Patterns of genetic differentiation and the footprints of historical migrations in the Iberian Peninsula, bioRxiv, 2018-03-13

Genetic differences within or between human populations (population structure) has been studied using a variety of approaches over many years. Recently there has been an increasing focus on studying genetic differentiation at fine geographic scales, such as within countries. Identifying such structure allows the study of recent population history, and identifies the potential for confounding in association studies, particularly when testing rare, often recently arisen variants. The Iberian Peninsula is linguistically diverse, has a complex demographic history, and is unique among European regions in having a centuries-long period of Muslim rule. Previous genetic studies of Spain have examined either a small fraction of the genome or only a few Spanish regions. Thus, the overall pattern of fine-scale population structure within Spain remains uncharacterised. Here we analyse genome-wide genotyping array data for 1,413 Spanish individuals sampled from all regions of Spain. We identify extensive fine-scale structure, down to unprecedented scales, smaller than 10 Km in some places. We observe a major axis of genetic differentiation that runs from east to west of the peninsula. In contrast, we observe remarkable genetic similarity in the north-south direction, and evidence of historical north-south population movement. Finally, without making particular prior assumptions about source populations, we show that modern Spanish people have regionally varying fractions of ancestry from a group most similar to modern north Moroccans. The north African ancestry results from an admixture event, which we date to 860 - 1120 CE, corresponding to the early half of Muslim rule. Our results indicate that it is possible to discern clear genetic impacts of the Muslim conquest and population movements associated with the subsequent Reconquista.

biorxiv genomics 500+-users 2018

Why should mitochondria define species?, bioRxiv, 2018-03-08

More than a decade of DNA barcoding encompassing about five million specimens covering 100,000 animal species supports the generalization that mitochondrial DNA clusters largely overlap with species as defined by domain experts. Most barcode clustering reflects synonymous substitutions. What evolutionary mechanisms account for synonymous clusters being largely coincident with species? The answer depends on whether variants are phenotypically neutral. To the degree that variants are selectable, purifying selection limits variation within species and neighboring species may have distinct adaptive peaks. Phenotypically neutral variants are only subject to demographic processes—drift, lineage sorting, genetic hitchhiking, and bottlenecks. The evolution of modern humans has been studied from several disciplines with detail unique among animal species. Mitochondrial barcodes provide a commensurable way to compare modern humans to other animal species. Barcode variation in the modern human population is quantitatively similar to that within other animal species. Several convergent lines of evidence show that mitochondrial diversity in modern humans follows from sequence uniformity followed by the accumulation of largely neutral diversity during a population expansion that began approximately 100,000 years ago. A straightforward hypothesis is that the extant populations of almost all animal species have arrived at a similar result consequent to a similar process of expansion from mitochondrial uniformity within the last one to several hundred thousand years.

biorxiv evolutionary-biology 0-100-users 2018

A comparison of single-cell trajectory inference methods towards more accurate and robust tools, bioRxiv, 2018-03-06

AbstractUsing single-cell-omics data, it is now possible to computationally order cells along trajectories, allowing the unbiased study of cellular dynamic processes. Since 2014, more than 50 trajectory inference methods have been developed, each with its own set of methodological characteristics. As a result, choosing a method to infer trajectories is often challenging, since a comprehensive assessment of the performance and robustness of each method is still lacking. In order to facilitate the comparison of the results of these methods to each other and to a gold standard, we developed a global framework to benchmark trajectory inference tools. Using this framework, we compared the trajectories from a total of 29 trajectory inference methods, on a large collection of real and synthetic datasets. We evaluate methods using several metrics, including accuracy of the inferred ordering, correctness of the network topology, code quality and user friendliness. We found that some methods, including Slingshot, TSCAN and Monocle DDRTree, clearly outperform other methods, although their performance depended on the type of trajectory present in the data. Based on our benchmarking results, we therefore developed a set of guidelines for method users. However, our analysis also indicated that there is still a lot of room for improvement, especially for methods detecting complex trajectory topologies. Our evaluation pipeline can therefore be used to spearhead the development of new scalable and more accurate methods, and is available at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpgithub.comdynversedynverse>github.comdynversedynverse<jatsext-link>.To our knowledge, this is the first comprehensive assessment of trajectory inference methods. For now, we exclusively evaluated the methods on their default parameters, but plan to add a detailed parameter tuning procedure in the future. We gladly welcome any discussion and feedback on key decisions made as part of this study, including the metrics used in the benchmark, the quality control checklist, and the implementation of the method wrappers. These discussions can be held at github.comdynversedynverseissues.

biorxiv bioinformatics 100-200-users 2018

Meta-analysis of genome-wide association studies for height and body mass index in ∼700,000 individuals of European ancestry, bioRxiv, 2018-03-03

Genome-wide association studies (GWAS) stand as powerful experimental designs for identifying DNA variants associated with complex traits and diseases. In the past decade, both the number of such studies and their sample sizes have increased dramatically. Recent GWAS of height and body mass index (BMI) in ∼250,000 European participants have led to the discovery of ∼700 and ∼100 nearly independent SNPs associated with these traits, respectively. Here we combine summary statistics from those two studies with GWAS of height and BMI performed in ∼450,000 UK Biobank participants of European ancestry. Overall, our combined GWAS meta-analysis reaches N∼700,000 individuals and substantially increases the number of GWAS signals associated with these traits. We identified 3,290 and 716 near-independent SNPs associated with height and BMI, respectively (at a revised genome-wide significance threshold of p&lt;1 × 10−8), including 1,185 height-associated SNPs and 554 BMI-associated SNPs located within loci not previously identified by these two GWAS. The genome-wide significant SNPs explain ∼24.6% of the variance of height and ∼5% of the variance of BMI in an independent sample from the Health and Retirement Study (HRS). Correlations between polygenic scores based upon these SNPs with actual height and BMI in HRS participants were 0.44 and 0.20, respectively. From analyses of integrating GWAS and eQTL data by Summary-data based Mendelian Randomization (SMR), we identified an enrichment of eQTLs amongst lead height and BMI signals, prioritisting 684 and 134 genes, respectively. Our study demonstrates that, as previously predicted, increasing GWAS sample sizes continues to deliver, by discovery of new loci, increasing prediction accuracy and providing additional data to achieve deeper insight into complex trait biology. All summary statistics are made available for follow up studies.

biorxiv genetics 200-500-users 2018

 

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