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Major computational challenges exist in relation to the collection, curation, processing and analysis of large genomic and imaging datasets, as well as the simulation of larger and more realistic models in systems biology. Here we discuss how a relative newcomer among programming languages—Julia—is poised to meet the current and emerging demands in the computational biosciences and beyond. Speed, flexibility, a thriving package ecosystem and readability are major factors that make high-performance computing and data analysis available to an unprecedented degree. We highlight how Julia’s design is already enabling new ways of analyzing biological data and systems, and we provide a list of resources that can facilitate the transition into Julian computing.

Increasing evidence links metabolism, protein synthesis, and growth signaling to impairments in the function of hematopoietic stem and progenitor cells (HSPCs) during aging. The Lin28b/Hmga2 pathway controls tissue development, and the postnatal downregulation of this pathway limits the self-renewal of adult vs fetal hematopoietic stem cells (HSCs). Igf2bp2 is an RNA binding protein downstream of Lin28b/Hmga2, which regulates messenger RNA stability and translation. The role of Igf2bp2 in HSC aging is unknown. In this study, an analysis of wild-type and Igf2bp2 knockout mice showed that Igf2bp2 regulates oxidative metabolism in HSPCs and the expression of metabolism, protein synthesis, and stemness-related genes in HSCs of young mice. Interestingly, Igf2bp2 expression and function strongly declined in aging HSCs. In young mice, Igf2bp2 deletion mimicked aging-related changes in HSCs, including changes in Igf2bp2 target gene expression and impairment of colony formation and repopulation capacity. In aged mice, Igf2bp2 gene status had no effect on these parameters in HSCs. Unexpectedly, Igf2bp2-deficient mice exhibited an amelioration of the aging-associated increase in HSCs and myeloid-skewed differentiation. The results suggest that Igf2bp2 controls mitochondrial metabolism, protein synthesis, growth, and stemness of young HSCs, which is necessary for full HSC function during young adult age. However, Igf2bp2 gene function is lost during aging, and it appears to contribute to HSC aging in 2 ways: the aging-related loss of Igf2bp2 gene function impairs the growth and repopulation capacity of aging HSCs, and the activity of Igf2bp2 at a young age contributes to aging-associated HSC expansion and myeloid skewing.

Analysis of cell–cell communication between embryonic stem cells using a combination of experiments and modeling shows that cells can communicate important messages over much larger distances than previously known, exhibiting quorum-sensing-like behavior.

The hematopoietic stem cell (HSC) niche provides essential microenvironmental cues for the production and maintenance of HSCs within the bone marrow. During inflammation, hematopoietic dynamics are perturbed, but it is not known whether changes to the HSC–niche interaction occur as a result. We visualize HSCs directly in vivo, enabling detailed analysis of the 3D niche dynamics and migration patterns in murine bone marrow following Trichinella spiralisinfection. Spatial statistical analysis of these HSC trajectories reveals two distinct modes of HSC behavior: (a) a pattern of revisiting previously explored space and (b) a pattern of exploring new space. Whereas HSCs from control donors predominantly follow pattern (a), those from infected mice adopt both strategies. Using detailed computational analyses of cell migration tracks and life‐history theory, we show that the increased motility of HSCs following infection can, perhaps counterintuitively, enable mice to cope better in deteriorating HSC–niche microenvironments following infection. StemCells2017;35:2292–2304 Hematopoietic stem cells (HSCs) are collected from infected and control mice and injected into recipient mice, where they are then imaged. HSCs are followed over time and their movement recorded. These tracks are then analyzed statistically, and the analysis shows that HSCs that have been exposed to Trichinellainfection exhibit different migration behavior than those in control mice. These differences suggest that they are searching for suitable niches in their new context.

Single-cell genomic technologies offer vast new resources with which to study cells, but their potential to inform parameter inference of cell dynamics has yet to be fully realized. Here we develop methods for Bayesian parameter inference with data that jointly measure gene expression and Ca2+dynamics in single cells. We propose to share information between cells via transfer learning: for a sequence of cells, the posterior distribution of one cell is used to inform the prior distribution of the next. In application to intracellular Ca2+signalling dynamics, we fit the parameters of a dynamical model for thousands of cells with variable single-cell responses. We show that transfer learning accelerates inference with sequences of cells regardless of how the cells are ordered. However, only by ordering cells based on their transcriptional similarity can we distinguish Ca2+dynamic profiles and associated marker genes from the posterior distributions. Inference results reveal complex and competing sources of cell heterogeneity: parameter covariation can diverge between the intracellular and intercellular contexts. Overall, we discuss the extent to which single-cell parameter inference informed by transcriptional similarity can quantify relationships between gene expression states and signalling dynamics in single cells.

