https://researchdata.se/sv/catalogue Search results sv RNA-Seq data was generated from stages of somatic (SE) and zygotic embryogenesis (ZE). The developing zygotes (Zem) were isolated from the female megagametyophyte (FG) tissue at later stages. Differential expression analysis was performed for each dataset and the results were compared to identify common and contrasting expression changes. The somatic embryogenesis data was used to predict long intergenic RNAs and a co-expression network was generated. The network was used to assign putative functional annotation to the lincRNAs using a guilt-by-association approach. The normalised expression values, results of differential expression test, results of functional enrichment of gene sets and figures representing these are included. The sequences of identified lncRNAs are included as well as annotation information. The data is structured in three folders: SE = Somatic Embryogenesis ZE = Zygotic Embryogenesis SE_ZE = All files related to the comparison of differentially expressed genes between the two datasets. Some of the file names or figures can contain abbreviations different from the ones in the original publications. A conversion table is provided in the README file. More information on the folder and file content can be found in the manifest file. Tue, 01 Oct 2024 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-25315867-v1 https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-25315867-v1 Umeå universitet Nathaniel Street Katja Stojkovič Ulrika Egertsdotter Kim-Cuong Le Nicolas Delhomme Camilla Canovi RNA-Seq data was generated from stages of somatic (SE) and zygotic embryogenesis (ZE). The developing zygotes (Zem) were isolated from the female megagametyophyte (FG) tissue at later stages. Differential expression analysis was performed for each dataset and the results were compared to identify common and contrasting expression changes. The somatic embryogenesis data was used to predict long intergenic RNAs and a co-expression network was generated. The network was used to assign putative functional annotation to the lincRNAs using a guilt-by-association approach. The normalised expression values, results of differential expression test, results of functional enrichment of gene sets and figures representing these are included. The sequences of identified lncRNAs are included as well as annotation information. The data is structured in three folders: SE = Somatic Embryogenesis ZE = Zygotic Embryogenesis SE_ZE = All files related to the comparison of differentially expressed genes between the two datasets. Some of the file names or figures can contain abbreviations different from the ones in the original publications. A conversion table is provided in the README file. More information on the folder and file content can be found in the manifest file. Tue, 01 Oct 2024 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-25315867 https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-25315867 Umeå universitet Nathaniel Street Katja Stojkovič Ulrika Egertsdotter Kim-Cuong Le Nicolas Delhomme Camilla Canovi Background to the study: We have produced a chromosome-scale genome assembly generated using long-read sequencing, optical and high-density genetic maps containing 39,894 annotated genes with functional annotations for 73,765 transcripts in 37,184 genes. We conducted whole-genome resequencing of the Umeå Aspen (UmAsp) collection comprising 227 aspen individuals. We utilised the assembly and existing whole genome re-sequencing data to perform genome-wide association analyses (GWAS) using Single Nucleotide Polymorphisms (SNPs) in the UmAsp, Swedish Aspen (SwAsp) and Scottish Aspen (ScotAsp) collections for leaf physiognomy phenotypes. We conducted Assay of Transposase Accessible Chromatin sequencing (ATAC-Seq) and identified genomic regions of accessible chromatin, and subset SNPs to these regions, which improved the GWAS detection rate. We identified candidate long non-coding RNAs in leaf samples and quantified their expression in an updated co-expression network, which we used to explore the functions of candidate genes identified from the GWAS. This data set comprises: the ATAC-Seq peaks from the ATAC-Sequencing of aspen leaves, 'Aspen leaf ATAC_Seq peaks.zip'; and the gene expression matrix of mean values per aspen genotype from the SwAsp collection, 'Gene_Expression_matrix_genotype_mean.tsv'. We provide a zipped directory for each of 'ScotAsp.zip', 'SwAsp.zip' and 'UmAsp.zip' providing the raw leaf image scans, the cropped leaf images and raw data files from the LAMINA leaf shape analyses of these images, and the processed data files and genotypic BLUP values for each of these ScotAsp, SwAsp and UmAsp collections. We provide the GWAS associations of SNPs ranked by decreasing P-value until the 1000th gene for each of the 26 leaf physiognomy traits for each collection, i.e. 'ScotAsp top-ranked GWAS results', 'SwAsp top-ranked GWAS results' and 'UmAsp top-ranked GWAS results'. The single nucleotide polymorphism (SNP) data for each of the aspen collections is in 'ScotAsp_biallelic_Het.HWE.recode.vcf.gz', 'SwAsp_AfterBatchRemoval_biallelic_Het.HWE.recode.vcf.gz' and 'UmAsp_biallelic_Het.MAF.HWE.recode_.vcf.gz'. Thu, 22 Aug 2024 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-25335448 https://researchdata.se/sv/catalogue/dataset/doi-10-17044-scilifelab-25335448 Umeå universitet Kathryn Robinson Bastian Schiffthaler Hui Liu Sara Westman Martha Rendon Anaya Teitur Kalman Vikash Kumar Camilla Canovi Carolina Bernhardsson Nicolas Delhomme Jerry Jenkins Jing Wang Niklas Mähler Kerstin Richau Victoria Stokes Stuart A'Hara Joan Cottrell Kizi Coeck Tim Diels Klaas Vandepoele Chanaka Mannapperuma Eung-Jun Park Stephane Plaisance Stefan Jansson Pär Ingvarsson Nathaniel Street