Unraveling the Genetic Structure of Brazilian Commercial Sugarcane Cultivars Through Microsatellite Markers

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2018 Apr 24

PMID 29684082

Citations 9

Authors

Joao Ricardo Vieira Manechini

Juliana Borges da Costa

Bruna Turcatto Pereira

Luciana Aparecida Carlini-Garcia

Mauro Alexandre Xavier

Marcos Guimaraes de Andrade Landell

Luciana Rossini Pinto

Affiliations

Soon will be listed here.

Abstract

The Brazilian sugarcane industry plays an important role in the worldwide supply of sugar and ethanol. Investigation into the genetic structure of current commercial cultivars and comparisons to the main ancestor species allow sugarcane breeding programs to better manage crosses and germplasm banks as well as to promote its rational use. In the present study, the genetic structure of a group of Brazilian cultivars currently grown by commercial producers was assessed through microsatellite markers and contrasted with a group of basic germplasm mainly composed of Saccharum officinarum and S. spontaneum accessions. A total of 285 alleles was obtained by a set of 12 SSRs primer pairs that taken together were able to efficiently distinguish and capture the genetic variability of sugarcane commercial cultivars and basic germplasm accessions allowing its application in a fast and cost-effective way for routine cultivar identification and management of sugarcane germplasm banks. Allelic distribution revealed that 97.6% of the cultivar alleles were found in the basic germplasm while 42% of the basic germplasm alleles were absent in cultivars. Of the absent alleles, 3% was exclusive to S. officinarum, 33% to S. spontaneum and 19% to other species/exotic hybrids. We found strong genetic differentiation between the Brazilian commercial cultivars and the two main species (S. officinarum: [Formula: see text] = 0.211 and S. spontaneum: [Formula: see text] = 0.216, P<0.001), and significant contribution of the latter in the genetic variability of commercial cultivars. Average dissimilarity within cultivars was 1.2 and 1.4 times lower than that within S. officinarum and S. spontaneum. Genetic divergence found between cultivars and S. spontaneum accessions has practical applications for energy cane breeding programs as the choice of more divergent parents will maximize the frequency of transgressive individuals in the progeny.

Citing Articles

Assessing the genetic integrity of sugarcane germplasm in the USDA-ARS National Plant Germplasm System collection using single-dose SNP markers.

Park S, Zhang D, Ali G Front Plant Sci. 2024; 14:1337736.

PMID: 38239228 PMC: 10794611. DOI: 10.3389/fpls.2023.1337736.

Genetic diversity and population structure of sugarcane introgressed hybrids by SSR markers.

Elumalai K, Srinivasan A 3 Biotech. 2023; 13(12):399.

PMID: 37974927 PMC: 10645997. DOI: 10.1007/s13205-023-03823-5.

Genetic diversity and population structure of Saccharum hybrids.

Perera M, Ostengo S, Malavera A, Balsalobre T, Onorato G, Noguera A PLoS One. 2023; 18(8):e0289504.

PMID: 37582090 PMC: 10426985. DOI: 10.1371/journal.pone.0289504.

A set of SSR markers to characterize genetic diversity in all Viburnum species.

Hamm T, Nowicki M, Boggess S, Ranney T, Trigiano R Sci Rep. 2023; 13(1):5343.

PMID: 37005396 PMC: 10067831. DOI: 10.1038/s41598-023-31878-0.

Planting Season Impacts Sugarcane Stem Development, Secondary Metabolite Levels, and Natural Antisense Transcription.

Wijma M, Lembke C, Diniz A, Santini L, Zambotti-Villela L, Colepicolo P Cells. 2021; 10(12).

PMID: 34943959 PMC: 8700069. DOI: 10.3390/cells10123451.

References

Jarne P, Lagoda P . Microsatellites, from molecules to populations and back. Trends Ecol Evol. 2011; 11(10):424-9. DOI: 10.1016/0169-5347(96)10049-5. View

Schlotterer C, Tautz D . Slippage synthesis of simple sequence DNA. Nucleic Acids Res. 1992; 20(2):211-5. PMC: 310356. DOI: 10.1093/nar/20.2.211. View

Scordia D, Cosentino S, Jeffries T . Second generation bioethanol production from Saccharum spontaneum L. ssp. aegyptiacum (Willd.) Hack. Bioresour Technol. 2010; 101(14):5358-65. DOI: 10.1016/j.biortech.2010.02.036. View

Saitou N, Nei M . The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol. 1987; 4(4):406-25. DOI: 10.1093/oxfordjournals.molbev.a040454. View

