Larroque J.,Office National de la Chasse et de la Faune Sauvage |
Larroque J.,University of Lyon |
Larroque J.,French National Center for Scientific Research |
Ruette S.,Office National de la Chasse et de la Faune Sauvage |
And 4 more authors.
Maintenance of genetic variation is of critical importance for wild populations since low levels limit the species’ ability to respond to different threats (diseases, predators, environmental changes) in both the long and the short term. Human activities could impact the genetic variation of wild species in multiple ways, including via fragmentation and harvesting. We used an individual-based landscape genetics approach to describe the impact of landscape elements and trapping pressure on the spatial genetic structure of a large sample (n = 370) of the stone marten (Martes foina) in central-eastern France (Bresse). An analysis of isolation-by-resistance using a causal modeling approach showed an influence of landscape cover and/or trapping pressure on gene flow according to age and sex class. Overall, the connectivity in the study area is provided mainly by vegetation cover, while roads and open areas partially impede it. Unexpectedly for this “urban adapter” species, buildings could reduce gene flow. We also emphasized the sex-dependent effect of trapping on gene flow. Genetic differentiation in males was influenced by trapping pressure and landscape structure while only the latter influenced genetic differentiation in females. A stronger isolation by distance in males than in females suggested that at the scale of the study area, males are more exposed to trapping pressure, which reduces effective dispersal. Overall, the combination of both landscape and trapping costs might create an ‘ecological trap’ that could disrupt gene flow, leading to a north–south division in the study area. © 2016 Springer Science+Business Media Dordrecht Source
Boison S.A.,University of Natural Resources and Life Sciences, Vienna |
Neves H.H.R.,Sao Paulo State University |
Perez O'Brien A.M.,University of Natural Resources and Life Sciences, Vienna |
Utsunomiya Y.T.,Sao Paulo State University |
And 4 more authors.
This study aimed at imputing non(un)-genotyped sires using a stepwise imputation approach that combines identity by descent (IBD) detection methods with other imputation algorithms. We also studied the effect of using actual or imputed genotypes of non-genotyped sires in estimating genomic relationships.Simulations and real data were used for the analysis. Fifty sire families were simulated and 23 sire families were derived from 995 Brazilian Nellore cattle genotyped with Illumina® Bovine HD (777,962 SNPs) SNP Chip. Un-genotyped sires were imputed using genotype information from progeny (5 or 10); progeny and grand offspring; a combination of progeny, mates of genotyped progeny and grand offspring; and the entire genotyped population. Stepwise imputation was done with an IBD detection method that uses simple inheritance rules (MERLIN) as a first step and subsequently with FImpute, MaCH or BEAGLE as the second step to infer genotypes that were not imputed unambiguously by MERLIN. The stepwise imputation procedure was compared to an approach that ignores the first step (MERLIN) but uses only prior pedigree information to impute non-genotyped animals. Imputation accuracy was assessed as percent of correctly called genotypes and the correlation between imputed and actual genotypes (in brackets).With real data, imputation accuracy ranged from 81.6% (0.856) to 97.4% (0.981) depending on the amount of genotyped information considered for the first step (MERLIN) and imputation algorithms used for the second step. Greater accuracies of imputing non-genotyped sires were obtained when the stepwise imputation approach was used with 10 genotyped offspring as the first step. The stepwise approach resulted in an increase of 1.2% (5 offsprings) and 4.7% (10 offsprings) in imputation accuracy. MaCH was more accurate in the second step, followed by FImpute then BEAGLE. Similar trends in imputation accuracy were observed for the simulated population. Generally, imputed genotypes were successfully used to estimate genomic relationships among close relatives but considerable bias was observed for true pairwise relationships of zero.In conclusion, high imputation accuracies can be achieved for non-genotyped animals when genotype information of 5 or 10 direct progeny is available for imputation. Performing preliminary IBD analysis and using non-ambiguous genotypes from that analysis in conventional imputation increased the imputation accuracy considerably. © 2014 Elsevier B.V. Source
Carneiro M.,University of Porto |
Rubin C.-J.,Uppsala University |
Palma F.D.,The Broad Institute of MIT and Harvard |
Palma F.D.,Genome Analysis Center |
And 48 more authors.
The genetic changes underlying the initial steps of animal domestication are still poorly understood.We generated a high-quality reference genome for the rabbit and compared it to resequencing data from populations of wild and domestic rabbits.We identified more than 100 selective sweeps specific to domestic rabbits but only a relatively small number of fixed (or nearly fixed) single-nucleotide polymorphisms (SNPs) for derived alleles. SNPs with marked allele frequency differences between wild and domestic rabbits were enriched for conserved noncoding sites. Enrichment analyses suggest that genes affecting brain and neuronal development have often been targeted during domestication. We propose that because of a truly complex genetic background, tame behavior in rabbits and other domestic animals evolved by shifts in allele frequencies at many loci, rather than by critical changes at only a few domestication loci. Source
Kumar P.,Animal Genomics Laboratory |
Kumar P.,Lund University |
Yadav P.,Animal Genomics Laboratory |
Verma A.,Animal Genomics Laboratory |
And 3 more authors.
Reproduction in Domestic Animals
Contents: The present study was aimed to validate expression stability of 6 housekeeping genes (viz. YWHAZ, SDHA, GAPDH, RPS15, RPS18 and RN18S1) in the oocytes and embryos of different stages in buffalo. A modified Trizol protocol was optimized for RNA isolation from as few as five oocytes. The expression level of selected genes was studied by an optimized real time PCR using DCT method and their stability of expression was evaluated by Microsoft Excel based visual application, geNORM. The analysis revealed that the RPS15 and GAPDH were the most stable genes across different samples. Also, the geometric mean of three genes (i.e. RPS15, RPS18 and GAPDH) were found suitable for normalization of real time PCR data from buffalo oocytes/embryos. The information would help in more accurate interpretation of gene expression data from oocytes/embryos towards understanding the molecular events in these cells during development. © 2012 Blackwell Verlag GmbH. Source
Rajput S.K.,Animal Genomics Laboratory |
Kumar S.,Animal Genomics Laboratory |
Dave V.P.,Amity University |
Rajput A.,Animal Genomics Laboratory |
And 3 more authors.
Applied Biochemistry and Biotechnology
Methylation of vertebrate DNA is one of the most important epigenetic alterations which have become a center of scientific attraction, especially because of its important role in the regulation of transcription, genomic imprinting, developmental process, and pathogenesis of various diseases. Currently, there are wide ranges of methods available to produce quantitative and qualitative information on genomic DNA methylation. The vast majority of these methods rely on the optimization of the efficient bisulfite treatment. However, all the available methods for bisulfite treatment suffer from major disadvantages, such as large amount of starting material, poor conversion efficiency as well as low recovery and integrity of DNA after bisulfite treatment. Here, we developed a simple, rapid, and convenient column-based bisulfite treatment method by improving the several critical steps, which leads to consistent C-to-U conversion rate 99-100%, >75% recovery of DNA after bisulfate treatment. In addition, it is commercially viable and requires very less amount (∼10 pg) of DNA. © Springer Science+Business Media, LLC 2012. Source