247 research outputs found
Fortissat Science Alliance podcast: Layla Mathieson
No full textLayla Mathieson was an EPSRC/MRC OPTIMA CDT PhD student studying optical medical imaging alongside an integrated Masters in healthcare innovation and entrepreneurship at the University of Edinburgh. She took part in the Fortissat Science Alliance podcast recordings in September 2021.What is the Fortissat Science Alliance?The Fortissat Science Alliance was a Wellcome Trust & Children In Need "Curiosity" project. This scheme provided informal STEM learning opportunities for young people who attended the community centre Getting Better Together Shotts (GBT Shotts) between 2019 and 2023. Due to the COVID-19 pandemic, deliveries had to pivot online so the podcast was founded. These recordings were made via Zoom with warm-up STEM activities sent to every young person in advance, along with a profile page for each researcher, so that they were relaxed and able to ask excellent questions.Link to episode on Spotify.Depending on the broadcast date, podcast deliveries were co-sponsored by Glasgow Science Festival, EXPLORATHON 2021, or EXPLORATHON 2022/23.For the duration of the project, it was supported jointly by Children in Need and the Wellcome Trust. In 2021, EXPLORATHON episodes were supported by the European Commission [grant agreement ID 101036101]. In 2022-23, EXPLORATHON episodes were supported by the Engineering & Physical Sciences Research Council [grant number EP/X020894/1]. Layla was supported by the EPSRC/MRC Centre for Doctoral Training in Optical Medical Imaging (OPTIMA).Author contributions to contentLayla Mathieson was the guest featured on this episode. Rebecca Hay was the youth worker coordinating the young people who conducted the interviews as well as co-editing and broadcasting the recordings. Iain Hamilton co-edited the episodes. Kirsty Ross was the STEM consultant for the project and uploaded completed episodes to Figshare.</p
Mingrelian SNP Genotype Data
No full text<p>This dataset contains data from 645,337 single nucleotide polymorphisms (SNPs) that were genotyped on GenoChip 2+ microarrays. The SNP data were ascertained from the mtDNA, Y-chromosome and autosomes for each individual, depending on their biological sex. In total, 5,205 mtDNA and 10,272 Y-chromosome SNPs were extracted from the array data. These data files have been uploaded as .csv files and also be uploaded as plink-formatted files. Details about the analysis of the SNP data can be found in the associated manuscript:</p><p>Theodore G Schurr, Ramaz Shengelia, Michel Shamoon-Pour, David Chitanava, Shorena Laliashvili, Irma Laliashvili, Redate Kibret, Yanu Kume-Kangkolo, Irakli Akhvlediani, Lia Bitadze, Iain Mathieson, Aram Yardumian, Genetic Analysis of Mingrelians Reveals Long-Term Continuity of Populations in Western Georgia (Caucasus), <i>Genome Biology and Evolution</i>, 2023; evad198, <a href="https://doi.org/10.1093/gbe/evad198">https://doi.org/10.1093/gbe/evad198</a></p>
Imputed data from for predicting skeletal stature using ancient DNA
No full textThese are the three imputed genotype datasets from the following publication. Please consult the paper for details of the imputation approach, metadata for the samples, and the original data sources. These data are freely available but you should cite the original sources, as well as our paper.
Predicting skeletal stature using ancient DNA; Cox S, Moots HM, Stock JT, Shbat A, Bitarello B, Nicklisch N, Alt K, Haak W, Rosenstock E, Ruff CB, Mathieson I; American Journal of Biological Anthropology, Jan 2022. https://doi.org/10.1002/ajpa.2442
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Genome-wide analysis identifies genetic effects on reproductive success and ongoing natural selection at the FADS locus
No full textThis manuscript represents a large collaboration with many "middle" contributing authors, including the author requesting this waiver (Daniel Chasman). Iain Mathieson, Felix R. Day, Nicola Barban, Felix C. Tropf, and David M. Brazel are the starred (equal contribution) first authors; Melinda C. Mills, and John R.B. Perry are the starred last authors. Corresponding: Iain Mathieson, Melinda C. Mills, and John Perry are the corresponding authors.
