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bioRxiv2025

Prevalent cross-cell type QTL trans-regulatory genetic effects impacting innate lymphoid cells in the small intestine

Tissue function in homeostasis and disease arise from coordinated interactions between different cell types and can vary between individuals in a population, in part due to the impact of genetic variants. In barrier tissues such as the gut, innate lymphoid cells (ILCs) play critical roles in maintaining tissue homeostasis and immunity, but the genetic basis and associated regulatory circuitry affecting tissue ILCs remain largely unknown. Here, we systematically mapped the regulatory functions of genetic variants across 273,370 gut ILCs profiled by single cell RNA-seq from 274 diversity outbred (DO) mice. Computational analysis identified quantitative trait loci (QTL) impacting ILCs at three levels: cell subtype-specific mRNA expression (local and distal), cell subset proportions, and ILC gene expression programs (in trans), of which we experimentally validated a pivotal role for the transcription factor Rbpj in regulating ILC3s. All three classes of ILC QTL display polygenic inheritance signatures and broadly overlap with QTL affecting peripheral cytokine levels that we measured in another 261 DO mice. Strikingly, nearly half of trans-QTL affecting ILC traits did not overlap (within a 50-kb window) genes expressed in ILCs, and such loci were enriched for genes expressed by non-ILCs especially enteric neurons and intestinal glia. This suggests that such loci may act instead across cell type boundaries and allowed us to recover causal trans-cell type regulatory circuits in the tissue, including loci encoding multiple neuron-expressed peptides, epithelial-cell expressed Sox9, and phagocyte-expressed Ccl17. Finally, human orthologs of genes in QTL impacting gene expression and cell proportions are enriched for autoimmune disease risk heritability, suggesting their relevance to human disease. Our findings highlight how the impact of genetic variants may propagate to maintain tissue homeostasis and show a path to understand causality in tissue biology using quantitative genetics.

genetics↗

bioRxiv2025

Discovery and characterisation of gene by environment and epistatic genetic effects in a vertebrate model

Phenotypic variation arises from the interplay between genetic and environmental factors. However, disentangling these interactions for complex traits remains challenging in observational cohorts such as human biobanks. Instead, model organisms where genetic (G) and environmental (E) variation can be controlled offer a valuable complement to human studies in the analysis of higher-order genetic effects such as GxE interactions, dominance, and epistasis. Here, we utilized 76 medaka strains of the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel, to compare heart rate plasticity across temperatures. An F2 segregation analysis identified 16 quantitative trait loci (QTLs), with many exhibiting dominance, GxE, GxG, and GxGxE interactions. We experimentally validated four candidate genes using gene editing, revealing their temperature-sensitive impact on heart function. Finally, we devised simulations to assess how GWAS discovery power is influenced by the choice of statistical models, showing that the apparent additivity in human GWAS is to be expected given study design and sample sizes of current studies. This work demonstrates the value of controlled model organism studies for dissecting the genetics of complex traits and provides guidance on the design of genetic association studies.

genetics↗

bioRxiv2025

Separating direct, indirect and parent-of-origin genetic effects in the human population

Here, we present a novel approach to estimate the degree to which the phenotypic effect of a DNA locus is attributable to four components: alleles in the child (direct genetic effects), alleles in the mother and the father (indirect genetic effects), or is dependent upon the parent from which it is inherited (parent-of-origin, PofO effects). Applying our model, JODIE, to 30,000 child-mother-father trios with phased DNA information from the Estonian Biobank (EstBB) and the Norwegian Mother, Father, Child Cohort (MoBa), we jointly estimate the phenotypic variance attributable to these four effects unbiased of assortative mating (AM) for height, body mass index (BMI) and childhood educational test score (EA). For all three traits, direct effects make the largest contribution to the genetic effect variance. But we find that parental indirect genetic effects make an equivalent combined contribution, and that there is a non-zero PofO effect variance for all traits. We calculate the heritability that would be obtained at the populationlevel in the absence of AM for common DNA loci, and show that the proportional contribution of direct effects to these heritability values can be calculated as 64.0% for EA in MoBa, 77.1% and 63.4% for height in MoBa and EstBB, and 81.2% and 88.0% for BMI in MoBa and EstBB. Additionally, using within-family genome-wide association testing, we identify 276 independently associated DNA regions that replicate across two additional biobanks, which all show a genotype-phenotype relationship that reflects an interplay of direct, indirect and PofO effects. Determining how direct, parental and PofO genetic effects combine across loci genome-wide to influence human phenotypic variation requires joint modeling of parental and child genotypes alongside the parental origin of loci and here, we make the first attempt to do this in the human population.

