Experimental approaches for gene regulatory network construction: the chick as a model system

Gene regulatory network reconstruction: harnessing the power of single-cell multi-omic data

Inferring gene regulatory networks (GRNs) is a fundamental challenge in biology that aims to unravel the complex relationships between genes and their regulators. Deciphering these networks plays a critical role in understanding the underlying regulatory crosstalk that drives many cellular processes and diseases. Recent advances in sequencing technology have led to the development of state-of-the-art GRN inference methods that exploit matched single-cell multi-omic data. By employing diverse mathematical and statistical methodologies, these methods aim to reconstruct more comprehensive and precise gene regulatory networks. In this review, we give a brief overview on the statistical and methodological foundations commonly used in GRN inference methods. We then compare and contrast the latest state-of-the-art GRN inference methods for single-cell matched multi-omics data, and discuss their assumptions, limitations and opportunities. Finally, we discuss the challenges and future directions that hold promise for further advancements in this rapidly developing field.

Ac/Ds transposition for CRISPR/dCas9-SID4x epigenome modulation in zebrafish

Due to its genetic amenability coupled with advances in genome editing, zebrafish is an excellent model to examine the function of (epi)genomic elements. Here, we repurposed the Ac/Ds maize transposition system to efficiently characterise zebrafish cis-regulated elements, also known as enhancers, in F0-microinjected embryos. We further used the system to stably express guide RNAs enabling CRISPR/dCas9-interference (CRISPRi) perturbation of enhancers without disrupting the underlying genetic sequence. In addition, we probed the phenomenon of antisense transcription at two neural crest gene loci. Our study highlights the utility of Ac/Ds transposition as a new tool for transient epigenome modulation in zebrafish.

De-novo reconstruction and identification of transcriptional gene regulatory network modules differentiating single-cell clusters

Single-cell RNA sequencing (scRNA-seq) technology provides an unprecedented opportunity to understand gene functions and interactions at single-cell resolution. While computational tools for scRNA-seq data analysis to decipher differential gene expression profiles and differential pathway expression exist, we still lack methods to learn differential regulatory disease mechanisms directly from the single-cell data. Here, we provide a new methodology, named DiNiro, to unravel such mechanisms de novo and report them as small, easily interpretable transcriptional regulatory network modules. We demonstrate that DiNiro is able to uncover novel, relevant, and deep mechanistic models that not just predict but explain differential cellular gene expression programs. DiNiro is available at https://exbio.wzw.tum.de/diniro/.

Inferring gene regulatory networks from single-cell RNA-seq temporal snapshot data requires higher-order moments

Single-cell RNA sequencing (scRNA-seq) has become ubiquitous in biology. Recently, there has been a push for using scRNA-seq snapshot data to infer the underlying gene regulatory networks (GRNs) steering cellular function. To date, this aspiration remains unrealized due to technical and computational challenges. In this work we focus on the latter, which is under-represented in the literature. We took a systemic approach by subdividing the GRN inference into three fundamental components: data pre-processing, feature extraction, and inference. We observed that the regulatory signature is captured in the statistical moments of scRNA-seq data and requires computationally intensive minimization solvers to extract it. Furthermore, current data pre-processing might not conserve these statistical moments. Although our moment-based approach is a didactic tool for understanding the different compartments of GRN inference, this line of thinking—finding computationally feasible multi-dimensional statistics of data—is imperative for designing GRN inference methods.

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Single-cell RNA-seq temporal snapshot data for detecting regulation

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Challenges in data pre-processing, feature extraction, and network inference for GRNs

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Encoding of regulatory information in higher-order raw moments

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Non-linear least-squares inference for temporal scRNA-seq snapshot data

Single-cell RNA sequencing (scRNA-seq) has become ubiquitous in biology. Recently, there has been a push for using scRNA-seq snapshot data to infer the underlying gene regulatory networks (GRNs) steering cellular function. A recent benchmark of 12 GRN methods demonstrated that the algorithms struggled to predict the ground-truth GRNs and speculated that the low performance was due to the insufficient resolution in the scRNA-seq data. Rather than proposing another method, this paper focuses on how to decompose a GRN problem into three subproblems (pre-processing, feature extraction, and inference), so that the gene regulatory information is preserved in each step. Subsequently, we discuss how to best approach each of the three subproblems.

Congenital Deafness and Recent Advances Towards Restoring Hearing Loss

Congenital hearing loss is the most common birth defect, estimated to affect 2-3 in every 1000 births. Currently there is no cure for hearing loss. Treatment options are limited to hearing aids for mild and moderate cases, and cochlear implants for severe and profound hearing loss. Here we provide a literature overview of the environmental and genetic causes of congenital hearing loss, common animal models and methods used for hearing research, as well as recent advances towards developing therapies to treat congenital deafness. © 2021 The Authors.

