SEARCH · PubMed Health

Results for “dual RNA-sequencing”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

4 recordsLinked to original sources

PubMed2025

Dual RNA isolation from blood: an optimized protocol for host and bacterial RNA purification for dual RNA-sequencing analysis in whole blood sepsis samples.

Dual RNA-sequencing (dual RNA-seq) holds significant promise for deciphering bacterial virulence mechanisms during systemic infections. However, its application in sepsis research is hindered by technical challenges, including a low bacterial burden in blood and limited sample volumes and RNA yield from vulnerable populations, such as neonates. We developed an optimized protocol [dual RNA isolation from blood (DRIB)] for simultaneous stabilization, isolation and purification of high-quality host leukocyte and bacterial RNA from low-volume whole blood samples (0.5 ml). This protocol is compatible with clinical sample collection workflows and high-throughput RNA sequencing. The feasibility of DRIB for dual RNA-seq was validated using a pilot cohort of clinical adult sepsis samples, enabling the investigation of host-bacterial gene expression during sepsis. The DRIB protocol yielded 2.10-6.91 µg of total RNA per clinical sample in our pilot cohort. Dual-species ribosomal RNA (rRNA) depletion and RNA-seq generated 16.6-24.8 million filtered reads per sample, with 63±7% of reads uniquely mapped to host or bacterial sequences. Host genes accounted for 51-68% (8.4-10.9 million) reads, while 0.5-6.7% (79,496-789,808 reads) mapped to bacterial genomes. Bioinformatic analysis revealed that both shared and individual transcriptional patterns were identified in host and bacterial responses, including pathways related to immune metabolism and metal-ion binding. Our optimized DRIB protocol and RNA-seq pipeline effectively captured both host and bacterial RNA transcription in clinical sepsis samples. Expanding this approach to larger cohorts and varying disease timepoints will provide crucial new insights into host-bacterial gene co-expression dynamics in sepsis progression and outcomes.

Humans↗

PubMed2025

CROPseq-multi: a universal solution for multiplexed perturbation in high-content pooled CRISPR screens.

Forward genetic screens seek to dissect complex biological systems by systematically perturbing genetic elements and observing the resulting phenotypes. While standard screening methodologies introduce individual perturbations, multiplexing perturbations improves the performance of single-target screens and enables combinatorial screens for the study of genetic interactions. Current tools for multiplexing perturbations are limited by technical challenges and do not offer compatibility across diverse screening methodologies, including enrichment, single-cell sequencing, and optical pooled screens. Here, we report the development of CROPseq-multi (CSM), a CROPseq1-inspired lentiviral system to multiplex Streptococcus pyogenes (Sp) Cas9-based perturbations with versatile readout compatibility and high performance for both perturbation and barcode identification. CSM has equivalent per-guide activity to CROPseq and low lentiviral recombination frequencies. Dual-guide CSM libraries are constructed in a single, facile molecular cloning step that facilitates the use of unique molecular identifiers. CSM is compatible with enrichment screening methodologies, single-cell RNA-sequencing readouts, and optical pooled screens. For optical pooled screens, an optimized and multiplexed in situ detection protocol improves barcode counts 10-fold (for mRNA detection), enables detection of recombination events, and reduces the number of sequencing cycles required for decoding by 3-fold relative to CROPseq. CROPseq-multi-v2 (CSMv2) adds compatibility for detection methods based on T7 RNA polymerase in vitro transcription2-5. CSM provides a single system for CRISPR screens that is compatible with individual and combinatorial perturbations, diverse SpCas9-based perturbation technologies, and multiple high-content, single-cell phenotypic readouts.

CRISPR Cas9↗

PubMed2025

Ovarian development is driven by early spatiotemporal priming of the coelomic epithelium.

Ovarian organogenesis requires the coordinated specification of supporting and steroidogenic cell lineages from multipotent coelomic epithelium (CE) progenitors. A longstanding question is whether the CE contains transcriptionally distinct, spatially organized progenitor subpopulations with predetermined lineage biases, or whether specification into supporting and steroidogenic lineages occurs only after delamination and integration into the bipotential gonad. The developmental origins of granulosa cells and the emergence of ovarian steroidogenic/stromal progenitors (SPs) also remain poorly defined. Here, we show that CE cells covering the fetal mouse ovary are transcriptionally heterogeneous and spatially organized into subdomains already primed toward supporting or steroidogenic fates. CE priming is dynamic, with transient coexistence of supporting- and steroidogenic-biased CE progenitors before resolving into a predominantly supporting-biased CE. Local delamination of these primed cells seeds intragonadal niches where pre-granulosa cells and SPs mirror the spatio-temporal arrangements of CE-primed progenitors. We further demonstrate a dual origin for the supporting lineage, with granulosa cells deriving from both the CE and supporting-like cells (SLCs). In parallel, we show that SPs arise from steroidogenic-primed CE cells, expand to represent 52% of ovarian somatic cells at birth, persist into adulthood and contribute to both theca and steroidogenic stromal cells. Together, these findings reveal transcriptionally and spatially distinct CE subpopulations that shape somatic lineage emergence with important implications for ovarian pathophysiology.

Ovarian development↗

PubMed2025

Developing a disease-specific accessible transcriptional signature as a biomarker for ataxia with oculomotor apraxia type 2.

BACKGROUND: Genetic ataxias are clinically heterogenous neurodegenerative conditions often involving rare or private mutations and it is often difficult to assign pathogenicity to rare gene variants solely based on DNA sequencing. An effective functional assay from an easy-to-obtain biospecimen would aid this assessment and be of high clinical value. SETX encodes a ubiquitous DNA/RNA helicase crucial for resolving R-loops and maintaining genome stability. Loss-of-function mutations cause a recessive disorder, Ataxia with Oculomotor Apraxia Type 2 (AOA2). METHODS: Here we utilize Weighted Gene Co-expression Network Analysis (WGCNA) from patient blood to construct an AOA2-specific transcriptomic signature as a biomarker to evaluate SETX variants in patients clinically suspected of having AOA2. RESULTS: WGCNA from peripheral blood RNA of 11 AOA2 patients from 7 families initially identified a single gene module that was modestly effective in distinguishing individuals with AOA2 from controls (sensitivity 73%, specificity 97%) and was able to robustly differentiate AOA2 patients from those with genetically distinct, yet phenotypically similar, neurological disorders (sensitivity 100%, specificity 100%). An independent derivation of the transcriptional biomarker identified a dual module model that was able to better distinguish individuals with AOA2 from controls (sensitivity 100%, specificity 97%). As validation, we examined a second cohort of 21 patients from 13 families and demonstrate that this dual module transcriptional biomarker could discriminate patients clinically suspected of AOA2 from controls (57%, 95%CI: 34%-78%). Overall, the transcriptional biomarker was able to separate AOA2 subjects (n = 32) from controls (n = 35) with 72% sensitivity and 97% specificity. Notably, this transcriptomic biomarker enabled verification of the first pathogenic SETX mutation found in a non-canonical transcript, expanding the spectrum of mutations that contribute to AOA2. CONCLUSIONS: Our study identified a transcriptional biomarker that was able to differentiate AOA2 from controls and from other related neurological disorders, consequently expanding the spectrum of known pathogenic mutations. This proof-of-concept study illustrates that transcriptional biomarkers may be used to validate variants of uncertain significance in known genetic diseases.

Humans↗