Poly(a) selection introduces bias and undue noise in direct RNA-sequencing

Nanopore direct RNA sequencing of human transcriptomes reveals the complexity of mRNA modifications and crosstalk between regulatory features

The identification and functional characterization of chemical modifications on an mRNA molecule, in particular N6-methyladenosine (m6A) modification, significantly broadened our understanding of RNA function and regulation. While interactions between RNA modifications and other RNA features have been proposed, direct evidence showing correlation is limited. Here, using Oxford Nanopore long-read direct RNA sequencing (dRNA-seq), we simultaneously interrogate the transcriptome and epitranscriptome of a human leukemia cell line to investigate the correlation between m6A modifications, mRNA abundance, mRNA stability, polyadenylation (poly(A)) tail length, and alternative splicing. High-quality dRNA-seq is important for unbiased and large-scale correlative analyses. Global assessments indicated a negative association between poly(A) tail length and mRNA abundance while uncovering pathway-specific responses upon depletion of the m6A-forming enzyme METTL3. Overall, our study presented a rich dRNA-seq data resource that has been validated and can be further exploited to inquire into the complexity of RNA modifications and potential interplays between RNA regulatory elements.

Long-read RNA sequencing reveals allele-specific N 6-methyladenosine modifications

Long-read sequencing technology enables highly accurate detection of allele-specific RNA expression, providing insights into the effects of genetic variation on splicing and RNA abundance. Furthermore, the ability to directly sequence RNA enables the detection of RNA modifications in tandem with ascertaining the allelic origin of each molecule. Here, we leverage these advantages to determine allele-biased patterns of N 6-methyladenosine (m6A) modifications in native mRNA. We used human and mouse cells with known genetic variants to assign the allelic origin of each mRNA molecule combined with a supervised machine learning model to detect read-level m6A modification ratios. Our analyses reveal the importance of sequences adjacent to the DRACH motif in determining m6A deposition, in addition to allelic differences that directly alter the motif. Moreover, we discover allele-specific m6A modification events with no genetic variants in close proximity to the differentially modified nucleotide, demonstrating the unique advantage of using long-reads and surpassing the capabilities of antibody-based short-read approaches. This technological advance will further our understanding of the role of genetics in determining mRNA modifications.

Detection of mRNA Transcript Variants

Most eukaryotic genes express more than one mature mRNA, defined as transcript variants. This complex phenomenon arises from various mechanisms, such as using alternative transcription start sites and alternative post-transcriptional processing events. The resulting transcript variants can lead to synthesizing proteins that possess distinct functional domains or may even generate noncoding RNAs, each with unique roles in cellular processes. The generation of these transcript variants is not merely a random occurrence; it is cell-type specific and varies with developmental stages, aging processes, or pathogenesis of diseases. This highlights the biological significance of transcript variants in regulating gene expression and their potential impact on cellular functionality. Despite the biological importance, investigating transcript variants has been hampered by challenges associated with detecting their expression. This review article addresses the advancements in molecular techniques in detecting transcript variants. Traditional methods such as RT-PCR and RT-qPCR can easily detect known transcript variants using primers that target unique exons associated with the variants. Other techniques like RACE-PCR and hybridization-based methods, including Northern blotting, RNase protection assays, and microarrays, have also been utilized to detect transcript variants. Nevertheless, RNA sequencing (RNA-Seq) has emerged as a powerful technique for identifying transcript variants, especially those with previously unknown sequences. The effectiveness of RNA sequencing in transcript variant detection depends on the specific sequencing approach and the precision of data analysis. By understanding the strengths and weaknesses of each laboratory technique, researchers can develop more effective strategies for detecting mRNA transcript variants. This ability will be crucial for our comprehensive understanding of gene regulation and the implications of transcript diversity in various biological contexts.

