Abstract

BackgroundThe genomic architecture of bud phenology and height growth remains poorly known in most forest trees. In non model species, QTL studies have shown limited application because most often QTL data could not be validated from one experiment to another. The aim of our study was to overcome this limitation by basing QTL detection on the construction of genetic maps highly-enriched in gene markers, and by assessing QTLs across pedigrees, years, and environments.ResultsFour saturated individual linkage maps representing two unrelated mapping populations of 260 and 500 clonally replicated progeny were assembled from 471 to 570 markers, including from 283 to 451 gene SNPs obtained using a multiplexed genotyping assay. Thence, a composite linkage map was assembled with 836 gene markers.For individual linkage maps, a total of 33 distinct quantitative trait loci (QTLs) were observed for bud flush, 52 for bud set, and 52 for height growth. For the composite map, the corresponding numbers of QTL clusters were 11, 13, and 10. About 20% of QTLs were replicated between the two mapping populations and nearly 50% revealed spatial and/or temporal stability. Three to four occurrences of overlapping QTLs between characters were noted, indicating regions with potential pleiotropic effects. Moreover, some of the genes involved in the QTLs were also underlined by recent genome scans or expression profile studies.Overall, the proportion of phenotypic variance explained by each QTL ranged from 3.0 to 16.4% for bud flush, from 2.7 to 22.2% for bud set, and from 2.5 to 10.5% for height growth. Up to 70% of the total character variance could be accounted for by QTLs for bud flush or bud set, and up to 59% for height growth.ConclusionsThis study provides a basic understanding of the genomic architecture related to bud flush, bud set, and height growth in a conifer species, and a useful indicator to compare with Angiosperms. It will serve as a basic reference to functional and association genetic studies of adaptation and growth in Picea taxa. The putative QTNs identified will be tested for associations in natural populations, with potential applications in molecular breeding and gene conservation programs. QTLs mapping consistently across years and environments could also be the most important targets for breeding, because they represent genomic regions that may be least affected by G × E interactions.

Highlights

  • The genomic architecture of bud phenology and height growth remains poorly known in most forest trees

  • For genera where a reference genome is already available [1] or for others with large and unsequenced genomes such as for the vast majority of forest tree species, quantitative trait locus (QTL) mapping still represent an attractive approach that can help improve our comprehension of the genomic architecture of adaptive traits [2,3,4]

  • With the expansion of genetic linkage maps with additional genebased SNPs, the present study highlighted the genomic architecture of the conifer white spruce for three adaptive traits by the identification of congruent QTLs underlying bud flush, bud set and height growth across different pedigrees, years, and environments

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Summary

Introduction

The genomic architecture of bud phenology and height growth remains poorly known in most forest trees. QTL studies have shown limited application because most often QTL data could not be validated from one experiment to another. For genera where a reference genome is already available [1] or for others with large and unsequenced genomes such as for the vast majority of forest tree species, quantitative trait locus (QTL) mapping still represent an attractive approach that can help improve our comprehension of the genomic architecture of adaptive traits [2,3,4]. In non-model plant species, there exists a vast body of literature on the genomic architecture of quantitative traits [6,7,8,9]. The comparison of QTLs among studies and species is made difficult due to the large varieties of experimental procedures used to score phenotypic traits. An additional reason is that syntenic QTLs are difficult to identify and validate due to the limited number of orthologous markers commonly positioned among unrelated families or species

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