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Patterson, N.

Publications and source records attributed to Patterson, N..

29 records · Page 2Linked to original sources

ContamLD: Estimation of Ancient Nuclear DNA Contamination Using Breakdown of Linkage Disequilibrium

We report a method, ContamLD, for estimating autosomal ancient DNA (aDNA) contamination by measuring the breakdown of linkage disequilibrium in a sequenced individual due to the introduction of contaminant DNA, leveraging the idea that contaminants should have haplotypes uncorrelated to those of the studied individual. Using simulated data, we confirm that ContamLD accurately infers contamination rates with low standard errors (e.g. less than 1.5% standard error in cases with <10% contamination and data from at least 500,000 sequences covering SNPs). This method is optimized for application to aDNA, leveraging characteristic aDNA damage patterns to provide calibrated contamination estimates. Availability: https://github.com/nathan-nakatsuka/ContamLD.

evolutionary biology↗

miqoGraph : Fitting admixture graphs using mixed-integer quadratic optimization

Admixture graphs represent the genetic relationship between a set of populations through splits, drift and admixture. In this paper we present the Julia package miqoGraph, which uses mixed-integer quadratic optimization to fit topology, drift lengths, and admixture proportions simultaneously. Inference of topology is particularly powerful, with integer optimization automating what is usually an arduous manual process.\n\nAvailabilityhttps://github.com/juliayyan/PhylogeneticTrees.jl\n\nContactjyyan@mit.edu

genomics↗

No statistical evidence for an effect of CCR5-Δ32 on lifespan in the UK Biobank cohort

A recent study reported that a 32-base-pair deletion in the CCR5 gene (CCR5-{triangleup}32) is deleterious in the homozygous state in humans. Evidence for this came from a survival analysis in the UK Biobank cohort, and from deviations from Hardy-Weinberg equilibrium at a polymorphism tagging the deletion (rs62625034). Here, we carry out a joint analysis of whole-genome genotyping data and whole-exome sequencing data from the UK Biobank, which reveals that technical artifacts are a more plausible cause for deviations from Hardy-Weinberg equilibrium at this polymorphism. Specifically, we find that individuals homozygous for the deletion in the sequencing data are underrepresented in the genotyping data due to an elevated rate of missing data at rs62625034, possibly because the probe for this SNP overlaps with the {triangleup}32 deletion. Another variant which has a higher concordance with the deletion in the sequencing data shows no associations with mortality. A phenome-wide scan for effects of variants tagging this deletion shows an overall inflation of association p-values, but identifies only one trait at p < 5x10-8, and no mediators for an effect on mortality. These analyses show that the original reports of a recessive deleterious effect of CCR5-{triangleup}32 are affected by a technical artifact, and that a closer investigation of the same data provides no positive evidence for an effect on lifespan.

genetics↗

Combining case-control status and family history of disease increases association power

Family history of disease can provide valuable information about an individuals genetic liability for disease in case-control association studies, but it is currently unclear how to best combine case-control status and family history of disease. We developed a new association method based on posterior mean genetic liabilities under a liability threshold model, conditional on both case-control status and family history (LT-FH); association statistics are computed via linear regression of genotypes and posterior mean genetic liabilities, equivalent to a score test. We applied LT-FH to 12 diseases from the UK Biobank (average N=350K). We compared LT-FH to genome-wide association without using family history (GWAS) and a previous proxy-based method for incorporating family history (GWAX). LT-FH was +63% (s.e. 6%) more powerful than GWAS and +36% (s.e. 4%) more powerful than the trait-specific maximum of GWAS and GWAX, based on the number of independent genome-wide significant loci detected across all diseases (e.g. 690 independent loci for LT-FH vs. 423 for GWAS); the second best method was GWAX for lower-prevalence diseases and GWAS for higher-prevalence diseases, consistent with simulations. We also confirmed that LT-FH was well-calibrated (assessed via stratified LD score regression attenuation ratio), consistent with simulations. When using BOLT-LMM (instead of linear regression) to compute association statistics for all three methods (increasing the power of each method), LT-FH was +67% (s.e. 6%) more powerful than GWAS and +39% (s.e. 4%) more powerful than the trait-specific maximum of GWAS and GWAX. In summary, LT-FH greatly increases association power in case-control association studies when family history of disease is available.

genetics↗

The Arrival of Steppe and Iranian Related Ancestry in the Islands of the Western Mediterranean

