Single-cell RNA sequencing in Drosophila: Technologies and applications

Single-cell transcriptomes provide insights into expansion of glial cells in Bombyx mori

The diversity of cell types in the brain and how these change during different developmental stages, remains largely unknown. The life cycle of insects is short and goes through 4 distinct stages including embryonic, larval, pupal, and adult stages. During postembryonic life, the larval brain transforms into a mature adult version after metamorphosis. The silkworm, Bombyx mori, is a lepidopteran model insect. Here, we characterized the brain cell repertoire of larval and adult B. mori by obtaining 50 708 single-cell transcriptomes. Seventeen and 12 cell clusters from larval and adult brains were assigned based on marker genes, respectively. Identified cell types include Kenyon cells, optic lobe cells, monoaminergic neurons, surface glia, and astrocyte glia. We further assessed the cell type compositions of larval and adult brains. We found that the transition from larva to adult resulted in great expansion of glial cells. The glial cell accounted for 49.8% of adult midbrain cells. Compared to flies and ants, the mushroom body kenyon cell is insufficient in B. mori, which accounts for 5.4% and 3.6% in larval and adult brains, respectively. Analysis of neuropeptide expression showed that the abundance and specificity of expression varied among individual neuropeptides. Intriguingly, we found that ion transport peptide was specifically expressed in glial cells of larval and adult brains. The cell atlas dataset provides an important resource to explore cell diversity, neural circuits and genetic profiles.

Fly Me to the Micron: Microtechnologies for Drosophila Research

Multicellular model organisms, such as Drosophila melanogaster (fruit fly), are frequently used in a myriad of biological research studies due to their biological significance and global standardization. However, traditional tools used in these studies generally require manual handling, subjective phenotyping, and bulk treatment of the organisms, resulting in laborious experimental protocols with limited accuracy. Advancements in microtechnology over the course of the last two decades have allowed researchers to develop automated, high-throughput, and multifunctional experimental tools that enable novel experimental paradigms that would not be possible otherwise. We discuss recent advances in microtechnological systems developed for small model organisms using D. melanogaster as an example. We critically analyze the state of the field by comparing the systems produced for different applications. Additionally, we suggest design guidelines, operational tips, and new research directions based on the technical and knowledge gaps in the literature. This review aims to foster interdisciplinary work by helping engineers to familiarize themselves with model organisms while presenting the most recent advances in microengineering strategies to biologists.

Single-cell transcriptomics dissecting the development and evolution of nervous system in insects

Insects can display a vast repertoire of complex and adaptive behaviors crucial for survival and reproduction. Yet, how the neural circuits underlying insect behaviors are assembled throughout development and remodeled during evolution remains largely obscure. The advent of single-cell transcriptomics has opened new paths to illuminate these historically intractable questions. Insect behavior is governed by its brain, whose functional complexity is realized through operations across multiple levels, from the molecular and cellular to the circuit and organ. Single-cell transcriptomics enables dissecting brain functions across all these levels and allows tracking regulatory dynamics throughout development and under perturbation. In this review, we mainly focus on the achievements of single-cell transcriptomics in dissecting the molecular and cellular architectures of nervous systems in representative insects, then discuss its applications in tracking the developmental trajectory and functional evolution of insect brains.

Deciphering the cellular heterogeneity of the insect brain with single-cell RNA sequencing

Insects show highly complicated adaptive and sophisticated behaviors, including spatial orientation skills, learning ability, and social interaction. These behaviors are controlled by the insect brain, the central part of the nervous system. The tiny insect brain consists of millions of highly differentiated and interconnected cells forming a complex network. Decades of research has gone into an understanding of which parts of the insect brain possess particular behaviors, but exactly how they modulate these functional consequences needs to be clarified. Detailed description of the brain and behavior is required to decipher the complexity of cell types, as well as their connectivity and function. Single-cell RNA-sequencing (scRNA-seq) has emerged recently as a breakthrough technology to understand the transcriptome at cellular resolution. With scRNA-seq, it is possible to uncover the cellular heterogeneity of brain cells and elucidate their specific functions and state. In this review, we first review the basic structure of insect brains and the links to insect behaviors mainly focusing on learning and memory. Then the scRNA applications on insect brains are introduced by representative studies. Single-cell RNA-seq has allowed researchers to classify cell subpopulations within different insect brain regions, pinpoint single-cell developmental trajectories, and identify gene regulatory networks. These developments empower the advances in neuroscience and shed light on the intricate problems in understanding insect brain functions and behaviors.

