Target repositioning using multi-layer networks and machine learning: The case of prostate cancer.

The discovery of novel therapeutic targets, defined as proteins which drugs can interact with to induce therapeutic benefits, typically represent the first and most important step of drug discovery. One solution for target discovery is target repositioning, a strategy which relies on the repurposing of known targets for new diseases, leading to new treatments, less side effects and potential drug synergies. Biological networks have emerged as powerful tools for integrating heterogeneous data and facilitating the prediction of biological or therapeutic properties. Consequently, they are widely employed to predict new therapeutic targets by characterizing potential candidates, often based on their interactions within a Protein-Protein Interaction (PPI) network, and their proximity to genes associated with the disease. However, over-reliance on PPI networks and the assumption that potential targets are necessarily near known genes can introduce biases that may limit the effectiveness of these methods. This study addresses these limitations in two ways. First, by exploiting a multi-layer network which incorporates additional information such as gene regulation, metabolite interactions, metabolic pathways, and several disease signatures such as Differentially Expressed Genes, mutated genes, Copy Number Alteration, and structural variants. Second, by extracting relevant features from the network using several approaches including proximity to disease-associated genes, but also unbiased approaches such as propagation-based methods, topological metrics, and module detection algorithms. Using prostate cancer as a case study, the best features were identified and utilized to train machine learning algorithms to predict 5 novel promising therapeutic targets for prostate cancer: IGF2R, C5AR, RAB7, SETD2 and NPBWR1.

A Machine Learning Approach to Identify Key Residues Involved in Protein-Protein Interactions Exemplified with SARS-CoV-2 Variants.

Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the human angiotensin-converting enzyme 2 (ACE2). The frequent mutations in the receptor-binding domain (RBD) of the spike protein induced the emergence of variants with increased contagion and can hinder vaccine efficiency. Hence, it is crucial to better understand the binding mechanisms of variant RBDs to human ACE2 and develop efficient methods to characterize this interaction. In this work, we present an approach that uses machine learning to analyze the molecular dynamics simulations of RBD variant trajectories bound to ACE2. Along with the binding free energy calculation, this method was used to characterize the major differences in ACE2-binding capacity of three SARS-CoV-2 RBD variants-namely the original Wuhan strain, Omicron BA.1, and the more recent Omicron BA.5 sublineages. Our analyses assessed the differences in binding free energy and shed light on how it affects the infectious rates of different variants. Furthermore, this approach successfully characterized key binding interactions and could be deployed as an efficient tool to predict different binding inhibitors to pave the way for new preventive and therapeutic strategies.

Genetics of flight in spongy moths (Lymantria dispar ssp.): functionally integrated profiling of a complex invasive trait.

BACKGROUND: Flight can drastically enhance dispersal capacity and is a key trait defining the potential of exotic insect species to spread and invade new habitats. The phytophagous European spongy moths (ESM, Lymantria dispar dispar) and Asian spongy moths (ASM; a multi-species group represented here by L. d. asiatica and L. d. japonica), are globally invasive species that vary in adult female flight capability-female ASM are typically flight capable, whereas female ESM are typically flightless. Genetic markers of flight capability would supply a powerful tool for flight profiling of these species at any intercepted life stage. To assess the functional complexity of spongy moth flight and to identify potential markers of flight capability, we used multiple genetic approaches aimed at capturing complementary signals of putative flight-relevant genetic divergence between ESM and ASM: reduced representation genome-wide association studies, whole genome sequence comparisons, and developmental transcriptomics. We then judged the candidacy of flight-associated genes through functional analyses aimed at addressing the proximate demands of flight and salient features of the ecological context of spongy moth flight evolution. RESULTS: Candidate gene sets were typically non-overlapping across different genetic approaches, with only nine gene annotations shared between any pair of approaches. We detected an array of flight-relevant functional themes across gene sets that collectively suggest divergence in flight capability between European and Asian spongy moth lineages has coincided with evolutionary differentiation in multiple aspects of flight development, execution, and surrounding life history. Overall, our results indicate that spongy moth flight evolution has shaped or been influenced by a large and functionally broad network of traits. CONCLUSIONS: Our study identified a suite of flight-associated genes in spongy moths suited to exploration of the genetic architecture and evolution of flight, or validation for flight profiling purposes. This work illustrates how complementary genetic approaches combined with phenotypically targeted functional analyses can help to characterize genetically complex traits.