A series of studies have documented how Steppe pastoralist-related ancestry reached central Europe by at least 2500 BCE, while Iranian farmer-related ancestry was present in Aegean Europe by at least 1900 BCE. However, the spread of these ancestries into the western Mediterranean where they have contributed to many populations living today remains poorly understood. We generated genome-wide ancient DNA from the Balearic Islands, Sicily, and Sardinia, increasing the number of individuals with reported data from these islands from 3 to 52. We obtained data from the oldest skeleton excavated from the Balearic islands (dating to [~]2400 BCE), and show that this individual had substantial Steppe pastoralist-derived ancestry; however, later Balearic individuals had less Steppe heritage reflecting geographic heterogeneity or immigration from groups with more European first farmer-related ancestry. In Sicily, Steppe pastoralist ancestry arrived by [~]2200 BCE and likely came at least in part from Spain as it was associated with Iberian-specific Y chromosomes. In Sicily, Iranian-related ancestry also arrived by the Middle Bronze Age, thus revealing that this ancestry type, which was ubiquitous in the Aegean by this time, also spread further west prior to the classical period of Greek expansion. In Sardinia, we find no evidence of either eastern ancestry type in the Nuragic Bronze Age, but show that Iranian-related ancestry arrived by at least [~]300 BCE and Steppe ancestry arrived by [~]300 CE, joined at that time or later by North African ancestry. These results falsify the view that the people of Sardinia are isolated descendants of Europes first farmers. Instead, our results show that the islands admixture history since the Bronze Age is as complex as that in many other parts of Europe.

genomics↗

Paleolithic DNA from the Caucasus reveals core of West Eurasian ancestry

The earliest ancient DNA data of modern humans from Europe dates to [~]40 thousand years ago1-4, but that from the Caucasus and the Near East to only [~]14 thousand years ago5,6, from populations who lived long after the Last Glacial Maximum (LGM) [~]26.5-19 thousand years ago7. To address this imbalance and to better understand the relationship of Europeans and Near Easterners, we report genome-wide data from two [~]26 thousand year old individuals from Dzudzuana Cave in Georgia in the Caucasus from around the beginning of the LGM. Surprisingly, the Dzudzuana population was more closely related to early agriculturalists from western Anatolia [~]8 thousand years ago8 than to the hunter-gatherers of the Caucasus from the same region of western Georgia of [~]13-10 thousand years ago5. Most of the Dzudzuana populations ancestry was deeply related to the post-glacial western European hunter-gatherers of the Villabruna cluster3, but it also had ancestry from a lineage that had separated from the great majority of non-African populations before they separated from each other, proving that such Basal Eurasians6,9 were present in West Eurasia twice as early as previously recorded5,6. We document major population turnover in the Near East after the time of Dzudzuana, showing that the highly differentiated Holocene populations of the region6 were formed by Ancient North Eurasian3,9,10 admixture into the Caucasus and Iran and North African11,12 admixture into the Natufians of the Levant. We finally show that the Dzudzuana population contributed the majority of the ancestry of post-Ice Age people in the Near East, North Africa, and even parts of Europe, thereby becoming the largest single contributor of ancestry of all present-day West Eurasians.

genetics↗

Polygenicity of complex traits is explained by negative selection

Complex traits and common disease are highly polygenic: thousands of common variants are causal, and their effect sizes are almost always small. Polygenicity could be explained by negative selection, which constrains common-variant effect sizes and may reshape their distribution across the genome. We refer to this phenomenon as flattening, as genetic signal is flattened relative to the underlying biology. We introduce a mathematical definition of polygenicity, the effective number of associated SNPs, and a robust statistical method to estimate it. This definition of polygenicity differs from the number of causal SNPs, a standard definition; it depends strongly on SNPs with large effects. In analyses of 33 complex traits (average N=361k), we determined that common variants are [~]4x more polygenic than low-frequency variants, consistent with pervasive flattening. Moreover, functionally important regions of the genome have increased polygenicity in proportion to their increased heritability, implying that heritability enrichment reflects differences in the number of associations rather than their magnitude (which is constrained by selection). We conclude that negative selection constrains the genetic signal of biologically important regions and genes, reshaping genetic architecture.

genetics↗

Quantification of genetic components of population differentiation in UK Biobank traits reveals signals of polygenic selection

