Betty Pelgas

Enhancing genetic mapping of complex genomes through the design of highly-multiplexed SNP arrays: application to the large and unsequenced genomes of white spruce and black spruce

BackgroundTo explore the potential value of high-throughput genotyping assays in the analysis of large and complex genomes, we designed two highly multiplexed Illumina bead arrays using the GoldenGate SNP assay for gene mapping in white spruce (Picea glauca [Moench] Voss) and black spruce (Picea mariana [Mill.] B.S.P.).ResultsEach array included 768 SNPs, identified by resequencing genomic DNA from parents of each mapping population. For white spruce and black spruce, respectively, 69.2% and 77.1% of genotyped SNPs had valid GoldenGate assay scores and segregated in the mapping populations. For each of these successful SNPs, on average, valid genotyping scores were obtained for over 99% of progeny. SNP data were integrated to pre-existing ALFP, ESTP, and SSR markers to construct two individual linkage maps and a composite map for white spruce and black spruce genomes. The white spruce composite map contained 821 markers including 348 gene loci. Also, 835 markers including 328 gene loci were positioned on the black spruce composite map. In total, 215 anchor markers (mostly gene markers) were shared between the two species. Considering lineage divergence at least 10 Myr ago between the two spruces, interspecific comparison of homoeologous linkage groups revealed remarkable synteny and marker colinearity.ConclusionThe design of customized highly multiplexed Illumina SNP arrays appears as an efficient procedure to enhance the mapping of expressed genes and make linkage maps more informative and powerful in such species with poorly known genomes. This genotyping approach will open new avenues for co-localizing candidate genes and QTLs, partial genome sequencing, and comparative mapping across conifers.

QTL mapping in white spruce: gene maps and genomic regions underlying adaptive traits across pedigrees, years and environments

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.

A spruce gene map infers ancient plant genome reshuffling and subsequent slow evolution in the gymnosperm lineage leading to extant conifers

BackgroundSeed plants are composed of angiosperms and gymnosperms, which diverged from each other around 300 million years ago. While much light has been shed on the mechanisms and rate of genome evolution in flowering plants, such knowledge remains conspicuously meagre for the gymnosperms. Conifers are key representatives of gymnosperms and the sheer size of their genomes represents a significant challenge for characterization, sequencing and assembling.ResultsTo gain insight into the macro-organisation and long-term evolution of the conifer genome, we developed a genetic map involving 1,801 spruce genes. We designed a statistical approach based on kernel density estimation to analyse gene density and identified seven gene-rich isochors. Groups of co-localizing genes were also found that were transcriptionally co-regulated, indicative of functional clusters. Phylogenetic analyses of 157 gene families for which at least two duplicates were mapped on the spruce genome indicated that ancient gene duplicates shared by angiosperms and gymnosperms outnumbered conifer-specific duplicates by a ratio of eight to one. Ancient duplicates were much more translocated within and among spruce chromosomes than conifer-specific duplicates, which were mostly organised in tandem arrays. Both high synteny and collinearity were also observed between the genomes of spruce and pine, two conifers that diverged more than 100 million years ago.ConclusionsTaken together, these results indicate that much genomic evolution has occurred in the seed plant lineage before the split between gymnosperms and angiosperms, and that the pace of evolution of the genome macro-structure has been much slower in the gymnosperm lineage leading to extent conifers than that seen for the same period of time in flowering plants. This trend is largely congruent with the contrasted rates of diversification and morphological evolution observed between these two groups of seed plants.

Development of high-density SNP genotyping arrays for white spruce (Picea glauca) and transferability to subtropical and nordic congeners.

High‐density SNP genotyping arrays can be designed for any species given sufficient sequence information of high quality. Two high‐density SNP arrays relying on the Infinium iSelect technology (Illumina) were designed for use in the conifer white spruce (Picea glauca). One array contained 7338 segregating SNPs representative of 2814 genes of various molecular functional classes for main uses in genetic association and population genetics studies. The other one contained 9559 segregating SNPs representative of 9543 genes for main uses in population genetics, linkage mapping of the genome and genomic prediction. The SNPs assayed were discovered from various sources of gene resequencing data. SNPs predicted from high‐quality sequences derived from genomic DNA reached a genotyping success rate of 64.7%. Nonsingleton in silico SNPs (i.e. a sequence polymorphism present in at least two reads) predicted from expressed sequenced tags obtained with the Roche 454 technology and Illumina GAII analyser resulted in a similar genotyping success rate of 71.6% when the deepest alignment was used and the most favourable SNP probe per gene was selected. A variable proportion of these SNPs was shared by other nordic and subtropical spruce species from North America and Europe. The number of shared SNPs was inversely proportional to phylogenetic divergence and standing genetic variation in the recipient species, but positively related to allele frequency in P. glauca natural populations. These validated SNP resources should open up new avenues for population genetics and comparative genetic mapping at a genomic scale in spruce species.

