Interaction of thyroid hormones and gonadotropin inhibitory hormone in the multifactorial control of zebrafish (Danio rerio) spermatogenesis

ABSTRACTReproduction is under multifactorial control of neurohormones, pituitary gonadotropins, as well as a number of gonadal hormones including sex steroids and growth factors. Gonadotropin-inhibitory hormone (Gnih), a novel RFamide neuropeptide, was shown to be involved in the control of pituitary gonadotropin production, as well as being involved as a paracrine factor in the regulation of gonadal function. In this context, recent studies have demonstrated that Gnih inhibited gonadotropin-induced spermatogenesis in the zebrafish testicular explants. Thyroid hormones are known to interact with the reproductive axis, and are, in particular, involved in the regulation of testicular function. Based on this background, we investigated the interaction between Gnih and thyroid hormones in the control of zebrafish spermatogenesis. To this end, zebrafish adult males were treated with the goitrogen methimazole (1mM for 21 days) in order to generate a hypothyroid model organism. Subsequently, a factorial design using an ex vivo testis culture system in combination with histomorphometrical and FACScan cell cycle analyses were adopted. Our results showed that methimazole treatment affected both basal and gonadotropin-induced spermatogenesis, in particular, meiosis and spermiogenesis. Moreover, the goitrogen treatment nullified the inhibitory actions of Gnih on the gonadotropin-induced spermatogenesis, specifically in the haploid cell population. We have demonstrated that thyroid hormones interaction with gonadotropin and Gnih are important components for the regulation of zebrafish spermatogenesis. The results provide a support for the hypothesis that thyroid hormones are important contributors in multifactorial control of spermatogenesis in zebrafish.

Establishment of an eHAP1 Human Haploid Cell Line Hybrid Reference Genome Assembled from Short and Long Reads

BackgroundHaploid cell lines are a valuable research tool with broad applicability for genetic assays. As such the fully haploid human cell line, eHAP1, has been used in a wide array of studies. However, the absence of a corresponding reference genome sequence for this cell line has limited the potential for more widespread applications to experiments dependent on available sequence, like capture-clone methodologies.ResultsWe generated ~15x coverage Nanopore long reads from ten GridION flowcells. We utilized this data to assemble a de novo draft genome using minimap and miniasm and subsequently polished using Racon. This assembly was further polished using previously generated, low-coverage, Illumina short reads with Pilon and ntEdit. This resulted in a hybrid eHAP1 assembly with >90% complete BUSCO scores. We further assessed the eHAP1 long read data for structural variants using Sniffles and identify a variety of rearrangements, including a previously established Philadelphia translocation. Finally, we demonstrate how some of these variants overlap open chromatin regions, potentially impacting regulatory regions.ConclusionsBy integrating both long and short reads, we generated a high-quality reference assembly for eHAP1 cells. We identify structural variants using long reads, including some that may impact putative regulatory elements. The union of long and short reads demonstrates the utility in combining sequencing platforms to generate a high-quality reference genome de novo solely from low coverage data. We expect the resulting eHAP1 genome assembly to provide a useful resource to enable novel experimental applications in this important model cell line.

Modelling Niemann-Pick disease type C in a human haploid cell line allows for patient variant characterization and clinical interpretation

The accurate clinical interpretation of human sequence variation is foundational to personalized medicine. This remains a pressing challenge, however, as genome sequencing becomes routine and new functionally undefined variants rapidly accumulate. Here, we describe a platform for the rapid generation, characterization and interpretation of genomic variants in haploid cells focusing on Niemann-Pick disease type C (NPC) as an example. NPC is a fatal neurodegenerative disorder characterized by a lysosomal accumulation of unesterified cholesterol and glycolipids. In 95% of cases, NPC is caused by mutations in the NPC1 gene, where over 200 unique disease-causing variants have been reported to date. Furthermore, the majority of patients with NPC are compound heterozygotes that often carry at least one private mutation, presenting a challenge for the characterization and classification of individual variants. Here, we have developed the first haploid cell model of NPC. This haploid cell model recapitulates the primary biochemical and molecular phenotypes typically found in patient-derived fibroblasts, illustrating its utility in modelling NPC. Additionally, we demonstrate the power of CRISPR-Cas9-mediated base editing in quickly and efficiently generating haploid cell models of individual patient variants in NPC. These models provide a platform for understanding the disease mechanisms underlying individual NPC1 variants while allowing for definitive clinical variant interpretation for NPC. While this study has focused on modelling NPC, the outlined approach could be translated widely and applied to a variety of genetic disorders or understanding the pathogenicity of somatic mutations in cancer.