The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock

Simple Summary:& nbsp;After domestication in specific regions, livestock followed human migrations and colonized the whole world. During this population expansion, human and natural selection, together with demographic events, molded the livestock genome leading to local breeds and populations able to produce milk, meat, wool and tractive power in many different agro-climatic conditions. The climate is changing, with temperatures and the frequency of extreme climatic events increasing, which affects livestock welfare and production efficiency, particularly of the highly productive breeds. Genomics is now able to explore the DNA of local breeds adapted to extreme environments in search of genes carrying signatures of selection for adaptation. This review summarizes methods used to accomplish this task, giving examples of results achieved and perspectives for future breeding. Livestock radiated out from domestication centres to most regions of the world, gradually adapting to diverse environments, from very hot to sub-zero temperatures and from wet and humid conditions to deserts. The climate is changing; generally global temperature is increasing, although there are also more extreme cold periods, storms, and higher solar radiation. These changes impact livestock welfare and productivity. This review describes advances in the methodology for studying livestock genomes and the impact of the environment on animal production, giving examples of discoveries made. Sequencing livestock genomes has facilitated genome-wide association studies to localize genes controlling many traits, and population genetics has identified genomic regions under selection or introgressed from one breed into another to improve production or facilitate adaptation. Landscape genomics, which combines global positioning and genomics, has identified genomic features that enable animals to adapt to local environments. Combining the advances in genomics and methods for predicting changes in climate is generating an explosion of data which calls for innovations in the way big data sets are treated. Artificial intelligence and machine learning are now being used to study the interactions between the genome and the environment to identify historic effects on the genome and to model future scenarios.

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

Stéphane Joost, Estelle Rochat, Elia Vajana

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.

2015

Aerosol Transport and Distribution

Quentin Bourgeois

The fourth report of the Intergovernmental Panel of Climate Change (IPCC) unambiguously indicates that the climate is changing. Climate change is induced by changes in atmospheric abundances of greenhouse gases and aerosols, solar radiation and land surface properties, which all alter the radiative balance of the Earth. Among them, greenhouse gases and aerosols are likely the compounds affecting the climate the most. While greenhouse gases warm the Earth, aerosols influence its radiative balance by scattering and absorbing solar radiation (the direct effect), and by modifying cloud amount and properties (the indirect effect). The radiative forcing of aerosols on the climate is however the less understood among the various forcings currently considered in the IPCC assessment. This is likely related to the lack of comprehensive and accurate observations of aerosols (and in particular of their vertical distribution) which thus makes global aerosol models difficult to constrain. Recent model intercomparisons have indicated that different assumptions regarding aerosol emissions, formation and growing properties, and removal processes generate large diversities within models. These large diversities are found in particular in the Arctic and the upper troposphere region where extreme surrounding conditions take place, limiting instrument sensitivity and accuracy. The objectives of this thesis are to better quantify the processes driving the aerosol distribution in regions where the uncertainties are the largest, including the Arctic region and the upper troposphere, and to assess the quality of CALIOP observations. For this purpose, we used the fully coupled global climate-aerosol-chemistry ECHAM5-HAMMOZ model conjointly with a suite of remote sensing observations including the CALIOP satellite instrument, which provides the vertical distribution of aerosols. The model predicts the size distribution and composition of aerosols as well as the number concentration of cloud droplets and ice crystals. We first investigated the processes that drive the transport of soluble and insoluble compounds toward the Arctic in the ECHAM5-HAMMOZ model. Recognizing that scavenging processes may be an issue in global models, we "re-visited" their properties in ECHAM5-HAMMOZ. We find that the model better reproduces the aerosol vertical distribution in the northern mid- and high-latitudes, especially in the free troposphere, by decreasing aerosol scavenging coefficients in the model. Using smaller aerosol scavenging coefficients results in an increase of aerosol burden and lifetime, especially in the Arctic. In addition, the Arctic haze phenomenon is better represented in the simulation using decreased aerosol scavenging coefficients. The relative contributions of different processes governing the transport of aerosols from the midlatitudes toward the Arctic together with the relative contributions of different geopolitical source regions were then quantified. We find that Europe and Siberia contribute the most to the Arctic pollution even though Asian anthropogenic emissions are much larger. The model suggests that BC emitted in Siberia and Europe is ten times more efficiently deposited onto the Arctic than BC emitted in Asia. We next investigated an aerosol layer that forms in the vicinity of the tropical tropopause layer (TTL) over the southern Asian and Indian Ocean region. Aerosols in this layer are observed with the CALIOP instrument even though ice clouds partly mask their signal. The aerosol layer follows the Inter Tropical Convergence Zone (ITCZ), which indicates that these aerosols are likely transported during convective processes. The ECHAM5.5-HAM2 model reproduces such an aerosol layer in the TTL over the same region but clearly overestimates CALIOP data. Model results suggest that aerosols in this layer are mostly sulfate particles transported during convective processes and originating from natural sources. The shortwave forcing of this aerosol layer is estimated. Finally, we assessed the accuracy of aerosol extinction retrievals from the CALIOP satellite instrument by comparing them with remote sensing observations such as AERONET, MODIS and MISR over the last four years. Overall, standard CALIOP products underestimate by 50% observed aerosol extinctions. However, this comparison is substantially improved by screening CALIOP data. The comparison of the CALIOP screened product with the ECHAM5.5-HAM2 model shows large disparities in model results. The model reproduces quite well the observed interannual variability and vertical distribution of aerosols in Europe and North Africa while it underestimates them in America and Asia. This is likely due to an underestimate of dust and anthropogenic emissions in North America and Asia.

EPFL2012

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

Stéphane Joost

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.