DNA methylation profiles in bovine sperm are associated with daughter fertility.

The current decline in dairy cattle fertility has resulted in significant financial losses for dairy farmers. In the past, most efforts to improve dairy cattle fertility have been focused on either management or genetics, while epigenetics have received less attention. In this study, 12 bulls were selected from a provided 100 bull list and studied (High daughter fertility = 6, Low daughter fertility = 6) for Enzymatic methylation sequencing in the Illumina HiSeq platform according to the Canadian daughter fertility index (DFI), sires with high and low daughter fertility have average DFI of 92 and 112.6, respectively. And the bull list provided shows a mean DFI of 103.4. 252 CpGs with methylation differences greater than 20% (q < 0.01) were identified, as well as the top 10 promising DMRs with a 15% methylation difference (q < 1.1e-26). Interestingly, the DMCs and DMRs were found to be distributed more on the X chromosome than on the autosome, and they were covered by gene clusters linked to germ cell formation and development. In conclusion, these findings could enhance our ability to make informed decisions when deciding on superior bulls and advance our understanding of paternal epigenetic inheritance.

Cytogenetic screening of a Canadian swine breeding nucleus using a newly developed karyotyping method named oligo-banding.

BACKGROUND: The frequency of chromosomal rearrangements in Canadian breeding boars has been estimated at 0.91 to 1.64%. These abnormalities are widely recognized as a potential cause of subfertility in livestock production. Since artificial insemination is practiced in almost all intensive pig production systems, the use of elite boars carrying cytogenetic defects that have an impact on fertility can lead to major economic losses. To avoid keeping subfertile boars in artificial insemination centres and spreading chromosomal defects within populations, cytogenetic screening of boars is crucial. Different techniques are used for this purpose, but several issues are frequently encountered, i.e. environmental factors can influence the quality of results, the lack of genomic information outputted by these techniques, and the need for prior cytogenetic skills. The aim of this study was to develop a new pig karyotyping method based on fluorescent banding patterns. RESULTS: The use of 207,847 specific oligonucleotides generated 96 fluorescent bands that are distributed across the 18 autosomes and the sex chromosomes. Tested alongside conventional G-banding, this oligo-banding method allowed us to identify four chromosomal translocations and a rare unbalanced chromosomal rearrangement that was not detected by conventional banding. In addition, this method allowed us to investigate chromosomal imbalance in spermatozoa. CONCLUSIONS: The use of oligo-banding was found to be appropriate for detecting chromosomal aberrations in a Canadian pig nucleus and its convenient design and use make it an interesting tool for livestock karyotyping and cytogenetic studies.

DNA methylation dynamic in male rat germ cells during gametogenesis.

In mammals, a near complete resetting of DNA methylation (DNAme) is observed during germline establishment. This wave of epigenetic reprogramming is sensitive to the environment, which could impair the establishment of an optimal state of the gamete epigenome, hence proper embryo development. Yet, we lack a comprehensive understanding of DNAme dynamics during spermatogenesis, especially in rats, the model of choice for toxicological studies. Using a combination of cell sorting and DNA methyl-seq capture, we generated a stage-specific mapping of DNAme in nine populations of differentiating germ cells from perinatal life to spermiogenesis. DNAme was found to reach its lowest level at gestational day 18, the last demethylated coding regions being associated with negative regulation of cell movement. The following de novo DNAme displayed three different kinetics with common and distinct genomic enrichments, suggesting a non-random process. DNAme variations were also detected at key steps of chromatin remodeling during spermiogenesis, revealing potential sensitivity. These methylome datasets for coding sequences during normal spermatogenesis in rat provide an essential reference for studying epigenetic-related effects of disease or environmental factors on the male germline.

Integrative analysis of green ash phloem transcripts and proteins during an emerald ash borer infestation.

