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Cell fate choice and commitment of multipotent progenitor cells to a differentiated lineage requires broad changes of their gene expression profile. But how progenitor cells overcome the stability of their gene expression configuration (attractor) to exit the attractor in one direction remains elusive. Here we show that commitment of blood progenitor cells to the erythroid or myeloid lineage is preceded by the destabilization of their high-dimensional attractor state, such that differentiating cells undergo a critical state transition. Single-cell resolution analysis of gene expression in populations of differentiating cells affords a new quantitative index for predicting critical transitions in a high-dimensional state space based on decrease of correlation between cells and concomitant increase of correlation between genes as cells approach a tipping point. The detection of \"rebellious cells\" that enter the fate opposite to the one intended corroborates the model of preceding destabilization of a progenitor attractor. Thus, early warning signals associated with critical transitions can be detected in statistical ensembles of high-dimensional systems, offering a formal theory-based approach for analyzing single-cell molecular profiles that goes beyond current computational pattern recognition, does not require knowledge of specific pathways, and could be used to predict impending major shifts in development and disease.

Steering the differentiation of induced pluripotent stem cells (iPSCs) toward specific cell types is crucial for patient-specific disease modeling and drug testing. This effort requires the capacity to predict and control when and how multipotent progenitor cells commit to the desired cell fate. Cell fate commitment represents a critical state transition or “tipping point” at which complex systems undergo a sudden qualitative shift. To characterize such transitions during iPSC to cardiomyocyte differentiation, we analyzed the gene expression patterns of 96 developmental genes at single-cell resolution. We identified a bifurcation event early in the trajectory when a primitive streak-like cell population segregated into the mesodermal and endodermal lineages. Before this branching point, we could detect the signature of an imminent critical transition: increase in cell heterogeneity and coordination of gene expression. Correlation analysis of gene expression profiles at the tipping point indicates transcription factors that drive the state transition toward each alternative cell fate and their relationships with specific phenotypic readouts. The latter helps us to facilitate small molecule screening for differentiation efficiency. To this end, we set up an analysis of cell population structure at the tipping point after systematic variation of the protocol to bias the differentiation toward mesodermal or endodermal cell lineage. We were able to predict the proportion of cardiomyocytes many days before cells manifest the differentiated phenotype. The analysis of cell populations undergoing a critical state transition thus affords a tool to forecast cell fate outcomes and can be used to optimize differentiation protocols to obtain desired cell populations.

An oral tradition for microRNA Recent work suggests that microRNAs, the ubiquitous, small, non-coding genetic elements with important regulatory roles, were important in the evolution of complexity in multicellular animals. What was the role of these microRNAs when they first evolved? A deep sequencing study of the marine ragworm Platynereis dumerilii , and comparison with other bilaterian animals, suggests that the most ancient known microRNA, miR-100, was initially active in neurosecretory cells around the mouth. Other highly conserved varieties were first present in specific tissues and organ systems, such as ciliated cells and parts of the nervous system, musculature and gut. This work suggests that the last common ancestor of bilaterian animals already had all these structures. Recent work suggests that microRNAs might have been important in the evolution of complexity in multicellular animals. Here it is shown that the most ancient known microRNA, miR–100, was initially active in neurosecretory cells around the mouth. Other highly conserved varieties were first present in specific tissues and organ systems. Thus, microRNA expression was initially restricted to an ancient set of ancient animal cell types and tissues. The spectacular escalation in complexity in early bilaterian evolution correlates with a strong increase in the number of microRNAs 1 , 2 . To explore the link between the birth of ancient microRNAs and body plan evolution, we set out to determine the ancient sites of activity of conserved bilaterian microRNA families in a comparative approach. We reason that any specific localization shared between protostomes and deuterostomes (the two major superphyla of bilaterian animals) should probably reflect an ancient specificity of that microRNA in their last common ancestor. Here, we investigate the expression of conserved bilaterian microRNAs in Platynereis dumerilii , a protostome retaining ancestral bilaterian features 3 , 4 , in Capitella , another marine annelid, in the sea urchin Strongylocentrotus , a deuterostome, and in sea anemone Nematostella , representing an outgroup to the bilaterians. Our comparative data indicate that the oldest known animal microRNA, miR-100, and the related miR-125 and let-7 were initially active in neurosecretory cells located around the mouth. Other sets of ancient microRNAs were first present in locomotor ciliated cells, specific brain centres, or, more broadly, one of four major organ systems: central nervous system, sensory tissue, musculature and gut. These findings reveal that microRNA evolution and the establishment of tissue identities were closely coupled in bilaterian evolution. Also, they outline a minimum set of cell types and tissues that existed in the protostome–deuterostome ancestor.