Single-cell RNA sequencing of mid-to-late stage spider embryos: new insights into spider development

BACKGROUND

The common house spider Parasteatoda tepidariorum represents an emerging new model organism of arthropod evolutionary and developmental (EvoDevo) studies. Recent technical advances have resulted in the first single-cell sequencing (SCS) data on this species allowing deeper insights to be gained into its early development, but mid-to-late stage embryos were not included in these pioneering studies.

RESULTS

Therefore, we performed SCS on mid-to-late stage embryos of Parasteatoda and characterized resulting cell clusters by means of in-silico analysis (comparison of key markers of each cluster with previously published information on these genes). In-silico prediction of the nature of each cluster was then tested/verified by means of additional in-situ hybridization experiments with additional markers of each cluster.

CONCLUSIONS

Our data show that SCS data reliably group cells with similar genetic fingerprints into more or less distinct clusters, and thus allows identification of developing cell types on a broader level, such as the distinction of ectodermal, mesodermal and endodermal cell lineages, as well as the identification of distinct developing tissues such as subtypes of nervous tissue cells, the developing heart, or the ventral sulcus (VS). In comparison with recent other SCS studies on the same species, our data represent later developmental stages, and thus provide insights into different stages of developing cell types and tissues such as differentiating neurons and the VS that are only present at these later stages.

The effects of methylphenidate and atomoxetine on Drosophila brain at single-cell resolution and potential drug repurposing for ADHD treatment

The stimulant methylphenidate (MPH) and the non-stimulant atomoxetine (ATX) are frequently used for the treatment of attention-deficit/hyperactivity disorder (ADHD); however, the function of these drugs in different types of brain cells and their effects on related genes remain largely unknown. To address these questions, we built a pipeline for the simultaneous examination of the activity behavior and transcriptional responses of Drosophila melanogaster at single-cell resolution following drug treatment. We selected the Drosophila with significantly increased locomotor activities (hyperactivity-like behavior) following the administration of each drug in comparison with the control (same food as the drug-treated groups with 5% sucrose, yeast, and blue food dye solution) using EasyFlyTracker. Subsequently, single cell RNA sequencing (scRNASEQ) was used to capture the transcriptome of 82,917 cells, unsupervised clustering analysis of which yielded 28 primary cell clusters representing the major cell types in adult Drosophila brain. Indeed, both neuronal and glial cells responded to MPH and ATX. Further analysis of differentially expressed genes (DEGs) revealed distinct transcriptional changes associated with these two drugs, such as two well-studied dopamine receptor genes (Dop2R and DopEcR) were responsive to MPH but not to ATX at their optimal doses, in addition to genes involved in dopamine metabolism pathways such as Syt1, Sytalpha, Syt7, and Ih in different cell types. More importantly, MPH also suppressed the expression of genes encoding other neurotransmitter receptors and synaptic signaling molecules in many cell types, especially those for Glu and GABA, while the responsive effects of ATX were much weaker. In addition to monoaminergic neuronal transmitters, other neurotransmitters have also shown a similar pattern with respect to a stronger effect associated with MPH than with ATX. Moreover, we identified four distinct glial cell subtypes responsive to the two drugs and detected a greater number of differentially expressed genes associated with ensheathing and astrocyte-like glia. Furthermore, our study provides a rich resource of candidate target genes, supported by drug set enrichment analysis (P = 2.10E-4; hypergeometric test), for the further exploration of drug repurposing. The whole list of candidates can be found at ADHDrug ( http://adhdrug.cibr.ac.cn/ ). In conclusion, we propose a fast and cost-efficient pipeline to explore the underlying molecular mechanisms of ADHD drug treatment in Drosophila brain at single-cell resolution, which may further facilitate drug repurposing applications.

