Infectious, inflammatory and autoimmune conditions present differently in males and females. SARS-CoV-2 infection in naive males is associated with increased risk of death, whereas females are at increased risk of long COVID1, similar to observations in other infections2. Females respond more strongly to vaccines, and adverse reactions are more frequent3, like most autoimmune diseases4. Immunological sex differences stem from genetic, hormonal and behavioural factors5 but their relative importance is only partially understood6-8. In individuals assigned female sex at birth and undergoing gender-affirming testosterone therapy (trans men), hormone concentrations change markedly but the immunological consequences are poorly understood. Here we performed longitudinal systems-level analyses in 23 trans men and found that testosterone modulates a cross-regulated axis between type-I interferon and tumour necrosis factor. This is mediated by functional attenuation of type-I interferon responses in both plasmacytoid dendritic cells and monocytes. Conversely, testosterone potentiates monocyte responses leading to increased tumour necrosis factor, interleukin-6 and interleukin-15 production and downstream activation of nuclear factor kappa B-regulated genes and potentiation of interferon-γ responses, primarily in natural killer cells. These findings in trans men are corroborated by sex-divergent responses in public datasets and illustrate the dynamic regulation of human immunity by sex hormones, with implications for the health of individuals undergoing hormone therapy and our understanding of sex-divergent immune responses in cisgender individuals.

T cells differentiate into functionally distinct states upon antigen encounter. These states are delineated by different cell surface markers for murine and human T cells, which hamper cross-species translation of T cell properties. We aimed to identify surface markers that reflect the graded nature of CD8+ T cell differentiation and delineate functionally comparable states in mice and humans. CITEseq analyses revealed that graded expression of CX3CR1, encoding the chemokine receptor CX3CR1, correlated with the CD8+ T cell differentiation gradient. CX3CR1 expression distinguished human and murine CD8+ and CD4+ T cell states, as defined by migratory and functional properties. Graded CX3CR1 expression, refined with CD62L, accurately captured the high-dimensional T cell differentiation continuum. Furthermore, the CX3CR1 expression gradient delineated states with comparable properties in humans and mice in steady state and on longitudinally tracked virus-specific CD8+ T cells in both species. Thus, graded CX3CR1 expression provides a strategy to translate the behavior of distinct T cell differentiation states across species.

The transcriptional error rate can be significantly increased by the presence of DNA lesions that instruct mis-insertion during transcription; a process referred to as transcriptional mutagenesis (TM) that can result in altered protein function. Herein, we determined the effect of O6-methylguanine (O6-meG) on transcription and subsequent transactivation activity of p53 in human lung H1299 cells. Levels of TM and effects on transactivation were determined genome wide by RNA-seq. Results showed that 47% of all p53 transcripts contained an uridine misincorporation opposite the lesion at 6 h post transfection, which was decreased to 18% at 24 h. TM at these levels reduced DNA binding activity of p53 to 21% and 80% compared to wild type p53, respectively. Gene expression data were analysed to identify differentially expressed genes due to TM of p53. We show a temporal repression of transactivation of > 100 high confidence p53 target genes including regulators of the cell cycle, DNA damage response and apoptosis. In addition, TM repressed the transcriptional downregulation by p53 of several negative regulators of proliferation and differentiation. Our work demonstrates that TM, even when restricting its effect to an individual transcription factor, has the potential to alter gene expression programs and diversify cellular phenotypes.

The relative role of genetic adaptation and phenotypic plasticity is of fundamental importance in evolutionary ecology [M. J. West-Eberhard, Proc. Natl. Acad. Sci. U.S.A. 102 (suppl. 1), 6543-6549 (2005)]. European eels have a complex life cycle, including transitions between life stages across ecological conditions in the Sargasso Sea, where spawning occurs, and those in brackish and freshwater bodies from northern Europe to northern Africa. Whether continental eel populations consist of locally adapted and genetically distinct populations or comprise a single panmictic population has received conflicting support. Here we use whole-genome sequencing and show that European eels belong to one panmictic population. A complete lack of geographical genetic differentiation is demonstrated. We postulate that this is possible because the most critical life stages-spawning and embryonic development-take place under near-identical conditions in the Sargasso Sea. We further show that within-generation selection, which has recently been proposed as a mechanism for genetic adaptation in eels, can only marginally change allele frequencies between cohorts of eels from different geographic regions. Our results strongly indicate plasticity as the predominant mechanism for how eels respond to diverse environmental conditions during postlarval stages, ultimately solving a long-standing question for a classically enigmatic species.

Long-read genome sequencing (lrGS) is a promising method in genetic diagnostics. Here we investigate the potential of lrGS to detect a disease-associated chromosomal translocation between 17p13 and the 19 centromere. We constructed two sets of phased and non-phased de novo assemblies; (i) based on lrGS only and (ii) hybrid assemblies combining lrGS with optical mapping using lrGS reads with a median coverage of 34X. Variant calling detected both structural variants (SVs) and small variants and the accuracy of the small variant calling was compared with those called with short-read genome sequencing (srGS). The de novo and hybrid assemblies had high quality and contiguity with N50 of 62.85 Mb, enabling a near telomere to telomere assembly with less than a 100 contigs per haplotype. Notably, we successfully identified the centromeric breakpoint of the translocation. A concordance of 92% was observed when comparing small variant calling between srGS and lrGS. In summary, our findings underscore the remarkable potential of lrGS as a comprehensive and accurate solution for the analysis of SVs and small variants. Thus, lrGS could replace a large battery of genetic tests that were used for the diagnosis of a single symptomatic translocation carrier, highlighting the potential of lrGS in the realm of digital karyotyping.

Recent advancements in in situ gene expression technologies constitute a new and rapidly evolving field of transcriptomics. With the recent launch of the 10x Genomics Visium platform, such methods have started to become widely adopted. The experimental protocol is conducted on individual tissue sections collected from a larger tissue sample. The two-dimensional nature of this data requires multiple consecutive sections to be collected from the sample in order to construct a comprehensive three-dimensional map of the tissue. However, there is currently no software available that lets the user process the images, align stacked experiments, and finally visualize them together in 3D to create a holistic view of the tissue. We have developed an R package named STUtility that takes 10x Genomics Visium data as input and provides features to perform standardized data transformations, alignment of multiple tissue sections, regional annotation, and visualizations of the combined data in a 3D model framework. STUtility lets the user process, analyze and visualize multiple samples of spatially resolved RNA sequencing and image data from the 10x Genomics Visium platform. The package builds on the Seurat framework and uses familiar APIs and well-proven analysis methods. An introduction to the software package is available at https://ludvigla.github.io/STUtility_web_site/ .

Fast and accurate quality control is essential for studies involving next-generation sequencing data. Whilst numerous tools exist to quantify QC metrics, there is no common approach to flexibly integrate these across tools and large sample sets. Assessing analysis results across an entire project can be time consuming and error prone; batch effects and outlier samples can easily be missed in the early stages of analysis. We present MultiQC, a tool to create a single report visualising output from multiple tools across many samples, enabling global trends and biases to be quickly identified. MultiQC can plot data from many common bioinformatics tools and is built to allow easy extension and customization. MultiQC is available with an GNU GPLv3 license on GitHub, the Python Package Index and Bioconda. Documentation and example reports are available at http://multiqc.info phil.ewels@scilifelab.se.