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opencc-zeroJan 2024View details →

Main model fits and substitution rate predictions for: A quantitative genetic model of background selection in humans

Across the human genome, there are large-scale fluctuations in genetic diversity caused by the indirect effects of selection. This can be thought of as a "linked selection signal" that reflects the impact of selection varying according to the placement of functional regions and recombination rates along the genome. Previous work has shown that negative selection against the steady influx of new deleterious mutations into conserved regions is the predominant mode of selection in humans. However, the theoretic model that underpins these results, classic Background Selection theory, is only applicable when new mutations are so deleterious that they cannot fix in the population. Here, we develop a statistical method based on a quantitative genetics view of the linked selection, which models the effects of weak draft created according to how polygenic additive fitness variance is distributed along the genome. We use a recent model that jointly predicts the equilibrium fitness variance and substitution rates due to both strong and weakly deleterious mutations, we estimate the distribution of fitness effects (DFE) and mutation rate across three human populations. While our model can accommodate weaker selection, we initially find evidence across three human populations of very strong selection against deleterious mutations consistent with previous work. However, the corollary predicted substitution rates for conserved regions are unreasonably low, and in disagreement with observed rates. We hypothesize this could be due to selected sites experiencing a further diminished population size due to selective interference. When we account for this in our method, we find evidence of weakly deleterious mutations in conserved regions which brings the predicted substitution rate into agreement with observations. However, these models lead to implausibly large mutation rate estimates. Overall, while our model of the genomic linked selection signal brings us a step towards uniting population and quantitative genetic selection models with the substitution process, our work suggests considerable uncertainty remains about the processes generating fitness variance in humans.

Figure 1 in Why we should develop guidelines and quantitative standards for using genetic data to delimit subspecies for data-poor organisms like cetaceans

Figure 1. Depiction of the divergence of lineages with four times (T1–T4) chosen to illustrate different levels of biological organization. At T1 the yellow lineage is found across the distribution and although there are likely Demographically Independent Populations (DIPs) that differ in frequencies of the blue, yellow, and red lineages, there are no discontinuities. At T2 some lineages may be diagnosable but likely do not yet appear to be separate lineages. At T3 three groups (the blue/green, yellow, and orange/red lineages) meet the subspecies definition (they are diagnosable and appear to be diverging separately). The divergence level is not sufficient that reconvergence can be ruled out. Between T3 and T4, barriers to gene flow change such that the yellow lineage comes into contact with the blue/green and red-dominated lineages. Blue has diverged in a manner by which gene flow does not resume and the green/yellow lineage dies out. The yellow lineage reconverges and persists alongside the red lineage with a small level of gene flow (orange). At T4 the blue lineage is a species evolving separately from the yellow/red species. The yellow/red species has two subspecies that are both diagnosable and partially diverged.

Figure 3 in Guidelines and quantitative standards to improve consistency in cetacean subspecies and species delimitation relying on molecular genetic data

Figure 3. Flow diagram for subspecies delineation using combined quantitative and qualitative standards. The threshold values assume the user is evaluating a case relying on mtDNA control region data. Percent Diagnosable (PD) is the smallest strata-specific correct classification score in a given comparison (e.g., PD50 in two-strata comparisons in Archer et al. 2017). The second box in the second row (other evidence to meet subspecies definition) allows for subspecies delineation when both conditions are not met using mtDNA. This box could be used either for the case when one condition is met and one unmet or when both just barely miss meeting the standards. For example, consider the case with PD <95% and dA> 0.004. Diagnosability could be achieved with morphological data or nuclear data that are sufficient for subspecies but not for full species.

Figure 2. A in Guidelines and quantitative standards to improve consistency in cetacean subspecies and species delimitation relying on molecular genetic data

Figure 2. A comparison of the pairs of populations (red triangles), subspecies (green squares) and species (blue circles) estimated by Rosel et al. (2017a). Net nucleotide divergence (dA) is shown on a natural log scale to better illustrate differences between the pairwise comparisons at low levels of divergence. Bars show the central 95th-pecentile of the estimate distributions. The solid vertical line at dA = 0.020 delimits all but one species and correctly excludes all subspecies pairs. The vertical dashed line at dA = 0.004 delimits all populations from the higher taxonomic levels and correctly delimits seven of eleven subspecies. The horizontal dashed lines are two potential thresholds for percent diagnosable (80% and 95%) that are discussed in the text.

