CORRECTING MODEL MISSPECIFICATION IN RELATIONSHIP ESTIMATES.

The datasets of large genotyping biobanks and direct-to-consumer genetic testing companies contain many related individuals. Until now, it has been widely accepted that the most distant relationships that can be detected are around fifteen degrees (approximately 8 th cousins) and that practical relationship estimates have a ceiling around ten degrees (approximately 5 th cousins). However, we show that these assumptions are incorrect and that they are due to a misapplication of relationship estimators. In particular, relationship estimators are applied almost exclusively to putative relatives who have been identified because they share detectable tracts of DNA identically by descent (IBD). However, no existing relationship estimator conditions on the event that two individuals share at least one detectable segment of IBD anywhere in the genome. As a result, the relationship estimates obtained using existing estimators are dramatically biased for distant relationships, inferring all sufficiently distant relationships to be around ten degrees regardless of the depth of the true relationship. Moreover, existing relationship estimators are derived under a model that assumes that each pair of related individuals shares a single common ancestor (or mating pair of ancestors). This model breaks down for relationships beyond 10 generations in the past because individuals share many thousands of cryptic common ancestors due to pedigree collapse. We first derive a corrected likelihood that conditions on the event that at least one segment is observed between a pair of putative relatives and we demonstrate that the corrected likelihood largely eliminates the bias in estimates of pairwise relationships and provides a more accurate characterization of the uncertainty in these estimates. We then reformulate the relationship inference problem to account for the fact that individuals share many common ancestors, not just one. We demonstrate that the most distant relationship that can be inferred may be forty degrees or more, rather than ten, extending the time-to-common ancestor from approximately 200 years in the past to approximately 600 years in the past or more. This dramatic increase in the range of relationship estimators makes it possible to infer relationships whose common ancestors lived before historical events such as European settlement of the Americas and the Transatlantic Slave Trade, and possibly much earlier.

SIMULATING PEDIGREES ASCERTAINED ON THE BASIS OF OBSERVED IBD SHARING.

In large genotyping datasets, individuals often have thousands of distant cousins with whom they share detectable segments of DNA identically by descent (IBD). The ability to simulate these distant relationships is important for developing and testing methods, carrying out power analyses, and performing population genetic analyses. Because distant relatives are unlikely to share detectable IBD segments by chance, many simulation replicates are needed to sample IBD between any given pair of distant relatives. Exponentially more samples are needed to simulate observable segments of IBD simultaneously among multiple pairs of distant relatives in a single pedigree. Using existing pedigree simulation methods that do not condition on the event that IBD is observed among certain pairs of relatives, the chances of sampling shared IBD patterns that reflect those observed in real data ascertained from large genotyping datasets are vanishingly small, even for pedigrees of modest size. Here, we show how to sample recombination breakpoints on a fixed pedigree while conditioning on the event that specified pairs of individuals share at least one observed segment of IBD. The resulting simulator makes it possible to sample genotypes and IBD segments on pedigrees that reflect those ascertained from biobank scale data.

Reconstructing parent genomes using siblings and other relatives.

Reconstructing the DNA of ancestors from their descendants has the potential to empower phenotypic analyses (including association and genetic nurture studies), improve pedigree reconstruction, and shed light on the ancestral population and phenotypes of ancestors. We developed HAPI-RECAP, a method that reconstructs the DNA of parents from full siblings and their relatives. This tool leverages HAPI2's output, a new phasing approach that applies to siblings (and optionally one or both parents) and reliably infers parent haplotypes but does not link the ungenotyped parents' DNA across chromosomes or between segments flanking ambiguities. By combining IBD between the reconstructed parents and the relatives, HAPI-RECAP resolves the source parent of these segments. Moreover, the method exploits crossovers the children inherited and sex-specific genetic maps to infer the reconstructed parents' sexes. We validated these methods on research participants from both 23andMe, Inc. and the San Antonio Mexican American Family Studies. Given data for one parent, HAPI2 reconstructs large fractions of the missing parent's DNA, between 77.6% and 99.97% among all families, and 90.3% on average in three- and four-child families. When reconstructing both parents, HAPI-RECAP inferred between 33.2% and 96.6% of the parents' genotypes, averaging 70.6% in four-child families. Reconstructed genotypes have average error rates < 10-3, or comparable to those from direct genotyping. HAPI-RECAP inferred the parent sexes 100% correctly given IBD-linked segments and can also reconstruct parents without any IBD. As datasets grow in size, more families will be implicitly collected; HAPI-RECAP holds promise to enable high quality parent genotype reconstruction.

