Female Genetic Contributions to Sperm Competition in Drosophila melanogaster

In many species, sperm can remain viable in the reproductive tract of a female well beyond the typical interval to remating. This creates an opportunity for sperm from different males to compete for oocyte fertilization inside the female’s reproductive tract. In Drosophila melanogaster, sperm characteristics and seminal fluid content affect male success in sperm competition. On the other hand, although genome-wide association studies (GWAS) have demonstrated that female genotype plays a role in sperm competition outcome as well, the biochemical, sensory, and physiological processes by which females detect and selectively use sperm from different males remain elusive. Here, we functionally tested 26 candidate genes implicated via a GWAS for their contribution to the female’s role in sperm competition, measured as changes in the relative success of the first male to mate (P1). Of these 26 candidates, we identified eight genes that affect P1 when knocked down in females, and showed that five of them do so when knocked down in the female nervous system. In particular, Rim knockdown in sensory pickpocket (ppk)+ neurons lowered P1, confirming previously published results, and a novel candidate, caup, lowered P1 when knocked down in octopaminergic Tdc2+ neurons. These results demonstrate that specific neurons in the female’s nervous system play a functional role in sperm competition and expand our understanding of the genetic, neuronal, and mechanistic basis of female responses to multiple matings. We propose that these neurons in females are used to sense, and integrate, signals from courtship or ejaculates, to modulate sperm competition outcome accordingly.

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Female genetic contributions to sperm competition in Drosophila melanogaster

10.1101/500546 ◽

2018 ◽

Author(s):

Dawn S. Chen ◽

Sofie Y.N. Delbare ◽

Simone L. White ◽

Jessica L. Sitnik ◽

Martik Chatterjee ◽

...

Keyword(s):

Nervous System ◽

Drosophila Melanogaster ◽

Sperm Competition ◽

Reproductive Tract ◽

Seminal Fluid ◽

Association Studies ◽

Genome Wide Association Studies ◽

Physiological Processes ◽

Female Genotype ◽

Mechanistic Basis

In many species, sperm can remain viable in the reproductive tract of a female well beyond the typical interval to remating. This creates an opportunity for sperm from different males to compete for oocyte fertilization inside the female’s reproductive tract. In Drosophila melanogaster, sperm morphology and seminal fluid content affect male success in sperm competition. On the other hand, although genome-wide association studies (GWAS) have demonstrated that female genotype plays a role in sperm competition outcome as well, the biochemical, sensory and physiological processes by which females detect and selectively use sperm from different males remain elusive. Here, we functionally tested 27 candidate genes implicated via a GWAS for their contribution to the female’s role in sperm competition, measured as changes in the relative success of the first male to mate (P1). Of these 27 candidates, we identified eight genes that affect P1 when knocked down in females, and also showed that six of them do so when knocked down in the female nervous system. Two genes in particular, Rim and caup, lowered P1 when knocked down in sensory pickpocket (ppk)+ neurons and octopaminergic Tdc2+ neurons, respectively. These results establish a functional role for the female’s nervous system in the process of sperm competition and expand our understanding of the genetic, neuronal and mechanistic basis of female responses to multiple matings. We propose that through their nervous system, females actively assess male compatibility based on courtship or ejaculates and modulate sperm competition outcome accordingly.

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Post-Copulatory Sexual Selection

Evolutionary Biology ◽

10.1093/obo/9780199941728-0131 ◽

2021 ◽

Author(s):

Patricia L.R. Brennan ◽

Dara N. Orbach

Keyword(s):

