Biology subjects

Balick, D. J.

Publications and source records attributed to Balick, D. J..

8 recordsLinked to original sources

bioRxiv2025

Inherent instability of simple DNA repeats shapes an evolutionarily stable distribution of repeat lengths

Using the Telomere-to-Telomere reference, we assembled the distribution of simple repeat lengths present in the human genome. Analyzing over two hundred mammalian genomes, we found remarkable consistency in the shape of the distribution across evolutionary epochs. All observed genomes harbor an excess of long repeats, which are potentially prone to developing into repeat expansion disorders. We measured mutation rates for repeat length instability, quantitatively modeled the per-generation action of mutations, and observed the corresponding long-term behavior shaping the repeat length distribution. We found that short repetitive sequences appear to be a straightforward consequence of random substitution. Evolving largely independently, longer repeats (above roughly 10 nt) emerge and persist in a rapidly mutating dynamic balance between expansion, contraction and interruption. These mutational processes, collectively, are sufficient to explain the abundance of long repeats, without invoking natural selection. Our analysis constrains properties of molecular mechanisms responsible for maintaining genome fidelity that underlie repeat instability.

genetics↗

bioRxiv2023

A field theoretic approach to non-equilibrium population genetics in the strong selection regime

Natural populations are virtually never observed in equilibrium, yet equilibrium approximations comprise the majority of our understanding of population genetics. Using standard tools from statistical physics, a formalism is presented that re-expresses the stochastic equations describing allelic evolution as a partition functional over all possible allelic trajectories ( paths) governed by selection, mutation, and drift. A perturbative field theory is developed for strong additive selection, relevant to disease variation, that facilitates the straightforward computation of closed-form approximations for time-dependent moments of the allele frequency distribution across a wide range of non-equilibrium scenarios; examples are presented for constant population size, exponential growth, bottlenecks, and oscillatory size, all of which align well to simulations and break down just above the drift barrier. Equilibration times are computed and, even for static population size, generically extend beyond the order 1/s timescale associated with exponential frequency decay. Though the mutation load is largely robust to variable population size, perturbative drift-based corrections to the deterministic trajectory are readily computed. Under strong selection, the variance of a new mutations frequency (related to homozygosity) is dominated by drift-driven dynamics and a transient increase in variance often occurs prior to equilibrating. The excess kurtosis over skew squared is roughly constant (i.e., independent of selection, provided 2Ns {gtrsim} 5) for static population size, and thus potentially sensitive to deviation from equilibrium. These insights highlight the value of such closed-form approximations, naturally generated from Feynman diagrams in a perturbative field theory, which can simply and accurately capture the parameter dependences describing a variety of non-equilibrium population genetic phenomena of interest.

genetics↗

bioRxiv2022

Strength of stabilizing selection on the amino-acid sequence is associated with the amount of non-additive variance in gene expression.

Contemporary populations are unlikely to respond to natural selection if much of their genetic variance is non-additive. Understanding the evolutionary and genomic factors that drive amounts of non-additive variance in natural populations is therefore of paramount importance. Here, we use a quantitative genetic breeding design to separate the additive from the non-additive components of expression variance in 17,657 gene transcripts of the outcrossing plant Arabidopsis lyrata. We partition the expressed genes according to their predominant variance components in a set of half- and full-sib families obtained by crossing individuals from different populations. As expected, a population-genetic simulation model shows that when divergent alleles segregate in the population, our ability to detect non-additive genetic variance is enhanced. Variation in its relative contribution can thus be analyzed and compared across transcribed genes. We find that most of the genetic variance in gene expression represents non-additive variance, especially among long genes or genes involved in epigenetic gene regulation. Genes with the most non-additive variance in our design not only display markedly lower rates of synonymous variation, they have also been exposed to stronger purifying selection compared to genes with high additive variance. Our study demonstrates that both the genomic architecture and the past history of purifying selection impacts the composition of genetic variance in gene expression.

