Vector Integration Sites Identification for Gene-Trap Screening in Mammalian Haploid Cells

Mammalian haploid stem cells: establishment, engineering and applications

Haploid embryonic stem cells (haESCs) contain only one set of genomes inherited from the sperm or egg and are termed AG- or PG-haESCs, respectively. Mammalian haESCs show genome-wide hypomethylation and dysregulated imprinting, whereas they can sustain genome integrity during derivation and long-term propagation. In addition, haESCs exhibit similar pluripotency to traditional diploid ESCs but are unique because they function as gametes and have been used to produce semi-cloned animals. More strikingly, unisexual reproduction has been achieved in mice by using haESCs. In combination with a gene editing or screening system, haESCs represent a powerful tool for studies of underlying gene functions and explorations of mechanisms of genetic and epigenetic regulation not only at the cellular level in vitro but also at the animal level in vivo. More importantly, genetically edited AG-haESC lines may further serve as an ideal candidate for the establishment of a sperm bank, which is a highly cost-effective approach, and a wide range of engineered semi-cloned mice have been produced. Here, we review the historical development, characteristics, advantages and disadvantages of haESCs. Additionally, we present an in-depth discussion of the recent advances in haESCs and their potential applications.

Genetic screening and multipotency in rhesus monkey haploid neural progenitor cells

Haploid embryonic stem cells (haESCs) have been extensively applied in forward and reverse genetic screening. However, a mammalian haploid somatic cell line is difficult to achieve because of spontaneous diploidization in differentiation. As a non-human primate species, monkeys are widely used in basic and pre-clinical research in which haploid cells are restricted to ESCs. Here, we report that rhesus monkey haESCs in an optimized culture medium show naïve-state pluripotency and stable haploidy. This model facilitated the derivation of haploid neural progenitor cells (haNPCs), which maintained haploidy and differentiation potential into neurons and glia for a long period in vitro High-throughput trapping mutations can be efficiently introduced into haNPCs via piggyBac transposons. This system proves useful when identifying gene targets of neural toxicants via a proof-of-concept experiment. Using CRISPR/Cas9 editing, we confirmed that B4GALT6, from the candidate gene list, is a resistance gene of A803467 (a tetrodotoxin-like toxicant). This model is the first non-human primate haploid somatic cell line with proliferative ability, multipotency and an intact genome, thus providing a cellular resource for recessive genetic and potential drug screening.

HaSAPPy: A tool for candidate identification in pooled forward genetic screens of haploid mammalian cells

Haploid cells are increasingly used for screening of complex pathways in animal genomes. Hemizygous mutations introduced through viral insertional mutagenesis can be directly selected for phenotypic changes. Here we present HaSAPPy a tool for analysing sequencing datasets of screens using insertional mutations in large pools of haploid cells. Candidate gene prediction is implemented through identification of enrichment of insertional mutations after selection by simultaneously evaluating several parameters. We have developed HaSAPPy for analysis of genetic screens for silencing factors of X chromosome inactivation in haploid mouse embryonic stem cells. To benchmark the performance, we further analyse several datasets of genetic screens in human haploid cells for which candidates have been validated. Our results support the effective candidate prediction strategy of HaSAPPy. HaSAPPy is implemented in Python, licensed under the MIT license, and is available from https://github.com/gdiminin/HaSAPPy.

New tools for old drugs: Functional genetic screens to optimize current chemotherapy

Despite substantial advances in the treatment of various cancers, many patients still receive anti-cancer therapies that hardly eradicate tumor cells but inflict considerable side effects. To provide the best treatment regimen for an individual patient, a major goal in molecular oncology is to identify predictive markers for a personalized therapeutic strategy. Regarding novel targeted anti-cancer therapies, there are usually good markers available. Unfortunately, however, targeted therapies alone often result in rather short remissions and little cytotoxic effect on the cancer cells. Therefore, classical chemotherapy with frequent long remissions, cures, and a clear effect on cancer cell eradication remains a corner stone in current anti-cancer therapy. Reliable biomarkers which predict the response of tumors to classical chemotherapy are rare, in contrast to the situation for targeted therapy. For the bulk of cytotoxic therapeutic agents, including DNA-damaging drugs, drugs targeting microtubules or antimetabolites, there are still no reliable biomarkers used in the clinic to predict tumor response. To make progress in this direction, meticulous studies of classical chemotherapeutic drug action and resistance mechanisms are required. For this purpose, novel functional screening technologies have emerged as successful technologies to study chemotherapeutic drug response in a variety of models. They allow a systematic analysis of genetic contributions to a drug-responsive or −sensitive phenotype and facilitate a better understanding of the mode of action of these drugs. These functional genomic approaches are not only useful for the development of novel targeted anti-cancer drugs but may also guide the use of classical chemotherapeutic drugs by deciphering novel mechanisms influencing a tumor’s drug response. Moreover, due to the advances of 3D organoid cultures from patient tumors and in vivo screens in mice, these genetic screens can be applied using conditions that are more representative of the clinical setting. Patient-derived 3D organoid lines furthermore allow the characterization of the “essentialome”, the specific set of genes required for survival of these cells, of an individual tumor, which could be monitored over the course of treatment and help understanding how drug resistance evolves in clinical tumors. Thus, we expect that these functional screens will enable the discovery of novel cancer-specific vulnerabilities, and through clinical validation, move the field of predictive biomarkers forward. This review focuses on novel advanced techniques to decipher the interplay between genetic alterations and drug response.