Streamlining of Simple Sequence Repeat Data Mining Methodologies and Pipelines for Crop Scanning

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Publicat a:Plants vol. 13, no. 18 (2024), p. 2619
Autor principal: Subramaniam Geethanjali
Altres autors: Kadirvel, Palchamy, Anumalla, Mahender, Nithyananth Hemanth Sadhana, Anandan Annamalai, Jauhar, Ali
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MDPI AG
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024 7 |a 10.3390/plants13182619  |2 doi 
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100 1 |a Subramaniam Geethanjali  |u Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641003, India; <email>geethanjalitnau@yahoo.com</email> (S.G.); <email>sadhanariya17@gmail.com</email> (N.H.S.) 
245 1 |a Streamlining of Simple Sequence Repeat Data Mining Methodologies and Pipelines for Crop Scanning 
260 |b MDPI AG  |c 2024 
513 |a Journal Article 
520 3 |a 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. 
653 |a Evolution 
653 |a Gene polymorphism 
653 |a Genetic markers 
653 |a Plant breeding 
653 |a Genomics 
653 |a Data mining 
653 |a Hybridization 
653 |a Knobs 
653 |a Adaptability 
653 |a Codominance 
653 |a Crops 
653 |a Genomes 
653 |a Nucleotide sequence 
653 |a Genes 
653 |a Genetic diversity 
653 |a Artificial chromosomes 
653 |a Genotyping 
653 |a Polymorphism 
653 |a Chromosomes 
653 |a Pipelines 
653 |a Gene sequencing 
653 |a Cloning 
653 |a Deoxyribonucleic acid--DNA 
653 |a Simple sequence repeats 
653 |a Single-nucleotide polymorphism 
653 |a Information processing 
653 |a Breeding 
653 |a Algorithms 
653 |a Software 
700 1 |a Kadirvel, Palchamy  |u Crop Improvement Section, ICAR-Indian Institute of Oilseeds Research, Rajendranagar, Hyderabad 500030, India; <email>kadirvel.palchamy@gmail.com</email> 
700 1 |a Anumalla, Mahender  |u Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), Los Baños 4031, Laguna, Philippines; <email>m.anumalla@irri.org</email>; IRRI South Asia Hub, Patancheru, Hyderabad 502324, India 
700 1 |a Nithyananth Hemanth Sadhana  |u Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641003, India; <email>geethanjalitnau@yahoo.com</email> (S.G.); <email>sadhanariya17@gmail.com</email> (N.H.S.) 
700 1 |a Anandan Annamalai  |u Indian Council of Agricultural Research (ICAR), Indian Institute of Seed Science, Bengaluru 560065, India 
700 1 |a Jauhar, Ali  |u Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), Los Baños 4031, Laguna, Philippines; <email>m.anumalla@irri.org</email> 
773 0 |t Plants  |g vol. 13, no. 18 (2024), p. 2619 
786 0 |d ProQuest  |t Agriculture Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3110667828/abstract/embedded/09EF48XIB41FVQI7?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3110667828/fulltextwithgraphics/embedded/09EF48XIB41FVQI7?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3110667828/fulltextPDF/embedded/09EF48XIB41FVQI7?source=fedsrch