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无注释基因组条件下叙利亚金黄地鼠肝脏脂代谢的高通量转录组分析。

High throughput transcriptome analysis of lipid metabolism in Syrian hamster liver in absence of an annotated genome.

机构信息

F. Hoffmann-La Roche AG, pRED, Postfach, Basel, 4070, Switzerland.

出版信息

BMC Genomics. 2013 Apr 10;14:237. doi: 10.1186/1471-2164-14-237.

Abstract

BACKGROUND

Whole transcriptome analyses are an essential tool for understanding disease mechanisms. Approaches based on next-generation sequencing provide fast and affordable data but rely on the availability of annotated genomes. However, there are many areas in biomedical research that require non-standard animal models for which genome information is not available. This includes the Syrian hamster Mesocricetus auratus as an important model for dyslipidaemia because it mirrors many aspects of human disease and pharmacological responses. We show that complementary use of two independent next generation sequencing technologies combined with mapping to multiple genome databases allows unambiguous transcript annotation and quantitative transcript imaging. We refer to this approach as "triple match sequencing" (TMS).

RESULTS

Contigs assembled from a normalized Roche 454 hamster liver library comprising 1.2 million long reads were used to identify 10'800 unique transcripts based on homology to RefSeq database entries from human, mouse, and rat. For mRNA quantification we mapped 82 million SAGE tags (SOLiD) from the same RNA source to the annotated hamster liver transcriptome contigs. We compared the liver transcriptome of hamster with equivalent data from human, rat, minipig, and cynomolgus monkeys to highlight differential gene expression with focus on lipid metabolism. We identify a cluster of five genes functionally related to HDL metabolism that is expressed in human, cynomolgus, minipig, and hamster but lacking in rat as a non-responder species for lipid lowering drugs.

CONCLUSIONS

The TMS approach is suited for fast and inexpensive transcript profiling in cells or tissues of species where a fully annotated genome is not available. The continuously growing number of well annotated reference genomes will further empower reliable transcript identification and thereby raise the utility of the method for any species of interest.

摘要

背景

全转录组分析是理解疾病机制的重要工具。基于下一代测序的方法提供了快速且经济实惠的数据,但依赖于注释基因组的可用性。然而,在生物医学研究中有许多领域需要非标准的动物模型,这些模型的基因组信息不可用。这包括叙利亚仓鼠(Mesocricetus auratus)作为脂代谢紊乱的重要模型,因为它反映了许多人类疾病和药物反应的方面。我们表明,两种独立的下一代测序技术的互补使用结合映射到多个基因组数据库可以实现明确的转录本注释和定量转录本成像。我们将这种方法称为“三重匹配测序”(TMS)。

结果

从包含 120 万个长读段的罗氏 454 正常化仓鼠肝脏文库组装的 contigs 基于与来自人类、小鼠和大鼠的 RefSeq 数据库条目同源性,鉴定了 10800 个独特的转录本。为了进行 mRNA 定量,我们将来自同一 RNA 源的 8200 万个 SAGE 标签(SOLiD)映射到注释的仓鼠肝脏转录本 contigs。我们比较了仓鼠与人类、大鼠、迷你猪和食蟹猴的肝脏转录组,以突出脂质代谢的差异基因表达。我们确定了一个与 HDL 代谢功能相关的五个基因簇,这些基因在人类、食蟹猴、迷你猪和仓鼠中表达,但在大鼠中作为降低脂质药物的非反应物种缺失。

结论

TMS 方法适用于快速且经济实惠的细胞或组织中转录本谱分析,对于没有完全注释基因组的物种。不断增加的注释良好的参考基因组数量将进一步增强可靠的转录本识别能力,从而提高该方法对任何感兴趣物种的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/063e/3639954/824cdd4868ea/1471-2164-14-237-1.jpg

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