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利用MACE(cDNA末端大规模分析)对红头丽蝇(双翅目:丽蝇科)蛹进行从头转录组分析和高灵敏度数字基因表达谱分析。

De novo transcriptome analysis and highly sensitive digital gene expression profiling of Calliphora vicina (Diptera: Calliphoridae) pupae using MACE (Massive Analysis of cDNA Ends).

作者信息

Zajac B K, Amendt J, Horres R, Verhoff M A, Zehner R

机构信息

Institute of Legal Medicine, University Hospital Frankfurt, Goethe University, Germany.

GenXPro GmbH, Altenhöferallee 2, 60438 Frankfurt am Main, Germany.

出版信息

Forensic Sci Int Genet. 2015 Mar;15:137-46. doi: 10.1016/j.fsigen.2014.11.013. Epub 2014 Nov 21.

Abstract

Determining a post-mortem interval using the weight or length of blow fly larvae to calculate the insect's age is well established. However, to date, there are only a handful studies dealing with age estimation of blow fly pupae, in which weight or length cannot be used as a relevant parameter. The analysis of genetic markers, which indicate a certain developmental stage, can extend the period for a successful post-mortem interval determination. In order to break new ground in the field of age determination of forensic relevant blow flies, we performed a de novo transcriptome analysis of Calliphora vicina pupae at 15 different developmental stages. Obtained data serve as base to establish molecular age determination techniques. We used a new, deeper, and more cost-effective digital gene expression profiling method called MACE (Massive Analysis of cDNA Ends). We generated 15 libraries out of 15 developmental stages, with 3-8 million reads per library. In total, 53,539 distinct transcripts were detected, and 7548 were annotated to known insect genes. The analysis provides high-resolution gene expression profiles of all covered transcripts, which were used to identify differentially expressed genetic markers as candidates for a molecular age estimation of C. vicina pupae. Moreover, the analysis allows insights into gene activity of pupal development and the relationship between different genes interesting for insect development in general.

摘要

利用丽蝇幼虫的重量或长度来计算昆虫的年龄从而确定死后间隔时间,这一方法已得到广泛认可。然而,迄今为止,仅有少数研究涉及丽蝇蛹的年龄估计,其中重量或长度无法作为相关参数。对指示特定发育阶段的遗传标记进行分析,可延长成功确定死后间隔时间的期限。为了在法医相关丽蝇年龄测定领域开辟新领域,我们对15个不同发育阶段的红头丽蝇蛹进行了从头转录组分析。获得的数据为建立分子年龄测定技术奠定了基础。我们使用了一种新的、更深入且更具成本效益的数字基因表达谱分析方法,称为MACE(cDNA末端大规模分析)。我们从15个发育阶段生成了15个文库,每个文库有300万至800万条 reads。总共检测到53539个不同的转录本,其中7548个被注释为已知的昆虫基因。该分析提供了所有涵盖转录本的高分辨率基因表达谱,用于识别差异表达的遗传标记,作为红头丽蝇蛹分子年龄估计的候选标记。此外,该分析有助于深入了解蛹发育的基因活性以及一般昆虫发育中不同基因之间的关系。

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