opencc-by-4.0Aug 2019View details →

Fig. 2 in Quantitative genetics of gastrointestinal strongyle burden and associated body condition in feral horses

Fig. 2. Predicted relationship between an individual's annual location and a) faecal egg count (measured as the natural logarithm of eggs per gram (EPG) + 25) and b) body condition. Location is scaled to a mean of 0 and standard deviation of 1, therefore 0 represents the centre of the island with −2 at the far west and 2 at the far east. The fitted line comes from the full univariate animal model in each case. In both cases, overlap between points is represented by darker point colour. In 2b. points have been jittered along the y axis to ease visualisation.

opencc-zeroOct 2021View details →

Data and code for: Plastic and quantitative genetic divergence mirror environmental gradients among wild, fragmented populations of Impatiens capensis

Premise of the study: Habitat fragmentation generates molecular genetic divergence among isolated populations but few studies have assessed phenotypic divergence and fitness in populations where the genetic consequences of habitat fragmentation are known. Phenotypic divergence could reflect plasticity, local adaptation, and/or genetic drift. Methods: We examined patterns and potential drivers of phenotypic divergence among 12 populations of jewelweed (Impatiens capensis Meerb.) that show strong molecular genetic signals of isolation and drift among fragmented habitats. We measured morphological and reproductive traits in both maternal plants within natural populations and their self-fertilized progeny grown together in a common garden. We also quantified environmental divergence between home sites and the common garden. Key results: Populations with less molecular genetic variation expressed less maternal phenotypic variation. Progeny in the common garden converged in phenotypes relative to their wild mothers but retained among-population differences in morphology, survival, and reproduction. Among-population phenotypic variance was 3-10x greater in home sites than in the common garden for 6 of 7 morphological traits measured. Patterns of phenotypic divergence paralleled environmental gradients in ways suggestive of adaptation. Progeny resembled their mothers less as the environmental distance between their home site and the common garden increased. Conclusions: Despite strong molecular signatures of isolation and drift, phenotypic differences among these Impatiens populations appear to reflect both adaptive quantitative genetic divergence and plasticity. Quantifying the extent of local adaptation and plasticity and how these covary with molecular and phenotypic variation help us predict when populations may lose their adaptive capacity.

publicOct 2021View details →

Data and code for: Plastic and quantitative genetic divergence mirror environmental gradients among wild, fragmented populations of Impatiens capensis

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publicSep 2024View details →

Data from: Age-dependent shaping of the social environment in a long-lived seabird – A quantitative genetic approach

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publicJun 2025View details →

Data from: The genetic architecture of quantitative variation in the self-incompatibility response within Phlox drummondii (Polemoniaceae)

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publicJan 2024View details →

Main model fits and substitution rate predictions for: A quantitative genetic model of background selection in humans

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opencc-zeroJul 2020View details →

Data from: The coevolution of male and female genitalia in a mammal: a quantitative genetic insight

Male genitalia are among the most phenotypically diverse morphological traits, and sexual selection is widely accepted as being responsible for their evolutionary divergence. Studies of house mice suggest that the shape of the baculum (penis bone) affects male reproductive fitness and experimentally imposed postmating sexual selection has been shown to drive divergence in baculum shape across generations. Much less is known of the morphology of female genitalia and its coevolution with male genitalia. In light of this, we used a paternal half-sibling design to explore patterns of additive genetic variation and covariation underlying baculum shape and female vaginal tract size in house mice (Mus musculus domesticus). We applied a landmark-based morphometrics approach to measure baculum size and shape in males and the length of the vaginal tract and width of the cervix in females. Our results reveal significant additive genetic variation in house mouse baculum morphology and cervix width, as well as evidence for genetic covariation between male and female genital measures. Our data thereby provide novel insight into the potential for the coevolutionary divergence of male and female genital traits in a mammal.

opencc-zeroJul 2020View details →

Data from: Can dominance genetic variance be ignored in evolutionary quantitative genetic analyses of wild populations?

