Genome Informatics Facility, Iowa State University, Osborne Dr, Ames, IA 50011, USA.
Department of Plant Pathology and Microbiology, Iowa State University, Pammel Dr, Ames, IA 50011, USA.
Database (Oxford). 2019 Jan 1;2019(1). doi: 10.1093/database/baz111.
Soybean is an important worldwide crop, and farmers continue to experience significant yield loss due to the soybean cyst nematode (SCN), Heterodera glycines. This soil-borne roundworm parasite is rated the most important pathogen problem in soybean production. The infective nematodes enter into complex interactions with their host plant by inducing the development of specialized plant feeding cells that provide the parasites with nourishment. Addressing the SCN problem will require the development of genomic resources and a global collaboration of scientists to analyze and use these resources. SCNBase.org was designed as a collaborative hub for the SCN genome. All data and analyses are downloadable and can be analyzed with three integrated genomic tools: JBrowse, Feature Search and BLAST. At the time of this writing, a number of genomic and transcriptomic data sets are already available, with 43 JBrowse tracks and 21 category pages describing SCN genomic analyses on gene predictions, transcriptome and read alignments, effector-like genes, expansion and contraction of genomic repeats, orthology and synteny with related nematode species, Single Nucleotide Polymorphism (SNPs) from 15 SCN populations and novel splice sites. Standard functional gene annotations were supplemented with orthologous gene annotations using a comparison to nine related plant-parasitic nematodes, thereby enabling functional annotations for 85% of genes. These annotations led to a greater grasp on the SCN effectorome, which include over 3324 putative effector genes. By designing SCNBase as a hub, future research findings and genomic resources can easily be uploaded and made available for use by others with minimal needs for further curation. By providing these resources to nematode research community, scientists will be empowered to develop novel, more effective SCN management tools.
大豆是一种重要的世界性作物,但由于大豆胞囊线虫(SCN)的侵害,农民的大豆产量仍持续遭受重大损失。这种土传的圆形线虫寄生虫被认为是大豆生产中最重要的病原体问题。感染性线虫通过诱导专门的植物取食细胞的发育,与宿主植物发生复杂的相互作用,为寄生虫提供营养。解决 SCN 问题需要开发基因组资源,并需要全球科学家合作来分析和利用这些资源。SCNBase.org 被设计为 SCN 基因组的协作中心。所有的数据和分析都可以下载,并可以使用三个集成的基因组工具进行分析:JBrowse、特征搜索和 BLAST。在撰写本文时,已经有许多基因组和转录组数据集可用,其中包括 43 个 JBrowse 轨道和 21 个类别页面,描述了 SCN 基因组分析的基因预测、转录组和读取比对、效应子样基因、基因组重复的扩展和收缩、与相关线虫物种的同源和同线性、来自 15 个 SCN 种群的单核苷酸多态性(SNP)和新的剪接位点。标准功能基因注释通过与 9 种相关植物寄生线虫进行比较,补充了同源基因注释,从而使 85%的基因具有功能注释。这些注释使我们对 SCN 效应子组有了更深入的了解,其中包括超过 3324 个推定的效应子基因。通过将 SCNBase 设计为一个中心,未来的研究发现和基因组资源可以很容易地上传到这个平台上,供其他人使用,而无需进行进一步的管理。通过向线虫研究社区提供这些资源,科学家将有能力开发出更有效、更有针对性的 SCN 管理工具。