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opencc-zeroOct 2021View details →

Contributions of genetic and non-genetic sources to variation in cooperative behaviour in a cooperative mammal

The evolution of cooperative behaviour is a major area of research among evolutionary biologists and behavioural ecologists, yet there are few estimates of its heritability or of its evolutionary potential and long-term studies of identifiable individuals are required to disentangle genetic and non-genetic components of cooperative behaviour. Here we use long-term data on over 1800 individually recognisable wild meerkats (Suricata suricatta) collected over 30 years and a multi-generational genetic pedigree to partition phenotypic variation in three cooperative behaviours (babysitting, pup feeding and sentinel behaviour) into individual, additive genetic and other sources, and to assess their repeatability and heritability. In addition to strong effects of sex, age and dominance status, we found significant repeatability in individual contributions to all three types of cooperative behaviour both within and across breeding seasons. Like most other studies of the heritability of social behaviour, we found that the heritability of cooperative behaviour was low. However, our analysis suggests that a substantial component of the repeatable individual differences in cooperative behaviour that we observed was a consequence of additive genetic variation. Our results consequently indicate that cooperative behaviour can respond to selection, and suggest scope for further exploration of the genetic basis of social behaviour.

opencc-by-4.0Oct 2022View details →

Association of genetic variation at the GJA5 locus with motor progression in Parkinson's

These are the GWAS summary statistics generated from the study described in the title

Fig. 7 in A new polymorphic species of Leptochelia (Crustacea: Tanaidacea) from Guinea Bissau, West Africa, with comments on genetic variation within Leptochelia

Fig. 7. Leptochelia africana sp. n., secondary male, paratype: (A) cheliped; (B) pereopod 1; (C) pereopod 2; (D) pereopod 3; (E) pereopod 4; (F) pereopod 5; (G) pereopod 6. Scale bar = 1.0 mm.

Fig. 3 in A new polymorphic species of Leptochelia (Crustacea: Tanaidacea) from Guinea Bissau, West Africa, with comments on genetic variation within Leptochelia

Fig. 3. Leptochelia africana sp. n., female, paratype: (A) cheliped; (B) pereopod 1; (C) pereopod 2; (D) pereopod 3; (E) pereopod 4; (F) pereopod 5; (G) pereopod 6; (H) pereopod 6, propodus/dactylus. Scale bars = 0.5 mm (A–G) and 0.1 mm (H).

Fig. 2 in A new polymorphic species of Leptochelia (Crustacea: Tanaidacea) from Guinea Bissau, West Africa, with comments on genetic variation within Leptochelia

Fig. 2. Leptochelia africana sp. n., female, paratype: (A) labrum, dorsal view; (B) same, lateral view; (C) left mandible; (D) right mandible; (E) labium; (F) maxillule; (G) maxilla; (H) maxilliped; (I) epignath. Scale bar = 0.1 mm.

Fig. 6 in A new polymorphic species of Leptochelia (Crustacea: Tanaidacea) from Guinea Bissau, West Africa, with comments on genetic variation within Leptochelia

Fig. 6. Leptochelia africana sp. n., secondary male, paratype: (A) antennule; (B) same, apex; (C) antenna; (D) labrum; (E) maxillule palp; (F) maxilliped; (G) epignath; (H) pleopod; (I) pleotelson/uropods. Scale bars = 0.5 mm (A, C, H, I) and 0.1 mm (B, D–G).

Fig. 1 in A new polymorphic species of Leptochelia (Crustacea: Tanaidacea) from Guinea Bissau, West Africa, with comments on genetic variation within Leptochelia

Fig. 1. Leptochelia africana sp. n., female: (A, B) holotype: (A) dorsal view, (B) lateral view; (C–F) paratype: (C) antennule, (D) antenna, (E) pleopod, (F) uropod. Scale bars = 1.0 mm (A, B) and 0.5 mm (C–F).

