Genetic diversity and population structure among 133 elite genotypes of sugarcane (Saccharum spp.) for use as parents in sugarcane varietal improvement

A measure of genetic diversity of genotypes to be used as parents is imperative to use them prudently in crop improvement. In this study, genetic diversity and population structure of 133 sugarcane hybrid derivatives were quantified using 20 sequence-tagged microsatellite sites (STMS) primers. The n...

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description A measure of genetic diversity of genotypes to be used as parents is imperative to use them prudently in crop improvement. In this study, genetic diversity and population structure of 133 sugarcane hybrid derivatives were quantified using 20 sequence-tagged microsatellite sites (STMS) primers. The number of alleles ranged from 9 to 27 with the average of 17.95 alleles per primer, while the polymorphism information content values of the primers ranged from 0.29 to 0.78. Cophenetic correlation coefficient value observed as 0.84 by STMS markers revealed that the cluster result was acceptable for the calculation of genetic similarity matrix. Principal component analysis showed that 133 genotypes fell in two groups, first and second components associated 8.34 and 3.22% with eigen values of 5.61 and 2.17, respectively. Similar trend was observed with principal coordinate analysis, wherein, the first and second component accounted to 8.34 and 3.22% with eigen values of 741.29 and 286.11. The similarity index values ranged from 0.50 to 0.87 for the possible 8778 combinations from 133 genotypes, of which 8069 combinations exhibited less/moderate genetic similarity indicating the availability of sufficient genetic diversity in the experimental material and hence their value in the genetic improvement of sugarcane. Dissimilarity analysis using DARwin of 133 genotypes could distinguish two major clusters and into five subclusters and the results matched with those of the population structure which also showed five subpopulations. The bigger group SP1 was predominantly comprised of clones developed at the main sugarcane-breeding place in India, located at Coimbatore. The subpopulation SP4 was formed largely with clones from research stations other than at Coimbatore and interspecific hybrids, while SP5 comprised of clones of early origin. These observations were similar to the radial tree based on the DARwin software in that 81.95% of the genotypes of each cluster were similar in the two analyses. The results thus showed that location and time of origin were two major factors that contributed to diversity. Based on analysis of molecular variance, subpopulations SP2 and SP4 were more variable from the rest. SP2 (comprising of Co 99008, Co 99006, Co 94012, Co 93023, CoC 671, Co 89034, Co 91003, Co 06022, Co 98017, Co 87044, Co 06018, Co 89003, Co 98014, and Co 86032) exhibited maximum genetic variation, the least gene flow, and the lowest heterozygosity value and would s
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S. ; Hemaprabha, G.</creator><creatorcontrib>Sarath Padmanabhan, T. S. ; Hemaprabha, G.</creatorcontrib><description>A measure of genetic diversity of genotypes to be used as parents is imperative to use them prudently in crop improvement. In this study, genetic diversity and population structure of 133 sugarcane hybrid derivatives were quantified using 20 sequence-tagged microsatellite sites (STMS) primers. The number of alleles ranged from 9 to 27 with the average of 17.95 alleles per primer, while the polymorphism information content values of the primers ranged from 0.29 to 0.78. Cophenetic correlation coefficient value observed as 0.84 by STMS markers revealed that the cluster result was acceptable for the calculation of genetic similarity matrix. Principal component analysis showed that 133 genotypes fell in two groups, first and second components associated 8.34 and 3.22% with eigen values of 5.61 and 2.17, respectively. Similar trend was observed with principal coordinate analysis, wherein, the first and second component accounted to 8.34 and 3.22% with eigen values of 741.29 and 286.11. The similarity index values ranged from 0.50 to 0.87 for the possible 8778 combinations from 133 genotypes, of which 8069 combinations exhibited less/moderate genetic similarity indicating the availability of sufficient genetic diversity in the experimental material and hence their value in the genetic improvement of sugarcane. Dissimilarity analysis using DARwin of 133 genotypes could distinguish two major clusters and into five subclusters and the results matched with those of the population structure which also showed five subpopulations. The bigger group SP1 was predominantly comprised of clones