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Geethanjali S, Kadirvel P, Anumalla M, Hemanth Sadhana N, Annamalai A, Ali J. Streamlining of Simple Sequence Repeat Data Mining Methodologies and Pipelines for Crop Scanning. PLANTS (BASEL, SWITZERLAND) 2024; 13:2619. [PMID: 39339594 PMCID: PMC11435353 DOI: 10.3390/plants13182619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Revised: 08/18/2024] [Accepted: 08/29/2024] [Indexed: 09/30/2024]
Abstract
Genetic markers are powerful tools for understanding genetic diversity and the molecular basis of traits, ushering in a new era of molecular breeding in crops. Over the past 50 years, DNA markers have rapidly changed, moving from hybridization-based and second-generation-based to sequence-based markers. Simple sequence repeats (SSRs) are the ideal markers in plant breeding, and they have numerous desirable properties, including their repeatability, codominance, multi-allelic nature, and locus specificity. They can be generated from any species, which requires prior sequence knowledge. SSRs may serve as evolutionary tuning knobs, allowing for rapid identification and adaptation to new circumstances. The evaluations published thus far have mostly ignored SSR polymorphism and gene evolution due to a lack of data regarding the precise placements of SSRs on chromosomes. However, NGS technologies have made it possible to produce high-throughput SSRs for any species using massive volumes of genomic sequence data that can be generated fast and at a minimal cost. Though SNP markers are gradually replacing the erstwhile DNA marker systems, SSRs remain the markers of choice in orphan crops due to the lack of genomic resources at the reference level and their adaptability to resource-limited labor. Several bioinformatic approaches and tools have evolved to handle genomic sequences to identify SSRs and generate primers for genotyping applications in plant breeding projects. This paper includes the currently available methodologies for producing SSR markers, genomic resource databases, and computational tools/pipelines for SSR data mining and primer generation. This review aims to provide a 'one-stop shop' of information to help each new user carefully select tools for identifying and utilizing SSRs in genetic research and breeding programs.
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Affiliation(s)
- Subramaniam Geethanjali
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641003, India
| | - Palchamy Kadirvel
- Crop Improvement Section, ICAR-Indian Institute of Oilseeds Research, Rajendranagar, Hyderabad 500030, India
| | - Mahender Anumalla
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), Los Baños 4031, Laguna, Philippines
- IRRI South Asia Hub, Patancheru, Hyderabad 502324, India
| | - Nithyananth Hemanth Sadhana
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641003, India
| | - Anandan Annamalai
- Indian Council of Agricultural Research (ICAR), Indian Institute of Seed Science, Bengaluru 560065, India
| | - Jauhar Ali
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), Los Baños 4031, Laguna, Philippines
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Diouf M, Zoclanclounon YAB, Mboup PA, Diouf D, Malédon E, Rivallan R, Chair H, Dossa K. Genome-wide development of intra- and inter-specific transferable SSR markers and construction of a dynamic web resource for yam molecular breeding: Y2MD. THE PLANT GENOME 2024; 17:e20428. [PMID: 38234122 DOI: 10.1002/tpg2.20428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 12/04/2023] [Accepted: 12/23/2023] [Indexed: 01/19/2024]
Abstract
Microsatellite markers are widely used in population genetics and breeding. Despite the economic significance of yams in developing countries, there is a paucity of microsatellite markers, and as of now, no comprehensive microsatellite marker database exists. In this study, we conducted genome-wide microsatellite marker development across four yam species, identified cross-species transferable markers, and designed an easy-to-use web portal for the yam researchers. The screening of Dioscorea alata, Dioscorea rotundata, Dioscorea dumetorum, and Dioscorea zingiberensis genomes resulted in 318,713, 322,501, 307,040, and 253,856 microsatellites, respectively. Mono-, di-, and tri-nucleotides were the most important types of repeats in the different species, and a total of 864,128 primer pairs were designed. Furthermore, we identified 1170 cross-species transferable microsatellite markers. Among them, 17 out of 18 randomly selected were experimentally validated with good discriminatory power, regardless of the species and ploidy levels. Ultimately, we created and deployed a dynamic Yam Microsatellite Markers Database (Y2MD) available at https://y2md.ucad.sn/. Y2MD is embedded with various useful tools such as JBrowse, Blast, insilicoPCR, and SSR Finder to facilitate the exploitation of microsatellite markers in yams. This study represents the first comprehensive microsatellite marker mining across several yam species and will contribute to advancing yam genetic research and marker-assisted breeding. The released user-friendly database constitutes a valuable platform for yam researchers.
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Affiliation(s)
- Moussa Diouf
- Département de Mathématiques et Informatique, Faculté des Sciences et Techniques, Université Cheikh Anta Diop, Dakar, Senegal
- Laboratoire Campus de Biotechnologies Végétales, Département de Biologie Végétale, Faculté des Sciences et Techniques, Université Cheikh Anta Diop, Dakar, Senegal
| | | | - Pape Adama Mboup
- Département de Mathématiques et Informatique, Faculté des Sciences et Techniques, Université Cheikh Anta Diop, Dakar, Senegal
| | - Diaga Diouf
- Laboratoire Campus de Biotechnologies Végétales, Département de Biologie Végétale, Faculté des Sciences et Techniques, Université Cheikh Anta Diop, Dakar, Senegal
| | - Erick Malédon
- UMR AGAP Institut, CIRAD, Petit Bourg, France
- UMR AGAP Institut, University of Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Ronan Rivallan
- UMR AGAP Institut, University of Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Hâna Chair
- UMR AGAP Institut, University of Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
| | - Komivi Dossa
- UMR AGAP Institut, CIRAD, Petit Bourg, France
- UMR AGAP Institut, University of Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France
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Zhang YY, Li HK, Huang X, Yuan YJ, Zhang XF, Gao XS, Wang XJ, Wei MM, Huang HS, Li W. Heterozygosity analysis of spontaneous 2n female gametes and centromere mapping of the diploid Hevea brasiliensis based on full-sib triploid populations. PLANT REPRODUCTION 2024; 37:47-56. [PMID: 37758937 DOI: 10.1007/s00497-023-00481-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 08/28/2023] [Indexed: 09/29/2023]
Abstract
KEY MESSAGE Unreduced megagametophytes via second-division restitution were confirmed through heterozygosity analysis, and four candidate physical centromeres of rubber were located for the first time. The evaluation of maternal heterozygosity restitution (MHR) is vital in identifying the mechanism of 2n gametogenesis and assessing the utilization value of 2n gametes. In this study, three full-sib triploid populations were employed to evaluate the MHR of 2n female gametes of rubber tree clone GT1 and to confirm their genetic derivation. The 2n female gametes of GT1 were derived from second-division restitution (SDR) and transmitted more than half of the parental heterozygosity. In addition, low recombination frequency markers were developed, and four candidate physical centromeres of rubber tree were located for the first time. The confirmation that 2n female gametes of rubber tree clone GT1 are derived from SDR provides insights into the molecular mechanisms of 2n gametogenesis. In addition, the identified centromere location will aid in the development of centromeric markers for the rapid identification of the 2n gametogenesis mechanism.
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Affiliation(s)
- Yuan-Yuan Zhang
- State Key Laboratory of Tropical Crop Breeding, State Centre for Rubber Breeding, Key Laboratory of Biology and Genetic Resources of Rubber Tree, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, 571101, Hainan, China.
| | - Hong-Kun Li
- Dehong Institute of Tropical Agricultural Sciences of Yunnan Province, Ruili, 678600, Yunnan, China
| | - Xiao Huang
- State Key Laboratory of Tropical Crop Breeding, State Centre for Rubber Breeding, Key Laboratory of Biology and Genetic Resources of Rubber Tree, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, 571101, Hainan, China
| | - Yu-Jiao Yuan
- College of Tropical Crops, Yunnan Agricultural University, Puer, 665099, Yunnan, China
| | - Xiao-Fei Zhang
- State Key Laboratory of Tropical Crop Breeding, State Centre for Rubber Breeding, Key Laboratory of Biology and Genetic Resources of Rubber Tree, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, 571101, Hainan, China
| | - Xin-Sheng Gao
- State Key Laboratory of Tropical Crop Breeding, State Centre for Rubber Breeding, Key Laboratory of Biology and Genetic Resources of Rubber Tree, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, 571101, Hainan, China
| | - Xiang-Jun Wang
- State Key Laboratory of Tropical Crop Breeding, State Centre for Rubber Breeding, Key Laboratory of Biology and Genetic Resources of Rubber Tree, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, 571101, Hainan, China
| | - Ming-Ming Wei
- State Key Laboratory of Tropical Crop Breeding, State Centre for Rubber Breeding, Key Laboratory of Biology and Genetic Resources of Rubber Tree, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, 571101, Hainan, China
| | - Hua-Sun Huang
- State Key Laboratory of Tropical Crop Breeding, State Centre for Rubber Breeding, Key Laboratory of Biology and Genetic Resources of Rubber Tree, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, 571101, Hainan, China
| | - Weiguo Li
- State Key Laboratory of Tropical Crop Breeding, State Centre for Rubber Breeding, Key Laboratory of Biology and Genetic Resources of Rubber Tree, Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, 571101, Hainan, China.
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Mokhtar MM, Alsamman AM, El Allali A. MegaSSR: a web server for large scale microsatellite identification, classification, and marker development. FRONTIERS IN PLANT SCIENCE 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] [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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Mokhtar MM, Alsamman AM, El Allali A. PlantLTRdb: An interactive database for 195 plant species LTR-retrotransposons. FRONTIERS IN PLANT SCIENCE 2023; 14:1134627. [PMID: 36950350 PMCID: PMC10025401 DOI: 10.3389/fpls.2023.1134627] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 02/16/2023] [Indexed: 05/29/2023]
Abstract
LTR-retrotransposons (LTR-RTs) are a large group of transposable elements that replicate through an RNA intermediate and alter genome structure. The activities of LTR-RTs in plant genomes provide helpful information about genome evolution and gene function. LTR-RTs near or within genes can directly alter gene function. This work introduces PlantLTRdb, an intact LTR-RT database for 195 plant species. Using homology- and de novo structure-based methods, a total of 150.18 Gbp representing 3,079,469 pseudomolecules/scaffolds were analyzed to identify, characterize, annotate LTR-RTs, estimate insertion ages, detect LTR-RT-gene chimeras, and determine nearby genes. Accordingly, 520,194 intact LTR-RTs were discovered, including 29,462 autonomous and 490,732 nonautonomous LTR-RTs. The autonomous LTR-RTs included 10,286 Gypsy and 19,176 Copia, while the nonautonomous were divided into 224,906 Gypsy, 218,414 Copia, 1,768 BARE-2, 3,147 TR-GAG and 4,2497 unknown. Analysis of the identified LTR-RTs located within genes showed that a total of 36,236 LTR-RTs were LTR-RT-gene chimeras and 11,619 LTR-RTs were within pseudo-genes. In addition, 50,026 genes are within 1 kbp of LTR-RTs, and 250,587 had a distance of 1 to 10 kbp from LTR-RTs. PlantLTRdb allows researchers to search, visualize, BLAST and analyze plant LTR-RTs. PlantLTRdb can contribute to the understanding of structural variations, genome organization, functional genomics, and the development of LTR-RT target markers for molecular plant breeding. PlantLTRdb is available at https://bioinformatics.um6p.ma/PlantLTRdb.
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Hou W, Zhang X, Liu Y, Liu Y, Feng BL. RNA-Seq and genetic diversity analysis of faba bean ( Vicia faba L.) varieties in China. PeerJ 2023; 11:e14259. [PMID: 36643650 PMCID: PMC9838209 DOI: 10.7717/peerj.14259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 09/27/2022] [Indexed: 01/11/2023] Open
Abstract
Background Faba bean (Vicia faba L) is one of the most important legumes in the world. However, there is relatively little genomic information available for this species owing to its large genome. The lack of data impedes the discovery of molecular markers and subsequent genetic research in faba bean. The objective of this study was to analyze the faba bean transcriptome, and to develop simple sequence repeat (SSR) markers to determine the genetic diversity of 226 faba bean varieties derived from different regions in China. Methods Faba bean varieties with different phenotype were used in transcriptome analysis. The functions of the unigenes were analyzed using various database. SSR markers were developed and the polymorphic markers were selected to conduct genetic diversity analysis. Results A total of 92.43 Gb of sequencing data was obtained in this study, and 133,487 unigene sequences with a total length of 178,152,541 bp were assembled. A total of 5,200 SSR markers were developed on the basis of RNA-Seq analysis. Then, 200 SSR markers were used to evaluate polymorphisms. In total, 103 (51.5%) SSR markers showed significant and repeatable bands between different faba bean varieties. Clustering analysis revealed that 226 faba bean materials were divided into five groups. Genetic diversity analysis revealed that the relationship between different faba beans in China was related, especially in the same region. These results provided a valuable data resource for annotating genes to different categories and developing SSR markers.
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Affiliation(s)
- Wanwei Hou
- College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
- Qinghai Academy of Agricultural and Forestry Sciences, Qinghai University, Xining, Qinghai, China
| | - Xiaojuan Zhang
- College of Eco-Environmental Engineering, Qinghai Universit, Xining, Qinghai, China
| | - Yuling Liu
- Qinghai Academy of Agricultural and Forestry Sciences, Qinghai University, Xining, Qinghai, China
| | - Yujiao Liu
- Qinghai Academy of Agricultural and Forestry Sciences, Qinghai University, Xining, Qinghai, China
| | - Bai li Feng
- College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
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Kumar S, Singh A, Shanker A. pSATdb: a database of mitochondrial common, polymorphic, and unique microsatellites. Life Sci Alliance 2022; 5:5/6/e202101307. [PMID: 35181599 PMCID: PMC8860089 DOI: 10.26508/lsa.202101307] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 02/03/2022] [Accepted: 02/04/2022] [Indexed: 12/02/2022] Open
Abstract
The polymorphic microSATellites database (pSATdb) provides information on common, polymorphic, and unique mitochondrial microsatellites. Microsatellites, also termed as simple sequence repeats, are repetitive tracts in a DNA sequence, typically consisting of one to six nucleotides. These repeats are found in all genomes and play key roles in phylogeny and species identification. Microsatellites are highly polymorphic, and their length may differ from species to species. There are several online resources dedicated to mitochondria; however, comprehensive information is not available about the length variation of mitochondrial microsatellites. Therefore, to explore it between species among a genus, we have developed a database named pSATdb (polymorphic microSATellites database; https://lms.snu.edu.in/pSATdb/). pSATdb contains 28,710 perfect microsatellites identified across 5,976 mitochondrial genome (mt-genome) sequences from 1,576 genera which includes 1,535 (5,846 mt-genome) and 41 (130 mt-genome) genera of Metazoa and Viridiplantae, respectively. pSATdb is the only database which provides genus-wise information about the length variation of mitochondrial microsatellites. Because of the emerging role of microsatellites in genomics studies, the identified common, polymorphic, and unique microsatellites stored in pSATdb will be effectively useful in various studies including genetic diversity, mapping, marker-assisted selection, and comparative population studies.
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Affiliation(s)
- Sonu Kumar
- Department of Bioinformatics, Central University of South Bihar, Gaya, India
| | - Ashutosh Singh
- Translational Bioinformatics Lab, Department of Life Sciences, Shiv Nadar University, Greater Noida, India
| | - Asheesh Shanker
- Department of Bioinformatics, Central University of South Bihar, Gaya, India
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Chen J, Li F, Wang M, Li J, Marquez-Lago TT, Leier A, Revote J, Li S, Liu Q, Song J. BigFiRSt: A Software Program Using Big Data Technique for Mining Simple Sequence Repeats From Large-Scale Sequencing Data. Front Big Data 2022; 4:727216. [PMID: 35118375 PMCID: PMC8805145 DOI: 10.3389/fdata.2021.727216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 12/13/2021] [Indexed: 11/22/2022] Open
Abstract
Background Simple Sequence Repeats (SSRs) are short tandem repeats of nucleotide sequences. It has been shown that SSRs are associated with human diseases and are of medical relevance. Accordingly, a variety of computational methods have been proposed to mine SSRs from genomes. Conventional methods rely on a high-quality complete genome to identify SSRs. However, the sequenced genome often misses several highly repetitive regions. Moreover, many non-model species have no entire genomes. With the recent advances of next-generation sequencing (NGS) techniques, large-scale sequence reads for any species can be rapidly generated using NGS. In this context, a number of methods have been proposed to identify thousands of SSR loci within large amounts of reads for non-model species. While the most commonly used NGS platforms (e.g., Illumina platform) on the market generally provide short paired-end reads, merging overlapping paired-end reads has become a common way prior to the identification of SSR loci. This has posed a big data analysis challenge for traditional stand-alone tools to merge short read pairs and identify SSRs from large-scale data. Results In this study, we present a new Hadoop-based software program, termed BigFiRSt, to address this problem using cutting-edge big data technology. BigFiRSt consists of two major modules, BigFLASH and BigPERF, implemented based on two state-of-the-art stand-alone tools, FLASH and PERF, respectively. BigFLASH and BigPERF address the problem of merging short read pairs and mining SSRs in the big data manner, respectively. Comprehensive benchmarking experiments show that BigFiRSt can dramatically reduce the execution times of fast read pairs merging and SSRs mining from very large-scale DNA sequence data. Conclusions The excellent performance of BigFiRSt mainly resorts to the Big Data Hadoop technology to merge read pairs and mine SSRs in parallel and distributed computing on clusters. We anticipate BigFiRSt will be a valuable tool in the coming biological Big Data era.
