Novel CIC variants identified in individuals with neurodevelopmental phenotypes.

Heterozygous pathogenic variants in CIC, which encodes a transcriptional repressor, have been identified in individuals with neurodevelopmental phenotypes. To date, 11 CIC variants have been associated with the CIC-related neurodevelopmental syndrome. Here, we describe three novel and one previously reported CIC variants in four individuals with neurodevelopmental delay. Notably, we report for the first time a de novo frameshift variant specific to the long isoform of CIC (CIC-L, NM_001304815.1:c.1100dup, p.Pro368AlafsTer16) in an individual with speech delay, intellectual disability, and autism spectrum disorder. Our investigation into the function of CIC-L reveals that partial loss of CIC-L leads to transcriptional derepression of CIC target genes. We also describe a missense variant (NM_015125.3:c.683G>A, p.Arg228Gln) in an individual with a history of speech delay and relapsed pre-B acute lymphoblastic leukemia. Functional studies of this variant suggest a partial loss of CIC transcriptional repressor activity. Our study expands the list of CIC pathogenic variants and contributes to the accumulating evidence that CIC haploinsufficiency or partial loss of function is a pathogenic mechanism causing neurodevelopmental phenotypes.

CRISPR-CLEAR: Nucleotide-Resolution Mapping of Regulatory Elements via Allelic Readout of Tiled Base Editing.

CRISPR tiling screens have advanced the identification and characterization of regulatory sequences but are limited by low resolution arising from the indirect readout of editing via guide RNA sequencing. This study introduces CRISPR-CLEAR, an end-to-end experimental assay and computational pipeline, which leverages targeted sequencing of CRISPR-introduced alleles at the endogenous target locus following dense base-editing mutagenesis. This approach enables the dissection of regulatory elements at nucleotide resolution, facilitating a direct assessment of genotype-phenotype effects.

Alzheimer's disease associated isoforms of human CD33 distinctively modulate microglial cell responses in 5XFAD mice.

Microglia play diverse pathophysiological roles in Alzheimer's disease (AD), with genetic susceptibility factors skewing microglial cell function to influence AD risk. CD33 is an immunomodulatory receptor associated with AD susceptibility through a single nucleotide polymorphism that modulates mRNA splicing, skewing protein expression from a long protein isoform (CD33M) to a short isoform (CD33m). Understanding how human CD33 isoforms differentially impact microglial cell function in vivo has been challenging due to functional divergence of CD33 between mice and humans. We address this challenge by studying transgenic mice expressing either of the human CD33 isoforms crossed with the 5XFAD mouse model of amyloidosis and find that human CD33 isoforms have opposing effects on the response of microglia to amyloid-ß (Aß) deposition. Mice expressing CD33M have increased Aß levels, more diffuse plaques, fewer disease-associated microglia, and more dystrophic neurites compared to 5XFAD control mice. Conversely, CD33m promotes plaque compaction and microglia-plaque contacts, and minimizes neuritic plaque pathology, highlighting an AD protective role for this isoform. Protective phenotypes driven by CD33m are detected at an earlier timepoint compared to the more aggressive pathology in CD33M mice that appears at a later timepoint, suggesting that CD33m has a more prominent impact on microglia cell function at earlier stages of disease progression. In addition to divergent roles in modulating phagocytosis, scRNAseq and proteomics analyses demonstrate that CD33m+ microglia upregulate nestin, an intermediate filament involved in cell migration, at plaque contact sites. Overall, our work provides new functional insights into how CD33, as a top genetic susceptibility factor for AD, modulates microglial cell function.

DNA-Diffusion: Leveraging Generative Models for Controlling Chromatin Accessibility and Gene Expression via Synthetic Regulatory Elements.

The challenge of systematically modifying and optimizing regulatory elements for precise gene expression control is central to modern genomics and synthetic biology. Advancements in generative AI have paved the way for designing synthetic sequences with the aim of safely and accurately modulating gene expression. We leverage diffusion models to design context-specific DNA regulatory sequences, which hold significant potential toward enabling novel therapeutic applications requiring precise modulation of gene expression. Our framework uses a cell type-specific diffusion model to generate synthetic 200 bp regulatory elements based on chromatin accessibility across different cell types. We evaluate the generated sequences based on key metrics to ensure they retain properties of endogenous sequences: transcription factor binding site composition, potential for cell type-specific chromatin accessibility, and capacity for sequences generated by DNA diffusion to activate gene expression in different cell contexts using state-of-the-art prediction models. Our results demonstrate the ability to robustly generate DNA sequences with cell type-specific regulatory potential. DNA-Diffusion paves the way for revolutionizing a regulatory modulation approach to mammalian synthetic biology and precision gene therapy.

Benchmarking computational methods to identify spatially variable genes and peaks.