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bioRxiv2025

Positive genetic interactions: high impact, but underrepresented in theliterature

Genetic interactions, where the combined effect of perturbing two genes leads to a phenotype that deviates from the expectation based on the effects of the individual perturbations, often provide important information about the functional architecture of biological systems. These interactions are commonly classified as negative or positive based on whether the phenotype of the double mutant is less than or greater than what would be expected based on the single mutant effects. When the trait in question is fitness, systematic studies of pairwise deletions have shown that negative interactions typically link genes with similar functional annotations, while positive interactions typically link genes that are less obviously related and thus often viewed as less informative. However, research in the sociology of science suggests that transformative discoveries often arise from unexpected, cross-domain linkages. To evaluate these competing perspectives, we integrated large-scale genetic interaction data in yeast with literature annotations from the Saccharomyces Genome Database and citation data from iCite. We found that positive genetic interactions are associated with greater scientific impact, as measured by citation metrics, contrary to prevailing assumptions. Despite their greater impact, positive interactions are significantly underrepresented in the scientific literature. Interestingly, the advent of an unbiased mapping technology capable of detecting positive and negative interactions with equal facility did not alleviate this bias, implicating factors beyond mere discoverability. We also find that the research building on positive interactions forms a more interconnected body of follow-on work. Together, our analyses reveal the underappreciated value of positive genetic interactions and suggest that investigating cross-domain genetic links represents an under-exploited opportunity deserving of greater attention.

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bioRxiv2025

Low genetic diversity in Colobus vellerosus populations in Kikele Sacred and Okuta Kobunan Forests, Benin

The critically endangered white-thighed colobus, Colobus vellerosus, is on the brink of extinction, necessitating the implementation of effective conservation management strategies. The population in Kikele village serves as the primary remaining stronghold for this species in Benin, comprising around twenty-eight individuals in the small Kikele Sacred Forest and an additional eight individuals in the community-managed Okuta Kobunan Forest. These two populations are believed to have descended from a single founding pair introduced to the Kikele region circa 1800. Given the small population size and the possible severe genetic bottleneck at its foundation, the genetic diversity might be extremely low. In our study, we conducted a first analysis of the genetic diversity of the two populations using mitochondrial markers, the complete cytochrome b (cytb) and a segment of the hypervariable control region (D-loop, 750 bp). Our findings revealed only one cytb haplotype, along with two haplotypes that differ by just one site in the D-loop. We recommend a range-wide population genetic assessment of the species to explore the possibility of translocations as a potential genetic rescue strategy.

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bioRxiv2025

A platform for the systematic interrogation of genetic interactions in human cells: 26 gene by genome-wide double knockout screens as a proof of concept

Genetic interactions are typically studied by looking at the phenotype that results from disruption of pairs of genes, as well as from higher order combinations of perturbations. Systematically interrogating all pairwise combinations provides insights into how genes are organized into pathways and complexes to sustain cellular homeostasis and how interacting genes respond to stressors and external signals. Genetic interactions have been studied extensively in yeast, due, in part, to the availability of a systematic collection of gene knockouts, and the development of Synthetic Genetic Array (SGA) technology. In contrast, such approaches are more challenging in human cells and therefore comparable data for human cells is scarce. This study introduces an innovative approach to functionally characterize genetic interactions in human cells through CRISPR/Cas9 screens using a pooled genome-wide knockout library in NALM6 cells. By combining a single guide RNA (sgRNA) targeting the gene of interest (aka the query) in cells already infected with an inducible genome-wide sgRNA pool, it is possible to achieve near saturation of genome-wide double knockouts. We conducted 26 of these screens, which we term "gene by genome-wide" knockout screens. This approach can be rapidly performed, in part, because it bypasses the need to generate genotyped isogenic knockout clones. Data from these screens identified both expected and novel synthetic lethal and synthetic rescue interactions, demonstrating that this strategy is effective for large-scale genetic research in human cells. Additionally, we show that these GBGW screens can be combined with chemical perturbation to reveal new synthetic interactions that are not apparent without drug treatment. Finally, we show that cDNA overexpression can be incorporated with genome-wide knockouts to systematically explore gain-of-function scenarios. The complete dataset is accessible on the ChemoGenix website (URL: https://chemogenix.iric.ca).

