Differentiation is accompanied by a progressive loss in transcriptional memory.

BACKGROUND: Cell differentiation requires the integration of two opposite processes, a stabilizing cellular memory, especially at the transcriptional scale, and a burst of gene expression variability which follows the differentiation induction. Therefore, the actual capacity of a cell to undergo phenotypic change during a differentiation process relies upon a modification in this balance which favors change-inducing gene expression variability. However, there are no experimental data providing insight on how fast the transcriptomes of identical cells would diverge on the scale of the very first two cell divisions during the differentiation process. RESULTS: In order to quantitatively address this question, we developed different experimental methods to recover the transcriptomes of related cells, after one and two divisions, while preserving the information about their lineage at the scale of a single cell division. We analyzed the transcriptomes of related cells from two differentiation biological systems (human CD34+ cells and T2EC chicken primary erythrocytic progenitors) using two different single-cell transcriptomics technologies (scRT-qPCR and scRNA-seq). CONCLUSIONS: We identified that the gene transcription profiles of differentiating sister cells are more similar to each other than to those of non-related cells of the same type, sharing the same environment and undergoing similar biological processes. More importantly, we observed greater discrepancies between differentiating sister cells than between self-renewing sister cells. Furthermore, a progressive increase in this divergence from first generation to second generation was observed when comparing differentiating cousin cells to self renewing cousin cells. Our results are in favor of a gradual erasure of transcriptional memory during the differentiation process.

Translation-dependent and -independent mRNA decay occur through mutually exclusive pathways defined by ribosome density during T cell activation.

mRNA translation and decay are tightly interconnected processes both in the context of mRNA quality-control pathways and for the degradation of functional mRNAs. Cotranslational mRNA degradation through codon usage, ribosome collisions, and the recruitment of specific proteins to ribosomes is an important determinant of mRNA turnover. However, the extent to which translation-dependent mRNA decay (TDD) and translation-independent mRNA decay (TID) pathways participate in the degradation of mRNAs has not been studied yet. Here we describe a comprehensive analysis of basal and signal-induced TDD and TID in mouse primary CD4+ T cells. Our results indicate that most cellular transcripts are decayed to some extent in a translation-dependent manner. Our analysis further identifies the length of untranslated regions, the density of ribosomes, and GC3 content as important determinants of TDD magnitude. Consistently, all transcripts that undergo changes in ribosome density within their coding sequence upon T cell activation display a corresponding change in their TDD level. Moreover, we reveal a dynamic modulation in the relationship between GC3 content and TDD upon T cell activation, with a reversal in the impact of GC3- and AU3-rich codons. Altogether, our data show a strong and dynamic interconnection between mRNA translation and decay in mammalian primary cells.

Condensin positioning at telomeres by shelterin proteins drives sister-telomere disjunction in anaphase.

The localization of condensin along chromosomes is crucial for their accurate segregation in anaphase. Condensin is enriched at telomeres but how and for what purpose had remained elusive. Here, we show that fission yeast condensin accumulates at telomere repeats through the balancing acts of Taz1, a core component of the shelterin complex that ensures telomeric functions, and Mit1, a nucleosome remodeler associated with shelterin. We further show that condensin takes part in sister-telomere separation in anaphase, and that this event can be uncoupled from the prior separation of chromosome arms, implying a telomere-specific separation mechanism. Consistent with a cis-acting process, increasing or decreasing condensin occupancy specifically at telomeres modifies accordingly the efficiency of their separation in anaphase. Genetic evidence suggests that condensin promotes sister-telomere separation by counteracting cohesin. Thus, our results reveal a shelterin-based mechanism that enriches condensin at telomeres to drive in cis their separation during mitosis.

RNA helicase-dependent gene looping impacts messenger RNA processing.

DDX5 and DDX17 are DEAD-box RNA helicase paralogs which regulate several aspects of gene expression, especially transcription and splicing, through incompletely understood mechanisms. A transcriptome analysis of DDX5/DDX17-depleted human cells confirmed the large impact of these RNA helicases on splicing and revealed a widespread deregulation of 3' end processing. In silico analyses and experiments in cultured cells showed the binding and functional contribution of the genome organizing factor CTCF to chromatin sites at or near a subset of DDX5/DDX17-dependent exons that are characterized by a high GC content and a high density of RNA Polymerase II. We propose the existence of an RNA helicase-dependent relationship between CTCF and the dynamics of transcription across DNA and/or RNA structured regions, that contributes to the processing of internal and terminal exons. Moreover, local DDX5/DDX17-dependent chromatin loops spatially connect RNA helicase-regulated exons with their cognate promoter, and we provide the first direct evidence that de novo gene looping modifies alternative splicing and polyadenylation. Overall our findings uncover the impact of DDX5/DDX17-dependent chromatin folding on pre-messenger RNA processing.

