International Journal of Genetics and Genomics

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Pathosystem, Epiphytology and Genomic Characterization of Groundnut Rosette Disease Pathogens

Received: 27 September 2020    Accepted: 12 October 2020    Published: 16 October 2020
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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.

DOI 10.11648/j.ijgg.20200804.11
Published in International Journal of Genetics and Genomics (Volume 8, Issue 4, December 2020)
Page(s) 120-126
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Arachis hypogaea, GRAV, GRV, sat-RNA, Genomics

References
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[3] Mabele, A. S., Were, H. K., Ndong’a, M. F. O. & Mukoye, B. (2019). Distribution, molecular detection and host range of groundnut rosette assistor virus in western Kenya. Journal of Plant Sciences. 7 (5): 100-105.
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Author Information
  • Department of Agriculture and Land Use Management (ALUM), Masinde Muliro University of Science and Technology (MMUST), Kakamega, Kenya

  • Department of Biological Sciences, Masinde Muliro University of Science and Technology (MMUST), Kakamega, Kenya

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    Anthony Simiyu Mabele, Mariam Nyongesa Were. (2020). Pathosystem, Epiphytology and Genomic Characterization of Groundnut Rosette Disease Pathogens. International Journal of Genetics and Genomics, 8(4), 120-126. https://doi.org/10.11648/j.ijgg.20200804.11

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    Anthony Simiyu Mabele; Mariam Nyongesa Were. Pathosystem, Epiphytology and Genomic Characterization of Groundnut Rosette Disease Pathogens. Int. J. Genet. Genomics 2020, 8(4), 120-126. doi: 10.11648/j.ijgg.20200804.11

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    Anthony Simiyu Mabele, Mariam Nyongesa Were. Pathosystem, Epiphytology and Genomic Characterization of Groundnut Rosette Disease Pathogens. Int J Genet Genomics. 2020;8(4):120-126. doi: 10.11648/j.ijgg.20200804.11

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  • @article{10.11648/j.ijgg.20200804.11,
      author = {Anthony Simiyu Mabele and Mariam Nyongesa Were},
      title = {Pathosystem, Epiphytology and Genomic Characterization of Groundnut Rosette Disease Pathogens},
      journal = {International Journal of Genetics and Genomics},
      volume = {8},
      number = {4},
      pages = {120-126},
      doi = {10.11648/j.ijgg.20200804.11},
      url = {https://doi.org/10.11648/j.ijgg.20200804.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijgg.20200804.11},
      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.},
     year = {2020}
    }
    

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    AU  - Anthony Simiyu Mabele
    AU  - Mariam Nyongesa Were
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    AB  - 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.
    VL  - 8
    IS  - 4
    ER  - 

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