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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2017

Cryptography for genetic material

Genetic information can be highly sensitive and can be used to identify its source. To conceal genetic information, cryptographic methods can be applied to genetic material itself, concealing sensitive information prior to the generation of sequence data. The cryptographic method described here uses randomly divided subsets of barcodes and random pooling to securely generate pools of genetic material. The privacy obtained by these methods are measured here using differential privacy.

genetics↗

bioRxiv2017

Additive genetic and environmental contributions to the longitudinal association between violent victimization and depression

Research suggests victims of violent crime are more likely to suffer from major depressive disorder (MDD) compared to non-victims. Less research has utilized longitudinal data to evaluate the directionality of this relationship or examined the genetic and environmental contributions to this association across the life course. The current study evaluated 473 full-sibling pairs and 209 half-sibling pairs (N = 1,364) from the National Longitudinal Survey of Youth (Mage = 20.14, SD = 3.94). Cross-lagged models were used to examine the directionality of effects between violent victimization and MDD over time. Biometric liability models were used to examine genetic and environmental influences on single and chronic violent victimization and MDD. Violent victimization was associated with increases in MDD during late adolescence, but MDD was more associated with increased risk for violent victimization across young adulthood. Biometric analysis indicated that 20% and 30% of the association between MDD and single and chronic victimization, respectively, was accounted for by common genetic influences. Results from the current study suggest individuals who exhibit symptoms of MDD are at higher risk for chronic victimization rather than developing MDD as a result of victimization. Shared genetic liability accounted for between 20 to 30% of this longitudinal relationship.

genetics↗

bioRxiv2017

116 independent genetic variants influence the neuroticism personality trait in over 329,000 UK Biobank individuals.

Neuroticism is a stable personality trait 1; twin studies report heritability between 30% and 50% 2, and SNP-based heritability is about 15% 3. Higher levels of neuroticism are associated with poorer mental and physical health 4,5, and the economic burden of neuroticism for societies is high 6. To date, genome-wide association (GWA) studies of neuroticism have identified up to 11 genetic loci 3,7. Here we report 116 significant independent genetic loci from a GWA of neuroticism in 329,821 UK Biobank participants, with replication available in a GWA meta-analysis of neuroticism in 122,867 individuals. Genetic signals for neuroticism were enriched in neuronal genesis and differentiation pathways, and substantial genetic correlations were found between neuroticism and depressive symptoms (rg = .82, SE=.03), major depressive disorder (rg = .69, SE=.07) and subjective wellbeing (rg = -.68, SE=.03) alongside other mental health traits. These discoveries significantly advance our understanding of neuroticism and its association with major depressive disorder.

genetics↗

bioRxiv2017

The genetic architecture of the network underlying flowering time variation in Arabidopsis thaliana

Flowering time is a key adaptive trait in plants and is tightly controlled by a complex regulatory network that responds to seasonal signals. In a rapidly changing climate, understanding the genetic basis of flowering time variation is important for both agriculture and ecology. Genetic mapping has revealed many genetic variants affecting flowering time, but the effects on the gene regulatory networks in population-scale are still largely unknown. We dissected flowering time networks using multi-layered Swedish population data from Arabidopsis thaliana, consisting of flowering time and transcriptome collected under constant 10{degrees}C growth temperature in addition to full genome sequence data. Our analysis identified multiple alleles of the key flowering time gene FLOWERING LOCUS C (FLC) as the primary determinant of the network underlying flowering time variation under our condition. Genetic variation of FLC affects multiple-pathways through known flowering-time genes including FLOWERING LOCUS T (FT), and SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1). We demonstrated that an extremely simple single-locus model of FLC involving allelic variation and expression explains almost a half of flowering time variation, with 60% of the effect being mediated through FLC expression. Furthermore, the accuracy of the model fitted at 10{degrees}C is almost unchanged at 16{degrees}C.

