CRISPRi-mediated functional analysis of lung disease-associated loci at non-coding regions

Patho-transcriptomic analysis of invasive mucinous adenocarcinoma of the lung (IMA): comparison with lung adenocarcinoma with signet ring cell features (SRCC)

Background

Invasive mucinous adenocarcinoma (IMA) comprises ∼5% of lung adenocarcinoma. There is no effective therapy for IMA when surgical resection is not possible. IMA is sometimes confused with adenocarcinoma with signet ring cell features (SRCC) pathologically since both adenocarcinomas feature tumor cells with abundant intracellular mucin. The molecular mechanisms by which such mucin-producing lung adenocarcinomas develop remain unknown.

Methods

Using a Visium spatial transcriptomics approach, we analyzed IMA and compared it with SRCC patho-transcriptomically. Combining spatial transcriptomics data with in vitro studies using RNA-seq and ChIP-seq, we assessed downstream targets of transcription factors HNF4A and SPDEF that are highly expressed in IMA and/or SRCC.

Results

Spatial transcriptomics analysis indicated that there are 6 distinct cell clusters in IMA and SRCC. Notably, two clusters (C1 and C3) of mucinous tumor cells exist in both adenocarcinomas albeit at a different ratio. Importantly, a portion of genes (e.g., NKX2-1 , GKN1 , HNF4A and FOXA3 ) are distinctly expressed while some mucous-related genes (e.g., SPDEF and FOXA2 ) are expressed in both adenocarcinomas. We determined that HNF4A induces MUC3A/B and TM4SF4 and that BI 6015, an HNF4A antagonist, suppressed the growth of IMA cells. Using mutant SPDEF that is associated with COVID-19, we also determined that an intact DNA-binding domain of SPDEF is required for SPDEF-mediated induction of mucin genes ( MUC5AC , MUC5B and AGR2 ). Additionally, we found that XMU-MP-1, a SPDEF inhibitor, suppressed the growth of IMA cells.

Conclusion

These results revealed that IMA and SRCC contain heterogenous tumor cell types, some of which are targetable.

Underlying causes for prevalent false positives and false negatives in STARR-seq data

Self-transcribing active regulatory region sequencing (STARR-seq) and its variants have been widely used to characterize enhancers. However, it has been reported that up to 87% of STARR-seq peaks are located in repressive chromatin and are not functional in the tested cells. While some of the STARR-seq peaks in repressive chromatin might be active in other cell/tissue types, some others might be false positives. Meanwhile, many active enhancers may not be identified by the current STARR-seq methods. Although methods have been proposed to mitigate systematic errors caused by the use of plasmid vectors, the artifacts due to the intrinsic limitations of current STARR-seq methods are still prevalent and the underlying causes are not fully understood. Based on predicted cis-regulatory modules (CRMs) and non-CRMs in the human genome as well as predicted active CRMs and non-active CRMs in a few human cell lines/tissues with STARR-seq data available, we reveal prevalent false positives and false negatives in STARR-seq peaks generated by major variants of STARR-seq methods and possible underlying causes. Our results will help design strategies to improve STARR-seq methods and interpret the results.

Genomic characterization and therapeutic utilization of IL-13-responsive sequences in asthma

Epithelial responses to the cytokine interleukin-13 (IL-13) cause airway obstruction in asthma. Here we utilized multiple genomic techniques to identify IL-13-responsive regulatory elements in bronchial epithelial cells and used these data to develop a CRISPR interference (CRISPRi)-based therapeutic approach to downregulate airway obstruction-inducing genes in a cell type- and IL-13-specific manner. Using single-cell RNA sequencing (scRNA-seq) and acetylated lysine 27 on histone 3 (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) in primary human bronchial epithelial cells, we identified IL-13-responsive genes and regulatory elements. These sequences were functionally validated and optimized via massively parallel reporter assays (MPRAs) for IL-13-inducible activity. The top secretory cell-selective sequence from the MPRA, a novel, distal enhancer of the sterile alpha motif pointed domain containing E-26 transformation-specific transcription factor (SPDEF) gene, was utilized to drive CRISPRi and knock down SPDEF or mucin 5AC (MUC5AC), both involved in pathologic mucus production in asthma. Our work provides a catalog of cell type-specific genes and regulatory elements involved in IL-13 bronchial epithelial response and showcases their use for therapeutic purposes.

