Propagation of seminal toxins through binary expression gene drives can suppress polyandrous populations

Gene drives can be highly effective in controlling a target population by disrupting a female fertility gene. To spread across a population, these drives require that disrupted alleles be largely recessive so as not to impose too high of a fitness penalty. We argue that this restriction may be relaxed by using a double gene drive design to spread a split binary expression system. One drive carries a dominant lethal/toxic effector alone and the other a transactivator factor, without which the effector will not act. Only after the drives reach sufficiently high frequencies would individuals have the chance to inherit both system components and the effector be expressed. We explore through mathematical modeling the potential of this design to spread dominant lethal/toxic alleles and suppress populations. We show that this system could be implemented to spread engineered seminal proteins designed to kill females, making it highly effective against polyandrous populations.

Modeling homing suppression gene drive in haplodiploid organisms

Gene drives have shown great promise for suppression of pest populations. These engineered alleles can function by a variety of mechanisms, but the most common is the CRISPR homing drive, which converts wild-type alleles to drive alleles in the germline of heterozygotes. Some potential target species are haplodiploid, in which males develop from unfertilized eggs and thus have only one copy of each chromosome. This prevents drive conversion, a substantial disadvantage compared to diploids where drive conversion can take place in both sexes. Here, we study the characteristics of homing suppression gene drives in haplodiploids and find that a drive targeting a female fertility gene could still be successful. However, such drives are less powerful than in diploids. They are substantially more vulnerable to high resistance allele formation in the embryo due to maternally deposited Cas9 and gRNA and also to somatic cleavage activity. Examining models of continuous space where organisms move over a landscape, we find that haplodiploid suppression drives surprisingly perform nearly as well as in diploids, possibly due to their ability to spread further before inducing strong suppression. Together, these results indicate that gene drive can potentially be used to effectively suppress haplodiploid populations.

The Male Fertility Gene Atlas: a web tool for collecting and integrating OMICS data in the context of male infertility

STUDY QUESTION How can one design and implement a system that provides a comprehensive overview of research results in the field of epi-/genetics of male infertility and germ cells? SUMMARY ANSWER Working at the interface of literature search engines and raw data repositories, the newly developed Male Fertility Gene Atlas (MFGA) provides a system that can represent aggregated results from scientific publications in a standardized way and perform advanced searches, for example based on the conditions (phenotypes) and genes related to male infertility. WHAT IS KNOWN ALREADY PubMed and Google Scholar are established search engines for research literature. Additionally, repositories like Gene Expression Omnibus and Sequence Read Archive provide access to raw data. Selected processed data can be accessed by visualization tools like the ReproGenomics Viewer. STUDY DESIGN, SIZE, DURATION The MFGA was developed in a time frame of 18 months under a rapid prototyping approach. PARTICIPANTS/MATERIALS, SETTING, METHODS In the context of the Clinical Research Unit ‘Male Germ Cells’ (CRU326), a group of around 50 domain experts in the fields of male infertility and germ cells helped to develop the requirements engineering and feedback loops. They provided a set of 39 representative and heterogeneous publications to establish a basis for the system requirements. MAIN RESULTS AND THE ROLE OF CHANCE The MFGA is freely available online at https://mfga.uni-muenster.de. To date, it contains 115 data sets corresponding to 54 manually curated publications and provides an advanced search function based on study conditions, meta-information and genes, whereby it returns the publications’ exact tables and figures that fit the search request as well as a list of the most frequently investigated genes in the result set. Currently, study data for 31 different tissue types, 32 different cell types and 20 conditions are available. Also, ∼8000 and ∼1000 distinct genes have been found to be mentioned in at least 10 and 15 of the publications, respectively. LARGE SCALE DATA Not applicable because no novel data were produced. LIMITATIONS, REASONS FOR CAUTION For the most part, the content of the system currently includes the selected publications from the development process. However, a structured process for the prospective literature search and inclusion into the MFGA has been defined and is currently implemented. WIDER IMPLICATIONS OF THE FINDINGS The technical implementation of the MFGA allows for accommodating a wide range of heterogeneous data from aggregated research results. This implementation can be transferred to other diseases to establish comparable systems and generally support research in the medical field. STUDY FUNDING/COMPETING INTEREST(S) This work was carried out within the frame of the German Research Foundation (DFG) Clinical Research Unit ‘Male Germ Cells: from Genes to Function’ (CRU326). The authors declare no conflicts of interest.

