Exome capture from the spruce and pine giga‐genomes

Contrasting demographic history and mutational load in three threatened whitebark pines (Pinus subsect. Gerardianae): implications for conservation

Demographic history and mutational load are of paramount importance for the adaptation of the endangered species. However, the effects of population evolutionary history and genetic load on the adaptive potential in endangered conifers remain unclear. Here, using population transcriptome sequencing, whole chloroplast genomes and mitochondrial DNA markers, combined with niche analysis, we determined the demographic history and mutational load for three threatened whitebark pines having different endangered statuses, Pinus bungeana, P. gerardiana and P. squamata. Demographic inference indicated that severe bottlenecks occurred in all three pines at different times, coinciding with periods of major climate and geological changes; in contrast, while P. bungeana experienced a recent population expansion, P. gerardiana and P. squamata maintained small population sizes after bottlenecking. Abundant homozygous-derived variants accumulated in the three pines, particularly in P. squamata, while the species with most heterozygous variants was P. gerardiana. Abundant moderately and few highly deleterious variants accumulated in the pine species that have experienced the most severe demographic bottlenecks (P. gerardiana and P. squamata), most likely because of purging effects. Finally, niche modeling showed that the distribution of P. bungeana might experience a significant expansion in the future, and the species' identified genetic clusters are also supported by differences in the ecological niche. The integration of genomic, demographic and niche data has allowed us to prove that the three threatened pines have contrasting patterns of demographic history and mutational load, which may have important implications in their adaptive potential and thus are also key for informing conservation planning.

Identifying genetic variation associated with environmental gradients and drought-tolerance phenotypes in ponderosa pine

As climate changes, understanding the genetic basis of local adaptation in plants becomes an ever more pressing issue. Combining genotype-environment association (GEA) with genotype-phenotype association (GPA) analysis has an exciting potential to uncover the genetic basis of environmental responses. We use these approaches to identify genetic variants linked to local adaptation to drought in Pinus ponderosa. Over 4 million Single Nucleotide Polymorphisms (SNPs) were identified using 223 individuals from across the Sierra Nevada of California. 927,740 (22.3%) SNPs were retained after filtering for proximity to genes and used in our association analyses. We found 1374 associated with five major climate variables, with the largest number (1151) associated with April 1st snowpack. We also conducted a greenhouse study with various drought-tolerance traits measured in first-year seedlings of a subset of the genotyped trees grown in the greenhouse. 796 SNPs were associated with control-condition trait values, while 1149 were associated with responsiveness of these traits to drought. While no individual SNPs were associated with both the environmental variables and the measured traits, several annotated genes were associated with both, particularly those involved in cell wall formation, biotic and abiotic stress responses, and ubiquitination. However, the functions of many of the associated genes have not yet been determined due to the lack of gene annotation information for conifers. Future studies are needed to assess the developmental roles and ecological significance of these unknown genes.

Utilization of Genotyping-by-Sequencing (GBS) for Rice Pre-Breeding and Improvement: A Review

Molecular markers play a crucial role in the improvement of rice. To benefit from these markers, genotyping is carried out to identify the differences at a specific position in the genome of individuals. The advances in sequencing technologies have led to the development of different genotyping techniques such as genotyping-by-sequencing. Unlike PCR-fragment-based genotyping, genotyping-by-sequencing has enabled the parallel sequencing and genotyping of hundreds of samples in a single run, making it more cost-effective. Currently, GBS is being used in several pre-breeding programs of rice to identify beneficial genes and QTL from different rice genetic resources. In this review, we present the current advances in the utilization of genotyping-by-sequencing for the development of rice pre-breeding materials and the improvement of existing rice cultivars. The challenges and perspectives of using this approach are also highlighted.

Using landscape genomics to delineate seed and breeding zones for lodgepole pine

Seed and breeding zones traditionally are delineated based on local adaptation of phenotypic traits associated with climate variables, an approach requiring long-term field experiments. In this study, we applied a landscape genomics approach to delineate seed and breeding zones for lodgepole pine. We used a gradient forest (GF) model to select environment-associated single nucleotide polymorphisms (SNPs) using three SNP datasets (full, neutral and candidate) and 20 climate variables for 1906 lodgepole pine (Pinus contorta) individuals in British Columbia and Alberta, Canada. The two GF models built with the full (28 954) and candidate (982) SNPs were compared. The GF models identified winter-related climate as major climatic factors driving genomic patterns of lodgepole pine's local adaptation. Based on the genomic gradients predicted by the full and candidate GF models, lodgepole pine distribution range in British Columbia and Alberta was delineated into six seed and breeding zones. Our approach is a novel and effective alternative to traditional common garden approaches for delineating seed and breeding zone, and could be applied to tree species lacking data from provenance trials or common garden experiments.

Development and Validation of a 36K SNP Array for Radiata Pine (Pinus radiata D.Don)

Radiata pine (Pinus radiata D.Don) is one of the world’s most domesticated pines and a key economic species in New Zealand. Thus, the development of genomic resources for radiata pine has been a high priority for both research and commercial breeding. Leveraging off a previously developed exome capture panel, we tested the performance of 438,744 single nucleotide polymorphisms (SNPs) on a screening array (NZPRAD01) and then selected 36,285 SNPs for a final genotyping array (NZPRAD02). These SNPs aligned to 15,372 scaffolds from the Pinus taeda L. v. 1.01e assembly, and 20,039 contigs from the radiata pine transcriptome assembly. The genotyping array was tested on more than 8000 samples, including material from archival progenitors, current breeding trials, nursery material, clonal lines, and material from Australia. Our analyses indicate that the array is performing well, with sample call rates greater than 98% and a sample reproducibility of 99.9%. Genotyping in two linkage mapping families indicated that the SNPs are well distributed across the 12 linkage groups. Using genotypic data from this array, we were also able to differentiate representatives of the five recognized provenances of radiata pine, Año Nuevo, Monterey, Cambria, Cedros and Guadalupe. Furthermore, principal component analysis of genotyped trees revealed clear patterns of population structure, with the primary axis of variation driven by provenance ancestry and the secondary axis reflecting breeding activities. This represents the first commercial use of genomics in a radiata pine breeding program.

