一种在全基因组水平上预测植物内源siRNAs的方法
收藏国家林业和草原科学数据中心2022-10-18 更新2024-03-06 收录
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资源简介：
基于全基因组测序数据，利用MITE-Hunter在全基因组中筛选出候选的MITEs元件，并根据配对序列的比对情况过滤假阳性结果；抽取每个MITEs元件两端长度为50 bp的序列；将两端抽取的序列做blast分析，筛选完全匹配的序列，将其作为候选siRNA；利用Pln24NT软件，借助已有的数据库验证siRNA。本发明所述方法能够增加预测通量，进而在大数据量的基础上快速预测出siRNA，并且具有普适性。
Based on whole-genome sequencing data, candidate MITE elements were first screened across the entire genome using MITE-Hunter, with false positive results filtered based on the alignment of paired sequences. Next, 50-bp flanking sequences of each MITE element were extracted. BLAST analysis was then conducted on these extracted flanking sequences, and sequences with perfect matches were selected as candidate siRNAs. Finally, these candidate siRNAs were validated using the Pln24NT software with pre-existing databases. The method described herein enhances prediction throughput, allowing rapid siRNA prediction from large-scale datasets while demonstrating broad general applicability.
提供机构：
国家林业和草原科学数据中心
创建时间：
2022-10-18
