Pathosystem, Epiphytology and Genomic Characterization of Groundnut Rosette Disease Pathogens

Anthony Simiyu Mabele, M. Were
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Abstract

Synergism among the groundnut rosette disease (GRD) pathogens of Groundnut rosette assistor virus (GRAV, Luteovirus) and Groundnut rosette virus (GRV, Umbravirus) associated with a satellite-ribonucleic acid (sat-RNA), have declined groundnut (Peanut, Arachis hypogaea L.) production in Kenya. The polyphagous groundnut aphid (Aphis craccivora Koch; Homoptera: Aphididae) efficiently transmits GRD in sub-Saharan Africa. Inadequate information available on the pathosystem, epiphytology and genomic characterization of GRAV, GRV and sat-RNA pathogens in Kenya, have hampered control and management technologies due to their intimate complex etiology, the bottleneck which this study unravels. A survey of GRD was conducted in western Kenya among the four counties of Bungoma, Busia, Kisumu and Kisii during the short rains season of 2019. A total of 10 symptomatic leaf samples were selected from the collected samples and preserved until use. Total RNA was extracted from the symptomatic leaf samples using GeneJET Plant RNA Purification Mini Kit according to the manufacturers’ protocol. RT-PCR detection of GRD pathogens was done using specific primers of GRAV, GRV and sat-RNA. DNA libraries were prepared and sequenced using the Sanger sequencing platform. Phylogenetic analyses and comparisons were performed using MEGA X software. The sequence quality were checked based on the peak of the electrophoregram and trimmed using CLC main work bench v20. The sequences were assembled with final consensus exported as FASTA file format and BLAST searched against NCBI database using BLASTn. The BLAST hit with nucleotide identity of at least 97% identity were considered, downloaded, uploaded to MEGA X and multiple alignment done with Gap Opening Penalty of 15 and Gap Extension Penalty of 5.5. Phylogenetic trees were constructed with best DNA/Protein model based on automatic Neighbor Joining Tree and Maximum Likelihood method of nucleotides substitution by Kimura 2 Parameter with Invariant Plus Gamma. The two GRAV isolates from Kenya (Ken_G10 and Ken_G2) clustered together in group II while the rest clustered in group I. The Kenyan novel GRAV isolates are more similar to each other than with any other sequences implying common ancestry than with the other African isolates. The Kenyan sat-RNA isolates formed two distinct groups with sub-groups within the clusters. Isolates Ken_G11 and Ken_G6 clustered together in group II while Ken_G10 and Ken_G7 clustered together in group I. Ken_G6 clustered with other Kenyan sat-RNA isolates implying a possible identity by descent (IBD), suggesting a possible impact of a genetic bottleneck whose cause should be investigated further to infer any conclusions.
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花生莲座病病原菌的病理系统、表观学和基因组特征
花生莲座病(GRD)病原体花生莲座辅助病毒(GRV, lutevirus)和花生莲座病毒(GRV, Umbravirus)之间的协同作用与卫星核糖核酸(sat-RNA)相关,导致肯尼亚花生(Peanut, arachhis hypogaea L.)产量下降。杂食性的花生蚜虫(蚜虫craccivora科赫;同翅目:蚜虫科)在撒哈拉以南非洲有效传播GRD。肯尼亚GRV、GRV和sat-RNA病原体的病理系统、表观学和基因组特征信息不足,由于其密切复杂的病因,阻碍了控制和管理技术,本研究解决了这一瓶颈。2019年短雨季期间,在肯尼亚西部邦戈马、布西亚、基苏木和基西四县开展了一项粮食生产总值调查。从采集的样品中选取10个有症状的叶片样品保存至使用。使用GeneJET植物RNA纯化迷你试剂盒,按照制造商的方案,从有症状的叶片样品中提取总RNA。采用GRV、GRV和sat-RNA特异性引物对GRD病原菌进行RT-PCR检测。利用Sanger测序平台制备DNA文库并进行测序。使用大型X软件系统进行了分析和比较。根据电泳图谱的峰值检查序列质量,并使用CLC主工作台v20进行裁剪。将最终一致的序列集合成FASTA文件格式,并使用BLASTn在NCBI数据库中进行BLAST检索。考虑核苷酸同源性至少为97%的BLAST命中,下载并上传到MEGA X,并进行多次比对,Gap Opening Penalty为15,Gap Extension Penalty为5.5。采用基于自动邻居连接树的最佳DNA/蛋白模型和Kimura 2参数核苷酸替换的最大似然方法构建系统发育树。来自肯尼亚的两个grv分离株(Ken_G10和Ken_G2)聚集在II组,而其余的聚集在i组。肯尼亚的新grv分离株比任何其他序列都更相似,这意味着共同的祖先比其他非洲分离株更相似。肯尼亚sat-RNA分离物形成了两个不同的群,群内有亚群。分离株Ken_G11和Ken_G6聚集在II群中,而Ken_G10和Ken_G7聚集在i群中。Ken_G6与其他肯尼亚sat-RNA分离株聚集在一起,暗示可能存在血统认同(IBD),表明可能存在遗传瓶颈的影响,其原因有待进一步研究以得出任何结论。
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