To understand the health impact of long-duration spaceflight, one identical twin astronaut was monitored before, during, and after a 1-year mission onboard the International Space Station; his twin served as a genetically matched ground control. Longitudinal assessments identified spaceflight-specific changes, including decreased body mass, telomere elongation, genome instability, carotid artery distension and increased intima-media thickness, altered ocular structure, transcriptional and metabolic changes, DNA methylation changes in immune and oxidative stress–related pathways, gastrointestinal microbiota alterations, and some cognitive decline postflight. Although average telomere length, global gene expression, and microbiome changes returned to near preflight levels within 6 months after return to Earth, increased numbers of short telomeres were observed and expression of some genes was still disrupted. These multiomic, molecular, physiological, and behavioral datasets provide a valuable roadmap of the putative health risks for future human spaceflight.
Summary The transcription factor IRF4 regulates immunoglobulin class switch recombination and plasma cell differentiation. Its differing concentrations appear to regulate mutually antagonistic programs of B and plasma cell gene expression. We show IRF4 to be also required for generation of germinal center (GC) B cells. Its transient expression in vivo induced the expression of key GC genes including Bcl6 and Aicda. In contrast, sustained and higher concentrations of IRF4 promoted the generation of plasma cells while antagonizing the GC fate. IRF4 co-bound with the transcription factors PU.1 or BATF to Ets or AP-1 composite motifs, associated with genes involved in B cell activation and the GC response. At higher concentrations IRF4 binding shifted to interferon sequence response motifs; these enriched for genes involved in plasma cell differentiation. Our results support a model of “kinetic control” in which signaling induced dynamics of IRF4 in activated B cells control their cell fate outcomes.
The molecular crosstalk between the interkeukin-7 receptor (IL-7R) and pre-BCR in B lymphopoiesis has been enigmatic. We demonstrate that in pre-B cells, the IL-7R, but not the pre-BCR, was coupled to the phosphatidylinositol-3-OH kinase (PI(3)K)–Akt module, signaling by which prevents Rag expression. Attenuation of IL-7 signaling resulted in up-regulation of Foxo1 and Pax5, which co-activated many pre-B cell genes, including Rag1,2 and Blnk. Induction of the latter gene enabled pre-BCR signaling via the Syk-BLNK module and promoted immunoglobulin light chain rearrangement. BLNK signaling also antagonized Akt activation, thereby augmenting Foxo1 and Pax5 accumulation. This self-reinforcing molecular circuit appears to sense limiting concentrations of IL-7 and functions to control the expansion and differentiation of pre-B cells.
During B lymphopoiesis, Igk recombination requires pre-B cell receptor (pre-BCR) expression and escape from interleukin 7 receptor (IL-7R) signaling. By activating the transcription factor STAT5, IL-7R signaling maintains proliferation and represses Igk germline transcription by unknown mechanisms. We demonstrate that STAT5 tetramer bound the Igk intronic enhancer (Eκi), leading to recruitment of the histone methyltransferase Ezh2. Ezh2 marked H3K27me3 throughout Jκ to Cκ. In the absence of Ezh2, IL-7 failed to repress Igk germline transcription. H3K27me3 modifications were lost after termination of IL-7R–STAT5 signaling and E2A bound Eκi, resulting in acquisition of H3K4me1 and H4Ac. Genome-wide analyses revealed a STAT5 tetrameric binding motif associated with transcriptional repression. These data demonstrate how IL-7R signaling represses Igk germline transcription and provide a general model for STAT5-mediated epigenetic transcriptional repression.
Robust methods for identifying patterns of expression in genome-wide data are important for generating hypotheses regarding gene function. To this end, several analytic methods have been developed for detecting periodic patterns. We improve one such method, JTK_CYCLE, by explicitly calculating the null distribution such that it accounts for multiple hypothesis testing and by including non-sinusoidal reference waveforms. We term this method empirical JTK_CYCLE with asymmetry search, and we compare its performance to JTK_CYCLE with Bonferroni and Benjamini-Hochberg multiple hypothesis testing correction, as well as to five other methods: cyclohedron test, address reduction, stable persistence, ANOVA, and F24. We find that ANOVA, F24, and JTK_CYCLE consistently outperform the other three methods when data are limited and noisy; empirical JTK_CYCLE with asymmetry search gives the greatest sensitivity while controlling for the false discovery rate. Our analysis also provides insight into experimental design and we find that, for a fixed number of samples, better sensitivity and specificity are achieved with higher numbers of replicates than with higher sampling density. Application of the methods to detecting circadian rhythms in a metadataset of microarrays that quantify time-dependent gene expression in whole heads of Drosophila melanogaster reveals annotations that are enriched among genes with highly asymmetric waveforms. These include a wide range of oxidation reduction and metabolic genes, as well as genes with transcripts that have multiple splice forms.
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