock prey and nearly-threatened argali in the diet of the snow leopard, we employed the recently developed DNA-based diet approach to study a snow leopard population located in the Tost Mountains, South Gobi, Mongolia. After DNA was extracted from the feces, a region of ~100 bp long from mitochondrial 12S rRNA gene was amplified, making use of universal primers for vertebrates and a blocking oligonucleotide specific to snow leopard DNA. The amplicons were then sequenced using a next-generation sequencing platform. We observed a total of five different prey items from 81 fecal samples. Siberian ibex predominated the diet (in 70.4% of the feces), followed by domestic goat (17.3%) and argali sheep (8.6%). The major part of the diet was comprised of large ungulates (in 98.8% of the feces) including wild ungulates (79%) and domestic livestock (19.7%). The findings of the present study will help to understand the feeding ecology of the snow leopard, as well as to address the conservation and management issues pertaining to this wild cat

Power and limitations of the chloroplast trnL (UAA) intron for plant DNA barcoding

DNA barcoding should provide rapid, accurate and automatable species identifications by using a standardized DNA region as a tag. Based on sequences available in GenBank and sequences produced for this study, we evaluated the resolution power of the whole chloroplast trnL (UAA) intron (254–767 bp) and of a shorter fragment of this intron (the P6 loop, 10–143 bp) amplified with highly conserved primers. The main limitation of the whole trnL intron for DNA barcoding remains its relatively low resolution (67.3% of the species from GenBank unambiguously identified). The resolution of the P6 loop is lower (19.5% identified) but remains higher than those of existing alternative systems. The resolution is much higher in specific contexts such as species originating from a single ecosystem, or commonly eaten plants. Despite the relatively low resolution, the whole trnL intron and its P6 loop have many advantages: the primers are highly conserved, and the amplification system is very robust. The P6 loop can even be amplified when using highly degraded DNA from processed food or from permafrost samples, and has the potential to be extensively used in food industry, in forensic science, in diet analyses based on feces and in ancient DNA studies

Prior Mating Experience Modulates the Dispersal of Drosophila in Males More Than in Females

Cues from both an animal’s internal physiological state and its local environment may influence its decision to disperse. However, identifying and quantifying the causative factors underlying the initiation of dispersal is difficult in uncontrolled natural settings. In this study, we automatically monitored the movement of fruit flies and examined the influence of food availability, sex, and reproductive status on their dispersal between laboratory environments. In general, flies with mating experience behave as if they are hungrier than virgin flies, leaving at a greater rate when food is unavailable and staying longer when it is available. Males dispersed at a higher rate and were more active than females when food was unavailable, but tended to stay longer in environments containing food than did females. We found no significant relationship between weight and activity, suggesting the behavioral differences between males and females are caused by an intrinsic factor relating to the sex of a fly and not simply its body size. Finally, we observed a significant difference between the dispersal of the natural isolate used throughout this study and the widely-used laboratory strain, Canton-S, and show that the difference cannot be explained by allelic differences in the foraging gene

Local adaptations of Mediterranean sheep and goats through an integrative approach

Small ruminants are suited to a wide variety of habitats and thus represent promising study models for identifying genes underlying adaptations. Here, we considered local Mediterranean breeds of goats (n = 17) and sheep (n = 25) from Italy, France and Spain. Based on historical archives, we selected the breeds potentially most linked to a territory and defined their original cradle (i.e., the geographical area in which the breed has emerged), including transhumant pastoral areas. We then used the programs PCAdapt and LFMM to identify signatures of artificial and environmental selection. Considering cradles instead of current GPS coordinates resulted in a greater number of signatures identified by the LFMM analysis. The results, combined with a systematic literature review, revealed a set of genes with potentially key adaptive roles in relation to the gradient of aridity and altitude. Some of these genes have been previously implicated in lipid metabolism (SUCLG2, BMP2), hypoxia stress/lung function (BMPR2), seasonal patterns (SOX2, DPH6) or neuronal function (TRPC4, TRPC6). Selection signatures involving the PCDH9 and KLH1 genes, as well as NBEA/NBEAL1, were identified in both species and thus could play an important adaptive role

ecoPrimers: inference of new DNA barcode markers from whole genome sequence analysis