Fig. 8. Protanais ligniamator Larsen, 2006 in A new polymorphic species of Leptochelia (Crustacea: Tanaidacea) from Guinea Bissau, West Africa, with comments on genetic variation within Leptochelia

Fig. 8. Protanais ligniamator Larsen, 2006, SEM: (A) pleopod 1; (B) same, exopod, higher magnification.

Fig. 5 in A new polymorphic species of Leptochelia (Crustacea: Tanaidacea) from Guinea Bissau, West Africa, with comments on genetic variation within Leptochelia

Fig. 5. Leptochelia africana sp. n., primary male, paratype: (A) cheliped; (B) pereopod 1; (C) pereopod 2; (D) pereopod 3; (E) pereopod 4; (F) pereopod 5; (G) pereopod 6; (H) uropod. Scale bar = 0.5 mm.

Fig. 4 in A new polymorphic species of Leptochelia (Crustacea: Tanaidacea) from Guinea Bissau, West Africa, with comments on genetic variation within Leptochelia

Fig. 4. Leptochelia africana sp. n., male paratypes: (A) secondary male, lateral view; (B–J) primary male: (B) dorsal view, (C) lateral view, (D) antennule, (E) antenna, (F) labrum, (G) maxillule palp, (H) maxilliped, (I) epignath, (J) pleopod. Scale bars = 1.0 mm (A–C), 0.5 mm (D, E, J) and 0.1 mm (F–H).

opencc-zeroMar 2023View details →

Genetic variation in mouse islet Ca2+ oscillations reveals novel regulators of islet function

Insufficient insulin secretion to meet metabolic demand results in diabetes. The intracellular flux of Ca2+ into β-cells triggers insulin release. Since genetics strongly influences variation in islet secretory responses, we surveyed islet Ca2+ dynamics in eight genetically diverse mouse strains. We found high strain variation in response to four conditions: 1) 8 mM glucose; 2) 8 mM glucose plus amino acids; 3) 8 mM glucose, amino acids, plus 10nM GIP; and 4) 2 mM glucose. These stimuli interrogate β-cell function, α-cell to β-cell signaling, and incretin responses. We then correlated components of the Ca2+ waveforms to islet protein abundances in the same strains used for the Ca2+ measurements. To focus on proteins relevant to human islet function, we identified human orthologues of correlated mouse proteins that are proximal to glycemic-associated SNPs in human GWAS. Several orthologues have previously been shown to regulate insulin secretion (e.g. ABCC8, PCSK1, and GCK), supporting our mouse-to-human integration as a discovery platform. By integrating these data, we nominated novel regulators of islet Ca2+ oscillations and insulin secretion with potential relevance for human islet function. We also provide a resource for identifying appropriate mouse strains in which to study these regulators.

opencc-zeroApr 2023View details →

Genotype and genetic diversity data for: Contrasts in riverscape patterns of intraspecific genetic variation in a diverse Neotropical fish community of high conservation value

Spatial patterns in genetic variation compared across species provide information about the predictability of genetic diversity of natural populations and areas requiring conservation measures. Due to their remarkable fish diversity, rivers in Neotropical regions are ideal systems to confront theory with observations and would benefit greatly from such approaches given their increasing vulnerability to anthropogenic pressures. We used SNP data from 18 fish species with contrasting life-history traits, co-sampled across 12 sites in the Maroni – a major river system from the Guiana Shield – to compare patterns of intraspecific genetic variation and identify their underlying drivers. Analyses of covariance revealed a decrease in genetic diversity as distance from the river outlet increased for 5 of the 18 species, illustrating a pattern commonly observed in riverscapes for species with low-to-medium dispersal abilities. However, mean within-site genetic diversity was lowest in the two easternmost tributaries of the Upper Maroni and around an urbanized location downstream, indicating the need to address the potential influence of local pressures in these areas, such as goldmining or fishing. Finally, the relative influence of isolation by stream distance, isolation by discontinuous river flow and isolation by spatial heterogeneity in effective size on pairwise genetic differentiation varied across species. Species with similar dispersal and reproductive guilds did not necessarily display shared patterns of population structure. Increasing the knowledge of specific life history traits and ecological requirements of fish species in these remote areas should help further understand factors that influence their current patterns of genetic variation.

