The Norway spruce and Scots pine genomes shed light on conifer genome innovation, organisation and climate adaptation doi-10-17044-scilifelab-28737623-0 https://doi.org/10.17044/SCILIFELAB.28737623 Swedish National Data Service Svensk nationell datatjänst Landing page The Norway spruce and Scots pine genomes shed light on conifer genome innovation, organisation and climate adaptation doi-10-17044-scilifelab-28737623-0 https://doi.org/10.17044/SCILIFELAB.28737623 Street, Nathaniel 2019-05476_VR Swedish National Data Service Svensk nationell datatjänst Landing page This repository contains files associated with the analysis performed during the Norway spruce and Scots pine genome assembly and annotation, associated epigenetic analyses, and population genetics in Norway spruce. The repository contains four folders that contain files relating to different sections in the associated publication: - Genome - Orthogroups - Epigenetics - Co-expression - Population genetics Further details are provided in Readme files within each folder. These files are referred to in the associated publication as “Data Availability” as a link to the Data Availability statement where details of this repository are provided. The two genomes were assembled using PacBio HiFi reads and Micro-C (Norway spruce) or Hi-C (Scots pine) chromatin contact data. The chromatin contact data was also used to perform analysis of global compartmentalisation of chromatin and to detect Topologically Associating Domains (TADs) and chromatin loops. The genomes were annotated using collections of RNA-Seq data and PacBio IsoSeq reads. A comparative co-expression network analysis was performed for data profiling wood formation in both species to identify conserved and diverged patterns of gene co-expression. This was linked to analysis of orthogroups to examine evidence for neo- and sub-functionalisation among paralogs. In Norway spruce and extensive set of individuals were re-sequenced using Illumina short read data. Subsets of those individuals were used to perform environmental GWAS, detect signals of selection and to identify geographically segregating gene presence/absence variants. The associated ENA Umbrella project is PRJEB88492. Access to data through an external actor. Åtkomst till data via extern aktör.