Insect Insights at the Single-Cell Level: Technologies and Applications

Single-cell techniques are a promising way to unravel the complexity and heterogeneity of transcripts at the cellular level and to reveal the composition of different cell types and functions in a tissue or organ. In recent years, advances in single-cell RNA sequencing (scRNA-seq) have further changed our view of biological systems. The application of scRNA-seq in insects enables the comprehensive characterization of both common and rare cell types and cell states, the discovery of new cell types, and revealing how cell types relate to each other. The recent application of scRNA-seq techniques to insect tissues has led to a number of exciting discoveries. Here we provide an overview of scRNA-seq and its application in insect research, focusing on biological applications, current challenges, and future opportunities to make new discoveries with scRNA-seq in insects.

Affordable, accurate and unbiased RNA sequencing by manual library miniaturization: A case study in barley

We present an easy-to-reproduce manual miniaturized full-length RNA sequencing (RNAseq) library preparation workflow that does not require the upfront investment in expensive lab equipment or long setup times. With minimal adjustments to an established commercial protocol, we were able to manually miniaturize the RNAseq library preparation by a factor of up to 1:8. This led to cost savings for miniaturized library preparation of up to 86.1% compared to the gold standard. The resulting data were the basis of a rigorous quality control analysis that inspected: sequencing quality metrics, gene body coverage, raw read duplications, alignment statistics, read pair duplications, detected transcripts and sequence variants. We also included a deep dive data analysis identifying rRNA contamination and suggested ways to circumvent these. In the end, we could not find any indication of biases or inaccuracies caused by the RNAseq library miniaturization. The variance in detected transcripts was minimal and not influenced by the miniaturization level. Our results suggest that the workflow is highly reproducible and the sequence data suitable for downstream analyses such as differential gene expression analysis or variant calling.

Liver in infections: a single-cell and spatial transcriptomics perspective

The liver is an immune organ that plays a vital role in the detection, capture, and clearance of pathogens and foreign antigens that invade the human body. During acute and chronic infections, the liver transforms from a tolerant to an active immune state. The defence mechanism of the liver mainly depends on a complicated network of intrahepatic and translocated immune cells and non-immune cells. Therefore, a comprehensive liver cell atlas in both healthy and diseased states is needed for new therapeutic target development and disease intervention improvement. With the development of high-throughput single-cell technology, we can now decipher heterogeneity, differentiation, and intercellular communication at the single-cell level in sophisticated organs and complicated diseases. In this concise review, we aimed to summarise the advancement of emerging high-throughput single-cell technologies and re-define our understanding of liver function towards infections, including hepatitis B virus, hepatitis C virus, Plasmodium, schistosomiasis, endotoxemia, and corona virus disease 2019 (COVID-19). We also unravel previously unknown pathogenic pathways and disease mechanisms for the development of new therapeutic targets. As high-throughput single-cell technologies mature, their integration into spatial transcriptomics, multiomics, and clinical data analysis will aid in patient stratification and in developing effective treatment plans for patients with or without liver injury due to infectious diseases.

Next-generation large-scale binary protein interaction network for Drosophila melanogaster

Generating reference maps of interactome networks illuminates genetic studies by providing a protein-centric approach to finding new components of existing pathways, complexes, and processes. We apply state-of-the-art methods to identify binary protein-protein interactions (PPIs) for Drosophila melanogaster. Four all-by-all yeast two-hybrid (Y2H) screens of > 10,000 Drosophila proteins result in the 'FlyBi' dataset of 8723 PPIs among 2939 proteins. Testing subsets of data from FlyBi and previous PPI studies using an orthogonal assay allows for normalization of data quality; subsequent integration of FlyBi and previous data results in an expanded binary Drosophila reference interaction network, DroRI, comprising 17,232 interactions among 6511 proteins. We use FlyBi data to generate an autophagy network, then validate in vivo using autophagy-related assays. The deformed wings (dwg) gene encodes a protein that is both a regulator and a target of autophagy. Altogether, these resources provide a foundation for building new hypotheses regarding protein networks and function.

