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A simple and efficient seed-based approach to induce callus production from B73 maize genotype

American Journal of Molecular Biology 2012年第4期2卷 380-385页

作者： simeon o.kotchoni Pacome A.Noumavo Adolphe Adjanohoun Daniel P.Russo John Dell’Angelo Emma W.Gachomo Lamine Baba-Moussa Department of Biology RutgersThe State University of New JerseyCamdenUSA Center for Computational and Integrative Biology(CCIB) The State University of New JerseyCamdenUSA Département de Biochimie et Biologie Cellulaire Universitéd’Abomey-CalaviCotonouBenin Centre de Recherches Agricoles Institut National des Recherches Agricoles du BeninAlladaBenin

The wild type maize genotype, B73, is not amenable for callus production and an efficient protocol for B73 maize callus induction has never been reported up-to-date. Scientific efforts in producing B73 maize callus using all known callus inducible media have been unsatisfactory. Here we developed and described an efficient protocol for callus induction from B73 maize seedlings. The protocol is based on well known callus inducible media CM4C where we have sequentially subtracted some chemical compounds and added some new compounds mediating cell proliferations. This newly described protocol was able to induce callus production in a wide range of crop species including rice and soybean. We found that cell proliferation factors, NAA (auxin analog) and 2,4 D (auxin influx carrier) were not only very crucial but required for positive B73 maize callus induction. The absence of one or the other will lead to the failure of B73 maize callus production. The well known CM4C callus induction composition lacks NAA. our findings will advance genetic studies of maize mutants generated from B73 genotype background.

关键词： B73 Maize Genotype Soybean Callus CM4C Maize Protocol Rice NAA 2,4-D

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Effect of Different Plant Growth Promoting Rhizobacteria on Maize Seed Germination and Seedling Development

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American Journal of Plant Sciences 2013年第5期4卷 1013-1021页

作者： Pacome A.Noumavo Eméric Kochoni Yédéou o.Didagbé Adolphe Adjanohoun Marcellin Allagbé Rachidatou Sikirou Emma W.Gachomo simeon o.kotchoni Lamine Baba-Moussa Laboratoire de Biologie et de Typage Moléculaire en Microbiologie Département de Biochimie et de Biologie CellulaireUniversitéd’Abomey-CalaviCotonouBénin Centre de Recherches Agri-coles Sud Institut National des Recherches Agricoles du BéninAttogonBénin Laboratoire de Défense des Cultures Centre de Recherches Agricoles d’AgonkanmeyInstitut National des Re-cherches Agricoles du BéninCotonouBénin Department of Biology The State University of New JerseyCamdenUSA Center for Computational and Integrative Biology The State University of New JerseyCamdenUSA

our study aimed at assessing the effects of 3 Plants Growth Promoting Rhizobacteria (PGPR) either singly or in combination on maize growth under laboratory and greenhouse conditions. Seeds were inoculated with single and combined solution of 108 CFU/ml of Rhizobacteria. Seeds were not inoculated for the control variant. The highest germination percentage was obtained with the combination of Pseudomonas fluorescens and Pseudomonas putida. This combination also recorded the best vigor index, plants circumferences number of leaves and the leaf area. The maximal heights of plants were observed with seeds treated with Azospirillum lipoferum with an increase of 37.32%. The highest rates of underground dry matter were recorded with A. lipoferum, with an increase of more than 56% comparative to control, while the combination P. fluorescens and P. putida increased the aerial dry matter of 59.11%. Finally, the highest value of the aerial biomass was obtained with the plants treated with the combination of P. fluorescens and P. putida and the highest underground biomass was obtained with plants treated only with A. lipoferum. These results suggest that specific combinations of PGPR can be considered as efficient alternative biofertilizers to promote maize seed germination, biomass and crop yield.

关键词： Azospirillum Pseudomonas PGPR Biofertlization Maize Seeds Germination Greenhouse

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Genome sequencing and next-generation sequence data analysis: A comprehensive compilation of bioinformatics tools and databases

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American Journal of Molecular Biology 2013年第2期3卷 115-130页

作者： Jose C. Jimenez-Lopez Emma W. Gachomo Sweta Sharma simeon o. kotchoni Department of Biochemistry Cell and Molecular Biology of Plants Estacion Experimental del Zaidin High Council for Scientific Research (CSIC) Granada Spain Department of Biology Rutgers University Camden USA

Genomics has become a ground-breaking field in all areas of the life sciences. The advanced genomics and the development of high-throughput techniques have lately provided insight into whole-genome characterization of a wide range of organisms. In the post-genomic era, new technologies have revealed an outbreak of prerequisite genomic sequences and supporting data to understand genome wide functional regulation of gene expression and metabolic pathways reconstruction. However, the availability of this plethora of genomic data presents a significant challenge for storage, analyses and data management. Analysis of this mega-data requires the development and application of novel bioinformatics tools that must include unified functional annotation, structural search, and comprehensive analysis and identification of new genes in a wide range of species with fully sequenced genomes. In addition, generation of systematically and syntactically unambiguous nomenclature systems for genomic data across species is a crucial task. Such systems are necessary for adequate handling genetic information in the context of comparative functional genomics. In this paper, we provide an overview of major advances in bioinformatics and computational biology in genome sequencing and next-generation sequence data analysis. We focus on their potential applications for efficient collection, storage, and analysis of genetic data/information from a wide range of gene banks. We also discuss the importance of establishing a unified nomenclature system through a functional and structural genomics approach.

关键词： Databases Computational Biology Genomics Proteomics Next-Generation Sequencing

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Genetic Diversity of Maize Accessions (Zea mays L.) Cultivated from Benin Using Microsatellites Markers

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American Journal of Molecular Biology 2016年第1期6卷 12-24页

作者： Hafiz A. Salami Kamirou Chabi Sika Wilfrid Padonou Djima Aly Chabi Yallou Adolphe Adjanohoun simeon kotchoni Lamine Baba-Moussa Laboratoire de Biologie et de Typage Moléculaire en Microbiologie Département de Biochimie et de Biologie Cellulaire Faculté des Sciences et Techniques Université d’Abomey-Calavi Cotonou Bénin Programme de Technologie Agricole (PTAA) Institut National des Recherches Agricoles du Bénin (INRAB) Porto-Novo Bénin Centre de Recherches Agricoles Sud Institut National des Recherches Agricoles du Bénin (INRAB) Cotonou Bénin Centre de Recherches Agricoles Nord Institut National des Recherches Agricoles du Bénin (INRAB) Ina Bénin Departement of Biology Rutgers University Camden USA

Maize (Zea mays L.) is the major cereal cultivated in Benin and it is important to know its genetic diversity to improve the yield. The genetic markers of important traits are evaluated in order to improve the maize inbred lines. The aim of this study was to evaluate the genetic diversity of Benin’s maize accessions by SSR marker. Thus, one hundred eighty seven maize accessions from three areas (South, Center and North) were analyzed using three SSR markers. A total of 227 polymorphic bands were produced and showed high genetic diversity (Shannon index = 0.51). The polymorphic information content (PIC) values for the SSR loci ranged from 0.58 to 0.81, with an average of 0.71. Genetic distance-based UPGMA dendrogram showed a genetic differentiation between accessions and they were grouped into four clusters in each area. This work provides necessary information that can be used not only to improve the maize production and conservation but also to better manage genetic species resources in Benin.

关键词： SSR PCR Molecular Characterization LZea mays L. Benin

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