Annagiulia Bonizzato

Cell states in hematopoiesis are controlled by master regulators and by complex circuits of a growing family of RNA species impacting cell phenotype maintenance and plasticity. Circular RNAs (circRNAs) are rapidly gaining the status of particularly stable transcriptome members with distinctive qualities. RNA-seq identified thousands of circRNAs with developmental stage- and tissue-specific expression corroborating earlier suggestions that circular isoforms are a natural feature of the cell expression program. CircRNAs are abundantly expressed also in the hematopoietic compartment. There are a number of studies on circRNAs in blood cells, a specific overview is however lacking. In this review we first present current insight in circRNA biogenesis discussing the relevance for hematopoiesis of the highly interleaved processes of splicing and circRNA biogenesis. Regarding molecular functions circRNAs modulate host gene expression, but also compete for binding of microRNAs, RNA-binding proteins or translation initiation and participate in regulatory circuits. We examine circRNA expression in the hematopoietic compartment and in hematologic malignancies and review the recent breakthrough study that identified pathogenic circRNAs derived from leukemia fusion genes. CircRNA high and regulated expression in blood cell types indicate that further studies are warranted to inform the position of these regulators in normal and malignant hematopoiesis.

Circular RNAs (circRNAs) are abundantly expressed in the haematopoietic compartment, but knowledge on their diversity among blood cell types is still limited. Nevertheless, emerging data indicate an array of circRNA functions exerted through interactions with other RNAs and proteins, by translation into peptides, and circRNA involvement as regulatory molecules in many biological processes and cancer mechanisms. Interestingly, the role of specific circRNAs in leukemogenesis has been disclosed by a few studies, mostly in acute myeloid leukemia. In this study, circRNA expression in B-cells, T-cells and monocytes of healthy subjects is described, including putative new circRNA genes. Expression comparison considered 6,228 circRNAs and highlighted cell population-specific expression and exon usage patterns. Differential expression has been confirmed by qRT-PCR for circRNAs specific of B-cells (circPAX5, circAFF3, circIL4R, and circSETBP1) or T-cells (circIKZF1, circTNIK, circTXK, and circFBXW7), and for circRNAs from intronic (circBCL2) and intergenic regions that were overexpressed in lymphocytes. Starting from this resource of circRNA expression in mature blood cell populations, targeted examination identified striking and generalized upregulated expression of circPAX5, circPVT1 and circHIPK3 in pediatric B-precursor acute lymphoblastic leukemia, and disclosed circRNAs with variable expression across cytogenetic subtypes.

Circular RNAs (circRNAs) are generated by backsplicing of immature RNA forming covalently closed loops of intron/exon RNA molecules. Pervasiveness, evolutionary conservation, massive and regulated expression, and posttranscriptional regulatory roles of circRNAs in eukaryotes have been appreciated and described only recently. Moreover, being easily detectable disease markers, circRNAs undoubtedly represent a molecular class with high bearing on molecular pathobiology. CircRNAs can be detected from RNAseq data using appropriate computational methods to identify the sequence reads spanning backsplice junctions that do not colinearly map to the reference genome. To this end, several programs were developed and critical assessment of various strategies and tools suggested the combination of at least two methods as good practice to guarantee robust circRNA detection. Here,we present CirComPara (http://github.com/egaffo/CirComPara), an automated bioinformatics pipeline, to detect, quantify and annotate circRNAs from RNAseq data using in parallel four different methods for backsplice identification. CirComPara also provides quantification of linear RNAs and gene expression, ultimately comparing and correlating circRNA and gene/transcript expression level. We applied our method to RNAseqdata of monocyte and macrophage samples in relation to haploinsufficiency of the RNAbinding splicing factor Quaking (QKI). The biological relevance of the results, in terms of number, types and variations of circRNAs expressed, illustrates CirComPara potential to enlarge the knowledge of the transcriptome, adding details on the circRNAome, and facilitating further computational and experimental studies.

