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Mokhtar MM, Alsamman AM, El Allali A. MegaSSR: a web server for large scale microsatellite identification, classification, and marker development. Front Plant Sci 2023; 14:1219055. [PMID: 38162302 PMCID: PMC10757629 DOI: 10.3389/fpls.2023.1219055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 08/18/2023] [Indexed: 01/03/2024]
Abstract
Next-generation sequencing technologies have opened new avenues for using genomic data to study and develop molecular markers and improve genetic resources. Simple Sequence Repeats (SSRs) as genetic markers are increasingly used in molecular diversity and molecular breeding programs that require bioinformatics pipelines to analyze the large amounts of data. Therefore, there is an ongoing need for online tools that provide computational resources with minimal effort and maximum efficiency, including automated development of SSR markers. These tools should be flexible, customizable, and able to handle the ever-increasing amount of genomic data. Here we introduce MegaSSR (https://bioinformatics.um6p.ma/MegaSSR), a web server and a standalone pipeline that enables the design of SSR markers in any target genome. MegaSSR allows users to design targeted PCR-based primers for their selected SSR repeats and includes multiple tools that initiate computational pipelines for SSR mining, classification, comparisons, PCR primer design, in silico PCR validation, and statistical visualization. MegaSSR results can be accessed, searched, downloaded, and visualized with user-friendly web-based tools. These tools provide graphs and tables showing various aspects of SSR markers and corresponding PCR primers. MegaSSR will accelerate ongoing research in plant species and assist breeding programs in their efforts to improve current genomic resources.
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Affiliation(s)
- Morad M. Mokhtar
- Bioinformatics Laboratory, College of Computing, Mohammed VI Polytechnic University, Benguerir, Morocco
- Agricultural Genetic Engineering Research Institute, Agricultural Research Center, Giza, Egypt
| | - Alsamman M. Alsamman
- Bioinformatics Laboratory, College of Computing, Mohammed VI Polytechnic University, Benguerir, Morocco
- Agricultural Genetic Engineering Research Institute, Agricultural Research Center, Giza, Egypt
- Biotechnology Department, International Center for Agricultural Research in the Dry Areas (ICARDA), Giza, Egypt
| | - Achraf El Allali
- Bioinformatics Laboratory, College of Computing, Mohammed VI Polytechnic University, Benguerir, Morocco
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Abstract
Background Simple sequence repeats (SSRs) have become widely used as molecular markers in plant genetic studies due to their abundance, high allelic variation at each locus and simplicity to analyze using conventional PCR amplification. To study plants with unknown genome sequence, SSR markers from Expressed Sequence Tags (ESTs), which can be obtained from the plant mRNA (converted to cDNA), must be utilized. With the advent of high-throughput sequencing technology, huge EST sequence data have been generated and are now accessible from many public databases. However, SSR marker identification from a large in-house or public EST collection requires a computational pipeline that makes use of several standard bioinformatic tools to design high quality EST-SSR primers. Some of these computational tools are not users friendly and must be tightly integrated with reference genomic databases. Results A web-based bioinformatic pipeline, called EST Analysis Pipeline Plus (ESAP Plus), was constructed for assisting researchers to develop SSR markers from a large EST collection. ESAP Plus incorporates several bioinformatic scripts and some useful standard software tools necessary for the four main procedures of EST-SSR marker development, namely 1) pre-processing, 2) clustering and assembly, 3) SSR mining and 4) SSR primer design. The proposed pipeline also provides two alternative steps for reducing EST redundancy and identifying SSR loci. Using public sugarcane ESTs, ESAP Plus automatically executed the aforementioned computational pipeline via a simple web user interface, which was implemented using standard PHP, HTML, CSS and Java scripts. With ESAP Plus, users can upload raw EST data and choose various filtering options and parameters to analyze each of the four main procedures through this web interface. All input EST data and their predicted SSR results will be stored in the ESAP Plus MySQL database. Users will be notified via e-mail when the automatic process is completed and they can download all the results through the web interface. Conclusions ESAP Plus is a comprehensive and convenient web-based bioinformatic tool for SSR marker development. ESAP Plus offers all necessary EST-SSR development processes with various adjustable options that users can easily use to identify SSR markers from a large EST collection. With familiar web interface, users can upload the raw EST using the data submission page and visualize/download the corresponding EST-SSR information from within ESAP Plus. ESAP Plus can handle considerably large EST datasets. This EST-SSR discovery tool can be accessed directly from: http://gbp.kku.ac.th/esap_plus/. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3328-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Piyarat Ponyared
- Department of Biology, Faculty of Science, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Jiradej Ponsawat
- Department of Computer Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Sissades Tongsima
- National Center for Genetic Engineering and Biotechnology (BIOTEC), Pathum Thani, 12120, Thailand
| | - Pusadee Seresangtakul
- Department of Computer Science, Faculty of Science, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Chutipong Akkasaeng
- Department of Plant Science and Agricultural Resources, Faculty of Agriculture, Khon Kaen University, Khon Kaen, 40002, Thailand
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Toal TW, Burkart-Waco D, Howell T, Ron M, Kuppu S, Britt A, Chetelat R, Brady SM. Indel Group in Genomes (IGG) Molecular Genetic Markers. Plant Physiol 2016; 172:38-61. [PMID: 27436831 PMCID: PMC5074621 DOI: 10.1104/pp.16.00354] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2016] [Accepted: 07/15/2016] [Indexed: 06/06/2023]
Abstract
Genetic markers are essential when developing or working with genetically variable populations. Indel Group in Genomes (IGG) markers are primer pairs that amplify single-locus sequences that differ in size for two or more alleles. They are attractive for their ease of use for rapid genotyping and their codominant nature. Here, we describe a heuristic algorithm that uses a k-mer-based approach to search two or more genome sequences to locate polymorphic regions suitable for designing candidate IGG marker primers. As input to the IGG pipeline software, the user provides genome sequences and the desired amplicon sizes and size differences. Primer sequences flanking polymorphic insertions/deletions are produced as output. IGG marker files for three sets of genomes, Solanum lycopersicum/Solanum pennellii, Arabidopsis (Arabidopsis thaliana) Columbia-0/Landsberg erecta-0 accessions, and S. lycopersicum/S. pennellii/Solanum tuberosum (three-way polymorphic) are included.
