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Using transcriptome Shannon entropy to evaluate the off-target effects and safety of insecticidal siRNAs
MA Wei-hua, WU Tong, ZHANG Zan, LI Hang, SITU Gong-ming, YIN Chuan-lin, YE Xin-hai, CHEN Meng-yao, ZHAO Xian-xin, HE Kang, LI Fei
2022, 21 (1): 170-177.   DOI: 10.1016/S2095-3119(20)63394-9
Abstract213)      PDF in ScienceDirect      
A recent breakthrough in agricultural biotechnology is the introduction of RNAi-mediated strategies in pest control.  However, the off-target effects of RNAi pest control are still not fully understood.  Here, we studied the off-target effects of two insecticidal siRNAs in both target and non-target insects.  The results revealed that off-target effects of insecticidal siRNAs occur widely in both target and non-target insects.  We classified the expression-changed genes according to their homology to the siRNA-targeted gene, related KEGG pathways with the siRNA-targeted gene and continuous matches with siRNAs.  Surprisingly, the unintended significant changes in gene expression levels did not strictly match with the number of contiguous nucleotides in the siRNAs.  As expected, the expression of small portions of the homologous and KEGG-related genes were significantly changed.  We calculated the Shannon entropy of the transcriptome profile of the insects after injecting them with insecticidal siRNAs.  Though hundreds of genes were affected in their expression levels post siRNA-treatment, the Shannon entropy of the transcriptome remained unchanged, suggesting that the transcriptome expression was balanced.  Our results provide evidence that siRNAs cross-reacted with individual genes in non-target species, but did not have significant effects on the integrity of the transcriptome profiles in either target or non-target species on a genomic scale.  The metric we proposed can be used to estimate the off-target effects of insecticidal siRNAs, which might be useful for evaluating the safety of RNAi in pest control.  
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InvasionDB: A genome and gene database of invasive alien species
HUANG Cong, LANG Kun, QIAN Wan-qiang, WANG Shu-ping, CAO Xiao-mei, HE Rui, ZHAN An-ran, CHEN Meng-yao, YANG Nian-wan, LI Fei
2021, 20 (1): 191-200.   DOI: 10.1016/S2095-3119(20)63231-2
Abstract280)      PDF in ScienceDirect      
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 135 494 miRNAs, 89 294 rRNAs, and 2 671 941 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.
 
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LncRNAs are potentially involved in the immune interaction between small brown planthopper and rice stripe virus
CHEN Meng-yao, YE Wan-yi, XIAO Hua-mei, LI Mei-zhen, CAO Zheng-hong, YE Xin-hai, ZHAO Xian-xin, HE Kang, LI Fei
2019, 18 (12): 2814-2822.   DOI: 10.1016/S2095-3119(19)62569-4
Abstract107)      PDF in ScienceDirect      
Small brown planthopper (SBPH, Laodelphax striatellus Fallén) is an important vector of major crop pathogen rice stripe virus (RSV).  Controlling SBPH population is an efficient approach to control RSV.  Long non-coding RNAs (lncRNA) have been reported to block virus replication in hosts.  However, the function of lncRNAs in RSV infection and replication is still unknown.  Here, we aimed to study regulatory mechanisms of lncRNA in an immune system during RSV infection.  First, lncRNA genes were predicted from SBPH transcriptomes using a bioinformatics pipeline based on characteristics of lncRNA.  We identified 4 786 lncRNA genes corresponding to 5 790 transcripts in SBPH from an RNA-Seq dataset of 15 transcriptomes.  Differential expression analysis indicated that 3, 11, and 25 lncRNA genes were highly expressed in gut, salivary gland, and ovary, respectively, of viruliferous SBPH (Student’s t-test, P<0.05).  We randomly selected eight lncRNAs for expression validation using quantitative real-time PCR, confirming the differential expression of these lncRNAs between viruliferous and non-viruliferous SBPH.  In summary, we present evidence that the expression of lncRNA genes was induced by RSV infection, suggesting that RSV might be involved in the antivirus immune system in SBPH and participate in regulating the RSV replication mechanism.  These data provide helpful information for future investigations of the interaction between lncRNA and RSV. 
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