Data from: Fitness change in relation to mutation number in spontaneous mutation accumulation lines of Chlamydomonas reinhardtii

Although all genetic variation ultimately stems from mutations, their properties are difficult to study directly. Here, we used multiple mutation accumulation (MA) lines derived from five genetic backgrounds of the green algae Chlamydomonas reinhardtii that have been previously subjected to whole genome sequencing to investigate the relationship between the number of spontaneous mutations and change in fitness from a non-evolved ancestor. MA lines were on average less fit than their ancestors and we detected a significantly negative correlation between the change in fitness and the total number of accumulated mutations in the genome. Likewise, the number of mutations located within coding regions significantly and negatively impacted MA line fitness. We used the fitness data to parameterize a maximum likelihood model to estimate discrete categories of mutational effects, and found that models containing one to two mutational effect categories (one neutral and one deleterious category) fitted the data best. However, the best-fitting mutational effects models were highly dependent on the genetic background of the ancestral strain.

尽管所有遗传变异最终都源自突变，但直接研究其特性却存在较大难度。本研究利用源自5种此前已完成全基因组测序的莱茵衣藻（Chlamydomonas reinhardtii）遗传背景的多组突变累积（MA）品系，探究了自发突变总数与非进化祖先适合度变化之间的关联。实验结果显示，MA品系的适合度平均低于其祖先菌株，且我们检测到适合度变化与基因组中累积突变总数之间存在显著负相关关系；同样，编码区域内的突变数量也对MA品系的适合度产生了显著负向影响。我们利用适合度数据构建最大似然模型以估算突变效应的离散类别，结果发现包含1至2类突变效应（1类中性突变与1类有害突变）的模型对数据的拟合效果最优。不过，拟合度最佳的突变效应模型高度依赖于祖先菌株的遗传背景。