PaperPlayer biorxiv genetics

Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.11.247049v1?rss=1

Authors: Balbona, J. V., Kim, Y., Keller, M. C.

Abstract:

Offspring resemble their parents for both genetic and environmental reasons. Understanding the relative magnitude of these alternatives has long been a core interest in behavioral genetics research, but traditional designs, which compare phenotypic covariances to make inferences about unmeasured genetic and environmental factors, have struggled to disentangle them. Recently, Kong et al. (2018) showed that by correlating offspring phenotypic values with the measured polygenic score of parents' nontransmitted alleles, one can estimate the effect of "genetic nurture"-- a type of passive gene-environment covariation that arises when heritable parental traits directly influence offspring traits. Here, we instantiate this basic idea in a set of causal models that provide novel insights into the estimation of parental influences on offspring. Most importantly, we show how jointly modeling the parental polygenic scores and the offspring phenotypes can provide an unbiased estimate of the variation attributable to the environmental influence of parents on offspring, even when the polygenic score accounts for a small fraction of trait heritability. This model can be further extended to a) account for the influence of assortative mating at both equilibrium and disequilibrium (after a single generation of assortment), and b) include measured parental phenotypes, allowing for the estimation of the total variation due to additive genetic effects and their covariance with the familial environment. By utilizing path analysis techniques developed for extended twin family designs, our approach provides a general framework for modeling polygenic scores in family studies and allows for various model extensions that can be used to answer old questions about familial influences in new ways.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.09.243311v1?rss=1

Authors: McInnes, G. M., Altman, R. B.

Abstract:

Pharmacogenetics studies how genetic variation leads to variability in drug response. Guidelines for selecting the right drug and right dose to patients based on their genetics are clinically effective, but are still widely unused. For some drugs, the normal clinical decision making process may lead to the optimal dose of a drug that minimizes side effects and maximizes effectiveness. Without measurements of genotype, physicians and patients may observe and adjust dosage in a manner that reflects the underlying genetics. The emergence of genetic data linked to longitudinal clinical data in large biobanks offers an opportunity to confirm known pharmacogenetic interactions as well as discover novel associations by investigating outcomes from normal clinical practice. Here we use the UK Biobank to search for pharmacogenetic interactions among 200 drugs and 9 genes among 200,000 participants. We identify associations between pharmacogene phenotypes and drug maintenance dose as well as side effect incidence. We find support for several known drug-gene associations as well as novel pharmacogenetic interactions.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.11.246827v1?rss=1

Authors: Kim, Y., Balbona, J., Keller, M. C.

Abstract:

In a companion paper (Balbona et al. (2020)), we introduced a series of causal models that use polygenic scores from transmitted and nontransmitted alleles, the offspring trait, and parental traits to estimate the variation due to the environmental influences the parental trait has on the offspring trait (vertical transmission) as well as additive genetic effects. These models also estimate and account for the gene-gene and gene-environment covariation that arises from assortative mating and vertical transmission respectively. In the current study, we simulated polygenic scores and phenotypes of parents and offspring under genetic and vertical transmission scenarios, assuming two types of assortative mating. We instantiated the models from our companion paper in the OpenMx software, and compared the true values of parameters to maximum likelihood estimates from models fitted on the simulated data to quantify the bias and precision of estimates. We show that parameter estimates from these models are unbiased when assumptions are met, but as expected, they are biased to the degree that assumptions are unmet. Standard errors of the estimated variances due to vertical transmission and to genetic effects decrease with increasing sample sizes and with increasing r2 values of the polygenic score. Even when the polygenic score explains a modest amount of trait variation (r2 = .05), standard errors of these standardized estimates were reasonable (< .05) for n = 16K trios, and smaller sample sizes (e.g., down to 4K) when the polygenic score is more predictive. These causal models offer a novel approach for understanding how parents influence their offspring, but their use requires polygenic scores on relevant traits that are modestly predictive (e.g., r2 > .025) as well as datasets with genomic and phenotypic information on parents and offspring. The utility of polygenic scores for elucidating parental influences should thus serve as additional motivation for large genomic biobanks to perform GWAS's on traits that may be relevant to parenting and to oversample close relatives, particularly parents and offspring.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.11.247031v1?rss=1

Authors: Fu, Y.-X., Wang, G., Chen, K., Ma, X., Liu, S., Miao, W.