30 years of [11C]methyl triflate.

Some scientific discoveries are well known only to a core group of researchers working on technical subjects. Nevertheless, they open new research directions, allow existing knowledge to be viewed in entirely new and useful ways, or provide a way to make something that was hard or impossible to make before. Carbon-11 methyl triflate ([11C]MeOTf) is one such advance, facilitating the synthesis of many carbon-11 radio tracers and broadening the range of applications of carbon-11 radiochemistry. The year 2022 marked the 30th anniversary of the original paper in Applied Radiation and Isotopes introducing a simple synthesis of [11C]MeOTf from carbon-11 methyl iodide ([11C]MeI) and it also marked the end of the fruitful career and life of the researcher who developed it, Douglas Jewett. It seems fitting to say a few words on how it came to be and how it has helped advance carbon-11 radiochemistry.

Bonsai: An efficient method for inferring large human pedigrees from genotype data.

Pedigree inference from genotype data is a challenging problem, particularly when pedigrees are sparsely sampled and individuals may be distantly related to their closest genotyped relatives. We present a method that infers small pedigrees of close relatives and then assembles them into larger pedigrees. To assemble large pedigrees, we introduce several formulas and tools including a likelihood for the degree separating two small pedigrees, a generalization of the fast DRUID point estimate of the degree separating two pedigrees, a method for detecting individuals who share background identity-by-descent (IBD) that does not reflect recent common ancestry, and a method for identifying the ancestral branches through which distant relatives are connected. Our method also takes several approaches that help to improve the accuracy and efficiency of pedigree inference. In particular, we incorporate age information directly into the likelihood rather than using ages only for consistency checks and we employ a heuristic branch-and-bound-like approach to more efficiently explore the space of possible pedigrees. Together, these approaches make it possible to construct large pedigrees that are challenging or intractable for current inference methods.

Fast and Robust Identity-by-Descent Inference with the Templated Positional Burrows-Wheeler Transform.

Estimating the genomic location and length of identical-by-descent (IBD) segments among individuals is a crucial step in many genetic analyses. However, the exponential growth in the size of biobank and direct-to-consumer genetic data sets makes accurate IBD inference a significant computational challenge. Here we present the templated positional Burrows-Wheeler transform (TPBWT) to make fast IBD estimates robust to genotype and phasing errors. Using haplotype data simulated over pedigrees with realistic genotyping and phasing errors, we show that the TPBWT outperforms other state-of-the-art IBD inference algorithms in terms of speed and accuracy. For each phase-aware method, we explore the false positive and false negative rates of inferring IBD by segment length and characterize the types of error commonly found. Our results highlight the fragility of most phased IBD inference methods; the accuracy of IBD estimates can be highly sensitive to the quality of haplotype phasing. Additionally, we compare the performance of the TPBWT against a widely used phase-free IBD inference approach that is robust to phasing errors. We introduce both in-sample and out-of-sample TPBWT-based IBD inference algorithms and demonstrate their computational efficiency on massive-scale data sets with millions of samples. Furthermore, we describe the binary file format for TPBWT-compressed haplotypes that results in fast and efficient out-of-sample IBD computes against very large cohort panels. Finally, we demonstrate the utility of the TPBWT in a brief empirical analysis, exploring geographic patterns of haplotype sharing within Mexico. Hierarchical clustering of IBD shared across regions within Mexico reveals geographically structured haplotype sharing and a strong signal of isolation by distance. Our software implementation of the TPBWT is freely available for noncommercial use in the code repository (https://github.com/23andMe/phasedibd, last accessed January 11, 2021).

