Division of Infectious Diseases, Department of Medicine, University of Alberta, Edmonton, AB T6G 2R3, Canada.
Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2R3, Canada.
Biomolecules. 2019 Jul 24;9(8):299. doi: 10.3390/biom9080299.
Plastid genome sequences are becoming more readily available with the increase in high-throughput sequencing, and whole-organelle genetic data is available for algae and plants from across the diversity of photosynthetic eukaryotes. This has provided incredible opportunities for studying species which may not be amenable to in vivo study or genetic manipulation or may not yet have been cultured. Research into plastid genomes has pushed the limits of what can be deduced from genomic information, and in particular genomic information obtained from public databases. In this Review, we discuss how research into plastid genomes has benefitted enormously from the explosion of publicly available genome sequence. We describe two case studies in how using publicly available gene data has supported previously held hypotheses about plastid traits from lineage-restricted experiments across algal and plant diversity. We propose how this approach could be used across disciplines for inferring functional and biological characteristics from genomic approaches, including integration of new computational and bioinformatic approaches such as machine learning. We argue that the techniques developed to gain the maximum possible insight from plastid genomes can be applied across the eukaryotic tree of life.
随着高通量测序的发展，质体基因组序列越来越容易获得，藻类和植物的整个细胞器遗传数据可用于光合作用真核生物的多样性。这为研究那些可能不易进行体内研究或遗传操作的物种，或尚未培养的物种提供了极好的机会。对质体基因组的研究推动了从基因组信息，特别是从公共数据库中获得的基因组信息中可以推断出的极限。在这篇综述中，我们讨论了质体基因组的研究如何从大量公开可用的基因组序列中受益匪浅。我们描述了两个案例研究，即如何使用公开可用的基因数据支持先前从藻类和植物多样性中受限于谱系的实验中关于质体特征的假设。我们提出了如何在跨学科领域中，从基因组方法推断功能和生物学特征，包括整合新的计算和生物信息学方法，如机器学习。我们认为，可以将从质体基因组中获得最大可能洞察力的技术应用于整个真核生物进化树上。
