Kermit Ritland

The Norway spruce genome sequence and conifer genome evolution

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.

Extensions of models for the estimation of mating systems using n independent loci

Inferences about plant mating systems increasingly use highly informative genetic markers, and investigate finer facets of the mating system. Here, four extensions of models for the estimation mating systems are described. (1) Multiallelic probabilities for the mixed selfing-random mating model are given; these are especially suitable for microsatellites; a generalized Kronecker operator is basis of this formula. (2) Multilocus probabilities for the ‘correlated-matings model’ are given; interestingly, comparisons between single- vs multilocus estimates of correlated-paternity can provide a new measure of population substructure. (3) A measure of biparental inbreeding, the ‘correlation of selfing among loci’, is shown to approximate the fraction of selfing due to uniparental (as opposed to biparental) inbreeding; also joint estimation of 1- 2- and 3-locus selfing rates allow separation, under a simple model, of the frequency vs the magnitude of biparental inbreeding. (4) Method-of-moments estimators for individual outcrossing rates are given. Formulae are given for both gymnosperms and angiosperms, and the computer program ‘MLTR’ implements these methods.

Estimators for pairwise relatedness and individual inbreeding coefficients

Method-of-moments estimators (MMEs) for the two-gene coefficients of relationship and inbreeding, and for thxe four-gene Cotterman coefficients, are described. These estimators, which use co-dominant genetic markers, are most appropriate for estimating pairwise relatedness or individual inbreeding coefficients, as opposed to their mean values in a group. This is because, compared to the maximum likelihood estimate (MLE), they show reduced small-sample bias and lack distributional assumptions. The ‘efficient’ MME is an optimally weighted average of estimates given by each allele at each locus. Generally, weights must be computed numerically, but if true coefficients are assumed zero, simplifiedestimators are obtained whose relative efficiencies are quite high. Population gene frequency is assumed to be assayed ina larger, ‘reference population’ sample, and the biases introduced by small reference samples and/or genetic drift of the reference population are discussed. Individual-level estimates of relatedness or inbreeding, while displaying high variance, are useful in several applications as a covariate in population studies.

Correlated matings in the partial selfer Mimulus guttatus

In partially selfing populations, siblings may be correlated for both selling and paternity. A model of the mating system based upon sampling pairs of progeny from a maternal parent is described. The model separates the correlation of selfing from the correlation of outcrossed paternal alleles and is an approach to paternity analysis suited for larger populations with fewer marker loci. Its parameters determine the components of genetic covariance between sibs and provide information about the average number of fathers in a maternal sibship.

Long‐distance gene flow and adaptation of forest trees to rapid climate change

Forest trees are the dominant species in many parts of the world and predicting how they might respond to climate change is a vital global concern. Trees are capable of long-distance gene flow, which can promote adaptive evolution in novel environments by increasing genetic variation for fitness. It is unclear, however, if this can compensate for maladaptive effects of gene flow and for the long-generation times of trees. We critically review data on the extent of long-distance gene flow and summarise theory that allows us to predict evolutionary responses of trees to climate change. Estimates of long-distance gene flow based both on direct observations and on genetic methods provide evidence that genes can move over spatial scales larger than habitat shifts predicted under climate change within one generation. Both theoretical and empirical data suggest that the positive effects of gene flow on adaptation may dominate in many instances. The balance of positive to negative consequences of gene flow may, however, differ for leading edge, core and rear sections of forest distributions. We propose future experimental and theoretical research that would better integrate dispersal biology with evolutionary quantitative genetics and improve predictions of tree responses to climate change.

Assembling the 20 Gb white spruce (Picea glauca) genome from whole-genome shotgun sequencing data

White spruce (Picea glauca) is a dominant conifer of the boreal forests of North America, and providing genomics resources for this commercially valuable tree will help improve forest management and conservation efforts. Sequencing and assembling the large and highly repetitive spruce genome though pushes the boundaries of the current technology. Here, we describe a whole-genome shotgun sequencing strategy using two Illumina sequencing platforms and an assembly approach using the ABySS software. We report a 20.8 giga base pairs draft genome in 4.9 million scaffolds, with a scaffold N50 of 20 356 bp. We demonstrate how recent improvements in the sequencing technology, especially increasing read lengths and paired end reads from longer fragments have a major impact on the assembly contiguity. We also note that scalable bioinformatics tools are instrumental in providing rapid draft assemblies. Availability: The Picea glauca genome sequencing and assembly data are available through NCBI (Accession#: ALWZ0100000000 PID: PRJNA83435). http://www.ncbi.nlm.nih.gov/bioproject/83435. Contact: ibirol@bcgsc.ca Supplementary information: Supplementary data are available at Bioinformatics online.

Marker‐inferred relatedness as a tool for detecting heritability in nature

This paper presents a perspective of how inferred relatedness, based on genetic marker data such as microsatellites or amplified fragment length polymorphisms (AFLPs), can be used to demonstrate quantitative genetic variation in natural populations. Variation at two levels is considered: among pairs of individuals within populations, and among pairs of subpopulations within a population. In the former, inferred pairwise relatedness, combined with trait measures, allow estimates of heritability ‘in the wild’. In the latter, estimates of QST are obtained, in the absence of known heritabilities, via estimates of pairwise FST. Estimators of relatedness based on the ‘Kronecker operator’ are given. Both methods require actual variation of relationship, a rarely studied aspect of population structure, and not necessarily present. Some conditions for appropriate population structures in the wild are identified, in part through a review of recent studies.

