Analysis of the leaf metabolome in Arabidopsis thaliana mutation accumulation lines reveals association of metabolic disruption and fitness consequence
Analysis of the leaf metabolome in Arabidopsis thaliana mutation accumulation lines reveals association of metabolic disruption and fitness consequence
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DOI：
10.1007/s10682-022-10210-8
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发表时间：
2022-09-10
影响因子：
1.9
通讯作者：
Olson-Manning，Carrie F.
中科院分区：
文献类型：
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作者：
Kreutzmann，Sydney;Pompa，Elizabeth;Olson-Manning，Carrie F.
了解突变影响适应度的机制和突变效应的分布是进化生物学的中心目标。突变累积(MA)系长期以来一直是了解新突变对适应度、表型变异和突变参数的影响的重要工具。然而，在预测特定的新突变对它们对健康的影响方面存在明显的差距。为了直接将自发突变的影响与它们的适合度效应联系起来，我们量化了386种已知化合物在拟南芥初级和次生代谢中的代谢表达，这些拟南芥品系的相对适合度始终高于和低于祖先系。高适合度和低适合度品系在平均突变数量上没有差异，并且共享相同类型的被破坏的代谢途径。然而，与祖先相比，低适合度品系比高适合度品系有更多的代谢亚通路被扰乱。这些结果表明，新突变对适应性的影响较少依赖于被破坏的特定代谢途径，而可能更多地依赖于被破坏的途径的数量。我们无法确定在注释良好的基因中或其附近的突变与其对特征良好的生化途径的影响有任何直接联系，可能是由于对分子功能的不完全注释或控制代谢表达的非遗传变异。我们的发现表明，生物体只需几个突变就可以探索相当大的生理空间。
Understanding the mechanisms by which mutations affect fitness and the distribution of mutational effects are central goals in evolutionary biology. Mutation accumulation (MA) lines have long been an important tool for understanding the effect of new mutations on fitness, phenotypic variation, and mutational parameters. However, there is a clear gap in predicting the effect of specific new mutations to their effects on fitness. In an attempt to directly connect the effect of spontaneous mutations to their fitness effects, we quantified the metabolic expression of 386 known compounds in primary and secondary metabolism inArabidopsis thalianaMA lines that had consistently higher and lower relative fitness than the progenitor. The high and low fitness lines do not have a difference in the average number of mutations and share the same types of metabolic pathways disrupted. However, compared to the progenitor, low fitness lines have significantly more metabolic subpathways disrupted than lines with higher fitness. These results suggest that the effect of a new mutation on fitness depends less on the specific metabolic pathways disrupted and potentially more on the number of disrupted pathways. We fail to identify any direct connection of mutations in or near well annotated genes to their effect on well-characterized biochemical pathways, possibly due to incomplete annotations of molecular function or to non-genetic variation controlling metabolic expression. Our findings indicate that organisms can explore a considerable amount of physiological space with only a few mutations.