developed at the main sugarcane-breeding place in India, located at Coimbatore. The subpopulation SP4 was formed largely with clones from research stations other than at Coimbatore and interspecific hybrids, while SP5 comprised of clones of early origin. These observations were similar to the radial tree based on the DARwin software in that 81.95% of the genotypes of each cluster were similar in the two analyses. The results thus showed that location and time of origin were two major factors that contributed to diversity. Based on analysis of molecular variance, subpopulations SP2 and SP4 were more variable from the rest. SP2 (comprising of Co 99008, Co 99006, Co 94012, Co 93023, CoC 671, Co 89034, Co 91003, Co 06022, Co 98017, Co 87044, Co 06018, Co 89003, Co 98014, and Co 86032) exhibited maximum genetic variation, the least gene flow, and the lowest heterozygosity value and would serve as the best group for utilization in genetic improvement. Graphical genotyping (GGT) image of each genotype was distinctly different, indicating the genetic uniqueness of sugarcane genotypes under study as revealed through STMS technology. A core set of 40 genotypes was identified using GGT 2.0 software program for the easiness of harnessing the available genetic diversity of 133 genotypes, through hybridization in sugarcane improvement programs.</description><identifier>ISSN: 2190-572X</identifier><identifier>EISSN: 2190-5738</identifier><identifier>DOI: 10.1007/s13205-018-1364-2</identifier><identifier>PMID: 30073124</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Agriculture ; Alleles ; Bioinformatics ; Biomaterials ; Biotechnology ; Cancer Research ; Chemistry ; Chemistry and Materials Science ; Clusters ; Computer programs ; Correlation coefficients ; Crop improvement ; Dissimilar materials ; Gene flow ; Gene polymorphism ; Genetic analysis ; Genetic diversity ; Genotyping ; Heterozygosity ; Hybridization ; Hybrids ; Interspecific ; Mathematical analysis ; Molecular chains ; Original ; Original Article ; Parents ; Polymorphism ; Population genetics ; Population structure ; Population studies ; Primers ; Principal components analysis ; Saccharum ; Similarity ; Sp1 protein ; Stem Cells ; Subpopulations ; Sugarcane ; Variance analysis</subject><ispartof>3 Biotech, 2018-08, Vol.8 (8), p.339-12, Article 339</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2018</rights><rights>3 Biotech is a copyright of Springer, (2018). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c470t-a8b5cf2ba4deb9f54d39f306679e8e209dd3736d4e41e1d2748267a14d9f25f3</citedby><cites>FETCH-LOGICAL-c470t-a8b5cf2ba4deb9f54d39f306679e8e209dd3736d4e41e1d2748267a14d9f25f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6060222/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6060222/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,41488,42557,51319,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30073124$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sarath Padmanabhan, T. S.</creatorcontrib><creatorcontrib>Hemaprabha, G.</creatorcontrib><title>Genetic diversity and population structure among 133 elite genotypes of sugarcane (Saccharum spp.) for use as parents in sugarcane varietal improvement</title><title>3 Biotech</title><addtitle>3 Biotech</addtitle><addtitle>3 Biotech</addtitle><description>A measure of genetic diversity of genotypes to be used as parents is imperative to use them prudently in crop improvement. In this study, genetic diversity and population structure of 133 sugarcane hybrid derivatives were quantified using 20 sequence-tagged microsatellite sites (STMS) primers. The number of alleles ranged from 9 to 27 with the average of 17.95 alleles per primer, while the polymorphism information content values of the primers ranged from 0.29 to 0.78. Cophenetic correlation coefficient value observed as 0.84 by STMS markers revealed that the cluster result was acceptable for the calculation of genetic similarity matrix. Principal component analysis showed that 133 genotypes fell in two groups, first and second components associated 8.34 and 3.22% with eigen values of 5.61 and 2.17, respectively. Similar trend was observed with principal coordinate analysis, wherein, the first and second component accounted to 8.34 and 3.22% with eigen values of 741.29 and 286.11. The similarity index values ranged from 0.50 to 0.87 for the possible 8778 combinations from 133 genotypes, of which 8069 combinations exhibited less/moderate genetic similarity indicating the availability of sufficient genetic diversity in the experimental material and hence their value in the genetic improvement of sugarcane. Dissimilarity analysis using DARwin of 133 genotypes could distinguish two major clusters and into five subclusters and the results