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Beaulieu, J.

Publications and source records attributed to Beaulieu, J..

15 recordsLinked to original sources

Development of a Microdroplet-Based Functional Genomic Screening pipeline by combination of DNA Nanoflowers and PURExpress Cell-Free Expression

We present a microfluidic workflow that couples reconstituted in vitro transcription-translation (IVTT) with ultra-high-throughput droplet screening to directly link genotype and phenotype within complex, heterogeneous DNA pools. The approach employs DNA nanoflowers as clonal, high-copy templates, enabling robust protein expression from single DNA molecules encapsulated in picoliter droplets. When integrated with fluorescence-assisted microdroplet sorting (FADS) and a DNA recovery pipeline that reconstituted selected libraries for subsequent iterative rounds, the platform achieves approximately 400-500-fold enrichment per selection cycle and supports functional discovery and directed evolution entirely independent of host cell expression. As a proof of principle, we demonstrate recovery of the recombinase RecA from an E. coli genomic library screened for single-stranded DNA binders, highlighting the platforms capability to identify DNA-interacting and DNA-modifying enzymes. By eliminating host-derived background activity and toxicity constraints that often complicate lysate- or cell-based metagenomic screens, this method expands access to enzyme classes that have historically been difficult to assay.

bioengineering↗

Variation in bud phenology, frost tolerance and non-structural carbohydrates among white spruce seed sources on climate-contrasted test sites: implications for assisted migration

To assess the potential impacts of climate change on white spruce local adaptation, six seed sources were evaluated seven years after plantation on two test sites with contrasting growing conditions and latitude in Quebec. Bud set, frost tolerance and analysis of non-structural carbohydrates (NSC) content showed important effects of test sites, seed sources, and their interactions on bud set phenology and growth. The average bud set initiation occurred one week later in the southern site compared to the northern site, whereas the late stage of bud set was similar between sites. Significant differences were observed between seed sources for some phenological stages. Frost tolerance was significantly lower in the southern site and below -12 {degrees}C for all seed sources sampled at the beginning of October. The trend in fructose and glucose content was opposite between sites in September. It decreased from September to October in the southern site and increased in the northern site, while sucrose content showed an opposite pattern, with the southwestern seed source harboring the lowest sucrose content. NSC content was also correlated to frost tolerance. Our study highlighted the crucial role of NSC in cold hardiness to early fall frosts and local adaptation. Implications for assisted migration are discussed.

plant biology↗

Statistical and structural bias in birth-death models

Accurate estimation of speciation ({lambda}) and extinction ({micro}) rates from phylogenetic trees is central to studies of diversification, yet it remains unclear whether commonly used estimators are unbiased. Here we examine two sources of error: (1) statistical bias in the estimators themselves, and the (2) structural bias introduced by how small trees are handled in likelihood calculations. For the Yule process, we re-derive the expected bias of the standard estimator, showing that [Formula] underestimates{lambda} by a factor of (n - 2)/(n - 1). Extending to the general birth-death model, we use symbolic regression to find functional forms that minimize the bias in both{lambda} and {micro}. The best-performing correction for{lambda} is identical to the Yule result, while the bias in {micro} depends on both sample size and the estimated extinction fraction ({micro}/{lambda}). Applying these corrections substantially improves the fit between the estimated and generating values. When these corrected estimators are used to derive other diversification-related parameters, turnover is nearly unbiased, but net diversification ({lambda} - {micro}) remains systematically underestimated due to the slight overestimation of {micro}. On the whole, these results clarify the statistical and structural sources of bias in diversification rate estimation and provide a general framework for improving inference under birth-death models.

evolutionary biology↗

Optimizing marker density for maximizing the accuracy of genomic prediction and heritability estimates in three major North American and European spruce species

Genomic prediction, also called genomic selection (GS), is being increasingly used in tree breeding with aim to accelerate genetic gains by shortening the long breeding cycles. However, high genotyping costs remain a challenge. This study aimed to determine the optimal marker density in genome coverage, to maximize GS accuracy and precision of heritability estimates for growth and wood quality traits. Thousands of SNPs representative of the exome of three major spruce species were used: 18,275 SNPs for black spruce (representing 10,894 distinct gene loci), 11,328 SNPs for white spruce (8647 gene loci), and 116,765 SNPs for Norway spruce (20,695 gene loci). For each species, a similar experimental design was used with related full-sib families replicated on two sites, and GBLUP prediction models were developed. The effect of varying the number of SNPs was examined by re-sampling subsets from 500 to 100,000 SNPs. Results indicated that plateaus in heritability estimates were reached as the marker density increased, stabilizing between 4000 to 8000 SNPs for a spruce genome size of around 2000 centimogans, a trend consistent across all traits and species. Predictive ability and prediction accuracy both increased with the number of SNPs up to a similar level, beyond which further improvements were marginal. Such optimal marker density should be financially attainable for most spruce breeding programs, striking a balance between the need for maximizing accuracy and that for minimizing genotyping costs. These findings should support the further deployment of GS in conifer breeding programs, with high selection precision and by reducing the financial burden of very high-density SNP coverage, even for conifers characterized by large giga-genomes.