genetics↗

bioRxiv2017

Genetic markers of ADHD-related variations in intracranial volume

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common and highly heritable neurodevelopmental disorder with a complex pathophysiology, where genetic risk is hypothesized to be mediated by alterations in structure and function of diverse brain networks. We tested one aspect of this hypothesis by investigating the genetic overlap between ADHD (n=55,374) and (mainly subcortical) brain volumes (n=11,221-24,704), using the largest publicly available studies. At the level of common variant genetic architecture, we discovered a significant negative genetic correlation between ADHD and intracranial volume (ICV). Meta-analysis of individual variants found significant loci associated with both ADHD risk and ICV; additional loci were identified for ADHD and amygdala, caudate nucleus, and putamen volumes. Gene-set analysis in the ADHD-ICV meta-analytic data showed significant association with variation in neurite outgrowth-related genes. In summary, our results suggest new hypotheses about biological mechanisms involved in ADHD etiology and highlight the need to study additional brain parameters.

genetics↗

bioRxiv2017

Systematic Mendelian randomization framework elucidates hundreds of genetic loci which may influence disease through changes in DNA methylation levels

We have undertaken an extensive Mendelian randomization (MR) study using methylation quantitative trait loci (mQTL) as genetic instruments to assess the potential causal relationship between genetic variation, DNA methylation and 139 complex traits. Using two-sample MR, we observed 1,191 effects across 62 traits where genetic variants were associated with both proximal DNA methylation (i.e. cis-mQTL) and complex trait variation (P<1.39x10-08). Joint likelihood mapping provided evidence that the causal mQTL for 364 of these effects across 58 traits was also likely the causal variant for trait variation. These effects showed a high rate of replication in the UK Biobank dataset for 14 selected traits, as 121 of the attempted 129 effects replicated. Integrating expression quantitative trait loci (eQTL) data suggested that genetic variants responsible for 319 of the 364 mQTL effects also influence gene expression, which indicates a coordinated system of effects that are consistent with causality. CpG sites were enriched for histone mark peaks in tissue types relevant to their associated trait and implicated genes were enriched across relevant biological pathways. Though we are unable to distinguish mediation from horizontal pleiotropy in these analyses, our findings should prove valuable in identifying candidate loci for further evaluation and help develop mechanistic insight into the aetiology of complex disease.

genetics↗

bioRxiv2017

Genetic pleiotropy between mood disorders, metabolic, and endocrine traits in a multigenerational pedigree

Bipolar disorder (BD) is a mental disorder characterized by alternating periods of depression and mania. Individuals with BD have higher levels of early mortality than the general population, and a substantial proportion of this may be due to increased risk for comorbid diseases. Recent evidence suggests that pleiotropy, either in the form of a single risk-allele or the combination of multiple loci genome-wide, may underlie medical comorbidity between traits and diseases. To identify the molecular events that underlie BD and related medical comorbidities, we generated imputed whole genome sequence (WGS) data using a population specific reference panel, for an extended multigenerational Old Order Amish pedigree (400 family members) segregating BD and related disorders. First, we investigated all putative disease-causing variants at known Mendelian disease loci present in this pedigree. Second, we performed genomic profiling using polygenic risk scores to establish each individual's risk for several complex diseases. To explore the contribution of disease genes to BD we performed gene-based and variant-based association tests for BD, and found that Mendelian disease genes are enriched in the top results from both tests (OR=20.3, p=1x10-3; OR=2.2, p=1x10-2). We next identified a set of Mendelian variants that co-occur in individuals with BD more frequently than their unaffected family members, including the R3527Q mutation in APOB associated with hypercholesterolemia. Using polygenic risk scores, we demonstrated that BD individuals from this pedigree were enriched for the same common risk-alleles for BD as in the general population ({beta}=0.416, p=6x10-4). Furthermore, in the extended Amish family we find evidence for a common genetic etiology between BD and clinical autoimmune thyroid disease (p=1x10-4), diabetes (p=1x10-3), and lipid traits such as triglyceride levels (p=3x10-4). We identify genomic regions that contribute to the differences between BD individuals and unaffected family members by calculating local genetic risk for independent LD blocks. Our findings provide evidence for the extensive genetic pleiotropy that can drive epidemiological findings of comorbidities between diseases and other complex traits. Identifying such patterns may enable the subtyping of complex diseases and facilitate our understanding of the genetic mechanisms underlying phenotypic heterogeneity.