Single-cell RNA sequencing reveals cell landscape following antimony exposure during spermatogenesis in Drosophila testes

Antimony (Sb), is thought to induce testicular toxicity, although this remains controversial. This study investigated the effects of Sb exposure during spermatogenesis in the Drosophila testis and the underlying transcriptional regulatory mechanism at single-cell resolution. Firstly, we found that flies exposed to Sb for 10 days led to dose-dependent reproductive toxicity during spermatogenesis. Protein expression and RNA levels were measured by immunofluorescence and quantitative real-time PCR (qRT-PCR). Single-cell RNA sequencing (scRNA-seq) was performed to characterize testicular cell composition and identify the transcriptional regulatory network after Sb exposure in Drosophila testes. scRNA-seq analysis revealed that Sb exposure influenced various testicular cell populations, especially in GSCs_to_Early_Spermatogonia and Spermatids clusters. Importantly, carbon metabolism was involved in GSCs/early spermatogonia maintenance and positively related with SCP-Containing Proteins, S-LAPs, and Mst84D signatures. Moreover, Seminal Fluid Proteins, Mst57D, and Serpin signatures were highly positively correlated with spermatid maturation. Pseudotime trajectory analysis revealed three novel states for the complexity of germ cell differentiation, and many novel genes (e.g., Dup98B) were found to be expressed in state-biased manners during spermatogenesis. Collectively, this study indicates that Sb exposure negatively impacts GSC maintenance and spermatid elongation, damaging spermatogenesis homeostasis via multiple signatures in Drosophila testes and therefore supporting Sb-mediated testicular toxicity.

Neural connectivity molecules best identify the heterogeneous clock and dopaminergic cell types in the Drosophila adult brain

Our recent single-cell sequencing of most adult Drosophila circadian neurons indicated notable and unexpected heterogeneity. To address whether other populations are similar, we sequenced a large subset of adult brain dopaminergic neurons. Their gene expression heterogeneity is similar to that of clock neurons, i.e., both populations have two to three cells per neuron group. There was also unexpected cell-specific expression of neuron communication molecule messenger RNAs: G protein-coupled receptor or cell surface molecule (CSM) transcripts alone can define adult brain dopaminergic and circadian neuron cell type. Moreover, the adult expression of the CSM DIP-beta in a small group of clock neurons is important for sleep. We suggest that the common features of circadian and dopaminergic neurons are general, essential for neuronal identity and connectivity of the adult brain, and that these features underlie the complex behavioral repertoire of Drosophila.

Drosophila melanogaster as a versatile model organism to study genetic epilepsies: An overview

Epilepsy is one of the most prevalent neurological disorders, affecting more than 45 million people worldwide. Recent advances in genetic techniques, such as next-generation sequencing, have driven genetic discovery and increased our understanding of the molecular and cellular mechanisms behind many epilepsy syndromes. These insights prompt the development of personalized therapies tailored to the genetic characteristics of an individual patient. However, the surging number of novel genetic variants renders the interpretation of pathogenetic consequences and of potential therapeutic implications ever more challenging. Model organisms can help explore these aspects in vivo. In the last decades, rodent models have significantly contributed to our understanding of genetic epilepsies but their establishment is laborious, expensive, and time-consuming. Additional model organisms to investigate disease variants on a large scale would be desirable. The fruit fly Drosophila melanogaster has been used as a model organism in epilepsy research since the discovery of "bang-sensitive" mutants more than half a century ago. These flies respond to mechanical stimulation, such as a brief vortex, with stereotypic seizures and paralysis. Furthermore, the identification of seizure-suppressor mutations allows to pinpoint novel therapeutic targets. Gene editing techniques, such as CRISPR/Cas9, are a convenient way to generate flies carrying disease-associated variants. These flies can be screened for phenotypic and behavioral abnormalities, shifting of seizure thresholds, and response to anti-seizure medications and other substances. Moreover, modification of neuronal activity and seizure induction can be achieved using optogenetic tools. In combination with calcium and fluorescent imaging, functional alterations caused by mutations in epilepsy genes can be traced. Here, we review Drosophila as a versatile model organism to study genetic epilepsies, especially as 81% of human epilepsy genes have an orthologous gene in Drosophila. Furthermore, we discuss newly established analysis techniques that might be used to further unravel the pathophysiological aspects of genetic epilepsies.