matched with those of the population structure which also showed five subpopulations. The bigger group SP1 was predominantly comprised of clones developed at the main sugarcane-breeding place in India, located at Coimbatore. The subpopulation SP4 was formed largely with clones from research stations other than at Coimbatore and interspecific hybrids, while SP5 comprised of clones of early origin. These observations were similar to the radial tree based on the DARwin software in that 81.95% of the genotypes of each cluster were similar in the two analyses. The results thus showed that location and time of origin were two major factors that contributed to diversity. Based on analysis of molecular variance, subpopulations SP2 and SP4 were more variable from the rest. SP2 (comprising of Co 99008, Co 99006, Co 94012, Co 93023, CoC 671, Co 89034, Co 91003, Co 06022, Co 98017, Co 87044, Co 06018, Co 89003, Co 98014, and Co 86032) exhibited maximum genetic variation, the least gene flow, and the lowest heterozygosity value and would serve as the best group for utilization in genetic improvement. Graphical genotyping (GGT) image of each genotype was distinctly different, indicating the genetic uniqueness of sugarcane genotypes under study as revealed through STMS technology. A core set of 40 genotypes was identified using GGT 2.0 software program for the easiness of harnessing the available genetic diversity of 133 genotypes, through hybridization in sugarcane improvement programs.</description><subject>Agriculture</subject><subject>Alleles</subject><subject>Bioinformatics</subject><subject>Biomaterials</subject><subject>Biotechnology</subject><subject>Cancer Research</subject><subject>Chemistry</subject><subject>Chemistry and Materials Science</subject><subject>Clusters</subject><subject>Computer programs</subject><subject>Correlation coefficients</subject><subject>Crop improvement</subject><subject>Dissimilar materials</subject><subject>Gene flow</subject><subject>Gene polymorphism</subject><subject>Genetic analysis</subject><subject>Genetic diversity</subject><subject>Genotyping</subject><subject>Heterozygosity</subject><subject>Hybridization</subject><subject>Hybrids</subject><subject>Interspecific</subject><subject>Mathematical analysis</subject><subject>Molecular chains</subject><subject>Original</subject><subject>Original Article</subject><subject>Parents</subject><subject>Polymorphism</subject><subject>Population genetics</subject><subject>Population structure</subject><subject>Population studies</subject><subject>Primers</subject><subject>Principal components analysis</subject><subject>Saccharum</subject><subject>Similarity</subject><subject>Sp1 protein</subject><subject>Stem Cells</subject><subject>Subpopulations</subject><subject>Sugarcane</subject><subject>Variance analysis</subject><issn>2190-572X</issn><issn>2190-5738</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kU1rFTEUhgdRbKn9AW4k4KYupuZrJjMbQYpWoeDCLtyF3ORkmjKTjPm4cH9J_6653HqtgtkkcJ7znvPmbZrXBF8SjMX7RBjFXYvJ0BLW85Y-a04pGXHbCTY8P77pj5PmPKV7XE9HupHgl80JqwKMUH7aPFyDh-w0Mm4LMbm8Q8obtIa1zCq74FHKsehcIiC1BD8hwhiC2WVAE_iQdyskFCxKZVJRKw_o4rvS-k7FsqC0rpfvkA0RlVT7E1pVBJ8Tcv5Jw1ZFB1nNyC1rDFtYKvKqeWHVnOD88T5rbj9_ur360t58u_569fGm1Vzg3Kph02lLN4ob2Iy244aNluG-FyMMQPFoDBOsNxw4AWKo4APthSLcjJZ2lp01Hw6ya9ksYHSdHNUs1-gWFXcyKCf_rnh3J6ewlT3uMaW0Clw8CsTws0DKcnFJwzxXY6EkSfHABKn_vkff_oPehxJ9dVcp0eOOcjxWihwoHUNKEexxGYLlPnh5CF7W4OU-eLlXfvPUxbHjd8wVoAcg1ZKfIP4Z_X_VX6Msu6U</recordid><startdate>20180801</startdate><enddate>20180801</enddate><creator>Sarath Padmanabhan, T. 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S. ; Hemaprabha, G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c470t-a8b5cf2ba4deb9f54d39f306679e8e209dd3736d4e41e1d2748267a14d9f25f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Agriculture</topic><topic>Alleles</topic><topic>Bioinformatics</topic><topic>Biomaterials</topic><topic>Biotechnology</topic><topic>Cancer Research</topic><topic>Chemistry</topic><topic>Chemistry and Materials Science</topic><topic>Clusters</topic><topic>Computer programs</topic><topic>Correlation coefficients</topic><topic>Crop improvement</topic><topic>Dissimilar materials</topic><topic>Gene flow</topic><topic>Gene polymorphism</topic><topic>Genetic analysis</topic><topic>Genetic diversity</topic><topic>Genotyping</topic><topic>Heterozygosity</topic><topic>Hybridization</topic><topic>Hybrids</topic><topic>Interspecific</topic><topic>Mathematical analysis</topic><topic>Molecular chains</topic><topic>Original</topic><topic>Original Article</topic><topic>Parents</topic><topic>Polymorphism</topic><topic>Population genetics</topic><topic>Population structure</topic><topic>Population studies</topic><topic>Primers</topic><topic>Principal components analysis</topic><topic>Saccharum</topic><topic>Similarity</topic><topic>Sp1 protein</topic><topic>Stem Cells</topic><topic>Subpopulations</topic><topic>Sugarcane</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sarath Padmanabhan, T. 