The use of MAS for raspberry breeding would be beneficial because it would allow early screening of seedlings and reduction in the number of plants needed to be grown to maturity.
Further, in the long term, it would reduce the cost and improve the accuracy in phenotyping traits such as disease resistance. Genomic selection (GS) is a more recently developed method whereby a large number of SNP markers are associated with traits of interest and a breeding value or genetic value is calculated for an individual based on the contribution of each SNP to an individuals phenotype. GS will allow breeders to detect many desirable genes in individuals early on in the life of a plant and recently GS has been applied to apple (Kumar et al. 2012).
Red raspberry is a good candidate for MAS and GS because it is diploid (2n=2x=14) with a relatively small genome (275Mbp), the haploid genome being only twice the size of
Arabidopsis (Graham et al. 2007). The application of molecular techniques to raspberry breeding has been fairly limited; however, some progress has being made toward this.
Graham et al. (2007) has reviewed progress in this area. Graham et al. (2004) created the first published raspberry linkage map on a population derived from ‗Glen Moy‘ × ‗Latham‘ using SSR and AFLP markers and this population has provided extensive opportunities for genetic mapping and QTL analysis for raspberry. QTL analysis was also carried out for three
qualitative plant characters; plant cane spininess, root sucker density and spread and these were located on two of the nine linkage groups identified. Graham et al. (2006) mapped Gene H to linkage group (LG) 2 of the ‗Glen Moy‘ × ‗Latham‘ linkage map. Gene H determines cane pubescence the presence of which has been associated with cane disease resistance specifically, cane Botrytis (Botrytis cinerea), cane blight (Leptosphaeria
coniothyrium) and spur blight (Didymella applanata) (Knight and Keep 1958). Woodhead et al. (2008) mapped a further 25 SSR markers and McCallum et al. (2010) found mapped major structural genes for anthocyanins on the ‗Glen Moy‘ × ‗Latham‘ positioned under QTL
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for fruit colour and anthocyanins. Using a different mapping population, Pattison et al. (2007) created a genetic linkage map and used molecular marker techniques to help determine the inheritance of Phytophthora root rot in raspberry and confirmed resistance was likely to be caused by two loci with dominant alleles.
More recently, using the ‗Glen Moy‘ × ‗Latham‘ mapping population, Paterson et al. (2012) identified QTL associated with raspberry flavour volatiles.
Rubus, belonging to Rosaceae, is thought to likely share common ancestral backgrounds with other genera in this family. Thus within the Rosaceae there may be genomic synteny in terms of gene identification and genomic organisation. Comparative genetic mapping of fruit species within Rosaceae has been carried out between Malus and Prunus (Dirlewanger et al.
2004), Prunus and Fragaria (Vilanova et al. 2008), Malus, Prunus and Fragaria (Illa et al.
2011) and this has led to the proposal of a common ancestor Rosaceae genome consisting of nine chromosomes (Vilanova et al. 2008; Velasco et al. 2010). More recently, Bushakra et al.
(2012) used RosCOS (Rosaceae conserved orthologous set) derived markers to compare the raspberry genome with that of Prunus, Fragaria and Malus and found a high degree of synteny between raspberry and strawberry genomes and supporting the theory that the raspberry genome is also derived from a single ancestor common to Rosaceae.
Recent investigation of the transferability of Fragaria-derived markers to Rubus and Rosa has highlighted the importance of marker source for successful transfer within Rosaceae.
Lewers et al. (2005) found that transferability of GenBank-derived Fragaria expressed sequence tag (EST)-SSR to be 20% in raspberry and similar results were found by Zorrilla-Fontanesi et al. (2011b). Marker transferability has been taken further with research into genetic map comparison between Rubus and Prunus, Malus and Fragaria by Bushakra et al.
(2012). Marker transferability between members of Rosaceae will enhance development of genomic tools amongst these crops and will especially aid raspberry.
Bushakra et al. (2012) used the same Rubus mapping population as in this study and their work was conducted at the same time. The study described here has focussed on developing functional markers and finding QTL associated with sugars and acids content where as
Bushakra‘s work focussed on using the Rubus map for comparative mapping within Rosaceae and QTL associated with anthocyanins.
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Chapter 3
Genetic parameters associated with yield and yield components in red raspberry
Accepted for publication: Acta Horticulturae 946 pp. 37-42.
See Appendix G.1 for manuscript Abstract
Breeding for high yield is a major objective of most small fruit breeding programmes worldwide. High yield and good fruit chemical characters are needed in new commercial process machine-harvested raspberry cultivars. In 2008, a genetic inheritance study was established in order to gain a better understanding of the heritability of traits associated with machine-harvesting and the most important yield components. The study was conducted over two seasons, in Washington State USA, on 1008 genotypes of red raspberry (Rubus idaeus) from a pairwise mating design study which was based on 85 full-sib families derived from 45 parents. Estimates of variance components, heritabilities, and phenotypic and genetic
correlations for yield and yield components were obtained. The highest genetic correlations with total yield were berry weight, cane length and cane diameter and highest expected genetic gain of total yield per breeding cycle was from indirect selection through berry weight.
3.1 Introduction
The New Zealand Institute for Plant & Food Research Limited (PFR) and Northwest Plant Company (NWP) have developed a raspberry breeding programme based in Whatcom County, Washington State, that is focused on developing new machine-harvested cultivars suited to process markets. Key targets of the programme include: high yield, firm fruit that will harvest by machine, high soluble solids content, moderately high acidity, good flavour, improved human health attributes and plant disease resistance. Stephens et al. (2009) outlined some of the difficulties breeders have with breeding for high yield. One of the major
problems breeders face is the time-consuming nature of yield measurements and thus any proxy for yield or quick test would be valuable. Raspberry plant yield can be increased by optimising several key components of yield including cane number, diameter and height, fruit lateral number and length, and fruit size. While all yield components interact with
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environmental influences to produce total yield, from a breeding point of view there are certain components that are likely to be better correlated with yield and are more heritable.
Dale and Daubeny (1985) showed that high yield in raspberries was closely related to high lateral numbers in Abbotsford, BC Canada, and thickness of floricanes in Invergowrie, Scotland. Several studies have shown that raspberry yield is highly positively correlated with fruit size (Dale 1976; Cormack and Woodward 1977; Dale and Daubeny 1985; Stephens et al. 2009) and this is probably the easiest component for which breeders can select. However, other components that contribute to yield may be important as well and could hold the key to major advances in fruit yield in the future. This is especially so where larger fruit size is not necessarily a desirable trait, such as for process markets.
In this paper we report on a study which builds on the work by Stephens et al. (2009) by estimating heritabilities, genetic and phenotypic correlations and expected genetic gains via direct and indirect selection for yield and yield components on red raspberry suited to machine harvest in Washington State, USA.