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Dorant, Yann; Benestan, Laura; Rougemont, Quentin; Normandeau, Eric; Boyle, Brian; Rochette, Rémy; Bernatchez, Louis 2019-05-29 Unraveling genetic population structure is challenging in species potentially characterized by large population size and high dispersal rates, often resulting in weak genetic differentiation. Genotyping a large number of samples can improve the detection of subtle genetic structure, but this may substantially increase sequencing cost and downstream bioinformatics computational time. To overcome this challenge, alternative, cost‐effective sequencing approaches, namely Pool‐seq and Rapture, have been developed. We empirically measured the power of resolution and congruence of these two methods in documenting weak population structure in nonmodel species with high gene flow comparatively to a conventional genotyping‐by‐sequencing (GBS) approach. For this, we used the American lobster (Homarus americanus) as a case study. First, we found that GBS, Rapture, and Pool‐seq approaches gave similar allele frequency estimates (i.e., correlation coefficient over 0.90) and all three revealed the same weak pattern of population structure. Yet, Pool‐seq data showed FST estimates three to five times higher than GBS and Rapture, while the latter two methods returned similar FST estimates, indicating that individual‐based approaches provided more congruent results than Pool‐seq. We conclude that despite higher costs, GBS and Rapture are more convenient approaches to use in the case of species exhibiting very weak differentiation. While both GBS and Rapture approaches provided similar results with regard to estimates of population genetic parameters, GBS remains more cost‐effective in project involving a relatively small numbers of genotyped individuals (e.g., <1,000). Overall, this study illustrates the complexity of estimating genetic differentiation and other summary statistics in complex biological systems characterized by large population size and migration rates.
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Bousquet, Jean; Pavy, Nathalie; Gagnon, France; Deschênes, Astrid; Boyle, Brian; Beaulieu, Jean 2015-09-17 Picea mariana is a widely distributed boreal conifer across Canada and the subject of advanced breeding programs for which population genomics and genomic selection approaches are being developed. Targeted sequencing was achieved after capturing P. mariana exome with probes designed from the sequenced transcriptome of Picea glauca, a distant relative. A high capture efficiency of 75.9% was reached although spruce has a complex and large genome including gene sequences interspersed by some long introns. The results confirmed the relevance of using probes from congeneric species to perform successfully interspecific exome capture in the genus Picea. A bioinformatics pipeline was developed including stringent criteria that helped detect a set of 97 075 highly reliable in silico SNPs. These SNPs were distributed across 14 909 genes. Part of an Infinium iSelect array was used to estimate the rate of true positives by validating 4267 of the predicted in silico SNPs by genotyping trees from P. mariana populations. The true positive rate was 96.2%, for in silico SNPs compared to a genotyping success rate of 96.7% for a set 1115 P. mariana control SNPs recycled from previous genotyping arrays. These results indicate the high success rate of the genotyping array and the relevance of the selection criteria used to delineate the new P. mariana in silico SNP resource. Furthermore, in silico SNPs were generally of medium to high frequency in natural populations, thus providing high informative value for future population genomics applications.
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Tumas, Hayley; Ilska, Joanna J.; Gérardi, Sebastien; Laroche, Jerome; A'Hara, Stuart; Boyle, Brian; Janes, Mateja; McLean, Paul; Lopez, Gustavo; Lee, Steve J.; Cottrell, Joan; Gorjanc, Gregor; Bousquet, Jean; Wolliams, John A.; Mackay, John J. 2024-01-19 <p class="paragraph" style="line-height:150%;vertical-align:baseline;"><span lang="EN-US" style="font-size:11.0pt;line-height:150%;font-family:'Calibri' , sans-serif;">In species with large and complex genomes such as conifers, dense linkage maps are a useful for supporting genome assembly and laying the genomic groundwork at the structural, populational and functional levels. However, most of the 600+ extant conifer species still lack extensive genotyping resources, which hampers the development of high-density linkage maps. In this study, </span><span class="normaltextrun"><span lang="EN-GB" style="font-size:11.0pt;line-height:150%;font-family:'Calibri' , sans-serif;">we developed a linkage map relying on 21,570 SNP makers in </span></span><span lang="EN-US" style="font-size:11.0pt;line-height:150%;font-family:'Calibri' , sans-serif;">Sitka spruce (<em>Picea sitchensis</em> [Bong.] Carr.)