We have extended the combined use of the "pseudo-testcross" mapping strategy and RAPD markers to map quantitative trait loci (QTLs) controlling traits related to vegetative propagation in Eucalyptus. QTL analyses were performed using two different interval mapping approaches, MAPMAKER-QTL (maximum likelihood) and QTL-STAT (non-linear least squares). A total of ten QTLs were detected for micropropagation response (measured as fresh weight of shoots, FWS), six for stump sprouting ability (measured as # stump sprout cuttings, #Cutt) and four for rooting ability (measured as % rooting of cuttings, %Root). With the exception of three QTLs, both interval-mapping methods yielded similar results in terms of QTL detection. Discrepancies in the most likely QTL location were observed between the two methods. In 75% of the cases the most likely position was in the same, or in an adjacent, interval. Standardized gene substitution effects for the QTLs detected were typically between 0.46 and 2.1 phenotypic standard deviations (σp), while differences between the family mean and the favorable QTL genotype were between 0.25 and 1.07 (σp). Multipoint estimates of the total genetic variation explained by the QTLs (89.0% for FWS, 67.1 % for#Cutt, 62.7% for %Root) indicate that a large proportion of the variation in these traits is controlled by a relatively small number of major-effect QTLs. In this cross, E. grandis is responsible for most of the inherited variation in the ability to form shoots, while E. urophylla contributes most of the ability in rooting. QTL mapping in the pseudo-testcross configuration relies on withinfamily linkage disequilibrium to establish marker/trait associations. With this approach QTL analysis is possible in any available full-sib family generated from undomesticated and highly heterozygous organisms such as forest trees. QTL mapping on two-generation pedigrees opens the possibility of using already existing families in retrospective QTL analyses to gather the quantitative data necessary for marker-assisted tree breeding.

Eucalypts are the world's most widely planted hardwood trees. Their outstanding diversity, adaptability and growth have made them a global renewable resource of fibre and energy. We sequenced and assembled .94% of the 640-megabase genome of Eucalyptus grandis. Of 36,376 predicted protein-coding genes, 34% occur in tandem duplications, the largest proportion thus far in plant genomes. Eucalyptus also shows the highest diversity of genes for specialized metabolites such as terpenes that act as chemical defence and provide unique pharmaceutical oils. Genome sequencing of the E. grandis sister species E. globulus and a set of inbred E. grandis tree genomes reveals dynamic genome evolution and hotspots of inbreeding depression. The E. grandis genome is the first reference for the eudicot order Myrtales and is placed here sister to the eurosids. This resource expands our understanding of the unique biology of large woody perennials and provides a powerful tool to accelerate comparative biology, breeding and biotechnology.A major opportunity for a sustainable energy and biomaterials economy in many parts of the world lies in a better understanding of the molecular basis of superior growth and adaptation in woody plants. Part of this opportunity involves species of Eucalyptus L'Hér, a genus of woody perennials native to Australia 1 . The remarkable adaptability of eucalypts coupled with their fast growth and superior wood properties has driven their rapid adoption for plantation forestry in more than 100 countries across six continents (.20 million ha) 2 , making eucalypts the most widely planted hardwood forest trees in the world. The subtropical E. grandis and the temperate E. globulus stand out as targets of breeding programmes worldwide. Planted eucalypts provide key renewable resources for the production of pulp, paper, biomaterials and bioenergy, while mitigating human pressures on native forests 3 . Eucalypts also have a large diversity and high concentration of essential oils (mixtures of mono-and sesquiterpenes), many of which have ecological functions as well as medicinal and industrial uses. Predominantly outcrossers 1 with hermaphroditic animal-pollinated flowers, eucalypts are highly heterozygous and display pre-and postzygotic barriers to selfing to reduce inbreeding depression for fitness and survival 4 .To mitigate the challenge of assembling a highly heterozygous genome, we sequenced the genome of 'BRASUZ1', a 17-year-old E. grandis genotype derived from one generation of selfing. The availability of annotated forest tree genomes from two separately evolving rosid lineages, Eucalyptus (order Myrtales) and Populus (order Malpighiales 5 ), in combination with genomes from domesticated woody plants (for example, Vitis, Prunus, Citrus), provides a comparative foundation for addressing

Background: Benefits from high-throughput sequencing using 454 pyrosequencing technology may be most apparent for species with high societal or economic value but few genomic resources. Rapid means of gene sequence and SNP discovery using this novel sequencing technology provide a set of baseline tools for genome-level research. However, it is questionable how effective the sequencing of large numbers of short reads for species with essentially no prior gene sequence information will support contig assemblies and sequence annotation.