Evidence for close molecular proximity between reverting and undifferentiated cells.

BACKGROUND: According to Waddington's epigenetic landscape concept, the differentiation process can be illustrated by a cell akin to a ball rolling down from the top of a hill (proliferation state) and crossing furrows before stopping in basins or "attractor states" to reach its stable differentiated state. However, it is now clear that some committed cells can retain a certain degree of plasticity and reacquire phenotypical characteristics of a more pluripotent cell state. In line with this dynamic model, we have previously shown that differentiating cells (chicken erythrocytic progenitors (T2EC)) retain for 24 h the ability to self-renew when transferred back in self-renewal conditions. Despite those intriguing and promising results, the underlying molecular state of those "reverting" cells remains unexplored. The aim of the present study was therefore to molecularly characterize the T2EC reversion process by combining advanced statistical tools to make the most of single-cell transcriptomic data. For this purpose, T2EC, initially maintained in a self-renewal medium (0H), were induced to differentiate for 24H (24H differentiating cells); then, a part of these cells was transferred back to the self-renewal medium (48H reverting cells) and the other part was maintained in the differentiation medium for another 24H (48H differentiating cells). For each time point, cell transcriptomes were generated using scRT-qPCR and scRNAseq. RESULTS: Our results showed a strong overlap between 0H and 48H reverting cells when applying dimensional reduction. Moreover, the statistical comparison of cell distributions and differential expression analysis indicated no significant differences between these two cell groups. Interestingly, gene pattern distributions highlighted that, while 48H reverting cells have gene expression pattern more similar to 0H cells, they are not completely identical, which suggest that for some genes a longer delay may be required for the cells to fully recover. Finally, sparse PLS (sparse partial least square) analysis showed that only the expression of 3 genes discriminates 48H reverting and 0H cells. CONCLUSIONS: Altogether, we show that reverting cells return to an earlier molecular state almost identical to undifferentiated cells and demonstrate a previously undocumented physiological and molecular plasticity during the differentiation process, which most likely results from the dynamic behavior of the underlying molecular network.

Divergent clonal differentiation trajectories establish CD8+ memory T cell heterogeneity during acute viral infections in humans.

The CD8+ T cell response to an antigen is composed of many T cell clones with unique T cell receptors, together forming a heterogeneous repertoire of effector and memory cells. How individual T cell clones contribute to this heterogeneity throughout immune responses remains largely unknown. In this study, we longitudinally track human CD8+ T cell clones expanding in response to yellow fever virus (YFV) vaccination at the single-cell level. We observed a drop in clonal diversity in blood from the acute to memory phase, suggesting that clonal selection shapes the circulating memory repertoire. Clones in the memory phase display biased differentiation trajectories along a gradient from stem cell to terminally differentiated effector memory fates. In secondary responses, YFV- and influenza-specific CD8+ T cell clones are poised to recapitulate skewed differentiation trajectories. Collectively, we show that the sum of distinct clonal phenotypes results in the multifaceted human T cell response to acute viral infections.

Characterizing the interplay between gene nucleotide composition bias and splicing.

BACKGROUND: Nucleotide composition bias plays an important role in the 1D and 3D organization of the human genome. Here, we investigate the potential interplay between nucleotide composition bias and the regulation of exon recognition during splicing. RESULTS: By analyzing dozens of RNA-seq datasets, we identify two groups of splicing factors that activate either about 3200 GC-rich exons or about 4000 AT-rich exons. We show that splicing factor-dependent GC-rich exons have predicted RNA secondary structures at 5' ss and are dependent on U1 snRNP-associated proteins. In contrast, splicing factor-dependent AT-rich exons have a large number of decoy branch points, SF1- or U2AF2-binding sites and are dependent on U2 snRNP-associated proteins. Nucleotide composition bias also influences local chromatin organization, with consequences for exon recognition during splicing. Interestingly, the GC content of exons correlates with that of their hosting genes, isochores, and topologically associated domains. CONCLUSIONS: We propose that regional nucleotide composition bias over several dozens of kilobase pairs leaves a local footprint at the exon level and induces constraints during splicing that can be alleviated by local chromatin organization at the DNA level and recruitment of specific splicing factors at the RNA level. Therefore, nucleotide composition bias establishes a direct link between genome organization and local regulatory processes, like alternative splicing.