The Male Fertility Gene Atlas – A web tool for collecting and integrating data about epi-/genetic causes of male infertility

Interconnecting results of previous OMICs studies is of major importance for identifying novel underlying causes of male infertility. To date, information can be accessed mainly through literature search engines and raw data repositories. However, both have limited capacity in identifying relevant publications based on aggregated research results e.g. genes mentioned in images and supplements. To address this gap, we present the Male Fertility Gene Atlas (MFGA), a web tool that enables standardised representation and search of aggregated result data of scientific publications. An advanced search function is provided for querying research results based on study conditions/phenotypes, meta information and genes returning the exact tables and figures from the publications fitting the search request as well as a list of most frequently investigated genes. As basic prerequisite, a flexible data model that can accommodate and structure a very broad range of meta information, data tables and images was designed and implemented for the system. The first version of the system is published at the URL https://mfga.uni-muenster.de and contains a set of 46 representative publications. Currently, study data for 28 different tissue types, 32 different cell types and 20 conditions is available. Also, ∼5,000 distinct genes have been found to be mentioned in at least ten of the publications. As a result, the MFGA is a valuable addition to available tools for research on the epi-/genetics of male infertility. The MFGA enables a more targeted search and interpretation of OMICs data on male infertility and germ cells in the context of relevant publications. Moreover, its capacity for aggregation allows for meta-analyses and data mining with the potential to reveal novel insights into male infertility based on available data.

How did a duplicated gene copy evolve into a restorer-of-fertility gene in a plant? The case of Oma1

Restorer-of-fertility ( Rf ) is a suppressor of cytoplasmic male sterility (CMS), a mitochondrion-encoded trait that has been reported in many plant species. The occurrence of CMS is considered to be independent in each lineage; hence, the question of how Rf evolved was raised. Sugar beet Rf resembles Oma1 , a gene for quality control of the mitochondrial inner membrane. Oma1 homologues comprise a small gene family in the sugar beet genome, unlike Arabidopsis and other eukaryotes. The sugar beet sequence that best matched Arabidopsis atOma1 was named bvOma1 ; sugar beet Rf ( RF1-Oma1 ) was another member. During anther development, atOma1 mRNA was detected from the tetrad to the microspore stages, whereas bvOma1 mRNA was detected at the microspore stage and RF1-Oma1 mRNA was detected during the meiosis and tetrad stages. A transgenic study revealed that, whereas RF1-Oma1 can bind to a CMS-specific protein and alter the higher-order structure of the CMS-specific protein complex, neither bvOma1 nor atOma1 show such activity. We favour the hypothesis that an ancestral Oma1 gene duplicated to form a small gene family, and that one of the copies evolved and acquired a novel expression pattern and protein function as an Rf , i.e. RF1-Oma1 evolved via neofunctionalization.

Gene drive for population genetic control: non-functional resistance and parental effects

Gene drive is a natural process of biased inheritance that, in principle, could be used to control pest and vector populations. As with any form of pest control, attention should be paid to the possibility of resistance evolving. For nuclease-based gene drive aimed at suppressing a population, resistance could arise by changes in the target sequence that maintain function, and various strategies have been proposed to reduce the likelihood that such alleles arise. Even if these strategies are successful, it is almost inevitable that alleles will arise at the target site that are resistant to the drive but do not restore function, and the impact of such sequences on the dynamics of control has been little studied. We use population genetic modelling of a strategy targeting a female fertility gene to demonstrate that such alleles may be expected to accumulate, and thereby reduce the reproductive load on the population, if nuclease expression per se causes substantial heterozygote fitness effects or if parental (especially paternal) deposition of nuclease either reduces offspring fitness or affects the genotype of their germline. All these phenomena have been observed in synthetic drive constructs. It will, therefore, be important to allow for non-functional resistance alleles in predicting the dynamics of constructs in cage populations and the impacts of any field release.