genetics↗

bioRxiv2017

Alzheimer’s Genetic Risk Score linked to Incident Mild Behavioral Impairment

Mild Behavioral Impairment (MBI) describes the emergence of later-life Neuropsychiatric Symptoms (NPS) as an at-risk state for cognitive decline and dementia and as a potential manifestation of prodromal dementia. How NPS mechanistically link to the development of Mild Cognitive Impairment (MCI) and Alzheimers disease (AD) is not fully understood. Potential mechanisms include either shared risk factors that are related to both NPS and cognitive impairment, or AD pathology promoting NPS. This is the first study to examine whether AD genetic loci, individually and as a genetic risk score, are a shared risk factor with MBI. 1377 older adults (aged 72-79; 738 males; 763 normal cognition) from the PATH Through Life project. MBI was assessed in accordance with Criterion 1 of the ISTAART-AA diagnostic criteria using the Neuropsychiatric Inventory. 25 LOAD risk loci were genotyped and a weighted genetic risk score (GRS) was constructed. Binomial logistic regression adjusting for age, gender, and education examined the association between LOAD GRS and MBI domains. An increase in the LOAD GRS and APOE*{varepsilon}4 were associated with higher likelihood of Affective Dysregulation; MS4A4A-rs4938933*C and MS4A6A-rs610932*G were associated with a reduced likelihood of Affective Dysregulation; ZCWPW1-rs1476679*C was associated with a reduced likelihood of Social Inappropriateness and Abnormal Perception; BIN1-rs744373*G and EPHA1-rs11767557*C were associated with higher likelihood of Abnormal Perception; NME8-rs2718058*G was associated with a reduced likelihood Decreased Motivation. These findings suggest a common genetic etiology between MBI and traditionally recognized memory problems observed in AD and improve our understanding of the pathophysiological features underlying MBI.

genetics↗

bioRxiv2017

Genetic variation across the human olfactory receptor repertoire alters odor perception

The human olfactory receptor repertoire is characterized by an abundance of genetic variation that affects receptor response, but the perceptual effects of this variation are unclear. To address this issue, we sequenced the OR repertoire in 332 individuals and examined the relationship between genetic variation and 276 olfactory phenotypes, including the perceived intensity and pleasantness of 68 odorants at two concentrations, detection thresholds of three odorants, and general olfactory acuity. Genetic variation in a single OR frequently associated with odorant perception, and we validated 10 cases in which in vitro OR function correlated with in vivo odorant perception using a functional assay. This more than doubles the published examples of this phenomenon. For eight of these 10 cases, reduced receptor function associated with reduced intensity perception. In addition, we used participant genotypes to quantify genetic ancestry and found that, in combination with single OR genotype, age and gender, we can explain between 10 and 20% of the perceptual variation in 15 olfactory phenotypes, highlighting the importance of single OR genotype, ancestry, and demographic factors in variation of olfactory perception.

genetics↗

bioRxiv2017

A genome-wide association study finds novel genetic associations with broadly-defined headache in UK Biobank (N = 223,773)

Headache is the most common neurological symptom and a leading cause of years lived with disability. We sought to identify the genetic variants associated with a broadly-defined headache phenotype in 223,773 subjects from the UK Biobank cohort. We defined headache based on a specific question answered by the UK Biobank participants. We performed a genome-wide association study of headache as a single entity, using 74,461 cases and 149,312 controls. We identified 3,343 SNPs which reached the genome-wide significance level of P < 5 x 10-8. The SNPs were located in 28 loci, with the top SNP of rs11172113 in the LRP1 gene having a P value of 4.92 x 10-47. Of the 28 loci, 14 have previously been associated with migraine. Among 14 new loci, rs77804065 with a P value of 5.87 x 10-15 in the LINC02210-CRHR1 gene was the top SNP.\n\nPositive relationships (P < 0.001) between multiple brain tissues and genetic associations were identified through tissue expression analysis, whereas no vascular related tissues showed significant relationships. We identified several significant positive genetic correlations between headache and other psychological traits including neuroticism, depressive symptoms, insomnia, and major depressive disorder.\n\nOur results suggest that brain function is closely related to broadly-defined headache. In addition, we also found that many psychological traits have genetic correlations with headache.

