Search bioRxiv⌕ Search

Biology subjects

Papavasileiou, S.

Publications and source records attributed to Papavasileiou, S..

3 recordsLinked to original sources

Integrated analysis of leukemic mutations and transcriptomes at the single-cell level

Single-cell RNA-sequencing-based characterization of cells that belong to the neoplastic clone is a major challenge in hematologic neoplasms, where malignant and normal cells coexist. Confident molecular profiling requires simultaneous analysis of gene expression and genetic mutations in individual cells, an ability that is not supported by the standard 10X Genomics workflow. Here, we systematically evaluated the potential and limitations of repurposing amplified cDNA generated during the 10X Genomics 3' workflow for post-hoc genotyping of individual cells. We first established a mixed leukemic cell line system comprising one cell line with KIT point mutations and another with the BCR::ABL1 fusion gene. Targeted long-read PacBio sequencing enabled post-hoc assignment of mutation data to transcriptionally profiled cells, but recovery differed between targets. Consistent with ambient RNA in microfluidics-based single-cell workflows, mutation-associated transcripts were detected in cells not expected to carry the corresponding mutations, illustrating how transcript recovery complicates cell-level genotype assignment. Target-specific thresholds mitigated this source of misclassification. In primary chronic myeloid leukemia samples, the post-hoc approach detected BCR::ABL1-positive cells at diagnosis, but not during imatinib treatment. Together, we present a framework for adding mutation status to cells already profiled using the 10X Genomics workflow and highlight broader considerations for transcript-based single-cell genotyping.

cancer biology↗

Single-cell omics-based characterization of human basophils reveals two transcriptionally distinct populations

BackgroundBasophils are implicated in various diseases including allergies, but a comprehensive characterization of human basophils has yet to be performed at the single-cell level. ObjectiveWe aimed to generate a single-cell omics-based resource of circulating human basophils, to be made accessible to the research community. We also sought to investigate basophil heterogeneity at the transcriptional and surface epitope levels. MethodsCirculating basophils were analyzed using short- and long-read single-cell RNA-sequencing in combination with large-scale immunoprofiling of more than 100 cell surface markers. ResultsWe used a cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) based cell barcoding system to accurately track side scatterlow lineage- CCR3+ Fc{varepsilon}RI+ basophils through the single-cell omics analysis. The approach allowed for accurate transcriptional profiling of basophils among low-density peripheral blood leukocytes. The generation of an additional dataset with only basophils revealed two transcriptionally distinct populations. Single-cell transcriptomic analysis of samples from additional donors was performed and coupled with a large-scale immunoprofiling screen, producing a third CITE-seq dataset containing basophils. The analysis verified the existence of the two transcriptionally distinct populations and revealed that these populations have similar immunophenotypes with regard to the investigated surface markers. Long-read single-cell RNA-sequencing analysis provided further insights into the gene expression dynamics of the circulating basophils and confirmed the transcriptionally defined basophil states. ConclusionsThe single-cell omics analysis revealed two transcriptionally distinct basophil populations. Our single-cell omics resource constitutes a reference for charting human basophils at the cellular and molecular levels in health and disease. Capsule summaryShort- and long-read single-cell RNA-sequencing coupled with large-scale immunoprofiling characterize human basophils in peripheral blood and reveal two transcriptionally distinct populations.

immunology↗

Large-scale identification of RBP-RNA interactions by RAPseq refines essentials of post-transcriptional gene regulation

Over the past decade, thousands of putative human RNA binding proteins (RBPs) have been identified and increased the demand for specifying RNA binding capacities. Here, we developed RNA affinity purification followed by sequencing (RAPseq) that enables in vitro large-scale profiling of RBP binding to native RNAs. First, by employing RAPseq, we found that vertebrate HURs recognize a conserved RNA binding motif and bind predominantly to introns in zebrafish compared to 3UTRs in human RNAs. Second, our dual RBP assays (co-RAPseq) uncovered cooperative RNA binding of HUR and PTBP1 within an optimal distance of 27 nucleotides. Third, we developed T7-RAPseq to discern m6A-dependent and - independent RNA binding sites of YTHDF1. Fourth, RAPseq of 26 novel non-canonical RBPs revealed specialized moonlighting interactions. Last, five pathological IGF2BP family variants exhibited different RNA binding patterns. Overall, our simple, scalable and versatile method enables to fast-forward RBP-related questions. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/467743v1_ufig1.gif" ALT="Figure 1"> View larger version (106K): org.highwire.dtl.DTLVardef@1f77ce0org.highwire.dtl.DTLVardef@12778fcorg.highwire.dtl.DTLVardef@77ff8corg.highwire.dtl.DTLVardef@2a7f24_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIRAPseq reveals in vitro-derived RBP-RNA interactomes C_LIO_LIthe vertebrate-conserved HUR binding motif adapted to species-unique RNA features C_LIO_LIco-RAPseq and T7-RAPseq uncover binding cooperativity and modification dependencies C_LIO_LInon-canonical RBPs have specialized RNA interactomes C_LI

genomics↗