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bioRxiv2025

High-resolution, genotype-free mapping of genetic variation with CRI-SPA-Map

Genetic variation within species shapes phenotypes, but identifying the specific genes and variants that cause phenotypic differences is costly and challenging. Here, we introduce CRI-SPA-Map, a genetic mapping strategy combining CRISPR-Cas9 genome engineering, selective ploidy ablation (SPA), and high-throughput phenotyping for precise genetic mapping with or without genotyping in the yeast Saccharomyces cerevisiae. In CRI-SPA-Map, a donor strain carrying SPA machinery is mated to a genetically different recipient strain harboring a genome-integrated selectable cassette. In the resulting diploid, CRISPR-Cas9 cuts the cassette for replacement with DNA from the homologous donor chromosome. Donor chromosomes are then removed using SPA to yield haploid recombinant strains. To establish CRI-SPA-Map, we mated a W303 SPA strain to 92 strains from the BY4742 yeast knockout collection that carry gene deletion cassettes on the left arm of chromosome XIV and created 1,451 recombinant isolates. Whole-genome sequencing verified that deletion cassette replacement introduced short donor DNA tracts of variable length, resulting in a finely recombined mapping population. Using only the known location of the gene deletions, which marks where donor DNA is introduced, we identified a 6.5 kb-region shaping yeast growth. Further dissection of this region pinpointed two causal variants in two genes, MKT1 and SAL1. Engineering these variants alone and in combination revealed gene-by-environment interactions at both genes, as well as epistatic interactions between them that were in turn dependent on the environment. CRI-SPA-Map is a cost-effective strategy for creating high-resolution recombinant panels of yeast strains for identifying the genetic basis of phenotypic variation.

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bioRxiv2025

Geography and forest naturalness as drivers of genetic diversity in saproxylic beetles

Understanding how geography and forest management shape genetic diversity is pivotal for the conservation of saproxylic beetles, the key indicators of forest ecosystem integrity. Using a multi-species Double Digest Restriction-site Associated DNA sequencing approach, we analyzed genome-scale SNP variation in 12 saproxylic beetle species (rare and common, incl. pests) differing in abundance, ecology, and mobility across central European forests, with respect to both geographic location and forest status. Analyses of distance-based redundancy test, molecular variance, and population structure consistently revealed that geography is the main determinant of genetic differentiation, with clear east-west clustering in several species. Forest status represented in four levels (commercial not protected, nature reserve, primeval not protected, and primeval protected) exerted a secondary but detectable effect in a subset of taxa, especially among rare and habitat-specialized species. For these species, populations from primeval protected sites showed distinct genetic structure compared to those from commercial stands. Our results highlight that regional connectivity, maintaining gene flow across a large spatial scale, should be prioritized in conservation planning, complemented by the protection of primeval forest refugia and the maintenance of structural complexity in commercial forests. By integrating high-resolution genomic data with geographical and management context, this study provides actionable insights into the processes shaping genetic structure in forest-dependent insects and underscores the importance of incorporating genetic monitoring into sustainable forest biodiversity management.

genetics↗

bioRxiv2017

Evaluating genetic ancestry and self-reported ethnicity in the context of carrier screening

BackgroundCurrent professional society guidelines recommend genetic carrier screening be offered on the basis of ethnicity, or when using expanded carrier screening panels, they recommend to compute residual risk based on ethnicity. We investigated the reliability of self-reported ethnicity in 9138 subjects referred to carrier screening. Self-reported ethnicity gathered from test requisition forms and during post-test genetic counseling, and genetic ancestry predicted by a statistical model, were compared for concordance.\n\nResultsWe identified several discrepancies between the two sources of self-reported ethnicity and genetic ancestry. Only 30.3% of individuals who indicated Mediterranean ancestry during consultation self-reported this on requisition forms. Additionally, the proportion of individuals who reported Southeast Asian but were estimated to have a different genetic ancestry was found to depend on the source of self-report. Finally, individuals who reported Latin American demonstrated a high degree of ancestral admixture. As a result, carrier rates and residual risks provided for patient decision-making are impacted if using self-reported ethnicity.\n\nConclusionOur analysis highlights the unreliability of ethnicity classification based on patient self-reports. We recommend the routine use of pan-ethnic carrier screening panels in reproductive medicine. Furthermore, the use of an ancestry model would allow better estimation of carrier rates and residual risks.

