Potential for marker-assisted selection for forest tree breeding: lessons from 20 years of MAS in crops

Muranty, Hélène; Jorge, Véronique; Bastien, Catherine; Lepoittevin, Camille; Bouffier, Laurent; Sanchez, Léopoldo

doi:10.1007/s11295-014-0790-5

Cited by 76 publications

(47 citation statements)

References 125 publications

(115 reference statements)

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“…LA uses information from recombination events between markers within a studied progeny of known pedigree. This approach has been widely used for forest trees since the early 1990s and has led to the detection of QTLs for several traits of economic interest, mostly in biparental crosses [5–7]. LD makes use of historical recombination events in an unknown pedigree from which the study population was derived.…”

Section: Introductionmentioning

confidence: 99%

Linkage and Association Mapping for Two Major Traits Used in the Maritime Pine Breeding Program: Height Growth and Stem Straightness

et al. 2016

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BackgroundIncreasing our understanding of the genetic architecture of complex traits, through analyses of genotype-phenotype associations and of the genes/polymorphisms accounting for trait variation, is crucial, to improve the integration of molecular markers into forest tree breeding. In this study, two full-sib families and one breeding population of maritime pine were used to identify quantitative trait loci (QTLs) for height growth and stem straightness, through linkage analysis (LA) and linkage disequilibrium (LD) mapping approaches.ResultsThe populations used for LA consisted of two unrelated three-generation full-sib families (n = 197 and n = 477). These populations were assessed for height growth or stem straightness and genotyped for 248 and 217 markers, respectively. The population used for LD mapping consisted of 661 founders of the first and second generations of the breeding program. This population was phenotyped for the same traits and genotyped for 2,498 single-nucleotide polymorphism (SNP) markers corresponding to 1,652 gene loci. The gene-based reference genetic map of maritime pine was used to localize and compare the QTLs detected by the two approaches, for both traits. LA identified three QTLs for stem straightness and two QTLs for height growth. The LD study yielded seven significant associations (P ≤ 0.001): four for stem straightness and three for height growth. No colocalisation was found between QTLs identified by LA and SNPs detected by LD mapping for the same trait.ConclusionsThis study provides the first comparison of LA and LD mapping approaches in maritime pine, highlighting the complementary nature of these two approaches for deciphering the genetic architecture of two mandatory traits of the breeding program.

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Section: Introductionmentioning

confidence: 99%

Linkage and Association Mapping for Two Major Traits Used in the Maritime Pine Breeding Program: Height Growth and Stem Straightness

et al. 2016

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“…This can be achieved by identifying and localizing the genomic regions controlling the variation of quantitative traits (QTLs). Largeeffect QTLs could theoretically be used in marker-assisted breeding schemes, but this approach has not yet been used in forest trees (Muranty et al 2014), mostly because the most relevant traits for forest tree breeding are highly complex and probably controlled by many small-effect QTLs. Furthermore, most of the QTLs detected have large confidence intervals and have not been validated.…”

Section: Genotype-phenotype Associationmentioning

confidence: 99%

“…Despite these parallel developments in breeding and QTL mapping, few breakthrough applications for forest trees using a synergistic combination of these two approaches have been reported. This situation was quantitatively assessed and discussed in a review work by Muranty et al (2014), which focused particularly on markerassisted selection. Indeed, forest trees are among the genetically improved species most likely to benefit from the use of gene-or marker-based information in breeding.…”

Section: Genomics and Breedingmentioning

confidence: 99%

Forest tree genomics: 10 achievements from the past 10 years and future prospects

Plomion

Bastien²,

Bogeat‐Triboulot

et al. 2016

Annals of Forest Science

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strategies in terms of conservation and use, as well as climate changes and associated threats. Genomics will undoubtedly play a major role over the next decade and beyond, not only to further understand the mechanisms underlying adaptation and evolution but also to develop and implement innovative management and policy actions to preserve the adaptability of natural forests and intensively managed plantations.

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“…However, resistance differs among cultivars, which can restrict the application of validated linked markers as a general tool for MAS 21,28 . Therefore, the identification and characterization of brown rust resistance genes in sugarcane have been slow 14 , mainly because selection approaches based on QTL mapping overestimate the effect of strong QTLs, while weak QTLs might not be identified 29,30 . In general, these methodologies have low power to detect rare variants with phenotypic associations 31 .…”

Section: Introductionmentioning

confidence: 99%

Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance

Aono

Costa

Rody

et al. 2020

Preprint

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Sugarcane is an economically important crop, but its genomic complexity has hindered advances in molecular approaches for genetic breeding. New cultivars are released based on the identification of interesting traits, and for sugarcane, brown rust resistance is a desirable characteristic due to the large economic impact of the disease. Although marker-assisted selection for rust resistance has been successful, the genes involved are still unknown, and the associated regions vary among cultivars, thus restricting methodological generalization. We used genotyping by sequencing of full-sib progeny to relate genomic regions with brown rust phenotypes. We established a pipeline to identify reliable SNPs in complex polyploid data, which were used for phenotypic prediction via machine learning. We identified 14,540 SNPs, which led to a mean prediction accuracy of 50% by using different models. We also tested feature selection algorithms to increase predictive accuracy, resulting in a reduced dataset with more explanatory power for rust phenotypes. Using different feature selection techniques, we achieved accuracy of up to 95% with a dataset of 131 SNPs related to brown rust QTL regions and auxiliary genes. Therefore, our novel strategy has the potential to assist studies of the genomic organization of brown rust resistance in sugarcane. 3/154/15 10/15

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Potential for marker-assisted selection for forest tree breeding: lessons from 20 years of MAS in crops

Cited by 76 publications

References 125 publications

Linkage and Association Mapping for Two Major Traits Used in the Maritime Pine Breeding Program: Height Growth and Stem Straightness

Linkage and Association Mapping for Two Major Traits Used in the Maritime Pine Breeding Program: Height Growth and Stem Straightness

Forest tree genomics: 10 achievements from the past 10 years and future prospects

Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance

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