Abstract:

Cell division is a necessity of life which can be either mitotic or amitotic. While both are fundamental, amitosis is sometimes considered a relic of little importance in biology. Nevertheless, eukaryotes often have polyploid cells, including cancer cells, which may divide amitotically. To understand how amitosis ensures the completion of cell division, we turn to the macronuclei of ciliates. The grand scheme governing the proliferation of the macronuclei of ciliate cells, which involves chromosomal replication and the amitosis, is currently unknown. Using a novel model that encompasses a wide range of mechanisms together with experimental data of the composition of mating types at different stages derived from a single karyonide of Tetrahymena thermophila, we show that the chromosomal replication of the macronucleus has a strong head-start effect, with only about five copies of chromosomes replicated at a time and persistent reuse of the chromosomes involved in the early replication. Furthermore the fission of a fully grown macronucleus is non-random, with a strong tendency to push chromosomes and their replications to the same daughter cell. Similar strategies may exist for other Tetrahymena species or ciliates, and have implications to the amitosis of polyploid cells of multicellular organisms.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.11.246611v1?rss=1

Authors: Ding, X., Fragoza, R., Singh, P., Zhang, S., Yu, H., Schimenti, J. C.

Abstract:

Purpose: Approximately 7% of men suffer from infertility worldwide and sperm abnormalities are the major cause. Though genetic defects are thought to underlie a substantial fraction of all male infertility cases, the actual molecular bases are usually undetermined. Because the consequences of most genetic variants in populations are unknown, this complicates genetic diagnosis even after genome sequencing of patients. Some patients with ciliopathies, including primary ciliary dyskinesia (PCD) and Bardet-Biedl syndrome (BBS), also suffer from infertility because sperm flagella, which share several characteristics with cilia, are also affected in these patients. Methods: To identify infertility-causing genetic variants in human populations, we used in silico predictions to identify potentially deleterious SNP (single nucleotide polymorphism) alleles of RABL2A, a gene essential for normal cilia and flagella function. Candidate variants were assayed for protein stability in vitro, and the destabilizing variants were modeled in mice using CRISPR/Cas9-mediated genome editing. The resulting mice were characterized phenotypically for reproductive and developmental defects. Results: Two of the SNP alleles, Rabl2L119F (rs80006029) and Rabl2V158F (rs200121688), destabilized the protein. Mice bearing these alleles exhibited PCD- and BBS-associated disorders including male infertility, early growth retardation, excessive weight gain in adulthood, heterotaxia, pre-axial polydactyly, neural tube defects (NTD) and hydrocephalus. Conclusion: Our study identified and validated pathogenicity of two variants causing ciliopathies and male infertility in human populations, and identified phenotypes not previously described for null alleles of Rabl2.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.10.245167v1?rss=1

Authors: Gaynor, R. C., Gorjanc, G., Hickey, J. M.

Abstract:

This paper introduces AlphaSimR, an R package for stochastic simulations of plant and animal breeding programs. AlphaSimR is a highly flexible software package able to simulate a wide range of plant and animal breeding programs for diploid and autopolyploid species. AlphaSimR is ideal for testing the overall strategy and detailed design of breeding programs. AlphaSimR utilizes a scripting approach to building simulations that is particularly well suited for modeling highly complex breeding programs, such as commercial breeding programs. The primary benefit of this scripting approach is that it frees users from preset breeding program designs and allows them to model nearly any breeding program design. This paper lists the main features of AlphaSimR and provides a brief example simulation to show how to use the software.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.09.243287v1?rss=1

Authors: Trochet, H., Hussin, J.

Abstract:

Genetic risk scores (GRS), also known as polygenic risk scores, are a tool to estimate individuals' liabilities to a disease or trait measurement based solely on genetic information. They have value in clinical applications as well as for assessing relationships between traits and discovering causal determinants of complex disease. However, it has been shown that these scores are not robust to differences across continental populations and may not be portable within them either. Even within a single population, they may have variable predictive ability across sexes and socioeconomic strata, raising questions about their potential biases. In this paper, we investigated the accuracy of two different GRS across population strata of the UK Biobank, separated along principal component (PC) axes, considering different approaches to account for social and environmental confounders. We found that these scores did not predict the real differences in phenotypes observed along the first principal component, with evidence of discrepancies on axes as high as PC45. These results demonstrate that the measures currently taken for correcting for population structure are not sufficient, and the need for social and environmental confounders to be factored into the creation of GRS.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.10.244293v1?rss=1

Authors: Elsworth, B. L., Lyon, M. S., Alexander, T., Liu, Y., Matthews, P., Hallett, J., Bates, P., Palmer, T., Haberland, V., Davey Smith, G., Zheng, J., Haycock, P., Gaunt, T. R., Hemani, G.