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bioRxiv2017

Genetics of trans-regulatory variation in gene expression

Heritable variation in gene expression provides a critical bridge between differences in genome sequence and the biology of many traits, including common human diseases. However, the sources of most regulatory genetic variation remain unknown. Here, we used transcriptome profiling in 1,012 yeast segregants to map the genetic basis of variation in gene expression with high statistical power. We identified expression quantitative trait loci (eQTL) that together account for over 70% of the total genetic contribution to variation in mRNA levels, allowing us to examine the sources of regulatory variation comprehensively. We found that variation in the expression of a typical gene has a complex genetic architecture involving multiple eQTL. We also detected hundreds of eQTL pairs with significant non-additive interactions in an unbiased genome-wide scan. Although most genes were influenced by a local eQTL located close to the gene, most expression variation arose from distant, trans-acting eQTL located far from their target genes. Nearly all distant eQTL clustered at 102 \"hotspot\" locations, some of which influenced the expression of thousands of genes. Hotspot regions were enriched for transcription factor genes and altered expression of their target genes though both direct and indirect mechanisms. Many local eQTL had no detectable effects on the expression of other genes in trans. These results reveal the complexity of genetic influences on transcriptome variation in unprecedented depth and detail.

genetics↗

bioRxiv2017

Multivariate analysis of the cotton seed ionome reveals integrated genetic signatures of abiotic stress response

To mitigate the effects of heat and drought stress, a better understanding of the genetic control of physiological responses to these environmental conditions is needed. To this end, we evaluated an upland cotton (Gossypium hirsutum L.) mapping population under water-limited and well-watered conditions in a hot, arid environment. The elemental concentrations (ionome) of seed samples from the population were profiled in addition to those of soil samples taken from throughout the field site to better model environmental variation. The elements profiled in seeds exhibited moderate to high heritabilities, as well as strong phenotypic and genotypic correlations between elements that were not altered by the imposed irrigation regimes. Quantitative trait loci (QTL) mapping results from a Bayesian classification method identified multiple genomic regions where QTL for individual elements colocalized, suggesting that genetic control of the ionome is highly interrelated. To more fully explore this genetic architecture, multivariate QTL mapping was implemented among groups of biochemically related elements. This analysis revealed both additional and pleiotropic QTL responsible for coordinated control of phenotypic variation for elemental accumulation. Machine learning algorithms that utilized only ionomic data predicted the irrigation regime under which genotypes were evaluated with very high accuracy. Taken together, these results demonstrate the extent to which the seed ionome is genetically interrelated and predictive of plant physiological responses to adverse environmental conditions.\n\nOne sentence summaryThe cotton seed ionome has a shared genetic basis that provides insight into the physiological status of the plant.

genetics↗

bioRxiv2017

Systems genetics identifies modifiers of Alzheimer’s disease risk and resilience

Identifying genes that modify symptoms of Alzheimers disease (AD) will provide novel therapeutic strategies to prevent, cure or delay AD. To discover genetic modifiers of AD, we combined a mouse model of AD with a genetically diverse reference panel to generate F1 mice harboring identical high-risk human AD mutations but which differ across the remainder of their genome. We first show that genetic variation profoundly modifies the impact of causal human AD mutations and validate this panel as an AD model by demonstrating a high degree of phenotypic, transcriptomic, and genetic overlap with human AD. Genetic mapping was used to identify candidate modifiers of cognitive deficits and amyloid pathology, and viral-mediated knockdown was used to functionally validate Trpc3 as a modifier of AD. Overall, work here introduces a humanized mouse population as an innovative and reproducible resource for the study of AD and identifies Trpc3 as a novel therapeutic target.\n\nHighlightsO_LINew transgenic mouse population enables mapping of AD risk and resilience factors\nC_LIO_LITranscriptomic and phenotypic profiles in diverse AD mice parallel those in humans\nC_LIO_LIApoe genotype and expression correlate with cognitive symptoms in mice\nC_LIO_LITrpc3 is a novel target to reduce amyloid load and cognitive symptoms in AD\nC_LI