Whole-exome sequencing of selected bread wheat recombinant inbred lines as a useful resource for allele mining and bulked segregant analysis

Although wheat (Triticum aestivum L.) is the main staple crop in the world and a major source of carbohydrates and proteins, functional genomics and allele mining are still big challenges. Given the advances in next-generation sequencing (NGS) technologies, the identification of causal variants associated with a target phenotype has become feasible. For these reasons, here, by combining sequence capture and target-enrichment methods with high-throughput NGS re-sequencing, we were able to scan at exome-wide level 46 randomly selected bread wheat individuals from a recombinant inbred line population and to identify and classify a large number of single nucleotide polymorphisms (SNPs). For technical validation of results, eight randomly selected SNPs were converted into Kompetitive Allele-Specific PCR (KASP) markers. This resource was established as an accessible and reusable molecular toolkit for allele data mining. The dataset we are making available could be exploited for novel studies on bread wheat genetics and as a foundation for starting breeding programs aimed at improving different key agronomic traits.

Genome-wide shifts in climate-related variation underpin responses to selective breeding in a widespread conifer

Temperate trees originating from warmer localities usually grow faster and acclimate to winter later than trees of the same species from colder localities. However, when trees are selected for faster growth, are climatically adaptive genes and traits affected? Our research demonstrates a simple, sensitive, broadly applicable, and elusive approach to integrating complex polygenic variation into applied environmental management. We show that selective breeding increases allele frequencies of many trait-associated genes, and that alleles that increase most display strong genetic linkage and potential trade-offs among traits. Increasing tree growth while maintaining adaptation is essential to reforestation in a changing climate, but this may be challenging because trait-associated genetic variation that underpins climate adaptation is responsive to selection for tree growth.

Locally adapted temperate tree populations exhibit genetic trade-offs among climate-related traits that can be exacerbated by selective breeding and are challenging to manage under climate change. To inform climatically adaptive forest management, we investigated the genetic architecture and impacts of selective breeding on four climate-related traits in 105 natural and 20 selectively bred lodgepole pine populations from western Canada. Growth, cold injury, growth initiation, and growth cessation phenotypes were tested for associations with 18,600 single-nucleotide polymorphisms (SNPs) in natural populations to identify “positive effect alleles” (PEAs). The effects of artificial selection for faster growth on the frequency of PEAs associated with each trait were quantified in breeding populations from different climates. Substantial shifts in PEA proportions and frequencies were observed across many loci after two generations of selective breeding for height, and responses of phenology-associated PEAs differed strongly among climatic regions. Extensive genetic overlap was evident among traits. Alleles most strongly associated with greater height were often associated with greater cold injury and delayed phenology, although it is unclear whether potential trade-offs arose directly from pleiotropy or indirectly via genetic linkage. Modest variation in multilocus PEA frequencies among populations was associated with large phenotypic differences and strong climatic gradients, providing support for assisted gene flow polices. Relationships among genotypes, phenotypes, and climate in natural populations were maintained or strengthened by selective breeding. However, future adaptive phenotypes and assisted gene flow may be compromised if selective breeding further increases the PEA frequencies of SNPs involved in adaptive trade-offs among climate-related traits.

Haploid, diploid, and pooled exome capture recapitulate features of biology and paralogy in two non-model tree species

Despite their suitability for studying evolution, many conifer species have large and repetitive giga‐genomes (16–31 Gbp) that create hurdles to producing high coverage SNP data sets that capture diversity from across the entirety of the genome. Due in part to multiple ancient whole genome duplication events, gene family expansion and subsequent evolution within Pinaceae, false diversity from the misalignment of paralog copies creates further challenges in accurately and reproducibly inferring evolutionary history from sequence data. Here, we leverage the cost‐saving benefits of pool‐seq and exome‐capture to discover SNPs in two conifer species, Douglas‐fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco, Pinaceae) and jack pine (Pinus banksiana Lamb., Pinaceae). We show, using minimal baseline filtering, that allele frequencies estimated from pooled individuals show a strong, positive correlation with those estimated by sequencing the same population as individuals (r > .948), on par with such comparisons made in model organisms. Further, we highlight the utility of haploid megagametophyte tissue for identifying sites that are probably due to misaligned paralogs. Together with additional minor filtering, we show that it is possible to remove many of the loci with large frequency estimate discrepancies between individual and pooled sequencing approaches, improving the correlation further (r > .973). Our work addresses bioinformatic challenges in non‐model organisms with large and complex genomes, highlights the use of megagametophyte tissue for the identification of paralogous artefacts, and suggests the combination of pool‐seq and exome capture to be robust for further evolutionary hypothesis testing in these systems.

Looking for the needle in a downsized haystack: Whole-exome sequencing unravels genomic signals of climatic adaptation in Douglas-fir (Pseudotsuga menziesii)

Conifers often occur along steep gradients of diverse climates throughout their natural ranges, which is expected to result in spatially varying selection to local climate conditions. However, signals of climatic adaptation can often be confounded, because unraveled clines covary with signals caused by neutral evolutionary processes such as gene flow and genetic drift. Consequently, our understanding of how selection and gene flow have shaped phenotypic and genotypic differentiation in trees is still limited.A 40-year-old common garden experiment comprising 16 Douglas-fir (Pseudotsuga menziesii) provenances from a north-to-south gradient of approx. 1,000 km was analyzed, and genomic information was obtained from exome capture, which resulted in an initial genomic dataset of >90,000 single nucleotide polymorphisms. We used a restrictive and conservative filtering approach, which permitted us to include only SNPs and individuals in environmental association analysis (EAA) that were free of potentially confounding effects (LD, relatedness among trees, heterozygosity deficiency, and deviations from Hardy-Weinberg proportions). We used four conceptually different genome scan methods based on FST outlier detection and gene-environment association in order to disentangle truly adaptive SNPs from neutral SNPs.We found that a relatively small proportion of the exome showed a truly adaptive signal (0.01%-0.17%) when population substructuring and multiple testing was accounted for. Nevertheless, the unraveled SNP candidates showed significant relationships with climate at provenance origins, which strongly suggests that they have featured adaptation in Douglas-fir along a climatic gradient. Two SNPs were independently found by three of the employed algorithms, and one of them is in close proximity to an annotated gene involved in circadian clock control and photoperiodism as was similarly found in Populus balsamifera. Synthesis. We conclude that despite neutral evolutionary processes, phenotypic and genomic signals of adaptation to climate are responsible for differentiation, which in particular explain disparity between the well-known coastal and interior varieties of Douglas-fir.