genetics↗

bioRxiv2021

Overcoming constraints on the detection of recessive selection in human genes from population frequency data

The identification of genes that evolve under recessive natural selection is a longstanding goal of population genetics research with important applications to disease gene discovery. We found that commonly used methods to evaluate selective constraint at the gene level are highly sensitive to genes under heterozygous selection but ubiquitously fail to detect recessively evolving genes. Additionally, more sophisticated likelihood-based methods designed to detect recessivity similarly lack power for a human gene of realistic length from current population sample sizes. However, extensive simulations suggested that recessive genes may be detectable in aggregate. Here, we offer a method informed by population genetics simulations designed to detect recessive purifying selection in gene sets. Applying this to empirical gene sets produced significant enrichments for strong recessive selection in genes previously inferred to be under recessive selection in a consanguineous cohort and in genes involved in autosomal recessive monogenic disorders.

genetics↗

bioRxiv2020

Probing the aggregated effects of purifying selection per individual on 1,250 medical phenotypes in the UK biobank

Understanding the relationship between natural selection and phenotypic variation has been a long-standing challenge in human population genetics. With the emergence of biobank-scale datasets, along with new statistical metrics to approximate strength of purifying selection at the variant level, it is now possible to correlate a proxy of individual relative fitness with a range of medical phenotypes. We calculated a per-individual deleterious load score by summing the total number of derived alleles per individual after incorporating a weight that approximates strength of purifying selection. We assessed four methods for the weight, including GERP, phyloP, CADD, and fitcons. By quantitatively tracking each of these scores with the site frequency spectrum, we identified phyloP as the most appropriate weight. The phyloP-weighted load score was then calculated across 15,129,142 variants in 335,161 individuals from the UK Biobank and tested for association on 1,380 medical phenotypes. After accounting for multiple test correction, we observed a strong association of the load score amongst coding sites only on 27 traits including body mass, adiposity and metabolic rate. We further observed that the association signals were driven by common variants (derived allele frequency > 5%) with high phyloP score (phyloP > 2). Finally, through permutation analyses, we showed that the load score amongst coding sites had an excess of nominally significant associations on many medical phenotypes. These results suggest a broad impact of deleterious load on medical phenotypes and highlight the deleterious load score as a tool to disentangle the complex relationship between natural selection and medical phenotypes. Author summaryThis study aims to augment our understanding between the complex relation between natural selection and human phenotypic variation. We developed a load score to approximate the relative fitness of an individual and correlate it with a set of medical phenotypes. Association tests between the load score amongst coding sites and 1,380 phenotypes in a sample of 335,161 individuals from the UK Biobank showed a strong association with 27 traits including body mass, adiposity and metabolic rate. Furthermore, an excess of nominal associations at suggestive levels was observed between the load score amongst coding sites and medical phenotypes than would be expected under a null model. These results suggest that the aggregate effect of deleterious mutations as measured by the load score has a broad effect on human phenotypes.

genetics↗

bioRxiv2020

Purifying selection on noncoding deletions of human regulatory elements detected using their cellular pleiotropy