Please note that while the uploaded version of the manuscript has been accepted, there may still be changes that would be incorporated in the final publication.Identifying genetic determinants of reproductive success may highlight mechanisms underlying fertility and identify alleles under present-day selection. Using data in 785,604 individuals of European ancestry, we identified 43 genomic loci associated with either number of children ever born (NEB) or childlessness. These loci span diverse aspects of reproductive biology, including puberty timing, age at first birth, sex hormone regulation, endometriosis and age at menopause. Missense variants in ARHGAP27 were associated with higher NEB but shorter reproductive lifespan, suggesting a trade-off at this locus between reproductive ageing and intensity. Other genes implicated by coding variants include PIK3IP1, ZFP82 and LRP4, and our results suggest a new role for the melanocortin 1 receptor (MC1R) in reproductive biology. As NEB is one component of evolutionary fitness, our identified associations indicate loci under present-day natural selection. Integration with data from historical selection scans highlighted an allele in the FADS1/2 gene locus that has been under selection for thousands of years and remains so today. Collectively, our findings demonstrate that a broad range of biological mechanisms contribute to reproductive success.Accepted Manuscrip
Genome-wide patterns of selection in 230 ancient Eurasians
No full textMathieson, Iain et al.Ancient DNA makes it possible to observe natural selection directly by analysing samples from populations before, during and after adaptation events. Here we report a genome-wide scan for selection using ancient DNA, capitalizing on the largest ancient DNA data set yet assembled: 230 West Eurasians who lived between 6500 and 300 bc, including 163 with newly reported data. The new samples include, to our knowledge, the first genome-wide ancient DNA from Anatolian Neolithic farmers, whose genetic material we obtained by extracting from petrous bones, and who we show were members of the population that was the source of Europe’s first farmers. We also report a transect of the steppe region in Samara between 5600 and 300 bc, which allows us to identify admixture into the steppe from at least two external sources. We detect selection at loci associated with diet, pigmentation and immunity, and two independent episodes of selection on height.I.M. was supported by the Human Frontier Science Program LT001095/2014-L. C.G. was supported by the Irish Research Council for Humanities and Social Sciences (IRCHSS). F.G. was supported by a grant of the Netherlands Organization for Scientific Research, no. 380-62-005. A.K., P.K. and O.M. were supported by RFBR no. 15-06-01916 and RFH no. 15-11-63008 and O.M. by a state grant of the Ministry of Education and Science of the Russia Federation no. 33.1195.2014/k. J.K. was supported by ERC starting grant APGREID and DFG grant KR 4015/1-1. K.W.A. was supported by DFG grant AL 287 / 14-1. C.L.-F. was supported by a BFU2015-64699-P grant from the Spanish government. W.H. and B.L. were supported by Australian Research Council DP130102158. R.P. was supported by ERC starting grant ADNABIOARC (263441), and an Irish Research Council ERC support grant. D.R. was supported by US National Science Foundation HOMINID grant BCS-1032255, US National Institutes of Health grant GM100233, and the Howard Hughes Medical Institute.Peer reviewe
Late Upper Palaeolithic hunter-gatherers in the Central Mediterranean: New archaeological and genetic data from the Late Epigravettian burial Oriente C (Favignana, Sicily)
No full textGrotta d’Oriente, a small coastal cave located on the island of Favignana (Sicily, Italy) is a key site for the study
of the early human colonization of Sicily. The individual known as Oriente C was found in the lower portion of
an anthropogenic deposit containing typical local Late Upper Palaeolithic (Late Epigravettian) stone assemblages.
Two radiocarbon dates on charcoal from the deposit containing the burial are consistent with the archaeological
context and refer Oriente C to a period spanning about 14,200–13,800 cal. BP. Anatomical features
are similar to those of Late Upper Palaeolithic populations of the Mediterranean and show some affinity with
Palaeolithic individuals of San Teodoro (Messina, Sicily). Here we present new ancient DNA data from Oriente C.
Our results, confirming previous genetic analysis, suggest a substantial genetic homogeneity among Late
Epigravettian hunter-gatherer populations of Central Mediterranean, presumably as a consequence of continuous
gene flow among different groups, or a range expansion following the Last Glacial Maximum (LGM)
Genes in space: selection, association and variation in spatially structured populations
No full textSpatial structure in a population creates distinctive patterns in genetic data. There are two reasons to model this process. First, since the genetic structure of a population is induced by its historical spatial structure, it can be used to make inference about history and demography. Second, these models provide corrections to other analyses that are confounded by spatial structure. Since is it is now common to collect genome-wide data on many thousands of samples, a major challenge is to develop fast, scalable, approximate algorithms that can analyse these datasets. A practical approach is to focus on subsets of the data that are most informative, for example rare variants.
First we look at the problem of estimating selection coefficients in spatially structured populations. We demonstrate this approach using classical datasets of moth colour morph frequencies, and then use it in a model incorporating both ancient and modern DNA to estimate the selective advantage of one of the best known examples of local adaptation in humans, lactase persistence in Europeans.
Next, we turn to the problem of association studies in spatially structured populations. We demonstrate that rare variants are more confounded by non-genetic risk than common variants. Excess confounding is a consequence of the fact that rare variants are highly in- formative about recent ancestry and therefore, in a spatially explicit model, about location.
Finally, we use this insight into rare variants to develop methods for inference about population history using rare variant and haplotype sharing as simple summary statistics. These approaches are extremely fast and can be applied to genome-wide data on thousands of samples, yet they provide an accurate description of the history of a population, both identifying recent ancestry and estimating migration rates between subpopulations.</p
<i>FADS1</i>and the timing of human adaptation to agriculture
No full textAbstractVariation at theFADS1/FADS2gene cluster is functionally associated with differences in lipid metabolism and is often hypothesized to reflect adaptation to an agricultural diet. Here, we test the evidence for this relationship using both modern and ancient DNA data. We show that almost all the inhabitants of Europe carried the ancestral allele until the derived allele was introduced approximately 8,500 years ago by Early Neolithic farming populations. However, we also show that it was not under strong selection in these populations. We find that this allele, and other proposed agricultural adaptations atLCT/MCM6andSLC22A4, were not strongly selected until much later, perhaps as late as the Bronze Age. Similarly, increased copy number variation at the salivary amylase geneAMY1is not linked to the development of agriculture although, in this case, the putative adaptation precedes the agricultural transition. Our analysis shows that selection at theFADSlocus was not tightly linked to the initial introduction of agriculture and the Neolithic transition. Further, it suggests that the strongest signals of recent human adaptation in Europe did not coincide with the Neolithic transition but with more recent changes in environment, diet or efficiency of selection due to increases in effective population size.</jats:p
Mingrelian SNP Genotype Data
No full text<p>This dataset contains data from 645,337 single nucleotide polymorphisms (SNPs) that were genotyped on GenoChip 2+ microarrays. The SNP data were ascertained from the mtDNA, Y-chromosome and autosomes for each individual, depending on their biological sex. In total, 5,205 mtDNA and 10,272 Y-chromosome SNPs were extracted from the array data. These data files have been uploaded as .csv files and will also be uploaded as plink-formatted files by 15 November 2023. Details about the analysis of the SNP data can be found in the associated manuscript (see citation below).</p>
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