opencc-zeroApr 2023View details →

Data for: Natural genetic variation in a dopamine receptor is associated with variation in female fertility in Drosophila melanogaster

Fertility is a major component of fitness but its genetic architecture remains poorly understood. Using a full diallel cross of 50 Drosophila melanogaster Genetic Reference Panel inbred lines with whole genome sequences, we found substantial genetic variation in fertility largely attributable to females. We mapped genes associated with variation in female fertility by genome-wide association analysis of common variants in the fly genome. Validation of candidate genes by RNAi knockdown confirmed the role of the dopamine 2-like receptor (Dop2R) in promoting egg laying. We replicated the Dop2R effect in an independently collected productivity dataset and showed that the effect of the Dop2R variant was mediated in part by regulatory gene expression variation. This study demonstrates the strong potential of genome-wide association analysis in this diverse panel of inbred strains and subsequent functional analyses for understanding the genetic architecture of fitness traits.

opencc-zeroApr 2023View details →

Data from: Strong selection is poorly aligned with genetic variation in Ipomoea hederacea

The multivariate evolution of populations is the result of the interactions between natural selection, drift, and the underlying genetic structure of the traits involved. Covariances among traits bias responses to selection, and the multivariate axis which describes the greatest genetic variation is expected to be aligned with patterns of divergence across populations. An exception to this expectation is when selection acts on trait combinations lacking genetic variance, which limits evolutionary change. Here we used a common garden field experiment of individuals from 57 populations of Ipomoea hederacea to characterize linear and nonlinear selection on five quantitative traits in the field. We then formally compare patterns of selection to previous estimates of within-population genetic covariance structure (the G-matrix) and population divergence in these traits. We found that selection is poorly aligned with previous estimates of genetic covariance structure and population divergence. In addition, the trait combinations favoured by selection were generally lacking genetic variation, possessing approximately 15-30% as much genetic variation as the most variable combination of traits. Our results suggest that patterns of population divergence are likely the result of the interplay between adaptive responses, correlated response, and selection favoring traits lacking genetic variation.

opencc-zeroJun 2023View details →

Data from: Additive genetic and environmental variation interact to shape the dynamics of seasonal migration in a wild bird population

Dissecting joint micro-evolutionary and plastic responses to environmental perturbations requires quantifying interacting components of genetic and environmental variation underlying expression of key traits. This ambition is particularly challenging for phenotypically discrete traits where multiscale decompositions are required to reveal non-linear transformations of underlying genetic and environmental variation into phenotypic variation, and when effects must be estimated from incomplete field observations. We devised a joint multistate capture-recapture and quantitative genetic animal model and fitted this model to full-annual-cycle resighting data from partially-migratory European shags (Gulosus aristotelis) to estimate key components of genetic, environmental and phenotypic variance in the ecologically critical discrete trait of seasonal migration versus residence. We demonstrate non-negligible additive genetic variance in latent liability for migration, resulting in detectable micro-evolutionary responses following two episodes of strong survival selection. Further, liability-scale additive genetic effects interacted with substantial permanent individual and temporary environmental effects to generate complex non-additive effects on expressed phenotypes, causing substantial intrinsic gene-by-environment interaction variance on the phenotypic scale. Our analyses therefore reveal how temporal dynamics of partial seasonal migration arise from combinations of instantaneous micro-evolution and within-individual phenotypic consistency, and highlight how intrinsic phenotypic plasticity could expose genetic variation underlying discrete traits to complex forms of selection.

opencc-by-4.0Dec 2022View details →

Data and Code for Publication "Inferring human neutral genetic variation from craniodental phenotypes"