Genomic deletions provide a powerful loss-of-function model in non-coding regions to assess the role of purifying selection on human noncoding genetic variation. Regulatory element function is char-acterized by non-uniform tissue/cell-type activity, necessarily linking the study of fitness consequences from regulatory variants to their corresponding cellular activity. We used deletions from the 1000 Genomes Project (1000GP) and a callset we generated from genomes of participants in the Alzheimers Disease Neuroimaging Initiative (ADNI) in order to examine whether purifying selection preserves noncoding sites of chromatin accessibility (DHS), histone modification (enhancer, transcribed, polycomb-repressed, heterochromatin), and topologically associated domain loops (TAD-loops). To examine this in a cellular activity-aware manner, we developed a statistical method, Pleiotropy Ratio Score (PlyRS), which calculates a correlation-adjusted count of "cellular pleiotropy" for each noncoding base-pair by analyzing shared regulatory annotations across tissues/cell-types. Comparing real deletion PlyRS values to simulations in a length-matched framework and using genomic covariates in analyses, we found that purifying selection acts to preserve both DHS and enhancer sites, as evident by both depletion of deletions overlapping these annotations and a shift in the allele frequency spectrum of overlapping deletions towards rare alleles. However, we did not find evidence of purifying selection for transcribed, polycomb-repressed, or heterochromatin sites. Additionally, we found evidence that purifying selection is acting on TAD-loop boundary integrity by preserving co-localized CTCF binding sites. Notably, at regions of DHS, enhancer, and CTCF within TAD-loop boundaries we found evidence that both sites of tissue/cell-type-specific activity and sites of cellularly pleiotropic activity are preserved by selection. Significance StatementWe used natural genomic deletions as a loss-of-function model to assess the role of purifying selection in preserving human noncoding regulatory sites. We examined this in a cellular activity-aware manner through development of a statistical method, Pleiotropy Ratio Score (PlyRS), which calculates an adjusted count of "cellular pleiotropy" for each noncoding basepair by analyzing correlations from shared regulatory annotations across tissues/cell-types. By comparing real deletion PlyRS values to simulations, we found that purifying selection acts to preserve both DHS and enhancer sites and TAD-loop boundary integrity by preserving co-localized CTCF binding sites. Notably, we found evidence at these regulatory regions that both sites of tissue/cell-type-specific activity and sites of cellularly pleiotropic activity are preserved by selection.

evolutionary biology↗

bioRxiv2018

Applicability of the mutation-selection balance model to population genetics of heterozygous protein-truncating variants in humans

The fate of alleles in the human population is believed to be highly affected by the stochastic force of genetic drift. Estimation of the strength of natural selection in humans generally necessitates a careful modeling of drift including complex effects of the population history and structure. Protein truncating variants (PTVs) are expected to evolve under strong purifying selection and to have a relatively high per-gene mutation rate. Thus, it is appealing to model the population genetics of PTVs under a simple deterministic mutation-selection balance, as has been proposed earlier [1]. Here, we investigated the limits of this approximation using both computer simulations and data-driven approaches. Our simulations rely on a model of demographic history estimated from 33,370 individual exomes of the Non-Finnish European subset of the ExAC dataset [2]. Additionally, we compared the African and European subset of the ExAC study and analyzed de novo PTVs. We show that the mutation-selection balance model is applicable to the majority of human genes, but not to genes under the weakest selection.

genetics↗

bioRxiv2017

Quantification of frequency-dependent genetic architectures and action of negative selection in 25 UK Biobank traits

Understanding the role of rare variants is important in elucidating the genetic basis of human diseases and complex traits. It is widely believed that negative selection can cause rare variants to have larger per-allele effect sizes than common variants. Here, we develop a method to estimate the minor allele frequency (MAF) dependence of SNP effect sizes. We use a model in which per-allele effect sizes have variance proportional to [p(1-p)], where p is the MAF and negative values of imply larger effect sizes for rare variants. We estimate by maximizing its profile likelihood in a linear mixed model framework using imputed genotypes, including rare variants (MAF >0.07%). We applied this method to 25 UK Biobank diseases and complex traits (N = 113,851). All traits produced negative estimates with 20 significantly negative, implying larger rare variant effect sizes. The inferred best-fit distribution of true values across traits had mean -0.38 (s.e. 0.02) and standard deviation 0.08 (s.e. 0.03), with statistically significant heterogeneity across traits (P = 0.0014). Despite larger rare variant effect sizes, we show that for most traits analyzed, rare variants (MAF <1%) explain less than 10% of total SNP-heritability. Using evolutionary modeling and forward simulations, we validated the model of MAF-dependent trait effects and estimated the level of coupling between fitness effects and trait effects. Based on this analysis an average genome-wide negative selection coefficient on the order of 10-4 or stronger is necessary to explain the values that we inferred.

genetics↗