Mathematical model and genomics construction of developmental biology patterns using digital image technology

Biological pattern formation ensures that tissues and organs develop in the correct place and orientation within the body. A great deal has been learned about cell and tissue staining techniques, and today’s microscopes can capture digital images. A light microscope is an essential tool in biology and medicine. Analyzing the generated images will involve the creation of unique analytical techniques. Digital images of the material before and after deformation can be compared to assess how much strain and displacement the material responds. Furthermore, this article proposes Development Biology Patterns using Digital Image Technology (DBP-DIT) to cell image data in 2D, 3D, and time sequences. Engineered materials with high stiffness may now be characterized via digital image correlation. The proposed method of analyzing the mechanical characteristics of skin under various situations, such as one direction of stress and temperatures in the hundreds of degrees Celsius, is achievable using digital image correlation. A DBP-DIT approach to biological tissue modeling is based on digital image correlation (DIC) measurements to forecast the displacement field under unknown loading scenarios without presupposing a particular constitutive model form or owning knowledge of the material microstructure. A data-driven approach to modeling biological materials can be more successful than classical constitutive modeling if adequate data coverage and advice from partial physics constraints are available. The proposed procedures include a wide range of biological objectives, experimental designs, and laboratory preferences. The experimental results show that the proposed DBP-DIT achieves a high accuracy ratio of 99,3%, a sensitivity ratio of 98.7%, a specificity ratio of 98.6%, a probability index of 97.8%, a balanced classification ratio of 97.5%, and a low error rate of 38.6%.

Isolation and RNA sequencing of single nuclei from Drosophila tissues

Many insect cells are encapsulated within the exoskeleton and cannot be dissociated intact, making them inaccessible to single-cell transcriptomic profiling. We have used single-nucleus RNA sequencing to extract transcriptomic information from multiple Drosophila tissues. Here, we describe procedures for the (1) dissociation of single nuclei, (2) isolation of single nuclei using two popular cell sorters, and (3) preparation of libraries for Smart-seq2 and 10× Genomics. This protocol enables generation of high-quality transcriptomes from single nuclei and can be applied to other species. For complete details on the use and execution of this protocol, please refer to McLaughlin et al. (2021) and Li et al. (2022).

Systematic expression profiling of Dpr and DIP genes reveals cell surface codes in Drosophila larval motor and sensory neurons

In complex nervous systems, neurons must identify their correct partners to form synaptic connections. The prevailing model to ensure correct recognition posits that cell-surface proteins (CSPs) in individual neurons act as identification tags. Thus, knowing what cells express which CSPs would provide insights into neural development, synaptic connectivity, and nervous system evolution. Here, we investigated expression of Dpr and DIP genes, two CSP subfamilies belonging to the immunoglobulin superfamily, in Drosophila larval motor neurons (MNs), muscles, glia and sensory neurons (SNs) using a collection of GAL4 driver lines. We found that Dpr genes are more broadly expressed than DIP genes in MNs and SNs, and each examined neuron expresses a unique combination of Dpr and DIP genes. Interestingly, many Dpr and DIP genes are not robustly expressed, but are found instead in gradient and temporal expression patterns. In addition, the unique expression patterns of Dpr and DIP genes revealed three uncharacterized MNs. This study sets the stage for exploring the functions of Dpr and DIP genes in Drosophila MNs and SNs and provides genetic access to subsets of neurons.

Single-Cell Profiling of Tumor Microenvironment Heterogeneity in Osteosarcoma Identifies a Highly Invasive Subcluster for Predicting Prognosis

Osteosarcoma is the most common malignant bone tumor in adolescents, and metastasis is the key reason for treatment failure and poor prognosis. Once metastasis occurs, the 5-year survival rate is only approximately 20%, and assessing and predicting the risk of osteosarcoma metastasis are still difficult tasks. In this study, cellular communication between tumor cells and nontumor cells was identified through comprehensive analysis of osteosarcoma single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data, illustrating the complex regulatory network in the osteosarcoma microenvironment. In line with the heterogeneity of osteosarcoma, we found subpopulations of osteosarcoma cells that highly expressed COL6A1, COL6A3 and MIF and were closely associated with lung metastasis. Then, BCDEG, a reliable risk regression model that could accurately assess the metastasis risk and prognosis of patients, was established, providing a new strategy for the diagnosis and treatment of osteosarcoma.

Cross-tissue and generation predictability of relative Wolbachia densities in the mosquito Aedes aegypti

BACKGROUND

The insect endosymbiotic bacterium Wolbachia is being deployed in field populations of the mosquito Aedes aegypti for biological control. This microbe prevents the replication of human disease-causing viruses inside the vector, including dengue, Zika and chikungunya. Relative Wolbachia densities may in part predict the strength of this 'viral blocking' effect. Additionally, Wolbachia densities may affect the strength of the reproductive manipulations it induces, including cytoplasmic incompatibility (CI), maternal inheritance rates or induced fitness effects in the insect host. High rates of CI and maternal inheritance and low rates of fitness effects are also key to the successful spreading of Wolbachia through vector populations and its successful use in biocontrol. The factors that control Wolbachia densities are not completely understood.