Genomic selection (GS) involves selection decisions based on genomic breeding values estimated as the sum of the effects of genome-wide markers capturing most quantitative trait loci (QTL) for the target trait(s). GS is revolutionizing breeding practice in domestic animals. The same approach and concepts can be readily applied to forest tree breeding where long generation times and late expressing complex traits are also a challenge. GS in forest trees would have additional advantages: large training populations can be easily assembled and accurately phenotyped for several traits, and the extent of linkage disequilibrium (LD) can be high in elite populations with small effective population size (N e ) frequently used in advanced forest tree breeding programs. Deterministic equations were used to assess the impact of LD (modeled by N e and intermarker distance), the size of the training set, trait heritability, and the number of QTL on the predicted accuracy of GS. Results indicate that GS has the potential to radically improve the efficiency of tree breeding. The benchmark accuracy of conventional BLUP selection is reached by GS even at a marker density~2 markers/cM when N e ≤30, while up to 20 markers/cM are necessary for larger N e . Shortening the breeding cycle by 50% with GS provides an increase ≥100% in selection efficiency. With the rapid technological advances and declining costs of genotyping, our cautiously optimistic outlook is that GS has great potential to accelerate tree breeding. However, further simulation studies and proof-of-concept experiments of GS are needed before recommending it for operational implementation.

OBITUARY Heinrich Rohrer, pioneer of scanning tunnelling microscopy, remembered p.30 GENES US Supreme Court patent rulings set a higher bar for innovation p.29 ART Exhibition revels in the power of unconstrained thought p.28 SPACE An elegy for the disappearing dark, banished by science p.26 Feeding the future We must mine the biodiversity in seed banks to help to overcome food shortages, urge Susan McCouch and colleagues. The International Center for Tropical Agriculture in Colombia holds 65,000 crop samples from 141 countries.

Cultivated peanut (Arachis hypogaea) is an important crop, widely grown in tropical and subtropical regions of the world. It is highly susceptible to several biotic and abiotic stresses to which wild species are resistant. As a first step towards the introgression of these resistance genes into cultivated peanut, a linkage map based on microsatellite markers was constructed, using an F(2) population obtained from a cross between two diploid wild species with AA genome (A. duranensis and A. stenosperma). A total of 271 new microsatellite markers were developed in the present study from SSR-enriched genomic libraries, expressed sequence tags (ESTs), and by "data-mining" sequences available in GenBank. Of these, 66 were polymorphic for cultivated peanut. The 271 new markers plus another 162 published for peanut were screened against both progenitors and 204 of these (47.1%) were polymorphic, with 170 codominant and 34 dominant markers. The 80 codominant markers segregating 1:2:1 (P<0.05) were initially used to establish the linkage groups. Distorted and dominant markers were subsequently included in the map. The resulting linkage map consists of 11 linkage groups covering 1,230.89 cM of total map distance, with an average distance of 7.24 cM between markers. This is the first microsatellite-based map published for Arachis, and the first map based on sequences that are all currently publicly available. Because most markers used were derived from ESTs and genomic libraries made using methylation-sensitive restriction enzymes, about one-third of the mapped markers are genic. Linkage group ordering is being validated in other mapping populations, with the aim of constructing a transferable reference map for Arachis.

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Summary• Genomic selection (GS) is expected to cause a paradigm shift in tree breeding by improving its speed and efficiency. By fitting all the genome-wide markers concurrently, GS can capture most of the 'missing heritability' of complex traits that quantitative trait locus (QTL) and association mapping classically fail to explain. Experimental support of GS is now required.• The effectiveness of GS was assessed in two unrelated Eucalyptus breeding populations with contrasting effective population sizes (N e = 11 and 51) genotyped with > 3000 DArT markers. Prediction models were developed for tree circumference and height growth, wood specific gravity and pulp yield using random regression best linear unbiased predictor (BLUP).• Accuracies of GS varied between 0.55 and 0.88, matching the accuracies achieved by conventional phenotypic selection. Substantial proportions (74-97%) of trait heritability were captured by fitting all genome-wide markers simultaneously. Genomic regions explaining trait variation largely coincided between populations, although GS models predicted poorly across populations, likely as a result of variable patterns of linkage disequilibrium, inconsistent allelic effects and genotype · environment interaction.• GS brings a new perspective to the understanding of quantitative trait variation in forest trees and provides a revolutionary tool for applied tree improvement. Nevertheless population-specific predictive models will likely drive the initial applications of GS in forest tree breeding.