Using non-conventional markers, DNA metabarcoding allows biodiversity assessment from complex substrates. In this article, we present ecoPrimers, a software for identifying new barcode markers and their associated PCR primers. ecoPrimers scans whole genomes to find such markers without a priori knowledge. ecoPrimers optimizes two quality indices measuring taxonomical range and discrimination to select the most efficient markers from a set of reference sequences, according to specific experimental constraints such as marker length or specifically targeted taxa. The key step of the algorithm is the identification of conserved regions among reference sequences for anchoring primers. We propose an efficient algorithm based on data mining, that allows the analysis of huge sets of sequences. We evaluate the efficiency of ecoPrimers by running it on three different sequence sets: mitochondrial, chloroplast and bacterial genomes. Identified barcode markers correspond either to barcode regions already in use for plants or animals, or to new potential barcodes. Results from empirical experiments carried out on a promising new barcode for analyzing vertebrate diversity fully agree with expectations based on bioinformatics analysis. These tests demonstrate the efficiency of ecoPrimers for inferring new barcodes fitting with diverse experimental contexts. ecoPrimers is available as an open source project at: http://www.grenoble.prabi.fr/trac/ecoPrimers

VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity

Background: Since their domestication 10,500 years ago, goat populations with distinctive genetic backgrounds have adapted to a broad variety of environments and breeding conditions. The VarGoats project is an international 1000-genome resequencing program designed to understand the consequences of domestication and breeding on the genetic diversity of domestic goats and to elucidate how speciation and hybridization have modeled the genomes of a set of species representative of the genus Capra. Findings: A dataset comprising 652 sequenced goats and 507 public goat sequences, including 35 animals representing eight wild species, has been collected worldwide. We identified 74,274,427 single nucleotide polymorphisms (SNPs) and 13,607,850 insertion-deletions (InDels) by aligning these sequences to the latest version of the goat reference genome (ARS1). A Neighbor-joining tree based on Reynolds genetic distances showed that goats from Africa, Asia and Europe tend to group into independent clusters. Because goat breeds from Oceania and Caribbean (Creole) all derive from imported animals, they are distributed along the tree according to their ancestral geographic origin. Conclusions: We report on an unprecedented international effort to characterize the genome-wide diversity of domestic goats. This large range of sequenced individuals represents a unique opportunity to ascertain how the demographic and selection processes associated with post-domestication history have shaped the diversity of this species. Data generated for the project will also be extremely useful to identify deleterious mutations and polymorphisms with causal effects on complex traits, and thus will contribute to new knowledge that could be used in genomic prediction and genome-wide association studies

VarGoats project : a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity

Since their domestication 10,500 years ago, goat populations with distinctive genetic backgrounds have adapted to a broad variety of environments and breeding conditions. The VarGoats project is an international 1000-genome resequencing program designed to understand the consequences of domestication and breeding on the genetic diversity of domestic goats and to elucidate how speciation and hybridization have modeled the genomes of a set of species representative of the genus Capra. A dataset comprising 652 sequenced goats and 507 public goat sequences, including 35 animals representing eight wild species, has been collected worldwide. We identified 74,274,427 single nucleotide polymorphisms (SNPs) and 13,607,850 insertion-deletions (InDels) by aligning these sequences to the latest version of the goat reference genome (ARS1). A Neighbor-joining tree based on Reynolds genetic distances showed that goats from Africa, Asia and Europe tend to group into independent clusters. Because goat breeds from Oceania and Caribbean (Creole) all derive from imported animals, they are distributed along the tree according to their ancestral geographic origin. We report on an unprecedented international effort to characterize the genome-wide diversity of domestic goats. This large range of sequenced individuals represents a unique opportunity to ascertain how the demographic and selection processes associated with post-domestication history have shaped the diversity of this species. Data generated for the project will also be extremely useful to identify deleterious mutations and polymorphisms with causal effects on complex traits, and thus will contribute to new knowledge that could be used in genomic prediction and genome-wide association studies