Data and code for publication: H. Rathmann et al., Inferring human neutral genetic variation from craniodental phenotypes. PNAS Nexus. The repository contains: <ul> <li>“R code for DP-DG analysis.txt”: R code for testing levels of neutral evolutionary signals preserved in five craniodental data types: cranial metrics, dental metrics, cranial non-metric traits, dental non-metric traits, and craniodental metrics and non-metric traits combined.</li> </ul> <ul> <li>“Cranial metric data.csv”: Dataset consisting of 37 cranial metric variables for 26 worldwide modern populations, provided in a comma-separated values file format. The data were collected by T. Hanihara and originally presented in the publication titled: T. Hanihara, Comparison of craniofacial features of major human groups. Am. J. Phys. Anthropol. 99, 389–412 (1996) (<a href="https://doi.org/10.1002/(SICI)1096-8644(199603)99:3%3c389::AID-AJPA3%3e3.0.CO;2-S">https://doi.org/10.1002/(SICI)1096-8644(199603)99:3<389::AID-AJPA3>3.0.CO;2-S</a>).</li> </ul> <ul> <li>“Dental metric data.csv”: Dataset comprising 28 dental metric variables for 26 worldwide modern populations, provided in a comma-separated values file format. The data were collected by T. Hanihara and originally presented in the publication titled: T. Hanihara, H. Ishida, Metric dental variation of major human populations. Am. J. Phys. Anthropol. 128, 287–298 (2005) (<a href="https://doi.org/10.1002/ajpa.20080">https://doi.org/10.1002/ajpa.20080</a>).</li> </ul> <ul> <li>“Cranial non-metric trait data.csv”: Dataset consisting of 24 cranial non-metric trait variables for 26 worldwide modern populations, provided in a comma-separated values file format. The data were collected for the most part by T. Hanihara and presented in the publication titled: T. Hanihara, H. Ishida, Y. Dodo, Characterization of biological diversity through analysis of discrete cranial traits. Am. J. Phys. Anthropol. 121, 241–251 (2003) (<a href="https://doi.org/10.1002/ajpa.10233">https://doi.org/10.1002/ajpa.10233</a>).</li> </ul> <ul> <li>“Dental non-metric trait data.csv”: Dataset comprising 25 dental non-metric trait variables for 26 worldwide modern populations, provided in a comma-separated values file format. The data were collected by C. G. Turner II, G. R. Scott, and J. D. Irish. This individual-level dataset was artificially created from population-level trait frequency information presented in the publications: G. R. Scott, J. D. Irish, Human Tooth Crown and Root Morphology (Cambridge University Press, 2017) (<a href="https://doi.org/10.1017/9781316156629">https://doi.org/10.1017/9781316156629</a>); and: J. D. Irish, A. Morez, L. Girdland Flink, E. L. W. Phillips, G. R. Scott, Do dental nonmetric traits actually work as proxies for neutral genomic data? Some answers from continental- and global-level analyses. Am. J. Phys. Anthropol. 172, 347–375 (2020) (<a href="https://doi.org/10.1002/ajpa.24052">https://doi.org/10.1002/ajpa.24052</a>).</li> </ul> <ul> <li>“SNP data.txt”: Dataset comprising 8,821 SNP markers for 26 worldwide modern populations, provided in a genepop file format. The data were obtained from various published sources: I. Lazaridis et al., Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature 513, 409–413 (2014) (<a href="https://doi.org/10.1038/nature13673">https://doi.org/10.1038/nature13673</a>); P. Qin, M. Stoneking, Denisovan ancestry in east Eurasian and native American populations. Mol. Biol. Evol. 32, 2665–2674 (2015) (<a href="https://doi.org/10.1093/molbev/msv141">https://doi.org/10.1093/molbev/msv141</a>); P. Skoglund et al., Genomic insights into the peopling of the Southwest Pacific. Nature 538, 510–513 (2016) (<a href="https://doi.org/10.1038/nature19844">https://doi.org/10.1038/nature19844</a>); M. R. Nelson et al., The Population Reference Sample, POPRES: a resource for population, disease, and pharmacological genetics research. Am. J. Hum. Genet. 83, 347–358 (2008) (<a href="https://doi.org/10.1016/j.ajhg.2008.08.005">https://doi.org/10.1016/j.ajhg.2008.08.005</a>); J. K. Pickrell, J. K. Pritchard, Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet. 8, e1002967 (2012) (<a href="https://doi.org/10.1371/journal.pgen.1002967">https://doi.org/10.1371/journal.pgen.1002967</a>); A. Bergström et al., Insights into human genetic variation and population history from 929 diverse genomes. Science 367 (2020) (<a href="https://doi.org/10.1126/science.aay5012">https://doi.org/10.1126/science.aay5012</a>); B. M. Henn et al., Genomic ancestry of North Africans supports back-to-Africa migrations. PLoS Genet. 8, e1002397 (2012) (<a href="https://doi.org/10.1371/journal.pgen.1002397">https://doi.org/10.1371/journal.pgen.1002397</a>); S. Mallick et al., The Simons Genome Diversity Project: 300 genomes from 142 diverse populations. Nature 538, 201–206 (2016) (<a href="https://doi.org/10.1038/nature18964">https://doi.org/10.1038/nature18964</a>); Lao et al., Correlation between genetic and geographic structure in Europe. Curr. Biol. 18, 1241–1248 (2008) (<a href="https://doi.org/10.1016/j.cub.2008.07.049">https://doi.org/10.1016/j.cub.2008.07.049</a>); and M. Lipson et al., Population Turnover in Remote Oceania Shortly after Initial Settlement. Curr. Biol. 28, 1157-1165.e7 (2018) (<a href="https://doi.org/10.1016/j.cub.2018.02.051">https://doi.org/10.1016/j.cub.2018.02.051</a>).</li> </ul> For population and variable names and abbreviations, see Supplementary Information in: H. Rathmann et al., Inferring human neutral genetic variation from craniodental phenotypes. PNAS Nexus.