BACKGROUND: Emerald ash borer (Agrilus planipennis; EAB) is an Asian insect species that has been invasive to North America for 20 years. During this time, the emerald ash borer has killed tens of millions of American ash (Fraxinus spp) trees. Understanding the inherent defenses of susceptible American ash trees will provide information to breed new resistant varieties of ash trees. RESULTS: We have performed RNA-seq on naturally infested green ash (F. pennsylvanica) trees at low, medium and high levels of increasing EAB infestation and proteomics on low and high levels of EAB infestation. Most significant transcript changes we detected occurred between the comparison of medium and high levels of EAB infestation, indicating that the tree is not responding to EAB until it is highly infested. Our integrative analysis of the RNA-Seq and proteomics data identified 14 proteins and 4 transcripts that contribute most to the difference between highly infested and low infested trees. CONCLUSIONS: The putative functions of these transcripts and proteins suggests roles of phenylpropanoid biosynthesis and oxidation, chitinase activity, pectinesterase activity, strigolactone signaling, and protein turnover.

Chromosome-level assembly of the Rangifer tarandus genome and validation of cervid and bovid evolution insights.

BACKGROUND: Genome assembly into chromosomes facilitates several analyses including cytogenetics, genomics and phylogenetics. Despite rapid development in bioinformatics, however, assembly beyond scaffolds remains challenging, especially in species without closely related well-assembled and available reference genomes. So far, four draft genomes of Rangifer tarandus (caribou or reindeer, a circumpolar distributed cervid species) have been published, but none with chromosome-level assembly. This emblematic northern species is of high interest in ecological studies and conservation since most populations are declining. RESULTS: We have designed specific probes based on Oligopaint FISH technology to upgrade the latest published reindeer and caribou chromosome-level genomes. Using this oligonucleotide-based method, we found six mis-assembled scaffolds and physically mapped 68 of the largest scaffolds representing 78% of the most recent R. tarandus genome assembly. Combining physical mapping and comparative genomics, it was possible to document chromosomal evolution among Cervidae and closely related bovids. CONCLUSIONS: Our results provide validation for the current chromosome-level genome assembly as well as resources to use chromosome banding in studies of Rangifer tarandus.

Design and validation of a 63K genome-wide SNP-genotyping platform for caribou/reindeer (Rangifer tarandus).

BACKGROUND: Development of large single nucleotide polymorphism (SNP) arrays can make genomic data promptly available for conservation problematic. Medium and high-density panels can be designed with sufficient coverage to offer a genome-wide perspective and the generated genotypes can be used to assess different genetic metrics related to population structure, relatedness, or inbreeding. SNP genotyping could also permit sexing samples with unknown associated metadata as it is often the case when using non-invasive sampling methods favored for endangered species. Genome sequencing of wild species provides the necessary information to design such SNP arrays. We report here the development of a SNP-array for endangered Rangifer tarandus using a multi-platform sequencing approach from animals found in diverse populations representing the entire circumpolar distribution of the species. RESULTS: From a very large comprehensive catalog of SNPs detected over the entire sample set (N = 894), a total of 63,336 SNPs were selected. SNP selection accounted for SNPs evenly distributed across the entire genome (~ every 50Kb) with known minor alleles across populations world-wide. In addition, a subset of SNPs was selected to represent rare and local alleles found in Eastern Canada which could be used for ecotype and population assignments - information urgently needed for conservation planning. In addition, heterozygosity from SNPs located in the X-chromosome and genotyping call-rate of SNPs located into the SRY gene of the Y-chromosome yielded an accurate and robust sexing assessment. All SNPs were validated using a high-throughput SNP-genotyping chip. CONCLUSION: This design is now integrated into the first genome-wide commercially available genotyping platform for Rangifer tarandus. This platform would pave the way to future genomic investigation of populations for this endangered species, including estimation of genetic diversity parameters, population assignments, as well as animal sexing from genetic SNP data for non-invasive samples.

Cytokines and Lipid Mediators of Inflammation in Lungs of SARS-CoV-2 Infected Mice.