genomics↗

Development and validation of an exome-wide SNP genotyping array for genomic prediction, GWAS and assessment of introgressive hybridization between black and red spruces, and transferability to white and Norway spruces

Introgressive hybridization plays a major role in shaping the evolutionary dynamics and adaptive potential of forest trees. In this study, we developed and validated an exome-wide bispecific SNP genotyping array (Pmr25k) for the closely related species black spruce (Picea mariana) and red spruce (Picea rubens), two ecologically and economically important North American conifers that form a widespread hybrid zone in eastern Canada. Exome capture and sequencing of pooled red spruce samples yielded over 25,000 high-quality SNPs, which were used in conjunction with a previously developed black spruce gene SNP resource of over 97,000 high-quality SNPs, to construct the bispecific genotyping array. The final array comprised 21,573 successfully manufactured SNPs, representing 14,200 distinct gene loci, of which 85% were segregating when both species were considered together. More than 4000 segregating SNPs could also be successfully used and genotyped in each of white spruce (Picea glauca) and Norway spruce (Picea abies), highlighting the conserved nature of DNA attachment sites and presence of homologous SNPs for many gene loci. The Pmr25k array thus provides an efficient and reliable high-throughput genotyping tool to investigate introgression, genetic adaptation at the gene level, and to assist genomic-based prediction for breeding and conservation efforts in boreal spruces.

genomics↗

eDNA provides accurate and precise estimates of abundance by integrating bioenergetics and particle mass-balance

Anthropogenic activities have led to an unprecedented crisis in freshwater biodiversity loss. The capacity to monitor the abundance of wild populations is critical to conserving biodiversity, but conventional physical specimen collection methods are invasive, costly, and labour-intensive. Environmental DNA (eDNA) offers a promising alternative, being easy to sample, with studies under controlled laboratory conditions showing consistent correlations between eDNA concentration and abundance. However, applying eDNA to monitor abundance remains contentious, as eDNA particle dynamics and the ecology of eDNA production can decouple this relationship in natural ecosystems. To address this, we provide a novel modeling method to produce population estimates from eDNA. We integrated bioenergetics and mass-balance frameworks to relate eDNA concentrations to freshwater fish population abundance estimated through conventional mark-recapture in Brook Trout (Salvelinus fontinalis) across nine Rocky Mountains lakes, five of which underwent size-selective harvesting over two years. Our integrated framework improved the variance explained in eDNA concentrations from 24% to 71%. The integrated model accurately distinguished most (94%) abundance estimates across populations and sampling periods, detecting both natural and harvest-induced reductions in abundance within several populations. This study is the first to empirically integrate the DNA production mechanism and particle dynamics and provide a new methodological approach enabling rapid and accurate abundance quantification. We also discuss how this new tool can be integrated in existing monitoring programs.

ecology↗

Distinct structural and functional heterochromatin partitioning of lamin B1 and B2 revealed using genome-wide Nicking Enzyme Epitope targeted DNA sequencing.

A genome-wide chromatin profiling technology, named as Nicking Enzyme Epitope targeted DNA sequencing (NEED-seq) in which antibody-targeted controlled nicking by Nt.CviPII-pGL is used to study specific protein-DNA complexes. NEED-seq is performed in situ in formaldehyde fixed cells, allowing for both visual and genomic resolution of epitope bound chromatin. When applied to nuclei, NEED-seq yielded genome-wide chromatin associated proteins and histone post-translational modifications (PTMs). NEED-seq of lamin B1/B2 demonstrated their association with heterochromatin. Lamin B1 and B2 associated domains (LAD) segregated to three different states, and states with stronger LAD correlated with heterochromatic marks. Hi-C analysis displayed A and B compartment with equal lamin B1/B2 distribution, although methylated DNA remained high in B compartment. LAD clustering with Hi-C resulted in subcompartments, with lamin B1-B2 partitioning to facultative and constitutive heterochromatin respectively and were associated with neuronal development. Thus, lamin B1 and B2 have structural and functional partitioning in mammalian nucleus. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/603107v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@44c36forg.highwire.dtl.DTLVardef@7ab1adorg.highwire.dtl.DTLVardef@126e99eorg.highwire.dtl.DTLVardef@1b38bd7_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1:C_FLOATNO Graphical abstract: Model depicting association of lamin B1 and B2 in A (facultative heterochromatin) and B (constitutive heterochromatin) compartmentalization. C_FIG

