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非模式植物中转录组分析策略。

Strategies for transcriptome analysis in nonmodel plants.

机构信息

Department of Horticulture, Cornell University, New York State Agricultural Experiment Station, Geneva, New York 14456, USA.

出版信息

Am J Bot. 2012 Feb;99(2):267-76. doi: 10.3732/ajb.1100334. Epub 2012 Feb 1.

Abstract

Even with recent reductions in sequencing costs, most plants lack the genomic resources required for successful short-read transcriptome analyses as performed routinely in model species. Several approaches for the analysis of short-read transcriptome data are reviewed for nonmodel species for which the genome of a close relative is used as the reference genome. Two approaches using a data set from Phytophthora-challenged Rubus idaeus (red raspberry) are compared. Over 70000000 86-nt Illumina reads derived from R. idaeus roots were aligned to the Fragaria vesca genome using publicly available informatics tools (Bowtie/TopHat and Cufflinks). Alignment identified 16956 putatively expressed genes. De novo assembly was performed with the same data set and a publicly available transcriptome assembler (Trinity). A BLAST search with a maximum e-value threshold of 1.0 × 10(-3) revealed that over 36000 transcripts had matches to plants and over 500 to Phytophthora. Gene expression estimates from alignment to F. vesca and de novo assembly were compared for raspberry (Pearson's correlation = 0.730). Together, alignment to the genome of a close relative and de novo assembly constitute a powerful method of transcriptome analysis in nonmodel organisms. Alignment to the genome of a close relative provides a framework for differential expression testing if alignments are made to the predefined gene-space of a close relative and de novo assembly provides a more robust method of identifying unique sequences and sequences from other organisms in a system. These methods are considered experimental in nonmodel systems, but can be used to generate resources and specific testable hypotheses.

摘要

即使最近测序成本有所降低,但大多数植物缺乏成功进行短读转录组分析所需的基因组资源,而短读转录组分析在模式物种中已常规进行。本文综述了几种用于非模式物种的短读转录组数据分析方法,这些方法利用近亲的基因组作为参考基因组。本文比较了使用近缘种拟南芥基因组作为参考基因组分析桃儿七短读转录组数据的两种方法。从桃儿七根部获得的超过 70000000 个 86-nt Illumina 读数使用公开的信息学工具(Bowtie/TopHat 和 Cufflinks)与 Fragaria vesca 基因组进行比对。比对鉴定出 16956 个推定表达基因。使用相同的数据集和公开的转录本组装器(Trinity)进行从头组装。用最大 e 值阈值为 1.0×10(-3) 的 BLAST 搜索发现,超过 36000 个转录本与植物有匹配,超过 500 个转录本与疫霉属有匹配。用与 Fragaria vesca 基因组比对和从头组装的方法对桃儿七的基因表达估计进行比较(Pearson 相关系数=0.730)。综上所述,与近亲基因组比对和从头组装构成了非模式生物转录组分析的有力方法。与近亲基因组比对为差异表达测试提供了框架,如果比对是针对近亲预定义基因空间进行的,而从头组装则提供了一种更强大的方法来识别系统中独特的序列和来自其他生物体的序列。这些方法在非模式系统中被认为是实验性的,但可以用来生成资源和具体的可测试假设。

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