Coronavirus disease 19 (COVID-19) is the clinical manifestation of severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) infection. A hallmark of COVID-19 is a lung inflammation characterized by an abundant leukocyte infiltrate, elevated levels of cytokines/chemokines, lipid mediators of inflammation (LMI) and microthrombotic events. Animal models are useful for understanding the pathophysiological events leading to COVID-19. One such animal model is the K18-ACE2 transgenic mice. Despite their importance in inflammation, the study of LMI in lung of SARS-CoV-2 infected K18-ACE2 mice has yet to be studied to our knowledge. Using tandem mass spectrometry, the lung lipidome at different time points of infection was analyzed. Significantly increased LMI included N-oleoyl-serine, N-linoleoyl-glycine, N-oleoyl-alanine, 1/2-linoleoyl-glycerol, 1/2-docosahexaenoyl-glycerol and 12-hydroxy-eicosapenatenoic acid. The levels of prostaglandin (PG) E1, PGF2α, stearoyl-ethanolamide and linoleoyl-ethanolamide were found to be significantly reduced relative to mock-infected mice. Other LMI were present at similar levels (or undetected) in both uninfected and infected mouse lungs. In parallel to LMI measures, transcriptomic and cytokine/chemokine profiling were performed. Viral replication was robust with maximal lung viral loads detected on days 2-3 post-infection. Lung histology revealed leukocyte infiltration starting on day 3 post-infection, which correlated with the presence of high concentrations of several chemokines/cytokines. At early times post-infection, the plasma of infected mice contained highly elevated concentration of D-dimers suggestive of blood clot formation/dissolution. In support, the presence of blood clots in the lung vasculature was observed during infection. RNA-Seq analysis of lung tissues indicate that SARS-CoV-2 infection results in the progressive modulation of several hundred genes, including several inflammatory mediators and genes related to the interferons. Analysis of the lung lipidome indicated modest, yet significant modulation of a minority of lipids. In summary, our study suggests that SARS-CoV-2 infection in humans and mice share common features, such as elevated levels of chemokines in lungs, leukocyte infiltration and increased levels of circulating D-dimers. However, the K18-ACE2 mouse model highlight major differences in terms of LMI being produced in response to SARS-CoV-2 infection. The potential reasons and impact of these differences on the pathology and therapeutic strategies to be employed to treat severe COVID-19 are discussed.

Alcohol induced increases in sperm Histone H3 lysine 4 trimethylation correlate with increased placental CTCF occupancy and altered developmental programming.

Using a mouse model, studies by our group reveal that paternal preconception alcohol intake affects offspring fetal-placental growth, with long-lasting consequences on adult metabolism. Here, we tested the hypothesis that chronic preconception male alcohol exposure impacts histone enrichment in sperm and that these changes are associated with altered developmental programming in the placenta. Using chromatin immunoprecipitation, we find alcohol-induced increases in sperm histone H3 lysine 4 trimethylation (H3K4me3) that map to promoters and presumptive enhancer regions enriched in genes driving neurogenesis and craniofacial development. Given the colocalization of H3K4me3 with the chromatin binding factor CTCF across both sperm and embryos, we next examined CTCF localization in the placenta. We find global changes in CTCF binding within placentae derived from the male offspring of alcohol-exposed sires. Furthermore, altered CTCF localization correlates with dysregulated gene expression across multiple gene clusters; however, these transcriptional changes only occur in male offspring. Finally, we identified a correlation between genomic regions exhibiting alcohol-induced increases in sperm H3K4me3 and increased CTCF binding in male placentae. Collectively, our analysis demonstrates that the chromatin landscape of sperm is sensitive to chronic alcohol exposure and that a subset of these affected regions exhibits increased placental CTCF enrichment.

CNVs with adaptive potential in Rangifer tarandus: genome architecture and new annotated assembly.

