A bayesian approach to inferring the genetic population structure of sugarcane accessions from INTA (Argentina)

Understanding the population structure and genetic diversity in sugarcane (Saccharum officinarum L.) accessions from INTA germplasm bank (Argentina) will be of great importance for germplasm collection and breeding improvement as it will identify diverse parental combinations to create segregating p...

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Autores principales:	Pocovi,Mariana Inés, Mariotti,Jorge Alberto
Lenguaje:	English
Publicado:	Instituto de Investigaciones Agropecuarias, INIA 2015
Materias:	AFLP bayesian clustering hierarchical clustering principal coordinate analysis Saccharum officinarum SSR
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392015000200003
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spelling	oai:scielo:S0718-583920150002000032018-10-01A bayesian approach to inferring the genetic population structure of sugarcane accessions from INTA (Argentina)Pocovi,Mariana InésMariotti,Jorge Alberto AFLP bayesian clustering hierarchical clustering principal coordinate analysis Saccharum officinarum SSR Understanding the population structure and genetic diversity in sugarcane (Saccharum officinarum L.) accessions from INTA germplasm bank (Argentina) will be of great importance for germplasm collection and breeding improvement as it will identify diverse parental combinations to create segregating progenies with maximum genetic variability for further selection. A Bayesian approach, ordination methods (PCoA, Principal Coordinate Analysis) and clustering analysis (UPGMA, Unweighted Pair Group Method with Arithmetic Mean) were applied to this purpose. Sixty three INTA sugarcane hybrids were genotyped for 107 Simple Sequence Repeat (SSR) and 136 Amplified Fragment Length Polymorphism (AFLP) loci. Given the low probability values found with AFLP for individual assignment (4.7%), microsatellites seemed to perform better (54%) for STRUCTURE analysis that revealed the germplasm to exist in five optimum groups with partly corresponding to their origin. However clusters shown high degree of admixture, F ST values confirmed the existence of differences among groups. Dissimilarity coefficients ranged from 0.079 to 0.651. PCoA separated sugarcane in groups that did not agree with those identified by STRUCTURE. The clustering including all genotypes neither showed resemblance to populations find by STRUCTURE, but clustering performed considering only individuals displaying a proportional membership > 0.6 in their primary population obtained with STRUCTURE showed close similarities. The Bayesian method indubitably brought more information on cultivar origins than classical PCoA and hierarchical clustering method.info:eu-repo/semantics/openAccessInstituto de Investigaciones Agropecuarias, INIAChilean journal of agricultural research v.75 n.2 20152015-06-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392015000200003en10.4067/S0718-58392015000200003
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	AFLP bayesian clustering hierarchical clustering principal coordinate analysis Saccharum officinarum SSR
spellingShingle	AFLP bayesian clustering hierarchical clustering principal coordinate analysis Saccharum officinarum SSR Pocovi,Mariana Inés Mariotti,Jorge Alberto A bayesian approach to inferring the genetic population structure of sugarcane accessions from INTA (Argentina)
description	Understanding the population structure and genetic diversity in sugarcane (Saccharum officinarum L.) accessions from INTA germplasm bank (Argentina) will be of great importance for germplasm collection and breeding improvement as it will identify diverse parental combinations to create segregating progenies with maximum genetic variability for further selection. A Bayesian approach, ordination methods (PCoA, Principal Coordinate Analysis) and clustering analysis (UPGMA, Unweighted Pair Group Method with Arithmetic Mean) were applied to this purpose. Sixty three INTA sugarcane hybrids were genotyped for 107 Simple Sequence Repeat (SSR) and 136 Amplified Fragment Length Polymorphism (AFLP) loci. Given the low probability values found with AFLP for individual assignment (4.7%), microsatellites seemed to perform better (54%) for STRUCTURE analysis that revealed the germplasm to exist in five optimum groups with partly corresponding to their origin. However clusters shown high degree of admixture, F ST values confirmed the existence of differences among groups. Dissimilarity coefficients ranged from 0.079 to 0.651. PCoA separated sugarcane in groups that did not agree with those identified by STRUCTURE. The clustering including all genotypes neither showed resemblance to populations find by STRUCTURE, but clustering performed considering only individuals displaying a proportional membership > 0.6 in their primary population obtained with STRUCTURE showed close similarities. The Bayesian method indubitably brought more information on cultivar origins than classical PCoA and hierarchical clustering method.
author	Pocovi,Mariana Inés Mariotti,Jorge Alberto
author_facet	Pocovi,Mariana Inés Mariotti,Jorge Alberto
author_sort	Pocovi,Mariana Inés
title	A bayesian approach to inferring the genetic population structure of sugarcane accessions from INTA (Argentina)
title_short	A bayesian approach to inferring the genetic population structure of sugarcane accessions from INTA (Argentina)
title_full	A bayesian approach to inferring the genetic population structure of sugarcane accessions from INTA (Argentina)
title_fullStr	A bayesian approach to inferring the genetic population structure of sugarcane accessions from INTA (Argentina)
title_full_unstemmed	A bayesian approach to inferring the genetic population structure of sugarcane accessions from INTA (Argentina)
title_sort	bayesian approach to inferring the genetic population structure of sugarcane accessions from inta (argentina)
publisher	Instituto de Investigaciones Agropecuarias, INIA
publishDate	2015
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392015000200003
work_keys_str_mv	AT pocovimarianaines abayesianapproachtoinferringthegeneticpopulationstructureofsugarcaneaccessionsfromintaargentina AT mariottijorgealberto abayesianapproachtoinferringthegeneticpopulationstructureofsugarcaneaccessionsfromintaargentina AT pocovimarianaines bayesianapproachtoinferringthegeneticpopulationstructureofsugarcaneaccessionsfromintaargentina AT mariottijorgealberto bayesianapproachtoinferringthegeneticpopulationstructureofsugarcaneaccessionsfromintaargentina
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A bayesian approach to inferring the genetic population structure of sugarcane accessions from INTA (Argentina)

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