METHODS

We used quantitative PCR-based methods to estimate relative density of the Wolbachia wAlbB strain in both the somatic and reproductive tissues of adult male and female mosquitoes, as well as in eggs. Using correlation analyses, we assessed whether densities in one tissue predict those in others within the same individual, but also across generations.

RESULTS

We found little relationship among the relative Wolbachia densities of different tissues in the same host. The results also show that there was very little relationship between Wolbachia densities in parents and those in offspring, both in the same and different tissues. The one exception was with ovary-egg relationships, where there was a strong positive association. Relative Wolbachia densities in reproductive tissues were always greater than those in the somatic tissues. Additionally, the densities were consistent in females over their lifetime regardless of tissue, whereas they were generally higher and more variable in males, particularly in the testes.

CONCLUSIONS

Our results indicate that either stochastic processes or local tissue-based physiologies are more likely factors dictating Wolbachia densities in Ae. aegypti individuals, rather than shared embryonic environments or heritable genetic effects of the mosquito genome. These findings have implications for understanding how relative Wolbachia densities may evolve and/or be maintained over the long term in Ae. aegypti.

Fly Cell Atlas: A single-nucleus transcriptomic atlas of the adult fruit fly

For more than 100 years, the fruit fly Drosophila melanogaster has been one of the most studied model organisms. Here, we present a single-cell atlas of the adult fly, Tabula Drosophilae, that includes 580,000 nuclei from 15 individually dissected sexed tissues as well as the entire head and body, annotated to >250 distinct cell types. We provide an in-depth analysis of cell type-related gene signatures and transcription factor markers, as well as sexual dimorphism, across the whole animal. Analysis of common cell types between tissues, such as blood and muscle cells, reveals rare cell types and tissue-specific subtypes. This atlas provides a valuable resource for the Drosophila community and serves as a reference to study genetic perturbations and disease models at single-cell resolution.

Micromanagement of Drosophila Post-Embryonic Development by Hox Genes

Hox genes function early in development to determine regional identity in animals. Consequently, the loss or gain of Hox gene expression can change this identity and cause homeotic transformations. Over 20 years ago, it was observed that the role of Hox genes in patterning animal body plans involves the fine-scale regulation of cell fate and identity during development, playing the role of 'micromanagers' as proposed by Michael Akam in key perspective papers. Therefore, as well as specifying where structures develop on animal bodies, Hox genes can help to precisely sculpt their morphology. Here, we review work that has provided important insights about the roles of Hox genes in influencing cell fate during post-embryonic development in Drosophila to regulate fine-scale patterning and morphology. We also explore how this is achieved through the regulation of Hox genes, specific co-factors and their complex regulation of hundreds of target genes. We argue that further investigating the regulation and roles of Hox genes in Drosophila post-embryonic development has great potential for understanding gene regulation, cell fate and phenotypic differentiation more generally.

Analysis of Single-Cell Transcriptome Data in Drosophila

The fly Drosophila is a versatile model organism that has led to fascinating biological discoveries. In the past few years, Drosophila researchers have used single-cell RNA-sequencing (scRNA-seq) to gain insights into the cellular composition, and developmental processes of various tissues and organs. Given the success of single-cell technologies a variety of computational tools and software packages were developed to enable and facilitate the analysis of scRNA-seq data. In this book chapter we want to give guidance on analyzing droplet-based scRNA-seq data from Drosophila. We will initially describe the preprocessing commonly done for Drosophila, point out possible downstream analyses, and finally highlight computational methods developed using Drosophila scRNA-seq data.

