Rainer Waldmann

In situ capturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and full-length sequence heterogeneity cannot be characterized at spatial resolution with current transcriptome profiling methods. To that end, we introduce spatial isoform transcriptomics (SiT), an explorative method for characterizing spatial isoform variation and sequence heterogeneity using long-read sequencing. We show in mouse brain how SiT can be used to profile isoform expression and sequence heterogeneity in different areas of the tissue. SiT reveals regional isoform switching of Plp1 gene between different layers of the olfactory bulb, and the use of external single-cell data allows the nomination of cell types expressing each isoform. Furthermore, SiT identifies differential isoform usage for several major genes implicated in brain function (Snap25, Bin1, Gnas) that are independently validated by in situ sequencing. SiT also provides for the first time an in-depth A-to-I RNA editing map of the adult mouse brain. Data exploration can be performed through an online resource (https://www.isomics.eu), where isoform expression and RNA editing can be visualized in a spatial context.

Background Wastewater surveillance has been proposed as an epidemiological tool to define the prevalence and evolution of the SARS-CoV-2 epidemics. However, most implemented SARS-CoV-2 wastewater surveillance projects were relying on qPCR measurement of virus titers and did not address the mutational spectrum of SARS-CoV-2 circulating in the population. Methods We have implemented a nanopore RNA sequencing monitoring system in the city of Nice (France, 550,000 inhabitants). Between October 2020 and March 2021, we monthly analyzed the SARS-CoV-2 variants in 113 wastewater samples collected in the main wastewater treatment plant and 20 neighborhoods. Findings We initially detected the lineages predominant in Europe at the end of 2020 (B.1.160, B.1.177, B.1.367, B.1.474, and B.1.221). In January, a localized emergence of a variant (Spike:A522S) of the B.1.1.7 lineage occurred in one neighborhood. It rapidly spread and became dominant all over the city. Other variants of concern (B.1.351, P.1) were also detected in some neighborhoods, but at low frequency. Comparison with individual clinical samples collected during the same week showed that wastewater sequencing correctly identified the same lineages as those found in COVID-19 patients. Interpretation Wastewater sequencing allowed to document the diversity of SARS-CoV-2 sequences within the different neighborhoods of the city of Nice. Our results illustrate how sequencing of sewage samples can be used to track pathogen sequence diversity in the current pandemics and in future infectious disease outbreaks.

In situ capturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and fulllength sequence heterogeneity cannot be characterized at spatial resolution with current transcriptome profiling methods. To that end, we introduce Spatial Isoform Transcriptomics (SiT), an explorative method for characterizing spatial isoform variation and sequence heterogeneity. We show in mouse brain how SIT can be used to profile isoform expression and sequence heterogeneity in different areas of the tissue. SiT reveals regional isoform switching of Plp1 gene between different layers of the olfactory bulb, and use of external single cell data allowed to nominate cell types expressing each isoform. Furthermore, SiT identifies differential isoform usage for several major genes implicated in brain function ( Snap25, Bin1, Gnas ) that we independently validated by in situ sequencing. SiT also provides for the first time an in-depth A-to-I RNA editing map of the adult mouse brain. Data exploration can be performed through an online resource ( https://www.isomics.eu ), where isoform expression and RNA editing can be visualized in a spatial context.

Droplet-based high throughput single cell sequencing techniques tremendously advanced our insight into cell-to-cell heterogeneity. However, those approaches only allow analysis of one extremity of the transcript after short read sequencing. In consequence, information on splicing and sequence heterogeneity is lost. To overcome this limitation, several approaches that use long-read sequencing were introduced recently. Yet, those techniques are limited by low sequencing depth and/or lacking or inaccurate assignment of unique molecular identifiers (UMIs), which are critical for elimination of PCR bias and artifacts. We introduce ScNaUmi-seq, an approach that combines the high throughput of Oxford Nanopore sequencing with an accurate cell barcode and UMI assignment strategy. UMI guided error correction allows to generate high accuracy full length sequence information with the 10x Genomics single cell isolation system at high sequencing depths. We analyzed transcript isoform diversity in embryonic mouse brain and show that ScNaUmi-seq allows defining splicing and SNVs (RNA editing) at a single cell level.

Droplet-based high throughput single cell isolation techniques tremendously boosted the throughput of single cell transcriptome profiling experiments. However, those approaches only allow analysis of one extremity of the transcript after short read sequencing. We introduce an approach that combines Oxford Nanopore sequencing with unique molecular identifiers to obtain error corrected full length sequence information with the 10×Genomics single cell isolation system. This allows to examine differential RNA splicing and RNA editing at a single cell level.

