Magnitude and predictability of ph fluctuations shape plastic responses to ocean acidification

16 pages, 5 figures, supplemental material https://www.journals.uchicago.edu/doi/suppl/10.1086/712930.-- Data and Code Availability: All raw data and referenced supplemental files in this article have been deposited in the Dryad Digital Repository (https://doi.org/10.5061/dryad.tqjq2bvxc; Bitter et al. 2020). All code associated with statistical analyses and figure generation for this article are publicly available at GitHub (https://github.com/MarkCBitter/pHFluctuation_Plasticity) and Zenodo (https://doi.org/10.5281/zenodo.4306829; Bitter 2020)Phenotypic plasticity is expected to facilitate the persistence of natural populations as global change progresses. The attributes of fluctuating environments that favor the evolution of plasticity have received extensive theoretical investigation, yet empirical validation of these findings is still in its infancy. Here, we combine high-resolution environmental data with a laboratory-based experiment to explore the influence of habitat pH fluctuation dynamics on the plasticity of gene expression in two populations of the Mediterranean mussel, Mytilus galloprovincialis. We linked differences in the magnitude and predictability of pH fluctuations in two habitats to population-specific gene expression profiles in ambient and stressful pH treatments. Our results demonstrate population-based differentiation in gene expression plasticity, whereby mussels native to a habitat exhibiting a large magnitude of pH fluctuations with low predictability display reduced phenotypic plasticity between experimentally imposed pH treatments. This work validates recent theoretical findings on evolution in fluctuating environments, suggesting that the predictability of fluctuating selection pressures may play a predominant role in shaping the phenotypic variation observed across natural populationsM.C.B. was supported by a National Science Foundation Graduate Research Fellowship Program grant (1746045) and a Department of Education grant (P200A150101). L.K. was supported by a National Science Foundation grant (OCE-1521597), which provided research support for this work. This research was also supported in part by the University of Chicago’s France and Chicago Collaborating in the Sciences program to C.A.P. and M.C.B.With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)Peer reviewe

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Sample Metadata

Metadata information for the 117 Olympia oysters (Ostrea lurida) included in the VCF files in this repository. STRATA: population assignment in analyses; LOCATION: sampling location name; REGION: assigned phylogeographic region; LATITUDE and LONGITIDE of sampling site; LIBRARY: the sequencing run of the sampl

Fasta file of outlier GBS loci

Fasta file of 129 genotype-by-sequencing loci potentially involved in local adaptation, as determined by at least two methods (pcadapt, OutFLANK, or BayeScan). The 18 loci with positive BLASTx hits are annotated

Parameters for ipyrad assembly

Parameters used in ipyrad for assembling genotype-by-sequencing data

Example parameter file for EEMS

A parameter file for running EEMS (Estimated Effective Migration Surfaces), including parameter values for setting the variance of the proposal distributions

Outfiles of ipyrad assembly

Outfiles produced by ipyrad after assembly of genotype-by-sequencing data. .vcf is used as the input for additional, downstream filtering. _stats.txt provides statistics over the course of the ipyrad run

VCF file of putative neutral SNPs

VCF file of 13,073 putative neutral SNPs derived from genotype-by-sequencing data of 117 Olympia oysters (Ostrea lurida) sampled across 19 populations. Obtained by filtering the full dataset of any SNP found on a locus containing at least one outlier SNP

Population Structure and Local Adaptation in the Olympia Oyster (Ostrea lurida)

Effective management of threatened species requires an understanding of both the genetic connectivity among populations and adaptive population divergence. For the numerous coastal marine species with planktonic dispersal, high connectivity can obscure population boundaries and oppose the diversifying effects of natural selection through homogenizing gene flow. Using an ecologically and commercially important marine bivalve as a model system, my dissertation aimed to characterize the spatial scales of neutral and adaptive differentiation in the face of gene flow and identify candidate loci under selection. The Olympia oyster (Ostrea lurida) is native from Baja California to the central coast of Canada and distributed over strong environmental gradients. Following devastating commercial exploitation by the early 20th century, recovery of O. lurida populations has faced other anthropogenic challenges, including ocean acidification. For my dissertation, I used high-throughput sequencing, bioinformatics, and mesocosm experiments to 1) describe the neutral and adaptive population genetic structure in O. lurida, 2) characterize adaptive phenotypic variation at a local scale, and 3) evaluate molecular responses to acidification stress across genetically diverged populations in two bivalve species. Significant population structure in the Olympia oyster was observed using both neutral and putative adaptive genetic markers derived from genotype-by-sequencing of oysters across 20 sites. To determine if local adaptation can occur among populations with high inferred gene flow, I investigated genetic and phenotypic variation among three populations of oysters in Puget Sound, WA. Through a common garden experiment on oysters that had been reared for up to two generations in common conditions, I demonstrated that these three populations exhibit heritable differences in reproductive timing, larval growth rate, and juvenile growth rate. Adaptations to natural long-standing variation of ocean pH in widespread species along western North America may be informative for predicting resilience to projected conditions. Overlapping the Olympia oyster’s range, the purple-hinged rock scallop (Crassadoma gigantea) is found from southern California to the Aleutian Islands. To understand inter- and intraspecific variation in response to reduced pH, I compared gene expression responses to two pH treatments (7.4 and 7.8) in adult oysters and rock scallops from multiple genetically diverged populations. Within species, genes were identified that exhibited a conserved response to pH across populations or a significant population-specific response—the latter are considered candidate genes involved in local adaptation