Interplay between coding and exonic splicing regulatory sequences.

The inclusion of exons during the splicing process depends on the binding of splicing factors to short low-complexity regulatory sequences. The relationship between exonic splicing regulatory sequences and coding sequences is still poorly understood. We demonstrate that exons that are coregulated by any given splicing factor share a similar nucleotide composition bias and preferentially code for amino acids with similar physicochemical properties because of the nonrandomness of the genetic code. Indeed, amino acids sharing similar physicochemical properties correspond to codons that have the same nucleotide composition bias. In particular, we uncover that the TRA2A and TRA2B splicing factors that bind to adenine-rich motifs promote the inclusion of adenine-rich exons coding preferentially for hydrophilic amino acids that correspond to adenine-rich codons. SRSF2 that binds guanine/cytosine-rich motifs promotes the inclusion of GC-rich exons coding preferentially for small amino acids, whereas SRSF3 that binds cytosine-rich motifs promotes the inclusion of exons coding preferentially for uncharged amino acids, like serine and threonine that can be phosphorylated. Finally, coregulated exons encoding amino acids with similar physicochemical properties correspond to specific protein features. In conclusion, the regulation of an exon by a splicing factor that relies on the affinity of this factor for specific nucleotide(s) is tightly interconnected with the exon-encoded physicochemical properties. We therefore uncover an unanticipated bidirectional interplay between the splicing regulatory process and its biological functional outcome.

Probabilistic count matrix factorization for single cell expression data analysis.

MOTIVATION: The development of high-throughput single-cell sequencing technologies now allows the investigation of the population diversity of cellular transcriptomes. The expression dynamics (gene-to-gene variability) can be quantified more accurately, thanks to the measurement of lowly expressed genes. In addition, the cell-to-cell variability is high, with a low proportion of cells expressing the same genes at the same time/level. Those emerging patterns appear to be very challenging from the statistical point of view, especially to represent a summarized view of single-cell expression data. Principal component analysis (PCA) is a most powerful tool for high dimensional data representation, by searching for latent directions catching the most variability in the data. Unfortunately, classical PCA is based on Euclidean distance and projections that poorly work in presence of over-dispersed count data with dropout events like single-cell expression data. RESULTS: We propose a probabilistic Count Matrix Factorization (pCMF) approach for single-cell expression data analysis that relies on a sparse Gamma-Poisson factor model. This hierarchical model is inferred using a variational EM algorithm. It is able to jointly build a low dimensional representation of cells and genes. We show how this probabilistic framework induces a geometry that is suitable for single-cell data visualization, and produces a compression of the data that is very powerful for clustering purposes. Our method is competed against other standard representation methods like t-SNE, and we illustrate its performance for the representation of single-cell expression data. AVAILABILITY AND IMPLEMENTATION: Our work is implemented in the pCMF R-package (https://github.com/gdurif/pCMF). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Males as somatic investment in a parthenogenetic nematode.

We report the reproductive strategy of the nematode Mesorhabditis belari This species produces only 9% males, whose sperm is necessary to fertilize and activate the eggs. However, most of the fertilized eggs develop without using the sperm DNA and produce female individuals. Only in 9% of eggs is the male DNA utilized, producing sons. We found that mixing of parental genomes only gives rise to males because the Y-bearing sperm of males are much more competent than the X-bearing sperm for penetrating the eggs. In this previously unrecognized strategy, asexual females produce few sexual males whose genes never reenter the female pool. Here, production of males is of interest only if sons are more likely to mate with their sisters. Using game theory, we show that in this context, the production of 9% males by M. belari females is an evolutionary stable strategy.

Condensin controls cellular RNA levels through the accurate segregation of chromosomes instead of directly regulating transcription.

