Prospects of Association Mapping in Perennial Horticultural Crops

Rikkerink, Erik H. A.; Oraguzie, Nnadozie; Gardiner, Susan E.

doi:10.1007/978-0-387-36011-9_11

Cited by 28 publications

(19 citation statements)

References 31 publications

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“…Unlike self-pollinated annuals, Linkage Disequilibrium (LD) in outcrossing plants rapidly breaks down, and availability of fewer molecular markers are not sufficient to detect genetic loci controlling agronomic traits of economic interest. As the apple is cross-pollinated and is highly heterozygous, large numbers of robust molecular markers, such as SNPs, are necessary to investigate marker-trait associations in unrelated germplasm, as well as study LD patterns in genes of interest (Rikkerink et al, 2007;Zhu et al, 2008).…”

Section: Discussionmentioning

confidence: 99%

A high-throughput apple SNP genotyping platform using the GoldenGate™ assay

Khan

Han

Zhao

et al. 2012

Gene

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Section: Discussionmentioning

confidence: 99%

A high-throughput apple SNP genotyping platform using the GoldenGate™ assay

Khan

Han

Zhao

et al. 2012

Gene

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“…Association mapping has been suggested to be used in perennial horticultural plants because of their long juvenile period, high costs of breeding programs and polyploidy (Rikkerink et al, 2007). Although there is no report on the association mapping of agronomic traits in olives, studies on the development of olive core collections suitable for association mapping have been recently reported by several groups (Belaj et al, 2012;El Bakkali et al, 2013).…”

Section: Association Of Ssr Markers With Fatty Acid Content Of Olive Oilmentioning

confidence: 99%

Association of SSR markers with contents of fatty acids in olive oil and genetic diversity analysis of an olive core collection

İpek

Şeker

et al. 2015

Genet. Mol. Res.

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ABSTRACT. The purpose of this research was to characterize an olive core collection using some agronomic characters and simple sequence repeat (SSR) markers and to determine SSR markers associated with the content of fatty acids in olive oil. SSR marker analysis demonstrated the presence of a high amount of genetic variation between the olive cultivars analyzed. A UPGMA dendrogram demonstrated that olive cultivars did not cluster on the basis of their geographic origin. Fatty acid components of olive oil in these cultivars were determined. The results also showed that there was a great amount of variation between the olive cultivars in terms of fatty acid composition. For example, oleic acid content ranged from 57.76 to 76.9% with standard deviation of 5.10%. Significant correlations between fatty acids of olive oil were observed. For instance, a very high negative correlation (-0.812) between oleic and linoleic acids was detected. A structured association analysis between the content of fatty acids in olive oil and SSR markers was performed. STRUCTURE analysis assigned olive cultivars to two M. Ipek et al. 2242©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 14 (1): 2241-2252 (2015) gene pools (K = 2). Assignment of olive cultivars to these gene pools was not based on geographical origin. Association between fatty acid traits and SSR markers was evaluated using the general linear model of TASSEL. Significant associations were determined between five SSR markers and stearic, oleic, linoleic, and linolenic acids of olive oil. Very high associations (P < 0.001) between ssrOeUA-DCA14 and stearic acid and between GAPU71B and oleic acid indicated that these markers could be used for marker-assisted selection in olive.

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“…Association mapping in the form of GWAS offers a more fine-scale approach than QTLs to identify smaller, individual markers in LD with target traits. This can overcome the detrimental effects of genetic drag as the marker intervals are shorter, as well as accounting for population structure (Khan and Korban 2012;Brachi et al 2011;Isik 2014;Myles et al 2009;Rikkerink et al 2007). The incorporation of population structure and kinship information can reduce a major problem of false associations between markers and phenotypes in a GWAS (Khan and Korban 2012;Brachi et al 2011;Iwata et al 2016).…”

Section: Using Genomic Information To Accelerate Genetic Gains In Trementioning

confidence: 99%

“…However, yield and other traits still need to be assessed over several locations before cultivars are recommended (Acquaah 2012). Selection of potential superior cultivars in the juvenile stage can also drastically reduce capital and maintenance costs (Rikkerink et al 2007;Luby and Shaw 2000).…”

Section: Yield Prediction Using Genomic Selectionmentioning

confidence: 99%

“…Accurate phenotyping is critical for GS; if the accuracy of phenotyping is poor, many more individuals will be needed in the reference population (Desta and Ortiz 2014). Accurate phenotyping requires multiple well-characterised environments, stringent selection criteria and large training populations (Resende et al 2012;Xu and Crouch 2008;Desta and Ortiz 2014;Rikkerink et al 2007). For many traits such as yield, data need to be collected across multiple years and sites, and is costly and time consuming (Resende et al 2012;Bernardo 2008;Xu et al 2012;Isik 2014;Stephens et al 2009).…”

Section: Yield Prediction Using Genomic Selectionmentioning

confidence: 99%

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Selection strategies to improve yield in macadamia using component traits and genomics

O’Connor¹

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Macadamias (Macadamia integrifolia, M. tetraphylla, and their hybrids) are native to the east coast of Australia, and are grown commercially around the world for their high quality edible nut kernel. Breeding new cultivars for high nut yield is a lengthy and laborious process that can take over two decades. Evaluations are time-consuming due to the long juvenile period of four or more years, and the low correlation between young and mature tree yield means that at least eight years of evaluations are required. Furthermore, yield has low heritability, and the large tree size necessitates low field planting density, and thus increases land use and evaluation costs. It is hypothesised that genetic gain for yield may be increased, compared to traditional breeding approaches, through the use of strategies including (i) indirect selection using yield component traits, (ii) marker-assisted selection and (iii) genomic selection. This thesis employed an experimental population of 295 seedling progeny and their 29 parents, at four sites across southeast Queensland, that were genotyped for 4,113 SNPs and 16,171 silicoDArT markers detected using Diversity Arrays Technology (DArT) methods. Population structure, genetic diversity and linkage disequilibrium (LD) between SNP markers was quantified to inform subsequent genomics analysis. LD decay was initially rapid at short distances (r 2 = 0.124 for SNPs within 1 kb of each other), but low level LD persisted for long distances. The seedling population was relatively genetically diverse (HE = 0.255), and very similar in diversity to that of the 29 parents (0.250). Furthermore, progeny with M. integrifolia x M. tetraphylla ancestry were more genetically diverse (HE = 0.278) than M. integrifolia seedlings (HE = 0.189). Progeny were moderately differentiated and clustered into three distinct groups, which represented M. integrifolia germplasm and two hybrid groups. Flowering and nut characteristics, tree growth and yield were measured on each tree. Estimations of trait heritability and genetic correlations between each component trait and yield were used to calculate selection efficiency of indirectly selecting for yield using component traits. Kernel recovery, an economically important trait, had high heritability (h 2 = 0.76) but was negatively genetically correlated with yield (rg =-0.27). Trunk circumference correlated strongly with yield (rg = 0.72) and was moderately heritable (h 2 = 0.44); however, a breeding aim is to reduce tree size without compromising yield. No component traits were appropriate or effective for indirectly selecting for high yield.

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Prospects of Association Mapping in Perennial Horticultural Crops

Cited by 28 publications

References 31 publications

A high-throughput apple SNP genotyping platform using the GoldenGate™ assay

A high-throughput apple SNP genotyping platform using the GoldenGate™ assay

Association of SSR markers with contents of fatty acids in olive oil and genetic diversity analysis of an olive core collection

Selection strategies to improve yield in macadamia using component traits and genomics

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