利用基因组简约法开发烟草SNP标记及遗传作图

提出了一种基于基因组简约法开发SNP标记的方法,即利用特定限制性内切酶酶切降低基因组复杂度,利用高通量测序平台对酶切位点周围的目标片段进行富集测序,设计一个生物信息学流程进行序列分析和SNP鉴定。以烤烟DH群体为例,通过基因组简约法收集烟草基因组代表性片段和高通量测序产生11.4 Gb数据,经生物信息学分析获得了1015个高质量SNP位点。以SSR标记为骨架,绘制包括SNP标记在内、标记总数为1307的烤烟遗传连锁图。最后利用该遗传图谱和普通烟草2个祖先种的基因组序列,分析烟草24个连锁群(染色体)之间的同源关系,发现了大量染色体之间的重组或交换事件以及部分染色体之间的共线性。

Development and Genetic Mapping of SNP Markers via Genome Complexity Reduction in Tobacco

We proposed an approach for development of the SNP markers via genome complexity reduction in this study. The restriction enzymes were employed to digest target genome and then collect and sequence the fragments flanking the restriction sites by next-generation sequencing platform. A bioinformatics pipeline was developed for the SNP calling. A flue-cured tobacco DH population was used as a case to test the approach. The tobacco representative fragments were collected via a genome complexity reduction method and sequenced by using Illumina GA sequencer. A total of 1015 SNPs were found based on 11.4 Gb Illumina data using the bioinformatics pipeline. Taken available SSR markers (as backbone markers) together, a genetic linkage map with 1 307 molecular markers was constructed. Large-scale inter-chromosomal (linkage group) DNA combinations or exchanges and several homologous pairs among the tobacco 24 chromosomes were detected based on the genetic map and the available genomic sequences of two tobacco (Nicotiana tabacum L.) wild progenitors.