Reply to Chen and Zhang: On interpreting genome-wide trends from yeast mutation accumulation data.
Reply to Chen and Zhang: On interpreting genome-wide trends from yeast mutation accumulation data.
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回复陈和张：从酵母突变积累数据解释全基因组趋势。
DOI：
10.1073/pnas.1413861111
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发表时间：
2014
影响因子：
11.1
通讯作者：
Petrov,DmitriA
中科院分区：
文献类型：
--
作者：
Zhu,YuanO;Siegal,MarkL;Hall,DavidW;Petrov,DmitriA
MA mutations in large numbers can provide an unbiased picture of genome-wide patterns. One previously observed pattern is a positive correlation between transcription rate and mutation rate, inferred to be the result of transcription-associated mutagenesis (TAM)(2). In our paper, we used a conservative subset of 181 SNMs to analyze nascent transcription rate (TR) microarray data (3) and noted that the SNM rates observed were not significantly different between genes with varying TRs. Chen and Zhang note that when mRNA sequencing data (mRNA-seq) or nascent transcript sequencing data (NET-seq) are applied to the same question using the full set of 559 exonic SNMs, positions with SNMs have significantly higher mean transcript coverage than the rest of the genome (2). They therefore conclude that the SNM data support TAM. As noted by Chen and Zhang, our discrepant conclusions could be caused by both the use of all 559 SNMs vs. a conservative subset of SNMs and the use of transcript sequencing vs. microarray data (2). Supporting the latter point, the correlation between the mRNA-seq and NET-seq datasets is strong (R2= 0.6344), whereas the correlations between these datasets and the TR microarray dataset we used are not (mRNA-seq∼ TR: R2= 0.1745, NET-seq∼ TR:
