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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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Chapuis MP, Plantamp C, Streiff R, Blondin L, Piou C. Microsatellite evolutionary rate and pattern in Schistocerca gregaria inferred from direct observation of germline mutations. Mol Ecol 2015; 24:6107-19. [PMID: 26562076 DOI: 10.1111/mec.13465] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2015] [Revised: 11/05/2015] [Accepted: 11/06/2015] [Indexed: 01/21/2023]
Abstract
Unravelling variation among taxonomic orders regarding the rate of evolution in microsatellites is crucial for evolutionary biology and population genetics research. The mean mutation rate of microsatellites tends to be lower in arthropods than in vertebrates, but data are scarce and mostly concern accumulation of mutations in model species. Based on parent-offspring segregations and a hierarchical Bayesian model, the mean rate of mutation in the orthopteran insect Schistocerca gregaria was estimated at 2.1e(-4) per generation per untranscribed dinucleotide locus. This is close to vertebrate estimates and one order of magnitude higher than estimates from species of other arthropod orders, such as Drosophila melanogaster and Daphnia pulex. We also found evidence of a directional bias towards expansions even for long alleles and exceptionally large ranges of allele sizes. Finally, at transcribed microsatellites, the mean rate of mutation was half the rate found at untranscribed loci and the mutational model deviated from that usually considered, with most mutations involving multistep changes that avoid disrupting the reading frame. Our direct estimates of mutation rate were discussed in the light of peculiar biological and genomic features of S. gregaria, including specificities in mismatch repair and the dependence of its activity to allele length. Shedding new light on the mutational dynamics of grasshopper microsatellites is of critical importance for a number of research fields. As an illustration, we showed how our findings improve microsatellite application in population genetics, by obtaining a more precise estimation of S. gregaria effective population size from a published data set based on the same microsatellites.
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Affiliation(s)
- M-P Chapuis
- CIRAD, UMR CBGP, Montpellier, F-34398, France
| | - C Plantamp
- Laboratoire de Biométrie et Biologie Evolutive, CNRS, UMR 5558, Université Lyon 1, Villeurbanne, 69622, France
| | - R Streiff
- INRA, UMR CBGP, Montpellier, F-34398, France.,INRA, UMR DGIMI, Montpellier, F-34000, France
| | - L Blondin
- CIRAD, UPR B-AMR, Montpellier, F-34398, France
| | - C Piou
- CIRAD, UMR CBGP, Montpellier, F-34398, France
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Yu JN, Won C, Jun J, Lim Y, Kwak M. Fast and cost-effective mining of microsatellite markers using NGS technology: an example of a Korean water deer Hydropotes inermis argyropus. PLoS One 2011; 6:e26933. [PMID: 22069476 PMCID: PMC3206051 DOI: 10.1371/journal.pone.0026933] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2011] [Accepted: 10/06/2011] [Indexed: 11/21/2022] Open
Abstract
Background Microsatellites, a special class of repetitive DNA sequence, have become one of the most popular genetic markers for population/conservation genetic studies. However, its application to endangered species has been impeded by high development costs, a lack of available sequences, and technical difficulties. The water deer Hydropotes inermis is the sole existing endangered species of the subfamily Capreolinae. Although population genetics studies are urgently required for conservation management, no species-specific microsatellite marker has been reported. Methods We adopted next-generation sequencing (NGS) to elucidate the microsatellite markers of Korean water deer and overcome these impediments on marker developments. We performed genotyping to determine the efficiency of this method as applied to population genetics. Results We obtained 98 Mbp of nucleotide information from 260,467 sequence reads. A total of 20,101 di-/tri-nucleotide repeat motifs were identified; di-repeats were 5.9-fold more common than tri-repeats. [CA]n and [AAC]n/[AAT]n repeats were the most frequent di- and tri-repeats, respectively. Of the 17,206 di-repeats, 12,471 microsatellite primer pairs were derived. PCR amplification of 400 primer pairs yielded 106 amplicons and 79 polymorphic markers from 20 individual Korean water deer. Polymorphic rates of the 79 new microsatellites varied from 2 to 11 alleles per locus (He: 0.050–0.880; Ho: 0.000–1.000), while those of known microsatellite markers transferred from cattle to Chinese water deer ranged from 4 to 6 alleles per locus (He: 0.279–0.714; Ho: 0.300–0.400). Conclusions Polymorphic microsatellite markers from Korean water deer were successfully identified using NGS without any prior sequence information and deposited into the public database. Thus, the methods described herein represent a rapid and low-cost way to investigate the population genetics of endangered/non-model species.
