Cargando…

PollenCALC: Software for estimation of pollen compatibility of self-incompatible allo- and autotetraploid species

BACKGROUND: Self-incompatibility (SI) is a biological mechanism to avoid inbreeding in allogamous plants. In grasses, this mechanism is controlled by a two-locus system (S-Z). Calculation of male and female gamete frequencies is complex for tetraploid species. We are not aware of any software availa...

Descripción completa

Detalles Bibliográficos
Autores principales: Aguirre, Andrea Arias, Wollenweber, Bernd, Frei, Ursula K, Lübberstedt, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3439690/
https://www.ncbi.nlm.nih.gov/pubmed/22676372
http://dx.doi.org/10.1186/1471-2105-13-125
Descripción
Sumario:BACKGROUND: Self-incompatibility (SI) is a biological mechanism to avoid inbreeding in allogamous plants. In grasses, this mechanism is controlled by a two-locus system (S-Z). Calculation of male and female gamete frequencies is complex for tetraploid species. We are not aware of any software available for predicting pollen haplotype frequencies and pollen compatibility in tetraploid species. RESULTS: PollenCALC is a software tool written in C++ programming language that can predict pollen compatibility percentages for polyploid species with a two-locus (S, Z) self-incompatibility system. The program predicts pollen genotypes and frequencies based on defined meiotic parameters for allo- or autotetraploid species with a gametophytic S-Z SI system. These predictions can be used to obtain expected values for for diploid and for (allo- or autotetraploidy SI grasses. CONCLUSION: The information provided by this calculator can be used to predict compatibility of pair-crosses in plant breeding applications, to analyze segregation distortion for S and Z genes, as well as linked markers in mapping populations, hypothesis testing of the number of S and Z alleles in a pair cross, and the underlying genetic model.