</span><span class="normaltextrun"><em><span lang="EN-GB" style="font-size:11.0pt;line-height:150%;font-family:'Calibri' , sans-serif;">, </span></em></span><span class="normaltextrun"><span lang="EN-US" style="font-size:11.0pt;line-height:150%;font-family:'Calibri' , sans-serif;">a long-lived conifer from western North America that is widely planted for productive forestry in the British Isles. </span></span><span lang="EN-US" style="font-size:11.0pt;line-height:150%;font-family:'Calibri' , sans-serif;">We used a single-step mapping approach to efficiently combine RAD-Seq and genotyping array SNP data for 528 individuals from two full-sib families. As expected for spruce taxa, the saturated map contained 12 linkages groups with a total length of 2,142 cM. The positioning of 5,414 unique gene coding sequences allowed us to compare our map with that of other Pinaceae species, which provided evidence for high levels of synteny and gene order conservation in this family. We then developed an integrated map for <em>P. sitchensis</em> and <em>P. glauca</em> based on 27,052 makers and 11,609 gene sequences. Altogether, these two linkage maps, the accompanying catalog of 286,159 SNPs and the genotyping chip developed herein opens new perspectives for a variety of fundamental and more applied research objectives, such as for the improvement of spruce genome assemblies, or for marker-assisted sustainable management of genetic resources in Sitka spruce and related species.</span></p>
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Picq, Sandrine; Keena, Melody; Havill, Nathan; Stewart, Don; Pouliot, Esther; Boyle, Brian; Levesque, Roger C.; Hamelin, Richard C.; Cusson, Michel 2017-09-25 Forest invasive alien species are a major threat to ecosystem stability and can have enormous economic and social impacts. For this reason, preventing the introduction of Asian gypsy moths (AGM; Lymantria dispar asiatica and L. d. japonica) into North America has been identified as a top priority by North American authorities. The AGM is an important defoliator of a wide variety of hardwood and coniferous trees, displaying a much broader host range and an enhanced dispersal ability relative to the already established European gypsy moth (L. d. dispar). Although molecular assays have been developed to help distinguish gypsy moth subspecies, these tools are not adequate for tracing the geographic origins of AGM samples intercepted on foreign vessels. Yet, this type of information would be very useful in characterizing introduction pathways and would help North American regulatory authorities in preventing introductions. The present proof-of-concept study assessed the potential of single nucleotide polymorphism (SNP) markers, obtained through genotyping-by-sequencing (GBS), to identify the geographic origins of gypsy moth samples. The approach was applied to eight laboratory-reared gypsy moth populations, whose original stocks came from locations distributed over the entire range of L. dispar, comprising representatives of the three recognized subspecies. The various analyses we performed showed strong differentiation among populations (Fst ≥ 0.237), enabling clear distinction of subspecies and geographic variants, while revealing introgression near the geographic boundaries between subspecies. This strong population structure resulted in 100% assignment success of moths to their original population when 2327 SNPs were used. Although the SNP panels we developed are not immediately applicable to contemporary, natural populations because of distorted allele frequencies in the laboratory-reared populations we used, our results attest to the potential of genome-wide SNP markers as a tool to identify the geographic origins of intercepted gypsy moth samples.
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Gérardi, Sébastien; Laoué, Justine; Depardieu, Claire; Lamothe, Manuel; Bomal, Claude; Azaiez, Aïda; Gros-Louis, Marie-Claude; Laroche, Jerôme; Boyle, Brian; Hammerbacher, Almuth; Isabel, Nathalie; Bousquet, Jean 2021-05-13 <p>Conifer forests worldwide are becoming increasingly vulnerable to the effects of climate change. Although the production of phenolic compounds (PCs) has been shown to be modulated by biotic and abiotic stresses, the genetic basis underlying the variation in their constitutive production level remains poorly documented in conifers. We used QTL mapping and RNA-Seq to explore the complex polygenic network underlying the constitutive production of PCs in a white spruce (<em>Picea glauca</em>) full-sib family for 2 years. QTL detection was performed for nine PCs and differentially expressed genes (DEGs) were identified between individuals with high and low PC contents for five PCs exhibiting stable QTLs across time. A total of 17 QTLs were detected for eight metabolites, including one major QTL explaining up to 91.3% of the neolignan-2 variance. The RNA-Seq analysis highlighted 50 DEGs associated with phenylpropanoid biosynthesis, several key transcription factors, and a subset of 137 genes showing opposite expression patterns in individuals with high levels of the flavonoids gallocatechin and taxifolin glucoside. A total of 19 DEGs co-localized with QTLs. Our findings represent a significant step toward resolving the genomic architecture of PC production in spruce and facilitate the functional characterization of genes and transcriptional networks responsible for differences in constitutive production of PCs in conifers.</p>

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