Rangifer tarandus has experienced recent drastic population size reductions throughout its circumpolar distribution and preserving the species implies genetic diversity conservation. To facilitate genomic studies of the species populations, we improved the genome assembly by combining long read and linked read and obtained a new highly accurate and contiguous genome assembly made of 13,994 scaffolds (L90 = 131 scaffolds). Using de novo transcriptome assembly of RNA-sequencing reads and similarity with annotated human gene sequences, 17,394 robust gene models were identified. As copy number variations (CNVs) likely play a role in adaptation, we additionally investigated these variations among 20 genomes representing three caribou ecotypes (migratory, boreal and mountain). A total of 1,698 large CNVs (length > 1 kb) showing a genome distribution including hotspots were identified. 43 large CNVs were particularly distinctive of the migratory and sedentary ecotypes and included genes annotated for functions likely related to the expected adaptations. This work includes the first publicly available annotation of the caribou genome and the first assembly allowing genome architecture analyses, including the likely adaptive CNVs reported here.

Comparing the whole genome methylation landscape of dairy calf blood cells revealed intergenerational inheritance of the maternal metabolism.

This study evaluated the hypothesis that the maternal metabolic stressed status could be inherited to their F1 daughters via epigenetic mechanism. The maternal cow blood ß-hydroxybutyric acid (BHB) level (≥0.9 mM/L) was used as an indicator of maternal metabolic stress. Eight newborn daughters' blood cells were used for methylation comparison and analysis. By Whole Genome Bisulphite Sequencing (WGBS), a total of 1,861 Differentially Methylated Regions (DMRs), including 944 differentially methylated cytosines (DMCs), were identified. Most DMRs were distributed in intronic and intergenic regions, and most of the DMR in promoter regions were hypermethylated. Differentially methylated genes (DMGs) with DMR methylation differences higher than 20% were mainly enriched in metabolism-related pathways. These results suggest that newborn calves' metabolic pathways were altered, with 64 DMGs being clustered with metabolic signalling by KEGG analysis. Our study revealed the whole epigenetic landscape of calf blood cells and suggested that the maternal metabolic status can affect the embryo's epigenetic status and metabolic-related pathways in offspring, providing further evidence for epigenetic intergenerational inheritance of metabolic stress in domestic animals. Besides, this study also contributed more evidence to support the Developmental Origins of Health and Disease (DOHAD) theory in large animals.

Hybridization and introgression drive genome evolution of Dutch elm disease pathogens.

Hybridization and the resulting introgression can drive the success of invasive species via the rapid acquisition of adaptive traits. The Dutch elm disease pandemics in the past 100 years were caused by three fungal lineages with permeable reproductive barriers: Ophiostoma ulmi, Ophiostoma novo-ulmi subspecies novo-ulmi and Ophiostoma novo-ulmi subspecies americana. Using whole-genome sequences and growth phenotyping of a worldwide collection of isolates, we show that introgression has been the main driver of genomic diversity and that it impacted fitness-related traits. Introgressions contain genes involved in host-pathogen interactions and reproduction. Introgressed isolates have enhanced growth rate at high temperature and produce different necrosis sizes on an in vivo model for pathogenicity. In addition, lineages diverge in many pathogenicity-associated genes and exhibit differential mycelial growth in the presence of a proxy of a host defence compound, implying an important role of host trees in the molecular and functional differentiation of these pathogens.

LD-annot: A Bioinformatics Tool to Automatically Provide Candidate SNPs With Annotations for Genetically Linked Genes.

A multitude of model and non-model species studies have now taken full advantage of powerful high-throughput genotyping advances such as SNP arrays and genotyping-by-sequencing (GBS) technology to investigate the genetic basis of trait variation. However, due to incomplete genome coverage by these technologies, the identified SNPs are likely in linkage disequilibrium (LD) with the causal polymorphisms, rather than be causal themselves. In addition, researchers could benefit from annotations for the identified candidate SNPs and, simultaneously, for all neighboring genes in genetic linkage. In such case, LD extent estimation surrounding the candidate SNPs is required to determine the regions encompassing genes of interest. We describe here an automated pipeline, "LD-annot," designed to delineate specific regions of interest for a given experiment and candidate polymorphisms on the basis of LD extent, and furthermore, provide annotations for all genes within such regions. LD-annot uses standard file formats, bioinformatics tools, and languages to provide identifiers, coordinates, and annotations for genes in genetic linkage with each candidate polymorphism. Although the focus lies upon SNP arrays and GBS data as they are being routinely deployed, this pipeline can be applied to a variety of datasets as long as genotypic data are available for a high number of polymorphisms and formatted into a vcf file. A checkpoint procedure in the pipeline allows to test several threshold values for linkage without having to rerun the entire pipeline, thus saving the user computational time and resources. We applied this new pipeline to four different sample sets: two breeding populations GBS datasets, one within-pedigree SNP set coming from whole genome sequencing (WGS), and a very large multi-varieties SNP dataset obtained from WGS, representing variable sample sizes, and numbers of polymorphisms. LD-annot performed within minutes, even when very high numbers of polymorphisms are investigated and thus will efficiently assist research efforts aimed at identifying biologically meaningful genetic polymorphisms underlying phenotypic variation. LD-annot tool is available under a GPL license from https://github.com/ArnaudDroitLab/LD-annot.

