Relatedness coefficients and their applications for triplets and quartets of genetic markers.

Relatedness coefficients which seek the identity-by-descent of genetic markers are described. The markers are in groups of two, three or four, and if four, can consist of two pairs. It is essential to use cumulants (not moments) for four-marker-gene probabilities, as the covariance of homozygosity, used in four-marker applications, can only be described with cumulants. A covariance of homozygosity between pairs of markers arises when populations follow a mixture distribution. Also, the probability of four markers all identical-by-descent equals the normalized fourth cumulant. In this article, a "genetic marker" generally represents either a gene locus or an allele at a locus. Applications of three marker coefficients mainly involve conditional regression, and applications of four marker coefficients can involve identity disequilibrium. Estimation of relatedness using genetic marker data is discussed. However, three- and four-marker estimators suffer from statistical and numerical problems, including higher statistical variance, complexity of estimation formula, and singularity at some intermediate allele frequencies.

Variation and Natural Heritability of Blueberry Floral Volatiles.

Vaccinium corymbosum (highbush blueberry) in British Columbia relies on honeybee pollination for a reliable fruit set. As floral volatiles may help explain pollinator preference for blueberry, we surveyed components of variation for volatiles using gas chromatography-mass spectrometry (GC/MS). Principal component analysis of GC chromatogram peaks revealed a grouping of cultivars by a biosynthetic pathway that also corresponds with their known pedigree. To identify genetic variance, we identified 34 chemicals with adequate sample sizes. We estimated "natural heritability" (using uncontrolled crosses in natural environments) in two ways: (1) as "clonal repeatability," which is equivalent to broad-sense heritability and is an upper bound for narrow-sense heritability, and (2) "marker-based heritability," which serves as a lower bound for narrow-sense heritability. Both methods indicate that heritability is relatively low, ca. 15%, and variable among traits. This is expected as the floral volatile release is changeable and dependent on environmental conditions. It might be possible to use highly heritable volatiles for breeding.

Performing parentage analysis for polysomic inheritances based on allelic phenotypes.

Polyploidy poses several problems for parentage analysis. We present a new polysomic inheritance model for parentage analysis based on genotypes or allelic phenotypes to solve these problems. The effects of five factors are simultaneously accommodated in this model: (1) double-reduction, (2) null alleles, (3) negative amplification, (4) genotyping errors and (5) self-fertilization. To solve genotyping ambiguity (unknown allele dosage), we developed a new method to establish the likelihood formulas for allelic phenotype data and to simultaneously include the effects of our five chosen factors. We then evaluated and compared the performance of our new method with three established methods by using both simulated data and empirical data from the cultivated blueberry (Vaccinium corymbosum). We also developed and compared the performance of two additional estimators to estimate the genotyping error rate and the sample rate. We make our new methods freely available in the software package polygene, at http://github.com/huangkang1987/polygene.

Partial correlation analysis of transcriptomes helps detangle the growth and defense network in spruce.

In plants, there can be a trade-off between resource allocations to growth vs defense. Here, we use partial correlation analysis of gene expression to make inferences about the nature of this interaction. We studied segregating progenies of Interior spruce subject to weevil attack. In a controlled experiment, we measured pre-attack plant growth and post-attack damage with several morphological measures, and profiled transcriptomes of 188 progeny. We used partial correlations of individual transcripts (expressed sequence tags, ESTs) with pairs of growth/defense traits to identify important nodes and edges in the inferred underlying gene network, for example, those pairs of growth/defense traits with high mutual correlation with a single EST transcript. We give a method to identify such ESTs. A terpenoid ABC transporter gene showed strongest correlations (P = 0.019); its transcript represented a hub within the compact 166-member gene-gene interaction network (P = 0.004) of the negative genetic correlations between growth and subsequent pest attack. A small 21-member interaction network (P = 0.004) represented the uncovered positive correlations. Our study demonstrates partial correlation analysis identifies important gene networks underlying growth and susceptibility to the weevil in spruce. In particular, we found transcripts that strongly modify the trade-off between growth and defense, and allow identification of networks more central to the trade-off.

The challenge of separating signatures of local adaptation from those of isolation by distance and colonization history: The case of two white pines.

