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Genome editing, specifically CRISPR/Cas9 technology, has revolutionized biomedical research and offers potential cures for genetic diseases. Despite rapid progress, low efficiency of targeted DNA integration and generation of unintended mutations represent major limitations for genome editing applications caused by the interplay with DNA double-strand break repair pathways. To address this, we conduct a large-scale compound library screen to identify targets for enhancing targeted genome insertions. Our study reveals DNA-dependent protein kinase (DNA-PK) as the most effective target to improve CRISPR/Cas9-mediated insertions, confirming previous findings. We extensively characterize AZD7648, a selective DNA-PK inhibitor, and find it to significantly enhance precise gene editing. We further improve integration efficiency and precision by inhibiting DNA polymerase theta (Polϴ). The combined treatment, named 2iHDR, boosts templated insertions to 80% efficiency with minimal unintended insertions and deletions. Notably, 2iHDR also reduces off-target effects of Cas9, greatly enhancing the fidelity and performance of CRISPR/Cas9 gene editing. Low efficiency of target DNA integration remains a challenge in genome engineering. Here the authors perform large-scale compound library and genetic screens to identify targets that enhance gene editing: they see that combined DNA-PK and Polϴ inhibition with potent compounds increases editing efficiency and precision.

Seasonal cues influence several aspects of the secondary growth of tree stems, including cambial activity, wood chemistry, and transition to latewood formation. We investigated seasonal changes in cambial activity, secondary cell wall formation, and tracheid cell death in woody tissues of Norway spruce (Picea abies) throughout one seasonal cycle. RNA sequencing was performed simultaneously in both the xylem and cambium/phloem tissues of the stem. Principal component analysis revealed gradual shifts in the transcriptomes that followed a chronological order throughout the season. A notable remodeling of the transcriptome was observed in the winter, with many genes having maximal expression during the coldest months of the year. A highly coexpressed set of monolignol biosynthesis genes showed high expression during the period of secondary cell wall formation as well as a second peak in midwinter. This midwinter peak in expression did not trigger lignin deposition, as determined by pyrolysis-gas chromatography/mass spectrometry. Coexpression consensus network analyses suggested the involvement of transcription factors belonging to the ASYMMETRIC LEAVES2/LATERAL ORGAN BOUNDARIES and MYELOBLASTOSIS-HOMEOBOX families in the seasonal control of secondary cell wall formation of tracheids. Interestingly, the lifetime of the latewood tracheids stretched beyond the winter dormancy period, correlating with a lack of cell death-related gene expression. Our transcriptomic analyses combined with phylogenetic and microscopic analyses also identified the cellulose and lignin biosynthetic genes and putative regulators for latewood formation and tracheid cell death in Norway spruce, providing a toolbox for further physiological and functional assays of these important phase transitions.

Current extinction rates are comparable to five prior mass extinctions in the earth’s history, and are strongly affected by human activities that have modified more than half of the earth’s terrestrial surface. Increasing human activity restricts animal movements and isolates formerly connected populations, a particular concern for the conservation of large carnivores, but no prior research has used high throughput sequencing in a standardized manner to examine genetic connectivity for multiple species of large carnivores and multiple ecosystems. Here, we used RAD SNP genotypes to test for differences in connectivity between multiple ecosystems for African wild dogs ( Lycaon pictus ) and lions ( Panthera leo ), and to test correlations between genetic distance, geographic distance and landscape resistance due to human activity. We found weaker connectivity, a stronger correlation between genetic distance and geographic distance, and a stronger correlation between genetic distance and landscape resistance for lions than for wild dogs, and propose a new hypothesis that adaptations to interspecific competition may help to explain differences in vulnerability to isolation by humans.