Multiplexed functional genomic assays to decipher the noncoding genome

Linkage disequilibrium and the incomplete regulatory annotation of the noncoding genome complicates the identification of functional noncoding genetic variants and their causal association with disease. Current computational methods for variant prioritization have limited predictive value, necessitating the application of highly parallelized experimental assays to efficiently identify functional noncoding variation. Here, we summarize two distinct approaches, massively parallel reporter assays and CRISPR-based pooled screens and describe their flexible implementation to characterize human noncoding genetic variation at unprecedented scale. Each approach provides unique advantages and limitations, highlighting the importance of multimodal methodological integration. These multiplexed assays of variant effects are undoubtedly poised to play a key role in the experimental characterization of noncoding genetic risk, informing our understanding of the underlying mechanisms of disease-associated loci and the development of more robust predictive classification algorithms.

CRISPRi links COVID-19 GWAS loci to LZTFL1 and RAVER1

Background

To identify host genetic variants (SNPs) associated with COVID-19 disease severity, a number of genome-wide association studies (GWAS) have been conducted. Since most of the identified variants are located at non-coding regions, such variants are presumed to affect the expression of neighbouring genes, thereby influencing COVID-19 disease severity. However, it remains largely unknown which genes are influenced by such COVID-19 GWAS loci.

Methods

CRISPRi (interference)-mediated gene expression analysis was performed to identify genes functionally regulated by COVID-19 GWAS loci by targeting regions near the loci (SNPs) in lung epithelial cell lines. The expression of CRISPRi-identified genes was investigated using COVID-19-contracted human and monkey lung single-nucleus/cell (sn/sc) RNA-seq datasets.

Findings

CRISPRi analysis indicated that a region near rs11385942 at chromosome 3p21.31 (locus of highest significance with COVID-19 disease severity at intron 5 of LZTFL1) significantly affected the expression of LZTFL1 (P<0.05), an airway cilia regulator. A region near rs74956615 at chromosome 19p13.2 (locus located at the 3’ untranslated exonic region of RAVER1), which is associated with critical illness in COVID-19, affected the expression of RAVER1 (P<0.05), a coactivator of MDA5 (IFIH1), which induces antiviral response genes, including ICAM1. The sn/scRNA-seq datasets indicated that the MDA5/RAVER1-ICAM1 pathway was activated in lung epithelial cells of COVID-19-resistant monkeys but not those of COVID-19-succumbed humans.

Interpretation

Patients with risk alleles of rs11385942 and rs74956615 may be susceptible to critical illness in COVID-19 in part through weakened airway viral clearance via LZTFL1-mediated ciliogenesis and diminished antiviral immune response via the MDA5/RAVER1 pathway, respectively.

Funding

NIH.

Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics

Multimorbidity is characterized by multidimensional complexity emerging from interactions between multiple diseases across levels of biological (including genetic) and environmental determinants and the complex array of interactions between and within cells, tissues and organ systems. Advances in spatial genomic research have led to an unprecedented expansion in our ability to link alterations in genome folding with changes that are associated with human disease. Studying disease-associated genetic variants in the context of the spatial genome has enabled the discovery of transcriptional regulatory programmes that potentially link dysregulated genes to disease development. However, the approaches that have been used have typically been applied to uncover pathological molecular mechanisms occurring in a specific disease-relevant tissue. These forms of reductionist, targeted investigations are not appropriate for the molecular dissection of multimorbidity that typically involves contributions from multiple tissues. In this perspective, we emphasize the importance of a whole-body understanding of multimorbidity and discuss how spatial genomics, when integrated with additional omic datasets, could provide novel insights into the molecular underpinnings of multimorbidity.

CRISPRi-mediated functional analysis of NKX2-1-binding sites in the lung

The transcription factor NKX2-1/TTF-1 is involved in lung pathophysiology, including breathing, innate defense and tumorigenesis. To understand the mechanism by which NKX2-1 regulates genes involved in such pathophysiology, we have previously performed ChIP-seq and identified genome-wide NKX2-1-binding sites, which revealed that NKX2-1 binds to not only proximal promoter regions but also multiple intra- and inter-genic regions of the genes regulated by NKX2-1. However, the roles of such regions, especially non-proximal ones, bound by NKX2-1 have not yet been determined. Here, using CRISPRi (CRISPR/dCas9-KRAB), we scrutinize the functional roles of 19 regions/sites bound by NKX2-1, which are located in genes involved in breathing and innate defense (SFTPB, LAMP3, SFTPA1, SFTPA2) and lung tumorigenesis (MYBPH, LMO3, CD274/PD-L1). Notably, the CRISPRi approach reveals that a portion of NKX2-1-binding sites are functionally indispensable while the rest are dispensable for the expression of the genes, indicating that functional roles of NKX2-1-binding sites are unequally yoked.