Biology subjects

Platt, A.

Publications and source records attributed to Platt, A..

6 recordsLinked to original sources

bioRxiv2018

Adaptive landscape of protein variation in human exomes

The human genome contains hundreds of thousands of missense mutations. However, only a handful of these variants are known to be adaptive, which implies that adaptation through protein sequence change is an extremely rare phenomenon in human evolution. Alternatively, existing methods may lack the power to pinpoint adaptive variation. We have developed and applied an Evolutionary Probability Approach (EPA) to discover candidate adaptive polymorphisms (CAPs) through the discordance between allelic evolutionary probabilities and their observed frequencies in human populations. EPA reveals thousands of missense CAPs, which suggest that a large number of previously optimal alleles had experienced a reversal of fortune in the human lineage. We explored non-adaptive mechanisms to explain CAPs, including the effects of demography, mutation rate variability, and negative and positive selective pressures in modern humans. Our analyses suggest that a large proportion of CAP alleles have increased in frequency due to beneficial selection. This conclusion is supported by the facts that a vast majority of adaptive missense variants discovered previously in humans are CAPs, and that hundreds of CAP alleles are protective in genotype-phenotype association data. Our integrated phylogenomic and population genetic EPA approach predicts the existence of thousands of signatures of non-neutral evolution in the human proteome. We expect this collection to be enriched in beneficial variation. EPA approach can be applied to discover candidate adaptive variation in any protein, population, or species for which allele frequency data and reliable multispecies alignments are available.

evolutionary biology↗

bioRxiv2018

Age distributions of rare lineages reveal recent demographic history and selection

The age of an allele of a given frequency offers insight into both its function and origin, and the distribution of ages of alleles in a population conveys significant information about its history. The rarer the allele the more likely it is to reveal functional biological insight and the more recent the historical revelation. By measuring the length of the haplotype shared between an individual carrying a rare variant and its closest relative not carrying the variant we are able to approximate the age of the variant and can apply this method even when only a single copy of a variant has been sampled in a population. Applying this technique to rare variants in a large population sample from the United Kingdom, we identify historical migration from West Africa approximately 400 years ago, evidence of direct selection against novel protein-altering rare variants in individual biological pathways, continued negative frequency dependent selection on protein-altering variants in olfactory transducers and the innate immune system, and map the impact of background selection on the most recent portions of the sample genealogy.

genomics↗

bioRxiv2017

Recent African gene flow responsible for excess of old rare genetic variation in Great Britain

Population genomic studies can reveal the allele frequencies at millions of SNPs, with the numbers of observed low frequency SNPs increasing as more genomes are sequenced. Rare alleles tend to be younger than common alleles and are especially useful for studying demographic history, selection and heritability1,2. However, allele frequency can be a poor proxy for allele age, as genetic drift and natural selection can lead to alleles that are both rare and old. In order to allow joint assessments of allele frequency and allele age, a new estimator of allele age was developed that can be applied to variants of the lowest observed frequencies (singletons). By examining the geographic and age distribution of very rare variants in a large genomic sample from the UK3, we identify new evidence of gene flow from Africa into the ancestors of the modern UK population. A substantial proportion of variants with observed frequencies as low as 1.4 x 10-4 are orders of magnitude older than can be explained without African gene flow and are found at much higher frequencies within modern African populations. We estimate that African populations contributed approximately 1.2% of the UK gene pool and did so approximately 400 years ago. These findings are relevant both to our understanding of human history and to the nature of rare variation segregating within populations: a variant that is rare because it is a recent mutation in the direct ancestor of the population will have had a very different evolutionary history than an ancient one that has persisted at high frequencies in a diverged population and only recently arrived through migration.

genomics↗

bioRxiv2017

Time-conditional properties of branches in coalescent gene trees

Coalescent gene trees have proven to be a powerful framework for formulating and solving problems in population genetics both in theory and practice. Using them, geneticists have been able to generate expectations for many attributes of a random sample of genotypes from a population given a model of the history of the population. This paper derives three new properties of coalescent gene trees that will help characterize the present-day impacts of historical events. Considering a single branch sampled at a given time ts in the past, it presents distributions describing 1) the length of time a branch sampled ts generations in the past had existed at the time of sampling, 2) the length of time that branch continues from time ts towards the present, and3) the the probability that the branch is ancestral to x individuals in a modern sample.

genetics↗

bioRxiv2017

T cell activation and the HLA locus associate with latent infections of human African trypanosomiasis

Infections by many pathogens can result in a wide range of phenotypes, from severe to mild, or even asymptomatic. Understanding the genetic basis of these phenotypes can lead to better tools to treat patients or detect reservoirs. To identify human genetic factors that contribute to symptoms diversity, we examined the range of disease severities caused by the parasite T. b. gambiense, the primary cause of human African trypanosomiasis (HAT). We analyzed the transcriptomes of immune cells from both symptomatic HAT cases and individuals with latent infections. Our analysis identified several genes and pathways that associated with the latent phenotype, primarily suggesting increased T and B cell activation in HAT patients relative to latent infections. We also used these transcriptome data to conduct an exome-wide single nucleotide polymorphism (SNP) association study. This suggested that SNPs in the human major histocompatibility locus (HLA) associate with severity, supporting the transcription data and suggesting that T cell activation is a determining factor in outcome. Finally, to establish if T cell activation controls disease severity, we blocked co-stimulatory dependent T cell activation in an animal model for HAT. This showed that reducing T cell activation during trypanosome infection improves symptoms and reduces parasitemia. Our data has used a combination of transcriptome-wide analysis and an in vivo model to reveal that T cell activation and the HLA locus associate with the development of symptoms during HAT. This may open new avenues for the development of new therapeutics and prognostics.

genetics↗

bioRxiv2017

Protein Evolution Depends On Multiple Distinct Population Size Parameters

That population size affects the fate of new mutations arising in genomes, modulating both how frequently they arise and how efficiently natural selection is able to filter them, is well established. It is therefore clear that these distinct roles for population size that characterize different processes should affect the evolution of proteins and need to be carefully defined. Empirical evidence is consistent with a role for demography in influencing protein evolution, supporting the idea that functional constraints alone do not determine the composition of coding sequences.\n\nGiven that the relationship between population size, mutant fitness and fixation probability has been well characterized, estimating fitness from observed substitutions is well within reach with well-formulated models. Molecular evolution research has, therefore, increasingly begun to leverage concepts from population genetics to quantify the selective effects associated with different classes of mutation. However, in order for this type of analysis to provide meaningful information about the intra- and inter-specific evolution of coding sequences, a clear definition of concepts of population size, what they influence, and how they are best parameterized is essential.\n\nHere, we present an overview of the many distinct concepts that \"population size\" and \"effective population size\" may refer to, what they represent for studying proteins, and how this knowledge can be harnessed to produce better specified models of protein evolution.

evolutionary biology↗