Accurately detecting signatures of local adaptation using genetic-environment associations (GEAs) requires controlling for neutral patterns of population structure to reduce the risk of false positives. However, a high degree of collinearity between climatic gradients and neutral population structure can greatly reduce power, and the performance of GEA methods in such case is rarely evaluated in empirical studies. In this study, we attempted to disentangle the effects of local adaptation and isolation by environment (IBE) from those of isolation by distance (IBD) and isolation by colonization from glacial refugia (IBC) using range-wide samples in two white pine species. For this, SNPs from 168 genes, including 52 candidate genes for growth and phenology, were genotyped in 133 and 61 populations of Pinus strobus and P. monticola, respectively. For P. strobus and using all 153 SNPs, climate (IBE) did not significantly explained among-population variation when controlling for IBD and IBC in redundancy analyses (RDAs). However, 26 SNPs were significantly associated with climate in single-locus GEA analyses (Bayenv2 and LFMM), suggesting that local adaptation took place in the presence of high gene flow. For P. monticola, we found no evidence of IBE using RDAs and weaker signatures of local adaptation using GEA and FST outlier tests, consistent with adaptation via phenotypic plasticity. In both species, the majority of the explained among-population variation (69 to 96%) could not be partitioned between the effects of IBE, IBD, and IBC. GEA methods can account differently for this confounded variation, and this could explain the small overlap of SNPs detected between Bayenv2 and LFMM. Our study illustrates the inherent difficulty of taking into account neutral structure in natural populations and the importance of sampling designs that maximize climatic variation, while minimizing collinearity between climatic gradients and neutral structure.

Estimating Relatedness in the Presence of Null Alleles.

Studies of genetics and ecology often require estimates of relatedness coefficients based on genetic marker data. However, with the presence of null alleles, an observed genotype can represent one of several possible true genotypes. This results in biased estimates of relatedness. As the numbers of marker loci are often limited, loci with null alleles cannot be abandoned without substantial loss of statistical power. Here, we show how loci with null alleles can be incorporated into six estimators of relatedness (two novel). We evaluate the performance of various estimators before and after correction for null alleles. If the frequency of a null allele is <0.1, some estimators can be used directly without adjustment; if it is >0.5, the potency of estimation is too low and such a locus should be excluded. We make available a software package entitled PolyRelatedness v1.6, which enables researchers to optimize these estimators to best fit a particular data set.

Reduced Genetic Diversity and Increased Dispersal in Guigna (Leopardus guigna) in Chilean Fragmented Landscapes.

Landscape fragmentation is often a major cause of species extinction as it can affect a wide variety of ecological processes. The impact of fragmentation varies among species depending on many factors, including their life-history traits and dispersal abilities. Felids are one of the groups most threatened by fragmented landscapes because of their large home ranges, territorial behavior, and low population densities. Here, we model the impacts of habitat fragmentation on patterns of genetic diversity in the guigna (Leopardus guigna), a small felid that is closely associated with the heavily human-impacted temperate rainforests of southern South America. We assessed genetic variation in 1798 base pairs of mitochondrial DNA sequences, 15 microsatellite loci, and 2 sex chromosome genes and estimated genetic diversity, kinship, inbreeding, and dispersal in 38 individuals from landscapes with differing degrees of fragmentation on Chiloé Island in southern Chile. Increased fragmentation was associated with reduced genetic diversity, but not with increased kinship or inbreeding. However, in fragmented landscapes, there was a weaker negative correlation between pairwise kinship and geographic distance, suggesting increased dispersal distances. These results highlight the importance of biological corridors to maximize connectivity in fragmented landscapes and contribute to our understanding of the broader genetic consequences of habitat fragmentation, especially for forest-specialist carnivores.

Contrasting patterns of genetic diversity across the ranges of Pinus monticola and P. strobus: a comparison between eastern and western North American postglacial colonization histories.