Apoplastic events such as monolignol oxidation and lignin polymerization are difficult to study in intact trees. To investigate the role of apoplastic hydrogen peroxide (H₂O₂) in gymnosperm phenolic metabolism, an extracellular lignin-forming cell culture of Norway spruce (Picea abies) was used as a research model. Scavenging of apoplastic H₂O₂ by potassium iodide repressed lignin formation, in line with peroxidases activating monolignols for lignin polymerization. Time-course analyses coupled to candidate substrate-product pair network propagation revealed differential accumulation of low-molecular-weight phenolics, including (glycosylated) oligolignols, (glycosylated) flavonoids, and proanthocyanidins, in lignin-forming and H₂O₂-scavenging cultures and supported that monolignols are oxidatively coupled not only in the cell wall but also in the cytoplasm, where they are coupled to other monolignols and proanthocyanidins. Dilignol glycoconjugates with reduced structures were found in the culture medium, suggesting that cells are able to transport glycosylated dilignols to the apoplast. Transcriptomic analyses revealed that scavenging of apoplastic H₂O₂ resulted in remodulation of the transcriptome, with reduced carbon flux into the shikimate pathway propagating down to monolignol biosynthesis. Aggregated coexpression network analysis identified candidate enzymes and transcription factors for monolignol oxidation and apoplastic H₂O₂ production in addition to potential H₂O₂ receptors. The results presented indicate that the redox state of the apoplast has a profound influence on cellular metabolism.

With the rapid advancement of high throughput sequencing, large numbers of genetic markers can be readily and cheaply acquired, but most current software packages for genetic map construction cannot handle such dense input. Modern computer architectures and server farms represent untapped resources that can be used to enable higher marker densities to be processed in tractable time. Here we present a pipeline using a modified version of OneMap that parallelizes over bottleneck functions and achieves substantial speedups for producing a high density linkage map (N = 20,000). Using simulated data we show that the outcome is as accurate as the traditional pipeline. We further demonstrate that there is a direct relationship between the number of markers used and the level of deviation between true and estimated order, which in turn impacts the final size of a genetic map.

Xylan is one of the main compounds determining wood properties in hardwood species. The xylan backbone is thought to be synthesized by a synthase complex comprising two members of the GT43 family. We downregulated all GT43 genes in hybrid aspen (Populus tremula × tremuloides) to understand their involvement in xylan biosynthesis. All three clades of the GT43 family were targeted for downregulation using RNA interference individually or in different combinations, either constitutively or specifically in developing wood. Simultaneous downregulation in developing wood of the B (IRX9) and C (IRX14) clades resulted in reduced xylan Xyl content relative to reducing end sequence, supporting their role in xylan backbone biosynthesis. This was accompanied by a higher lignocellulose saccharification efficiency. Unexpectedly, GT43 suppression in developing wood led to an overall growth stimulation, xylem cell wall thinning and a shift in cellulose orientation. Transcriptome profiling of these transgenic lines indicated that cell cycling was stimulated and secondary wall biosynthesis was repressed. We suggest that the reduced xylan elongation is sensed by the cell wall integrity surveying mechanism in developing wood. Our results show that wood-specific suppression of xylan-biosynthetic GT43 genes activates signaling responses, leading to increased growth and improved lignocellulose saccharification.

Leaf shape is a defining feature of how we recognize and classify plant species. Although there is extensive variation in leaf shape within many species, few studies have disentangled the underlying genetic architecture. We characterized the genetic architecture of leaf shape variation in Eurasian aspen (Populus tremula L.) by performing genome‐wide association study (GWAS) for physiognomy traits. To ascertain the roles of identified GWAS candidate genes within the leaf development transcriptional program, we generated RNA‐Seq data that we used to perform gene co‐expression network analyses from a developmental series, which is publicly available within the PlantGenIE resource. We additionally used existing gene expression measurements across the population to analyze GWAS candidate genes in the context of a population‐wide co‐expression network and to identify genes that were differentially expressed between groups of individuals with contrasting leaf shapes. These data were integrated with expression GWAS (eQTL) results to define a set of candidate genes associated with leaf shape variation. Our results identified no clear adaptive link to leaf shape variation and indicate that leaf shape traits are genetically complex, likely determined by numerous small‐effect variations in gene expression. Genes associated with shape variation were peripheral within the population‐wide co‐expression network, were not highly connected within the leaf development co‐expression network, and exhibited signatures of relaxed selection. As such, our results are consistent with the omnigenic model. We characterized the genetic architecture of leaf shape variation in Eurasian aspen (Populus tremula L.) by performing a genome‐wide association studies (GWAS) for physiognomy traits. Our results identified no clear adaptive link to leaf shape variation and indicate that leaf shape traits are genetically complex, likely determined by numerous small‐effect variations in gene expression. Genes associated with shape variation were peripheral within the population‐wide co‐expression network, were not highly connected within the leaf development co‐expression network, and exhibited signatures of relaxed selection.

