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We assembled the 9.8-Gbp genome of western redcedar (WRC; Thuja plicata), an ecologically and economically important conifer species of the Cupressaceae. The genome assembly, derived from a uniquely inbred tree produced through five generations of self-fertilization (selfing), was determined to be 86% complete by BUSCO analysis, one of the most complete genome assemblies for a conifer. Population genomic analysis revealed WRC to be one of the most genetically depauperate wild plant species, with an effective population size of approximately 300 and no significant genetic differentiation across its geographic range. Nucleotide diversity, π, is low for a continuous tree species, with many loci showing zero diversity, and the ratio of π at zero- to fourfold degenerate sites is relatively high (approximately 0.33), suggestive of weak purifying selection. Using an array of genetic lines derived from up to five generations of selfing, we explored the relationship between genetic diversity and mating system. Although overall heterozygosity was found to decline faster than expected during selfing, heterozygosity persisted at many loci, and nearly 100 loci were found to deviate from expectations of genetic drift, suggestive of associative overdominance. Nonreference alleles at such loci often harbor deleterious mutations and are rare in natural populations, implying that balanced polymorphisms are maintained by linkage to dominant beneficial alleles. This may account for how WRC remains responsive to natural and artificial selection, despite low genetic diversity.

Abstract Background In a context of climate change, phenotypic plasticity provides long-lived species, such as trees, with the means to adapt to environmental variations occurring within a single generation. In eucalyptus plantations, water availability is a key factor limiting productivity. However, the molecular mechanisms underlying the adaptation of eucalyptus to water shortage remain unclear. In this study, we compared the molecular responses of two commercial eucalyptus hybrids during the dry season. Both hybrids differ in productivity when grown under water deficit. Results Pyrosequencing of RNA extracted from shoot apices provided extensive transcriptome coverage - a catalog of 129,993 unigenes (49,748 contigs and 80,245 singletons) was generated from 398 million base pairs, or 1.14 million reads. The pyrosequencing data enriched considerably existing Eucalyptus EST collections, adding 36,985 unigenes not previously represented. Digital analysis of read abundance in 14,460 contigs identified 1,280 that were differentially expressed between the two genotypes, 155 contigs showing differential expression between treatments (irrigated vs. non irrigated conditions during the dry season), and 274 contigs with significant genotype-by-treatment interaction. The more productive genotype displayed a larger set of genes responding to water stress. Moreover, stress signal transduction seemed to involve different pathways in the two genotypes, suggesting that water shortage induces distinct cellular stress cascades. Similarly, the response of functional proteins also varied widely between genotypes: the most productive genotype decreased expression of genes related to photosystem, transport and secondary metabolism, whereas genes related to primary metabolism and cell organisation were over-expressed. Conclusions For the most productive genotype, the ability to express a broader set of genes in response to water availability appears to be a key characteristic in the maintenance of biomass growth during the dry season. Its strategy may involve a decrease of photosynthetic activity during the dry season associated with resources reallocation through major changes in the expression of primary metabolism associated genes. Further efforts will be needed to assess the adaptive nature of the genes highlighted in this study.

Abstract Background Technological advances are progressively increasing the application of genomics to a wider array of economically and ecologically important species. High-density maps enriched for transcribed genes facilitate the discovery of connections between genes and phenotypes. We report the construction of a high-density linkage map of expressed genes for the heterozygous genome of Eucalyptus using Single Feature Polymorphism (SFP) markers. Results SFP discovery and mapping was achieved using pseudo-testcross screening and selective mapping to simultaneously optimize linkage mapping and microarray costs. SFP genotyping was carried out by hybridizing complementary RNA prepared from 4.5 year-old trees xylem to an SFP array containing 103,000 25-mer oligonucleotide probes representing 20,726 unigenes derived from a modest size expressed sequence tags collection. An SFP-mapping microarray with 43,777 selected candidate SFP probes representing 15,698 genes was subsequently designed and used to genotype SFPs in a larger subset of the segregating population drawn by selective mapping. A total of 1,845 genes were mapped, with 884 of them ordered with high likelihood support on a framework map anchored to 180 microsatellites with average density of 1.2 cM. Using more probes per unigene increased by two-fold the likelihood of detecting segregating SFPs eventually resulting in more genes mapped. In silico validation showed that 87% of the SFPs map to the expected location on the 4.5X draft sequence of the Eucalyptus grandis genome. Conclusions The Eucalyptus 1,845 gene map is the most highly enriched map for transcriptional information for any forest tree species to date. It represents a major improvement on the number of genes previously positioned on Eucalyptus maps and provides an initial glimpse at the gene space for this global tree genome. A general protocol is proposed to build high-density transcript linkage maps in less characterized plant species by SFP genotyping with a concurrent objective of reducing microarray costs. HIgh-density gene-rich maps represent a powerful resource to assist gene discovery endeavors when used in combination with QTL and association mapping and should be especially valuable to assist the assembly of reference genome sequences soon to come for several plant and animal species.