Stem cells are fundamental to human life and offer great therapeutic potential, yet their biology remains incompletely—or in cases even poorly—understood. The field of stem cell biology has grown substantially in recent years due to a combination of experimental and theoretical contributions: the experimental branch of this work provides data in an ever‐increasing number of dimensions, while the theoretical branch seeks to determine suitable models of the fundamental stem cell processes that these data describe. The application of population dynamics to biology is amongst the oldest applications of mathematics to biology, and the population dynamics perspective continues to offer much today. Here we describe the impact that such a perspective has made in the field of stem cell biology. Using hematopoietic stem cells as our model system, we discuss the approaches that have been used to study their key properties, such as capacity for self‐renewal, differentiation, and cell fate lineage choice. We will also discuss the relevance of population dynamics in models of stem cells and cancer, where competition naturally emerges as an influential factor on the temporal evolution of cell populations. StemCells2017;35:80–88 Population dynamics can explain the maintenance, dominance, and extinction of stem cells and their progeny, through careful use of mathematical models. In the hematopoietic stem cell niche, competition between healthy and leukemic stem cells impacts cancer incidence and progression. Gray arrows: cell production by differentiation; red dashed arrows: possible regulatory interactions.

Kong et al. present Capybara, a computational method to identify cell states from single-cell gene expression data. Notably, Capybara can identify intermediate cell states and cell state transitions, offering biologists new means with which to interrogate the states and fates of cells.

Neural crest (NC) cells migrate throughout vertebrate embryos to give rise to a huge variety of cell types, but when and where lineages emerge and their regulation remain unclear. We have performed single-cell RNA sequencing (RNA-seq) of cranial NC cells from the first pharyngeal arch in zebrafish over several stages during migration. Computational analysis combining pseudotime and real-time data reveals that these NC cells first adopt a transitional state, becoming specified mid-migration, with the first lineage decisions being skeletal and pigment, followed by neural and glial progenitors. In addition, by computationally integrating these data with RNA-seq data from a transgenic Wnt reporter line, we identify gene cohorts with similar temporal responses to Wnts during migration and show that one, Atp6ap2, is required for melanocyte differentiation. Together, our results show that cranial NC cell lineages arise progressively and uncover a series of spatially restricted cell interactions likely to regulate such cell-fate decisions.

Our knowledge of transcriptional heterogeneities in epithelial stem and progenitor cell compartments is limited. Epidermal basal cells sustain cutaneous tissue maintenance and drive wound healing. Previous studies have probed basal cell heterogeneity in stem and progenitor potential, but a comprehensive dissection of basal cell dynamics during differentiation is lacking. Using single-cell RNA sequencing coupled with RNAScope and fluorescence lifetime imaging, we identify three non-proliferative and one proliferative basal cell state in homeostatic skin that differ in metabolic preference and become spatially partitioned during wound re-epithelialization. Pseudotemporal trajectory and RNA velocity analyses predict a quasi-linear differentiation hierarchy where basal cells progress from Col17a1Hi/Trp63Histate to early-response state, proliferate at the juncture of these two states, or become growth arrested before differentiating into spinous cells. Wound healing induces plasticity manifested by dynamic basal-spinous interconversions at multiple basal transcriptional states. Our study provides a systematic view of epidermal cellular dynamics, supporting a revised “hierarchical-lineage” model of homeostasis.

Haematopoietic stem cells (HSCs) are responsible for maintaining immune cells, red blood cells and platelets throughout life. HSCs must be located in their ecological niche (the bone marrow) to function correctly, that is, to regenerate themselves and their progeny; the latter eventually exit the bone marrow and enter circulation. We propose that cells with oncogenic potential—cancer/leukaemia stem cells (LSC)—and their progeny will also occupy this niche. Mathematical models, which describe the dynamics of HSCs, LSCs and their progeny allow investigation into the conditions necessary for defeating a malignant invasion of the niche. Two such models are developed and analysed here. To characterize their behaviour, we use an inferential framework that allows us to study regions in parameter space that give rise to desired behaviour together with an assessment of the robustness of the dynamics. Using this approach, we map out conditions under which HSCs can outcompete LSCs. In therapeutic applications, we clearly want to drive haematopoiesis into such regimes and the current analysis provide some guidance as to how we can identify new therapeutic targets. Our results suggest that maintaining a viable population of HSCs and their progenies in the niche may often already be nearly sufficient to eradicate LSCs from the system.