genetics↗

bioRxiv2017

Genetic architecture drives seasonal onset of hibernation in the 13-lined ground squirrel

Hibernation is a highly dynamic phenotype whose timing, for many mammals, is controlled by a circannual clock and accompanied by rhythms in body mass and food intake. When housed in an animal facility, 13-lined ground squirrels exhibit individual variation in the seasonal onset of hibernation, which is not explained by environmental or biological factors, such as body mass and sex. We hypothesized that underlying genetic architecture instead drives variation in this timing. After first increasing the contiguity of the genome assembly, we therefore employed a genotype-by-sequencing approach to characterize genetic variation in 153 13-lined ground squirrels. Combining this with datalogger records, we estimated high heritability (61-100%) for the seasonal onset of hibernation. After applying a genome-wide scan with 46,996 variants, we also identified 21 loci significantly associated with hibernation immergence, which alone accounted for 54% of the variance in the phenotype. The most significant marker (SNP 15, p=3.81x10-6) was located near prolactin-releasing hormone receptor (PRLHR), a gene that regulates food intake and energy homeostasis. Other significant loci were located near genes functionally related to hibernation physiology, including muscarinic acetylcholine receptor M2 (CHRM2), involved in the control of heart rate, exocyst complex component 4 (EXOC4) and prohormone convertase 2 (PCSK2), both of which are involved in insulin signaling and processing. Finally, we applied an expression quantitative loci (eQTL) analysis using existing transcriptome datasets, and we identified significant (q<0.1) associations for 9/21 variants. Our results highlight the power of applying a genetic mapping strategy to hibernation and present new insight into the genetics driving its seasonal onset.

genetics↗

bioRxiv2017

polymapR: linkage analysis and genetic map construction from F1 populations of outcrossing polyploids

MotivationPolyploid species carry more than two copies of each chromosome, a condition found in many of the worlds most important crops. Genetic mapping in polyploids is more complex than in diploid species, resulting in a lack of available software tools. These are needed if we are to realise all the opportunities offered by modern genotyping platforms for genetic research and breeding in polyploid crops.\n\nResultspolymapR is an R package for genetic linkage analysis and integrated genetic map construction from bi-parental populations of outcrossing autopolyploids. It can currently analyse triploid, tetraploid and hexaploid marker datasets and is applicable to various crops including potato, leek, alfalfa, blueberry, chrysanthemum, sweet potato or kiwifruit. It can detect, estimate and correct for preferential chromosome pairing, and has been tested on high-density marker datasets from potato, rose and chrysanthemum, generating high-density integrated linkage maps in all of these crops.\n\nAvailability and ImplementationpolymapR is freely available under the general public license from the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/packages=polymapR.\n\nContactChris Maliepaard chris.maliepaard@wur.nl or Roeland E. Voorrips roeland.voorrips@wur.nl

genetics↗

bioRxiv2018

Genome-wide analysis of adolescent psychotic-like experiences shows genetic overlap with psychiatric disorders

This study aimed to test for overlap in genetic influences between psychotic experience traits shown by adolescents in the community, and clinically-recognized psychiatric disorders in adulthood, specifically schizophrenia, bipolar disorder, and major depression. The full spectra of psychotic experience domains, both in terms of their severity and type (positive, cognitive, and negative), were assessed using self- and parent-ratings in three European community samples aged 15-19 years (Final N incl. siblings = 6,297-10,098). A mega-genome-wide association study (mega-GWAS) for each psychotic experience domain was performed. SNP-heritability of each psychotic experience domain was estimated using genomic-relatedness-based restricted maximum-likelihood (GREML) and linkage disequilibrium-(LD-) score regression. Genetic overlap between specific psychotic experience domains and schizophrenia, bipolar disorder, and major depression was assessed using polygenic risk scoring (PRS) and LD-score regression. GREML returned SNP-heritability estimates of 3-9% for psychotic experience trait domains, with higher estimates for less skewed traits (Anhedonia, Cognitive Disorganization) than for more skewed traits (Paranoia and Hallucinations, Parent-rated Negative Symptoms). Mega-GWAS analysis identified one genome-wide significant association for Anhedonia within IDO2 but which did not replicate in an independent sample. PRS analysis revealed that the schizophrenia PRS significantly predicted all adolescent psychotic experience trait domains (Paranoia and Hallucinations only in non-zero scorers). The major depression PRS significantly predicted Anhedonia and Parent-rated Negative Symptoms in adolescence. Psychotic experiences during adolescence in the community show additive genetic effects and partly share genetic influences with clinically-recognized psychiatric disorders, specifically schizophrenia and major depression.

