Single-cell RNA sequencing (scRNA-seq) has become an empowering technology to profile the transcriptomes of individual cells on a large scale. Early analyses of differential expression have aimed at identifying differences between subpopulations to identify subpopulation markers. More generally, such methods compare expression levels across sets of cells, thus leading to cross-condition analyses. Given the emergence of replicated multi-condition scRNA-seq datasets, an area of increasing focus is making sample-level inferences, termed here as differential state analysis; however, it is not clear which statistical framework best handles this situation. Here, we surveyed methods to perform cross-condition differential state analyses, including cell-level mixed models and methods based on aggregated pseudobulk data. To evaluate method performance, we developed a flexible simulation that mimics multi-sample scRNA-seq data. We analyzed scRNA-seq data from mouse cortex cells to uncover subpopulation-specific responses to lipopolysaccharide treatment, and provide robust tools for multi-condition analysis within the muscat R package.

Reproducibility in research can be compromised by both biological and technical variation, but most of the focus is on removing the latter. Here we investigate the effects of biological variation in HeLa cell lines using a systems-wide approach. We determine the degree of molecular and phenotypic variability across 14 stock HeLa samples from 13 international laboratories. We cultured cells in uniform conditions and profiled genome-wide copy numbers, mRNAs, proteins and protein turnover rates in each cell line. We discovered substantial heterogeneity between HeLa variants, especially between lines of the CCL2 and Kyoto varieties, and observed progressive divergence within a specific cell line over 50 successive passages. Genomic variability has a complex, nonlinear effect on transcriptome, proteome and protein turnover profiles, and proteotype patterns explain the varying phenotypic response of different cell lines to Salmonella infection. These findings have implications for the interpretation and reproducibility of research results obtained from human cultured cells.

IntroductionProtective immunity against pathogens relies on the production of high-affinity antibodies by long-lived plasma cells (PCs). Moreover, the ability to respond faster and with more potent antibodies to subsequent encounters with the same infectious agent depends on the generation of long-lived memory B cells. Both, high-affinity memory B cells and PCs differentiate from antigenspecific B cells that are recruited into the GC reaction during T cell-dependent immune responses (1). In GCs, B cells undergo clonal expansion, a process during which they accumulate mutations at high frequency within the Ig heavy and light chain variable (V) region genes. The highly dynamic nature of the GC reaction is characterized by repeated cycles of cell division, Ig somatic mutation, and strict selection based on the ability of B cells to capture and present antigen to T follicular helper cells (2). These processes occur within distinct areas of the GC reached by B cells through migratory paths regulated by chemokine gradients (1). The molecular determinants enabling cyclic reentry of B cells into the proliferating and mutating compartment of centroblasts, preventing terminal differentiation and the ensuing exit from the GC, remain poorly characterized.

Doublets are prevalent in single-cell sequencing data and can lead to artifactual findings. A number of strategies have therefore been proposed to detect them. Building on the strengths of existing approaches, we developed scDblFinder, a fast, flexible and accurate Bioconductor-based doublet detection method. Here we present the method, justify its design choices, demonstrate its performance on both single-cell RNA and accessibility (ATAC) sequencing data, and provide some observations on doublet formation, detection, and enrichment analysis. Even in complex datasets, scDblFinder can accurately identify most heterotypic doublets, and was already found by an independent benchmark to outcompete alternatives.

Yin and yang 1 (YY1) is a well-known zinc-finger transcription factor with crucial roles in normal development and malignancy. YY1 acts both as a repressor and as an activator of gene expression. We have identified 23 individuals with de novo mutations or deletions of YY1 and phenotypic features that define a syndrome of cognitive impairment, behavioral alterations, intrauterine growth restriction, feeding problems, and various congenital malformations. Our combined clinical and molecular data define "YY1 syndrome" as a haploinsufficiency syndrome. Through immunoprecipitation of YY1-bound chromatin from affected individuals' cells with antibodies recognizing both ends of the protein, we show that YY1 deletions and missense mutations lead to a global loss of YY1 binding with a preferential retention at high-occupancy sites. Finally, we uncover a widespread loss of H3K27 acetylation in particular on the YY1-bound enhancers, underscoring a crucial role for YY1 in enhancer regulation. Collectively, these results define a clinical syndrome caused by haploinsufficiency of YY1 through dysregulation of key transcriptional regulators.

Down syndrome (DS) is mostly caused by a trisomy of the entire Chromosome 21 (Trisomy 21, T21). Here, we use SWATH mass spectrometry to quantify protein abundance and protein turnover in fibroblasts from a monozygotic twin pair discordant for T21, and to profile protein expression in 11 unrelated DS individuals and matched controls. The integration of the steadystate and turnover proteomic data indicates that protein-specific degradation of members of stoichiometric complexes is a major determinant of T21 gene dosage outcome, both within and between individuals. This effect is not apparent from genomic and transcriptomic data. The data also reveal that T21 results in extensive proteome remodeling, affecting proteins encoded by all chromosomes. Finally, we find broad, organelle-specific post-transcriptional effects such as significant downregulation of the mitochondrial proteome contributing to T21 hallmarks. Overall, we provide a valuable proteomic resource to understand the origin of DS phenotypic manifestations.

We undertook a functional dissection of chromatin remodeler BAZ1B in neural crest (NC) stem cells (NCSCs) from a uniquely informative cohort of typical and atypical patients harboring 7q11.23 copy number variants. Our results reveal a key contribution of BAZ1B to NCSC in vitro induction and migration, coupled with a crucial involvement in NC-specific transcriptional circuits and distal regulation. By intersecting our experimental data with new paleogenetic analyses comparing modern and archaic humans, we found a modern-specific enrichment for regulatory changes both in BAZ1B and its experimentally defined downstream targets, thereby providing the first empirical validation of the human self-domestication hypothesis and positioning BAZ1B as a master regulator of the modern human face. In so doing, we provide experimental evidence that the craniofacial and cognitive/behavioral phenotypes caused by alterations of the Williams-Beuren syndrome critical region can serve as a powerful entry point into the evolution of the modern human face and prosociality.

Cell reprogramming promises to make characterization of the impact of human genetic variation on health and disease experimentally tractable by enabling the bridging of genotypes to phenotypes in developmentally relevant human cell lineages. Here we apply this paradigm to two disorders caused by symmetrical copy number variations of 7q11.23, which display a striking combination of shared and symmetrically opposite phenotypes--Williams-Beuren syndrome and 7q-microduplication syndrome. Through analysis of transgene-free patient-derived induced pluripotent stem cells and their differentiated derivatives, we find that 7q11.23 dosage imbalance disrupts transcriptional circuits in disease-relevant pathways beginning in the pluripotent state. These alterations are then selectively amplified upon differentiation of the pluripotent cells into disease-relevant lineages. A considerable proportion of this transcriptional dysregulation is specifically caused by dosage imbalances in GTF2I, which encodes a key transcription factor at 7q11.23 that is associated with the LSD1 repressive chromatin complex and silences its dosage-sensitive targets.