Accurate orthology prediction is crucial for many applications in the post-genomic era. The lack of broadly accepted benchmark tests precludes a comprehensive analysis of orthology inference. So far, functional annotation between orthologs serves as a performance proxy. However, this violates the fundamental principle of orthology as an evolutionary definition, while it is often not applicable due to limited experimental evidence for most species. Therefore, we constructed high quality \"gold standard\" orthologous groups that can serve as a benchmark set for orthology inference in bacterial species. Herein, we used this dataset to demonstrate 1) why a manually curated, phylogeny-based dataset is more appropriate for benchmarking orthology than other popular practices and 2) how it guides database design and parameterization through careful error quantification. More specifically, we illustrate how function-based tests often fail to identify false assignments, misjudging the true performance of orthology inference methods. We also examined how our dataset can instruct the selection of a \"core\" species repertoire to improve detection accuracy. We conclude that including more genomes at the proper evolutionary distances can influence the overall quality of orthology detection. The curated gene families, called Reference Orthologous Groups, are publicly available at http://eggnog.embl.de/orthobench2.

Background Genes of conserved order in bacterial genomes tend to evolve slower than genes whose order is not conserved. In addition, genes with a GC content lower than the GC content of the resident genome are known to be selectively silenced by the histone-like nucleoid structuring protein (H-NS) in Salmonella . Results In this study, we use a comparative genomics approach to demonstrate that in Salmonella , genes whose order is not conserved (or genes without homologs) in closely related bacteria possess a significantly lower average GC content in comparison to genes that preserve their relative position in the genome. Moreover, these genes are more frequently targeted by H-NS than genes that have conserved their genomic neighborhood. We also observed that duplicated genes that do not preserve their genomic neighborhood are, on average, under less selective pressure. Conclusions We establish a strong association between gene order, GC content and gene silencing in a model bacterial species. This analysis suggests that genes that are not under strong selective pressure (evolve faster than others) in Salmonella tend to accumulate more AT-rich mutations and are eventually silenced by H-NS. Our findings may establish new approaches for a better understanding of bacterial genome evolution and function, using information from functional and comparative genomics.

Recently duplicated genes are believed to often overlap in function and expression. A priori, they are thus less likely to be essential. Although this was indeed observed in yeast, mouse singletons and duplicates were reported to be equally often essential. This contradiction can only partly be explained by experimental biases. We herein show that older genes (i.e., genes with earlier phyletic origin) are more likely to be essential, regardless of their duplication status. At a given phyletic gene age, duplicates are always less likely to be essential compared with singletons. The “paradoxical” high essentiality among mouse gene duplicates is then caused by different age profiles of singletons and duplicates, with the latter tending to be derived from older genes.

Several cyclic processes take place within a single organism. For example, the cell cycle is coordinated with the 24 h diurnal rhythm in animals and plants, and with the 40 min ultradian rhythm in budding yeast. To examine the evolution of periodic gene expression during these processes, we performed the first systematic comparison in three organisms ( Homo sapiens , Arabidopsis thaliana and Saccharomyces cerevisiae ) by using public microarray data. We observed that although diurnal‐regulated and ultradian‐regulated genes are not generally cell‐cycle‐regulated, they tend to have cell‐cycle‐regulated paralogues. Thus, diverged temporal expression of paralogues seems to facilitate cellular orchestration under different periodic stimuli. Lineage‐specific functional repertoires of periodic‐associated paralogues imply that this mode of regulation might have evolved independently in several organisms. Bork et al . present the first systematic comparison of transcriptionally regulated genes during multiple periodic cellular processes and show that diurnal‐/ultradian‐regulated and cell cycle‐regulated genes tend to be paralogs of each other. This is observed in Arabidopsis, human, and budding yeast, despite different sets of genes being duplicated and transcriptionally regulated in each organism. These findings suggest that temporal sub‐ or neo‐functionalization of duplicated genes has taken place independently in the three lineages.

