WIDDE: a Web-Interfaced next generation database for genetic diversity exploration, with a first application in cattle

Abstract

BackgroundThe advent and democratization of next generation sequencing and genotyping technologies lead to a huge amount of data for the characterization of population genetic diversity in model and non model-species. However, efficient storage, management, cross-analyzing and exploration of such dense genotyping datasets remain challenging. This is particularly true for the bovine species where many SNP datasets have been generated in various cattle populations with different genotyping tools.DescriptionWe developed WIDDE, a Web-Interfaced Next Generation Database that stands as a generic tool applicable to a wide range of species and marker types (http://widde.toulouse.inra.fr). As a first illustration, we hereby describe its first version dedicated to cattle biodiversity, which includes a large and evolving cattle genotyping dataset for over 750,000 SNPs available on 129 (89 public) different cattle populations representative of the world-wide bovine genetic diversity and on 7 outgroup bovid species. This version proposes an optional marker and individual filtering step, an export of genotyping data in different popular formats, and an exploration of genetic diversity through a principal component analysis. Users can also explore their own genotyping data together with data from WIDDE, assign their samples to WIDDE populations based on distance assignment method and supervised clustering, and estimate their ancestry composition relative to the populations represented in the database.ConclusionThe cattle version of WIDDE represents to our knowledge the first database dedicated to cattle biodiversity and SNP genotyping data that will be very useful for researchers interested in this field. As a generic tool applicable to a wide range of marker types, WIDDE is overall intended to the genetic diversity exploration of any species and will be extended to other species shortly. The structure makes it easy to include additional output formats and new tools dedicated to genetic diversity exploration.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2181-1) contains supplementary material, which is available to authorized users.

A model‐based approach to characterize individual inbreeding at both global and local genomic scales

“…For illustration purposes, we used publicly available genotyping data from (i) the Human Genome Diversity Panel (HGDP) (Li et al., ) as downloaded from ftp://ftp.cephb.fr/hgdp_supp10/Harvard_HGDP-CEPH; (ii) the dog LUPA project (Vaysse et al., ) as downloaded from http://dogs.genouest.org/SWEEP.dir/Supplemental.html; and (iii) the Sheep Diversity panel (Kijas et al., ) as downloaded from the WIDDE database (Sempere et al., ). We then used the software plink (Purcell et al., ) to process and filter the genotyping data by removing individuals with a genotyping call rate below 90%.…”

“…For illustration purposes, we used publicly available genotyping data from (i) the Human Genome Diversity Panel (HGDP) (Li et al, 2008) as downloaded from ftp://ftp.cephb.fr/hgdp_supp10/Harvard_ (Sempere et al, 2015). We then used the software PLINK (Purcell et al, 2007) to process and filter the genotyping data by removing individuals with a genotyping call rate below 90%.…”

A genomic map of climate adaptation in Mediterranean cattle breeds

“…DNA samples were genotyped on the Illumina BovineSNP50 chip (v2) at Labogena platform (INRA, Jouy‐en‐Josas) using standard procedures (http://www.illumina.com). Genotypes were then integrated in the WIDDE database (Sempéré et al, ). Using WIDDE utilities, these newly generated data were combined with existing publicly available ones (Decker et al, ; Gautier et al, ; Gautier, Laloë, et al ; Matukumalli et al, ) to generate two data sets referred to as the WORLD‐Set and the MED‐Set (Figure a and Table ).…”

“…ANA and TUR hybrids breeds, not considered in the MED-Set are in black. (b) to (f) Geographic pattern of the annual mean temperature (b), the temperature annual range (c), the annual precipitation (d), the annual mean radiation (e) and the annual mean moisture index ( (Sempéré et al, 2015). Using WIDDE utilities, these newly generated data were combined with existing publicly available ones (Decker et al, 2014;Gautier et al, 2009;Gautier, Laloë, et al 2010;Matukumalli et al, 2009) to generate two data sets referred to as the WORLD-Set and the MED-Set ( Figure 1a and Table 1…”

Erratum to: Gigwa-Genotype investigator for genome-wide analyses

“…BMC Genomics 2015 16:940” [2], not to “Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case. BMC Bioinf.…”