The rate of meiotic recombination is one of the central factors determining genome-wide levels of linkage disequilibrium which has important consequences for the efficiency of natural selection and for the dissection of quantitative traits. Here we present a new, high-resolution linkage map for Populus tremula that we use to anchor approximately two thirds of the P. tremula draft genome assembly on to the expected 19 chromosomes, providing us with the first chromosome-scale assembly for P. tremula (Table 2). We then use this resource to estimate variation in recombination rates across the P. tremula genome and compare these results to recombination rates based on linkage disequilibrium in a large number of unrelated individuals. We also assess how variation in recombination rates is associated with a number of genomic features, such as gene density, repeat density and methylation levels. We find that recombination rates obtained from the two methods largely agree, although the LD-based method identifies a number of genomic regions with very high recombination rates that the map-based method fails to detect. Linkage map and LD-based estimates of recombination rates are positively correlated and show similar correlations with other genomic features, showing that both methods can accurately infer recombination rate variation across the genome. Recombination rates are positively correlated with gene density and negatively correlated with repeat density and methylation levels, suggesting that recombination is largely directed toward gene regions in P. tremula.

The advancement of high-throughput sequencing (HTS) technologies and the rapid development of numerous analysis algorithms and pipelines in this field has resulted in an unprecedentedly high demand for training scientists in HTS data analysis. Embarking on developing new training materials is challenging for many reasons. Trainers often do not have prior experience in preparing or delivering such materials and struggle to keep them up to date. A repository of curated HTS training materials would support trainers in materials preparation, reduce the duplication of effort by increasing the usage of existing materials, and allow for the sharing of teaching experience among the HTS trainers' community. To achieve this, we have developed a strategy for materials' curation and dissemination. Standards for describing training materials have been proposed and applied to the curation of existing materials. A Git repository has been set up for sharing annotated materials that can now be reused, modified, or incorporated into new courses. This repository uses Git; hence, it is decentralized and self-managed by the community and can be forked/built-upon by all users. The repository is accessible at http://bioinformatics.upsc.se/htmr.

Norway spruce (Picea abies (L.) Karst.) is a conifer species of substanital economic and ecological importance. In common with most conifers, the P. abies genome is very large (∼20 Gbp) and contains a high fraction of repetitive DNA. The current P. abies genome assembly (v1.0) covers approximately 60% of the total genome size but is highly fragmented, consisting of >10 million scaffolds. The genome annotation contains 66,632 gene models that are at least partially validated (www.congenie.org), however, the fragmented nature of the assembly means that there is currently little information available on how these genes are physically distributed over the 12 P. abies chromosomes. By creating an ultra-dense genetic linkage map, we anchored and ordered scaffolds into linkage groups, which complements the fine-scale information available in assembly contigs. Our ultra-dense haploid consensus genetic map consists of 21,056 markers derived from 14,336 scaffolds that contain 17,079 gene models (25.6% of the validated gene models) that we have anchored to the 12 linkage groups. We used data from three independent component maps, as well as comparisons with previously published Picea maps to evaluate the accuracy and marker ordering of the linkage groups. We demonstrate that approximately 3.8% of the anchored scaffolds and 1.6% of the gene models covered by the consensus map have likely assembly errors as they contain genetic markers that map to different regions within or between linkage groups. We further evaluate the utility of the genetic map for the conifer research community by using an independent data set of unrelated individuals to assess genome-wide variation in genetic diversity using the genomic regions anchored to linkage groups. The results show that our map is sufficiently dense to enable detailed evolutionary analyses across the P. abies genome.