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Affiliation(s)
- Jinxiang Chen
- Department of Software Engineering, College of Information Engineering, Northwest A&F University, Yangling, China
| | - Fuyi Li
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Melbourne, VIC, Australia
- Monash Centre for Data Science, Monash University, Melbourne, VIC, Australia
- Department of Microbiology and Immunity, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, VIC, Australia
| | - Miao Wang
- Department of Software Engineering, College of Information Engineering, Northwest A&F University, Yangling, China
| | - Junlong Li
- Department of Software Engineering, College of Information Engineering, Northwest A&F University, Yangling, China
| | - Tatiana T. Marquez-Lago
- Department of Genetics, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
- Department of Cell, Developmental and Integrative Biology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - André Leier
- Department of Genetics, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
- Department of Cell, Developmental and Integrative Biology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Jerico Revote
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Melbourne, VIC, Australia
| | - Shuqin Li
- Department of Software Engineering, College of Information Engineering, Northwest A&F University, Yangling, China
| | - Quanzhong Liu
- Department of Software Engineering, College of Information Engineering, Northwest A&F University, Yangling, China
- Quanzhong Liu
| | - Jiangning Song
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Melbourne, VIC, Australia
- Monash Centre for Data Science, Monash University, Melbourne, VIC, Australia
- *Correspondence: Jiangning Song
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Mokhtar MM, El Allali A, Hegazy MEF, Atia MAM. PlantPathMarks (PPMdb): an interactive hub for pathways-based markers in plant genomes. Sci Rep 2021; 11:21300. [PMID: 34716373 PMCID: PMC8556342 DOI: 10.1038/s41598-021-00504-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 09/06/2021] [Indexed: 11/12/2022] Open
Abstract
Over the past decade, the problem of finding an efficient gene-targeting marker set or signature for plant trait characterization has remained challenging. Many databases focusing on pathway mining have been released with one major deficiency, as they lack to develop marker sets that target only genes controlling a specific pathway or certain biological process. Herein, we present the PlantPathMarks database (PPMdb) as a comprehensive, web-based, user-friendly, and interactive hub for pathway-based markers in plant genomes. Based on our newly developed pathway gene set mining approach, two novel pathway-based marker systems called pathway gene-targeted markers (PGTMs) and pathway microsatellite-targeted markers (PMTMs) were developed as a novel class of annotation-based markers. In the PPMdb database, 2,690,742 pathway-based markers reflecting 9,894 marker panels were developed across 82 plant genomes. The markers include 691,555 PGTMs and 1,999,187 PMTMs. Across these genomes, 165,378 enzyme-coding genes were mapped against 126 KEGG reference pathway maps. PPMdb is furnished with three interactive visualization tools (Map Browse, JBrowse and Species Comparison) to visualize, map, and compare the developed markers over their KEGG reference pathway maps. All the stored marker panels can be freely downloaded. PPMdb promises to create a radical shift in the paradigm of the area of molecular marker research. The use of PPMdb as a mega-tool represents an impediment for non-bioinformatician plant scientists and breeders. PPMdb is freely available at http://ppmdb.easyomics.org.
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Affiliation(s)
- Morad M Mokhtar
- African Genome Center, Mohammed VI Polytechnic University, Ben Guerir, Morocco
| | - Achraf El Allali
- African Genome Center, Mohammed VI Polytechnic University, Ben Guerir, Morocco.
| | | | - Mohamed A M Atia
- Molecular Genetics and Genome Mapping Laboratory, Genome Mapping Department, Agricultural Genetic Engineering Research Institute (AGERI), Agriculture Research Center (ARC), Giza, 12619, Egypt.
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Omar HS, Elsayed TR, Reyad NEHA, Shamkh IM, Sedeek MS. Gene-targeted molecular phylogeny, phytochemical analysis, antibacterial and antifungal activities of some medicinal plant species cultivated in Egypt. PHYTOCHEMICAL ANALYSIS : PCA 2021; 32:724-739. [PMID: 33314357 DOI: 10.1002/pca.3018] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 11/09/2020] [Accepted: 11/10/2020] [Indexed: 06/12/2023]
Abstract
INTRODUCTION Medicinal plants have been used in healthcare since time immemorial, as have their therapeutic activities and the production of plant-based medicines. OBJECTIVES This study aims to use gene-targeted molecular markers for genetic diversity analysis of 16 medicinal plants. Besides, phytochemical analysis antibacterial and antifungal activities of some medicinal plant extracts commonly used in Egypt are compared to major compounds. METHODS DNA-based classification of 16 medicinal species using Conserved DNA-Derived Polymorphism (CDDP) and Start Codon Targeted (SCoT) primers. Three species representing three orders (Pelargonium graveolens, Matricaria chamomilla, and Hyoscyamus muticus were analysed [high-performance liquid chromatography (HPLC), gas chromatography-mass spectrometry (GC-MS)] and evaluated for their antibacterial and antifungal activities against (Escherichia coli O157: H7 ATCC 93111, Salmonella typhimurium ATCC 14028, Methicillin-resistant Staphylococcus aureus (MRSA) ATCC 43300, Bacillus ceruse ATCC 33018, and Sclerotinia sclerotiorum in comparison with some of their antimicrobial components. RESULTS Our results revealed 309 and 349 polymorphic bands with 100% polymorphism. Among them, 51 and 57 were unique loci for CDDP and SCoT, respectively. The 16 species were categorised into three groups depending on the similarity matrix. The results of antibacterial and antifungal activities revealed that Pelargonium oil showed significant antifungal and antibacterial activities against the tested pathogens. Gallic acid severely reduced all tested bacteria's growth, but atropine severely reduced the growth of the B. ceruse only. Molecular modelling revealed their activity against sclerotium development. CONCLUSION The gene-targeted marker techniques were highly useful tools for the classification of the 16 medicinal plant species, despite displaying high similarities at morphological and phytochemical analyses but, have antifungal and antibacterial activities.