Accurately estimating genetic variance components is important for studying evolution in the wild. Empirical work on domesticated and wild outbred populations suggests that dominance genetic variance represents a substantial part of genetic variance, and theoretical work predicts that ignoring dominance can inflate estimates of additive genetic variance. Whether this issue is pervasive in natural systems is unknown, because we lack estimates of dominance variance in wild populations obtained in situ. Here, we estimate dominance and additive genetic variance, maternal variance, and other sources of non-genetic variance in 8 traits measured in over 9000 wild nestlings linked through a genetically resolved pedigree. We find that dominance variance, when estimable, does not statistically differ from zero and represents a modest amount (2-36%) of genetic variance. Simulations show that 1) inferences of all variance components for an average trait are unbiased; 2) the power to detect dominance variance is low; 3) ignoring dominance can mildly inflate additive genetic variance and heritability estimates but such inflation becomes substantial when maternal effects are also ignored. These findings hence suggest that dominance is a small source of phenotypic variance in the wild and highlight the importance of proper model construction for accurately estimating evolutionary potential.

opencc-zeroDec 2019View details →

Data from: Quantitative genetics of the use of conspecific and heterospecific social cues for breeding site choice

Social information use for decision-making is common and affects ecological and evolutionary processes, including social aggregation, species coexistence and cultural evolution. Despite increasing ecological knowledge on social information use, very little is known about its genetic basis and therefore its evolutionary potential. Genetic variation in a trait affecting an individual's social and non-social environment may have important implications for population dynamics, interspecific interactions and for expression of other, environmentally plastic traits. We estimated repeatability, additive genetic variance and heritability of the use of conspecific and heterospecific social cues (abundance and breeding success) for breeding site choice in a population of wild collared flycatchers Ficedula albicollis. Repeatability was found for two social cues: previous year conspecific breeding success and previous year heterospecific abundance. Yet, additive genetic variances for these two social cues, and thus heritabilities, were low. This suggests that most of the phenotypic variation in the use of social cues and resulting conspecific and heterospecific social environment experienced by individuals in this population stems from phenotypic plasticity. Given the important role of social information use on ecological and evolutionary processes, more studies on genetic versus environmental determinism of social information use are needed.

opencc-zeroFeb 2024View details →

Dissecting the genetic architecture of quantitative traits using genome-wide identity-by-descent sharing

Additive and dominance genetic variances underlying the expression of quantitative traits are important quantities for predicting short-term responses to selection, but they are notoriously challenging to estimate in most non-model wild populations. Specifically, large-sized or panmictic populations may be characterized by low variance in genetic relatedness among individuals which in turn, can prevent accurate estimation of quantitative genetic parameters. We used estimates of genome-wide identity-by-descent (IBD) sharing from autosomal SNP loci to estimate quantitative genetic parameters for ecologically important traits in nine-spined sticklebacks (Pungitius pungitius) from a large, outbred population. Using empirical and simulated datasets, with varying sample sizes and pedigree complexity, we assessed the performance of different crossing schemes in estimating additive genetic variance and heritability for all traits. We found that low variance in relatedness characteristic of wild outbred populations with high migration rate can impair the estimation of quantitative genetic parameters and bias heritability estimates downwards. On the other hand, the use of a half-sib/full-sib design allowed precise estimation of genetic variance components, and revealed significant additive variance and heritability for all measured traits, with negligible dominance contributions. Genome-partitioning and QTL mapping analyses revealed that most traits had a polygenic basis and were controlled by genes at multiple chromosomes. Furthermore, different QTL contributed to variation in the same traits in different populations suggesting heterogenous underpinnings of parallel evolution at the phenotypic level. Our results provide important guidelines for future studies aimed at estimating adaptive potential in the wild, particularly for those conducted in outbred large-sized populations.

zenodo36/100

Minimal dataset for the manuscript "Better together against genetic heterogeneity: a sex-combined joint main and interaction analysis of 290 quantitative traits in the UK Biobank".

