The hidden costs of aneuploidy: New insights from yeast
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作者:
Wang, Yuerong
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Univ Chinese Acad Sci, Coll Life Sci, Beijing 100049, Peoples R China
BGI Res, Changzhou 213299, Peoples R China
BGI Res, Shenzhen 518083, Peoples R China
BGI Res, Guangdong Prov Key Lab Genome Read & Write, Shenzhen 518083, Peoples R ChinaUniv Chinese Acad Sci, Coll Life Sci, Beijing 100049, Peoples R China
Wang, Yuerong
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Fu, Xian
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h-index: 0
机构:
BGI Res, Changzhou 213299, Peoples R China
BGI Res, Shenzhen 518083, Peoples R China
BGI Res, Guangdong Prov Key Lab Genome Read & Write, Shenzhen 518083, Peoples R ChinaUniv Chinese Acad Sci, Coll Life Sci, Beijing 100049, Peoples R China
Fu, Xian
[2
,3
,4
]
Shen, Yue
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h-index: 0
机构:
BGI Res, Changzhou 213299, Peoples R China
BGI Res, Shenzhen 518083, Peoples R China
BGI Res, Guangdong Prov Key Lab Genome Read & Write, Shenzhen 518083, Peoples R ChinaUniv Chinese Acad Sci, Coll Life Sci, Beijing 100049, Peoples R China
Shen, Yue
[2
,3
,4
]
机构:
[1] Univ Chinese Acad Sci, Coll Life Sci, Beijing 100049, Peoples R China
[2] BGI Res, Changzhou 213299, Peoples R China
[3] BGI Res, Shenzhen 518083, Peoples R China
[4] BGI Res, Guangdong Prov Key Lab Genome Read & Write, Shenzhen 518083, Peoples R China
The molecular mechanisms underlying the paradoxical effects(1) of aneuploidy are still not completely understood. In this issue, Rojas et al.(2) systematically analyzed the associated costs of aneuploidy and the molecular drivers involved, which revealed that aneuploidy stress is primarily driven by the cumulative effects of genes per chromosome. Notably, gene length was predicted as the most significant indicator of aneuploidy toxicity by machine learning.