Toward genomic selection in Pinus taeda: Integrating resources to support array design in a complex conifer genome

PREMISE

An informatics approach was used for the construction of an Axiom genotyping array from heterogeneous, high-throughput sequence data to assess the complex genome of loblolly pine (Pinus taeda).

METHODS

High-throughput sequence data, sourced from exome capture and whole genome reduced-representation approaches from 2698 trees across five sequence populations, were analyzed with the improved genome assembly and annotation for the loblolly pine. A variant detection, filtering, and probe design pipeline was developed to detect true variants across and within populations. From 8.27 million variants, a total of 642,275 were evaluated and 423,695 of those were screened across a range-wide population.

RESULTS

The final informatics and screening approach delivered an Axiom array representing 46,439 high-confidence variants to the forest tree breeding and genetics community. Based on the annotated reference genome, 34% were located in or directly upstream or downstream of genic regions.

DISCUSSION

The Pita50K array represents a genome-wide resource developed from sequence data for an economically important conifer, loblolly pine. It uniquely integrates independent projects that assessed trees sampled across the native range. The challenges associated with the large and repetitive genome are addressed in the development of this resource.

Evaluation of the efficiency of genomic versus pedigree predictions for growth and wood quality traits in Scots pine

BACKGROUND

Genomic selection (GS) or genomic prediction is a promising approach for tree breeding to obtain higher genetic gains by shortening time of progeny testing in breeding programs. As proof-of-concept for Scots pine (Pinus sylvestris L.), a genomic prediction study was conducted with 694 individuals representing 183 full-sib families that were genotyped with genotyping-by-sequencing (GBS) and phenotyped for growth and wood quality traits. 8719 SNPs were used to compare different genomic with pedigree prediction models. Additionally, four prediction efficiency methods were used to evaluate the impact of genomic breeding value estimations by assigning diverse ratios of training and validation sets, as well as several subsets of SNP markers.

RESULTS

Genomic Best Linear Unbiased Prediction (GBLUP) and Bayesian Ridge Regression (BRR) combined with expectation maximization (EM) imputation algorithm showed slightly higher prediction efficiencies than Pedigree Best Linear Unbiased Prediction (PBLUP) and Bayesian LASSO, with some exceptions. A subset of approximately 6000 SNP markers, was enough to provide similar prediction efficiencies as the full set of 8719 markers. Additionally, prediction efficiencies of genomic models were enough to achieve a higher selection response, that varied between 50-143% higher than the traditional pedigree-based selection.

CONCLUSIONS

Although prediction efficiencies were similar for genomic and pedigree models, the relative selection response was doubled for genomic models by assuming that earlier selections can be done at the seedling stage, reducing the progeny testing time, thus shortening the breeding cycle length roughly by 50%.

Genomic Selection for Forest Tree Improvement: Methods, Achievements and Perspectives

The breeding of forest trees is only a few decades old, and is a much more complicated, longer, and expensive endeavor than the breeding of agricultural crops. One breeding cycle for forest trees can take 20–30 years. Recent advances in genomics and molecular biology have revolutionized traditional plant breeding based on visual phenotype assessment: the development of different types of molecular markers has made genotype selection possible. Marker-assisted breeding can significantly accelerate the breeding process, but this method has not been shown to be effective for selection of complex traits on forest trees. This new method of genomic selection is based on the analysis of all effects of quantitative trait loci (QTLs) using a large number of molecular markers distributed throughout the genome, which makes it possible to assess the genomic estimated breeding value (GEBV) of an individual. This approach is expected to be much more efficient for forest tree improvement than traditional breeding. Here, we review the current state of the art in the application of genomic selection in forest tree breeding and discuss different methods of genotyping and phenotyping. We also compare the accuracies of genomic prediction models and highlight the importance of a prior cost-benefit analysis before implementing genomic selection. Perspectives for the further development of this approach in forest breeding are also discussed: expanding the range of species and the list of valuable traits, the application of high-throughput phenotyping methods, and the possibility of using epigenetic variance to improve of forest trees.

Whole-exome sequencing reveals a long-term decline in effective population size of red spruce (Picea rubens)

Understanding the factors influencing the current distribution of genetic diversity across a species range is one of the main questions of evolutionary biology, especially given the increasing threat to biodiversity posed by climate change. Historical demographic processes such as population expansion or bottlenecks and decline are known to exert a predominant influence on past and current levels of genetic diversity, and revealing this demo-genetic history can have immediate conservation implications. We used a whole-exome capture sequencing approach to analyze polymorphism across the gene space of red spruce (Picea rubens Sarg.), an endemic and emblematic tree species of eastern North America high-elevation forests that are facing the combined threat of global warming and increasing human activities. We sampled a total of 340 individuals, including populations from the current core of the range in northeastern USA and southeastern Canada and from the southern portions of its range along the Appalachian Mountains, where populations occur as highly fragmented mountaintop "sky islands." Exome capture baits were designed from the closely relative white spruce (P. glauca Voss) transcriptome, and sequencing successfully captured most regions on or near our target genes, resulting in the generation of a new and expansive genomic resource for studying standing genetic variation in red spruce applicable to its conservation. Our results, based on over 2 million exome-derived variants, indicate that red spruce is structured into three distinct ancestry groups that occupy different geographic regions of its highly fragmented range. Moreover, these groups show small Ne , with a temporal history of sustained population decline that has been ongoing for thousands (or even hundreds of thousands) of years. These results demonstrate the broad potential of genomic studies for revealing details of the demographic history that can inform management and conservation efforts of nonmodel species with active restoration programs, such as red spruce.

No evidence for accumulation of deleterious mutations and fitness degradation in clonal fish hybrids: Abandoning sex without regrets

Despite its inherent costs, sexual reproduction is ubiquitous in nature, and the mechanisms to protect it from a competitive displacement by asexuality remain unclear. Popular mutation-based explanations, like the Muller's ratchet and the Kondrashov's hatchet, assume that purifying selection may not halt the accumulation of deleterious mutations in the nonrecombining genomes, ultimately leading to their degeneration. However, empirical evidence is scarce and it remains particularly unclear whether mutational degradation proceeds fast enough to ensure the decay of clonal organisms and to prevent them from outcompeting their sexual counterparts. To test this hypothesis, we jointly analysed the exome sequences and the fitness-related phenotypic traits of the sexually reproducing fish species and their clonal hybrids, whose evolutionary ages ranged from F1 generations to 300 ky. As expected, mutations tended to accumulate in the clonal genomes in a time-dependent manner. However, contrary to the predictions, we found no trend towards increased nonsynonymity of mutations acquired by clones, nor higher radicality of their amino acid substitutions. Moreover, there was no evidence for fitness degeneration in the old clones compared with that in the younger ones. In summary, although an efficacy of purifying selection may still be reduced in the asexual genomes, our data indicate that its efficiency is not drastically decreased. Even the oldest investigated clone was found to be too young to suffer fitness consequences from a mutation accumulation. This suggests that mechanisms other than mutation accumulation may be needed to explain the competitive advantage of sex in the short term.