A MARKER-BASED METHOD FOR INFERENCES ABOUT QUANTITATIVE INHERITANCE IN NATURAL POPULATIONS

A marker‐based method for studying quantitative genetic characters in natural populations is presented and evaluated. The method involves regressing quantitative trait similarity on marker‐estimated relatedness between individuals. A procedure is first given for estimating the narrow sense heritability and additive genetic correlations among traits, incorporating shared environments. Estimation of the actual variance of relatedness is required for heritability, but not for genetic correlations. The approach is then extended to include isolation by distance of environments, dominance, and shared levels of inbreeding. Investigations of statistical properties show that good estimates do not require great marker polymorphism, but rather require significant variation of actual relatedness; optimal allocation generally favors sampling many individuals at the expense of assaying fewer marker loci; when relatedness declines with physical distance, it is optimal to restrict comparisons to within a certain distance; the power to estimate shared environments and inbreeding effects is reasonable, but estimates of dominance variance may be difficult under certain patterns of relationship; and any linkage of markers to quantitative trait loci does not cause significant problems. This marker‐based method makes possible studies with long‐lived organisms or with organisms difficult to culture, and opens the possibility that quantitative trait expression in natural environments can be analyzed in an unmanipulative way.

Genomics of hybrid poplar (Populus trichocarpa× deltoides) interacting with forest tent caterpillars (Malacosoma disstria): normalized and full-length cDNA libraries, expressed sequence tags, and a cDNA microarray for the study of insect-induced defences in poplar

As part of a genomics strategy to characterize inducible defences against insect herbivory in poplar, we developed a comprehensive suite of functional genomics resources including cDNA libraries, expressed sequence tags (ESTs) and a cDNA microarray platform. These resources are designed to complement the existing poplar genome sequence and poplar (Populus spp.) ESTs by focusing on herbivore‐ and elicitor‐treated tissues and incorporating normalization methods to capture rare transcripts. From a set of 15 standard, normalized or full‐length cDNA libraries, we generated 139 007 3′‐ or 5′‐end sequenced ESTs, representing more than one‐third of the c. 385 000 publicly available Populus ESTs. Clustering and assembly of 107 519 3′‐end ESTs resulted in 14 451 contigs and 20 560 singletons, altogether representing 35 011 putative unique transcripts, or potentially more than three‐quarters of the predicted c. 45 000 genes in the poplar genome. Using this EST resource, we developed a cDNA microarray containing 15 496 unique genes, which was utilized to monitor gene expression in poplar leaves in response to herbivory by forest tent caterpillars (Malacosoma disstria). After 24 h of feeding, 1191 genes were classified as up‐regulated, compared to only 537 down‐regulated. Functional classification of this induced gene set revealed genes with roles in plant defence (e.g. endochitinases, Kunitz protease inhibitors), octadecanoid and ethylene signalling (e.g. lipoxygenase, allene oxide synthase, 1‐aminocyclopropane‐1‐carboxylate oxidase), transport (e.g. ABC proteins, calreticulin), secondary metabolism [e.g. polyphenol oxidase, isoflavone reductase, (–)‐germacrene D synthase] and transcriptional regulation [e.g. leucine‐rich repeat transmembrane kinase, several transcription factor classes (zinc finger C3H type, AP2/EREBP, WRKY, bHLH)]. This study provides the first genome‐scale approach to characterize insect‐induced defences in a woody perennial providing a solid platform for functional investigation of plant–insect interactions in poplar.

Robust simple sequence repeat markers for spruce (Picea spp.) from expressed sequence tags

Traditionally, simple sequence repeat (SSR) markers have been developed from libraries of genomic DNA. However, the large, repetitive nature of conifer genomes makes development of robust, single-copy SSR markers from genomic DNA difficult. Expressed sequence tags (ESTs), or sequences of messenger RNA, offer the opportunity to exploit single, low-copy, conserved sequence motifs for SSR development. From a 20,275-unigene spruce EST set, we identified 44 candidate EST-SSR markers. Of these, 25 amplified and were polymorphic in white, Sitka, and black spruce; 20 amplified in all 23 spruce species tested; the remaining five amplified in all except one species. In addition, 101 previously described spruce SSRs (mostly developed from genomic DNA), were tested. Of these, 17 amplified across white, Sitka, and black spruce. The 25 EST-SSRs had approximately 9% less heterozygosity than the 17 genomic-derived SSRs (mean H=0.65 vs 0.72), but appeared to have less null alleles, as evidenced by much lower apparent inbreeding (mean F=0.046 vs 0.126). These robust SSRs are of particular use in comparative studies, and as the EST-SSRs are within the expressed portion of the genome, they are more likely to be associated with a particular gene of interest, improving their utility for quantitative trait loci mapping and allowing detection of selective sweeps at specific genes.