The genomic architecture and association genetics of adaptive characters using a candidate SNP approach in boreal black spruce

BackgroundThe genomic architecture of adaptive traits remains poorly understood in non-model plants. Various approaches can be used to bridge this gap, including the mapping of quantitative trait loci (QTL) in pedigrees, and genetic association studies in non-structured populations. Here we present results on the genomic architecture of adaptive traits in black spruce, which is a widely distributed conifer of the North American boreal forest. As an alternative to the usual candidate gene approach, a candidate SNP approach was developed for association testing.ResultsA genetic map containing 231 gene loci was used to identify QTL that were related to budset timing and to tree height assessed over multiple years and sites. Twenty-two unique genomic regions were identified, including 20 that were related to budset timing and 6 that were related to tree height. From results of outlier detection and bulk segregant analysis for adaptive traits using DNA pool sequencing of 434 genes, 52 candidate SNPs were identified and subsequently tested in genetic association studies for budset timing and tree height assessed over multiple years and sites. A total of 34 (65%) SNPs were significantly associated with budset timing, or tree height, or both. Although the percentages of explained variance (PVE) by individual SNPs were small, several significant SNPs were shared between sites and among years.ConclusionsThe sharing of genomic regions and significant SNPs between budset timing and tree height indicates pleiotropic effects. Significant QTLs and SNPs differed quite greatly among years, suggesting that different sets of genes for the same characters are involved at different stages in the tree’s life history. The functional diversity of genes carrying significant SNPs and low observed PVE further indicated that a large number of polymorphisms are involved in adaptive genetic variation. Accordingly, for undomesticated species such as black spruce with natural populations of large effective size and low linkage disequilibrium, efficient marker systems that are predictive of adaptation should require the survey of large numbers of SNPs. Candidate SNP approaches like the one developed in the present study could contribute to reducing these numbers.

Efficient screening for expressed sequence tag polymorphisms (ESTPs) by DNA pool sequencing and denaturing gradient gel electrophoresis (DGGE) in spruces

There is an urgent need to accelerate the development of informative codominant markers of coding regions such as ESTPs (expressed sequence tag polymorphisms) to estimate map synteny within and among taxa. A set of primer pairs for 207 ESTs or cDNAs from Picea and Pinus taxa was screened on three distantly-related taxa in the genus Picea, P. mariana (Mill.) B.S.P., P. glauca (Moench) Voss and P. abies (L.) Karst. Of these, 118 (57%) resulted in positive amplification of single-locus gene products in the first two species. To detect polymorphism, these 118 markers were further screened on a panel of 10 pedigree parents for each of P. mariana and P. glauca, either by agarose gel electrophoresis (AGE) or by parallel denaturing gradient gel electrophoresis (DGGE) with standard conditions of 15-45% urea-formamide. Of these, 87 and 74 were found polymorphic in P. mariana and P. glauca, respectively, and 65 were polymorphic in both species. DNA pool sequencing has been explored as a possible strategy to increase economically the detection throughput of SNPs and small indels, and to characterize the types of DNA polymorphism detected by DGGE. Different DNA samples of known sequences were pooled in different ratio mixtures before and after PCR amplifications to determine their minimum relative abundance for detection of DNA polymorphisms by sequencing. For detection of a polymorphism in the DNA pools, the minimum level of relative abundance was 10%. Pooling DNA samples before or after PCR amplification had no effect on the detection of polymorphism by sequencing. For each species panel, the DNAs were pooled and then amplified and sequenced for the 118 primer pairs. With this strategy, the number of ESTPs increased to 107 in P. mariana and 106 in P. glauca, and the number of ESTPs shared by both species increased to 99. About half of the ESTP markers displayed both SNP and indel polymorphisms while the other half displayed only SNPs. Most of the additional ESTPs were amenable to detection by DGGE or CAPS (Cleaved Amplified Polymorphic Sequence) for mapping purposes.

A roadmap of apical bud formation in white spruce identifies potential regulators of time to bud set

Background Bud development is an adaptation that temperate forest trees have acquired to survive inclement winter conditions and resume growth the following spring. Bud development is a complex physiological and developmental process comprising bud formation, cold and desiccation tolerance development, and dormancy acquisition [1]. Because bud formation is accompanied by growth cessation, the timing of bud formation represents a trade-off between acquisition of winter hardiness and duration of active growth [2]. This is particularly true for determinate species such as white spruce (Picea glauca [Moench] Voss), where preformed stem units contained within the apical bud constitute most of next season’s growth. Timing of bud set in white spruce shows genetic variation [3]. Our goal is to identify genes that exert genetic control over time to bud set in white spruce. As first steps towards that goal, we have conducted microarray gene expression profiling of shoot tips during the transition from active growth to dormancy in white spruce, and identified candidate regulators of bud formation by comparing these differentially expressed (DE) genes to results obtained from QTL analyses of time to bud set conducted using the same genes as molecular markers.