UNLABELLED: • Premises of the study: Understanding the influence of recent glacial and postglacial periods on species' distributions is key for predicting the effects of future environmental changes. We investigated the influence of two physiographic landscapes on population structure and postglacial colonization of two white pine species of contrasting habitats: P. monticola, which occurs in the highly mountainous region of western North America, and P. strobus, which occurs in a much less mountainous area in eastern North America.• METHODS: To characterize the patterns of genetic diversity and population structure across the ranges of both species, 158 and 153 single nucleotide polymorphism (SNP) markers derived from expressed genes were genotyped on range-wide samples of 61 P. monticola and 133 P. strobus populations, respectively.• KEY RESULTS: In P. monticola, a steep latitudinal decrease in genetic diversity likely resulted from postglacial colonization involving rare long-distance dispersal (LDD) events. In contrast, no geographic patterns of diversity were detected in P. strobus, suggesting recolonization via a gradually advancing front or frequent LDD events. For each species, structure analyses identified two distinct southern and northern genetic groups that likely originated from two different glacial lineages. At a finer scale, and for the two species, smaller subgroups were detected that could be remnants of cryptic refugia.• CONCLUSION: During postglacial colonization, the western and eastern North American landscapes had different impacts on genetic signatures in P. monticola compared with P. strobus. We discuss the importance of our findings for conservation programs and predictions of species' response to climate change.

Estimating pairwise relatedness between individuals with different levels of ploidy.

Estimates of relatedness coefficients, based on genetic marker data, are often necessary for studies of genetics and ecology. Whilst many estimates based on method-of-moment or maximum-likelihood methods exist for diploid organisms, no such estimators exist for organisms with multiple ploidy levels, which occur in some insect and plant species. Here, we extend five estimators to account for different levels of ploidy: one relatedness coefficient estimator, three coefficients of coancestry estimators and one maximum-likelihood estimator. We use arrhenotoky (when unfertilized eggs develop into haploid males) as an example in evaluations of estimator performance by Monte Carlo simulation. Also, three virtual sex-determination systems are simulated to evaluate their performances for higher levels of ploidy. Additionally, we used two real data sets to test the robustness of these estimators under actual conditions. We make available a software package, PolyRelatedness, for other researchers to apply to organisms that have various levels of ploidy.

Insights into conifer giga-genomes.

Insights from sequenced genomes of major land plant lineages have advanced research in almost every aspect of plant biology. Until recently, however, assembled genome sequences of gymnosperms have been missing from this picture. Conifers of the pine family (Pinaceae) are a group of gymnosperms that dominate large parts of the world's forests. Despite their ecological and economic importance, conifers seemed long out of reach for complete genome sequencing, due in part to their enormous genome size (20-30 Gb) and the highly repetitive nature of their genomes. Technological advances in genome sequencing and assembly enabled the recent publication of three conifer genomes: white spruce (Picea glauca), Norway spruce (Picea abies), and loblolly pine (Pinus taeda). These genome sequences revealed distinctive features compared with other plant genomes and may represent a window into the past of seed plant genomes. This Update highlights recent advances, remaining challenges, and opportunities in light of the publication of the first conifer and gymnosperm genomes.

Evolution of gene structure in the conifer Picea glauca: a comparative analysis of the impact of intron size.

BACKGROUND: A positive relationship between genome size and intron length is observed across eukaryotes including Angiosperms plants, indicating a co-evolution of genome size and gene structure. Conifers have very large genomes and longer introns on average than most plants, but impacts of their large genome and longer introns on gene structure has not be described. RESULTS: Gene structure was analyzed for 35 genes of Picea glauca obtained from BAC sequencing and genome assembly, including comparisons with A. thaliana, P. trichocarpa and Z. mays. We aimed to develop an understanding of impact of long introns on the structure of individual genes. The number and length of exons was well conserved among the species compared but on average, P. glauca introns were longer and genes had four times more intronic sequence than Arabidopsis, and 2 times more than poplar and maize. However, pairwise comparisons of individual genes gave variable results and not all contrasts were statistically significant. Genes generally accumulated one or a few longer introns in species with larger genomes but the position of long introns was variable between plant lineages. In P. glauca, highly expressed genes generally had more intronic sequence than tissue preferential genes. Comparisons with the Pinus taeda BACs and genome scaffolds showed a high conservation for position of long introns and for sequence of short introns. A survey of 1836 P. glauca genes obtained by sequence capture mostly containing introns <1 Kbp showed that repeated sequences were 10× more abundant in introns than in exons. CONCLUSION: Conifers have large amounts of intronic sequence per gene for seed plants due to the presence of few long introns and repetitive element sequences are ubiquitous in their introns. Results indicate a complex landscape of intron sizes and distribution across taxa and between genes with different expression profiles.

