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我们能用1000个质体基因组做什么?

What can we do with 1000 plastid genomes?

作者信息

Tonti-Filippini Julian, Nevill Paul G, Dixon Kingsley, Small Ian

机构信息

ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia.

Department of Environment and Agriculture, ARC Centre for Mine Site Restoration, Curtin University, Kent Street, Bentley, WA, 6102, Australia.

出版信息

Plant J. 2017 May;90(4):808-818. doi: 10.1111/tpj.13491. Epub 2017 Mar 30.

DOI:10.1111/tpj.13491
PMID:28112435
Abstract

The plastid genome of plants is the smallest and most gene-rich of the three genomes in each cell and the one generally present in the highest copy number. As a result, obtaining plastid DNA sequence is a particularly cost-effective way of discovering genetic information about a plant. Until recently, the sequence information gathered in this way was generally limited to small portions of the genome amplified by polymerase chain reaction, but recent advances in sequencing technology have stimulated a substantial rate of increase in the sequencing of complete plastid genomes. Within the last year, the number of complete plastid genomes accessible in public sequence repositories has exceeded 1000. This sudden flood of data raises numerous challenges in data analysis and interpretation, but also offers the keys to potential insights across large swathes of plant biology. We examine what has been learnt so far, what more could be learnt if we look at the data in the right way, and what we might gain from the tens of thousands more genome sequences that will surely arrive in the next few years. The most exciting new discoveries are likely to be made at the interdisciplinary interfaces between molecular biology and ecology.

摘要

植物的质体基因组是每个细胞中三个基因组里最小且基因最丰富的,并且通常以最高的拷贝数存在。因此,获取质体DNA序列是发现植物遗传信息的一种特别经济高效的方式。直到最近,通过这种方式收集的序列信息通常仅限于通过聚合酶链反应扩增的基因组小片段,但测序技术的最新进展促使完整质体基因组测序的大幅增加。在过去一年里,公共序列数据库中可获取的完整质体基因组数量已超过1000个。这突如其来的数据洪流在数据分析和解释方面带来了诸多挑战,但也为深入了解大片植物生物学领域提供了关键线索。我们审视了目前所学到的内容,如果以正确的方式看待这些数据还能学到什么,以及在未来几年肯定会出现的数以万计的更多基因组序列中我们可能会获得什么。最令人兴奋的新发现可能会在分子生物学与生态学的跨学科交叉点上产生。

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