Genomic Diversity Evaluation of Populus trichocarpa Germplasm for Rare Variant Genetic Association Studies

Genome-wide association studies are powerful tools to elucidate the genome-to-phenome relationship. In order to explain most of the observed heritability of a phenotypic trait, a sufficient number of individuals and a large set of genetic variants must be examined. The development of high-throughput technologies and cost-efficient resequencing of complete genomes have enabled the genome-wide identification of genetic variation at large scale. As such, almost all existing genetic variation becomes available, and it is now possible to identify rare genetic variants in a population sample. Rare genetic variants that were usually filtered out in most genetic association studies are the most numerous genetic variations across genomes and hold great potential to explain a significant part of the missing heritability observed in association studies. Rare genetic variants must be identified with high confidence, as they can easily be confounded with sequencing errors. In this study, we used a pre-filtered data set of 1,014 pure Populus trichocarpa entire genomes to identify rare and common small genetic variants across individual genomes. We compared variant calls between Platypus and HaplotypeCaller pipelines, and we further applied strict quality filters for improved genetic variant identification. Finally, we only retained genetic variants that were identified by both variant callers increasing calling confidence. Based on these shared variants and after stringent quality filtering, we found high genomic diversity in P. trichocarpa germplasm, with 7.4 million small genetic variants. Importantly, 377k non-synonymous variants (5% of the total) were uncovered. We highlight the importance of genomic diversity and the potential of rare defective genetic variants in explaining a significant portion of P. trichocarpa's phenotypic variability in association genetics. The ultimate goal is to associate both rare and common alleles with poplar's wood quality traits to support selective breeding for an improved bioenergy feedstock.

Novel genomic resources for shelled pteropods: a draft genome and target capture probes for Limacina bulimoides, tested for cross-species relevance

BACKGROUND

Pteropods are planktonic gastropods that are considered as bio-indicators to monitor impacts of ocean acidification on marine ecosystems. In order to gain insight into their adaptive potential to future environmental changes, it is critical to use adequate molecular tools to delimit species and population boundaries and to assess their genetic connectivity. We developed a set of target capture probes to investigate genetic variation across their large-sized genome using a population genomics approach. Target capture is less limited by DNA amount and quality than other genome-reduced representation protocols, and has the potential for application on closely related species based on probes designed from one species.

RESULTS

We generated the first draft genome of a pteropod, Limacina bulimoides, resulting in a fragmented assembly of 2.9 Gbp. Using this assembly and a transcriptome as a reference, we designed a set of 2899 genome-wide target capture probes for L. bulimoides. The set of probes includes 2812 single copy nuclear targets, the 28S rDNA sequence, ten mitochondrial genes, 35 candidate biomineralisation genes, and 41 non-coding regions. The capture reaction performed with these probes was highly efficient with 97% of the targets recovered on the focal species. A total of 137,938 single nucleotide polymorphism markers were obtained from the captured sequences across a test panel of nine individuals. The probes set was also tested on four related species: L. trochiformis, L. lesueurii, L. helicina, and Heliconoides inflatus, showing an exponential decrease in capture efficiency with increased genetic distance from the focal species. Sixty-two targets were sufficiently conserved to be recovered consistently across all five species.

CONCLUSION

The target capture protocol used in this study was effective in capturing genome-wide variation in the focal species L. bulimoides, suitable for population genomic analyses, while providing insights into conserved genomic regions in related species. The present study provides new genomic resources for pteropods and supports the use of target capture-based protocols to efficiently characterise genomic variation in small non-model organisms with large genomes.

275 years of forestry meets genomics in Pinus sylvestris

Pinus sylvestris has a long history of basic and applied research that is relevant for both forestry and evolutionary studies. Its patterns of adaptive variation and role in forest economic and ecological systems have been studied extensively for nearly 275 years, detailed demography for a 100 years and mating system more than 50 years. However, its reference genome sequence is not yet available and genomic studies have been lagging compared to, for example, Pinus taeda and Picea abies, two other economically important conifers. Despite the lack of reference genome, many modern genomic methods are applicable for a more detailed look at its biological characteristics. For example, RNA-seq has revealed a complex transcriptional landscape and targeted DNA sequencing displays an excess of rare variants and geographically homogenously distributed molecular genetic diversity. Current DNA and RNA resources can be used as a reference for gene expression studies, SNP discovery, and further targeted sequencing. In the future, specific consequences of the large genome size, such as functional effects of regulatory open chromatin regions and transposable elements, should be investigated more carefully. For forest breeding and long-term management purposes, genomic data can help in assessing the genetic basis of inbreeding depression and the application of genomic tools for genomic prediction and relatedness estimates. Given the challenges of breeding (long generation time, no easy vegetative propagation) and the economic importance, application of genomic tools has a potential to have a considerable impact. Here, we explore how genomic characteristics of P. sylvestris, such as rare alleles and the low extent of linkage disequilibrium, impact the applicability and power of the tools.

Evaluating genomic data for management of local adaptation in a changing climate: A lodgepole pine case study

We evaluate genomic data, relative to phenotypic and climatic data, as a basis for assisted gene flow and genetic conservation. Using a seedling common garden trial of 281 lodgepole pine (Pinus contorta) populations from across western Canada, we compare genomic data to phenotypic and climatic data to assess their effectiveness in characterizing the climatic drivers and spatial scale of local adaptation in this species. We find that phenotype-associated loci are equivalent or slightly superior to climate data for describing local adaptation in seedling traits, but that climate data are superior to genomic data that have not been selected for phenotypic associations. We also find agreement between the climate variables associated with genomic variation and with 20-year heights from a long-term provenance trial, suggesting that genomic data may be a viable option for identifying climatic drivers of local adaptation where phenotypic data are unavailable. Genetic clines associated with the experimental traits occur at broad spatial scales, suggesting that standing variation of adaptive alleles for this and similar species does not require management at scales finer than those indicated by phenotypic data. This study demonstrates that genomic data are most useful when paired with phenotypic data, but can also fill some of the traditional roles of phenotypic data in management of species for which phenotypic trials are not feasible.