Condensins are genome organisers that shape chromosomes and promote their accurate transmission. Several studies have also implicated condensins in gene expression, although any mechanisms have remained enigmatic. Here, we report on the role of condensin in gene expression in fission and budding yeasts. In contrast to previous studies, we provide compelling evidence that condensin plays no direct role in the maintenance of the transcriptome, neither during interphase nor during mitosis. We further show that the changes in gene expression in post-mitotic fission yeast cells that result from condensin inactivation are largely a consequence of chromosome missegregation during anaphase, which notably depletes the RNA-exosome from daughter cells. Crucially, preventing karyotype abnormalities in daughter cells restores a normal transcriptome despite condensin inactivation. Thus, chromosome instability, rather than a direct role of condensin in the transcription process, changes gene expression. This knowledge challenges the concept of gene regulation by canonical condensin complexes.

High dimensional classification with combined adaptive sparse PLS and logistic regression.

Motivation: The high dimensionality of genomic data calls for the development of specific classification methodologies, especially to prevent over-optimistic predictions. This challenge can be tackled by compression and variable selection, which combined constitute a powerful framework for classification, as well as data visualization and interpretation. However, current proposed combinations lead to unstable and non convergent methods due to inappropriate computational frameworks. We hereby propose a computationally stable and convergent approach for classification in high dimensional based on sparse Partial Least Squares (sparse PLS). Results: We start by proposing a new solution for the sparse PLS problem that is based on proximal operators for the case of univariate responses. Then we develop an adaptive version of the sparse PLS for classification, called logit-SPLS, which combines iterative optimization of logistic regression and sparse PLS to ensure computational convergence and stability. Our results are confirmed on synthetic and experimental data. In particular, we show how crucial convergence and stability can be when cross-validation is involved for calibration purposes. Using gene expression data, we explore the prediction of breast cancer relapse. We also propose a multicategorial version of our method, used to predict cell-types based on single-cell expression data. Availability and implementation: Our approach is implemented in the plsgenomics R-package. Contact: ghislain.durif@inria.fr. Supplementary information: Supplementary data are available at Bioinformatics online.

Transposable Element Misregulation Is Linked to the Divergence between Parental piRNA Pathways in Drosophila Hybrids.

Interspecific hybridization is a genomic stress condition that leads to the activation of transposable elements (TEs) in both animals and plants. In hybrids between Drosophila buzzatii and Drosophila koepferae, mobilization of at least 28 TEs has been described. However, the molecular mechanisms underlying this TE release remain poorly understood. To give insight on the causes of this TE activation, we performed a TE transcriptomic analysis in ovaries (notorious for playing a major role in TE silencing) of parental species and their F1 and backcrossed (BC) hybrids. We find that 15.2% and 10.6% of the expressed TEs are deregulated in F1 and BC1 ovaries, respectively, with a bias toward overexpression in both cases. Although differences between parental piRNA (Piwi-interacting RNA) populations explain only partially these results, we demonstrate that piRNA pathway proteins have divergent sequences and are differentially expressed between parental species. Thus, a functional divergence of the piRNA pathway between parental species, together with some differences between their piRNA pools, might be at the origin of hybrid instabilities and ultimately cause TE misregulation in ovaries. These analyses were complemented with the study of F1 testes, where TEs tend to be less expressed than in D. buzzatii. This can be explained by an increase in piRNA production, which probably acts as a defence mechanism against TE instability in the male germline. Hence, we describe a differential impact of interspecific hybridization in testes and ovaries, which reveals that TE expression and regulation are sex-biased.

TEtools facilitates big data expression analysis of transposable elements and reveals an antagonism between their activity and that of piRNA genes.

Over recent decades, substantial efforts have been made to understand the interactions between host genomes and transposable elements (TEs). The impact of TEs on the regulation of host genes is well known, with TEs acting as platforms of regulatory sequences. Nevertheless, due to their repetitive nature it is considerably hard to integrate TE analysis into genome-wide studies. Here, we developed a specific tool for the analysis of TE expression: TEtools. This tool takes into account the TE sequence diversity of the genome, it can be applied to unannotated or unassembled genomes and is freely available under the GPL3 (https://github.com/l-modolo/TEtools). TEtools performs the mapping of RNA-seq data obtained from classical mRNAs or small RNAs onto a list of TE sequences and performs differential expression analyses with statistical relevance. Using this tool, we analyzed TE expression from five Drosophila wild-type strains. Our data show for the first time that the activity of TEs is strictly linked to the activity of the genes implicated in the piwi-interacting RNA biogenesis and therefore fits an arms race scenario between TE sequences and host control genes.