opencc-by-4.0Sep 2023View details →

Genetic variation of Scots pine in Eurasia: Impact of postglacial recolonisation and human-mediated gene transfer

The dataset comprises nuclear microsatellite data (PCR products lengths) used in the paper "Genetic variation of Scots pine in Eurasia: Impact of postglacial recolonisation and human-mediated gene transfer". The pdf file includes the list of populations. Abstract: Scots pine (Pinus sylvestris L.) seems to be a species of low conservation priority because it has a very wide Eurasian distribution and plays a leading role in many forest tree breeding programs. Nevertheless, considering its economic value, long breeding history, range fragmentation, and increased mortality, which is also projected in the future, it requires a more detailed description of its genetic resources. Our goal was to compare patterns of genetic variation found in biparentally inherited nuclear DNA with previous research carried out with mitochondrial and chloroplast DNA due to their different modes of transmission. We analysed the genetic variation and relationships of 60 populations across the distribution of Scots pine in Eurasia (1,262 individuals) using a set of nuclear DNA markers. We confirmed the high genetic variation and low genetic differentiation of Scots pine spanning large geographical areas. Nevertheless, there was a clear division between European and Asian gene pools. The genetic variation of Asian populations was lower than in Europe. Spain, Turkey, and the Apennines constituted separate gene pools, the latter showing the lowest values of all genetic variation parameters. The analyses showed that most populations experienced genetic bottlenecks in the distant past. Ongoing admixture was found in Fennoscandia. Our results suggest a much simpler recolonization history of the Asian than European part of the Scots pine distribution, with migration from limited sources and possible founder effects. Eastern European stands seem to have descended from the Urals refugium. It appears that Central Europe and Fennoscandia share at least one glacial refugium in the Balkans and migrants from higher latitudes, as well as from southeastern regions. The low genetic structure between Central Europe and Fennoscandia, along with their high genetic admixture, may result at least partially from past human activities related to the transfer of germplasm in the 19th and early 20th centuries. In light of ongoing climate changes and projected range shifts of Scots pine, conservation strategies are especially needed for marginal and isolated stands of this species. Genetic research should also be complemented in parts of the species distribution that have thus far been poorly studied.

publicFeb 2024View details →

Structural genomic variation in the inbred Scandinavian wolf population contributes to the realized genetic load but is positively affected by immigration

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publicDec 2024View details →

Genetic variation in parasite avoidance, yet no evidence for constitutive fitness costs

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