genomics↗

Error causes a perceived pull to the present in evolutionary rates

Across a variety of biological datasets, from genomes to conservation to the fossil record, evolutionary rates appear to increase toward the present or over short time scales. This has long been seen as an indication of processes operating differently at different time scales, even potentially as an indicator of a need for new theory connecting macroevolution and microevolution. Here we introduce a set of models that assess the relationship between rate and time and demonstrate that these patterns are statistical artifacts of time-independent errors present across ecological and evolutionary datasets, which produce hyperbolic patterns of rates through time. We show that plotting a noisy numerator divided by time versus time leads to the observed hyperbolic pattern; in fact, randomizing the amount of change over time generates patterns functionally identical to observed patterns. Ignoring errors can not only obscure true patterns but create novel patterns that have long misled scientists.

evolutionary biology↗

Near-perfect precise on-target editing of human hematopoietic stem and progenitor cells

Precision gene editing in primary hematopoietic stem and progenitor cells (HSPCs) would facilitate both curative treatments for monogenic disorders as well as disease modelling. Precise efficiencies even with the CRISPR/Cas system, however, remain limited. Through an optimization of guide RNA delivery, donor design, and additives, we have now obtained mean precise editing efficiencies >90% on primary cord blood HSCPs with minimal toxicity and without observed off-target editing. The main protocol modifications needed to achieve such high efficiencies were the addition of the DNA-PK inhibitor AZD7648, and the inclusion of spacer-breaking silent mutations in the donor in addition to mutations disrupting the PAM sequence. Critically, editing was even across the progenitor hierarchy, did not substantially distort the hierarchy or affect lineage outputs in colony-forming cell assays or the frequency of high self-renewal potential long-term culture initiating cells. As modelling of many diseases requires heterozygosity, we also demonstrated that the overall editing and zygosity can be tuned by adding in defined mixtures of mutant and wild-type donor. With these optimizations, editing at near-perfect efficiency can now be accomplished directly in human HSPCs. This will open new avenues in both therapeutic strategies and disease modelling.

bioengineering↗

Long-term responses of life-history strategies to climatic variability in flowering plants

O_LIThe evolution of annual or perennial strategies in flowering plants may depend on a broad array of temperature and precipitation variables. Previously documented correlations between life history strategy and climate appear to be clade-specific and fail to consider the coevolution of climatic niches and life history strategies. C_LIO_LIHere we combine annual and perennial life history data with geographic distribution for 9,939 flowering plant species and utilize a recently developed method that accounts for the joint evolution of continuous and discrete traits to evaluate two hypotheses: (1) annuals tend to evolve in highly seasonal regions prone to extreme heat and drought, and (2) annuals tend to have faster rates of climatic niche evolution than perennials. C_LIO_LIWe find temperature, particularly the maximum temperature of the warmest month, is the most consistent climatic factor influencing life history evolution in flowering plants. Unexpectedly, we find that the rates of climatic niche evolution are faster in perennials than in annual lineages. C_LIO_LIWe propose that annuals are consistently favored in areas prone to extreme heat due to their ability to escape heat stress as seeds, but they tend to be outcompeted by perennials in regions where extreme heat is uncommon or nonexistent. C_LI

evolutionary biology↗

Generalized Hidden Markov Models for Phylogenetic Comparative Datasets

O_LIHidden Markov models (HMM) have emerged as an important tool for understanding the evolution of characters that take on discrete states. Their flexibility and biological sensibility make them appealing for many phylogenetic comparative applications. C_LIO_LIPreviously available packages placed unnecessary limits on the number of observed and hidden states that can be considered when estimating transition rates and inferring ancestral states on a phylogeny. C_LIO_LITo address these issues, we expanded the capabilities of the R package corHMM to handle n-state and n-character problems and provide users with a streamlined set of functions to create custom HMMs for any biological question of arbitrary complexity. C_LIO_LIWe show that increasing the number of observed states increases the accuracy of ancestral state reconstruction. We also explore the conditions for when an HMM is most effective, finding that an HMM is an appropriate model when the degree of rate heterogeneity is moderate to high. C_LIO_LIFinally, we demonstrate the importance of these generalizations by reconstructing the phyllotaxy of the ancestral angiosperm flower. Partially contradicting previous results, we find the most likely state to be a whorled perianth, whorled androecium, whorled gynoecium. The difference between our analysis and previous studies was that our modeling explicitly allowed for the correlated evolution of several flower characters. C_LI

evolutionary biology↗

A spatially-explicit model of stabilizing selection for improving phylogeneticinference