Dataset "lin2024-sex_combined_interaction-association_signifincant_in_one_or_more_tests-summary.txt" is a minimal dataset to reproduce the figures and tables in the manuscript "Better together against genetic heterogeneity: a sex-combined joint main and interaction analysis of 290 quantitative traits in the UK Biobank".  To generate this dataset, see "https://github.com/BoxiLin/t2meta" Steps 0, 1. This dataset is the input for Steps 2, 3, 4, 5 to generate Figures 1-3 and Table 2-3.   ##### Column information ######################## The following columns are annotations on each variant in the GWAS, calculated across the analysis subset of 361,194 samples by the Neale lab: code: Phenotype identifier in the form of "[UKB Data field]_raw" variant: Unique variant identifier in the form "chr:pos:ref:alt", where "ref" is aligned to the forward strand. chr: Chromosome of the variant. pos: Position of the variant in GRCh37 coordinates. rsid: rs ID ref: Reference allele on the forward strand. alt: Alternate allele (not necessarily minor allele). p_hwe: Hardy-Weinberg p-value. info: Imputation INFO score as provided by UK Biobank.   The following columns are sex-stratified test statistics calculated by the Neale lab: minor_allele.x: Minor allele (AF < 0.5) in the female GWAS  minor_AF.x: Minor allele frequency in the female GWAS  beta.x: Estimated effect size of alt allele in the female GWAS  se.x: Estimated standard error of beta in the female GWAS tstat.x: t-statistic of beta estimate (= beta/se) in the female GWAS  pval.x: p-value of beta significance test in the female GWAS  minor_allele.y: Minor allele (AF < 0.5) in the male GWAS  minor_AF.y: Minor allele frequency in the male GWAS  beta.y: Estimated effect size of alt allele in the male GWAS  se.y: Estimated standard error of beta in the male GWAS  tstat.y: t-statistic of beta estimate (= beta/se) in the male GWAS  pval.y: p-value of beta significance test in the male GWAS    The following columns are sex-combined test statistics calculated in our analysis: T.I: test statsitic for interaction effect-only  p.T.I:  p-value of the interaction effect-only test  TSG.L:  test statsitic for inverse variance weighted meta-analysis p.TSG.L: p-value of the inverse variance weighted meta-analysis TSG.Q: test statsitic for the omnibus meta-analysis p.TSG.Q: p-value for the omnibus meta-analysis

opencc-by-4.0Mar 2024View details →

zenodo36/100

Figure 1 in Guidelines and quantitative standards to improve consistency in cetacean subspecies and species delimitation relying on molecular genetic data

Figure 1. Guidelines for studies of cetacean taxonomy based on genetic data.

opencc-zeroApr 2022View details →

The quantitative genetics of fitness in a wild seabird

Additive genetic variance in fitness is a prerequisite for adaptive evolution, as a trait must be genetically correlated with fitness to evolve. Despite its relevance, additive genetic variance in fitness has not often been estimated in nature. Here, we investigate additive genetic variance in lifetime and annual fitness components in common terns (Sterna hirundo). Using 28 years of data comprising ca. 6000 pedigreed individuals, we find that additive genetic variances in the Zero-inflated and Poisson components of lifetime fitness were effectively zero, but estimated with high uncertainty. Similarly, additive genetic variances in adult annual reproductive success and survival did not differ from zero, but were again associated with high uncertainty. Simulations suggested that we would be able to detect additive genetic variances as low as 0.05 for the Zero-inflated component of fitness, but not for the Poisson component, for which adequate statistical power would require c. two more decades (four tern generations) of data collection. As such, our study suggests heritable variance in common tern fitness to be rather low if not zero, shows how studying the quantitative genetics of fitness in natural populations remains challenging, and highlights the importance of maintaining long-term individual-based studies of natural populations.

opencc-zeroDec 2020View details →

Quantitative trait locus mapping reveals an independent genetic basis for joint divergence in leaf function, life-history, and floral traits between scarlet monkeyflower (Mimulus cardinalis) populations

PREMISE Across taxa, vegetative and floral traits that vary along a fast-slow life-history axis are often correlated with leaf functional traits arrayed along the leaf economics spectrum, suggesting a constrained set of adaptive trait combinations. Such broad-scale convergence may arise from genetic constraints imposed by pleiotropy (or tight linkage) within species, or from natural selection alone. Understanding the genetic basis of trait syndromes and their components is key to distinguishing these alternatives and predicting evolution in novel environments. METHODS We used a line-cross approach and quantitative trait locus (QTL) mapping to characterize the genetic basis of twenty leaf functional/physiological, life history, and floral traits in hybrids between annualized and perennial populations of scarlet monkeyflower (Mimulus cardinalis). RESULTS We mapped both single and multi-trait QTLs for life history, leaf function and reproductive traits, but found no evidence of genetic co-ordination across categories. A major QTL for three leaf functional traits (thickness, photosynthetic rate, and stomatal resistance) suggests that a simple shift in leaf anatomy may be key to adaptation to seasonally dry habitats. CONCLUSIONS Our results suggest that the co-ordination of resource-acquisitive leaf physiological traits with a fast life history and more selfing mating system results from environmental selection rather than functional or genetic constraint. Independent assortment of distinct trait modules, as well as a simple genetic basis to leaf physiological traits associated with drought escape, may facilitate adaptation to changing climates.