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Long non-coding RNAs (lncRNAs) have emerged as important regulators of many bio- logical processes, although their regulatory roles remain poorly characterized in woody plants, especially in gymnosperms. A major challenge of working with lncRNAs is to assign functional annotations, since they have a low coding potential and low cross-species conservation.

We utilised an existing RNA-Sequencing resource and performed short RNA sequencing of somatic embryogenesis developmental stages in Norway spruce (Picea abies L. Karst). We implemented a pipeline to identify lncRNAs located within the intergenic space (lincRNAs) and generated a co-expression network including protein coding, lincRNA and miRNA genes.

To assign putative functional annotation, we employed a guilt-by-association approach using the co-expression network and integrated these results with annota- tion assigned using semantic similarity and co-expression. Moreover, we evaluated the relationship between lincRNAs and miRNAs, and identified which lincRNAs are conserved in other species. We identified lincRNAs with clear evidence of differential expression during somatic embryogenesis and used network connectivity to identify those with the greatest regulatory potential.

This work provides the most comprehensive view of lincRNAs in Norway spruce and is the first study to perform global identification of lincRNAs during somatic embryogen- esis in conifers. The data have been integrated into the expression visualisation tools at the PlantGenIE.org web resource to enable easy access to the community. This will facilitate the use of the data to address novel questions about the role of lincRNAs in the regulation of embryogenesis and facilitate future comparative genomics studies.

Somatic embryogenesis (SE) is a powerful model system for studying embryo development and an important method for scaling up availability of elite and climate-adapted genetic material of Norway spruce (Picea abies L. Karst). However, there are several steps during the development of the somatic embryo (Sem) that are suboptimal compared to zygotic embryo (Zem) development. These differences are poorly understood and result in substantial yield losses during plant production, which limits cost-effective large-scale production of SE plants. This study presents a comprehensive data resource profiling gene expression during zygotic and somatic embryo development to support studies aiming to advance understanding of gene regulatory programmes controlling embryo development. Transcriptome expression patterns were analysed during zygotic embryogenesis (ZE) in Norway spruce, including separated samples of the female gametophytes and Zem, and at multiple stages during SE. Expression data from eight developmental stages of SE, starting with pro-embryogenic masses (PEMs) up until germination, revealed extensive modulation of the transcriptome between the early and mid-stage maturing embryos and at the transition of desiccated embryos to germination. Comparative analysis of gene expression changes during ZE and SE identified differences in the pattern of gene expression changes and functional enrichment of these provided insight into the associated biological processes. Orthologs of transcription factors known to regulate embryo development in angiosperms were differentially regulated during Zem and Sem development and in the different zygotic embryo tissues, providing clues to the differences in development observed between Zem and Sem. This resource represents the most comprehensive dataset available for exploring embryo development in conifers.

Aspen (Populus tremula L.) is a keystone species and a model system for forest tree genomics. We present an updated resource comprising a chromosome-scale assem- bly, population genetics and genomics data. Using the resource, we explore the genetic basis of natural variation in leaf size and shape, traits with complex genetic architecture.

We generated the genome assembly using long-read sequencing, optical and high-density genetic maps. We conducted whole-genome resequencing of the Umeå Aspen (UmAsp) collection. Using the assembly and re-sequencing data from the UmAsp, Swedish Aspen (SwAsp) and Scottish Aspen (ScotAsp) collections we performed genome-wide association analyses (GWAS) using Single Nucleotide Polymorphisms (SNPs) for 26 leaf physiognomy phenotypes. We conducted Assay of Transposase Accessible Chromatin sequencing (ATAC-Seq), identified genomic regions of accessible chromatin, and subset SNPs to these regions, improving the GWAS detection rate. We identified candidate long non-coding RNAs in leaf samples, quantified their expression in an updated co-expression network, and used this to explore the functions of candidate genes identified from the GWAS.

A GWAS found SNP associations for seven traits. The associated SNPs were in or near genes annotated with developmental functions, which represent candidates for further study. Of particular interest was a !177-kbp region harbouring associations with several leaf phenotypes in ScotAsp.

We have incorporated the assembly, population genetics, genomics, and GWAS data into the PlantGenIE.org web resource, including updating existing genomics data to the new genome version, to enable easy exploration and visualisation. We provide all raw and processed data to facilitate reuse in future studies.

Protein coding genes have been extensively studied in both plant and animal genomes, while non-coding portions of the genomes were considered not relevant for a long time. This was due to the fact that non-coding led immediately to not functional, until the discovery of let-7, the first conserved miRNA, in Caenorhabditis elegans. From here on, several studies on small RNAs (sRNAs) were performed, while long non-coding RNAs (lncRNAs) have risen to attention in the last two decades, also because of their usage as diagnostic biomarkers in cancer. Studies to assign function to RNAs have progressed more slowly in plants compared to the animal kingdom and there is still a lot to explore even in the protein coding space, above all if we consider huge genomes like Norway spruce and Scots pine, so the non-coding part of the genome still represents an abyss to discover. In my PhD I mostly focused on a subclass of non-coding RNAs in Norway spruce and aspen. Long non-coding RNAs are considered arbitrarily longer than 200 nucleotides (nt) and can have one small open reading frame (sORF, length < 300 nt) coding for a short peptide (not a complete protein). lncRNAs tend to be expressed at lower levels than genes, but with precise spatio-temporal patterns. They are mostly expressed in particular tissues, stages of a biological process and/or particular conditions, that are often related to biotic or abiotic stresses. They have low levels of sequence homology conservation, even in close related species. In particular, I studied the class of lncRNAs located in the intergenic space, the long intergenic non-coding RNAs (lincRNAs). 

In the first part of this thesis, I developed a pipeline to identify lincRNAs. This pipeline allows to identify in silico bona fide lincRNAs starting from an RNA-Sequencing dataset. It is an ensemble method, considering different tools and the characteristics of lincRNAs. 

In the second part of this thesis, I focused on functionally annotating lincRNAs. To achieve this challenge, I decided to use the guilt-by-association strategy. This method relies on a co-expression network containing both lincRNAs and protein coding genes. Through a functional enrichment of the protein coding genes, it is possible to transfer the same annotation to a lincRNA co-expressed in the same module. I have also tried to relate lincRNAs to a possible function in the de novo methylation of DNA via the RdDM pathway in Norway spruce.

In the last part of this thesis, I identified lincRNAs expressed during leaf development in aspen and produced CRISPR-Cas9 mutants lacking the sequence of two lincRNAs in order to provide a functional validation. 

In general, RNA-Sequencing has enabled and advanced the identification of lincRNAs, and this thesis demonstrates an implemented strategy to identify and assign putative functional information to lincRNAs, deepening the knowledge in the non-coding abyss.