Gene and protein expression in human megakaryocytes derived from induced pluripotent stem cells

Integrating population genetics, stem cell biology and cellular genomics to study complex human diseases

Human pluripotent stem (hPS) cells can, in theory, be differentiated into any cell type, making them a powerful in vitro model for human biology. Recent technological advances have facilitated large-scale hPS cell studies that allow investigation of the genetic regulation of molecular phenotypes and their contribution to high-order phenotypes such as human disease. Integrating hPS cells with single-cell sequencing makes identifying context-dependent genetic effects during cell development or upon experimental manipulation possible. Here we discuss how the intersection of stem cell biology, population genetics and cellular genomics can help resolve the functional consequences of human genetic variation. We examine the critical challenges of integrating these fields and approaches to scaling them cost-effectively and practically. We highlight two areas of human biology that can particularly benefit from population-scale hPS cell studies, elucidating mechanisms underlying complex disease risk loci and evaluating relationships between common genetic variation and pharmacotherapeutic phenotypes.

Overcoming the Variability of iPSCs in the Manufacturing of Cell-Based Therapies

Various factors are known to contribute to the diversity of human induced pluripotent stem cells (hiPSCs). Among these are the donor's genetic background and family history, the somatic cell source, the iPSC reprogramming method, and the culture system of choice. Moreover, variability is seen even in iPSC clones, generated in a single reprogramming event, where the donor, somatic cell type, and reprogramming platform are the same. The diversity seen in iPSC lines often translates to epigenetic differences, as well as to differences in the expansion rate, iPSC line culture robustness, and their ability to differentiate into specific cell types. As such, the diversity of iPSCs presents a hurdle to standardizing iPSC-based cell therapy manufacturing. In this review, we will expand on the various factors that impact iPSC diversity and the strategies and tools that could be taken by the industry to overcome the differences amongst various iPSC lines, therefore enabling robust and reproducible iPSC-based cell therapy manufacturing processes.

resVAE ensemble: Unsupervised identification of gene sets in multi-modal single-cell sequencing data using deep ensembles

Feature identification and manual inspection is currently still an integral part of biological data analysis in single-cell sequencing. Features such as expressed genes and open chromatin status are selectively studied in specific contexts, cell states or experimental conditions. While conventional analysis methods construct a relatively static view on gene candidates, artificial neural networks have been used to model their interactions after hierarchical gene regulatory networks. However, it is challenging to identify consistent features in this modeling process due to the inherently stochastic nature of these methods. Therefore, we propose using ensembles of autoencoders and subsequent rank aggregation to extract consensus features in a less biased manner. Here, we performed sequencing data analyses of different modalities either independently or simultaneously as well as with other analysis tools. Our resVAE ensemble method can successfully complement and find additional unbiased biological insights with minimal data processing or feature selection steps while giving a measurement of confidence, especially for models using stochastic or approximation algorithms. In addition, our method can also work with overlapping clustering identity assignment suitable for transitionary cell types or cell fates in comparison to most conventional tools.

Secondary analyses for genome-wide association studies using expression quantitative trait loci

Genome-wide association studies (GWAS) have successfully identified thousands of single nucleotide polymorphisms (SNPs) associated with complex traits; however, the identified SNPs account for a fraction of trait heritability, and identifying the functional elements through which genetic variants exert their effects remains a challenge. Recent evidence suggests that SNPs associated with complex traits are more likely to be expression quantitative trait loci (eQTL). Thus, incorporating eQTL information can potentially improve power to detect causal variants missed by traditional GWAS approaches. Using genomic, transcriptomic, and platelet phenotype data from the Genetic Study of Atherosclerosis Risk family-based study, we investigated the potential to detect novel genomic risk loci by incorporating information from eQTL in the relevant target tissues (i.e., platelets and megakaryocytes) using established statistical principles in a novel way. Permutation analyses were performed to obtain family-wise error rates for eQTL associations, substantially lowering the genome-wide significance threshold for SNP-phenotype associations. In addition to confirming the well known association between PEAR1 and platelet aggregation, our eQTL-focused approach identified a novel locus (rs1354034) and gene (ARHGEF3) not previously identified in a GWAS of platelet aggregation phenotypes. A colocalization analysis showed strong evidence for a functional role of this eQTL.

Modeling genetic platelet disorders with human pluripotent stem cells: mega-progress but wanting more on our plate(let)

PURPOSE OF REVIEW

Megakaryocytes are rare hematopoietic cells that play an instrumental role in hemostasis, and other important biological processes such as immunity and wound healing. With the advent of cell reprogramming technologies and advances in differentiation protocols, it is now possible to obtain megakaryocytes from any pluripotent stem cell (PSC) via hematopoietic induction. Here, we review recent advances in PSC-derived megakaryocyte (iMK) technology, focusing on platform validation, disease modeling and current limitations.

RECENT FINDINGS

A comprehensive study confirmed that iMK can recapitulate many transcriptional and functional aspects of megakaryocyte and platelet biology, including variables associated with complex genetic traits such as sex and race. These findings were corroborated by several pathological models in which iMKs revealed molecular mechanisms behind inherited platelet disorders and assessed the efficacy of novel pharmacological interventions. However, current differentiation protocols generate primarily embryonic iMK, limiting the clinical and translational potential of this system.

SUMMARY

iMK are strong candidates to model pathologic mutations involved in platelet defects and develop innovative therapeutic strategies. Future efforts on generating definitive hematopoietic progenitors would improve current platelet generation protocols and expand our capacity to model neonatal and adult megakaryocyte disorders.