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Affiliation(s)
- Hanaa S Omar
- Genetics Department, Faculty of Agriculture, Cairo University, Giza, Egypt
| | - Tarek R Elsayed
- Microbiology Department, Faculty of Agriculture, Cairo University, Giza, Egypt
| | | | - Israa M Shamkh
- Chemo Informatics Lab, Faculty of Agriculture, Cairo University, Research Park, CURP, Giza, Egypt
| | - Mohamed S Sedeek
- Pharmacognosy Department, Faculty of Pharmacy, Cairo University, Giza, Egypt
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Atia MAM, El-Moneim DA, Abdelmoneim TK, Reda EH, Shakour ZTA, El-Halawany AM, El-Kashoury ESA, Shams KA, Abdel-Azim NS, Hegazy MEF. Evaluation of genetic variability and relatedness among eight Centaurea species through CAAT-box derived polymorphism (CBDP) and start codon targeted polymorphism (SCoT) markers. BIOTECHNOL BIOTEC EQ 2021. [DOI: 10.1080/13102818.2021.1960891] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Affiliation(s)
- Mohamed Atia Mohamed Atia
- Genome Mapping Department, Agricultural Genetic Engineering Research Institute (AGERI), Agricultural Research Center (ARC), Giza, Egypt
| | - Diaa Abd El-Moneim
- Department of Plant Production (Genetic Branch), Faculty of Environmental and Agricultural Sciences, Arish University, Arish, Egypt
| | - Taghreed Khaled Abdelmoneim
- Genome Mapping Department, Agricultural Genetic Engineering Research Institute (AGERI), Agricultural Research Center (ARC), Giza, Egypt
| | - Eman Hussein Reda
- Phytochemistry Laboratory, National Organization for Drug Control and Research, Giza, Egypt
| | | | | | | | - Khaled Ahmed Shams
- Chemistry of Medicinal Plants Department, National Research Centre, Giza, Egypt
| | | | - Mohamed-Elamir Fathy Hegazy
- Chemistry of Medicinal Plants Department, National Research Centre, Giza, Egypt
- Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Mainz, Germany
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12
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Fungal Genomic Resources for Strain Identification and Diversity Analysis of 1900 Fungal Species. J Fungi (Basel) 2021; 7:jof7040288. [PMID: 33921243 PMCID: PMC8070597 DOI: 10.3390/jof7040288] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 03/03/2021] [Accepted: 03/04/2021] [Indexed: 11/17/2022] Open
Abstract
Identification and diversity analysis of fungi is greatly challenging. Though internal transcribed spacer (ITS), region-based DNA fingerprinting works as a “gold standard” for most of the fungal species group, it cannot differentiate between all the groups and cryptic species. Therefore, it is of paramount importance to find an alternative approach for strain differentiation. Availability of whole genome sequence data of nearly 2000 fungal species are a promising solution to such requirement. We present whole genome sequence-based world’s largest microsatellite database, FungSatDB having >19M loci obtained from >1900 fungal species/strains using >4000 assemblies across globe. Genotyping efficacy of FungSatDB has been evaluated by both in-silico and in-vitro PCR. By in silico PCR, 66 strains of 8 countries representing four continents were successfully differentiated. Genotyping efficacy was also evaluated by in vitro PCR in four fungal species. This approach overcomes limitation of ITS in species, strain signature, and diversity analysis. It can accelerate fungal genomic research endeavors in agriculture, industrial, and environmental management.
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13
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Pezoa I, Villacreses J, Rubilar M, Pizarro C, Galleguillos MJ, Ejsmentewicz T, Fonseca B, Espejo J, Polanco V, Sánchez C. Generation of Chloroplast Molecular Markers to Differentiate Sophora toromiro and Its Hybrids as a First Approach to Its Reintroduction in Rapa Nui (Easter Island). PLANTS (BASEL, SWITZERLAND) 2021; 10:plants10020342. [PMID: 33578941 PMCID: PMC7916652 DOI: 10.3390/plants10020342] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 02/06/2021] [Accepted: 02/07/2021] [Indexed: 05/03/2023]
Abstract
Sophora toromiro is an endemic tree of Rapa Nui with religious and cultural relevance that despite being extinct in the wild, still persists in botanical gardens and private collections around the world. The authenticity of some toromiro trees has been questioned because the similarities among hybrid lines leads to misclassification of the species. The conservation program of toromiro has the objective of its reinsertion into Rapa Nui, but it requires the exact genotyping and certification of the selected plants in order to efficiently reintroduce the species. In this study, we present for the first time the complete chloroplast genome of S. toromiro and four other Sophora specimens, which were sequenced de-novo and assembled after mapping the raw reads to a chloroplast database. The length of the chloroplast genomes ranges from 154,239 to 154,473 bp. A total of 130-143 simple sequence repeats (SSR) loci and 577 single nucleotide polymorphisms (SNPs) were identified.
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Affiliation(s)
- Ignacio Pezoa
- School of Biotechnology, Universidad Mayor, Santiago 8580745, Chile; (I.P.); (V.P.)
- Advanced Genomics Core, Universidad Mayor, Santiago 8580745, Chile; (J.V.); (C.P.); (M.J.G.); (T.E.); (B.F.)
