improving-crispr-cas9-screens-car-t-cells-refined-method-for-library

Improving CRISPR-Cas9 Screens in CAR T Cells: A Refined Method for Library Preparation

Chimeric antigen receptor (CAR) T cell therapies have demonstrated remarkable efficacy in several hematological malignancies, yet their success has not ...

Centro de Investigacion Biomedica en Red de Cancer (CIBERONC)

Cima Universidad de Navarra, IdiSNA

Cancer Center Clinica Universidad de Navarra (CCUN)

Universidad de Navarra

Single-cell RNA-Sequencing has the potential to provide deep biological insights by revealing complex regulatory interactions across diverse cell phenotypes at single-cell resolution. However, current single-cell gene regulatory network inference methods produce a single regulatory network per input dataset, limiting their capability to uncover complex regulatory relationships across related cell phenotypes. We present SimiC, a single-cell gene regulatory inference framework that overcomes this limitation by jointly inferring distinct, but related, gene regulatory dynamics per phenotype. We show that SimiC uncovers key regulatory dynamics missed by previously proposed methods across a range of systems, both model and non-model alike. In particular, SimiC was able to uncover CAR T cell dynamics after tumor recognition and key regulatory patterns on a regenerating liver, and was able to implicate glial cells in the generation of distinct behavioral states in honeybees. SimiC hence establishes a new approach to quantitating regulatory architectures between distinct cellular phenotypes, with far-reaching implications for systems biology.

SimiC enables the inference of complex gene regulatory dynamics across cell phenotypes.

Towards scalable genomic data access.

For the last two decades, the amount of genomic data produced by scientific and medical applications has been growing at a rapid pace. To enable software solutions that analyze, process, and transmit these data in an efficient and interoperable way, ISO and IEC released the first version of the compression standard MPEG-G in 2019. However, non-proprietary implementations of the standard are not openly available so far, limiting fair scientific assessment of the standard and, therefore, hindering its broad adoption. In this paper, we present Genie, to the best of our knowledge the first open-source encoder that compresses genomic data according to the MPEG-G standard. We demonstrate that Genie reaches state-of-the-art compression ratios while offering interoperability with any other standard-compliant decoder independent from its manufacturer. Finally, the ISO/IEC ecosystem ensures the long-term sustainability and decodability of the compressed data through the ISO/IEC-supported reference decoder.

Genie: the first open-source ISO/IEC encoder for genomic data.

While myelodysplastic syndromes with del(5q) (del(5q) MDS) comprises a well-defined hematological subgroup, the molecular basis underlying its origin remains unknown. Using single cell RNA-seq (scRNA-seq) on CD34 progenitors from del(5q) MDS patients, we have identified cells harboring the deletion, characterizing the transcriptional impact of this genetic insult on disease pathogenesis and treatment response. Interestingly, both del(5q) and non-del(5q) cells present similar transcriptional lesions, indicating that all cells, and not only those harboring the deletion, may contribute to aberrant hematopoietic differentiation. However, gene regulatory network (GRN) analyses reveal a group of regulons showing aberrant activity that could trigger altered hematopoiesis exclusively in del(5q) cells, pointing to a more prominent role of these cells in disease phenotype. In del(5q) MDS patients achieving hematological response upon lenalidomide treatment, the drug reverts several transcriptional alterations in both del(5q) and non-del(5q) cells, but other lesions remain, which may be responsible for potential future relapses. Moreover, lack of hematological response is associated with the inability of lenalidomide to reverse transcriptional alterations. Collectively, this study reveals transcriptional alterations that could contribute to the pathogenesis and treatment response of del(5q) MDS.

Single-cell transcriptional profile of CD34+ hematopoietic progenitor cells from del(5q) myelodysplastic syndromes and impact of lenalidomide.

Long non-coding RNAs (lncRNAs) play fundamental roles in cellular processes and pathologies, regulating gene expression at multiple levels. Despite being highly cell type-specific, their study at single-cell (sc) level is challenging due to their less accurate annotation and low expression compared to protein-coding genes. Here, we systematically benchmark different preprocessing methods and develop a computational framework, named ELATUS, based on the combination of the pseudoaligner Kallisto with selective functional filtering. ELATUS enhances the detection of functional lncRNAs from scRNA-seq data, detecting their expression with higher concordance than standard methods with the ATAC-seq profiles in single-cell multiome data. Interestingly, the better results of ELATUS are due to its advanced performance with an inaccurate reference annotation such as that of lncRNAs. We independently confirm the expression patterns of cell type-specific lncRNAs exclusively detected with ELATUS and unveil biologically important lncRNAs, such as AL121895.1, a previously undocumented cis-repressor lncRNA, whose role in breast cancer progression is unnoticed by traditional methodologies. Our results emphasize the necessity for an alternative scRNA-seq workflow tailored to lncRNAs that sheds light on the multifaceted roles of lncRNAs.

Article	Year
SimiC enables the inference of complex gene regulatory dynamics across cell phenotypes. Communications biology\| PubMed ID: 35414121	2022
Towards scalable genomic data access. Nature computational science\| PubMed ID: 38217235	2021
Genie: the first open-source ISO/IEC encoder for genomic data. Communications biology\| PubMed ID: 38724695	2024
Single-cell transcriptional profile of CD34+ hematopoietic progenitor cells from del(5q) myelodysplastic syndromes and impact of lenalidomide. Nature communications\| PubMed ID: 38902243	2024
Uncovering functional lncRNAs by scRNA-seq with ELATUS. Nature communications\| PubMed ID: 39521797	2024
Author Correction: Uncovering functional lncRNAs by scRNA-seq with ELATUS. Nature communications\| PubMed ID: 39774948	2025

Mikel Hernaez

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