Rojas Julie, Hose James, Auguste Dutcher H, Place Michael, Wolters John F, Hittinger Chris Todd, Gasch Audrey P
Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, WI 53706, USA.
Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI 53706, USA.
bioRxiv. 2024 Apr 13:2024.04.09.588778. doi: 10.1101/2024.04.09.588778.
Although implicated as deleterious in many organisms, aneuploidy can underlie rapid phenotypic evolution. However, aneuploidy will only be maintained if the benefit outweighs the cost, which remains incompletely understood. To quantify this cost and the molecular determinants behind it, we generated a panel of chromosome duplications in and applied comparative modeling and molecular validation to understand aneuploidy toxicity. We show that 74-94% of the variance in aneuploid strains' growth rates is explained by the additive cost of genes on each chromosome, measured for single-gene duplications using a genomic library, along with the deleterious contribution of snoRNAs and beneficial effects of tRNAs. Machine learning to identify properties of detrimental gene duplicates provided no support for the balance hypothesis of aneuploidy toxicity and instead identified gene length as the best predictor of toxicity. Our results present a generalized framework for the cost of aneuploidy with implications for disease biology and evolution.
尽管非整倍体在许多生物体中被认为是有害的，但它可能是快速表型进化的基础。然而，只有当益处超过成本时，非整倍体才会维持下去，而这一点仍未被完全理解。为了量化这种成本及其背后的分子决定因素，我们在[具体内容缺失]中生成了一组染色体重复，并应用比较建模和分子验证来理解非整倍体毒性。我们表明，非整倍体菌株生长速率中74 - 94%的变异是由每条染色体上基因的累加成本所解释的，这是通过使用基因组文库对单基因重复进行测量得到的，同时还有小核仁RNA的有害贡献和转运RNA的有益作用。通过机器学习来识别有害基因重复的特性，并未为非整倍体毒性的平衡假说提供支持，反而将基因长度确定为毒性的最佳预测指标。我们的结果提出了一个关于非整倍体成本的通用框架，对疾病生物学和进化具有启示意义。