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Affiliation(s)
- Jeong-Nam Yu
- National Institute of Biological Resources, Environmental Research Complex, Incheon, Korea
| | - Changman Won
- National Institute of Biological Resources, Environmental Research Complex, Incheon, Korea
| | - Jumin Jun
- National Institute of Biological Resources, Environmental Research Complex, Incheon, Korea
- Department of Life Sciences, Ewha Womans University, Seoul, Korea
| | - YoungWoon Lim
- National Institute of Biological Resources, Environmental Research Complex, Incheon, Korea
| | - Myounghai Kwak
- National Institute of Biological Resources, Environmental Research Complex, Incheon, Korea
- * E-mail:
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Hickner PV, deBruyn B, Lovin DD, Mori A, Saski CA, Severson DW. Enhancing genome investigations in the mosquito Culex quinquefasciatus via BAC library construction and characterization. BMC Res Notes 2011; 4:358. [PMID: 21914202 PMCID: PMC3180476 DOI: 10.1186/1756-0500-4-358] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2011] [Accepted: 09/13/2011] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Culex quinquefasciatus (Say) is a major species in the Culex pipiens complex and an important vector for several human pathogens including West Nile virus and parasitic filarial nematodes causing lymphatic filariasis. It is common throughout tropical and subtropical regions and is among the most geographically widespread mosquito species. Although the complete genome sequence is now available, additional genomic tools are needed to improve the sequence assembly. FINDINGS We constructed a bacterial artificial chromosome (BAC) library using the pIndigoBAC536 vector and HindIII partially digested DNA isolated from Cx. quinquefasciatus pupae, Johannesburg strain (NDJ). Insert size was estimated by NotI digestion and pulsed-field gel electrophoresis of 82 randomly selected clones. To estimate genome coverage, each 384-well plate was pooled for screening with 29 simple sequence repeat (SSR) and five gene markers. The NDJ library consists of 55,296 clones arrayed in 144 384-well microplates. Fragment insert size ranged from 50 to 190 kb in length (mean = 106 kb). Based on a mean insert size of 106 kb and a genome size of 579 Mbp, the BAC library provides ~10.1-fold coverage of the Cx. quinquefasciatus genome. PCR screening of BAC DNA plate pools for SSR loci from the genetic linkage map and for four genes associated with reproductive diapause in Culex pipiens resulted in a mean of 9.0 positive plate pools per locus. CONCLUSION The NDJ library represents an excellent resource for genome assembly enhancement and characterization in Culex pipiens complex mosquitoes.
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Affiliation(s)
- Paul V Hickner
- Eck Institute for Global Health, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Becky deBruyn
- Eck Institute for Global Health, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Diane D Lovin
- Eck Institute for Global Health, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Akio Mori
- Eck Institute for Global Health, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
| | | | - David W Severson
- Eck Institute for Global Health, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
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Song X, Goicoechea JL, Ammiraju JSS, Luo M, He R, Lin J, Lee SJ, Sisneros N, Watts T, Kudrna DA, Golser W, Ashley E, Collura K, Braidotti M, Yu Y, Matzkin LM, McAllister BF, Markow TA, Wing RA. The 19 genomes of Drosophila: a BAC library resource for genus-wide and genome-scale comparative evolutionary research. Genetics 2011; 187:1023-30. [PMID: 21321134 PMCID: PMC3070512 DOI: 10.1534/genetics.111.126540] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2011] [Accepted: 02/05/2011] [Indexed: 11/18/2022] Open
Abstract
The genus Drosophila has been the subject of intense comparative phylogenomics characterization to provide insights into genome evolution under diverse biological and ecological contexts and to functionally annotate the Drosophila melanogaster genome, a model system for animal and insect genetics. Recent sequencing of 11 additional Drosophila species from various divergence points of the genus is a first step in this direction. However, to fully reap the benefits of this resource, the Drosophila community is faced with two critical needs: i.e., the expansion of genomic resources from a much broader range of phylogenetic diversity and the development of additional resources to aid in finishing the existing draft genomes. To address these needs, we report the first synthesis of a comprehensive set of bacterial artificial chromosome (BAC) resources for 19 Drosophila species from all three subgenera. Ten libraries were derived from the exact source used to generate 10 of the 12 draft genomes, while the rest were generated from a strategically selected set of species on the basis of salient ecological and life history features and their phylogenetic positions. The majority of the new species have at least one sequenced reference genome for immediate comparative benefit. This 19-BAC library set was rigorously characterized and shown to have large insert sizes (125-168 kb), low nonrecombinant clone content (0.3-5.3%), and deep coverage (9.1-42.9×). Further, we demonstrated the utility of this BAC resource for generating physical maps of targeted loci, refining draft sequence assemblies and identifying potential genomic rearrangements across the phylogeny.
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Affiliation(s)
- Xiang Song
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Jose Luis Goicoechea
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Jetty S. S. Ammiraju
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Meizhong Luo
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Ruifeng He
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Jinke Lin
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - So-Jeong Lee
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Nicholas Sisneros
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Tom Watts
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - David A. Kudrna
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Wolfgang Golser
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Elizabeth Ashley
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Kristi Collura
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Michele Braidotti
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Yeisoo Yu
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Luciano M. Matzkin
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Bryant F. McAllister
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Therese Ann Markow
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
| | - Rod A. Wing
- Arizona Genomics Institute and BIO5 Institute, School of Plant Sciences, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, Division of Biological Sciences, University of California at San Diego, La Jolla, California 92093 and Department of Biology, University of Iowa, Iowa City, Iowa 52242
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