DNA Motif Recognition Modeling from Protein Sequences.
DNA Motif Recognition Modeling from Protein Sequences.
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DOI：
10.1016/j.isci.2018.09.003
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发表时间：
2018-09-28
期刊：
影响因子：
5.8
通讯作者：
Wong KC
中科院分区：
文献类型：
--
作者：
Wong KC
虽然现有的DNA序列基序发现工作非常多，但在不进行任何湿实验室实验的情况下，从多个DNA结合结构域家族的蛋白质序列中推断DNA基序的机制知识仍然缺乏。因此，提出了k谱识别模型，以尽可能高的分辨率解决问题。k谱模型可以从蛋白质序列中捕获DNA基序模式，其中局部序列上下文和核苷酸依赖性可以完全考虑在内。采用多种评估指标，对5个dna结合家族（即bHLH， bZIP， ETS， Forkhead和Homeodomain）的92种蛋白的数百万k-mer结合强度进行了测量，展示了其竞争优势。此外，它不仅有助于DNA基序识别建模，而且可以帮助在全基因组范围内优先考虑转录因子结合位点上观察到的甚至未观察到的单核苷酸变异结合。基于蛋白质的DNA基序建模是理解基因调控的基础。该框架首次以最高的序列分辨率提出，并在来自5个家族的92种蛋白质的数百万k-mer强度上进行了验证。它可以优先考虑DNA基序上未观察到的调节单核苷酸变异。数量遗传学;生物信息学;计算生物学;DNA图案
Although the existing works on DNA motif discovery on DNA sequences are plethoric, mechanistic knowledge to infer DNA motifs from protein sequences across multiple DNA-binding domain families without conducting any wet-lab experiments is still lacking. Therefore, the k-spectrum recognition modeling is proposed to address the issues at the highest possible resolutions. The k-spectrum model can capture DNA motif patterns from protein sequences at the resolution in which local sequence context and nucleotide dependency can be taken into account completely. Multiple evaluation metrics are adopted and measured on millions of k-mer binding intensities from 92 proteins across 5 DNA-binding families (i.e., bHLH, bZIP, ETS, Forkhead, and Homeodomain), demonstrating its competitive edges. In addition, it not only can contribute to DNA motif recognition modeling but also can help prioritize the observed or even unobserved binding of single nucleotide variants on transcription factor binding sites in a genome-wide manner. DNA motif modeling from protein is fundamental for understanding gene regulation A framework is proposed at the highest possible sequence resolution for the first time It is validated on millions of k-mer intensities from 92 proteins across 5 families It can prioritize the unobserved regulatory single nucleotide variants on DNA motifs Genetics; Quantitative Genetics; Bioinformatics; Computational Biology; DNA Motifs
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影响因子：
48
作者：
Kasinathan, Sivakanthan;Orsi, Guillermo A.;Zentner, Gabriel E.;Ahmad, Kami;Henikoff, Steven
通讯作者：
Henikoff, Steven
DOI：
10.1093/bioinformatics/btx480
发表时间：
2017-11-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
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作者：
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通讯作者：
Gao X
影响因子：
14.9
作者：
Kheradpour P;Kellis M
通讯作者：
Kellis M
影响因子：
14.9
作者：
Jones, S;Shanahan, HP;Thornton, JM
通讯作者：
Thornton, JM
影响因子：
5.8
作者：
Macintyre, Geoff;Bailey, James;Kowalczyk, Adam
通讯作者：
Kowalczyk, Adam