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衣藻基因组计划:十年回顾。

The Chlamydomonas genome project: a decade on.

作者信息

Blaby Ian K, Blaby-Haas Crysten E, Tourasse Nicolas, Hom Erik F Y, Lopez David, Aksoy Munevver, Grossman Arthur, Umen James, Dutcher Susan, Porter Mary, King Stephen, Witman George B, Stanke Mario, Harris Elizabeth H, Goodstein David, Grimwood Jane, Schmutz Jeremy, Vallon Olivier, Merchant Sabeeha S, Prochnik Simon

机构信息

Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA.

Centre National de la Recherche Scientifique (CNRS), Unité Mixte de Recherche 7141, Institut de Biologie Physico-Chimique, Paris, France.

出版信息

Trends Plant Sci. 2014 Oct;19(10):672-80. doi: 10.1016/j.tplants.2014.05.008. Epub 2014 Jun 17.

DOI:10.1016/j.tplants.2014.05.008
PMID:24950814
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4185214/
Abstract

The green alga Chlamydomonas reinhardtii is a popular unicellular organism for studying photosynthesis, cilia biogenesis, and micronutrient homeostasis. Ten years since its genome project was initiated an iterative process of improvements to the genome and gene predictions has propelled this organism to the forefront of the omics era. Housed at Phytozome, the plant genomics portal of the Joint Genome Institute (JGI), the most up-to-date genomic data include a genome arranged on chromosomes and high-quality gene models with alternative splice forms supported by an abundance of whole transcriptome sequencing (RNA-Seq) data. We present here the past, present, and future of Chlamydomonas genomics. Specifically, we detail progress on genome assembly and gene model refinement, discuss resources for gene annotations, functional predictions, and locus ID mapping between versions and, importantly, outline a standardized framework for naming genes.

摘要

莱茵衣藻这种绿藻是用于研究光合作用、纤毛生物发生和微量营养素稳态的一种广受欢迎的单细胞生物。自其基因组计划启动十年以来,对基因组和基因预测的迭代改进过程已将这种生物推向了组学时代的前沿。最新的基因组数据存于联合基因组研究所(JGI)的植物基因组门户网站Phytozome中,包括按染色体排列的基因组和高质量的基因模型,这些模型具有由大量全转录组测序(RNA-Seq)数据支持的可变剪接形式。我们在此展示莱茵衣藻基因组学的过去、现在和未来。具体而言,我们详述了基因组组装和基因模型优化方面的进展,讨论了基因注释、功能预测以及不同版本之间基因座ID映射的资源,并且重要的是,概述了一个标准化的基因命名框架。

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本文引用的文献

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