Abstract:

Data generated by genome-wide association studies (GWAS) are growing fast with the linkage of biobank samples to health records, and expanding capture of high-dimensional molecular phenotypes. However the utility of these efforts can only be fully realised if their complete results are collected from their heterogeneous sources and formats, harmonised and made programmatically accessible. Here we present the OpenGWAS database, an open source, open access, scalable and high-performance cloud-based data infrastructure that imports and publishes complete GWAS summary datasets and metadata for the scientific community. Our import pipeline harmonises these datasets against dbSNP and the human genome reference sequence, generates summary reports and standardises the format of results and metadata. Users can access the data via a website, an application programming interface, R and Python packages, and also as downloadable files that can be rapidly queried in high performance computing environments. OpenGWAS currently contains 126 billion genetic associations from 14,582 complete GWAS datasets representing a range of different human phenotypes and disease outcomes across different populations. We developed R and Python packages to serve as conduits between these GWAS data sources and a range of available analytical tools, enabling Mendelian randomization, genetic colocalisation analysis, fine mapping, genetic correlation and locus visualisation. OpenGWAS is freely accessible at https://gwas.mrcieu.ac.uk, and has been designed to facilitate integration with third party analytical tools.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.10.236562v1?rss=1

Authors: Roule, T., Ariel, F., Hartmann, C., Crespi, M., Blein, T.

Abstract:

Clustered organization of biosynthetic non-homologous genes is emerging as a characteristic feature of plant genomes. The co-regulation of clustered genes seems to largely depend on epigenetic reprogramming and three-dimensional chromatin conformation. Here we identified the long noncoding RNA (lncRNA) MARneral Silencing (MARS), localized inside the Arabidopsis marneral cluster, and which controls the local epigenetic activation of its surrounding region in response to ABA. MARS modulates the POLYCOMB REPRESSIVE COMPLEX 1 (PRC1) component LIKE-HETEROCHROMATIN PROTEIN 1 (LHP1) binding throughout the cluster in a dose-dependent manner, determining H3K27me3 deposition and chromatin condensation. In response to ABA, MARS decoys LHP1 away from the cluster and promotes the formation of a chromatin loop bringing together the MARNERAL SYNTHASE 1 (MRN1) locus and a distal ABA-responsive enhancer. The enrichment of co-regulated lncRNAs in clustered metabolic genes in Arabidopsis suggests that the acquisition of novel noncoding transcriptional units may constitute an additional regulatory layer driving the evolution of biosynthetic pathways.

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Link to bioRxiv paper:

http://biorxiv.org/cgi/content/short/2020.08.10.244244v1?rss=1

Authors: Hannan, F. M., Stevenson, M., Bayliss, A. L., Stokes, V. j., Stewart, M. E., Kooblall, K. G., Gorvin, C. M., Codner, G. F., Teboul, L., Wells, S., Thakker, R. V.

Abstract:

Mutations of the adaptor protein-2 sigma subunit (AP2S1) gene which encodes AP2-sigma2, a component of the ubiquitous AP2 heterotetrameric complex involved in endosomal trafficking of the calcium-sensing receptor (CaSR), cause familial hypocalciuric hypercalcemia type 3 (FHH3). FHH3 patients have heterozygous AP2S1 missense Arg15 mutations (p.Arg15Cys, p.Arg15His or p.Arg15Leu) with marked hypercalcemia and occasional hypophosphatemia and osteomalacia. To further characterise the phenotypic spectrum and calcitropic pathophysiology of FHH3, we used CRISPR/Cas9 genome editing to generate mice harboring the AP2S1 p.Arg15Leu mutation, which causes the most severe FHH3 phenotype. Heterozygous (Ap2s1+/L15) mice were viable, and had marked hypercalcemia, hypermagnesemia, hypophosphatemia, and increased plasma concentrations of parathyroid hormone, fibroblast growth factor 23 and alkaline phosphatase activity, but normal pro-collagen type 1 N-terminal pro-peptide and 1,25 dihydroxyvitamin D. Homozygous (Ap2s1L15/L15) mice invariably died perinatally. The AP2S1 p.Arg15Leu mutation impaired protein-protein interactions between AP2-sigma2 and the other AP2 subunits, and the CaSR. Cinacalcet, a CaSR allosteric activator, ameliorated the hypercalcemia and elevated PTH concentrations, but not the diminished AP2-sigma2-CaSR interaction. Thus, our studies have established a mouse model with a germline loss-of-function AP2S1 mutation that is representative for FHH3 in humans, and demonstrated that cinacalcet corrects the abnormalities of plasma calcium and PTH.

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