AnABlast: a new in silico strategy for the genome-wide search of novel genes and fossil regions.
AnABlast: a new in silico strategy for the genome-wide search of novel genes and fossil regions.
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DOI：
10.1093/dnares/dsv025
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发表时间：
2015-12
期刊：
影响因子：
--
通讯作者：
Perez-Pulido AJ
中科院分区：
文献类型：
--
作者：
Jimenez J;Duncan CD;Gallardo M;Mata J;Perez-Pulido AJ
在计算机程序的辅助下，基因组注释是现代生物学的重大进步之一。然而，对小而复杂的编码序列的电子识别仍然是具有挑战性的。我们观察到，从编码-但很少从非编码-DNA序列推断的氨基酸序列在低严格的BLAST搜索中积累了比对，这表明这种比对积累可以用来突出已测序DNA中的编码区。为了研究这种可能性，我们开发了一个计算机程序(AnABlast)，它使用低严格的BLAST策略生成查询氨基酸序列中累积的比对曲线。为了验证这种方法，用ANABlast分析了分裂酵母基因组每两个注释外显子之间的所有六帧DNA序列的翻译。ANABlast生成的图谱确定了已知基因的三个新副本，以及实验证据支持的四个新基因。还推测了新的假基因、祖先的羧基和氨基末端消减、复杂的基因重排、古老的mitDNA片段和细菌起源。因此，这种新颖的电子方法提供了一个强大的工具来发现新的基因以及化石编码序列，从而提供了对已注释基因组的进化史的洞察。
Genome annotation, assisted by computer programs, is one of the great advances in modern biology. Nevertheless, the in silico identification of small and complex coding sequences is still challenging. We observed that amino acid sequences inferred from coding—but rarely from non-coding—DNA sequences accumulated alignments in low-stringency BLAST searches, suggesting that this alignments accumulation could be used to highlight coding regions in sequenced DNA. To investigate this possibility, we developed a computer program (AnABlast) that generates profiles of accumulated alignments in query amino acid sequences using a low-stringency BLAST strategy. To validate this approach, all six-frame translations of DNA sequences between every two annotated exons of the fission yeast genome were analysed with AnABlast. AnABlast-generated profiles identified three new copies of known genes, and four new genes supported by experimental evidence. New pseudogenes, ancestral carboxyl- and amino-terminal subtractions, complex gene rearrangements, and ancient fragments of mitDNA and of bacterial origin, were also inferred. Thus, this novel in silico approach provides a powerful tool to uncover new genes, as well as fossil-coding sequences, thus providing insight into the evolutionary history of annotated genomes.
影响因子：
3.7
作者：
Dargahi D;Baillie D;Pio F
通讯作者：
Pio F