UrQt: an efficient software for the Unsupervised Quality trimming of NGS data.

BACKGROUND: Quality control is a necessary step of any Next Generation Sequencing analysis. Although customary, this step still requires manual interventions to empirically choose tuning parameters according to various quality statistics. Moreover, current quality control procedures that provide a "good quality" data set, are not optimal and discard many informative nucleotides. To address these drawbacks, we present a new quality control method, implemented in UrQt software, for Unsupervised Quality trimming of Next Generation Sequencing reads. RESULTS: Our trimming procedure relies on a well-defined probabilistic framework to detect the best segmentation between two segments of unreliable nucleotides, framing a segment of informative nucleotides. Our software only requires one user-friendly parameter to define the minimal quality threshold (phred score) to consider a nucleotide to be informative, which is independent of both the experiment and the quality of the data. This procedure is implemented in C++ in an efficient and parallelized software with a low memory footprint. We tested the performances of UrQt compared to the best-known trimming programs, on seven RNA and DNA sequencing experiments and demonstrated its optimality in the resulting tradeoff between the number of trimmed nucleotides and the quality objective. CONCLUSIONS: By finding the best segmentation to delimit a segment of good quality nucleotides, UrQt greatly increases the number of reads and of nucleotides that can be retained for a given quality objective. UrQt source files, binary executables for different operating systems and documentation are freely available (under the GPLv3) at the following address: https://lbbe.univ-lyon1.fr/-UrQt-.html .

De novo assembly and annotation of the Asian tiger mosquito (Aedes albopictus) repeatome with dnaPipeTE from raw genomic reads and comparative analysis with the yellow fever mosquito (Aedes aegypti).

Repetitive DNA, including transposable elements (TEs), is found throughout eukaryotic genomes. Annotating and assembling the "repeatome" during genome-wide analysis often poses a challenge. To address this problem, we present dnaPipeTE-a new bioinformatics pipeline that uses a sample of raw genomic reads. It produces precise estimates of repeated DNA content and TE consensus sequences, as well as the relative ages of TE families. We shows that dnaPipeTE performs well using very low coverage sequencing in different genomes, losing accuracy only with old TE families. We applied this pipeline to the genome of the Asian tiger mosquito Aedes albopictus, an invasive species of human health interest, for which the genome size is estimated to be over 1 Gbp. Using dnaPipeTE, we showed that this species harbors a large (50% of the genome) and potentially active repeatome with an overall TE class and order composition similar to that of Aedes aegypti, the yellow fever mosquito. However, intraorder dynamics show clear distinctions between the two species, with differences at the TE family level. Our pipeline's ability to manage the repeatome annotation problem will make it helpful for new or ongoing assembly projects, and our results will benefit future genomic studies of A. albopictus.

A new genome-wide method to track horizontally transferred sequences: application to Drosophila.

Because of methodological breakthroughs and the availability of an increasing amount of whole-genome sequence data, horizontal transfers (HTs) in eukaryotes have received much attention recently. Contrary to similar analyses in prokaryotes, most studies in eukaryotes usually investigate particular sequences corresponding to transposable elements (TEs), neglecting the other components of the genome. We present a new methodological framework for the genome-wide detection of all putative horizontally transferred sequences between two species that requires no prior knowledge of the transferred sequences. This method provides a broader picture of HTs in eukaryotes by fully exploiting complete-genome sequence data. In contrast to previous genome-wide approaches, we used a well-defined statistical framework to control for the number of false positives in the results, and we propose two new validation procedures to control for confounding factors. The first validation procedure relies on a comparative analysis with other species of the phylogeny to validate HTs for the nonrepeated sequences detected, whereas the second one built upon the study of the dynamics of the detected TEs. We applied our method to two closely related Drosophila species, Drosophila melanogaster and D. simulans, in which we discovered 10 new HTs in addition to all the HTs previously detected in different studies, which underscores our method's high sensitivity and specificity. Our results favor the hypothesis of multiple independent HTs of TEs while unraveling a small portion of the network of HTs in the Drosophila phylogeny.