Missing compared to what? Revisiting heritability, genes and culture

Feldman, Marcus W.; Ramachandran, Sohini

doi:10.1098/rstb.2017.0064

Cited by 62 publications

(53 citation statements)

References 52 publications

(101 reference statements)

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“…0.5%) when excluding the epistatic interactions matrix (HE results with epistatic interactions were inconclusive due to large standard errors). We also tried to limit confounding due to shared environmental effects [2,84] by excluding ~399,000 pairs (~0.15%) of individuals with a shared household (spouses or parent-child pairs) from the analysis without excluding the individuals themselves, using HE (Methods). This led to a heritability estimate of 26.3% (s.e.…”

Section: Estimating the Heritability Of Longevity And Reproductive Fimentioning

confidence: 99%

Estimating variance components in population scale family trees

Shor

Geiger

Erlich

et al. 2018

Preprint

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The rapid digitization of genealogical and medical records enables the assembly of extremely large pedigree records spanning millions of individuals. Such pedigrees provide the opportunity to answer genetic and epidemiological questions in scales much larger than previously possible. Linear mixed models (LMMs) are often used for analysis of pedigree data. However, LMMs cannot naturally scale to large pedigrees spanning millions of individuals, owing to their steep computational and storage requirements. Here we propose a novel modeling framework called Sparse Cholesky factorIzation LMM (SciLMM), that alleviates these difficulties by exploiting the sparsity patterns found in large pedigree data. The proposed framework can construct a matrix of genetic relationships between trillions of pairs of individuals in several hours, and can fit the corresponding LMM in several days. We demonstrate the capabilities of SciLMM via simulation studies and by estimating the heritability of longevity in a very large pedigree spanning millions of individuals and over five centuries of human history. The SciLMM framework enables the analysis of extremely large pedigrees that was not previously possible. SciLMM

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Section: Estimating the Heritability Of Longevity And Reproductive Fimentioning

confidence: 99%

Estimating variance components in population scale family trees

Shor

Geiger

Erlich

et al. 2018

Preprint

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“…by use of 4 Here, we focus on the application of the exhaustive scan approach to rare-variant (RV) 66 association studies based on sequenced or genotyped data. RV analysis is motivated by the 67 observation that, although genome-wide association studies (GWAS) have usually identified 68 common risk alleles for a wide range of complex diseases (MANOLIO et al 2009), most of 69 these alleles cause at most moderate increases in risk and contribute little to the overall 70 heritability of diseases individually, leaving large portions of human diseases' heritability 71 unexplained (FELDMAN and RAMACHANDRAN 2018;MANOLIO et al 2009). This observation 72 motivated studies to focus on the role of RVs, aiming to deliver functionally interpretable 73 variants of moderate to large effect sizes and explaining additional disease risk variability.…”

Section: Introduction 40mentioning

confidence: 99%

The exhaustive genomic scan approach, with an application to rare-variant association analysis

Kanoungi

Nothnagel

Becker³

et al. 2019

Preprint

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26Region-based genome-wide scans are usually performed by use of a priori chosen analysis 27 regions. Such an approach will likely miss the region comprising the strongest signal and, 28 thus, may result in increased type II error rates and decreased power. Here, we propose a 29 genomic exhaustive scan approach that analyzes all possible subsequences and does not rely 30 on a prior definition of the analysis regions. As a prime instance, we present a 31 computationally ultra-efficient implementation using the rare-variant collapsing test for 32 phenotypic association, the genomic exhaustive collapsing scan (GECS). Our implementation 33 allows for the identification of regions comprising the strongest signals in large, genome-wide 34 rare-variant association studies while controlling the family-wise error rate via permutation. 35Application of GECS to two genomic data sets revealed several novel significantly associated 36 regions for age-related macular degeneration and for schizophrenia. Our approach also offers 37 a high potential for genome-wide scans for selection, methylation and other analyses. 38 39 (FWER) via repeated case-control status permutation which provides optimal power to detect 126 association (MEINSHAUSEN et al. 2011). Based on simulations, we derive empirical thresholds 127 for genome-wide significance in case-control WGS studies for different sample sizes and 128 minor allele frequency thresholds, in an approach similar to (PULIT et al. 2017). In applying 129 GECS to two real-world data sets, we show that our approach is feasible and scalable with 130 large, modern association studies and provides a fine-grained, base-pair resolution of 131 associated regions contained in the data (Figure 1), which will enable a deeper understanding 132 of the effect of RVs on the etiology of complex diseases. 133 Results 134Simulation studies 135 Global significance thresholds. As expected, the GECS-specific thresholds for genome-wide 136 significance were always more stringent than those for the single-marker analysis (SMA) and 137 were inversely correlated with sample size and MAF T (Figure S3-4).