A pairwise relatedness estimator for polyploids.

Studies in genetics and ecology often require estimates of relatedness coefficients based on genetic marker data. Many diploid estimators have been developed using either method-of-moments or maximum-likelihood estimates. However, there are no relatedness estimators for polyploids. The development of a moment estimator for polyploids with polysomic inheritance, which simultaneously incorporates the two-gene relatedness coefficient and various 'higher-order' coefficients, is described here. The performance of the estimator is compared to other estimators under a variety of conditions. When using a small number of loci, the estimator is biased because of an increase in ill-conditioned matrices. However, the estimator becomes asymptotically unbiased with large numbers of loci. The ambiguity of polyploid heterozygotes (when balanced heterozygotes cannot be distinguished from unbalanced heterozygotes) is also considered; as with low numbers of loci, genotype ambiguity leads to bias. A software, PolyRelatedness, implementing this method and supporting a maximum ploidy of 8 is provided.

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.

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

UNLABELLED: 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.

Genetical genomics identifies the genetic architecture for growth and weevil resistance in spruce.

In plants, relationships between resistance to herbivorous insect pests and growth are typically controlled by complex interactions between genetically correlated traits. These relationships often result in tradeoffs in phenotypic expression. In this study we used genetical genomics to elucidate genetic relationships between tree growth and resistance to white pine terminal weevil (Pissodes strobi Peck.) in a pedigree population of interior spruce (Picea glauca, P. engelmannii and their hybrids) that was growing at Vernon, B.C. and segregating for weevil resistance. Genetical genomics uses genetic perturbations caused by allelic segregation in pedigrees to co-locate quantitative trait loci (QTLs) for gene expression and quantitative traits. Bark tissue of apical leaders from 188 trees was assayed for gene expression using a 21.8K spruce EST-spotted microarray; the same individuals were genotyped for 384 SNP markers for the genetic map. Many of the expression QTLs (eQTL) co-localized with resistance trait QTLs. For a composite resistance phenotype of six attack and oviposition traits, 149 positional candidate genes were identified. Resistance and growth QTLs also overlapped with eQTL hotspots along the genome suggesting that: 1) genetic pleiotropy of resistance and growth traits in interior spruce was substantial, and 2) master regulatory genes were important for weevil resistance in spruce. These results will enable future work on functional genetic studies of insect resistance in spruce, and provide valuable information about candidate genes for genetic improvement of spruce.

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.

Population genetics of the white-phased "Spirit" black bear of British Columbia.

The Spirit (or Kermode) bear is a white-phased black bear found on the northwest coast of British Columbia, and is one of the most striking color polymorphisms found in mammals. A single nucleotide polymorphism at the melanocortin 1 receptor gene (mc1r) locus is the cause of this recessive w variant. Recently, evidence suggests that the white color provides a selective advantage during salmon hunting. Here we examine the effects of favorable selection, gene flow, genetic drift, and positive-assortative mating in an effort to understand the establishment and maintenance of this polymorphism and the observed heterozygote deficiency for mc1r but not for microsatellite loci. It appears that genetic drift was important in the establishment of the w allele and that the selective advantage was important to counteract immigration from populations without the w allele. Positive-assortative mating can result in a deficiency of heterozygotes but needs to be quite high to result in the large deficiency of heterozygotes observed, suggesting that other factors must also be contributing. Examination of population genetic factors, singly and jointly, provides insight into the establishment and maintenance of this unusual polymorphism.

Slow but not low: genomic comparisons reveal slower evolutionary rate and higher dN/dS in conifers compared to angiosperms.