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bioRxiv2017

Genetic evidence for shared risks across psychiatric disorders and related traits in a Swedish population twin sample

Psychiatric traits related to categorically-defined psychiatric disorders are heritable and present to varying degrees in the general population. In this study, we test the hypothesis that genetic risk factors associated with psychiatric disorders are also associated with continuous variation in milder population traits. We combine a contemporary twin analytic approach with polygenic risk score (PRS) analyses in a large population-based twin sample. Questionnaires assessing traits of autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), learning difficulties, tic disorders (TD), obsessive-compulsive disorder (OCD), anxiety, major depressive disorder (MDD), mania and psychotic experiences were administered to a large, Swedish twin sample. Individuals with clinical psychiatric diagnoses were identified using the Swedish National Patient Register. Joint categorical/continuous twin modeling was used to estimate genetic correlations between psychiatric diagnoses and continuous traits. PRS for psychiatric disorders were calculated based on independent discovery genetic data. The association between PRS for each disorder and related continuous traits was tested. We found mild to strong genetic correlations between psychiatric diagnoses and corresponding traits (ranging from .31-.69) in the twin analyses. There was also evidence of association between PRS for ASD, ADHD, TD, OCD, anxiety, MDD and schizophrenia with related population traits. These results indicate that genetic factors which predispose to psychiatric disorders are also associated with milder variation in characteristic traits throughout the general population, for many psychiatric phenotypes. This finding supports the conceptualization of psychiatric disorders as the extreme ends of continuous traits.

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bioRxiv2018

DNA methylation mediates genetic liability to non-syndromic cleft lip/palate

BackgroundNon-syndromic cleft lip/palate (nsCL/P) is a complex trait with genetic and environmental risk factors. Around 40 distinct genetic risk loci have been identified for nsCL/P, but many reside in non-protein-coding regions with an unclear function. We hypothesised that one possibility is that the genetic risk variants influence susceptibility to nsCL/P through gene regulation pathways, such as those involving DNA methylation.\n\nMethodsUsing nsCL/P Genome-wide association study summary data and methylation data from four studies, we used Mendelian randomization and joint likelihood mapping to identify putative loci where genetic liability to nsCL/P may be mediated by variation in DNA methylation in blood.\n\nResultsThere was evidence at three independent loci, VAX1 (10q25.3), LOC146880 (17q23.3) and NTN1 (17p13.1), that liability to nsCL/P and variation in DNA methylation might be driven by the same genetic variant. Follow up analyses using DNA methylation data, derived from lip and palate tissue, and gene expression catalogues provided further insight into possible biological mechanisms.\n\nConclusionsGenetic variation may increase liability to nsCL/P by influencing DNA methylation and gene expression at VAX1, LOC146880 and NTN1.

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bioRxiv2018

Alzheimer’s environmental and genetic risk scores are differentially associated with ‘g’ and δ

IntroductionWe investigated the association of the Australian National University Alzheimers Disease Risk Index (ANU-ADRI) and an AD genetic risk score (GRS) with cognitive performance.\n\nMethodsThe ANU-ADRI (composed of 11 risk factors for AD) and GRS (composed of 25 AD risk loci) were computed in 1,061 community-dwelling older adults. Participants were assessed on 11 cognitive tests and activities of daily living. Structural equation modelling was used to evaluate the association of the ANU-ADRI and GRS with: 1) general cognitive ability (g) 2) dementia related variance in cognitive performance ({delta}) and 3) verbal ability, episodic memory, executive function and processing speed.\n\nResultsA worse ANU-ADRI score was associated with poorer performance in g, {delta}, and each cognitive domain. A worse GRS was associated with poorer performance in {delta} and episodic memory.\n\nDiscussionThe ANU-ADRI was broadly associated with worse cognitive performance, validating its further use in early dementia risk assessment.\n\nHighlightsO_LIAn environmental/lifestyle dementia risk index is broadly associated with cognitive performance\nC_LIO_LIAn Alzheimers genetic risk score is associated with dementia severity and episodic memory\nC_LIO_LIThe environmental risk index is more strongly associated with dementia severity than genetic risk\nC_LI\n\nResearch in ContextO_ST_ABSSystematic ReviewC_ST_ABSThe authors reviewed the literature using online databases (e.g. PubMed). Previous research has highlighted the need for dementia risk assessment tools to be evaluated on outcomes prior to dementia onset, such as cognitive performance. The relevant citations have been appropriately cited.\n\nInterpretationThe Australian National University Alzheimers Disease Risk Index (ANU-ADRI) was more broadly associated with cognitive performance than Alzheimers genetic risk. For the ANU-ADRI, stronger effects were observed for dementia-related variance in cognitive task performance that for variance in general cognitive function. This suggests that ANU-ADRI is more specifically associated with dementia-related processes and further validates its use in early risk assessment for dementia.\n\nFuture DirectionsAccordingly, future studies should seek to evaluate the association of the ANU-ADRI and genetic risk with AD biomarkers and longitudinal cognitive performance to evaluate differential trajectories in g and {delta}.

