InvasionDB: A genome and gene database of invasive alien species

• 作者: CAO Xiao-mei CHEN Meng-yao HE Rui HUANG Cong LANG Kun LI Fei QIAN Wan-qiang WANG Shu-ping YANG Nian-wan ZHAN An-ran
• 来源期刊: 农业科学学报（英文）
• 年，卷（期）: 2021,（1）
• 所属期刊栏目: Plant Protection
• 页码范围: 191-200
• 页数: 10页
• 语种: 英文
• DOI: 10.1016/S2095-3119(20)63231-2

摘要

Invasive alien species (IAS) are species whose introduction to areas outside of their native range cause harm to economics, biodiversity, and the environment. Understanding the genetic basis of invasiveness is critical for preventing invasion by an alien species and managing IAS with eco-friendly control methods. In addition, uncovering the genomic features of IAS is essential for accurately predicting invasiveness. However, even though increasing efforts have been devoted to sequencing the genomes of IAS, there is still not an integrated genome database for the invasive biology community. Here, we first determined a list of invasive plants and animals by mining references and databases. Then, we retrieved the genomic and gene data of these IAS, and constructed a database, InvasionDB. InvasionDB encompasses 131 IAS genomes, 76 annotated IAS assemblies, and links these data to conventional functions such as searching for gene coding sequences and Pfam, KEGG, NR annotations, BLAST server, JBrowse, and downloads services. Next, we analyzed 19 invasiveness-related gene families which confer invasiveness in insects. To study the roles of noncoding RNA in invasiveness, we also annotated 135494 miRNAs, 89294 rRNAs, and 2671941 tRNAs from these IAS. In summary, InvasionDB is useful for studying the invasiveness at the genomic level, and thus helps to develop novel management strategies to control IAS.