Utilization of Tissue Ploidy Level Variation in de Novo Transcriptome Assembly of Pinus sylvestris

Compared to angiosperms, gymnosperms lag behind in the availability of assembled and annotated genomes. Most genomic analyses in gymnosperms, especially conifer tree species, rely on the use of de novo assembled transcriptomes. However, the level of allelic redundancy and transcript fragmentation in these assembled transcriptomes, and their effect on downstream applications have not been fully investigated. Here, we assessed three assembly strategies for short-reads data, including the utility of haploid megagametophyte tissue during de novo assembly as single-allele guides, for six individuals and five different tissues in Pinus sylvestris. We then contrasted haploid and diploid tissue genotype calls obtained from the assembled transcriptomes to evaluate the extent of paralog mapping. The use of the haploid tissue during assembly increased its completeness without reducing the number of assembled transcripts. Our results suggest that current strategies that rely on available genomic resources as guidance to minimize allelic redundancy are less effective than the application of strategies that cluster redundant assembled transcripts. The strategy yielding the lowest levels of allelic redundancy among the assembled transcriptomes assessed here was the generation of SuperTranscripts with Lace followed by CD-HIT clustering. However, we still observed some levels of heterozygosity (multiple gene fragments per transcript reflecting allelic redundancy) in this assembled transcriptome on the haploid tissue, indicating that further filtering is required before using these assemblies for downstream applications. We discuss the influence of allelic redundancy when these reference transcriptomes are used to select regions for probe design of exome capture baits and for estimation of population genetic diversity.

Somatic mutations substantially increase the per-generation mutation rate in the conifer Picea sitchensis

The rates and biological significance of somatic mutations have long been a subject of debate. Somatic mutations in plants are expected to accumulate with vegetative growth and time, yet rates of somatic mutations are unknown for conifers, which can reach exceptional sizes and ages. We investigated somatic mutation rates in the conifer Sitka spruce (Picea sitchensis (Bong.) Carr.) by analyzing a total of 276 Gb of nuclear DNA from the tops and bottoms of 20 old‐growth trees averaging 76 m in height. We estimate a somatic base substitution rate of 2.7 × 10⁻⁸ per base pair within a generation. To date, this is one of the highest estimated per‐generation rates of mutation among eukaryotes, indicating that somatic mutations contribute substantially to the total per‐generation mutation rate in conifers. Nevertheless, as the sampled trees are centuries old, the per‐year rate is low in comparison with nontree taxa. We argue that although somatic mutations raise genetic load in conifers, they generate important genetic variation and enable selection both among cell lineages within individual trees and among offspring.

Multiomics analysis reveals a distinct mechanism of oleaginousness in the emerging model alga Chromochloris zofingiensis

Chromochloris zofingiensis, featured due to its capability to simultaneously synthesize triacylglycerol (TAG) and astaxanthin, is emerging as a leading candidate alga for production uses. To better understand the oleaginous mechanism of this alga, we conducted a multiomics analysis by systematically integrating time-resolved transcriptomes, lipidomes and metabolomes in response to nitrogen deprivation. The data analysis unraveled the distinct mechanism of TAG accumulation, which involved coordinated stimulation of multiple biological processes including supply of energy and reductants, carbon reallocation from protein and starch, and 'pushing' and 'pulling' carbon to TAG synthesis. Unlike the model alga Chlamydomonas, de novo fatty acid synthesis in C. zofingiensis was promoted, together with enhanced turnover of both glycolipids and phospholipids, supporting the drastic need of acyls for TAG assembly. Moreover, genomewide analysis identified many key functional enzymes and transcription factors that had engineering potential for TAG modulation. Two genes encoding glycerol-3-phosphate acyltransferase (GPAT), the first committed enzyme for TAG assembly, were found in the C. zofingiensis genome; in vivo functional characterization revealed that extrachloroplastic GPAT instead of chloroplastic GPAT played a central role in TAG synthesis. These findings illuminate distinct oleaginousness mechanisms in C. zofingiensis and pave the way towards rational manipulation of this alga to becone an emerging model for trait improvements.

Purifying selection does not drive signatures of convergent local adaptation of lodgepole pine and interior spruce

BACKGROUND

Lodgepole pine (Pinus contorta) and interior spruce (Picea glauca, Picea engelmannii, and their hybrids) are distantly related conifer species. Previous studies identified 47 genes containing variants associated with environmental variables in both species, providing evidence of convergent local adaptation. However, if the intensity of purifying selection varies with the environment, clines in nucleotide diversity could evolve through linked (background) selection that would yield allele frequency-environment signatures resembling local adaptation. If similar geographic patterns in the strength of purifying selection occur in these species, this could result in the convergent signatures of local adaptation, especially if the landscape of recombination is conserved. In the present study, we investigated whether spatially/environmentally varying purifying selection could give rise to the convergent signatures of local adaptation that had previously reported.

RESULTS

We analyzed 86 lodgepole pine and 50 interior spruce natural populations spanning heterogeneous environments in western Canada where previous analyses had found signatures of convergent local adaptation. We estimated nucleotide diversity and Tajima's D for each gene within each population and calculated the strength of correlations between nucleotide diversity and environmental variables. Overall, these estimates in the genes with previously identified convergent local adaptation signatures had no similar pattern between pine and spruce. Clines in nucleotide diversity along environmental variables were found for interior spruce, but not for lodgepole pine. In spruce, genes with convergent adaption signatures showed a higher strength of correlations than genes without convergent adaption signatures, but there was no such disparity in pine, which suggests the pattern in spruce may have arisen due to a combination of selection and hybridization.

CONCLUSIONS

The results rule out purifying/background selection as a driver of convergent local adaption signatures in lodgepole pine and interior spruce.