Lima M, Garcia A, Oliveira K, Matsuoka S, Arizono H, De Souza Jr C . Analysis of genetic similarity detected by AFLP and coefficient of parentage among genotypes of sugar cane ( Saccharum spp.). Theor Appl Genet. 2003; 104(1):30-8. DOI: 10.1007/s001220200003. View

Pritchard J, Stephens M, Donnelly P . Inference of population structure using multilocus genotype data. Genetics. 2000; 155(2):945-59. PMC: 1461096. DOI: 10.1093/genetics/155.2.945. View

Edme S, Glynn N, Comstock J . Genetic segregation of microsatellite markers in Saccharum officinarum and S. spontaneum. Heredity (Edinb). 2006; 97(5):366-75. DOI: 10.1038/sj.hdy.6800888. View

Pinto L, Oliveira K, Cesar Ulian E, Garcia A, de Souza A . Survey in the sugarcane expressed sequence tag database (SUCEST) for simple sequence repeats. Genome. 2004; 47(5):795-804. DOI: 10.1139/g04-055. View

Dal-Bianco M, Carneiro M, Hotta C, Chapola R, Hoffmann H, Garcia A . Sugarcane improvement: how far can we go?. Curr Opin Biotechnol. 2011; 23(2):265-70. DOI: 10.1016/j.copbio.2011.09.002. View

10.

You Q, Xu L, Zheng Y, Que Y . Genetic diversity analysis of sugarcane parents in Chinese breeding programmes using gSSR markers. ScientificWorldJournal. 2013; 2013:613062. PMC: 3749591. DOI: 10.1155/2013/613062. View

11.

Aitken K, Jackson P, McIntyre C . A combination of AFLP and SSR markers provides extensive map coverage and identification of homo(eo)logous linkage groups in a sugarcane cultivar. Theor Appl Genet. 2005; 110(5):789-801. DOI: 10.1007/s00122-004-1813-7. View

12.

Marconi T, Costa E, Miranda H, Mancini M, Cardoso-Silva C, Oliveira K . Functional markers for gene mapping and genetic diversity studies in sugarcane. BMC Res Notes. 2011; 4:264. PMC: 3158763. DOI: 10.1186/1756-0500-4-264. View

13.

Evanno G, Regnaut S, Goudet J . Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol. 2005; 14(8):2611-20. DOI: 10.1111/j.1365-294X.2005.02553.x. View

14.

Liu X, Li X, Liu H, Xu C, Lin X, Li C . Phylogenetic Analysis of Different Ploidy Saccharum spontaneum Based on rDNA-ITS Sequences. PLoS One. 2016; 11(3):e0151524. PMC: 4795546. DOI: 10.1371/journal.pone.0151524. View

15.

Nayak S, Song J, Villa A, Pathak B, Ayala-Silva T, Yang X . Promoting utilization of Saccharum spp. genetic resources through genetic diversity analysis and core collection construction. PLoS One. 2014; 9(10):e110856. PMC: 4205016. DOI: 10.1371/journal.pone.0110856. View

16.

Kopelman N, Mayzel J, Jakobsson M, Rosenberg N, Mayrose I . Clumpak: a program for identifying clustering modes and packaging population structure inferences across K. Mol Ecol Resour. 2015; 15(5):1179-91. PMC: 4534335. DOI: 10.1111/1755-0998.12387. View

17.

Hallden C, Nilsson N, Rading I, Sall T . Evaluation of RFLP and RAPD markers in a comparison of Brassica napus breeding lines. Theor Appl Genet. 2013; 88(1):123-8. DOI: 10.1007/BF00222404. View

18.

Cordeiro G, Casu R, McIntyre C, Manners J, Henry R . Microsatellite markers from sugarcane (Saccharum spp.) ESTs cross transferable to erianthus and sorghum. Plant Sci. 2001; 160(6):1115-1123. DOI: 10.1016/s0168-9452(01)00365-x. View

19.

Oliveira K, Pinto L, Marconi T, Mollinari M, Ulian E, Chabregas S . Characterization of new polymorphic functional markers for sugarcane. Genome. 2009; 52(2):191-209. DOI: 10.1139/g08-105. View

20.

Pan Y, Burner D, Legendre B . An assessment of the phylogenetic relationship among sugarcane and related taxa based on the nucleotide sequence of 5S rRNA intergenic spacers. Genetica. 2001; 108(3):285-95. DOI: 10.1023/a:1004191625603. View