Cell states in haematopoiesis are controlled by complex circuits, involving master regulators transcription factors and a growing family of RNA species, shaping cell phenotype, its maintenance and plasticity. Amongst RNA species, circular RNAs (circRNAs) are rapidly gaining the status of particularly stable transcriptome members with distinctive qualities. Regarding molecular functions, circRNAs modulate host gene expression, compete for binding of microRNAs, RNA-binding proteins and translation initiation, and participate in regulatory circuits. RNA-seq studies identified thousands of circRNAs with developmental stage- and tissue-specific expression corroborating earlier suggestions that circular isoforms are a natural feature of the cell expression program. circRNAs are abundantly expressed and highly regulated also in the haematopoietic compartment, as described by recent and preliminary studies on circRNAs in blood cells.
\n
\nIn my PhD project we focused on the development of a bioinformatics pipeline to detect, quantify and characterize circRNAs from RNA-seq data, by combining both publicly available tools and custom scripts. Aiming to increase the discovery power of the pipeline as well as results robustness, we combined four programs for circRNA detection in parallel.
\n
\nThe pipeline was tested on a publicly available dataset of haematopoietic lineage cells such as Haematopoietic Stem Cells, Lymphoid progenitors, Myeloid Progenitors and Megakaryocyte–Erythroblast Progenitors. This pilot analysis allowed to retrieve a great number of circRNAs despite features of the data that were not optimal for circRNA detection. Major results from the pilot study were the identification of distinct sets of circRNAs specifically expressed in different cell types, and the feasibility and convenience of circRNA detection in published datasets to complement the original studies.
\n
\nIn parallel, we studied circRNA and linear RNA expression in differentiated cells of the haematopoietic compartment, specifically B cells T cells and Monocytes. We produced RNA-seq data of 12 samples, obtained by cell sorting from peripheral blood of healthy donors and using ribosomal RNA depletion for the library construction.
\nOut of the over 115000 detected backsplices supported by at least two reads, we selected putative circRNAs found by at least two methods, gaining also indirect support that most of them are truly circular forms thanks to independent evidence. This subset consists of 26211 circRNAs expressed by 7307 different genes, with 38.6% of genes expressing one circRNA each, and 40.7% of genes producing from 2 to 5 different circular isoforms and the remaining genes expressing a higher number of circRNAs. The large majority of circRNAs are exonic, 11.5% have backsplice ends falling into intronic regions and only a few (2.5%) probably derive from genomic regions annotated as intergenic. Comparison with the analysis of the linear transcriptome pointed out that the expression levels of linear and circular RNAs expressed from the same gene have only a very slight tendency toward positive correlation, with most of the pairs showing scarce or even negative correlations, suggesting specific regulatory mechanisms underlying the expression of circRNAs.
\n
\nThe comparison between B cells T cells and Monocytes indicated groups of circRNAs expressed in all the cell types and specific of each cell type. Unsupervised analyses of expression profiles showed for the first time specificities of circRNA expression associated to different blood cells. B cells and T cells circRNAomes are similar from quantitative and qualitative points of view, whereas Monocytes express a lower number of circRNAs and have a more specific circRNAome. Indeed, differential expression tests outlined sets of circRNAs with significantly variable expression in B cells compared to Monocytes (2589), B cells compared to T cells (168) and Monocytes compared to T cells (977). Differentially expressed circRNAs are associated to genes enriched in protein products involved in key blood processes and pathways. Finally, we focused on 74 circRNAs upregulated in B cells compared to both Monocytes and T cells, 40 upregulated in T cells and 159 upregulated in Monocytes, for a total of 273 circRNAs with differential expression and cell specificity. Additional criteria for circRNA prioritization selected circRNAs associated to genes with key functions in haematopoiesis, or altered/deregulated in haematologic malignancies. Prioritized circRNAs will undergo experimental validations. The sequence analyses for in silico prediction of possible circRNAs functions, as presence of multiple miRNA binding sites, protein binding motifs, or open reading frames, will be the starting point for experimental studies to better elucidate the functions of more promising circRNAs.
\n
\nIn conclusion we performed the first study of circRNAs in normal B cells T cells and Monocytes grounding on several biological replicates of each cell type being informative on circRNA differential expression. The integration of circular and linear RNA expression profiles with gene annotations and functions, in conjunction with differential expression data, produced new and original results. We showed that taking into account circRNA expression might add definition to the representation of transcriptome variations in normal haematopoiesis, posing the basis to better comprehend the role of circRNAs in the regulatory circuits of blood cells differentiation, which is a prerequisite for transferring this knowledge to research on haematological malignancies.