A single-plasmid approach for genome editing coupled with long-term lineage analysis in chick embryos

An important strategy for establishing mechanisms of gene function during development is through mutation of individual genes and analysis of subsequent effects on cell behavior. Here, we present a single-plasmid approach for genome editing in chick embryos to study experimentally perturbed cells in an otherwise normal embryonic environment. To achieve this, we have engineered a plasmid that encodes Cas9 protein, gene-specific guide RNA (gRNA), and a fluorescent marker within the same construct. Using transfection- and electroporation-based approaches, we show that this construct can be used to perturb gene function in early embryos as well as human cell lines. Importantly, insertion of this cistronic construct into replication-incompetent avian retroviruses allowed us to couple gene knockouts with long-term lineage analysis. We demonstrate the application of our newly engineered constructs and viruses by perturbing β-catenin in vitro and Sox10, Pax6 and Pax7 in the neural crest, retina, and neural tube and segmental plate in vivo, respectively. Together, this approach enables genes of interest to be knocked out in identifiable cells in living embryos and can be broadly applied to numerous genes in different embryonic tissues.

Exploiting transfer learning for the reconstruction of the human gene regulatory network

MOTIVATION

The reconstruction of gene regulatory networks (GRNs) from gene expression data has received increasing attention in recent years, due to its usefulness in the understanding of regulatory mechanisms involved in human diseases. Most of the existing methods reconstruct the network through machine learning approaches, by analyzing known examples of interactions. However, (i) they often produce poor results when the amount of labeled examples is limited, or when no negative example is available and (ii) they are not able to exploit information extracted from GRNs of other (better studied) related organisms, when this information is available.

RESULTS

In this paper, we propose a novel machine learning method that overcomes these limitations, by exploiting the knowledge about the GRN of a source organism for the reconstruction of the GRN of the target organism, by means of a novel transfer learning technique. Moreover, the proposed method is natively able to work in the positive-unlabeled setting, where no negative example is available, by fruitfully exploiting a (possibly large) set of unlabeled examples. In our experiments, we reconstructed the human GRN, by exploiting the knowledge of the GRN of Mus musculus. Results showed that the proposed method outperforms state-of-the-art approaches and identifies previously unknown functional relationships among the analyzed genes.

AVAILABILITY AND IMPLEMENTATION

http://www.di.uniba.it/∼mignone/systems/biosfer/index.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Neural stem cells deriving from chick embryonic hindbrain recapitulate hindbrain development in culture

Neural stem cells (NSCs) are self-renewing multipotent cells that line the neural-tube and generate all the nervous system. Understanding NSC biology is fundamental for neurodevelopmental research and therapy. Many studies emphasized the need to culture NSCs, which are typically purified from mammalian embryonic/adult brains. These sources are somewhat limited in terms of quantity, availability and animal ethical guidelines. Therefore, new sources are needed. The chick is a powerful system for experimental embryology which contributed enormously to neurodevelopmental concepts. Its accessibility, genetic/molecular manipulations, and homology to other vertebrates, makes it valuable for developmental biology research. Recently, we identified a population of NSCs in the chick hindbrain. It resides in rhombomere-boundaries, expresses Sox2 and generates progenitors and neurons. Here, we investigated whether these cells can recapitulate hindbrain development in culture. By developing approaches to propagate and image cells, manipulate their growth-conditions and separate them into subpopulations, we demonstrate the ordered formation of multipotent and self-renewing neurospheres that maintain regional identity and display differential stem/differentiation/proliferation properties. Live imaging revealed new cellular dynamics in the culture. Collectively, these NSC cultures reproduce major aspects of hindbrain development in-vitro, proposing the chick as a model for culturing hindbrain-NSCs that can be directly applied to other neural-tube domains and species.

Optimization of CRISPR/Cas9 genome editing for loss-of-function in the early chick embryo

The advent of CRISPR/Cas9 has made genome editing possible in virtually any organism, including those not previously amenable to genetic manipulations. Here, we present an optimization of CRISPR/Cas9 for application to early avian embryos with improved efficiency via a three-fold strategy. First, we employed Cas9 protein flanked with two nuclear localization signal sequences for improved nuclear localization. Second, we used a modified guide RNA (gRNA) scaffold that obviates premature termination of transcription and unstable Cas9-gRNA interactions. Third, we used a chick-specific U6 promoter that yields 4-fold higher gRNA expression than the previously utilized human U6. For rapid screening of gRNAs for in vivo applications, we also generated a chicken fibroblast cell line that constitutively expresses Cas9. As proof of principle, we performed electroporation-based loss-of-function studies in the early chick embryo to knock out Pax7 and Sox10, key transcription factors with known functions in neural crest development. The results show that CRISPR/Cas9-mediated deletion causes loss of their respective proteins and transcripts, as well as predicted downstream targets. Taken together, the results reveal the utility of this optimized CRISPR/Cas9 method for targeted gene knockout in chicken embryos in a manner that is reproducible, robust and specific.