Exome Resequencing Reveals Evolutionary History, Genomic Diversity, and Targets of Selection in the Conifers Pinus taeda and Pinus elliottii

Loblolly pine (Pinus taeda) and slash pine (Pinus elliottii) are ecologically and economically important pine species that dominate many forest ecosystems in the southern United States, but like all conifers, the study of their genetic diversity and demographic history has been hampered by their large genome size. A small number of studies mainly based on candidate-gene sequencing have been reported for P. taeda to date, whereas none are available for P. elliottii. Targeted exome resequencing has recently enabled population genomics studies for conifers, approach used here to assess genomic diversity, signatures of selection, population structure, and demographic history of P. elliottii and P. taeda. Extensive similarities were revealed between these species: both species feature rapid linkage disequilibrium decay and high levels of genetic diversity. Moreover, genome-wide positive correlations for measures of genetic diversity between the species were also observed, likely due to shared structural genomic constraints. Also, positive selection appears to be targeting a common set of genes in both pines. Demographic history differs between both species, with only P. taeda being affected by a dramatic bottleneck during the last glacial period. The ability of P. taeda to recover from a dramatic reduction in population size while still retaining high levels of genetic diversity shows promise for other pines facing environmental stressors associated with climate change, indicating that these too may be able to adapt successfully to new future conditions even after a drastic population size contraction.

Digging for the spiny rat and hutia phylogeny using a gene capture approach, with the description of a new mammal subfamily

Next generation sequencing (NGS) and genomic database mining allow biologists to gather and select large molecular datasets well suited to address phylogenomics and molecular evolution questions. Here we applied this approach to a mammal family, the Echimyidae, for which generic relationships have been difficult to recover and often referred to as a star phylogeny. These South-American spiny rats represent a family of caviomorph rodents exhibiting a striking diversity of species and life history traits. Using a NGS exon capture protocol, we isolated and sequenced ca. 500 nuclear DNA exons for 35 species belonging to all major echimyid and capromyid clades. Exons were carefully selected to encompass as much diversity as possible in terms of rate of evolution, heterogeneity in the distribution of site-variation and nucleotide composition. Supermatrix inferences and coalescence-based approaches were subsequently applied to infer this family's phylogeny. The inferred topologies were the same for both approaches, and support was maximal for each node, entirely resolving the ambiguous relationships of previous analyses. Fast-evolving nuclear exons tended to yield more reliable phylogenies, as slower-evolving sequences were not informative enough to disentangle the short branches of the Echimyidae radiation. Based on this resolved phylogeny and on molecular and morphological evidence, we confirm the rank of the Caribbean hutias - formerly placed in the Capromyidae family - as Capromyinae, a clade nested within Echimyidae. We also name and define Carterodontinae, a new subfamily of Echimyidae, comprising the extant monotypic genus Carterodon from Brazil, which is the closest living relative of West Indies Capromyinae.

A dedicated target capture approach reveals variable genetic markers across micro- and macro-evolutionary time scales in palms

Understanding the genetics of biological diversification across micro- and macro-evolutionary time scales is a vibrant field of research for molecular ecologists as rapid advances in sequencing technologies promise to overcome former limitations. In palms, an emblematic, economically and ecologically important plant family with high diversity in the tropics, studies of diversification at the population and species levels are still hampered by a lack of genomic markers suitable for the genotyping of large numbers of recently diverged taxa. To fill this gap, we used a whole genome sequencing approach to develop target sequencing for molecular markers in 4,184 genome regions, including 4,051 genes and 133 non-genic putatively neutral regions. These markers were chosen to cover a wide range of evolutionary rates allowing future studies at the family, genus, species and population levels. Special emphasis was given to the avoidance of copy number variation during marker selection. In addition, a set of 149 well-known sequence regions previously used as phylogenetic markers by the palm biological research community were included in the target regions, to open the possibility to combine and jointly analyse already available data sets with genomic data to be produced with this new toolkit. The bait set was effective for species belonging to all three palm sub-families tested (Arecoideae, Ceroxyloideae and Coryphoideae), with high mapping rates, specificity and efficiency. The number of high-quality single nucleotide polymorphisms (SNPs) detected at both the sub-family and population levels facilitates efficient analyses of genomic diversity across micro- and macro-evolutionary time scales.

A catalog of annotated high-confidence SNPs from exome capture and sequencing reveals highly polymorphic genes in Norway spruce (Picea abies)

BACKGROUND

Norway spruce [Picea abies (L.) Karst.] is ecologically and economically one of the most important conifer worldwide. Our main goal was to develop a large catalog of annotated high confidence gene SNPs that should sustain the development of genomic tools for the conservation of natural and domesticated genetic diversity resources, and hasten tree breeding efforts in this species.

RESULTS

Targeted sequencing was achieved by capturing P. abies exome with probes previously designed from the sequenced transcriptome of white spruce (Picea glauca (Moench) Voss). Capture efficiency was high (74.5%) given a high level of exome conservation between the two species. Using stringent criteria, we delimited a set of 61,771 high-confidence SNPs across 13,543 genes. To validate SNPs, a high-throughput genotyping array was developed for a subset of 5571 predicted SNPs representing as many different gene loci, and was used to genotype over 1000 trees. The estimated true positive rate of the resource was 84.2%, which was comparable with the genotyping success rate obtained for P. abies control SNPs recycled from previous genotyping efforts. We also analyzed SNP abundance across various gene functional categories. Several GO terms and gene families involved in stress response were found over-represented in highly polymorphic genes.

CONCLUSION

The annotated high-confidence SNP catalog developed herein represents a valuable genomic resource, being representative of over 13 K genes distributed across the P. abies genome. This resource should serve a variety of population genomics and breeding applications in Norway spruce.

Modularity of genes involved in local adaptation to climate despite physical linkage

BACKGROUND

Linkage among genes experiencing different selection pressures can make natural selection less efficient. Theory predicts that when local adaptation is driven by complex and non-covarying stresses, increased linkage is favored for alleles with similar pleiotropic effects, with increased recombination favored among alleles with contrasting pleiotropic effects. Here, we introduce a framework to test these predictions with a co-association network analysis, which clusters loci based on differing associations. We use this framework to study the genetic architecture of local adaptation to climate in lodgepole pine, Pinus contorta, based on associations with environments.

RESULTS

We identify many clusters of candidate genes and SNPs associated with distinct environments, including aspects of aridity and freezing, and discover low recombination rates among some candidate genes in different clusters. Only a few genes contain SNPs with effects on more than one distinct aspect of climate. There is limited correspondence between co-association networks and gene regulatory networks. We further show how associations with environmental principal components can lead to misinterpretation. Finally, simulations illustrate both benefits and caveats of co-association networks.

