超高精度大规模测序mapping算法FANSe在非模式生物中的应用  

Application of the hyper-accurate mapping algorithm FANSe for next-generation sequencing in non-model organisms

作　　者：曹欣[1] 张弓[1] 

机构地区：[1]暨南大学生命与健康工程研究院功能蛋白质广东省普通高校重点实验室,广州510632

出　　处：《中国科学：生命科学》2017年第7期702-707,共6页Scientia Sinica(Vitae)

基　　金：国家高技术研究发展计划青年科学家专题项目(批准号:2014AA020504);国家自然科学基金(批准号:81322028)资助

摘　　要：大规模测序技术以其高通量、低成本的优势在生物学中得到广泛的应用.但对于基因组尚未被准确测定的非模式生物,传统算法受制于较低的精度、稳健性和容错性,难以有效应对.FANSe系列算法作为目前精度最高、容错性最好的大规模测序快速比对算法,解决了非模式生物二代测序应用所面临的参考库不准确问题,可为非模式生物的基因组、转录组、蛋白质组研究提供准确的结果.本文总结了目前基于FANSe的多种分析方案在非模式动物、植物、微生物以及复杂的共生体系中的应用,为非模式生物的研究提供参考.Next-generation sequencing（NGS） has been widely used in biology studies for its high throughput and low cost.However,for the non-model organisms,whose genome has not been accurately sequenced,the traditional mapping algorithms cannot process them efficiently due to the low accuracy,robustness and error tolerance.FANSe series algorithms is the most accurate and error tolerant mapping algorithm for NGS.It solves the problem of the inaccurate reference database,which is the common problem in the NGS for non-model organisms.Therefore,FANSe provides accurate results for genome,transcriptome and proteome studies of non-model organisms.This review summarizes multiple analysis strategy using FANSe in non-model animals,plants,microorganisms and complex symbiosis system as examples for non-model organisms studies.

关 键 词：二代测序 FANSe算法 非模式生物 高精准 

分 类 号：Q78[生物学—分子生物学]