Single-Cell RNA Sequencing Reveals Extensive Heterogeneity and Unique Gene Trajectories in Non-Transformed and Transformed Human Lung Epithelial Cells: Insights into the Role of LncRNAs in Tumor Heterogeneity

Lung cancer exhibits substantial inter- and intra-tumor heterogeneity, with features that present significant challenges in advancing biomarker discovery and the development of targeted therapeutics. To fill this gap, we employed single-cell RNA sequencing (scRNA-seq) and advanced bioinformatics tools to evaluate the transcriptomic heterogeneity of immortalized, non-transformed (BEAS2B) and transformed (H460) lung epithelial cell lines and their responses to carcinogen challenge. Gene expression profiles resolved four primary clusters further discretized into unique subclusters based on genetic signatures and phenotypic profiles. Profiles of long non-coding RNAs (lncRNAs) identified microRNA host genes, antisense RNA genes, divergent transcript, and long intergenic non-coding RNAs as contributors to cellular heterogeneity. These findings indicate that distinct patterns of gene expression, remarkably in lncRNAs, define cellular heterogeneity in non-transformed versus transformed cells. These features can be exploited for the development of therapies directed at specific cell subpopulations in precancerous lesions and within lung tumors.

RiboTag RNA Sequencing Identifies Local Translation of HSP70 in Astrocyte Endfeet After Cerebral Ischemia

Brain ischemia causes disruption in cerebral blood flow and blood-brain barrier integrity, which are normally maintained by astrocyte endfeet. Emerging evidence points to dysregulation of the astrocyte translatome during ischemia, but its effects on the endfoot translatome are unknown. In this study, we aimed to investigate the early effects of ischemia on the astrocyte endfoot translatome in a rodent cerebral ischemia and reperfusion model of stroke. To do so, we immunoprecipitated astrocyte-specific tagged ribosomes (RiboTag IP) from mechanically isolated brain microvessels. In mice subjected to middle cerebral artery occlusion and reperfusion and contralateral controls, we sequenced ribosome-bound RNAs from perivascular astrocyte endfeet and identified 205 genes that were differentially expressed in the endfoot translatome after ischemia. The main biological processes associated with these differentially expressed genes included proteostasis, inflammation, cell cycle/death, and metabolism. Transcription factors whose targets were enriched amongst upregulated translating genes included HSF1, the master regulator of the heat shock response. The most highly upregulated genes in the translatome were HSF1-dependent Hspa1a and Hspa1b, which encode the inducible HSP70. Using qPCR, Western blot, and immunohistochemistry, we confirmed that HSP70 is upregulated in astrocyte endfeet after ischemia. This coincided with an increase in ubiquitination across the proteome that suggests that ischemia induces a disruption in proteostasis in astrocyte endfeet. These findings suggest a robust proteostasis response to proteotoxic stress in the endfoot translatome after ischemia. Modulating proteostasis in endfeet may be a strategy to preserve endfoot function and BBB integrity after ischemic stroke.

Insights into the human cDNA: A descriptive study using library screening in yeast

The utilization of human cDNA libraries in yeast genetic screens is an approach that has been used to identify novel gene functions and/or genetic and physical interaction partners through forward genetics using yeast two-hybrid (Y2H) and classical cDNA library screens. Here, we summarize several challenges that have been observed during the implementation of human cDNA library screens in Saccharomyces cerevisiae (budding yeast). Upon the utilization of DNA repair deficient-yeast strains to identify novel genes that rescue the toxic effect of DNA-damage inducing drugs, we have observed a wide range of transcripts that could rescue the strains. However, after several rounds of screening, most of these hits turned out to be false positives, most likely due to spontaneous mutations in the yeast strains that arise as a rescue mechanism due to exposure to toxic DNA damage inducing-drugs. The observed transcripts included mitochondrial hits, non-coding RNAs, truncated cDNAs, and transcription products that resulted from the internal priming of genomic regions. We have also noticed that most cDNA transcripts are not fused with the GAL4 activation domain (GAL4AD), rendering them unsuitable for Y2H screening. Consequently, we utilized Sanger sequencing to screen 282 transcripts obtained from either four different yeast screens or through direct fishing from a human kidney cDNA library. The aim was to gain insights into the different transcription products and to highlight the challenges of cDNA screening approaches in the presence of a significant number of undesired transcription products. In summary, this study describes the challenges encountering human cDNA library screening in yeast as a valuable technique that led to the identification of important molecular mechanisms. The results open research venues to further optimize the process and increase its efficiency.