CONCLUSIONS

Our results support the prediction that different selection pressures favor the evolution of distinct groups of genes, each associating with a different aspect of climate. But our results went against the prediction that loci experiencing different sources of selection would have high recombination among them. These results give new insight into evolutionary debates about the extent of modularity, pleiotropy, and linkage in the evolution of genetic architectures.

Guidelines for planning genomic assessment and monitoring of locally adaptive variation to inform species conservation

Identifying and monitoring locally adaptive genetic variation can have direct utility for conserving species at risk, especially when management may include actions such as translocations for restoration, genetic rescue, or assisted gene flow. However, genomic studies of local adaptation require careful planning to be successful, and in some cases may not be a worthwhile use of resources. Here, we offer an adaptive management framework to help conservation biologists and managers decide when genomics is likely to be effective in detecting local adaptation, and how to plan assessment and monitoring of adaptive variation to address conservation objectives. Studies of adaptive variation using genomic tools will inform conservation actions in many cases, including applications such as assisted gene flow and identifying conservation units. In others, assessing genetic diversity, inbreeding, and demographics using selectively neutral genetic markers may be most useful. And in some cases, local adaptation may be assessed more efficiently using alternative approaches such as common garden experiments. Here, we identify key considerations of genomics studies of locally adaptive variation, provide a road map for successful collaborations with genomics experts including key issues for study design and data analysis, and offer guidelines for interpreting and using results from genomic assessments to inform monitoring programs and conservation actions.

Targeted resequencing of coding DNA sequences for SNP discovery in nonmodel species

Targeted capture coupled with high-throughput sequencing can be used to gain information about nuclear sequence variation at hundreds to thousands of loci. Divergent reference capture makes use of molecular data of one species to enrich target loci in other (related) species. This is particularly valuable for nonmodel organisms, for which often no a priori knowledge exists regarding these loci. Here, we have used targeted capture to obtain data for 809 nuclear coding DNA sequences (CDS) in a nonmodel organism, the Eurasian lynx Lynx lynx, using baits designed with the help of the published genome of a related model organism (the domestic cat Felis catus). Using this approach, we were able to survey intraspecific variation at hundreds of nuclear loci in L. lynx across the species' European range. A large set of biallelic candidate SNPs was then evaluated using a high-throughput SNP genotyping platform (Fluidigm), which we then reduced to a final 96 SNP-panel based on assay performance and reliability; validation was carried out with 100 additional Eurasian lynx samples not included in the SNP discovery phase. The 96 SNP-panel developed from CDS performed very successfully in the identification of individuals and in population genetic structure inference (including the assignment of individuals to their source population). In keeping with recent studies, our results show that genic SNPs can be valuable for genetic monitoring of wildlife species.

Capturing variation in Lens (Fabaceae): Development and utility of an exome capture array for lentil

PREMISE OF THE STUDY

Lentil is an important legume crop with reduced genetic diversity caused by domestication bottlenecks. Due to its large and complex genome, tools for reduced representation sequencing are needed. We developed an exome capture array for use in various genetic diversity studies.

METHODS

Based on the CDC Redberry draft genome, we developed an exome capture array using multiple sources of transcript resources. The probes were designed to target not only the cultivated lentil, but also wild species. We assessed the utility of the developed method by applying the generated data set to population structure and phylogenetic analyses.

RESULTS

The data set includes 16 wild lentils and 22 cultivar accessions of lentil. Alignment rates were over 90%, and the genic regions were well represented in the capture array. After stringent filtering, 6.5 million high-quality variants were called, and the data set was used to assess the interspecific relationships within the genus Lens.

DISCUSSION

The developed exome capture array provides large amounts of genomic data to be used in many downstream analyses. The method will have useful applications in marker-assisted breeding programs aiming to improve the quality of cultivated lentil.

Development of Target Sequence Capture and Estimation of Genomic Relatedness in a Mixed Oak Stand

Anticipating the evolutionary responses of long-lived organisms, such as trees, to environmental changes, requires the assessment of genetic variation of adaptive traits in natural populations. To this end, high-density markers are needed to calculate genomic relatedness between individuals allowing to estimate the genetic variance of traits in wild populations. We designed a targeted capture-based, next-generation sequencing assay based on the highly heterozygous pedunculate oak (Quercus robur) reference genome, for the sequencing of 3 Mb of genic and intergenic regions. Using a mixed stand of 293 Q. robur and Q. petraea genotypes we successfully captured over 97% of the target sequences, corresponding to 0.39% of the oak genome, with sufficient depth (97×) for the detection of about 190,000 SNPs evenly spread over the targeted regions. We validated the technique by evaluating its reproducibility, and comparing the genomic relatedness of trees with their known pedigree relationship. We explored the use of the technique on other related species and highlighted the advantages and limitations of this approach. We found that 92.07% of target sequences in Q. suber and 70.36% of sequences in Fagus sylvatica were captured. We used this SNP resource to estimate genetic relatedness in the mixed oak stand. Mean pairwise genetic relatedness was low within each species with a few values exceeding 0.25 (half-sibs) or 0.5 (full-sibs). Finally, we applied the technique to a long-standing issue in population genetics of trees regarding the relationship between inbreeding and components of fitness. We found very weak signals for inbreeding depression for reproductive success and no signal for growth within both species.

Bioinformatically predicted deleterious mutations reveal complementation in the interior spruce hybrid complex

BACKGROUND

Mutation load is expected to be reduced in hybrids via complementation of deleterious alleles. While local adaptation of hybrids confounds phenotypic tests for reduced mutation load, it may be possible to assess variation in load by analyzing the distribution of putatively deleterious alleles. Here, we use this approach in the interior spruce (Picea glauca x P. engelmannii) hybrid complex, a group likely to suffer from high mutation load and in which hybrids exhibit local adaptation to intermediate conditions. We used PROVEAN to bioinformatically predict whether non-synonymous alleles are deleterious, based on conservation of the position and abnormality of the amino acid change.

RESULTS

As expected, we found that predicted deleterious alleles were at lower average allele frequencies than alleles not predicted to be deleterious. We were unable to detect a phenotypic effect on juvenile growth rate of the many rare alleles predicted to be deleterious. Both the proportion of alleles predicted to be deleterious and the proportion of loci homozygous for predicted deleterious alleles were higher in P. engelmannii (Engelmann spruce) than in P. glauca (white spruce), due to higher diversity and frequencies of rare alleles in Engelmann. Relative to parental species, the proportion of alleles predicted to be deleterious was intermediate in hybrids, and the proportion of loci homozygous for predicted deleterious alleles was lowest.

