137 research outputs found

    Use of Microsatellites to Study Agricultural Biodiversity and Food Traceability

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    Molecular markers are useful tools for measuring the genetic diversity among agricultural species. In plants, microsatellites are still the most used markers for germplasm characterization, conservation, and traceability purposes, while in the livestock sector, although having represented the standard for at least two decades, they are still used only for minor farm animal species. In this work, together with a review on the use of microsatellites in livestock, we also illustrate the use of these markers for the characterization of agricultural diversity and food traceability through two case studies: (i) the analysis of genetic diversity in ancient fruit tree cultivars of apple (Malus Ă— domestica Borkh.), pear (Pyrus communis L.), sweet cherry (Prunus avium L.), and sour cherry (Prunus cerasus L.) from Northern Italy and (ii) the molecular authentication of wheat food chain. In the former case, a high genetic variability as well as the presence of different ploidy levels were detected, while in the latter microsatellite markers were shown to be useful for traceability and product authentication along the whole food chain. Overall, the presented evidence confirms the versatility of microsatellites as markers for both agrobiodiversity characterization and food traceability in cultivated plants and farm animals

    High performance computation of landscape genomic models integrating local indices of spatial association

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    Since its introduction, landscape genomics has developed quickly with the increasing availability of both molecular and topo-climatic data. The current challenges of the field mainly involve processing large numbers of models and disentangling selection from demography. Several methods address the latter, either by estimating a neutral model from population structure or by inferring simultaneously environmental and demographic effects. Here we present Samβ\betaada, an integrated approach to study signatures of local adaptation, providing rapid processing of whole genome data and enabling assessment of spatial association using molecular markers. Specifically, candidate loci to adaptation are identified by automatically assessing genome-environment associations. In complement, measuring the Local Indicators of Spatial Association (LISA) for these candidate loci allows to detect whether similar genotypes tend to gather in space, which constitutes a useful indication of the possible kinship relationship between individuals. In this paper, we also analyze SNP data from Ugandan cattle to detect signatures of local adaptation with Samβ\betaada, BayEnv, LFMM and an outlier method (FDIST approach in Arlequin) and compare their results. Samβ\betaada is an open source software for Windows, Linux and MacOS X available at \url{http://lasig.epfl.ch/sambada}Comment: 1 figure in text, 1 figure in supplementary material The structure of the article was modified and some explanations were updated. The methods and results presented are the same as in the previous versio

    Promoting collaboration between livestock and wildlife conservation genetics communities

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    The collaboration between livestock and wildlife conservation genetics communities has the potential to help promote shared priorities, with respect to emerging technologies and new analytical approaches such as next generation sequencing incorporating adaptive variation. The GLOBALDIV Consortium recently organized an international workshop held at the Ecole Polytechnique Fédérale de Lausanne (Switzerland) including a whole-day session with contributions aimed at taking stock of the situation regarding the extent of information and methodology exchange between the two communities. Discussions permitted the identification of potential benefits of further promoting cooperation in the context of genetic monitoring in particular, a central concept to current concerns for both the livestock and wildlife conservation communitie

    Assessing the spatial dependence of adaptive loci in 43 European and Western Asian goat breeds using AFLP markers

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    Background During the past decades, neutral DNA markers have been extensively employed to study demography, population genetics and structure in livestock, but less interest has been devoted to the evaluation of livestock adaptive potential through the identification of genomic regions likely to be under natural selection. Methodology/Principal findings Landscape genomics can greatly benefit the entire livestock system through the identification of genotypes better adapted to specific or extreme environmental conditions, therefore we analyzed 101 AFLP markers in 43 European and Western Asian goat breeds both with the software MATSAM, based on a correlative approach (SAM), and with MCHEZA and BAYESCAN, two FST based software able to detect markers carrying signatures of natural selection. MATSAM identified four loci possibly under natural selection - also confirmed by FSToutlier methods - and significantly associated with environmental variables such as diurnal temperature range, frequency of precipitation, relative humidity and solar radiation. Conclusions/Significance These results show that landscape genomics can provide useful information on the environmental factors affecting the adaptive potential of livestock living in specific climatic conditions. Besides adding conservation value to livestock genetic resources, this knowledge may lead to the development of novel molecular tools useful to preserve the adaptive potential of local breeds during genetic improvement programs, and to increase the adaptability of industrial breeds to changing environments

    Spatial Areas of Genotype Probability of Cattle Genomic Variants Involved in the Resistance to East Coast Fever: A Tool to Predict Future Disease-Vulnerable Geographical Regions

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    East Coast Fever (ECF) is a livestock disease caused by Theileria parva, a protozoan transmitted by the vector tick Rhipicephalus appendiculatus. This disease causes high mortality in cattle populations of Central and Eastern Africa, especially in exotic breeds. Here, we highlight genomic regions likely involved into tolerance/resistance mechanisms against ECF, and we introduce the estimation of their Spatial Area of Genotype Probability (SPAG) to delimit areas where the concerned genotypes are predicted to be present. During the NEXTGEN project, 803 Ugandan cattle were geo-referenced and genotyped (54K SNPs), while 532 tick occurrences were retrieved from a published database. To get a proxy of the parasite selective pressure, we used WorldClim bioclimatic variables to model vector ecological niche. Landscape genomics models were then used to detect cattle genotypes associated with vector probability of presence, and to estimate their SPAGs. Finally, climate change scenarios for 2070 were considered to compare the predicted shift in the vector niche with the estimated current SPAG. The analysis revealed two main areas of presence of possibly resistance-related genotypes, one South and one East of Lake Victoria. Climate change will probably shift tick niche southwards in the Eastern regions of Lake Victoria, inducing a critical area that currently does not show the candidate genotypes, but where disease will likely spread in the future. The combined use of SPAGs and niche maps could therefore facilitate the identification of regions of concern and to direct future targeted breeding schemes