Abstract Background High-throughput SNP genotyping has become an essential requirement for molecular breeding and population genomics studies in plant species. Large scale SNP developments have been reported for several mainstream crops. A growing interest now exists to expand the speed and resolution of genetic analysis to outbred species with highly heterozygous genomes. When nucleotide diversity is high, a refined diagnosis of the target SNP sequence context is needed to convert queried SNPs into high-quality genotypes using the Golden Gate Genotyping Technology (GGGT). This issue becomes exacerbated when attempting to transfer SNPs across species, a scarcely explored topic in plants, and likely to become significant for population genomics and inter specific breeding applications in less domesticated and less funded plant genera. Results We have successfully developed the first set of 768 SNPs assayed by the GGGT for the highly heterozygous genome of Eucalyptus from a mixed Sanger/454 database with 1,164,695 ESTs and the preliminary 4.5X draft genome sequence for E. grandis. A systematic assessment of in silico SNP filtering requirements showed that stringent constraints on the SNP surrounding sequences have a significant impact on SNP genotyping performance and polymorphism. SNP assay success was high for the 288 SNPs selected with more rigorous in silico constraints; 93% of them provided high quality genotype calls and 71% of them were polymorphic in a diverse panel of 96 individuals of five different species. SNP reliability was high across nine Eucalyptus species belonging to three sections within subgenus Symphomyrtus and still satisfactory across species of two additional subgenera, although polymorphism declined as phylogenetic distance increased. Conclusions This study indicates that the GGGT performs well both within and across species of Eucalyptus notwithstanding its nucleotide diversity ≥2%. The development of a much larger array of informative SNPs across multiple Eucalyptus species is feasible, although strongly dependent on having a representative and sufficiently deep collection of sequences from many individuals of each target species. A higher density SNP platform will be instrumental to undertake genome-wide phylogenetic and population genomics studies and to implement molecular breeding by Genomic Selection in Eucalyptus.

Abstract Background Aluminum (Al) toxicity is one of the most important yield-limiting factors of many crops worldwide. The primary symptom of Al toxicity syndrome is the inhibition of root growth leading to poor water and nutrient absorption. Al tolerance has been extensively studied using hydroponic experiments. However, unlike soil conditions, this method does not address all of the components that are necessary for proper root growth and development. In the present study, we grew two maize genotypes with contrasting tolerance to Al in soil containing toxic levels of Al and then compared their transcriptomic responses. Results When grown in acid soil containing toxic levels of Al, the Al-sensitive genotype (S1587-17) showed greater root growth inhibition, more Al accumulation and more callose deposition in root tips than did the tolerant genotype (Cat100-6). Transcriptome profiling showed a higher number of genes differentially expressed in S1587-17 grown in acid soil, probably due to secondary effects of Al toxicity. Genes involved in the biosynthesis of organic acids, which are frequently associated with an Al tolerance response, were not differentially regulated in both genotypes after acid soil exposure. However, genes related to the biosynthesis of auxin, ethylene and lignin were up-regulated in the Al-sensitive genotype, indicating that these pathways might be associated with root growth inhibition. By comparing the two maize lines, we were able to discover genes up-regulated only in the Al-tolerant line that also presented higher absolute levels than those observed in the Al-sensitive line. These genes encoded a lipase hydrolase, a retinol dehydrogenase, a glycine-rich protein, a member of the WRKY transcriptional family and two unknown proteins. Conclusions This work provides the first characterization of the physiological and transcriptional responses of maize roots when grown in acid soil containing toxic levels of Al. The transcriptome profiles highlighted several pathways that are related to Al toxicity and tolerance during growth in acid soil. We found several genes that were not found in previous studies using hydroponic experiments, increasing our understanding of plant responses to acid soil. The use of two germplasms with markedly different Al tolerances allowed the identification of genes that are a valuable tool for assessing the mechanisms of Al tolerance in maize in acid soil.

Abstract 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. Results With the purpose of generating the first broad survey of gene sequences in Eucalyptus grandis, the most widely planted hardwood tree species, we used 454 technology to sequence and assemble 148 Mbp of expressed sequences (EST). EST sequences were generated from a normalized cDNA pool comprised of multiple tissues and genotypes, promoting discovery of homologues to almost half of Arabidopsis genes, and a comprehensive survey of allelic variation in the transcriptome. By aligning the sequencing reads from multiple genotypes we detected 23,742 SNPs, 83% of which were validated in a sample. Genome-wide nucleotide diversity was estimated for 2,392 contigs using a modified theta (θ) parameter, adapted for measuring genetic diversity from polymorphisms detected by randomly sequencing a multi-genotype cDNA pool. Diversity estimates in non-synonymous nucleotides were on average 4x smaller than in synonymous, suggesting purifying selection. Non-synonymous to synonymous substitutions (Ka/Ks) among 2,001 contigs averaged 0.30 and was skewed to the right, further supporting that most genes are under purifying selection. Comparison of these estimates among contigs identified major functional classes of genes under purifying and diversifying selection in agreement with previous researches. Conclusion In providing an abundance of foundational transcript sequences where limited prior genomic information existed, this work created part of the foundation for the annotation of the E. grandis genome that is being sequenced by the US Department of Energy. In addition we demonstrated that SNPs sampled in large-scale with 454 pyrosequencing can be used to detect evolutionary signatures among genes, providing one of the first genome-wide assessments of nucleotide diversity and Ka/Ks for a non-model plant species.

Summary: Forests face many threats. While traditional breeding may be too slow to deliver well‐adapted trees, genomic selection (GS) can accelerate the process. We describe a comprehensive study of GS from proof of concept to operational application in western redcedar (WRC, Thuja plicata).Using genomic data, we developed models on a training population (TrP) of trees to predict breeding values (BVs) in a target seedling population (TaP) for growth, heartwood chemistry, and foliar chemistry traits. We used cross‐validation to assess prediction accuracy (PACC) in the TrP; we also validated models for early‐expressed foliar traits in the TaP.Prediction accuracy was high across generations, environments, and ages. PACC was not reduced to zero among unrelated individuals in TrP and was only slightly reduced in the TaP, confirming strong linkage disequilibrium and the ability of the model to generate accurate predictions across breeding generations. Genomic BV predictions were correlated with those from pedigree but displayed a wider range of within‐family variation due to the ability of GS to capture the Mendelian sampling term.Using predicted TaP BVs in multi‐trait selection, we functionally implemented and integrated GS into an operational tree‐breeding program. [ABSTRACT FROM AUTHOR]