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bioRxiv2018

A genetic perspective on the relationship between eudaimonic -and hedonic well-being

Whether hedonism or eudaimonism are two distinguishable forms of well-being is a topic of ongoing debate. To shed light on the relation between the two, large-scale available molecular genetic data were leveraged to gain more insight into the genetic architecture of the overlap between hedonic and eudaimonic well-being. Hence, we conducted the first genome-wide association studies (GWAS) of eudaimonic well-being (N = [~]108K) and linked it to a GWAS of hedonic well-being (N = [~] 222K). We identified the first two genome-wide significant independent loci for eudaimonic well-being and 6 independent loci for hedonic well-being. Joint analyses revealed a moderate phenotypic correlation (r = 0.53), but a high genetic correlation (rg = 0.78) between eudaimonic and hedonic well-being. For both traits we identified enrichment in the frontal cortex -and cingulate cortex as well as the cerebellum to be top ranked. Bi-directional Mendelian Randomization analyses using two-sample MR indicated some evidence for a causal relationship from hedonic well-being to eudaimonic well-being whereas no evidence was found for the reverse. Additionally, genetic correlations patterns with a range of positive and negative related phenotypes were largely similar for hedonic -and eudaimonic well-being. Our results reveal a large genetic overlap between hedonism and eudaimonism.

genetics↗

bioRxiv2018

An ultra-dense haploid genetic map for evaluating the highly fragmented genome assembly of Norway spruce (Picea abies)

Norway spruce (Picea abies (L.) Karst.) is a conifer species of substanital economic and ecological importance. In common with most conifers, the P. abies genome is very large ([~]20 Gbp) and contains a high fraction of repetitive DNA. The current P. abies genome assembly (v1.0) covers approximately 60% of the total genome size but is highly fragmented, consisting of >10 million scaffolds. The genome annotation contains 66,632 gene models that are at least partially validated (www.congenie.org), however, the fragmented nature of the assembly means that there is currently little information available on how these genes are physically distributed over the 12 P. abies chromosomes. By creating an ultra-dense genetic linkage map, we anchored and ordered scaffolds into linkage groups, which complements the fine-scale information available in assembly contigs. Our ultra-dense haploid consensus genetic map consists of 21,056 markers derived from 14,336 scaffolds that contain 17,079 gene models (25.6% of the validated gene models) that we have anchored to the 12 linkage groups. We used data from three independent component maps, as well as comparisons with previously published Picea maps to evaluate the accuracy and marker ordering of the linkage groups. We demonstrate that approximately 3.8% of the anchored scaffolds and 1.6% of the gene models covered by the consensus map have likely assembly errors as they contain genetic markers that map to different regions within or between linkage groups. We further evaluate the utility of the genetic map for the conifer research community by using an independent data set of unrelated individuals to assess genome-wide variation in genetic diversity using the genomic regions anchored to linkage groups. The results show that our map is sufficiently dense to enable detailed evolutionary analyses across the P. abies genome.

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bioRxiv2018

Brain scans from 21297 individuals reveal the genetic architecture of hippocampal subfield volumes

The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimers disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields genetic architecture. T1-weighted brain scans (n=21297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, covarying for total hippocampal volume. We further calculated the single nucleotide polymorphism (SNP)-based heritability of twelve subfields, as well as their genetic correlation with each other, with other structural brain features, and with AD and schizophrenia. All outcome measures were corrected for age, sex, and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from .14 to .27, all p< 1x10-16) and clustered together based on their genetic correlations compared to other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.

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