- Network Biology Laboratory, Centro de Genómica y Bioinformática, Facultad de Ciencias, Universidad Mayor, Santiago 8580745, Chile
| | - Javier Villacreses
- Advanced Genomics Core, Universidad Mayor, Santiago 8580745, Chile; (J.V.); (C.P.); (M.J.G.); (T.E.); (B.F.)
- Network Biology Laboratory, Centro de Genómica y Bioinformática, Facultad de Ciencias, Universidad Mayor, Santiago 8580745, Chile
- PhD Program in Integrative Genomics, Universidad Mayor, Santiago 8580745, Chile;
| | - Miguel Rubilar
- PhD Program in Integrative Genomics, Universidad Mayor, Santiago 8580745, Chile;
| | - Carolina Pizarro
- Advanced Genomics Core, Universidad Mayor, Santiago 8580745, Chile; (J.V.); (C.P.); (M.J.G.); (T.E.); (B.F.)
| | - María Jesús Galleguillos
- Advanced Genomics Core, Universidad Mayor, Santiago 8580745, Chile; (J.V.); (C.P.); (M.J.G.); (T.E.); (B.F.)
| | - Troy Ejsmentewicz
- Advanced Genomics Core, Universidad Mayor, Santiago 8580745, Chile; (J.V.); (C.P.); (M.J.G.); (T.E.); (B.F.)
| | - Beatriz Fonseca
- Advanced Genomics Core, Universidad Mayor, Santiago 8580745, Chile; (J.V.); (C.P.); (M.J.G.); (T.E.); (B.F.)
| | - Jaime Espejo
- National Botanic Garden of Viña del Mar, Valparaíso 2561881, Chile;
| | - Víctor Polanco
- School of Biotechnology, Universidad Mayor, Santiago 8580745, Chile; (I.P.); (V.P.)
| | - Carolina Sánchez
- Advanced Genomics Core, Universidad Mayor, Santiago 8580745, Chile; (J.V.); (C.P.); (M.J.G.); (T.E.); (B.F.)
- Applied Genomics Laboratory, Centro de Genómica y Bioinformática, Facultad de Ciencias, Universidad Mayor, Santiago 8580745, Chile
- Correspondence: ; Tel.: +56-2-2328-1305
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14
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citSATdb: Genome-Wide Simple Sequence Repeat (SSR) Marker Database of Citrus Species for Germplasm Characterization and Crop Improvement. Genes (Basel) 2020; 11:genes11121486. [PMID: 33321957 PMCID: PMC7764524 DOI: 10.3390/genes11121486] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 11/23/2020] [Accepted: 11/26/2020] [Indexed: 11/17/2022] Open
Abstract
Microsatellites or simple sequence repeats (SSRs) are popular co-dominant markers that play an important role in crop improvement. To enhance genomic resources in general horticulture, we identified SSRs in the genomes of eight citrus species and characterized their frequency and distribution in different genomic regions. Citrus is the world's most widely cultivated fruit crop. We have implemented a microsatellite database, citSATdb, having the highest number (~1,296,500) of putative SSR markers from the genus Citrus, represented by eight species. The database is based on a three-tier approach using MySQL, PHP, and Apache. The markers can be searched using multiple search parameters including chromosome/scaffold number(s), motif types, repeat nucleotides (1-6), SSR length, patterns of repeat motifs and chromosome/scaffold location. The cross-species transferability of selected markers can be checked using e-PCR. Further, the markers can be visualized using the Jbrowse feature. These markers can be used for distinctness, uniformity, and stability (DUS) tests of variety identification, marker-assisted selection (MAS), gene discovery, QTL mapping, and germplasm characterization. citSATdb represents a comprehensive source of markers for developing/implementing new approaches for molecular breeding, required to enhance Citrus productivity. The potential polymorphic SSR markers identified by cross-species transferability could be used for genetic diversity and population distinction in other species.
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15
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Mokhtar MM, Hussein EHA, El-Assal SEDS, Atia MAM. VfODB: a comprehensive database of ESTs, EST-SSRs, mtSSRs, microRNA-target markers and genetic maps in Vicia faba. AOB PLANTS 2020; 12:plaa064. [PMID: 33408850 PMCID: PMC7759246 DOI: 10.1093/aobpla/plaa064] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 11/21/2020] [Indexed: 05/20/2023]
Abstract
Faba bean (Vicia faba) is an essential food and fodder legume crop worldwide due to its high content of proteins and fibres. Molecular markers tools represent an invaluable tool for faba bean breeders towards rapid crop improvement. Although there have historically been few V. faba genome resources available, several transcriptomes and mitochondrial genome sequence data have been released. These data in addition to previously developed genetic linkage maps represent a great resource for developing functional markers and maps that can accelerate the faba bean breeding programmes. Here, we present the Vicia faba Omics database (VfODB) as a comprehensive database integrating germplasm information, expressed sequence tags (ESTs), expressed sequence tags-simple sequence repeats (EST-SSRs), and mitochondrial-simple sequence repeats (mtSSRs), microRNA-target markers and genetic maps in faba bean. In addition, KEGG pathway-based markers and functional maps are integrated as a novel class of annotation-based markers/maps. Collectively, we developed 31 536 EST markers, 9071 EST-SSR markers and 3023 microRNA-target markers based on V. faba RefTrans V2 mining. By mapping 7940 EST and 2282 EST-SSR markers against the KEGG pathways database we successfully developed 107 functional maps. Also, 40 mtSSR markers were developed based on mitochondrial genome mining. On the data curation level, we retrieved 3461 markers representing 12 types of markers (CAPS, EST, EST-SSR, Gene marker, INDEL, Isozyme, ISSR, RAPD, SCAR, RGA, SNP and SSR), which mapped across 18 V. faba genetic linkage maps. VfODB provides two user-friendly tools to identify, classify SSR motifs and in silico amplify their targets. VfODB can serve as a powerful database and helpful platform for faba bean research community as well as breeders interested in Genomics-Assisted Breeding.