The genetic architecture of most human complex traits is highly polygenic, motivating efforts to detect polygenic selection involving a large number of loci. In contrast to previous work relying on top GWAS loci, we developed a method that uses genome-wide association statistics and linkage disequilibrium patterns to estimate the genome-wide genetic component of population differentiation of a complex trait along a continuous gradient, enabling powerful inference of polygenic selection. We analyzed 43 UK Biobank traits and focused on PC1 and North-South and East-West birth coordinates across 337K unrelated British-ancestry samples, for which our method produced close to unbiased estimates of genetic components of population differentiation and high power to detect polygenic selection in simulations across different trait architectures. For PC1, we identified signals of polygenic selection for height (74.5{+/-}16.7% of 9.3% total correlation with PC1 attributable to genome-wide genetic effects; P = 8.4x10-6) and red hair pigmentation (95.9{+/-}24.7% of total correlation with PC1 attributable to genome-wide genetic effects; P = 1.1x10-4); the bulk of the signal remained when removing genome-wide significant loci, even though red hair pigmentation includes loci of large effect. We also detected polygenic selection for height, systolic blood pressure, BMI and basal metabolic rate along North-South birth coordinate, and height and systolic blood pressure along East-West birth coordinate. Our method detects polygenic selection in modern human populations with very subtle population structure and elucidates the relative contributions of genetic and non-genetic components of trait population differences.

genetics↗

Signals of polygenic adaptation on height have been overestimated due to uncorrected population structure in genome-wide association studies

Genetic predictions of height differ among human populations and these differences are too large to be explained by genetic drift. This observation has been interpreted as evidence of polygenic adaptation. Differences across populations were detected using SNPs genome-wide significantly associated with height, and many studies also found that the signals grew stronger when large numbers of subsignificant SNPs were analyzed. This has led to excitement about the prospect of analyzing large fractions of the genome to detect subtle signals of selection and claims of polygenic adaptation for multiple traits. Polygenic adaptation studies of height have been based on SNP effect size measurements in the GIANT Consortium meta-analysis. Here we repeat the height analyses in the UK Biobank, a much more homogeneously designed study. Our results show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population structure.

evolutionary biology↗

Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk

Biological interpretation of GWAS data frequently involves analyzing unsigned genomic annotations comprising SNPs involved in a biological process and assessing enrichment for disease signal. However, it is often possible to generate signed annotations quantifying whether each SNP allele promotes or hinders a biological process, e.g., binding of a transcription factor (TF). Directional effects of such annotations on disease risk enable stronger statements about causal mechanisms of disease than enrichments of corresponding unsigned annotations. Here we introduce a new method, signed LD profile regression, for detecting such directional effects using GWAS summary statistics, and we apply the method using 382 signed annotations reflecting predicted TF binding. We show via theory and simulations that our method is well-powered and is well-calibrated even when TF binding sites co-localize with other enriched regulatory elements, which can confound unsigned enrichment methods. We further validate our method by showing that it recovers known transcriptional regulators when applied to molecular QTL in blood. We then apply our method to eQTL in 48 GTEx tissues, identifying 651 distinct TF-tissue expression associations at per-tissue FDR < 5%, including 30 associations with robust evidence of tissue specificity. Finally, we apply our method to 46 diseases and complex traits (average N = 289,617) and identify 77 annotation-trait associations at per-trait FDR < 5% representing 12 independent TF-trait associations, and we conduct gene-set enrichment analyses to characterize the underlying transcriptional programs. Our results implicate new causal disease genes (including causal genes at known GWAS loci), and in some cases suggest a detailed mechanism for a causal genes effect on disease. Our method provides a new way to leverage functional data to draw inferences about disease etiology.

genetics↗

The Genomic History Of Southeastern Europe

Farming was first introduced to southeastern Europe in the mid-7th millennium BCE - brought by migrants from Anatolia who settled in the region before spreading throughout Europe. To clarify the dynamics of the interaction between the first farmers and indigenous hunter-gatherers where they first met, we analyze genome-wide ancient DNA data from 223 individuals who lived in southeastern Europe and surrounding regions between 12,000 and 500 BCE. We document previously uncharacterized genetic structure, showing a West-East cline of ancestry in hunter-gatherers, and show that some Aegean farmers had ancestry from a different lineage than the northwestern Anatolian lineage that formed the overwhelming ancestry of other European farmers. We show that the first farmers of northern and western Europe passed through southeastern Europe with limited admixture with local hunter-gatherers, but that some groups mixed extensively, with relatively sex-balanced admixture compared to the male-biased hunter-gatherer admixture that prevailed later in the North and West. Southeastern Europe continued to be a nexus between East and West after farming arrived, with intermittent genetic contact from the Steppe up to 2,000 years before the migration that replaced much of northern Europes population.

genetics↗