The large repertoire of conifer NLR resistance genes includes drought responsive and highly diversified RNLs.

The NLRs or NBS-LRRs (nucleotide-binding, leucine-rich-repeat) form the largest resistance gene family in plants, with lineage-specific contingents of TNL, CNL and RNL subfamilies and a central role in resilience to stress. The origin, evolution and distribution of NLR sequences has been unclear owing in part to the variable size and diversity of the RNL subfamily and a lack of data in Gymnosperms. We developed, searched and annotated transcriptomes assemblies of seven conifers and identified a resource of 3816 expressed NLR sequences. Our analyses encompassed sequences data spanning the major groups of land plants and determinations of NLR transcripts levels in response to drought in white spruce. We showed that conifers have among the most diverse and numerous RNLs in tested land plants. We report an evolutionary swap in the formation of RNLs, which emerged from the fusion of an RPW8 domain to a NB-ARC domain of CNL. We uncovered a quantitative relationship between RNLs and TNLs across all land plants investigated, with an average ratio of 1:10. The conifer RNL repertoire harbours four distinct groups, with two that differ from Angiosperms, one of which contained several upregulated sequences in response to drought while the majority of responsive NLRs are downregulated.

Gene copy number variations involved in balsam poplar (Populus balsamifera L.) adaptive variations.

Gene copy number variations (CNVs) involved in phenotypic variations have already been shown in plants, but genomewide testing of CNVs for adaptive variation was not doable until recent technological developments. Thus, reports of the genomic architecture of adaptation involving CNVs remain scarce to date. Here, we investigated F1 progenies of an intraprovenance cross (north-north cross, 58th parallel) and an interprovenances cross (north-south cross, 58th/49th parallels) for CNVs using comparative genomic hybridization on arrays of probes targeting gene sequences in balsam poplar (Populus balsamifera L.), a widespread North American forest tree. A total of 1,721 genes were found in varying copy numbers over the set of 19,823 tested genes. These gene CNVs presented an estimated average size of 8.3 kb and were distributed over poplar's 19 chromosomes including 22 hotspot regions. Gene CNVs number was higher for the interprovenance progeny in accordance with an expected higher genetic diversity related to the composite origin of this family. Regression analyses between gene CNVs and seven adaptive trait variations resulted in 23 significant links; among these adaptive gene CNVs, 30% were located in hotspots. One-to-five gene CNVs were found related to each of the measured adaptive traits and annotated for both biotic and abiotic stress responses. These annotations can be related to the occurrence of a higher pathogenic pressure in the southern parts of balsam poplar's distribution, and higher photosynthetic assimilation rates and water-use efficiency at high latitudes. Overall, our findings suggest that gene CNVs typically having higher mutation rates than SNPs may in fact represent efficient adaptive variations against fast-evolving pathogens.

Genomic Diversity Evaluation of Populus trichocarpa Germplasm for Rare Variant Genetic Association Studies.