Nonsteroidal sulfamate derivatives as new therapeutic approaches for Neurofibromatosis 2 (NF2).

BACKGROUND: Neurofibromatosis 1 and 2, although involving two different tumour suppressor genes (neurofibromin and merlin, respectively), are both cancer predisposition syndromes that disproportionately affect cells of neural crest origin. New therapeutic approaches for both NF1 and NF2 are badly needed. In promising previous work we demonstrated that two non-steroidal analogues of 2-methoxy-oestradiol (2ME2), STX3451(2-(3-bromo-4,5-dimethoxybenzyl)-7-methoxy-6-sulfamoyloxy-1,2,3,4-tetrahydroisoquinoline), and STX2895 (7-Ethyl-6-sulfamoyloxy-2-(3,4,5-trimethoxybenzyl)-1,2,3,4-tetrahydroisoquinoline) reduced tumour cell growth and induced apoptosis in malignant and benign human Neurofibromatosis 1 (NF1) tumour cells. In earlier NF1 mechanism of action studies we found that in addition to their effects on non-classical hormone-sensitive pathways, STX agents acted on the actin- and myosin-cytoskeleton, as well as PI3Kinase and MTOR signaling pathways. Tumour growth in NF2 cells is affected by different inhibitors from those affecting NF1 growth pathways: specifically, NF2 cells are affected by merlin-downstream pathway inhibitors. Because Merlin, the affected tumour suppressor gene in NF2, is also known to be involved in stabilizing membrane-cytoskeletal complexes, as well as in cell proliferation, and apoptosis, we looked for potentially common mechanisms of action in the agents' effects on NF1 and NF2. We set out to determine whether STX agents could therefore also provide a prospective avenue for treatment of NF2. METHODS: STX3451 and STX2895 were tested in dose-dependent studies for their effects on growth parameters of malignant and benign NF2 human tumour cell lines in vitro. The mechanisms of action of STX3451 and STX2895 were also analysed. RESULTS: Although neither of the agents tested affected cell growth or apoptosis in the NF2 tumour cell lines tested through the same mechanisms by which they affect these parameters in NF1 tumour cell lines, both agents disrupted actin- and myosin-based cytoskeletal structures in NF2 cell lines, with subsequent effects on growth and cell death. CONCLUSIONS: Both STX3451 and STX2895 provide new approaches for inducing cell death and lowering tumour burden in NF2 as well as in NF1, which both have limited treatment options.

On the joint distribution of tree height and tree length under the coalescent.

Many statistics that examine genetic variation depend on the underlying shapes of genealogical trees. Under the coalescent model, we investigate the joint distribution of two quantities that describe genealogical tree shape: tree height and tree length. We derive a recursive formula for their exact joint distribution under a demographic model of a constant-sized population. We obtain approximations for the mean and variance of the ratio of tree height to tree length, using them to show that this ratio converges in probability to 0 as the sample size increases. We find that as the sample size increases, the correlation coefficient for tree height and length approaches (π2-6)∕[π2π2-18]≈0.9340. Using simulations, we examine the joint distribution of height and length under demographic models with population growth and population subdivision. We interpret the joint distribution in relation to problems of interest in data analysis, including inference of the time to the most recent common ancestor. The results assist in understanding the influences of demographic histories on two fundamental features of tree shape.

Parallel Trajectories of Genetic and Linguistic Admixture in a Genetically Admixed Creole Population.