Olfactory Receptor Gene Regulation in Insects: Multiple Mechanisms for Singular Expression

The singular expression of insect olfactory receptors in specific populations of olfactory sensory neurons is fundamental to the encoding of odors in patterns of neuronal activity in the brain. How a receptor gene is selected, from among a large repertoire in the genome, to be expressed in a particular neuron is an outstanding question. Focusing on Drosophila melanogaster, where most investigations have been performed, but incorporating recent insights from other insect species, we review the multilevel regulatory mechanisms of olfactory receptor expression. We discuss how cis-regulatory elements, trans-acting factors, chromatin modifications, and feedback pathways collaborate to activate and maintain expression of the chosen receptor (and to suppress others), highlighting similarities and differences with the mechanisms underlying singular receptor expression in mammals. We also consider the plasticity of receptor regulation in response to environmental cues and internal state during the lifetime of an individual, as well as the evolution of novel expression patterns over longer timescales. Finally, we describe the mechanisms and potential significance of examples of receptor co-expression.

Drosophila, an Integrative Model to Study the Features of Muscle Stem Cells in Development and Regeneration

Muscle stem cells (MuSCs) are essential for muscle growth, maintenance and repair. Over the past decade, experiments in Drosophila have been instrumental in understanding the molecular and cellular mechanisms regulating MuSCs (also known as adult muscle precursors, AMPs) during development. A large number of genetic tools available in fruit flies provides an ideal framework to address new questions which could not be addressed with other model organisms. This review reports the main findings revealed by the study of Drosophila AMPs, with a specific focus on how AMPs are specified and properly positioned, how they acquire their identity and which are the environmental cues controlling their behavior and fate. The review also describes the recent identification of the Drosophila adult MuSCs that have similar characteristics to vertebrates MuSCs. Integration of the different levels of MuSCs analysis in flies is likely to provide new fundamental knowledge in muscle stem cell biology largely applicable to other systems.

Single-Cell RNA Sequencing Analysis of the Drosophila Larval Ventral Cord

Drosophila provides a powerful genetic system and an excellent model to study the development and function of the nervous system. The fly's small brain and complex behavior has been instrumental in mapping neuronal circuits and elucidating the neural basis of behavior. The fast pace of fly development and the wealth of genetic tools has enabled systematic studies on cell differentiation and fate specification, and has uncovered strategies for axon guidance and targeting. The accessibility of neuronal structures and the ability to edit and manipulate gene expression in selective cells and/or synaptic compartments has revealed mechanisms for synapse assembly and neuronal connectivity. Recent advances in single-cell RNA sequencing (scRNA-seq) have further enhanced our appreciation and understanding of neuronal diversity in a fly brain. However, due to the small size of the fly brain and its constituent cells, scRNA-seq methodologies require a few adaptations. Here, we describe a set of protocols optimized for scRNA-seq analysis of the Drosophila larval ventral nerve cord, starting from tissue dissection and cell dissociation to cDNA library preparation, sequencing, and data analysis. We apply this workflow to three separate samples and detail the technical challenges associated with successful application of scRNA-seq to studies on neuronal diversity. An accompanying article (Vicidomini, Nguyen, Choudhury, Brody, & Serpe, 2021) presents a custom multistage analysis pipeline that integrates modules contained in different R packages to ensure high-flexibility, high-quality RNA-seq data analysis. These protocols are developed for Drosophila larval ventral nerve cord, but could easily be adapted to other tissues and model organisms. © 2021 U.S. Government. Basic Protocol 1: Dissection of larval ventral nerve cords and preparation of single-cell suspensions Basic Protocol 2: Preparation and sequencing of single-cell transcriptome libraries Basic Protocol 3: Alignment of raw sequencing data to indexed genome and generation of count matrices.

DRscDB: A single-cell RNA-seq resource for data mining and data comparison across species

With the advent of single-cell RNA sequencing (scRNA-seq) technologies, there has been a spike in studies involving scRNA-seq of several tissues across diverse species including Drosophila. Although a few databases exist for users to query genes of interest within the scRNA-seq studies, search tools that enable users to find orthologous genes and their cell type-specific expression patterns across species are limited. Here, we built a new search database, DRscDB (https://www.flyrnai.org/tools/single_cell/web/), to address this need. DRscDB serves as a comprehensive repository for published scRNA-seq datasets for Drosophila and relevant datasets from human and other model organisms. DRscDB is based on manual curation of Drosophila scRNA-seq studies of various tissue types and their corresponding analogous tissues in vertebrates including zebrafish, mouse, and human. Of note, our search database provides most of the literature-derived marker genes, thus preserving the original analysis of the published scRNA-seq datasets. Finally, DRscDB serves as a web-based user interface that allows users to mine gene expression data from scRNA-seq studies and perform cell cluster enrichment analyses pertaining to various scRNA-seq studies, both within and across species.