The Genomic Medicine for Everyone (Geno4ME) study was established across the seven-state Providence Health system to enable genomics research and genome-guided care across patients’ lifetimes. We included multi-lingual outreach to underrepresented groups, a novel electronic informed consent and education platform, and whole genome sequencing with clinical return of results and electronic health record integration for 78 hereditary disease genes and four pharmacogenes. Whole genome sequences were banked for research and variant reanalysis. The program provided genetic counseling, pharmacist support, and guideline-based clinical recommendations for patients and their providers. Over 30,800 potential participants were initially contacted, with 2716 consenting and 2017 having results returned (47.5% racial and ethnic minority individuals). Overall, 432 (21.4%) had test results with one or more management recommendations related to hereditary disease(s) and/or pharmacogenomics. We propose Geno4ME as a framework to integrate population health genomics into routine healthcare.

Accurate orthology prediction is crucial for many applications in the post-genomic era. The lack of broadly accepted benchmark tests precludes a comprehensive analysis of orthology inference. So far, functional annotation between orthologs serves as a performance proxy. However, this violates the fundamental principle of orthology as an evolutionary definition, while it is often not applicable due to limited experimental evidence for most species. Therefore, we constructed high quality \"gold standard\" orthologous groups that can serve as a benchmark set for orthology inference in bacterial species. Herein, we used this dataset to demonstrate 1) why a manually curated, phylogeny-based dataset is more appropriate for benchmarking orthology than other popular practices and 2) how it guides database design and parameterization through careful error quantification. More specifically, we illustrate how function-based tests often fail to identify false assignments, misjudging the true performance of orthology inference methods. We also examined how our dataset can instruct the selection of a \"core\" species repertoire to improve detection accuracy. We conclude that including more genomes at the proper evolutionary distances can influence the overall quality of orthology detection. The curated gene families, called Reference Orthologous Groups, are publicly available at http://eggnog.embl.de/orthobench2.

The question of the existence of cancer is inadequately answered by invoking somatic mutations or the disruptions of cellular and tissue control mechanisms. As such uniformly random events alone cannot account for the almost inevitable occurrence of an extremely complex process such as cancer. In the different epistemic realm, an ultimate explanation of cancer is that cancer is a reversion of a cell to an ancestral pre-Metazoan state, i.e. a cellular form of atavism. Several studies have suggested that genes involved in cancer have evolved at particular evolutionary time linked to the unicellular-multicellular transition. Here we used a refined phylostratigraphic analysis of evolutionary ages of the known genes/pathways associated with cancer and the genes differentially expressed between normal and cancer tissue as well as between embryonic and mature (differentiated) cells. We found that cancer-specific transcriptomes and cancer-related pathways were enriched for genes that evolved in the pre-Metazoan era and depleted of genes that evolved in the post-Metazoan era. By contrast an opposite relation was found for cell maturation: the age distribution frequency of the genes expressed in differentiated epithelial cells were enriched for post-Metazoan genes and depleted of pre-Metazoan ones. These findings support the atavism theory that cancer cells manifest the reactivation of an ancient ancestral state featuring unicellular modalities. Thus our bioinformatics analyses suggest that not only does oncogenesis recapitulate ontogenesis, and ontogenesis recapitulates phylogenesis, but also oncogenesis recapitulates phylogenesis. This more encompassing perspective may offer a natural organizing framework for genetic alterations in cancers and point to new treatment options that target the genes controlling the atavism transition.