Sexual Selection ◽

Sperm Competition ◽

Female Choice ◽

Reproductive Tract ◽

Seminal Fluid ◽

Fertilization Success ◽

Female Reproductive Tract ◽

Cryptic Female Choice ◽

Trade Offs ◽

Morphological Criteria

The field of post-copulatory sexual selection investigates how female and male adaptations have evolved to influence the fertilization of eggs while optimizing fitness during and after copulation, when females mate with multiple males. When females are polyandrous (one female mates with multiple males), they may optimize their mating rate and control the outcome of mating interactions to acquire direct and indirect benefits. Polyandry may also favor the evolution of male traits that offer an advantage in post-copulatory male-male sperm competition. Sperm competition occurs when the sperm, seminal fluid, and/or genitalia of one male directly impacts the outcome of fertilization success of a rival male. When a female mates with multiple males, she may use information from a number of traits to choose who will sire her offspring. This cryptic female choice (CFC) to bias paternity can be based on behavioral, physiological, and morphological criteria (e.g., copulatory courtship, volume and/or composition of seminal fluid, shape of grasping appendages). Because male fitness interests are rarely perfectly aligned with female fitness interests, sexual conflict over mating and fertilization commonly occur during copulatory and post-copulatory interactions. Post-copulatory interactions inherently involve close associations between female and male reproductive characteristics, which in many species potentially include sperm storage and sperm movement inside the female reproductive tract, and highlight the intricate coevolution between the sexes. This coevolution is also common in genital morphology. The great diversity of genitalia among species is attributed to sexual selection. The evolution of genital attributes that allow females to maintain reproductive autonomy over paternity via cryptic female choice or that prevent male manipulation and sexual control via sexually antagonistic coevolution have been well documented. Additionally, cases where genitalia evolve through intrasexual competition are well known. Another important area of study in post-copulatory sexual selection is the examination of trade-offs between investments in pre-copulatory and post-copulatory traits, since organisms have limited energetic resources to allocate to reproduction, and securing both mating and fertilization is essential for reproductive success.

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Inference and visualization of phenome-wide causal relationships using genetic data: an application to dental caries and periodontitis

10.1101/865956 ◽

2019 ◽

Cited By ~ 1

Author(s):

Simon Haworth ◽

Pik Fang Kho ◽

Pernilla Lif Holgerson ◽

Liang-Dar Hwang ◽

Nicholas J. Timpson ◽

...

Keyword(s):

Dental Caries ◽

Causal Inference ◽

Mendelian Randomization ◽

Association Studies ◽

List Type ◽

Genome Wide Association Studies ◽

Causal Relationships ◽

Link Type ◽

Alternative Method ◽

Causal Variable

AbstractBackgroundHypothesis-free Mendelian randomization studies provide a way to assess the causal relevance of a trait across the human phenome but can be limited by statistical power or complicated by horizontal pleiotropy. The recently described latent causal variable (LCV) approach provides an alternative method for causal inference which might be useful in hypothesis-free experiments.MethodsWe developed an automated pipeline for phenome-wide tests using the LCV approach including steps to estimate partial genetic causality, filter to a meaningful set of estimates, apply correction for multiple testing and then present the findings in a graphical summary termed a causal architecture plot. We apply this process to body mass index and lipid traits as exemplars of traits where there is strong prior expectation for causal effects and dental caries and periodontitis as exemplars of traits where there is a need for causal inference.ResultsThe results for lipids and BMI suggest that these traits are best viewed as creating consequences on a multitude of traits and conditions, thus providing additional evidence that supports viewing these traits as targets for interventions to improve health. On the other hand, caries and periodontitis are best viewed as a downstream consequence of other traits and diseases rather than a cause of ill health.ConclusionsThe automated process is available as part of the MASSIVE pipeline from the Complex-Traits Genetics Virtual Lab (https://vl.genoma.io) and results are available in (https://view.genoma.io). We propose causal architecture plots based on phenome-wide partial genetic causality estimates as a way visualizing the overall causal map of the human phenome.Key messagesThe latent causal variable approach uses summary statistics from genome-wide association studies to estimate a parameter termed genetic causality proportion.Systematic estimation of genetic causality proportion for many pairs of traits provides an alternative method for phenome-wide causal inference with some theoretical and practical advantages compared to phenome-wide Mendelian randomization.Using this approach, we confirm that lipid traits are an upstream risk factor for other traits and diseases, and we identify that dental diseases are predominantly a downstream consequence of other traits rather than a cause of poor systemic health.The method assumes no bidirectional causality and no confounding by environmental correlates of genotypes, so care is needed when these assumptions are not met.We developed an automated and accessible pipeline for estimating phenome-wide causal relationships and generating interactive visual summaries.

