BackgroundArgentina has a long tradition of sunflower breeding, and its germplasm is a valuable genetic resource worldwide. However, knowledge of the genetic constitution and variability levels of the Argentinean germplasm is still scarce, rendering the global map of cultivated sunflower diversity incomplete. In this study, 42 microsatellite loci and 384 single nucleotide polymorphisms (SNPs) were used to characterize the first association mapping population used for quantitative trait loci mapping in sunflower, along with a selection of allied open-pollinated and composite populations from the germplasm bank of the National Institute of Agricultural Technology of Argentina. The ability of different kinds of markers to assess genetic diversity and population structure was also evaluated.ResultsThe analysis of polymorphism in the set of sunflower accessions studied here showed that both the microsatellites and SNP markers were informative for germplasm characterization, although to different extents. In general, the estimates of genetic variability were moderate. The average genetic diversity, as quantified by the expected heterozygosity, was 0.52 for SSR loci and 0.29 for SNPs. Within SSR markers, those derived from non-coding regions were able to capture higher levels of diversity than EST-SSR. A significant correlation was found between SSR and SNP- based genetic distances among accessions. Bayesian and multivariate methods were used to infer population structure. Evidence for the existence of three different genetic groups was found consistently across data sets (i.e., SSR, SNP and SSR + SNP), with the maintainer/restorer status being the most prevalent characteristic associated with group delimitation.ConclusionThe present study constitutes the first report comparing the performance of SSR and SNP markers for population genetics analysis in cultivated sunflower. We show that the SSR and SNP panels examined here, either used separately or in conjunction, allowed consistent estimations of genetic diversity and population structure in sunflower breeding materials. The generated knowledge about the levels of diversity and population structure of sunflower germplasm is an important contribution to this crop breeding and conservation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-014-0360-x) contains supplementary material, which is available to authorized users.
Heteropteran chromosomes are holokinetic; during mitosis, sister chromatids segregate parallel to each other but, during meiosis, kinetic activity is restricted to one pair of telomeric regions. This meiotic behaviour has been corroborated for all rod bivalents. For ring bivalents, we have previously proposed that one of the two chiasmata releases first, and a telokinetic activity is also achieved. In the present work we analyse the meiotic behaviour of ring bivalents in Pachylis argentinus (Coreidae) and Nezara viridula (Pentatomidae) and we describe for the first time the chromosome complement and male meiosis of the former (2n = 12 + 2m + X0, pre-reduction of the X). Both species possess a large chromosome pair with a secondary constriction which is a nucleolus organizer region as revealed by in-situ hybridization. Here we propose a new mode of segregation for ring bivalents: when the chromosome pair bears a secondary constriction, it is not essential that one of the chiasmata releases first since these regions or repetitive DNA sequences adjacent to them become functional as alternative sites for microtubule attachment and they undertake chromosome segregation to the poles during anaphase I.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.