genetics↗

bioRxiv2018

Disentangling genetic overlap between Attention-Deficit/Hyperactivity Disorder, literacy and language

Interpreting polygenic overlap between ADHD and both literacy- and language-related impairments is challenging as genetic confounding can bias associations. Here, we investigate evidence for links between polygenic ADHD risk and multiple literacy- and language-related abilities (LRAs), assessed in UK children (N[≤]5,919), conditional on genetic effects shared with educational attainment (EA). Genome-wide summary statistics on clinical ADHD and years-of-schooling were obtained from large consortia (N[≤]326,041). ADHD-polygenic scores (ADHD-PGS) were inversely associated with LRAs in ALSPAC, most consistently with reading-related abilities, and explained [≤]1.6% phenotypic variation. Polygenic links were then dissected into both genetic effects shared with and independent of EA using multivariable regressions (MVR), analogous to Mendelian Randomization approaches accounting for mediating effects. Conditional on EA, polygenic ADHD risk remained associated with multiple literacy-related skills, phonemic awareness and verbal intelligence, but not language-related skills such as listening comprehension and non-word repetition. Pooled reading performance showed the strongest overlap with ADHD independent of EA. Using conservative ADHD-instruments (P-threshold<5x10-8) this corresponded to a 0.35 decrease in Z-scores per log-odds in ADHD-liability (P=9.2x10-5). Using subthreshold ADHD-instruments (P-threshold<0.0015), these associations had lower magnitude, but higher predictive accuracy, with a 0.03 decrease in Z-scores (P=1.4x10-6). Polygenic ADHD-effects shared with EA were of equal strength and at least equal magnitude compared to those independent of EA, for all LRAs studied, and only detectable using subthreshold instruments. Thus, ADHD-related polygenic links are highly susceptible to genetic confounding, concealing an ADHD-specific association profile that primarily involves reading-related impairments, but few language-related problems.

genetics↗

bioRxiv2018

Large-Scale Genome-Wide Meta Analysis of Polycystic Ovary Syndrome Suggests Shared Genetic Architecture for Different Diagnosis Criteria.

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed with different criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease indicate shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. Only one locus differed in its association by diagnostic criteria, otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or Rotterdam criteria across common variants at 13 loci.

genetics↗

bioRxiv2018

Towards automation of germline variant curation inclinical cancer genetics

Cancer care professionals are confronted with interpreting results from multiplexed gene sequencing of patients at hereditary risk for cancer. Assessments for variant classification now require orthogonal data searches, requiring aggregation of multiple lines of evidence from diverse resources. The burden of evidence for each variant to meet thresholds for pathogenicity or actionability now poses a growing challenge for those seeking to counsel patients and families following germline genetic testing. A computational algorithm that automates, provides uniformity and significantly accelerates this interpretive process is needed. The tool described here, Pathogenicity of Mutation Analyzer (PathoMAN) automates germline genomic variant curation from clinical sequencing based on ACMG guidelines. PathoMAN aggregates multiple tracks of genomic, protein and disease specific information from public sources. We compared expert manually curated variant data from studies on (i) prostate cancer (ii) breast cancer and (iii) ClinVar to assess performance. PathoMAN achieves high concordance (83.1% pathogenic, 75.5% benign) and negligible discordance (0.04% pathogenic, 0.9% benign) when contrasted against expert curation. Some loss of resolution (8.6% pathogenic, 23.64% benign) and gain of resolution (6.6% pathogenic, 1.6% benign) was also observed. We highlight the advantages and weaknesses related to the programmable automation of variant classification. We also propose a new nosology for the five ACMG classes to facilitate more accurate reporting to ClinVar. The proposed refinements will enhance utility of ClinVar to allow further automation in cancer genetics. PathoMAN will reduce the manual workload of domain level experts. It provides a substantial advance in rapid classification of genetic variants by generating robust models using a knowledge-base of diverse genetic data https://pathoman.mskcc.org.

