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...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, Invasion DB. Invasion DB 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 invasivenessrelated gene families which confer invasiveness in insects. To study the roles of noncoding RNA in invasiveness, we also annotated 135 494 mi RNAs, 89 294 r RNAs, and 2 671 941 t RNAs from these IAS. In summary, Invasion DB is useful for studying the invasiveness at the genomic level, and thus helps to develop novel management strategies to control IAS.展开更多
基金supported by the National Key Research and Development Program of China (2017YFC1200600 and 2016YFC1200602)the Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences (caascx-2017-2021-IAS)the Shenzhen Science and Technology Program, China (KQTD20180411143628272)。
文摘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, Invasion DB. Invasion DB 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 invasivenessrelated gene families which confer invasiveness in insects. To study the roles of noncoding RNA in invasiveness, we also annotated 135 494 mi RNAs, 89 294 r RNAs, and 2 671 941 t RNAs from these IAS. In summary, Invasion DB is useful for studying the invasiveness at the genomic level, and thus helps to develop novel management strategies to control IAS.
