Yeast QTL study revealed the importance of pan-genome on life span regulation in specific environmental condition. Pan-genome is involved in life span regulation

Genome-based prediction is one main goal of biology. Even for monogenic traits, prediction may deviate from reality notably due to the presence of genetic modifiers that are found in specific individuals. This is even harder for complex or polygenic phenotypes that need to integrate variations in many genes or pathways. Aging is a fundamental process of life and is regulated by nine known hallmarks. Each of them has the potential of being regulated by different pathways. We used the natural variation found in the budding yeast Saccharomyces cerevisiae to investigate the impact of genetic diversity on aging mechanisms in two different conditions. We found broad variation of chronological aging in both conditions that differs largely despite similar amount of glucose and raffinose were used. An enzyme encoded in the pan-genome of specific strains, described as a melibiase, is responsible to the liberation of all sugar molecules in the trisaccharide raffinose leading ultimately to a decrease of aging in this condition. Moreover, linkage mapping analysis using a biparental population allowed us to detect the WHI2 gene as major regulator of CLS in both glucose and raffinose conditions independently of the presence of the melibiase. Combination of both pan-genome information and Quantitative Trait Locus data are needed to accurate aging prediction in a condition-dependent manner.

基于基因组的预测是生物学的核心目标之一。即便针对单基因性状（monogenic traits），由于特定个体中存在的遗传修饰因子（genetic modifiers），预测结果也可能与实际情况产生显著偏差。而对于需要整合众多基因或通路变异的复杂或多基因表型（polygenic phenotypes）而言，这一预测难度将进一步提升。衰老是生命的基本过程，目前已明确其受九大特征调控，且每一项特征均可能受不同通路调控。本研究以出芽酵母——酿酒酵母（Saccharomyces cerevisiae）的自然变异为材料，探究了遗传多样性在两种不同培养条件下对衰老机制的影响。研究发现，尽管两种培养条件下所使用的葡萄糖与棉子糖剂量一致，二者的时序衰老（chronological aging, CLS）仍存在显著差异。特定菌株泛基因组（pan-genome）所编码的一种被称为棉子糖酶（melibiase）的酶，可水解三糖棉子糖中的全部糖分子，最终降低该条件下的衰老程度。此外，通过对双亲本群体开展连锁作图分析，我们发现WHI2基因可作为葡萄糖与棉子糖两种条件下CLS的主要调控因子，且不受棉子糖酶存在与否的影响。若要实现条件依赖性的精准衰老预测，需同时结合泛基因组信息与数量性状位点（Quantitative Trait Locus, QTL）数据。