QTL mapping and breeding value estimation through pedigree-based analysis of fruit size and weight in four diverse peach breeding programs

Fresnedo-Ramírez, Jonathan; Frett, Terrence J.; Sandefur, Paul; Bink, M.C.A.M.; Weg, Eric van de

doi:10.1007/s11295-016-0985-z

Cited by 46 publications

(33 citation statements)

References 72 publications

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“…The Bayesian QTL mapping approach implemented by FlexQTL ™ (Bink et al, 2008 andBink et al, 2014) allows analyzing multiple pedigreelinked progenies at the same time; reducing the limitations derived from QTL analyses using single populations. This approach has been successfully used in recent years for QTL analyses of different traits in Rosaceae species, such as sweet cherry (Rosyara et al, 2013), apple (Bink et al, 2014;Guan et al, 2015;Allard et al, 2016;Di Guardo et al, 2017;Howard et al, 2018), peach (Fresnedo-Ramírez et al, 2015;Fresnedo-Ramírez et al, 2016;Hernández Mora et al, 2017), and strawberry (Roach et al, 2016;Mangandi et al, 2017;Anciro et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Genetic Dissection of Bloom Time in Low Chilling Sweet Cherry (Prunus avium L.) Using a Multi-Family QTL Approach

et al. 2020

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Bloom time in sweet cherry (Prunus avium L.) is a highly heritable trait that varies between genotypes and depends on the environmental conditions. Bud-break occurs after chill and heat requirements of each genotype are fulfilled, and dormancy is released. Bloom time is a critical trait for fruit production as matching cultivar adaptation to the growing area is essential for adequate fruit set. Additionally, low chilling cultivars are of interest to extend sweet cherry production to warmer regions, and for the crop adaptation to increasing winter and spring temperatures. The aim of this work is to investigate the genetic control of this trait by analyzing multiple families derived from the low chilling and extra-early flowering local Spanish cultivar 'Cristobalina' and other cultivars with higher chilling requirements and medium to late bloom times. Bloom time evaluation in six related sweet cherry populations confirmed a high heritability of this trait, and skewed distribution toward late flowering, revealing possible dominance of the late bloom alleles. SNP genotyping of the six populations (n = 406) resulted in a consensus map of 1269 SNPs. Quantitative trait loci (QTL) analysis using the Bayesian approach implemented by FlexQTL™ software revealed two major QTLs on linkage groups 1 and 2 (qP-BT1.1m and qP-BT2.1m) that explained 47.6% of the phenotypic variation. The QTL on linkage group 1 was mapped to a 0.26 Mbp region that overlaps with the DORMANCY ASSOCIATED MADS-BOX (DAM) genes. This finding is consistent with peach results that indicate that these genes are major determinants of chilling requirement in Prunus. Haplotype analysis of the linkage group 1 and 2 QTL regions showed that 'Cristobalina' was the only cultivar tested that contributed early bloom time alleles for these two QTLs. This work contributes to knowledge of the genetic control of chilling requirement and bloom date and will enable marker-assisted selection for low chilling in sweet cherry breeding programs.

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Section: Introductionmentioning

confidence: 99%

Genetic Dissection of Bloom Time in Low Chilling Sweet Cherry (Prunus avium L.) Using a Multi-Family QTL Approach

et al. 2020

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“…The software package FlexQTL™ utilizes a Bayesian pedigree-based analyses (PBA) approach for QTL discovery and characterization via the software Pedimap (Voorrips et al 2012 ) and Visual FlexQTL™ (van de Weg et al 2004 , 2015 ) which support the graphical representation of FlexQTL™ outputs (van de Weg et al 2004 ). Loci for economically important traits have been characterized using this software in fruit crops including sweet cherry (Rosyara et al 2013 ; Cai et al 2017 ), peach (Fresnedo-Ramirez et al 2015 , 2016 ; Hernández-Mora et al 2017a , b ) and apple (Allard et al 2016 ; Di Guardo et al 2017 ; Durand et al 2017 ; Howard et al 2017 ; van de Weg et al 2017 ).…”