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Qtlizer: comprehensive QTL annotation of GWAS results

Scientific Reports ◽

10.1038/s41598-020-75770-7 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Matthias Munz ◽

Inken Wohlers ◽

Eric Simon ◽

Tobias Reinberger ◽

Hauke Busch ◽

...

Keyword(s):

Association Studies ◽

Housekeeping Genes ◽

R Package ◽

Genome Wide Association Studies ◽

Protein Abundance ◽

Base Pairs ◽

Link Type ◽

Genome Wide ◽

Wide Range ◽

Distance Limit

AbstractExploration of genetic variant-to-gene relationships by quantitative trait loci such as expression QTLs is a frequently used tool in genome-wide association studies. However, the wide range of public QTL databases and the lack of batch annotation features complicate a comprehensive annotation of GWAS results. In this work, we introduce the tool “Qtlizer” for annotating lists of variants in human with associated changes in gene expression and protein abundance using an integrated database of published QTLs. Features include incorporation of variants in linkage disequilibrium and reverse search by gene names. Analyzing the database for base pair distances between best significant eQTLs and their affected genes suggests that the commonly used cis-distance limit of 1,000,000 base pairs might be too restrictive, implicating a substantial amount of wrongly and yet undetected eQTLs. We also ranked genes with respect to the maximum number of tissue-specific eQTL studies in which a most significant eQTL signal was consistent. For the top 100 genes we observed the strongest enrichment with housekeeping genes (P = 2 × 10–6) and with the 10% highest expressed genes (P = 0.005) after grouping eQTLs by r2 > 0.95, underlining the relevance of LD information in eQTL analyses. Qtlizer can be accessed via https://genehopper.de/qtlizer or by using the respective Bioconductor R-package (https://doi.org/10.18129/B9.bioc.Qtlizer).

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Structural variants and selective sweep foci contribute to insecticide resistance in the Drosophila melanogaster genetic reference panel

10.1101/301937 ◽

2018 ◽

Cited By ~ 1

Author(s):

Paul Battlay ◽

Llewellyn Green ◽

Pontus B. Leblanc ◽

Joshua M. Schmidt ◽

Alexandre Fournier-Level ◽

...

Keyword(s):

Drosophila Melanogaster ◽

Transposable Element ◽

Selective Sweep ◽

Association Studies ◽

Transcript Abundance ◽

Reference Panel ◽

Drosophila Genome ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Number Variation

AbstractPatterns of nucleotide polymorphism within populations of Drosophila melanogaster suggest that insecticides have been the selective agents driving the strongest recent bouts of positive selection. However, there is a need to explicitly link selective sweep loci to the particular insecticide phenotypes that could plausibly account for the drastic selective responses that are observed in these non-target insects. Here, we screen the Drosophila Genetic Reference Panel with two common insecticides; malathion (an organophosphate) and permethrin (a pyrethroid). Genome wide association studies map ‘survival-on-malathion’ to two of the largest sweeps in the D. melanogaster genome; Ace and Cyp6g1. Malathion survivorship also correlates with lines which have high levels of Cyp12d1 and Jheh1 and Jheh2 transcript abundance. Permethrin phenotypes map to the largest cluster of P450 genes in the Drosophila genome, however in contrast to a selective sweep driven by insecticide use, the derived state seems to be associated with susceptibility. These results underscore previous findings that highlight the importance of structural variation to insecticide phenotypes: Cyp6g1 exhibits copy number variation and transposable element insertions, Cyp12d1 is tandemly duplicated, the Jheh loci are associated with a Bari1 transposable element insertion, and a Cyp6a17 deletion is associated with susceptibility.

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Genome-wide association study identifies novel type II diabetes risk loci in Jordan subpopulations

PeerJ ◽

10.7717/peerj.3618 ◽

2017 ◽

Vol 5 ◽

pp. e3618 ◽

Cited By ~ 4

Author(s):

Rana Dajani ◽

Jin Li ◽

Zhi Wei ◽

Michael E. March ◽

Qianghua Xia ◽

...

