Improved Identification of Small Open Reading Frames Encoded Peptides by Top-Down Proteomic Approaches and De Novo Sequencing.
Improved Identification of Small Open Reading Frames Encoded Peptides by Top-Down Proteomic Approaches and De Novo Sequencing.
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通过自上而下的蛋白质组学方法和从头测序改进小开放阅读框编码肽的鉴定
DOI：
10.3390/ijms22115476
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发表时间：
2021-05-22
影响因子：
5.6
通讯作者：
Wan C
中科院分区：
文献类型：
--
作者：
Wang B;Wang Z;Pan N;Huang J;Wan C
小开放阅读框（sORFs）具有翻译潜能，可产生在各种生物过程中起关键作用的肽段。然而，许多sORF编码的肽段（SEPs）仍处于预测阶段。在此，我们构建了一种结合自上而下和从头测序的策略来分析SEPs，以提高SEP的鉴定和序列覆盖度。通过从头测序，我们鉴定出了1682种映射到2544个人类sORFs的肽段，这些在本研究中均为首次表征。这些新的sORFs中有三分之二存在阅读框移位，并使用非ATG起始密码子。自上而下的方法鉴定出了241种人类SEPs，具有较高的序列覆盖度。通过自下而上的数据库搜索得到的肽段平均长度为19个氨基酸（AA）；从头测序得到的为9个AA；自上而下的方法得到的为25个AA。较长的肽段可提高序列覆盖度，更有效地将SEPs与已知基因编码序列区分开来。自上而下的方法在鉴定具有连续K/R或高K/R含量的肽段方面具有优势，这在自下而上的方法中是不利的。我们的方法能够探索新的编码sORFs，并获得其SEPs的高精度序列，这也有利于未来的功能研究。
Small open reading frames (sORFs) have translational potential to produce peptides that play essential roles in various biological processes. Nevertheless, many sORF-encoded peptides (SEPs) are still on the prediction level. Here, we construct a strategy to analyze SEPs by combining top-down and de novo sequencing to improve SEP identification and sequence coverage. With de novo sequencing, we identified 1682 peptides mapping to 2544 human sORFs, which were all first characterized in this work. Two-thirds of these new sORFs have reading frame shifts and use a non-ATG start codon. The top-down approach identified 241 human SEPs, with high sequence coverage. The average length of the peptides from the bottom-up database search was 19 amino acids (AA); from de novo sequencing, it was 9 AA; and from the top-down approach, it was 25 AA. The longer peptide positively boosts the sequence coverage, more efficiently distinguishing SEPs from the known gene coding sequence. Top-down has the advantage of identifying peptides with sequential K/R or high K/R content, which is unfavorable in the bottom-up approach. Our method can explore new coding sORFs and obtain highly accurate sequences of their SEPs, which can also benefit future function research.
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影响因子：
7.4
作者：
Ma J;Diedrich JK;Jungreis I;Donaldson C;Vaughan J;Kellis M;Yates JR 3rd;Saghatelian A
通讯作者：
Saghatelian A
影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
Hao, Yajing;Zhang, Lili;Chen, Runsheng
通讯作者：
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