    Meta-Analysis of Mitochondrial DNA Reveals Several Population Bottlenecks during Worldwide Migrations of Cattle

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    Several studies have investigated the differentiation of mitochondrial DNA in Eurasian, African and American cattle as well as archaeological bovine material. A global survey of these studies shows that haplogroup distributions are more stable in time than in space. All major migrations of cattle have shifted the haplogroup distributions considerably with a reduction of the number of haplogroups and/or an expansion of haplotypes that are rare or absent in the ancestral populations. The most extreme case is the almost exclusive colonization of Africa by the T1 haplogroup, which is rare in Southwest Asian cattle. In contrast, ancient samples invariably show continuity with present-day cattle from the same location. These findings indicate strong maternal founder effects followed by limited maternal gene flow when new territories are colonized. However, effects of adaptation to new environments may also play a rol

    Adaptive introgression from indicine cattle into white cattle breeds from Central Italy

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    Cattle domestication occurred at least twice independently and gave rise to the modern taurine and indicine cattle breeds. European cattle diversity is generally dominated by taurine cattle, although elevated levels of indicine ancestry have been recorded in several breeds from southern Europe. Here we use genome-wide high-density SNP genotyping data to investigate the taurine and indicine ancestry in southern European cattle, based on a dataset comprising 508 individuals from 23 cattle breeds of taurine, indicine and mixed ancestry, including three breeds from Central Italy known to exhibit the highest levels of indicine introgression among southern European breeds. Based on local genomic ancestry analyses, we reconstruct taurine and indicine ancestry genome-wide and along chromosomes. We scrutinise local genomic introgression signals and identify genomic regions that have introgressed from indicine into taurine cattle under positive selection, harbouring genes with functions related to body size and feed efficiency. These findings suggest that indicine-derived traits helped enhance Central Italian cattle through adaptive introgression. The identified genes could provide genomic targets for selection for improved cattle performance. Our findings elucidate the key role of adaptive introgression in shaping the phenotypic features of modern cattle, aided by cultural and livestock exchange among historic human societies

    Effect of climate change on the spatial distribution of genomic variants involved in the resistance to East Coast Fever in Ugandan cattle

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    East Coast Fever (ECF) is a major livestock disease caused by Theileria parva Theiler, 1904, an emo-parasite protozoan transmitted by the tick Rhipicephalus appendiculatus Neumann, 1901. This disease provokes high mortality in cattle populations of East and Central Africa, especially in exotic breeds and crossbreds (Olwoch et al., 2008). Here, we use landscape genomics (Joost et al., 2007) to highlight genomic regions likely involved into tolerance/resistance mechanisms against ECF, and we introduce Spatial Areas of Genotype Probability (SPAG) to delimit territories where favourable allelic variants are predicted to be present. Between 2010 and 2012, the NEXTGEN project (nextgen.epfl.ch) carried out the geo-referencing and genotyping (54K SNPs) of 803 Ugandan cattle, among which 496 were tested for T. parva presence. Moreover, 532 additional R. appendiculatus occurrences were obtained from a published database (Cumming, 1998). Current and future values of 19 bioclimatic variables were also retrieved from the WorldClim database (www.worldclim.org/). In order to evaluate the selective pressure of the parasite, we used MAXENT (Phillips et al., 2006; Muscarella et al., 2014) and a mixed logistic regression (Bates et al., 2014) to model and map the ecological niches of both T. parva and R. appendiculatus. Then, we used a correlative approach (Stucki et al., 2014) to detect molecular markers positively associated with the resulting probabilities of presence and built the corresponding SPAG. Finally, we considered bioclimatic predictors representing two different climate change scenarios for 2070 - one moderate and one severe - to forecast the simultaneous shift of both SPAG and vector/pathogen niches. While suitable ecological conditions for T. parva are predicted to remain constant, the best environment for the vector is predicted around Lake Victoria. However, when considering future conditions, parasite occurrence is expected to decrease because of the contraction of suitable environments for the tick in both scenarios. Landscape genomics’ analyses revealed several markers significantly associated with a high probability of presence of the tick and of the parasite. Among them, we found the marker ARS-BFGL-NGS-113888, whose heterozygous genotype AG showed a positive association. Interestingly, this marker is located close to the gene IRAK-M, an essential component of the Toll-like receptors involved in the immune response against pathogens (Kobayashi et al., 2002). If the implication of this gene into resistance mechanisms against ECF is confirmed, the corresponding SPAG (Figure 1) represents either areas where the variant of interest shows a high probability to exist now, or areas where ecological characteristics are the most favorable to induce its presence under future climatic conditions. Beyond the results presented here, the combined use of SPAG and niche maps could help identifying critical geographical regions that do not present the favourable genetic variant in the present, but where a parasite is likely to expand its range in the future. This may represent a valuable tool to support the identification of current resistant populations and to direct future targeted crossbreeding schemes

    SamBada in Uganda: landscape genomics study of traditional cattle breeds with a large SNP dataset

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    Since its introduction, landscape genomics has developed quickly with the increasing availability of both molecular and topo-climatic data. Current challenges involve processing large numbers of models and disentangling selection from demography. Several methods address the latter, either by estimating a neutral model from population structure or by inferring simultaneously environmental and demographic effects. Here we present Sam!ada, an integrated software for landscape genomic analysis of large datasets. This tool was developed in the framework of NextGen with the objective of characterising traditional Ugandan cattle breeds using single nucleotide polymorphisms (SNPs) data
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