Joint analyses of genes and languages, both of which are transmitted in populations by descent with modification-genes vertically by Mendel's laws, language via combinations of vertical, oblique, and horizontal processes [1-4]-provide an informative approach for human evolutionary studies [5-10]. Although gene-language analyses have employed extensive data on individual genetic variation [11-23], their linguistic data have not considered corresponding long-recognized [24] variability in individual speech patterns, or idiolects. Genetically admixed populations that speak creole languages show high genetic and idiolectal variation-genetic variation owing to heterogeneity in ancestry within admixed groups [25, 26] and idiolectal variation owing to recent language formation from differentiated sources [27-31]. To examine cotransmission of genetic and linguistic variation within populations, we collected genetic markers and speech recordings in the admixed creole-speaking population of Cape Verde, whose Kriolu language traces to West African languages and Portuguese [29, 32-35] and whose genetic ancestry has individual variation in European and continental African contributions [36-39]. In parallel with the combined Portuguese and West African origin of Kriolu, we find that genetic admixture in Cape Verde varies on an axis separating Iberian and Senegambian populations. We observe, analogously to vertical genetic transmission, transmission of idiolect from parents to offspring, as idiolect is predicted by parental birthplace, even after controlling for shared parent-child birthplaces. Further, African genetic admixture correlates with an index tabulating idiolectal features with likely African origins. These results suggest that Cape Verdean genetic and linguistic admixture have followed parallel evolutionary trajectories, with cotransmission of genetic and linguistic variation.

The Effects of Population Size Histories on Estimates of Selection Coefficients from Time-Series Genetic Data.

Many approaches have been developed for inferring selection coefficients from time series data while accounting for genetic drift. These approaches have been motivated by the intuition that properly accounting for the population size history can significantly improve estimates of selective strengths. However, the improvement in inference accuracy that can be attained by modeling drift has not been characterized. Here, by comparing maximum likelihood estimates of selection coefficients that account for the true population size history with estimates that ignore drift by assuming allele frequencies evolve deterministically in a population of infinite size, we address the following questions: how much can modeling the population size history improve estimates of selection coefficients? How much can mis-inferred population sizes hurt inferences of selection coefficients? We conduct our analysis under the discrete Wright-Fisher model by deriving the exact probability of an allele frequency trajectory in a population of time-varying size and we replicate our results under the diffusion model. For both models, we find that ignoring drift leads to estimates of selection coefficients that are nearly as accurate as estimates that account for the true population history, even when population sizes are small and drift is high. This result is of interest because inference methods that ignore drift are widely used in evolutionary studies and can be many orders of magnitude faster than methods that account for population sizes.

SpectralTDF: transition densities of diffusion processes with time-varying selection parameters, mutation rates and effective population sizes.

MOTIVATION: In the Wright-Fisher diffusion, the transition density function describes the time evolution of the population-wide frequency of an allele. This function has several practical applications in population genetics and computing it for biologically realistic scenarios with selection and demography is an important problem. RESULTS: We develop an efficient method for finding a spectral representation of the transition density function for a general model where the effective population size, selection coefficients and mutation parameters vary over time in a piecewise constant manner. AVAILABILITY AND IMPLEMENTATION: The method, called SpectralTDF, is available at https://sourceforge.net/projects/spectraltdf/ CONTACT: yss@berkeley.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Theory and applications of a deterministic approximation to the coalescent model.

Under the coalescent model, the random number nt of lineages ancestral to a sample is nearly deterministic as a function of time when nt is moderate to large in value, and it is well approximated by its expectation E[nt]. In turn, this expectation is well approximated by simple deterministic functions that are easy to compute. Such deterministic functions have been applied to estimate allele age, effective population size, and genetic diversity, and they have been used to study properties of models of infectious disease dynamics. Although a number of simple approximations of E[nt] have been derived and applied to problems of population-genetic inference, the theoretical accuracy of the resulting approximate formulas and the inferences obtained using these approximations is not known, and the range of problems to which they can be applied is not well understood. Here, we demonstrate general procedures by which the approximation nt≈E[nt] can be used to reduce the computational complexity of coalescent formulas, and we show that the resulting approximations converge to their true values under simple assumptions. Such approximations provide alternatives to exact formulas that are computationally intractable or numerically unstable when the number of sampled lineages is moderate or large. We also extend an existing class of approximations of E[nt] to the case of multiple populations of time-varying size with migration among them. Our results facilitate the use of the deterministic approximation nt≈E[nt] for deriving functionally simple, computationally efficient, and numerically stable approximations of coalescent formulas under complicated demographic scenarios.