Genome-wide association studies are powerful tools to elucidate the genome-to-phenome relationship. In order to explain most of the observed heritability of a phenotypic trait, a sufficient number of individuals and a large set of genetic variants must be examined. The development of high-throughput technologies and cost-efficient resequencing of complete genomes have enabled the genome-wide identification of genetic variation at large scale. As such, almost all existing genetic variation becomes available, and it is now possible to identify rare genetic variants in a population sample. Rare genetic variants that were usually filtered out in most genetic association studies are the most numerous genetic variations across genomes and hold great potential to explain a significant part of the missing heritability observed in association studies. Rare genetic variants must be identified with high confidence, as they can easily be confounded with sequencing errors. In this study, we used a pre-filtered data set of 1,014 pure Populus trichocarpa entire genomes to identify rare and common small genetic variants across individual genomes. We compared variant calls between Platypus and HaplotypeCaller pipelines, and we further applied strict quality filters for improved genetic variant identification. Finally, we only retained genetic variants that were identified by both variant callers increasing calling confidence. Based on these shared variants and after stringent quality filtering, we found high genomic diversity in P. trichocarpa germplasm, with 7.4 million small genetic variants. Importantly, 377k non-synonymous variants (5% of the total) were uncovered. We highlight the importance of genomic diversity and the potential of rare defective genetic variants in explaining a significant portion of P. trichocarpa's phenotypic variability in association genetics. The ultimate goal is to associate both rare and common alleles with poplar's wood quality traits to support selective breeding for an improved bioenergy feedstock.

Gene copy number variations in adaptive evolution: The genomic distribution of gene copy number variations revealed by genetic mapping and their adaptive role in an undomesticated species, white spruce (Picea glauca).

Gene copy number variation (CNV) has been associated with phenotypic variability in animals and plants, but a genomewide understanding of their impacts on phenotypes is largely restricted to human and agricultural systems. As such, CNVs have rarely been considered in investigations of the genomic architecture of adaptation in wild species. Here, we report on the genetic mapping of gene CNVs in white spruce, which lacks a contiguous assembly of its large genome (~20 Gb), and their relationships with adaptive phenotypic variation. We detected 3,911 gene CNVs including de novo structural variations using comparative genome hybridization on arrays (aCGH) in a large progeny set. We inferred the heterozygosity at CNV loci within parents by comparing haploid and diploid tissues and genetically mapped 82 gene CNVs. Our analysis showed that CNVs were distributed over 10 linkage groups and identified four CNV hotspots that we predict to occur in other species of the Pinaceae. Significant relationships were found between 29 of the gene CNVs and adaptive traits based on regression analyses with timings of bud set and bud flush, and height growth, suggesting a role for CNVs in climate adaptation. The importance of CNVs in adaptive evolution of white spruce was also indicated by functional gene annotations and the clustering of 31% of the mapped adaptive gene CNVs in CNV hotspots. Taken together, these results illustrate the feasibility of studying CNVs in undomesticated species and represent a major step towards a better understanding of the roles of CNVs in adaptive evolution.

CNVs into the wild: screening the genomes of conifer trees (Picea spp.) reveals fewer gene copy number variations in hybrids and links to adaptation.

BACKGROUND: Copy number variations (CNVs) have been linked to different phenotypes in human, including many diseases. A genome-scale understanding of CNVs is available in a few plants but none are wild species, leaving a knowledge gap regarding their genome biology and evolutionary role. We developed a reliable CNV detection method for species lacking contiguous reference genome. We selected multiple probes within 14,078 gene sequences and developed comparative genome hybridization on arrays. Gene CNVs were assessed in three full-sib families from species with 20 Gb genomes, i.e., white and black spruce, and interior spruce - a natural hybrid. RESULTS: We discovered hundreds of gene CNVs in each species, 3612 in total, which were enriched in functions related to stress and defense responses and narrow expression profiles, indicating a potential role in adaptation. The number of shared CNVs was in accordance with the degree of relatedness between individuals and species. The genetically mapped subset of these genes showed a wide distribution across the genome, implying numerous structural variations. The hybrid family presented significantly fewer CNVs, suggesting that the admixture of two species within one genome reduces the occurrence of CNVs. CONCLUSIONS: The approach we developed is of particular interest in non-model species lacking a reference genome. Our findings point to a role for CNVs in adaptation. Their reduced abundance in the hybrid may limit genetic variability and evolvability of hybrids. We propose that CNVs make a qualitatively distinct contribution to adaptation which could be important for short term change.