Single cell RNA sequencing approaches are instrumental in studies of cell-to-cell variability. 5΄ selective transcriptome profiling approaches allow simultaneous definition of the transcription start size and have advantages over 3΄ selective approaches which just provide internal sequences close to the 3΄ end. The only currently existing 5΄ selective approach requires costly and labor intensive fragmentation and cell barcoding after cDNA amplification. We developed an optimized 5΄ selective workflow where all the cell indexing is done prior to fragmentation. With our protocol, cell indexing can be performed in the Fluidigm C1 microfluidic device, resulting in a significant reduction of cost and labor. We also designed optimized unique molecular identifiers that show less sequence bias and vulnerability towards sequencing errors resulting in an improved accuracy of molecule counting. We provide comprehensive experimental workflows for Illumina and Ion Proton sequencers that allow single cell sequencing in a cost range comparable to qPCR assays.

Open reading frames are common in long noncoding RNAs (lncRNAs) and 5’UTRs of protein coding transcripts (uORFs). The question of whether those ORFs are translated was recently addressed by several groups using ribosome profiling. Most of those studies concluded that certain lncRNAs and uORFs are translated, essentially based on computational analysis of ribosome footprints. However, major discrepancies remain on the scope of translation and the translational status of individual ORFs. In consequence, further criteria are required to reliably identify translated ORFs from ribosome profiling data. We examined the effect of the translation inhibitors pateamine A, harringtonine and puromycin on murine ES cell ribosome footprints. We found that pateamine A, a drug that targets eIF4A, allows a far more accurate identification of translated sequences than previously used drugs and computational scoring schemes. Our data show that at least one third but less than two thirds of ES cell lncRNAs are translated. We also identified translated uORFs in hundreds of annotated coding transcripts including key pluripotency transcripts, such as dicer, lin28, trim71, and ctcf. Pateamine A inhibition data clearly increase the precision of the detection of translated ORFs in ribosome profiling experiments. Our data show that translation of lncRNAs and uORFs in murine ES cells is rather common although less pervasive than previously suggested. The observation of translated uORFs in several key pluripotency transcripts suggests that translational regulation by uORFs might be part of the network that defines mammalian stem cell identity.

Background: In severe obesity, as well as in normal development, the growth of adipose tissue is the result of an increase in adipocyte size and numbers, which is underlain by the stimulation of adipogenic differentiation of precursor cells. A better knowledge of the pathways that regulate adipogenesis is therefore essential for an improved understanding of adipose tissue expansion. As microRNAs (miRNAs) have a critical role in many differentiation processes, our study aimed to identify the role of miRNA-mediated gene silencing in the regulation of adipogenic differentiation. Results: We used deep sequencing to identify small RNAs that are differentially expressed during adipogenesis of adipose tissue-derived stem cells. This approach revealed the un-annotated miR-642a-3p as a highly adipocyte-specific miRNA. We then focused our study on the miR-30 family, which was also up-regulated during adipogenic differentiation and for which the role in adipogenesis had not yet been elucidated. Inhibition of the miR-30 family blocked adipogenesis, whilst over-expression of miR-30a and miR-30d stimulated this process. We additionally showed that both miR-30a and miR-30d target the transcription factor RUNX2, and stimulate adipogenesis via the modulation of this major regulator of osteogenesis. Conclusions: Overall, our data suggest that the miR-30 family plays a central role in adipocyte development. Moreover, as adipose tissue-derived stem cells can differentiate into either adipocytes or osteoblasts, the down-regulation of the osteogenesis regulator RUNX2 represents a plausible mechanism by which miR-30 miRNAs may contribute to adipogenic differentiation of adipose tissue-derived stem cells.

Multiciliated cells lining the surface of some vertebrate epithelia are essential for various physiological processes, such as airway cleansing. However, the mechanisms governing motile cilia biosynthesis remain poorly elucidated. We identify miR-449 microRNAs as evolutionarily conserved key regulators of vertebrate multiciliogenesis. In human airway epithelium and Xenopus laevis embryonic epidermis, miR-449 microRNAs strongly accumulated in multiciliated cells. In both models, we show that miR-449 microRNAs promote centriole multiplication and multiciliogenesis by directly repressing the Delta/Notch pathway. We established Notch1 and its ligand Delta-like 1(DLL1) as miR-449 bona fide targets. Human DLL1 and NOTCH1 protein levels were lower in multiciliated cells than in surrounding cells, decreased after miR-449 overexpression and increased after miR-449 inhibition. In frog, miR-449 silencing led to increased Dll1 expression. Consistently, overexpression of Dll1 mRNA lacking miR-449 target sites repressed multiciliogenesis, whereas both Dll1 and Notch1 knockdown rescued multiciliogenesis in miR-449-deficient cells. Antisense-mediated protection of miR-449-binding sites of endogenous human Notch1 or frog Dll1 strongly repressed multiciliogenesis. Our results unravel a conserved mechanism whereby Notch signalling must undergo miR-449-mediated inhibition to permit differentiation of ciliated cell progenitors.

Extensive sequencing efforts, combined with ad hoc bioinformatics developments, have now led to the identification of 1222 distinct miRNAs in human (derived from 1368 distinct genomic loci) and of many miRNAs in other multicellular organisms. The present chapter is aimed at describing a general experimental strategy to identify specific miRNA expression profiles and to highlight the functional networks operating between them and their mRNA targets, including several miRNAs deregulated in cystic fibrosis and during differentiation of airway epithelial cells.