Macrophage migration inhibitory factor acts as a neurotrophin in the developing inner ear.

This study is the first to demonstrate that macrophage migration inhibitory factor (MIF), an immune system 'inflammatory' cytokine that is released by the developing otocyst, plays a role in regulating early innervation of the mouse and chick inner ear. We demonstrate that MIF is a major bioactive component of the previously uncharacterized otocyst-derived factor, which directs initial neurite outgrowth from the statoacoustic ganglion (SAG) to the developing inner ear. Recombinant MIF acts as a neurotrophin in promoting both SAG directional neurite outgrowth and neuronal survival and is expressed in both the developing and mature inner ear of chick and mouse. A MIF receptor, CD74, is found on both embryonic SAG neurons and adult mouse spiral ganglion neurons. Mif knockout mice are hearing impaired and demonstrate altered innervation to the organ of Corti, as well as fewer sensory hair cells. Furthermore, mouse embryonic stem cells become neuron-like when exposed to picomolar levels of MIF, suggesting the general importance of this cytokine in neural development.

Improvements to a class of distance matrix methods for inferring species trees from gene trees.

Among the methods currently available for inferring species trees from gene trees, the GLASS method of Mossel and Roch (2010), the Shallowest Divergence (SD) method of Maddison and Knowles (2006), the STEAC method of Liu et al. (2009), and a related method that we call Minimum Average Coalescence (MAC) are computationally efficient and provide branch length estimates. Further, GLASS and STEAC have been shown to be consistent estimators of tree topology under a multispecies coalescent model. However, divergence time estimates obtained with these methods are all systematically biased under the model because the pairwise interspecific gene divergence times on which they rely must be more ancient than the species divergence time. Jewett and Rosenberg (2012) derived an expression for the bias of GLASS and used it to propose an improved method that they termed iGLASS. Here, we derive the biases of SD, STEAC, and MAC, and we propose improved analogues of these methods that we call iSD, iSTEAC, and iMAC. We conduct simulations to compare the performance of these methods with their original counterparts and with GLASS and iGLASS, finding that each of them decreases the bias and mean squared error of pairwise divergence time estimates. The new methods can therefore contribute to improvements in the estimation of species trees from information on gene trees.

A coalescent model for genotype imputation.

The potential for imputed genotypes to enhance an analysis of genetic data depends largely on the accuracy of imputation, which in turn depends on properties of the reference panel of template haplotypes used to perform the imputation. To provide a basis for exploring how properties of the reference panel affect imputation accuracy theoretically rather than with computationally intensive imputation experiments, we introduce a coalescent model that considers imputation accuracy in terms of population-genetic parameters. Our model allows us to investigate sampling designs in the frequently occurring scenario in which imputation targets and templates are sampled from different populations. In particular, we derive expressions for expected imputation accuracy as a function of reference panel size and divergence time between the reference and target populations. We find that a modestly sized "internal" reference panel from the same population as a target haplotype yields, on average, greater imputation accuracy than a larger "external" panel from a different population, even if the divergence time between the two populations is small. The improvement in accuracy for the internal panel increases with increasing divergence time between the target and reference populations. Thus, in humans, our model predicts that imputation accuracy can be improved by generating small population-specific custom reference panels to augment existing collections such as those of the HapMap or 1000 Genomes Projects. Our approach can be extended to understand additional factors that affect imputation accuracy in complex population-genetic settings, and the results can ultimately facilitate improvements in imputation study designs.

The cytokine macrophage migration inhibitory factor (MIF) acts as a neurotrophin in the developing inner ear of the zebrafish, Danio rerio.

