Articles

POMEGRANATE BREEDING: UTILIZATION OF MOLECULAR AND GENETIC DATA FOR IMPROVEMENT OF FRUIT QUALITY AND ADAPTATION TO DIFFERENT CLIMATIC CONDITIONS

Article number
1089_31
Pages
249 – 252
Language
English
Abstract
Pomegranate is known as a most valuable plant with a high range of beneficial health effects.
In recent years the increasing demand for pomegranate fruit worldwide encouraged its planting in many countries which differ in their climatic conditions and agricultural practices.
Although the pomegranate plant can grow in relatively variable environments, production of high quality fruit in the required color, size, taste and time of ripening is of a challenge.
In order to facilitate breeding efficiency for better cultivars we utilized the highly divergent pomegranate germplasm collected from different parts of the world to establish a genetic and molecular infrastructure.
This includes segregating populations for various traits, several thousand single nucleotide polymorphism (SNP) markers, transcriptome data from four cultivars, SNP chip, expression chip, a genetic map and fruit and tree phenotypic and metabolic data.
The availability of these data and tools enabled us to associate several important traits such as fruit peel and aril color, anthocyanin content, seed hardness, total soluble solids, acidity, total polyphenols, plant height and dormancy control with SNP markers.
For some traits such as peel color components, the genetic markers are estimated to be within a range of 1 cM. The data collected are being used in several directions such as marker assisted selection (MAS) for expanding the production season.
The long range goal of our breeding program is aimed towards production of elite cultivars suitable to grow and produce high quality fruit in arid, semi-arid and moderate weather regions.

Publication
Authors
R. Harel-Beja, I. Bar-Ya’akov, K. Hatib, T. Trainin, Z. Ben-Simhon, D. Holland, R. Eshed, M. Sharabi, M. Rubinstein, R. Ophir, A. Sherman
Keywords
Punica granatum L., germplasm collection, segregating populations, transcriptome, SNP markers, genetic map
Full text
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