BACKGROUND: Comparative genomics can inform us about the processes of mutation and selection across diverse taxa. Among seed plants, gymnosperms have been lacking in genomic comparisons. Recent EST and full-length cDNA collections for two conifers, Sitka spruce (Picea sitchensis) and loblolly pine (Pinus taeda), together with full genome sequences for two angiosperms, Arabidopsis thaliana and poplar (Populus trichocarpa), offer an opportunity to infer the evolutionary processes underlying thousands of orthologous protein-coding genes in gymnosperms compared with an angiosperm orthologue set. RESULTS: Based upon pairwise comparisons of 3,723 spruce and pine orthologues, we found an average synonymous genetic distance (dS) of 0.191, and an average dN/dS ratio of 0.314. Using a fossil-established divergence time of 140 million years between spruce and pine, we extrapolated a nucleotide substitution rate of 0.68 × 10(-9) synonymous substitutions per site per year. When compared to angiosperms, this indicates a dramatically slower rate of nucleotide substitution rates in conifers: on average 15-fold. Coincidentally, we found a three-fold higher dN/dS for the spruce-pine lineage compared to the poplar-Arabidopsis lineage. This joint occurrence of a slower evolutionary rate in conifers with higher dN/dS, and possibly positive selection, showcases the uniqueness of conifer genome evolution. CONCLUSIONS: Our results are in line with documented reduced nucleotide diversity, conservative genome evolution and low rates of diversification in conifers on the one hand and numerous examples of local adaptation in conifers on the other hand. We propose that reduced levels of nucleotide mutation in large and long-lived conifer trees, coupled with large effective population size, were the main factors leading to slow substitution rates but retention of beneficial mutations.

Estimating selfing rates from reconstructed pedigrees using multilocus genotype data.

Several methods have been developed to estimate the selfing rate of a population from a sample of individuals genotyped for several marker loci. These methods can be based on homozygosity excess (or inbreeding), identity disequilibrium, progeny array (PA) segregation or population assignment incorporating partial selfing. Progeny array-based method is generally the best because it is not subject to some assumptions made by other methods (such as lack of misgenotyping, absence of biparental inbreeding and presence of inbreeding equilibrium), and it can reveal other facets of a mixed-mating system such as patterns of shared paternity. However, in practice, it is often difficult to obtain PAs, especially for animal species. In this study, we propose a method to reconstruct the pedigree of a sample of individuals taken from a monoecious diploid population practicing mixed mating, using multilocus genotypic data. Selfing and outcrossing events are then detected when an individual derives from identical parents and from two distinct parents, respectively. Selfing rate is estimated by the proportion of selfed offspring in the reconstructed pedigree of a sample of individuals. The method enjoys many advantages of the PA method, but without the need of a priori family structure, although such information, if available, can be utilized to improve the inference. Furthermore, the new method accommodates genotyping errors, estimates allele frequencies jointly and is robust to the presence of biparental inbreeding and inbreeding disequilibrium. Both simulated and empirical data were analysed by the new and previous methods to compare their statistical properties and accuracies.

Defense mechanisms against herbivory in Picea: sequence evolution and expression regulation of gene family members in the phenylpropanoid pathway.

BACKGROUND: In trees, a substantial amount of carbon is directed towards production of phenolics for development and defense. This metabolic pathway is also a major factor in resistance to insect pathogens in spruce. In such gene families, environmental stimuli may have an important effect on the evolutionary fate of duplicated genes, and different expression patterns may indicate functional diversification. RESULTS: Gene families in spruce (Picea) have expanded to superfamilies, including O-methyltransferases, cytochrome-P450, and dirigents/classIII-peroxidases. Neo-functionalization of superfamily members from different clades is reflected in expression diversification. Genetical genomics can provide new insights into the genetic basis and evolution of insect resistance in plants. Adopting this approach, we merged genotype data (252 SNPs in a segregating pedigree), gene expression levels (for 428 phenylpropanoid-related genes) and measures of susceptibility to Pissodes stobi, using a partial-diallel crossing-design with white spruce (Picea glauca). Thirty-eight expressed phenylpropanoid-related genes co-segregated with weevil susceptibility, indicating either causative or reactive effects of these genes to weevil resistance. We identified eight regulatory genomic regions with extensive overlap of quantitative trait loci from susceptibility and growth phenotypes (pQTLs) and expression QTL (eQTL) hotspots. In particular, SNPs within two different CCoAOMT loci regulate phenotypic variation from a common set of 24 genes and three resistance traits. CONCLUSIONS: Pest resistance was associated with individual candidate genes as well as with trans-regulatory hotspots along the spruce genome. Our results showed that specific genes within the phenylpropanoid pathway have been duplicated and diversified in the conifer in a process fundamentally different from short-lived angiosperm species. These findings add to the information about the role of the phenylpropanoid pathway in the evolution of plant defense mechanisms against insect pests and provide substantial potential for the functional characterization of several not yet resolved alternative pathways in plant defenses.