GENESPACE tracks regions of interest and gene copy number variation across multiple genomes.
GENESPACE tracks regions of interest and gene copy number variation across multiple genomes.
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Genespace跟踪了多个基因组的感兴趣区域和基因拷贝数变化。
DOI：
10.7554/elife.78526
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发表时间：
2022-09-09
期刊：
影响因子：
7.7
通讯作者：
Schmutz, Jeremy
中科院分区：
文献类型：
--
作者：
Lovell, John T.;Sreedasyam, Avinash;Schranz, M. Eric;Wilson, Melissa;Carlson, Joseph W.;Harkess, Alex;Emms, David;Goodstein, David M.;Schmutz, Jeremy
许多分类群中多个染色体规模参考基因组序列的发展已经产生了分子进化模式和过程的高分辨率视图。尽管如此，在几乎所有真核系统中，利用多个基因组的信息仍然是一个重大挑战。这些挑战包括研究染色体结构的进化、寻找数量性状基因座的候选基因、以及测试有关物种形成和适应的假设。在这里，我们提出了 GENESPACE，它通过整合保守的基因顺序和直系学来定义多个基因组中所有基因的预期物理位置，从而解决这些挑战。我们通过剖析生物组织三个层面的存在与不存在、拷贝数和结构变异来证明这种实用性：跨越 3 亿年的脊椎动物性染色体进化、禾本科（禾本科）植物家族的多样性以及 26 个玉米品种。 GENESPACE R 软件包中构建和可视化同线性直系同源的方法为现有基因家族和同线性程序提供了重要补充，特别是在多倍体、远交和其他复杂基因组中。基因组是个体的完整 DNA 序列。它是医学、农业和保护生物学许多研究的重要基础。遗传学的进步使得快速测序或读出许多生物体的基因组成为可能。对于密切相关的物种，科学家可以进行详细的比较，揭示具有共同过去或共同作用的相似基因，但比较关系较远的生物体仍然很困难。一项主要挑战是基因在进化过程中经常丢失或重复。更有信心的一种方法是研究“同线性”，或者基因在基因组中如何组织或排序。在某些物种群体中，同线性在数百万年的进化中持续存在。将序列相似性与基因顺序相结合可以使远缘物种之间的比较更加稳健。为此，洛弗尔等人。开发了 GENESPACE，这是一种将 DNA 序列之间的相似性与基因组中基因顺序联系起来的软件。这使得研究人员能够可视化和探索相关的 DNA 序列，并确定基因是否丢失或重复。为了证明 GENESPACE 的价值，Lovell 等人。探索脊椎动物和开花植物的进化。该软件能够突出鸟类和哺乳动物独特性染色体之间的共享序列，并且能够追踪在玉米、小麦和水稻等草类作物进化中重要的基因位置。以这种方式探索遗传密码可以更好地理解基因组重要部分的进化。它还可以让科学家找到用于作物改良等应用的目标基因。洛弗尔等人。设计的 GENESPACE 软件易于其他科学家使用，使他们只需很少的编程技能即可制作图形并执行分析。
The development of multiple chromosome-scale reference genome sequences in many taxonomic groups has yielded a high-resolution view of the patterns and processes of molecular evolution. Nonetheless, leveraging information across multiple genomes remains a significant challenge in nearly all eukaryotic systems. These challenges range from studying the evolution of chromosome structure, to finding candidate genes for quantitative trait loci, to testing hypotheses about speciation and adaptation. Here, we present GENESPACE, which addresses these challenges by integrating conserved gene order and orthology to define the expected physical position of all genes across multiple genomes. We demonstrate this utility by dissecting presence–absence, copy-number, and structural variation at three levels of biological organization: spanning 300 million years of vertebrate sex chromosome evolution, across the diversity of the Poaceae (grass) plant family, and among 26 maize cultivars. The methods to build and visualize syntenic orthology in the GENESPACE R package offer a significant addition to existing gene family and synteny programs, especially in polyploid, outbred, and other complex genomes. The genome is the complete DNA sequence of an individual. It is a crucial foundation for many studies in medicine, agriculture, and conservation biology. Advances in genetics have made it possible to rapidly sequence, or read out, the genome of many organisms. For closely related species, scientists can then do detailed comparisons, revealing similar genes with a shared past or a common role, but comparing more distantly related organisms remains difficult. One major challenge is that genes are often lost or duplicated over evolutionary time. One way to be more confident is to look at ‘synteny’, or how genes are organized or ordered within the genome. In some groups of species, synteny persists across millions of years of evolution. Combining sequence similarity with gene order could make comparisons between distantly related species more robust. To do this, Lovell et al. developed GENESPACE, a software that links similarities between DNA sequences to the order of genes in a genome. This allows researchers to visualize and explore related DNA sequences and determine whether genes have been lost or duplicated. To demonstrate the value of GENESPACE, Lovell et al. explored evolution in vertebrates and flowering plants. The software was able to highlight the shared sequences between unique sex chromosomes in birds and mammals, and it was able to track the positions of genes important in the evolution of grass crops including maize, wheat, and rice. Exploring the genetic code in this way could lead to a better understanding of the evolution of important sections of the genome. It might also allow scientists to find target genes for applications like crop improvement. Lovell et al. have designed the GENESPACE software to be easy for other scientists to use, allowing them to make graphics and perform analyses with few programming skills.