Section: Introductionmentioning

confidence: 99%

FaRCa1: a major subgenome-specific locus conferring resistance to Colletotrichum acutatum in strawberry

et al. 2018

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Optimal strategies for genetic improvement in crops depend on accurate assessments of the genetic architecture of traits. The overall objective of the present study was to determine the genetic architecture of anthracnose fruit rot (AFR) resistance caused by the fungus Colletotrichum acutatum in the University of Florida strawberry ( Fragaria × ananassa ) breeding germplasm. In 2016–2017, 33 full-sib families resulting from crosses between parents with varying levels of AFR resistance were tested. In 2017–2018, six full-sib families resulting from putative heterozygous resistant parents and homozygous susceptible parents were tested. Additionally, a validation population consisting of 77 advanced selections and ten cultivars was tested in the second season. Inoculation was performed using a mixture of three local isolates of the C. acutatum species complex. Phenotypes were scored weekly, and genotyping was performed using the IStraw35 Affymetrix Axiom ® SNP array. A pedigree-based QTL analysis was performed using FlexQTL™ software. A major resistance locus, which we name FaRCa1 , was detected in both seasons with a peak located at 55–56 cM on LG 6B and explaining at least 50% of the phenotypic variation across trials and seasons. The resistant allele exhibited partial dominance in all trials. The FaRCa1 locus is distinct from the previously discovered Rca2 locus, which mapped to LG 7B. While Rca2 is effective against European isolates from pathogenicity group 2, FaRCa1 appears to confer resistance to isolates of pathogenicity group 1. Electronic supplementary material The online version of this article (10.1007/s00122-018-3263-7) contains supplementary material, which is available to authorized users.

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“…To assign genetic positions to unmapped markers, the common approach was to use a genome-wide mean as a conversion factor [ 35 ]. In order to overcome the problem of using the static conversion factor, Fresnedo et al [ 30 ] developed a consensus RosBREED [ 36 ] linkage map (RC 1 ) for peach predicting genetic distances by incorporating the physical and genetic positions of 68 markers from the Prunus bin map [ 37 ]. However, this map was developed by calculating genetic positions using polynomial equations, not by merging individual peach linkage maps.…”

Section: Introductionmentioning

confidence: 99%

High-density multi-population consensus genetic linkage map for peach

et al. 2018

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Highly saturated genetic linkage maps are extremely helpful to breeders and are an essential prerequisite for many biological applications such as the identification of marker-trait associations, mapping quantitative trait loci (QTL), candidate gene identification, development of molecular markers for marker-assisted selection (MAS) and comparative genetic studies. Several high-density genetic maps, constructed using the 9K SNP peach array, are available for peach. However, each of these maps is based on a single mapping population and has limited use for QTL discovery and comparative studies. A consensus genetic linkage map developed from multiple populations provides not only a higher marker density and a greater genome coverage when compared to the individual maps, but also serves as a valuable tool for estimating genetic positions of unmapped markers. In this study, a previously developed linkage map from the cross between two peach cultivars ‘Zin Dai’ and ‘Crimson Lady’ (ZC2) was improved by genotyping additional progenies. In addition, a peach consensus map was developed based on the combination of the improved ZC2 genetic linkage map with three existing high-density genetic maps of peach and a reference map of Prunus. A total of 1,476 SNPs representing 351 unique marker positions were mapped across eight linkage groups on the ZC2 genetic map. The ZC2 linkage map spans 483.3 cM with an average distance between markers of 1.38 cM/marker. The MergeMap and LPmerge tools were used for the construction of a consensus map based on markers shared across five genetic linkage maps. The consensus linkage map contains a total of 3,092 molecular markers, consisting of 2,975 SNPs, 116 SSRs and 1 morphological marker associated with slow ripening in peach (SR). The consensus map provides valuable information on marker order and genetic position for QTL identification in peach and other genetic studies within Prunus and Rosaceae.

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QTL mapping and breeding value estimation through pedigree-based analysis of fruit size and weight in four diverse peach breeding programs

Cited by 46 publications

References 72 publications

Genetic Dissection of Bloom Time in Low Chilling Sweet Cherry (Prunus avium L.) Using a Multi-Family QTL Approach

Genetic Dissection of Bloom Time in Low Chilling Sweet Cherry (Prunus avium L.) Using a Multi-Family QTL Approach

FaRCa1: a major subgenome-specific locus conferring resistance to Colletotrichum acutatum in strawberry

High-density multi-population consensus genetic linkage map for peach

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