Macrophage migration inhibitory factor (MIF) plays versatile roles in the immune system. MIF is also widely expressed during embryonic development, particularly in the nervous system, although its roles in neural development are only beginning to be understood. Evidence from frogs, mice and zebrafish suggests that MIF has a major role as a neurotrophin in the early development of sensory systems, including the auditory system. Here we show that the zebrafish mif pathway is required for both sensory hair cell (HC) and sensory neuronal cell survival in the ear, for HC differentiation, semicircular canal formation, statoacoustic ganglion (SAG) development, and lateral line HC differentiation. This is consistent with our findings that MIF is expressed in the developing mammalian and avian auditory systems and promotes mouse and chick SAG neurite outgrowth and neuronal survival, demonstrating key instructional roles for MIF in vertebrate otic development.

iGLASS: an improvement to the GLASS method for estimating species trees from gene trees.

Several methods have been designed to infer species trees from gene trees while taking into account gene tree/species tree discordance. Although some of these methods provide consistent species tree topology estimates under a standard model, most either do not estimate branch lengths or are computationally slow. An exception, the GLASS method of Mossel and Roch, is consistent for the species tree topology, estimates branch lengths, and is computationally fast. However, GLASS systematically overestimates divergence times, leading to biased estimates of species tree branch lengths. By assuming a multispecies coalescent model in which multiple lineages are sampled from each of two taxa at L independent loci, we derive the distribution of the waiting time until the first interspecific coalescence occurs between the two taxa, considering all loci and measuring from the divergence time. We then use the mean of this distribution to derive a correction to the GLASS estimator of pairwise divergence times. We show that our improved estimator, which we call iGLASS, consistently estimates the divergence time between a pair of taxa as the number of loci approaches infinity, and that it is an unbiased estimator of divergence times when one lineage is sampled per taxon. We also show that many commonly used clustering methods can be combined with the iGLASS estimator of pairwise divergence times to produce a consistent estimator of the species tree topology. Through simulations, we show that iGLASS can greatly reduce the bias and mean squared error in obtaining estimates of divergence times in a species tree.

MLH1 founder mutations with moderate penetrance in Spanish Lynch syndrome families.

The variants c.306+5G>A and c.1865T>A (p.Leu622His) of the DNA repair gene MLH1 occur frequently in Spanish Lynch syndrome families. To understand their ancestral history and clinical effect, we performed functional assays and a penetrance analysis and studied their genetic and geographic origins. Detailed family histories were taken from 29 carrier families. Functional analysis included in silico and in vitro assays at the RNA and protein levels. Penetrance was calculated using a modified segregation analysis adjusted for ascertainment. Founder effects were evaluated by haplotype analysis. The identified MLH1 c.306+5G>A and c.1865T>A (p.Leu622His) variants are absent in control populations and segregate with the disease. Tumors from carriers of both variants show microsatellite instability and loss of expression of the MLH1 protein. The c.306+5G>A variant is a pathogenic mutation affecting mRNA processing. The c.1865T>A (p.Leu622His) variant causes defects in MLH1 expression and stability. For both mutations, the estimated penetrance is moderate (age-cumulative colorectal cancer risk by age 70 of 20.1% and 14.1% for c.306+5G>A and of 6.8% and 7.3% for c.1865T>A in men and women carriers, respectively) in the lower range of variability estimated for other pathogenic Spanish MLH1 mutations. A common haplotype was associated with each of the identified mutations, confirming their founder origin. The ages of c.306+5G>A and c.1865T>A mutations were estimated to be 53 to 122 and 12 to 22 generations, respectively. Our results confirm the pathogenicity, moderate penetrance, and founder origin of the MLH1 c.306+5G>A and c.1865T>A mutations. These findings have important implications for genetic counseling and molecular diagnosis of Lynch syndrome.

Genome-wide association studies in diverse populations.

Genome-wide association (GWA) studies have identified a large number of SNPs associated with disease phenotypes. As most GWA studies have been performed in populations of European descent, this Review examines the issues involved in extending the consideration of GWA studies to diverse worldwide populations. Although challenges exist with issues such as imputation, admixture and replication, investigation of a greater diversity of populations could make substantial contributions to the goal of mapping the genetic determinants of complex diseases for the human population as a whole.