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Affiliation(s)
- Morad M Mokhtar
- Molecular Genetics and Genome Mapping Laboratory, Genome Mapping Department, Agricultural Genetic Engineering Research Institute (AGERI), Agricultural Research Center (ARC), Giza, Egypt
| | | | | | - Mohamed A M Atia
- Molecular Genetics and Genome Mapping Laboratory, Genome Mapping Department, Agricultural Genetic Engineering Research Institute (AGERI), Agricultural Research Center (ARC), Giza, Egypt
- Corresponding author’s e-mail address:
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16
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Naranpanawa DNU, Chandrasekara CHWMRB, Bandaranayake PCG, Bandaranayake AU. Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists. Sci Rep 2020; 10:18236. [PMID: 33106560 PMCID: PMC7588437 DOI: 10.1038/s41598-020-75270-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2019] [Accepted: 09/21/2020] [Indexed: 02/07/2023] Open
Abstract
Recent advances in next-generation sequencing technologies have paved the path for a considerable amount of sequencing data at a relatively low cost. This has revolutionized the genomics and transcriptomics studies. However, different challenges are now created in handling such data with available bioinformatics platforms both in assembly and downstream analysis performed in order to infer correct biological meaning. Though there are a handful of commercial software and tools for some of the procedures, cost of such tools has made them prohibitive for most research laboratories. While individual open-source or free software tools are available for most of the bioinformatics applications, those components usually operate standalone and are not combined for a user-friendly workflow. Therefore, beginners in bioinformatics might find analysis procedures starting from raw sequence data too complicated and time-consuming with the associated learning-curve. Here, we outline a procedure for de novo transcriptome assembly and Simple Sequence Repeats (SSR) primer design solely based on tools that are available online for free use. For validation of the developed workflow, we used Illumina HiSeq reads of different tissue samples of Santalum album (sandalwood), generated from a previous transcriptomics project. A portion of the designed primers were tested in the lab with relevant samples and all of them successfully amplified the targeted regions. The presented bioinformatics workflow can accurately assemble quality transcriptomes and develop gene specific SSRs. Beginner biologists and researchers in bioinformatics can easily utilize this workflow for research purposes.
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Affiliation(s)
- D N U Naranpanawa
- Agricultural Biotechnology Centre, Faculty of Agriculture, University of Peradeniya, Peradeniya, 20400, Sri Lanka
- Postgraduate Institute of Science, University of Peradeniya, Peradeniya, 20400, Sri Lanka
| | - C H W M R B Chandrasekara
- Agricultural Biotechnology Centre, Faculty of Agriculture, University of Peradeniya, Peradeniya, 20400, Sri Lanka
| | - P C G Bandaranayake
- Agricultural Biotechnology Centre, Faculty of Agriculture, University of Peradeniya, Peradeniya, 20400, Sri Lanka
| | - A U Bandaranayake
- Department of Computer Engineering, Faculty of Engineering, University of Peradeniya, Peradeniya, 20400, Sri Lanka.
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17
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Avvaru AK, Sharma D, Verma A, Mishra RK, Sowpati DT. MSDB: a comprehensive, annotated database of microsatellites. Nucleic Acids Res 2020; 48:D155-D159. [PMID: 31599331 PMCID: PMC6943038 DOI: 10.1093/nar/gkz886] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2019] [Revised: 09/28/2019] [Accepted: 10/01/2019] [Indexed: 11/18/2022] Open
Abstract
Microsatellites are short tandem repeats of 1–6 nucleotide motifs, studied for their utility as genome markers and in forensics. Recent evidence points to the role of microsatellites in important regulatory functions, and their length polymorphisms at coding regions are linked to various neurodegenerative disorders in humans. Microsatellites show a taxon-specific enrichment in eukaryotic genomes, and their evolution remains poorly understood. Though other databases of microsatellites exist, they fall short on several fronts. MSDB (MicroSatellite DataBase) is a collection of >4 billion microsatellites from 37 680 genomes presented in a user-friendly web portal for easy, interactive analysis and visualization. This is by far the most comprehensive, annotated, updated database to access and analyze microsatellite data of multiple species. The features of MSDB enable users to explore the data as tables that can be filtered and exported, and also as interactive charts to view and compare the data of multiple species simultaneously. Its modularity and architecture permit seamless updates with new data, making it a powerful tool and useful resource to researchers working on this important class of DNA elements, particularly in context of their evolution and emerging roles in genome organization and gene regulation.