Methods and tools for spatial mapping of single-cell RNAseq clusters in Drosophila

Single-cell RNA sequencing (scRNAseq) experiments provide a powerful means to identify clusters of cells that share common gene expression signatures. A major challenge in scRNAseq studies is to map the clusters to specific anatomical regions along the body and within tissues. Existing data, such as information obtained from large-scale in situ RNA hybridization studies, cell type specific transcriptomics, gene expression reporters, antibody stainings, and fluorescent tagged proteins, can help to map clusters to anatomy. However, in many cases, additional validation is needed to precisely map the spatial location of cells in clusters. Several approaches are available for spatial resolution in Drosophila, including mining of existing datasets, and use of existing or new tools for direct or indirect detection of RNA, or direct detection of proteins. Here, we review available resources and emerging technologies that will facilitate spatial mapping of scRNAseq clusters at high resolution in Drosophila. Importantly, we discuss the need, available approaches, and reagents for multiplexing gene expression detection in situ, as in most cases scRNAseq clusters are defined by the unique coexpression of sets of genes.

Single-cell transcriptomes of developing and adult olfactory receptor neurons in Drosophila

Recognition of environmental cues is essential for the survival of all organisms. Transcriptional changes occur to enable the generation and function of the neural circuits underlying sensory perception. To gain insight into these changes, we generated single-cell transcriptomes of Drosophila olfactory- (ORNs), thermo-, and hygro-sensory neurons at an early developmental and adult stage using single-cell and single-nucleus RNA sequencing. We discovered that ORNs maintain expression of the same olfactory receptors across development. Using receptor expression and computational approaches, we matched transcriptomic clusters corresponding to anatomically and physiologically defined neuron types across multiple developmental stages. We found that cell-type-specific transcriptomes partly reflected axon trajectory choices in development and sensory modality in adults. We uncovered stage-specific genes that could regulate the wiring and sensory responses of distinct ORN types. Collectively, our data reveal transcriptomic features of sensory neuron biology and provide a resource for future studies of their development and physiology.

Temporal evolution of single-cell transcriptomes of Drosophila olfactory projection neurons

Neurons undergo substantial morphological and functional changes during development to form precise synaptic connections and acquire specific physiological properties. What are the underlying transcriptomic bases? Here, we obtained the single-cell transcriptomes of Drosophila olfactory projection neurons (PNs) at four developmental stages. We decoded the identity of 21 transcriptomic clusters corresponding to 20 PN types and developed methods to match transcriptomic clusters representing the same PN type across development. We discovered that PN transcriptomes reflect unique biological processes unfolding at each stage-neurite growth and pruning during metamorphosis at an early pupal stage; peaked transcriptomic diversity during olfactory circuit assembly at mid-pupal stages; and neuronal signaling in adults. At early developmental stages, PN types with adjacent birth order share similar transcriptomes. Together, our work reveals principles of cellular diversity during brain development and provides a resource for future studies of neural development in PNs and other neuronal types.

Cell Dissociation from Butterfly Pupal Wing Tissues for Single-Cell RNA Sequencing

Butterflies are well known for their beautiful wings and have been great systems to understand the ecology, evolution, genetics, and development of patterning and coloration. These color patterns are mosaics on the wing created by the tiling of individual units called scales, which develop from single cells. Traditionally, bulk RNA sequencing (RNA-seq) has been used extensively to identify the loci involved in wing color development and pattern formation. RNA-seq provides an averaged gene expression landscape of the entire wing tissue or of small dissected wing regions under consideration. However, to understand the gene expression patterns of the units of color, which are the scales, and to identify different scale cell types within a wing that produce different colors and scale structures, it is necessary to study single cells. This has recently been facilitated by the advent of single-cell sequencing. Here, we provide a detailed protocol for the dissociation of cells from Bicyclus anynana pupal wings to obtain a viable single-cell suspension for downstream single-cell sequencing. We outline our experimental design and the use of fluorescence-activated cell sorting (FACS) to obtain putative scale-building and socket cells based on size. Finally, we discuss some of the current challenges of this technique in studying single-cell scale development and suggest future avenues to address these challenges.