CONCLUSION

Given that most deleterious alleles are recessive, this suggests that mutation load is reduced in hybrids due to complementation of deleterious alleles. This effect may enhance the fitness of hybrids.

Genomic prediction accuracies in space and time for height and wood density of Douglas-fir using exome capture as the genotyping platform

Background

Genomic selection (GS) can offer unprecedented gains, in terms of cost efficiency and generation turnover, to forest tree selective breeding; especially for late expressing and low heritability traits. Here, we used: 1) exome capture as a genotyping platform for 1372 Douglas-fir trees representing 37 full-sib families growing on three sites in British Columbia, Canada and 2) height growth and wood density (EBVs), and deregressed estimated breeding values (DEBVs) as phenotypes. Representing models with (EBVs) and without (DEBVs) pedigree structure. Ridge regression best linear unbiased predictor (RR-BLUP) and generalized ridge regression (GRR) were used to assess their predictive accuracies over space (within site, cross-sites, multi-site, and multi-site to single site) and time (age-age/ trait-trait).

Results

The RR-BLUP and GRR models produced similar predictive accuracies across the studied traits. Within-site GS prediction accuracies with models trained on EBVs were high (RR-BLUP: 0.79–0.91 and GRR: 0.80–0.91), and were generally similar to the multi-site (RR-BLUP: 0.83–0.91, GRR: 0.83–0.91) and multi-site to single-site predictive accuracies (RR-BLUP: 0.79–0.92, GRR: 0.79–0.92). Cross-site predictions were surprisingly high, with predictive accuracies within a similar range (RR-BLUP: 0.79–0.92, GRR: 0.78–0.91). Height at 12 years was deemed the earliest acceptable age at which accurate predictions can be made concerning future height (age-age) and wood density (trait-trait). Using DEBVs reduced the accuracies of all cross-validation procedures dramatically, indicating that the models were tracking pedigree (family means), rather than marker-QTL LD.

Conclusions

While GS models’ prediction accuracies were high, the main driving force was the pedigree tracking rather than LD. It is likely that many more markers are needed to increase the chance of capturing the LD between causal genes and markers.

Growth gains from selective breeding in a spruce hybrid zone do not compromise local adaptation to climate

Hybrid zones contain extensive standing genetic variation that facilitates rapid responses to selection. The Picea glauca × Picea engelmannii hybrid zone in western Canada is the focus of tree breeding programs that annually produce ~90 million reforestation seedlings. Understanding the direct and indirect effects of selective breeding on adaptive variation is necessary to implement assisted gene flow (AGF) polices in Alberta and British Columbia that match these seedlings with future climates. We decomposed relationships among hybrid ancestry, adaptive traits, and climate to understand the implications of selective breeding for climate adaptations and AGF strategies. The effects of selection on associations among hybrid index estimated from ~6,500 SNPs, adaptive traits, and provenance climates were assessed for ~2,400 common garden seedlings. Hybrid index differences between natural and selected seedlings within breeding zones were small in Alberta (average +2%), but larger and more variable in BC (average −7%, range −24% to +1%), slightly favoring P. glauca ancestry. The average height growth gain of selected seedlings over natural seedlings within breeding zones was 36% (range 12%–86%). Clines in growth with temperature‐related variables were strong, but differed little between selected and natural populations. Seedling hybrid index and growth trait associations with evapotranspiration‐related climate variables were stronger in selected than in natural seedlings, indicating possible preadaptation to drier future climates. Associations among cold hardiness, hybrid ancestry, and cold‐related climate variables dominated signals of local adaptation and were preserved in breeding populations. Strong hybrid ancestry–phenotype–climate associations suggest that AGF will be necessary to match interior spruce breeding populations with shifting future climates. The absence of antagonistic selection responses among traits and maintenance of cold adaptation in selected seedlings suggests breeding populations can be safely redeployed using AGF prescriptions similar to those of natural populations.

A Guide to Genome-Wide Association Mapping in Plants

Genome-wide association studies (GWAS) have developed into a valuable approach for identifying the genetic basis of phenotypic variation. In this article, we provide an overview of the design, analysis, and interpretation of GWAS. First, we present results from simulations that explore key elements of experimental design as well as considerations for collecting the relevant genomic and phenotypic data. Next, we outline current statistical methods and tools used for GWA analyses and discuss the inclusion of covariates to account for population structure and the interpretation of results. Given that many false positive associations will occur in any GWA analysis, we highlight strategies for prioritizing GWA candidates for further statistical and empirical validation. While focused on plants, the material we cover is also applicable to other systems. © 2017 by John Wiley & Sons, Inc.

Advances in ecological genomics in forest trees and applications to genetic resources conservation and breeding

Forest trees are an unparalleled group of organisms in their combined ecological, economic and societal importance. With widespread distributions, predominantly random mating systems and large population sizes, most tree species harbour extensive genetic variation both within and among populations. At the same time, demographic processes associated with Pleistocene climate oscillations and land-use change have affected contemporary range-wide diversity and may impinge on the potential for future adaptation. Understanding how these adaptive and neutral processes have shaped the genomes of trees species is therefore central to their management and conservation. As for many other taxa, the advent of high-throughput sequencing methods is expected to yield an understanding of the interplay between the genome and environment at a level of detail and depth not possible only a few years ago. An international conference entitled 'Genomics and Forest Tree Genetics' was held in May 2016, in Arcachon (France), and brought together forest geneticists with a wide range of research interests to disseminate recent efforts that leverage contemporary genomic tools to probe the population, quantitative and evolutionary genomics of trees. An important goal of the conference was to discuss how such data can be applied to both genome-enabled breeding and the conservation of forest genetic resources under land use and climate change. Here, we report discoveries presented at the meeting and discuss how the ecological genomic toolkit can be used to address both basic and applied questions in tree biology.

Capturing Darwin's dream

Evolutionary biologists from Darwin forward have dreamed of having data that would elucidate our understanding of evolutionary history and the diversity of life. Sequence capture is a relatively old DNA technology, but its use is growing rapidly due to advances in (i) massively parallel DNA sequencing approaches and instruments, (ii) massively parallel bait construction, (iii) methods to identify target regions and (iv) sample preparation. We give a little historical context to these developments, summarize some of the important advances reported in this special issue and point to further advances that can be made to help fulfill Darwin's dream.