Conifers have dominated forests for more than 200 million years and are of huge ecological and economic importance. Here we present the draft assembly of the 20-gigabase genome of Norway spruce (Picea abies), the first available for any gymnosperm. The number of well-supported genes (28,354) is similar to the >100 times smaller genome of Arabidopsis thaliana, and there is no evidence of a recent whole-genome duplication in the gymnosperm lineage. Instead, the large genome size seems to result from the slow and steady accumulation of a diverse set of long-terminal repeat transposable elements, possibly owing to the lack of an efficient elimination mechanism. Comparative sequencing of Pinus sylvestris, Abies sibirica, Juniperus communis, Taxus baccata and Gnetum gnemon reveals that the transposable element diversity is shared among extant conifers. Expression of 24-nucleotide small RNAs, previously implicated in transposable element silencing, is tissue-specific and much lower than in other plants. We further identify numerous long (>10,000 base pairs) introns, gene-like fragments, uncharacterized long non-coding RNAs and short RNAs. This opens up new genomic avenues for conifer forestry and breeding.

Summary: Association mapping is rapidly becoming the main method for dissecting the genetic architecture of complex traits in plants. Currently most association mapping studies in plants are preformed using sets of genes selected to be putative candidates for the trait of interest, but rapid developments in genomics will allow for genome‐wide mapping in virtually any plant species in the near future. As the costs for genotyping are decreasing, the focus has shifted towards phenotyping. In plants, clonal replication and/or inbred lines allows for replicated phenotyping under many different environmental conditions. Reduced sequencing costs will increase the number of studies that use RNA sequencing data to perform expression quantitative trait locus (eQTL) mapping, which will increase our knowledge of how gene expression variation contributes to phenotypic variation. Current population sizes used in association mapping studies are modest in size and need to be greatly increased if mutations explaining less than a few per cent of the phenotypic variation are to be detected. Association mapping has started to yield insights into the genetic architecture of complex traits in plants, and future studies with greater genome coverage will help to elucidate how plants have managed to adapt to a wide variety of environmental conditions. Contents Summary 909 I. Introduction 910 II. Genotyping 910 III. Phenotyping 911 IV. Study designs 912 V. The genetics of the ‘omics’ 912 VI. Missing heritability: the dark matter of the genome 913 VII. Gene interactions 914 VIII. Many rare alleles 914 IX. Looking in the wrong place 914 X. Looking but not seeing 915 XI. Needles in a haystack 915 XII. Confounding effects 916 XIII. Replicating and verifying associations 916 XIV. The genetic architecture of quantitative traits in plants 917 XV. Outlook 918 Acknowledgements 919 References 919

Summary: Accessing and exploring large‐scale genomics data sets remains a significant challenge to researchers without specialist bioinformatics training. We present the integrated PlantGenIE.org platform for exploration of Populus, conifer and Arabidopsis genomics data, which includes expression networks and associated visualization tools. Standard features of a model organism database are provided, including genome browsers, gene list annotation, Blast homology searches and gene information pages. Community annotation updating is supported via integration of WebApollo. We have produced an RNA‐sequencing (RNA‐Seq) expression atlas for Populus tremula and have integrated these data within the expression tools. An updated version of the ComPlEx resource for performing comparative plant expression analyses of gene coexpression network conservation between species has also been integrated. The PlantGenIE.org platform provides intuitive access to large‐scale and genome‐wide genomics data from model forest tree species, facilitating both community contributions to annotation improvement and tools supporting use of the included data resources to inform biological insight.

The AspWood large-scale data set comprises high-spatial-resolution RNA-seq transcriptome profiles collected across the phloem-cambium-xylem developmental zone o