Climate Genomics for Farm Animal Adaptation

ClimGen是一个侧重于识别和利用组学技术建立牲畜对气候变化的适应能力的项目。该项目将汇集以往和正在进行的国家、欧盟和全球为了解牲畜对极端气候的适应所做的努力，寻求确定可用于预测牲畜种群对热及相关挑战的适应的基因组工具和生物标志物。除了科学调查，ClimGen还将开发和评估改良育种策略的效果，这些策略利用组学信息迅速使牲畜种群具备抵御气候变化短期、中期和长期负面影响所需的复原力。ClimGen还将作为利益相关者的相关信息来源，他们将参与并影响项目的发展。ClimGen的活动可以分为三个部分。首先，我们将开展数据挖掘和空白填补工作，以确定在整个欧洲以及非洲北部和中部具有挑战性的气候条件下发生的牛、绵羊和山羊种群的基因组选择目标。将分析来自欧洲各地的重复气候对比数据，包括喀尔巴阡山脉地区的新样本、极北地区的牛和羊数据以及极南地区（摩洛哥）的绵羊和山羊数据。通过这种方式，ClimGen将最大限度地利用已经产生但没有被分析以检测不同气候的适应情况的数据，并且将只专注于在最需要数据的热点地区生成数据。其次，我们将开展三个案例研究实验，在转录组和表观基因组中寻找气候适应的生物标志物。这些研究将分析对比系统，并试图检测1)在对比热环境下的绵羊和山羊，2)在控制温度环境下的热应激猪，以及3)在免疫和热应激下的红腿鹧鸪的特征变化。生物标志物反应将在这些不同的系统中进行比较，并与第一个活动中确定的选择目标进行比较。最后，这些数据将用于评估利用最先进的模拟技术为牲畜种群培育气候适应能力的新策略，假设采用混合和基因组选择等不同方法，并将其与更传统的育种方法在短期、中期和长期时间尺度上的相对效率进行比较。

ClimGen is a project that focuses on the identification and use of 'omics technology for building livestock resilience to climate change. Bringing together previous and ongoing national, EU and global efforts to understand livestock adaptation to climatic extremes, the project will seek to identify genomic tools and biomarkers that can be used to predict adaptation in livestock populations to thermal and related challenges. Alongside scientific investigation, ClimGen will also develop and assess the efficacy of modified breeding strategies that use 'omics information to rapidly equip livestock populations with the resilience that will be required to withstand the predicted negative effects of climate change in the short, medium and long-term. ClimGen will also act as a source of relevant information for Stakeholders, who will both participate in and influence the development of the project. ClimGen's activities can be divided into three. First we will carry out a data-mining and gap filling exercise for identifying genomic targets of selection in cattle, sheep and goat populations that occur in challenging climates throughout Europe and in northern and central Africa. Replicated climate contrast data will be analysed from across Europe, including new samples in the Carpathian region, data for cattle and sheep in the extreme north and data for sheep and goats in the extreme south (Morocco). In this way ClimGen will make maximum use of data that have already been generated but not analysed to detect adaptation across climates and will only concentrate on producing data in hotspot regions where it is most needed.Second, we will carry out three case study experiments to find biomarkers of climate adaptation within the transcriptome and epigenome. These studies will analyse contrasting systems and seek to detect profile changes in 1) sheep and goats in contrasting thermal environments, 2) in pigs under thermal stress with controlled temperature environments and 3) in red-legged partridges under immune and thermal stress. Biomarker responses will be compared among these diverse systems and compared with the selection targets identified in the first activity.Finally, these data will be used in an assessment of new strategies for breeding climate resilience into livestock populations using state-of-the-art simulations, assuming different approaches such as admixture and genomic selection, which will be compared with more traditional breeding methods in terms of their comparative efficiency over short, medium and longer timescales.