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Results for “combinatorial indexing”

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PubMed2025

Transcript-guided targeted cell enrichment for scalable single-nucleus RNA sequencing.

Large-scale single-cell atlases have revealed many aging- and disease-associated cell types, yet these populations are often underrepresented in heterogeneous tissues, limiting detailed molecular analyses. To address this, we developed EnrichSci-a scalable, microfluidics-free platform that combines hybridization chain reaction RNA fluorescence in situ hybridization (FISH) with combinatorial indexing to profile single-nucleus transcriptomes of target cell types with full gene-body coverage. Applied to oligodendrocytes in the aging mouse brain, EnrichSci uncovered aging-associated molecular dynamics across distinct oligodendrocyte subtypes, revealing both shared and subtype-specific gene expression changes. Additionally, we identified aging-associated exon-level signatures missed by conventional gene-level analyses, highlighting post-transcriptional regulation as a critical dimension of cell-state dynamics in aging. By coupling transcript-guided enrichment with a scalable sequencing workflow, EnrichSci provides a versatile approach to decode dynamic regulatory landscapes in diverse cell types from complex tissues.

Animals↗

PubMed2026

Mapping convergent regulators of melanoma drug resistance by PerturbFate.

High-throughput genomic studies have uncovered associations between diverse genetic alterations and disease phenotypes. However, elucidating how perturbations in functionally disparate genes give rise to convergent cellular states remains challenging. Here we present PerturbFate, a high-throughput, cost-effective, combinatorial-indexing single-cell platform that enables systematic interrogation of massively parallel CRISPR interference1 perturbations across the full spectrum of gene regulation, from chromatin remodelling and nascent transcription to steady-state transcriptomic phenotypes. Using PerturbFate, we profiled more than 300,000 cultured melanoma cells to characterize multimodal phenotypic and gene regulatory responses to perturbations in more than 140 vemurafenib resistance-associated genes. We uncovered a shared dedifferentiated cell state marked by convergent cooperative transcription factor activities across diverse genetic perturbations. We further dissected phenotypic responses to perturbations in Mediator complex components, linking module-specific biochemical properties to convergent transcriptional activations. We identified common regulatory nodes that drive similar phenotypic outcomes across distinct genetic perturbations. We also delineated how perturbations in functionally unrelated genes reshape cell state. Thus, PerturbFate establishes a versatile platform for identifying key molecular regulators by anchoring multimodal regulatory dynamics to disease-relevant phenotypes.

Humans↗

PubMed2026

Diversity and evolution of chromatin regulatory states across eukaryotes.

Histone post-translational modifications (hPTMs) are key regulators of chromatin states, influencing gene expression, epigenetic memory and transposable element repression across eukaryotic genomes. While many hPTMs are evolutionarily conserved, the extent to which the chromatin states they define are similarly preserved remains unclear. Here we developed a combinatorial indexing chromatin immunoprecipitation followed by sequencing method to simultaneously profile specific hPTMs across diverse eukaryotic lineages, including amoebozoans, rhizarians, discobans and cryptomonads. Our analyses revealed highly conserved euchromatin states at active gene promoters and gene bodies. In contrast, we observed diverse configurations of repressive heterochromatin states associated with silenced genes and transposable elements, characterized by various combinations of hPTMs such as H3K9me3, H3K27me3 and/or different H3K79 methylations. These findings suggest that, while core hPTMs are ancient and broadly conserved, their functional readout has diversified throughout eukaryotic evolution, shaping lineage-specific chromatin landscapes.

Histones↗

PubMed2026

Comparative Effectiveness of Pharmacogenomics for Treatment of Depression.

PURPOSE/BACKGROUND: Pharmacogenomics (PGx), or the use of genetic information to assess drug-gene interactions, is an important step toward precision medicine. It is unclear if clinician use of PGx yields better outcomes for their patients. This study compared the effectiveness of combinatorial PGx-guided plus guideline-informed treatment (PGx+GIT) with guideline-informed treatment (GIT) alone to improve well-being in individuals with major depressive disorder. METHODS/PROCEDURES: Eligible participants (N=201) were randomized to PGx+GIT or GIT alone. PGx was measured with the proprietary GeneSight combinatorial test. PGx+GIT participant clinicians received test results within 2 business days to inform decisions about medication changes. Participants completed the World Health Organization Well-Being Index (WHO-5), Patient Health Questionnaire (PHQ-9), and PROMIS Profile physical functioning and social roles and activity domains every 2 weeks for 2 months and then every 2 months for the remaining 10 months. Monthly medication changes operationalized as necessary clinical adjustments were tracked with the medication recommendation tracking form. FINDINGS/RESULTS: Both groups improved average well-being over the 12-month study period (model-based change in WHO-5 per log (week) [95% CI]: 4.1 [3.3, 5.0] PGx+GIT and 4.8 [4.0, 5.5] GIT). PGx+GIT did not result in superior improvement in well-being (model-based difference [95% CI]: -0.6 [-1.8, 0.5], P =0.270), or any secondary outcomes. The effect of randomized treatment on well-being was not moderated by depression severity, number of previous failed medications for major depressive disorder, or presence of a comorbid condition. IMPLICATIONS/CONCLUSIONS: These data suggest PGx+GIT was not superior to GIT alone, possibly due to a ceiling effect of GIT, or PGx did not yield better results.

Humans↗

PubMed2026

A combinatorial construct library enables an expanded expression range of secreted therapeutic proteins by probiotic yeast.

Orally administered engineered probiotics, including Saccharomyces cerevisiae var. boulardii (Sb), are of emerging interest as protein therapeutic delivery platforms to treat gastrointestinal diseases. Tools to readily optimize protein output are required to optimize the therapeutic index of Sb-produced therapies. In this study, a 125-plex Sb secretion construct library was developed consisting of all possible combinations of five promoters, five secretion signals, and five terminators, which enabled a greater than 1800-fold range in Sb expression of a Gaussia luciferase (GLuc) reporter. Secretion signal and promoter identities had significant effects on secretion output. This library further enabled a 28-fold improvement of binding activity of Sb-secreted haPD-1, an established anti-tumor immunotherapeutic, and improved haPD-1 detection in mouse stool samples following oral gavage of Sb_haPD-1. Sb secretion trends of both GLuc and haPD-1 in vitro mirrored payload expression in vivo. This protein secretion library toolkit will serve as a valuable resource to rapidly optimize protein therapeutic output from engineered Sb.

Saccharomyces boulardii↗