Ultraconserved elements (UCEs) are stretches of hundreds of nucleotides with highly conserved cores flanked by variable regions. Although the selective forces responsible for the preservation of UCEs are unknown, they are nonetheless believed to contain phylogenetically meaningful information from deep to shallow divergence events. Phylogenetic applications of UCEs assume the same degree of rate heterogeneity applies across the entire locus, including variable flanking regions. We present a Wright-Fisher model of selection on nucleotides (SelON) which includes the effects of mutation, drift, and spatially varying, stabilizing selection for an optimal nucleotide sequence. The SelON model assumes the strength of stabilizing selection follows a position dependent Gaussian function whose exact shape can vary between UCEs. We evaluate SelON by comparing its performance to a simpler and spatially invariant GTR+{Gamma} model using an empirical dataset of 400 vertebrate UCEs used to determine the phylogenetic position of turtles. We observe much improvement in model fit of SelON over the GTR+{Gamma} model, and support for turtles as sister to lepidosaurs. Overall, the UCE specific parameters SelON estimates provide a compact way of quantifying the strength and variation in selection within and across UCEs. SelON can also be extended to include more realistic mapping functions between sequence and stabilizing selection as well as allow for greater levels of rate heterogeneity. By more explicitly modeling the nature of selection on UCEs, SelON and similar approaches can be used to better understand the biological mechanisms responsible for their preservation across highly divergent taxa and long evolutionary time scales.

evolutionary biology↗

Hidden state models improve the adequacy of state-dependent diversification approaches using empirical trees, including biogeographical models

The state-dependent speciation and extinction models (SSE) have recently been criticized due to their high rates of \"false positive\" results and many researchers have advocated avoiding SSE models in favor of other \"non-parametric\" or \"semi-parametric\" approaches. The hidden Markov modeling (HMM) approach provides a partial solution to the issues of model adequacy detected with SSE models. The inclusion of \"hidden states\" can account for rate heterogeneity observed in empirical phylogenies and allows detection of true signals of state-dependent diversification or diversification shifts independent of the trait of interest. However, the adoption of HMM into other classes of SSE models has been hampered by the interpretational challenges of what exactly a \"hidden state\" represents, which we clarify herein. We show that HMM models in combination with a model-averaging approach naturally account for hidden traits when examining the meaningful impact of a suspected \"driver\" of diversification. We also extend the HMM to the geographic state-dependent speciation and extinction (GeoSSE) model. We test the efficacy of our \"GeoHiSSE\" extension with both simulations and an empirical data set. On the whole, we show that hidden states are a general framework that can generally distinguish heterogeneous effects of diversification attributed to a focal character.

evolutionary biology↗

Insights into global planktonic diatom diversity:Comparisons between phylogenetically meaningful unitsthat account for time

Metabarcoding has offered unprecedented insights into microbial diversity. In many studies, short DNA sequences are binned into consecutively higher Linnaean ranks, and ranked groups (e.g., genera) are the units of biodiversity analyses. These analyses assume that Linnaean ranks are biologically meaningful and that identically ranked groups are comparable. We used a meta-barcode dataset for marine planktonic diatoms to illustrate the limits of this approach. We found that the 20 most abundant marine planktonic diatom genera ranged in age from 4 to 134 million years, indicating the non-equivalence of genera because some had more time to diversify than others. Still, species richness was only weakly correlated with genus age, highlighting variation in rates of speciation and/or extinction. Taxonomic classifications often do not reflect phylogeny, so genus-level analyses can include phylogenetically nested genera, further confounding rank-based analyses. These results underscore the indispensable role of phylogeny in understanding patterns of microbial diversity.

evolutionary biology↗

Population Genetics Based Phylogenetics Under Stabilizing Selection for an Optimal Amino Acid Sequence: A Nested Modeling Approach

We present a new phylogenetic approach SelAC (Selection on Amino acids and Codons), whose substitution rates are based on a nested model linking protein expression to population genetics. Unlike simpler codon models which assume a single substitution matrix for all sites, our model more realistically represents the evolution of protein coding DNA under the assumption of consistent, stabilizing selection using cost-benefit approach. This cost-benefit approach allows us generate a set of 20 optimal amino acid specific matrix families using just a handful of parameters and naturally links the strength of stabilizing selection to protein synthesis levels, which we can estimate. Using a yeast dataset of 100 orthologs for 6 taxa, we find SelAC fits the data much better than popular models by 104-105 AICc units. Our results indicate there is great potential for more accurate inference of phylogenetic trees and branch lengths from already existing data through the use of nested, mechanistic models. Additional parameters estimated by SelAC indicate that a large amount of non-phylogenetic, but biologically meaningful, information can be inferred from exisiting data. For example, SelAC prediction of gene specific protein synthesis rates correlates well with both empirical (r=0.33-0.48) and other theoretical predictions (r=0.45-0.64) for multiple yeast species. SelAC also provides estimates of the optimal amino acid at each site. Finally, because SelAC is a nested approach based on clearly stated biological assumptions, future modifications, such as including shifts in the optimal amino acid sequence within or across lineages, are possible.

evolutionary biology↗