The microRNA processor DROSHA is a candidate gene for a severe progressive neurological disorder

Exploring noncoding variants in genetic diseases: from detection to functional insights

Previous studies on genetic diseases predominantly focused on protein-coding variations, overlooking the vast noncoding regions in the human genome. The development of high-throughput sequencing technologies and functional genomics tools has enabled the systematic identification of functional noncoding variants. These variants can impact gene expression, regulation, and chromatin conformation, thereby contributing to disease pathogenesis. Understanding the mechanisms that underlie the impact of noncoding variants on genetic diseases is indispensable for the development of precisely targeted therapies and the implementation of personalized medicine strategies. The intricacies of noncoding regions introduce a multitude of challenges and research opportunities. In this review, we introduce a spectrum of noncoding variants involved in genetic diseases, along with research strategies and advanced technologies for their precise identification and in-depth understanding of the complexity of the noncoding genome. We will delve into the research challenges and propose potential solutions for unraveling the genetic basis of rare and complex diseases.

Integrating non-mammalian model organisms in the diagnosis of rare genetic diseases in humans

Next-generation sequencing technology has rapidly accelerated the discovery of genetic variants of interest in individuals with rare diseases. However, showing that these variants are causative of the disease in question is complex and may require functional studies. Use of non-mammalian model organisms - mainly fruitflies (Drosophila melanogaster), nematode worms (Caenorhabditis elegans) and zebrafish (Danio rerio) - enables the rapid and cost-effective assessment of the effects of gene variants, which can then be validated in mammalian model organisms such as mice and in human cells. By probing mechanisms of gene action and identifying interacting genes and proteins in vivo, recent studies in these non-mammalian model organisms have facilitated the diagnosis of numerous genetic diseases and have enabled the screening and identification of therapeutic options for patients. Studies in non-mammalian model organisms have also shown that the biological processes underlying rare diseases can provide insight into more common mechanisms of disease and the biological functions of genes. Here, we discuss the opportunities afforded by non-mammalian model organisms, focusing on flies, worms and fish, and provide examples of their use in the diagnosis of rare genetic diseases.

miRNA dosage control in development and human disease

In mammals, miRNAs recognize target mRNAs via base pairing, which leads to a complex 'multiple-to-multiple' regulatory network. Previous studies have focused on the regulatory mechanisms and functions of individual miRNAs, but alterations of many individual miRNAs do not strongly disturb the miRNA regulatory network. Recent studies revealed the important roles of global miRNA dosage control events in physiological processes and pathogenesis, suggesting that miRNAs can be considered as a 'cellular buffer' that controls cell fate. Here, we review the current state of research on how global miRNA dosage is tightly controlled to regulate development, tumorigenesis, neurophysiology, and immunity. We propose that methods of controlling global miRNA dosage may serve as effective therapeutic tools to cure human diseases.

The microRNAs (miRs) overexpressing mesenchymal stem cells (MSCs) therapy in neurological disorders; hope or hype

Altered expression of multiple miRNAs was found to be extensively involved in the pathogenesis of different neurological disorders including Alzheimer's disease, Parkinson's disease, stroke, epilepsy, multiple sclerosis, amyotrophic lateral sclerosis, and Huntington's disease. One of the biggest concerns within gene-based therapy is the delivery of the therapeutic microRNAs to the intended place, which is obligated to surpass the biological barriers without undergoing degradation in the bloodstream or renal excretion. Hence, the delivery of modified and unmodified miRNA molecules using excellent vehicles is required. In this light, mesenchymal stem cells (MSCs) have attracted increasing attention. The MSCs can be genetically modified to express or overexpress a particular microRNA aimed with promote neurogenesis and neuroprotection. The current review has focused on the therapeutic capabilities of microRNAs-overexpressing MSCs to ameliorate functional deficits in neurological conditions.

A concurrent dual analysis of genomic data augments diagnoses: Experiences of 2 clinical sites in the Undiagnosed Diseases Network

PURPOSE

Next-generation sequencing (NGS) has revolutionized the diagnostic process for rare/ultrarare conditions. However, diagnosis rates differ between analytical pipelines. In the National Institutes of Health-Undiagnosed Diseases Network (UDN) study, each individual's NGS data are concurrently analyzed by the UDN sequencing core laboratory and the clinical sites. We examined the outcomes of this practice.

METHODS

A retrospective review was performed at 2 UDN clinical sites to compare the variants and diagnoses/candidate genes identified with the dual analyses of the NGS data.

RESULTS

In total, 95 individuals had 100 diagnoses/candidate genes. There was 59% concordance between the UDN sequencing core laboratories and the clinical sites in identifying diagnoses/candidate genes. The core laboratory provided more diagnoses, whereas the clinical sites prioritized more research variants/candidate genes (P < .001). The clinical sites solely identified 15% of the diagnoses/candidate genes. The differences between the 2 pipelines were more often because of variant prioritization disparities than variant detection.

CONCLUSION

The unique dual analysis of NGS data in the UDN synergistically enhances outcomes. The core laboratory provided a clinical analysis with more diagnoses and the clinical sites prioritized more research variants/candidate genes. Implementing such concurrent dual analyses in other genomic research studies and clinical settings can improve both variant detection and prioritization.