Biodiversity resilience relies on genetic diversity, which sustains the persistence and evolutionary potential of organisms in dynamic ecosystems. Genomics is a powerful tool for estimating genome-wide genetic diversity, offering precise and accurate estimates of the status and trajectory of genetic diversity within species and populations. However, the widespread integration of genomic information into biodiversity conservation and management efforts faces challenges due to a lack of standardised genome-wide data generation methods and applications. The heterogeneity of approaches can make it difficult to consistently interpret the results and clearly communicate key information to stakeholders such as practitioners and decision-makers. To begin to address these challenges, the European Reference Genome Atlas (ERGA) promotes the standardisation of methodologies for high-quality reference genome sequencing and analysis as part of the global network of the Earth BioGenome Project. ERGA is also proactively developing best practices to engage stakeholders in biodiversity genomics research, starting with examining case studies and conducting mapping efforts to familiarise researchers with pathways to effective engagement. An emerging theme is the researchers’ experience of variable perceptions amongst stakeholders of the value and utility of reference genomes and genomics data in biodiversity conservation and management. Addressing this issue calls for consensus on standardised genome-wide data generation methods and applications that will help to deliver the highest standards for accuracy, interpretability, and comparability. We believe converging on consensus methods standardisation is essential for fostering the stakeholder trust and confidence required to successfully promote widespread adoption of genome-wide genetic diversity assessments in biodiversity conservation and management.

Cold acclimation in plants is a complex phenomenon involving numerous stress-responsive transcriptional and metabolic pathways. Existing gene expression studies have primarily addressed cold acclimation responses in herbaceous plants, and few have focused on perennial evergreens, such as conifers, that survive extremely low temperatures during winter. Relative to Arabidopsis leaves, the main transcriptional response of Norway spruce (Picea abies (L.) H. Karst) needles exposed to cold was delayed, and this delay was associated with slower development of freezing tolerance. Despite this difference in timing, our results indicate that, similar to herbaceous species, Norway spruce principally utilizes early response transcription factors (TFs) of the APETALA 2/ethylene-responsive element binding factor (AP2/ERF) superfamily and NAM (no apical meristem)/ATAF (Arabidopsis Transcription Factors)/CUC (cup shaped cotyledon) (NACs). The needles and root of Norway spruce showed contrasting results, in keeping with their different metabolic and developmental states. Regulatory network analysis identified conserved TFs, including a root-specific bHLH101 homolog, and other members of the same TF family with a pervasive role in cold regulation, such as homologs of ICE1 and AKS3, and also homologs of the NAC (anac47 and anac28) and AP2/ERF superfamilies (DREB2 and ERF3), providing new functional insights into cold stress response strategies in Norway spruce.

Leaf shape is a defining feature of how we recognise and classify plant species. Although there is extensive variation in leaf shape within many species, few studies have disentangled the underlying genetic architecture. We characterised the genetic architecture of leaf shape variation in Eurasian aspen (Populus tremula L.) by performing a genome wide association studies (GWAS) for physiognomy traits. To ascertain the roles of identified GWAS candidate genes within the leaf development transcriptional program, we performed gene co-expression network analyses from a developmental series, which is publicly available at http://aspleaf.plantgenie.org. We additionally used gene expression measurements across the population to analyse 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.

Leaf shape is a defining feature of how we recognise and classify plant species. Although there is extensive variation in leaf shape within many species, few studies have disentangled the underlying genetic architecture. We characterised the genetic architecture of leaf shape variation in Eurasian aspen (Populus tremula L.) by performing a genome wide association studies (GWAS) for physiognomy traits. To ascertain the roles of identified GWAS candidate genes within the leaf development transcriptional program, we performed gene co-expression network analyses from a developmental series, which is publicly available at http://aspleaf.plantgenie.org. We additionally used gene expression measurements across the population to analyse 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.