Keyword(s):

Type Ii Diabetes ◽

Genome Wide Association Study ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Type Ii ◽

Arab Population ◽

Public Health Burden ◽

Link Type ◽

Genome Wide

The prevalence of Type II Diabetes (T2D) has been increasing and has become a disease of significant public health burden in Jordan. None of the previous genome-wide association studies (GWAS) have specifically investigated the Middle East populations. The Circassian and Chechen communities in Jordan represent unique populations that are genetically distinct from the Arab population and other populations in the Caucasus. Prevalence of T2D is very high in both the Circassian and Chechen communities in Jordan despite low obesity prevalence. We conducted GWAS on T2D in these two populations and further performed meta-analysis of the results. We identified a novel T2D locus at chr20p12.2 at genome-wide significance (rs6134031, P = 1.12 × 10−8) and we replicated the results in the Wellcome Trust Case Control Consortium (WTCCC) dataset. Another locus at chr12q24.31 is associated with T2D at suggestive significance level (top SNP rs4758690, P = 4.20 × 10−5) and it is a robust eQTL for the gene, MLXIP (P = 1.10 × 10−14), and is significantly associated with methylation level in MLXIP, the functions of which involves cellular glucose response. Therefore, in this first GWAS of T2D in Jordan subpopulations, we identified novel and unique susceptibility loci which may help inform the genetic underpinnings of T2D in other populations.

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The power of a multivariate approach to genome-wide association studies: an example with Drosophila melanogaster wing shape

10.1101/108308 ◽

2017 ◽

Author(s):

William Pitchers ◽

Jessica Nye ◽

Eladio J. Márquez ◽

Alycia Kowalski ◽

Ian Dworkin ◽

...

Keyword(s):

Drosophila Melanogaster ◽

Multivariate Analyses ◽

Association Studies ◽

Significant Snps ◽

Wing Shape ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Phenotypic Effect ◽

Genome Wide ◽

Univariate Analyses

AbstractDue to the complexity of genotype-phenotype relationships, simultaneous analyses of genomic associations with multiple traits will be more powerful and more informative than a series of univariate analyses. In most cases, however, studies of genotype-phenotype relationships have analyzed only one trait at a time, even as the rapid advances in molecular tools have expanded our view of the genotype to include whole genomes. Here, we report the results of a fully integrated multivariate genome-wide association analysis of the shape of the Drosophila melanogaster wing in the Drosophila Genetic Reference Panel. Genotypic effects on wing shape were highly correlated between two different labs. We found 2,396 significant SNPs using a 5% FDR cutoff in the multivariate analyses, but just 4 significant SNPs in univariate analyses of scores on the first 20 principal component axes. A key advantage of multivariate analysis is that the direction of the estimated phenotypic effect is much more informative than a univariate one. Exploiting this feature, we show that the directions of effects were on average replicable in an unrelated panel of inbred lines. Effects of knockdowns of genes implicated in the initial screen were on average more similar than expected under a null model. Association studies that take a phenomic approach in considering many traits simultaneously are an important complement to the power of genomics. Multivariate analyses of such data are more powerful, more informative, and allow the unbiased study of pleiotropy.

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pyseer: a comprehensive tool for microbial pangenome-wide association studies

10.1101/266312 ◽

2018 ◽

Cited By ~ 1

Author(s):

John A Lees ◽

Marco Galardini ◽

Stephen D Bentley ◽

Jeffrey N Weiser ◽

Jukka Corander

Keyword(s):

Input Data ◽

Association Studies ◽

Genome Wide Association ◽

Supplementary Information ◽

Genome Wide Association Studies ◽

Supplementary Data ◽

New Methods ◽

Link Type ◽

Genome Wide

AbstractSummaryGenome-wide association studies (GWAS) in microbes face different challenges to eukaryotes and have been addressed by a number of different methods. pyseer brings these techniques together in one package tailored to microbial GWAS, allows greater flexibility of the input data used, and adds new methods to interpret the association results.Availability and Implementationpyseer is written in python and is freely available at https://github.com/mgalardini/pyseer, or can be installed through pip. Documentation and a tutorial are available at http://[email protected] and [email protected] informationSupplementary data are available online.