Spatially resolved transcriptomics offers unprecedented insight by enabling the profiling of gene expression within the intact spatial context of cells, effectively adding a new and essential dimension to data interpretation. To efficiently detect spatial structure of interest, an essential step in analyzing such data involves identifying spatially variable genes. Despite researchers having developed several computational methods to accomplish this task, the lack of a comprehensive benchmark evaluating their performance remains a considerable gap in the field. Here, we present a systematic evaluation of 14 methods using 60 simulated datasets generated by four different simulation strategies, 12 real-world transcriptomics, and three spatial ATAC-seq datasets. We find that spatialDE2 consistently outperforms the other benchmarked methods, and Moran's I achieves competitive performance in different experimental settings. Moreover, our results reveal that more specialized algorithms are needed to identify spatially variable peaks.

A Versatile Strategy for Genetic Manipulation of Cajal-Retzius Cells in the Adult Mouse Hippocampus.

Cajal-Retzius (CR) cells are transient neurons with long-lasting effects on the architecture and circuitry of the neocortex and hippocampus. Contrary to the prevailing assumption that CR cells completely disappear in rodents shortly after birth, a substantial portion of these cells persist in the hippocampus throughout adulthood. The role of these surviving CR cells in the adult hippocampus is largely unknown, partly because of the paucity of suitable tools to dissect their functions in the adult versus the embryonic brain. Here, we show that genetic crosses of the ΔNp73-Cre mouse line, widely used to target CR cells, to reporter mice induce reporter expression not only in CR cells, but also progressively in postnatal dentate gyrus granule neurons. Such a lack of specificity may confound studies of CR cell function in the adult hippocampus. To overcome this, we devise a method that not only leverages the temporary CR cell-targeting specificity of the ΔNp73-Cre mice before the first postnatal week, but also capitalizes on the simplicity and effectiveness of freehand neonatal intracerebroventricular injection of adeno-associated virus. We achieve robust Cre-mediated recombination that remains largely restricted to hippocampal CR cells from early postnatal age to adulthood. We further demonstrate the utility of this method to manipulate neuronal activity of CR cells in the adult hippocampus. This versatile and scalable strategy will facilitate experiments of CR cell-specific gene knockdown and/or overexpression, lineage tracing, and neural activity modulation in the postnatal and adult brain.

Reconstruction of full-length LINE-1 progenitors from ancestral genomes.

Sequences derived from the Long INterspersed Element-1 (L1) family of retrotransposons occupy at least 17% of the human genome, with 67 distinct subfamilies representing successive waves of expansion and extinction in mammalian lineages. L1s contribute extensively to gene regulation, but their molecular history is difficult to trace, because most are present only as truncated and highly mutated fossils. Consequently, L1 entries in current databases of repeat sequences are composed mainly of short diagnostic subsequences, rather than full functional progenitor sequences for each subfamily. Here, we have coupled 2 levels of sequence reconstruction (at the level of whole genomes and L1 subfamilies) to reconstruct progenitor sequences for all human L1 subfamilies that are more functionally and phylogenetically plausible than existing models. Most of the reconstructed sequences are at or near the canonical length of L1s and encode uninterrupted ORFs with expected protein domains. We also show that the presence or absence of binding sites for KRAB-C2H2 Zinc Finger Proteins, even in ancient-reconstructed progenitor L1s, mirrors binding observed in human ChIP-exo experiments, thus extending the arms race and domestication model. RepeatMasker searches of the modern human genome suggest that the new models may be able to assign subfamily resolution identities to previously ambiguous L1 instances. The reconstructed L1 sequences will be useful for genome annotation and functional study of both L1 evolution and L1 contributions to host regulatory networks.

Global properties of regulatory sequences are predicted by transcription factor recognition mechanisms.

BACKGROUND: Mammalian genomes contain millions of putative regulatory sequences, which are delineated by binding of multiple transcription factors. The degree to which spacing and orientation constraints among transcription factor binding sites contribute to the recognition and identity of regulatory sequence is an unresolved but important question that impacts our understanding of genome function and evolution. Global mechanisms that underlie phenomena including the size of regulatory sequences, their uniqueness, and their evolutionary turnover remain poorly described. RESULTS: Here, we ask whether models incorporating different degrees of spacing and orientation constraints among transcription factor binding sites are broadly consistent with several global properties of regulatory sequence. These properties include length, sequence diversity, turnover rate, and dominance of specific TFs in regulatory site identity and cell type specification. Models with and without spacing and orientation constraints are generally consistent with all observed properties of regulatory sequence, and with regulatory sequences being fundamentally small (~ 1 nucleosome). Uniqueness of regulatory regions and their rapid evolutionary turnover are expected under all models examined. An intriguing issue we identify is that the complexity of eukaryotic regulatory sites must scale with the number of active transcription factors, in order to accomplish observed specificity. CONCLUSIONS: Models of transcription factor binding with or without spacing and orientation constraints predict that regulatory sequences should be fundamentally short, unique, and turn over rapidly. We posit that the existence of master regulators may be, in part, a consequence of evolutionary pressure to limit the complexity and increase evolvability of regulatory sites.