genetics↗

bioRxiv2018

Genome-wide association study of social genetic effects on 170 phenotypes in laboratory mice

The phenotype of one individual can be affected not only by the individuals own genotypes (direct genetic effects, DGE) but also by genotypes of interacting partners (indirect genetic effects, IGE). IGE have been detected using polygenic models in multiple species, including laboratory mice and humans. However, the underlying mechanisms remain largely unknown. Genome-wide association studies of IGE (igeGWAS) can point to IGE genes, but have not yet been applied to non-familial IGE arising from "peers" and affecting biomedical phenotypes. In addition, the extent to which igeGWAS will identify loci not identified by dgeGWAS remains an open question. Finally, findings from igeGWAS have not been confirmed by experimental manipulation. We leveraged a dataset of 170 behavioural, physiological and morphological phenotypes measured in 1,812 genetically heterogeneous laboratory mice to study IGE arising between same-sex, adult, unrelated laboratory mice housed in the same cage. We developed methods for igeGWAS in this context and identified 24 significant IGE loci for 17 phenotypes (FDR < 10%). There was no overlap between IGE loci and DGE loci for the same phenotype, which was consistent with the moderate genetic correlations between DGE and IGE for the same phenotype estimated using polygenic models. Finally, we fine-mapped seven significant IGE loci to individual genes and confirmed, in an experiment with a knockout model, that Epha4 gives rise to IGE on stress-coping strategy and wound healing. Our results demonstrate the potential for igeGWAS to identify IGE genes and shed some light into the mechanisms of peer influence.

genetics↗

bioRxiv2018

Genetic contributions to ectopic sperm cell migration in Caenorhabditis nematodes

Reproductive barriers involving gametic incompatibilities can act to enhance population divergence and promote the persistence of species boundaries. Observing gametic interactions in internal fertilizing organisms, however, presents a considerable practical challenge to characterizing mechanisms of such gametic isolation. Here we exploit the transparency of Caenorhabditis nematodes to investigate gametic isolation mediated by sperm that can migrate to ectopic locations, with this sperm invasion capable of inducing female sterility and premature death. As a step toward identifying genetic factors and mechanisms associated with female susceptibility to sperm invasion, we characterized a panel of 25 C. elegans genetic mutants to test for effects on the incidence and severity of sperm invasion in both conspecific and interspecies matings. We found genetic perturbations to contribute to distinct patterns of susceptibility that identify ovulation dynamics and sperm guidance cues as modulators of ectopic sperm migration incidence and severity. Genotypes confer distinctive phenotypic sensitivities to the sperm from conspecific C. elegans males versus heterospecific C. nigoni males, implicating evolution of functional divergence in the history of these species for components of sperm-reproductive tract interactions. Sexually-antagonistic co-evolution within species that drives divergent trait and molecular evolution between species provides a working model to explain mismatched species-specific gametic interactions that promote or mitigate ectopic sperm migration.\n\nArticle SummaryHere we exploit the transparency of C. elegans roundworms to investigate reproductive barriers between species resulting from sperm-cell invasion into ectopic tissues, causing female sterility and premature death. We quantify female sensitivity to sperm invasion from conspecific and interspecific matings in a panel of 25 C. elegans genetic mutants, to demonstrate how ovulation dynamics and sperm guidance cues act as modulators of ectopic sperm-cell migration incidence and severity. We observe both conserved and divergent responses to different species, implicating evolution of functional divergence for components of sperm-reproductive tract interactions consistent with the outcome of sexually-antagonistic co-evolution.

genetics↗