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Integration of genome-wide association studies and gene coexpression networks unveils promising soybean resistance genes against five common fungal pathogens

Scientific Reports ◽

10.1038/s41598-021-03864-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Fabricio Almeida-Silva ◽

Thiago M. Venancio

Keyword(s):

Candidate Genes ◽

Resistance Genes ◽

Association Studies ◽

Fungal Species ◽

Genome Wide Association ◽

Economic Losses ◽

Genome Wide Association Studies ◽

Link Type ◽

Physical Defense ◽

Genome Wide

AbstractSoybean is one of the most important legume crops worldwide. However, soybean yield is dramatically affected by fungal diseases, leading to economic losses of billions of dollars yearly. Here, we integrated publicly available genome-wide association studies and transcriptomic data to prioritize candidate genes associated with resistance to Cadophora gregata, Fusarium graminearum, Fusarium virguliforme, Macrophomina phaseolina, and Phakopsora pachyrhizi. We identified 188, 56, 11, 8, and 3 high-confidence candidates for resistance to F. virguliforme, F. graminearum, C. gregata, M. phaseolina and P. pachyrhizi, respectively. The prioritized candidate genes are highly conserved in the pangenome of cultivated soybeans and are heavily biased towards fungal species-specific defense responses. The vast majority of the prioritized candidate resistance genes are related to plant immunity processes, such as recognition, signaling, oxidative stress, systemic acquired resistance, and physical defense. Based on the number of resistance alleles, we selected the five most resistant accessions against each fungal species in the soybean USDA germplasm. Interestingly, the most resistant accessions do not reach the maximum theoretical resistance potential. Hence, they can be further improved to increase resistance in breeding programs or through genetic engineering. Finally, the coexpression network generated here is available in a user-friendly web application (https://soyfungigcn.venanciogroup.uenf.br/) and an R/Shiny package (https://github.com/almeidasilvaf/SoyFungiGCN) that serve as a public resource to explore soybean-pathogenic fungi interactions at the transcriptional level.

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Two Synthetic 18-Way Outcrossed Populations of Diploid Budding Yeast with Utility for Complex Trait Dissection

Genetics ◽

10.1534/genetics.120.303202 ◽

2020 ◽

Vol 215 (2) ◽

pp. 323-342 ◽

Cited By ~ 2

Author(s):

Robert A. Linder ◽

Arundhati Majumder ◽

Mahul Chakraborty ◽

Anthony Long

Keyword(s):

Complex Traits ◽

De Novo ◽

Budding Yeast ◽

Association Studies ◽

Haplotype Frequency ◽

Error Rates ◽

Genome Wide Association Studies ◽

Link Type ◽

Standing Variation ◽

Median Error

Advanced-generation multiparent populations (MPPs) are a valuable tool for dissecting complex traits, having more power than genome-wide association studies to detect rare variants and higher resolution than F2 linkage mapping. To extend the advantages of MPPs in budding yeast, we describe the creation and characterization of two outbred MPPs derived from 18 genetically diverse founding strains. We carried out de novo assemblies of the genomes of the 18 founder strains, such that virtually all variation segregating between these strains is known, and represented those assemblies as Santa Cruz Genome Browser tracks. We discovered complex patterns of structural variation segregating among the founders, including a large deletion within the vacuolar ATPase VMA1, several different deletions within the osmosensor MSB2, a series of deletions and insertions at PRM7 and the adjacent BSC1, as well as copy number variation at the dehydrogenase ALD2. Resequenced haploid recombinant clones from the two MPPs have a median unrecombined block size of 66 kb, demonstrating that the population is highly recombined. We pool-sequenced the two MPPs to 3270× and 2226× coverage and demonstrated that we can accurately estimate local haplotype frequencies using pooled data. We further downsampled the pool-sequenced data to ∼20–40× and showed that local haplotype frequency estimates remained accurate, with median error rates 0.8 and 0.6% at 20× and 40×, respectively. Haplotypes frequencies are estimated much more accurately than SNP frequencies obtained directly from the same data. Deep sequencing of the two populations revealed that 10 or more founders are present at a detectable frequency for > 98% of the genome, validating the utility of this resource for the exploration of the role of standing variation in the architecture of complex traits.

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