Biology subjects

Lenz, P.

Publications and source records attributed to Lenz, P..

5 recordsLinked to original sources

bioRxiv2025

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↗

bioRxiv2025

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↗

bioRxiv2025

Testing genomic offset with common gardens in genetically structured black spruce (Picea mariana)

Boreal forests play a crucial role in regulating climate via storage and release of carbon. Anticipated changes in climate are expected to increase mortality and reduce biomass in many boreal tree species, putting at risk the functioning of this ecosystem and hence its role in carbon sequestration. Genomic offset methods leverage spatial distribution of genomic diversity and its association with environmental variables to predict population vulnerability to projected changes in climate. Here, we analyse over 60 populations and more than 1400 individuals of black spruce (Picea mariana (Mill.) B.S.P), a dominant boreal forest species, to compare population-level genomic offsets calculated using Gradient Forest and redundancy analysis (RDA) against multiple fitness traits measured in four long-term (>40 yr) common gardens. Within common gardens, we found that genomic offset predictions were largely unaffected by the model choice, the number or type of markers used for model training, with the strongest discrepancies observed for LFMM climate-associated markers. Model performance remained relatively stable when the number or size of populations in the training set was reduced, suggesting that these models can reliably project genomic offsets for new populations. However, model performances varied among common gardens, with highly accurate fitness predictions in some gardens but contradictory results in others. Model performance was influenced by the choice of climate predictors, their relationships with fitness traits, and the genetic cluster in which the models were evaluated. Overall, our results highlight the challenges of projecting genomic offsets across large spatial scales in genetically structured species, due to spatial variation in environmental drivers of adaptation and complex interactions among them. By capitalizing on our comprehensive validation, we identified the most robust models for projecting fitness declines in black spruce under future climate scenarios.

evolutionary biology↗

bioRxiv2024

Spruce hybrids show superior cumulative growth and intermediate response to climate anomalies, as compared to their ecologically divergent parental species

Climate change brings new constraints to which trees will have to adapt, including more frequent weather extremes. Black spruce and red spruce are phylogenetically close but adapted to different ecological conditions, and they form a natural hybrid zone where their distributions come into contact. Thus, they represent an interesting model to study the effect of introgressive hybridization in the context of climate change, given that interspecific gene flow could affect their capacity to adapt where their natural distributions overlap. Using a common-garden field test gathering 20-year-old progeny trees resulting from rigorous controlled crosses including previously verified genetic identity of the parents, growth patterns and wood density differences could be observed between species and between them and their F1 hybrids. A dendroecological analytical approach relying on wood cores was used and revealed similar wood responses to climatic variations between species, both through lifetime climate sensitivity and through episodic stress response indexes. They were however differentially expressed in early- and latewood between black spruce and red spruce, differences likely driven by diverging cambial phenology adaptations to different growing season lengths. F1 hybrids exhibited hybrid vigor for cumulative growth under the test site conditions, but showed intermediate values for traits related to climate response. These results offer new perspectives for understanding the dynamics of adaptation in hybrid zones in the context of climate change, as well as for guiding conservation and genetic improvement efforts. HighlightsO_LIF1 cumulative growth is higher than their ecologically contrasted parents. C_LIO_LIHybrids had intermediate climate responses C_LIO_LIParental species responded similarly to climate anomalies, but in various intra-ring part. C_LIO_LICambial phenology likely drives divergences in wood reaction to climate anomalies C_LI

plant biology↗

bioRxiv2022

Conservation of spatiotemporal DNA replication origin and terminus segregation patterns in Sinorhizobium meliloti with re-engineered bi- and monopartite genomes

Multipartite bacterial genomes pose challenges for genome engineering and establishment of additional replicons. We simplified the tripartite genome structure (3.65 Mbp chromosome, 1.35 Mbp megaplasmid pSymA, 1.68 Mbp chromid pSymB) of Sinorhizobium meliloti. Strains with bi- and monopartite genome configurations were generated by targeted replicon fusions. Our design preserved key genomic features, such as replichore ratios, GC skew, and KOPS and coding sequence distribution. Under standard culture conditions, growth rates of these strains and the wild type were nearly comparable. Spatiotemporal replicon organization and segregation were maintained in the triple replicon fusion strain. Deletion of the replication initiator-encoding genes including the oriVs of pSymA and pSymB from this strain resulted in a monopartite genome with oriC as the sole origin of replication, a strongly unbalanced replichore ratio, slow growth and an aberrant cellular localization of oriC. Suppressor mutation R436H in the cell cycle histidine kinase CckA and a 3.2 Mbp inversion, both individually, largely restored growth. These strains will facilitate integration of secondary replicons in S. meliloti, and thus be useful for genome engineering applications, such as generating hybrid genomes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/493018v3_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1d016caorg.highwire.dtl.DTLVardef@8856ddorg.highwire.dtl.DTLVardef@fee530org.highwire.dtl.DTLVardef@78d9cd_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