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S.</au><au>Hemaprabha, G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genetic diversity and population structure among 133 elite genotypes of sugarcane (Saccharum spp.) for use as parents in sugarcane varietal improvement</atitle><jtitle>3 Biotech</jtitle><stitle>3 Biotech</stitle><addtitle>3 Biotech</addtitle><date>2018-08-01</date><risdate>2018</risdate><volume>8</volume><issue>8</issue><spage>339</spage><epage>12</epage><pages>339-12</pages><artnum>339</artnum><issn>2190-572X</issn><eissn>2190-5738</eissn><abstract>A measure of genetic diversity of genotypes to be used as parents is imperative to use them prudently in crop improvement. In this study, genetic diversity and population structure of 133 sugarcane hybrid derivatives were quantified using 20 sequence-tagged microsatellite sites (STMS) primers. The number of alleles ranged from 9 to 27 with the average of 17.95 alleles per primer, while the polymorphism information content values of the primers ranged from 0.29 to 0.78. Cophenetic correlation coefficient value observed as 0.84 by STMS markers revealed that the cluster result was acceptable for the calculation of genetic similarity matrix. Principal component analysis showed that 133 genotypes fell in two groups, first and second components associated 8.34 and 3.22% with eigen values of 5.61 and 2.17, respectively. Similar trend was observed with principal coordinate analysis, wherein, the first and second component accounted to 8.34 and 3.22% with eigen values of 741.29 and 286.11. The similarity index values ranged from 0.50 to 0.87 for the possible 8778 combinations from 133 genotypes, of which 8069 combinations exhibited less/moderate genetic similarity indicating the availability of sufficient genetic diversity in the experimental material and hence their value in the genetic improvement of sugarcane. Dissimilarity analysis using DARwin of 133 genotypes could distinguish two major clusters and into five subclusters and the results matched with those of the population structure which also showed five subpopulations. The bigger group SP1 was predominantly comprised of clones developed at the main sugarcane-breeding place in India, located at Coimbatore. The subpopulation SP4 was formed largely with clones from research stations other than at Coimbatore and interspecific hybrids, while SP5 comprised of clones of early origin. These observations were similar to the radial tree based on the DARwin software in that 81.95% of the genotypes of each cluster were similar in the two analyses. The results thus showed that location and time of origin were two major factors that contributed to diversity. Based on analysis of molecular variance, subpopulations SP2 and SP4 were more variable from the rest. SP2 (comprising of Co 99008, Co 99006, Co 94012, Co 93023, CoC 671, Co 89034, Co 91003, Co 06022, Co 98017, Co 87044, Co 06018, Co 89003, Co 98014, and Co 86032) exhibited maximum genetic variation, the least gene flow, and the lowest heterozygosity value and would serve as the best group for utilization in genetic improvement. Graphical genotyping (GGT) image of each genotype was distinctly different, indicating the genetic uniqueness of sugarcane genotypes under study as revealed through STMS technology. A core set of 40 genotypes was identified using GGT 2.0 software program for the easiness of harnessing the available genetic diversity of 133 genotypes, through hybridization in sugarcane improvement programs.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>30073124</pmid><doi>10.1007/s13205-018-1364-2</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record>
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subjects Agriculture
Alleles
Bioinformatics
Biomaterials
Biotechnology
Cancer Research
Chemistry
Chemistry and Materials Science
Clusters
Computer programs
Correlation coefficients
Crop improvement
Dissimilar materials
Gene flow
Gene polymorphism
Genetic analysis
Genetic diversity
Genotyping
Heterozygosity
Hybridization
Hybrids
Interspecific
Mathematical analysis
Molecular chains
Original
Original Article
Parents
Polymorphism
Population genetics
Population structure
Population studies
Primers
Principal components analysis
Saccharum
Similarity
Sp1 protein
Stem Cells
Subpopulations
Sugarcane
Variance analysis
title Genetic diversity and population structure among 133 elite genotypes of sugarcane (Saccharum spp.) for use as parents in sugarcane varietal improvement
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