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“…She proposes interpretation and generalizations from comparing these results with data on toolkit complexity in different hunter -gatherer groups. Last, Feldman & Ramachandran [14] bring cultural evolution to bear on modern genetic analysis, highlighting potentially misleading interpretations of genome-wide association studies that aim to assess the genetic underpinnings of behavioural traits such as IQ without considering potential processes of cultural transmission that may have profound effects on these traits.…”

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confidence: 99%

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confidence: 99%

“…The aim of this issue is to advance interdisciplinary discussion of the roles that culture plays in shaping the course of human evolution, exploring the mechanisms of cultural evolution from their cognitive underpinnings in individuals, through the behavioural ecology of learning from others, to the dynamics of transmission at the level of individuals and populations. The articles in this issue bring insights from disparate disciplines to bear on major questions in cultural evolution [1-11] and suggest broad-scale ways in which the study of cultural evolution can be synthesized with other disciplines [12][13][14].In the introduction to this issue [15], we outline how integrative studies are poised to move the field of cultural evolution forward; we demonstrate the utility of this approach by reviewing a number of interdisciplinary studies in cultural evolution and related fields that encompass behavioural ecology, population dynamics, cognition and genetics. Next, in the special issue's first article, Truskanov & Prat [1] bring insights from the behavioural ecology of social learning in non-human animals to bear on the underlying mechanisms of cultural transmission.…”

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confidence: 99%

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Bridging cultural gaps: interdisciplinary studies in human cultural evolution

Kolodny

Feldman

Creanza

2018

Phil. Trans. R. Soc. B

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One contribution of 16 to a theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'. Within the blink of an eye on a geological timescale, humans advanced from using basic stone tools to examining the rocks on Mars; however, our exact evolutionary path and the relative importance of genetic and cultural evolution in directing it remain a mystery. Our cultural capacities-to generate new ideas, to communicate and learn from one another, and to form vast social networks-together make us uniquely human, but the origins, the mechanisms and the evolutionary impact of these capacities are not well understood.This special issue comprises studies that bring together perspectives from anthropology, archaeology, biology, computer science, ecology and psychology to help elucidate the cultural forces affecting human evolution. These studies explore avenues in which approaches and insights from different fields may inform one another or be brought together to generate novel interdisciplinary research agendas, with the goal of advancing the study of human uniqueness and its pre-hominid origins. The aim of this issue is to advance interdisciplinary discussion of the roles that culture plays in shaping the course of human evolution, exploring the mechanisms of cultural evolution from their cognitive underpinnings in individuals, through the behavioural ecology of learning from others, to the dynamics of transmission at the level of individuals and populations. The articles in this issue bring insights from disparate disciplines to bear on major questions in cultural evolution [1-11] and suggest broad-scale ways in which the study of cultural evolution can be synthesized with other disciplines [12][13][14].In the introduction to this issue [15], we outline how integrative studies are poised to move the field of cultural evolution forward; we demonstrate the utility of this approach by reviewing a number of interdisciplinary studies in cultural evolution and related fields that encompass behavioural ecology, population dynamics, cognition and genetics. Next, in the special issue's first article, Truskanov & Prat [1] bring insights from the behavioural ecology of social learning in non-human animals to bear on the underlying mechanisms of cultural transmission. They address the widespread misconception that high fidelity of transmission depends on precise copying of cultural information and suggest the opposite: fidelity of transmission might depend on inexact copying, coupled with trial-and-error exploration, which together allow flexibility in applying a learned behaviour and tailoring it to the current environment. Stressing the importance of mechanisms of social learning in a broader perspective, Heyes [12] proposes that insights from the cognitive sciences must inform cultural evolution and vice versa: the two fields need one another. Applying this approach to a topic at the heart of cultural evolution, she outlines the possible cognitive processes that may underlie cultural transmission, as...

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Missing compared to what? Revisiting heritability, genes and culture

Cited by 62 publications

References 52 publications

Estimating variance components in population scale family trees

Estimating variance components in population scale family trees

The exhaustive genomic scan approach, with an application to rare-variant association analysis

Bridging cultural gaps: interdisciplinary studies in human cultural evolution

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