Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Québec, Québec, G1V 4C7, Canada.
BMC Genomics. 2011 Mar 10;12:145. doi: 10.1186/1471-2164-12-145.
The 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.
Four 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.
This 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.
在大多数树种中,芽物候和高度生长的基因组结构仍然知之甚少。在非模式物种中,由于通常无法从一个实验验证到另一个实验,因此 QTL 研究的应用受到限制。我们研究的目的是通过基于高度富集基因标记的遗传图谱的构建来克服这一限制,并通过跨系谱、年份和环境评估 QTL 来实现这一目标。
从 471 到 570 个标记中组装了 4 个饱和个体连锁图谱,代表了 260 个和 500 个无性繁殖后代的两个不相关的作图群体,其中包括使用多重基因分型测定法获得的 283 到 451 个基因 SNPs。然后,用 836 个基因标记组装了一个复合连锁图谱。对于个体连锁图谱,总共观察到 33 个不同的芽萌动、52 个芽休眠和 52 个高度生长的数量性状位点 (QTL)。对于复合图谱,相应的 QTL 簇数分别为 11、13 和 10。大约 20%的 QTL 在两个作图群体之间得到了复制,近 50%的 QTL 表现出空间和/或时间稳定性。在不同性状之间注意到了 3 到 4 个重叠的 QTL 事件,表明存在潜在的多效性效应的区域。此外,一些参与 QTL 的基因也被最近的基因组扫描或表达谱研究所强调。总的来说,每个 QTL 解释的表型方差比例从芽萌动的 3.0%到 16.4%,从芽休眠的 2.7%到 22.2%,从高度生长的 2.5%到 10.5%。芽萌动或芽休眠的 QTL 可以解释高达 70%的总性状方差,而高度生长的 QTL 可以解释高达 59%的总性状方差。
本研究为针叶树种芽萌动、芽休眠和高度生长的基因组结构提供了基本认识,并为与被子植物进行比较提供了有用的指标。它将作为研究适应和生长的功能和关联遗传的基本参考。鉴定的潜在 QTN 将在自然种群中进行关联测试,在分子育种和基因保护计划中具有潜在的应用。在年份和环境中一致映射的 QTL 也可能是最重要的育种目标,因为它们代表基因组区域可能受 G × E 相互作用影响最小。