The chick eye in vision research: An excellent model for the study of ocular disease

The domestic chicken, Gallus gallus, serves as an excellent model for the study of a wide range of ocular diseases and conditions. The purpose of this manuscript is to outline some anatomic, physiologic, and genetic features of this organism as a robust animal model for vision research, particularly for modeling human retinal disease. Advantages include a sequenced genome, a large eye, relative ease of handling and maintenance, and ready availability. Relevant similarities and differences to humans are highlighted for ocular structures as well as for general physiologic processes. Current research applications for various ocular diseases and conditions, including ocular imaging with spectral domain optical coherence tomography, are discussed. Several genetic and non-genetic ocular disease models are outlined, including for pathologic myopia, keratoconus, glaucoma, retinal detachment, retinal degeneration, ocular albinism, and ocular tumors. Finally, the use of stem cell technology to study the repair of damaged tissues in the chick eye is discussed. Overall, the chick model provides opportunities for high-throughput translational studies to more effectively prevent or treat blinding ocular diseases.

Lineage specification of early embryos and embryonic stem cells at the dawn of enabling technologies

Establishment of progenitor cell populations and lineage diversity during embryogenesis and the differentiation of pluripotent stem cells is a fascinating and intricate biological process. Conceptually, an understanding of this developmental process provides a framework to integrate stem-cell pluripotency, cell competence and differentiating potential with the activity of extrinsic and intrinsic molecular determinants. The recent advent of enabling technologies of high-resolution transcriptome analysis at the cellular, population and spatial levels proffers the capability of gaining deeper insights into the attributes of the gene regulatory network and molecular signaling in lineage specification and differentiation. In this review, we provide a snapshot of the emerging enabling genomic technologies that contribute to the study of development and stem-cell biology.

From blastocyst to gastrula: gene regulatory networks of embryonic stem cells and early mouse embryogenesis

To date, many regulatory genes and signalling events coordinating mammalian development from blastocyst to gastrulation stages have been identified by mutational analyses and reverse-genetic approaches, typically on a gene-by-gene basis. More recent studies have applied bioinformatic approaches to generate regulatory network models of gene interactions on a genome-wide scale. Such models have provided insights into the gene networks regulating pluripotency in embryonic and epiblast stem cells, as well as cell-lineage determination in vivo. Here, we review how regulatory networks constructed for different stem cell types relate to corresponding networks in vivo and provide insights into understanding the molecular regulation of the blastocyst-gastrula transition.

Evolving gene regulatory networks into cellular networks guiding adaptive behavior: an outline how single cells could have evolved into a centralized neurosensory system

Understanding the evolution of the neurosensory system of man, able to reflect on its own origin, is one of the major goals of comparative neurobiology. Details of the origin of neurosensory cells, their aggregation into central nervous systems and associated sensory organs and their localized patterning leading to remarkably different cell types aggregated into variably sized parts of the central nervous system have begun to emerge. Insights at the cellular and molecular level have begun to shed some light on the evolution of neurosensory cells, partially covered in this review. Molecular evidence suggests that high mobility group (HMG) proteins of pre-metazoans evolved into the definitive Sox [SRY (sex determining region Y)-box] genes used for neurosensory precursor specification in metazoans. Likewise, pre-metazoan basic helix-loop-helix (bHLH) genes evolved in metazoans into the group A bHLH genes dedicated to neurosensory differentiation in bilaterians. Available evidence suggests that the Sox and bHLH genes evolved a cross-regulatory network able to synchronize expansion of precursor populations and their subsequent differentiation into novel parts of the brain or sensory organs. Molecular evidence suggests metazoans evolved patterning gene networks early, which were not dedicated to neuronal development. Only later in evolution were these patterning gene networks tied into the increasing complexity of diffusible factors, many of which were already present in pre-metazoans, to drive local patterning events. It appears that the evolving molecular basis of neurosensory cell development may have led, in interaction with differentially expressed patterning genes, to local network modifications guiding unique specializations of neurosensory cells into sensory organs and various areas of the central nervous system.