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Affiliation(s)
- Akshay Kumar Avvaru
- CSIR-Centre for Cellular and Molecular Biology, Hyderabad - 500007, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad - 201002, India
| | - Deepak Sharma
- CSIR-Centre for Cellular and Molecular Biology, Hyderabad - 500007, India
| | - Archana Verma
- CSIR-Centre for Cellular and Molecular Biology, Hyderabad - 500007, India
| | - Rakesh K Mishra
- CSIR-Centre for Cellular and Molecular Biology, Hyderabad - 500007, India
| | - Divya Tej Sowpati
- CSIR-Centre for Cellular and Molecular Biology, Hyderabad - 500007, India
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18
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Abouseadaa HH, Atia MAM, Younis IY, Issa MY, Ashour HA, Saleh I, Osman GH, Arif IA, Mohsen E. Gene-targeted molecular phylogeny, phytochemical profiling, and antioxidant activity of nine species belonging to family Cactaceae. Saudi J Biol Sci 2020; 27:1649-1658. [PMID: 32489307 PMCID: PMC7253903 DOI: 10.1016/j.sjbs.2020.03.007] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Revised: 03/02/2020] [Accepted: 03/04/2020] [Indexed: 12/21/2022] Open
Abstract
Cactaceae plant family comprises over 130 genera and 2000 species of succulent flowering plants. The genera Mammillaria and Notocactus (Parodia), which have medicinal and nutritional applications as well as aesthetic appeal, are considered to be among the major genera of the family. Several species of both genera show morphological and chemical similarities and diversities according to environmental conditions and genotypes. Here, we assessed the genetic relationships of nine species belonging to two major genera Mammillaria and Notocactus under the family Cactaceae, using two modern gene-targeting marker techniques, the Start Codon Targeted (SCoT) Polymorphism and the Conserved DNA-Derived Polymorphism (CDDP). Besides, we screened the various phytochemicals and evaluated the antioxidant activities of the nine species of cacti. Five out of the 10 SCoT and eight CDDP primers used to screen genetic variations within the nine species yielded species-specific reproducible bands. The entire 156 loci were detected, of which 107 were polymorphic, 26 were monomorphic, and 23 were unique loci. The nine species were categorized into two groups based on the dendrogram and similarity matrix. Phytochemical profiling revealed that sterols, triterpenes, flavonoids, and tannins were found in all the tested species. Additionally, two Notocactus species (N. shlosserii and N. roseoluteus) and one Mammillaria species (M. spinosissima) revealed a considerable antioxidant activity. Our results demonstrated that gene-targeting marker techniques were highly powerful tools for the classification and characterization of the nine investigated species, despite displaying high similarities at both morphological and phytochemical levels.
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Affiliation(s)
| | - Mohamed A M Atia
- Molecular Genetics and Genome Mapping Lab., Agriculture Genetic Engineering Research Institute (AGERI), Agriculture Research Center (ARC), Egypt
| | - Inas Y Younis
- Pharmacognosy Department, Faculty of Pharmacy, Cairo University, Egypt
| | - Marwa Y Issa
- Pharmacognosy Department, Faculty of Pharmacy, Cairo University, Egypt
| | - Haraz A Ashour
- Pharmacy Department, King Abdullah medical complex, Jeddah, Saudi Arabia
| | - Ibrahim Saleh
- Prince Sultan Research Chair for Environment and Wildlife, Department of Botany & Microbiology, College of Sciences, King Saud University (KSU), Riyadh, Saudi Arabia
| | - Gamal H Osman
- Department of Biology, Faculty of Applied Science, Umm Al-Qura University, Makkah, Saudi Arabia.,Research Laboratories Center, Faculty of Applied Science, Umm Al-Qura University, Makkah, Saudi Arabia.,Microbial Genetics Department, Agricultural Genetic Engineering Research Institute (AGERI), ARC, Giza, Egypt
| | - Ibrahim A Arif
- Prince Sultan Research Chair for Environment and Wildlife, Department of Botany & Microbiology, College of Sciences, King Saud University (KSU), Riyadh, Saudi Arabia
| | - Engy Mohsen
- Pharmacognosy Department, Faculty of Pharmacy, Cairo University, Egypt
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19
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Du L, Liu Q, Zhao K, Tang J, Zhang X, Yue B, Fan Z. PSMD: An extensive database for pan-species microsatellite investigation and marker development. Mol Ecol Resour 2019; 20:283-291. [PMID: 31599098 DOI: 10.1111/1755-0998.13098] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 09/18/2019] [Accepted: 09/24/2019] [Indexed: 12/21/2022]
Abstract
Microsatellites are widely distributed throughout nearly all genomes which have been extensively exploited as powerful genetic markers for diverse applications due to their high polymorphisms. Their length variations are involved in gene regulation and implicated in numerous genetic diseases even in cancers. Although much effort has been devoted in microsatellite database construction, the existing microsatellite databases still had some drawbacks, such as limited number of species, unfriendly export format, missing marker development, lack of compound microsatellites and absence of gene annotation, which seriously restricted researchers to perform downstream analysis. In order to overcome the above limitations, we developed PSMD (Pan-Species Microsatellite Database, http://big.cdu.edu.cn/psmd/) as a web-based database to facilitate researchers to easily identify microsatellites, exploit reliable molecular markers and compare microsatellite distribution pattern on genome-wide scale. In current release, PSMD comprises 678,106,741 perfect microsatellites and 43,848,943 compound microsatellites from 18,408 organisms, which covered almost all species with available genomic data. In addition to interactive browse interface, PSMD also offers a flexible filter function for users to quickly gain desired microsatellites from large data sets. PSMD allows users to export GFF3 formatted file and CSV formatted statistical file for downstream analysis. We also implemented an online tool for analysing occurrence of microsatellites with user-defined parameters. Furthermore, Primer3 was embedded to help users to design high-quality primers with customizable settings. To our knowledge, PSMD is the most extensive resource which is likely to be adopted by scientists engaged in biological, medical, environmental and agricultural research.
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Affiliation(s)
- Lianming Du
- Institute for Advanced Study, Chengdu University, Chengdu, China
| | - Qin Liu
- Key Laboratory of Bio-resources and Eco-environment, Ministry of Education, College of Life Science, Sichuan University, Chengdu, China.,College of Life Sciences and Food Engineering, Yibin University, Yibin, China
| | - Kelei Zhao
- Institute for Advanced Study, Chengdu University, Chengdu, China
| | - Jie Tang
- School of Pharmacy and Bioengineering, Chengdu University, Chengdu, China
| | - Xiuyue Zhang
- Key Laboratory of Bio-resources and Eco-environment, Ministry of Education, College of Life Science, Sichuan University, Chengdu, China
| | - Bisong Yue
- Key Laboratory of Bio-resources and Eco-environment, Ministry of Education, College of Life Science, Sichuan University, Chengdu, China
| | - Zhenxin Fan
- Key Laboratory of Bio-resources and Eco-environment, Ministry of Education, College of Life Science, Sichuan University, Chengdu, China
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