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Affiliation(s)
- Ted W Toal
- Department of Biochemistry and Molecular Medicine (T.W.T.), Department of Plant Sciences (D.B.-W., T.H., R.C.), Department of Plant Biology (M.R., S.K., A.B., S.M.B.), and Genome Center (S.M.B.), University of California, Davis, California 95616
| | - Diana Burkart-Waco
- Department of Biochemistry and Molecular Medicine (T.W.T.), Department of Plant Sciences (D.B.-W., T.H., R.C.), Department of Plant Biology (M.R., S.K., A.B., S.M.B.), and Genome Center (S.M.B.), University of California, Davis, California 95616
| | - Tyson Howell
- Department of Biochemistry and Molecular Medicine (T.W.T.), Department of Plant Sciences (D.B.-W., T.H., R.C.), Department of Plant Biology (M.R., S.K., A.B., S.M.B.), and Genome Center (S.M.B.), University of California, Davis, California 95616
| | - Mily Ron
- Department of Biochemistry and Molecular Medicine (T.W.T.), Department of Plant Sciences (D.B.-W., T.H., R.C.), Department of Plant Biology (M.R., S.K., A.B., S.M.B.), and Genome Center (S.M.B.), University of California, Davis, California 95616
| | - Sundaram Kuppu
- Department of Biochemistry and Molecular Medicine (T.W.T.), Department of Plant Sciences (D.B.-W., T.H., R.C.), Department of Plant Biology (M.R., S.K., A.B., S.M.B.), and Genome Center (S.M.B.), University of California, Davis, California 95616
| | - Anne Britt
- Department of Biochemistry and Molecular Medicine (T.W.T.), Department of Plant Sciences (D.B.-W., T.H., R.C.), Department of Plant Biology (M.R., S.K., A.B., S.M.B.), and Genome Center (S.M.B.), University of California, Davis, California 95616
| | - Roger Chetelat
- Department of Biochemistry and Molecular Medicine (T.W.T.), Department of Plant Sciences (D.B.-W., T.H., R.C.), Department of Plant Biology (M.R., S.K., A.B., S.M.B.), and Genome Center (S.M.B.), University of California, Davis, California 95616
| | - Siobhan M Brady
- Department of Biochemistry and Molecular Medicine (T.W.T.), Department of Plant Sciences (D.B.-W., T.H., R.C.), Department of Plant Biology (M.R., S.K., A.B., S.M.B.), and Genome Center (S.M.B.), University of California, Davis, California 95616
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Dehury B, Panda D, Sahu J, Sahu M, Sarma K, Barooah M, Sen P, Modi MK. In silico identification and characterization of conserved miRNAs and their target genes in sweet potato (Ipomoea batatas L.) expressed sequence tags (ESTs). Plant Signal Behav 2013; 8:e26543. [PMID: 24067297 PMCID: PMC4091516 DOI: 10.4161/psb.26543] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The endogenous small non-coding micro RNAs (miRNAs), which are typically ~21-24 nt nucleotides, play a crucial role in regulating the intrinsic normal growth of cells and development of the plants as well as in maintaining the integrity of genomes. These small non-coding RNAs function as the universal specificity factors in post-transcriptional gene silencing. Discovering miRNAs, identifying their targets, and further inferring miRNA functions is a routine process to understand normal biological processes of miRNAs and their roles in the development of plants. Comparative genomics based approach using expressed sequence tags (EST) and genome survey sequences (GSS) offer a cost-effective platform for identification and characterization of miRNAs and their target genes in plants. Despite the fact that sweet potato (Ipomoea batatas L.) is an important staple food source for poor small farmers throughout the world, the role of miRNA in various developmental processes remains largely unknown. In this paper, we report the computational identification of miRNAs and their target genes in sweet potato from their ESTs. Using comparative genomics-based approach, 8 potential miRNA candidates belonging to miR168, miR2911, and miR156 families were identified from 23 406 ESTs in sweet potato. A total of 42 target genes were predicted and their probable functions were illustrated. Most of the newly identified miRNAs target transcription factors as well as genes involved in plant growth and development, signal transduction, metabolism, defense, and stress response. The identification of miRNAs and their targets is expected to accelerate the pace of miRNA discovery, leading to an improved understanding of the role of miRNA in development and physiology of sweet potato, as well as stress response.
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