Biology subjects

Wohns, A. W.

Publications and source records attributed to Wohns, A. W..

7 recordsLinked to original sources

bioRxiv2023

A general and efficient representation of ancestral recombination graphs

As a result of recombination, adjacent nucleotides can have different paths of genetic inheritance and therefore the genealogical trees for a sample of DNA sequences vary along the genome. The structure capturing the details of these intricately interwoven paths of inheritance is referred to as an ancestral recombination graph (ARG). Classical formalisms have focused on mapping coalescence and recombination events to the nodes in an ARG. This approach is out of step with modern developments, which do not represent genetic inheritance in terms of these events or explicitly infer them. We present a simple formalism that defines an ARG in terms of specific genomes and their intervals of genetic inheritance, and show how it generalises these classical treatments and encompasses the outputs of recent methods. We discuss nuances arising from this more general structure, and argue that it forms an appropriate basis for a software standard in this rapidly growing field.

genetics↗

bioRxiv2023

Medieval social landscape through the genetic history of Cambridgeshire before and after the Black Death

The extent of the devastation of the Black Death pandemic (1346-53) on European populations is known from documentary sources and its bacterial source illuminated by studies of ancient pathogen DNA. What has remained less understood is the effect of the pandemic on human mobility and genetic diversity at local scale in the context of the social stratification of medieval communities. Here we study 275 newly reported ancient genomes from later medieval and post-medieval Cambridgeshire, from individuals buried before, during, and after the Black Death. The majority of individuals examined had local genetic ancestries. Consistent with the function of the institutions, we found a lack of close relatives among the friars and the inmates of the hospital in contrast to their abundance in general urban and rural parish communities. Accounting for the genetic component for height accentuates the disparities between social groups in stature estimated from long bones, as a proxy for health and the quality of life. While we detect long-term shifts in local genetic ancestry in Cambridgeshire that either pre- or postdate the Black Death, we find no evidence of major changes in genetic ancestry nor, in contrast to recent claims, higher differentiation of immune loci between cohorts living before and after the Black Death.

genetics↗

bioRxiv2022

Expanding the stdpopsim species catalog, and lessons learned forrealistic genome simulations

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic data sets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and to the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than three-fold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

bioinformatics↗

bioRxiv2022

Extremely sparse models of linkage disequilibrium in ancestrally diverse association studies

Linkage disequilibrium (LD) is the correlation among nearby genetic variants. In genetic association studies, LD is often modeled using massive local correlation matrices, but this approach is slow, especially in ancestrally diverse studies. Here, we introduce LD graphical models (LDGMs), which are an extremely sparse and efficient representation of LD. LDGMs are derived from genome-wide genealogies; statistical relationships among alleles in the LDGM correspond to genealogical relationships among haplotypes. We publish LDGMs and ancestry specific LDGM precision matrices for 18 million common SNPs (MAF>1%) in five ancestry groups, validate their accuracy, and demonstrate order-of-magnitude improvements in runtime for commonly used LD matrix computations. We implement an extremely fast multi-ancestry polygenic prediction method, BLUPx-ldgm, which performs better than a similar method based on the reference LD correlation matrix. LDGMs will enable sophisticated methods that scale to ancestrally genetic association data across millions of variants and individuals.

genetics↗

bioRxiv2021

Efficient ancestry and mutation simulation with msprime 1.0

Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this necessity, a large number of specialised simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and tskit library. We summarise msprimes many features, and show that its performance is excellent, often many times faster and more memory efficient than specialised alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.

genetics↗

bioRxiv2021

A unified genealogy of modern and ancient genomes

The sequencing of modern and ancient genomes from around the world has revolutionised our understanding of human history and evolution1,2. However, the general problem of how best to characterise the full complexity of ancestral relationships from the totality of human genomic variation remains unsolved. Patterns of variation in each data set are typically analysed independently, and often using parametric models or data reduction techniques that cannot capture the full complexity of human ancestry3,4. Moreover, variation in sequencing technology5,6, data quality7 and in silico processing8,9, coupled with complexities of data scale10, limit the ability to integrate data sources. Here, we introduce a non-parametric approach to inferring human genealogical history that overcomes many of these challenges and enables us to build the largest genealogy of both modern and ancient humans yet constructed. The genealogy provides a lossless and compact representation of multiple datasets, addresses the challenges of missing and erroneous data, and benefits from using ancient samples to constrain and date relationships. Using simulations and empirical analyses, we demonstrate the power of the method to recover relationships between individuals and populations, as well as to identify descendants of ancient samples. Finally, we show how applying a simple non-parametric estimator of ancestor geographical location to the inferred genealogy recapitulates key events in human history. Our results demonstrate that whole-genome genealogies are a powerful means of synthesising genetic data and provide rich insights into human evolution.

genomics↗

bioRxiv2018

Inferring the ancestry of everyone

A central problem in evolutionary biology is to infer the full genealogical history of a set of DNA sequences. This history contains rich information about the forces that have influenced a sexually reproducing species. However, existing methods are limited: the most accurate is unable to cope with more than a few dozen samples. With modern genetic data sets rapidly approaching millions of genomes, there is an urgent need for efficient inference methods to exploit such rich resources. We introduce an algorithm to infer whole-genome history which has comparable accuracy to the state-of-the-art but can process around four orders of magnitude more sequences. Additionally, our method results in an \"evolutionary encoding\" of the original sequence data, enabling efficient access to genealogies and calculation of genetic statistics over the data. We apply this technique to human data from the 1000 Genomes Project, Simons Genome Diversity Project and UK Biobank, showing that the genealogies we estimate are both rich in biological signal and efficient to process.

evolutionary biology↗