Hypothesis-free phenotype prediction within a genetics-first framework.

Cohort-wide sequencing studies have revealed that the largest category of variants is those deemed 'rare', even for the subset located in coding regions (99% of known coding variants are seen in less than 1% of the population. Associative methods give some understanding how rare genetic variants influence disease and organism-level phenotypes. But here we show that additional discoveries can be made through a knowledge-based approach using protein domains and ontologies (function and phenotype) that considers all coding variants regardless of allele frequency. We describe an ab initio, genetics-first method making molecular knowledge-based interpretations for exome-wide non-synonymous variants for phenotypes at the organism and cellular level. By using this reverse approach, we identify plausible genetic causes for developmental disorders that have eluded other established methods and present molecular hypotheses for the causal genetics of 40 phenotypes generated from a direct-to-consumer genotype cohort. This system offers a chance to extract further discovery from genetic data after standard tools have been applied.

A genetically engineered, stem-cell-derived cellular vaccine.

Despite rapid clinical translation of COVID-19 vaccines in response to the global pandemic, an opportunity remains for vaccine technology innovation to address current limitations and meet challenges of inevitable future pandemics. We describe a universal vaccine cell (UVC) genetically engineered to mimic natural physiological immunity induced upon viral infection of host cells. Cells engineered to express the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike as a representative viral antigen induce robust neutralizing antibodies in immunized non-human primates. Similar titers generated in this established non-human primate (NHP) model have translated into protective human neutralizing antibody levels in SARS-CoV-2-vaccinated individuals. Animals vaccinated with ancestral spike antigens and subsequently challenged with SARS-CoV-2 Delta variant in a heterologous challenge have an approximately 3 log decrease in viral subgenomic RNA in the lungs. This cellular vaccine is designed as a scalable cell line with a modular poly-antigenic payload, allowing for rapid, large-scale clinical manufacturing and use in an evolving viral variant environment.

Experimental and Computational Approaches to Direct Cell Reprogramming: Recent Advancement and Future Challenges.

The process of direct cell reprogramming, also named transdifferentiation, permits for the conversion of one mature cell type directly into another, without returning to a dedifferentiated state. This makes direct reprogramming a promising approach for the development of several cellular and tissue engineering therapies. To achieve the change in the cell identity, direct reprogramming requires an arsenal of tools that combine experimental and computational techniques. In the recent years, several methods of transdifferentiation have been developed. In this review, we will introduce the concept of direct cell reprogramming and its background, and cover the recent developments in the experimental and computational prediction techniques with their applications. We also discuss the challenges of translating this technology to clinical setting, accompanied with potential solutions.

Genetic Association of Hematopoietic Stem Cell Transplantation Outcome beyond Histocompatibility Genes.

The outcome of hematopoietic stem cell transplantation (HSCT) is controlled by genetic factors among which the leukocyte antigen human leukocyte antigen (HLA) matching is most important. In addition, minor histocompatibility antigens and non-HLA gene polymorphisms in genes controlling immune responses are known to contribute to the risks associated with HSCT. Besides single-nucleotide polymorphisms (SNPs) in protein coding genes, SNPs in regulatory elements such as microRNAs (miRNAs) contribute to these genetic risks. However, genetic risks require for their realization the expression of the respective gene or miRNA. Thus, gene and miRNA expression studies may help to identify genes and SNPs that indeed affect the outcome of HSCT. In this review, we summarize gene expression profiling studies that were performed in recent years in both patients and animal models to identify genes regulated during HSCT. We discuss SNP-mRNA-miRNA regulatory networks and their contribution to the risks associated with HSCT in specific examples, including forkheadbox protein 3 and regulatory T cells, the role of the miR-155 and miR-146a regulatory network for graft-versus-host disease, and the function of MICA and its receptor NKG2D for the outcome of HSCT. These examples demonstrate how SNPs affect expression or function of proteins that modulate the alloimmune response and influence the outcome of HSCT. Specific miRNAs targeting these genes and directly affecting expression of mRNAs are identified. It might be valuable in the future to determine SNPs and to analyze miRNA and mRNA expression in parallel in cohorts of HSCT patients to further elucidate genetic risks of HSCT.