Long-read RNA sequencing of archival tissues reveals novel genes and transcripts associated with clear cell renal cell carcinoma recurrence and immune evasion

The use of long-read direct RNA sequencing (DRS) and PCR cDNA sequencing (PCS) in clinical oncology remains limited, with no direct comparison between the two methods. We used DRS and PCS to study clear cell renal cell carcinoma (ccRCC), focusing on new transcript and gene discovery. Twelve primary ccRCC archival tumors, six from patients who went on to relapse, were analyzed. Results were validated in an independent cohort of 20 patients by qRT-PCR and compared to DRS analysis of RCC4 cells. In archival clinical samples and due to the long-term storage, the average read length was lower (400-500 nt) than that achieved through DRS of RCC4 cells (>1100 nt). Still, deconvolution analysis showed a loss of immune infiltrate in primary tumors of patients who relapse as reported by others. Differentially expressed genes in patients who went on to relapse were determined with good overlap between DRS and PCS, identifying LINC04216 and the T-cell exhaustion marker TOX as novel candidate recurrence-associated genes. Novel transcript analysis revealed over 10,000 candidate novel transcripts detected by both methods and in ccRCC cells in vitro, including a novel CD274 (PD-L1) transcript encoding for the soluble version of the protein with a longer 3' UTR and lower stability than the annotated transcript. Both methods identified 414 novel genes, also detected in RCC4 cells, including a novel noncoding gene overexpressed in patients who relapse. Overall, we showcase the use of PCS and DRS in archival tumor samples to uncover unmapped features of cancer transcriptomes, linked to disease progression and immune evasion.

High-resolution reconstruction of a C. elegans ribosome sheds light on evolutionary dynamics and tissue specificity

Caenorhabditis elegans is an important model organism for human health and disease, with foundational contributions to the understanding of gene expression and tissue patterning in animals. An invaluable tool in modern gene expression research is the presence of a high-resolution ribosome structure, though no such structure exists for C. elegans Here, we present a high-resolution single-particle cryogenic electron microscopy (cryo-EM) reconstruction and molecular model of a C. elegans ribosome, revealing a significantly streamlined animal ribosome. Many facets of ribosome structure are conserved in C. elegans, including overall ribosomal architecture and the mechanism of cycloheximide, whereas other facets, such as expansion segments and eL28, are rapidly evolving. We identify uL5 and uL23 as two instances of tissue-specific ribosomal protein paralog expression conserved in Caenorhabditis, suggesting that C. elegans ribosomes vary across tissues. The C. elegans ribosome structure will provide a basis for future structural, biochemical, and genetic studies of translation in this important animal system.

RiboTag RNA Sequencing Identifies Local Translation of HSP70 In Astrocyte Endfeet After Cerebral Ischemia

Brain ischemia causes disruption in cerebral blood flow and blood-brain barrier (BBB) integrity which are normally maintained by the astrocyte endfeet. Emerging evidence points to dysregulation of the astrocyte translatome during ischemia, but its effects on the endfoot translatome are unknown. In this study, we aimed to investigate the early effects of ischemia on the astrocyte endfoot translatome in a rodent model of cerebral ischemia-reperfusion. To do so, we immunoprecipitated astrocyte-specific tagged ribosomes (RiboTag IP) from mechanically isolated brain microvessels. In mice subjected to middle cerebral artery occlusion and reperfusion and contralateral controls, we sequenced ribosome-bound RNAs from perivascular astrocyte endfeet and identified 205 genes that were differentially expressed in the translatome after ischemia. Pathways associated with the differential expressions included proteostasis, inflammation, cell cycle, and metabolism. Transcription factors whose targets were enriched amongst upregulated translating genes included HSF1, the master regulator of the heat shock response. The most highly upregulated genes in the translatome were HSF1-dependent Hspa1a and Hspa1b , which encode the inducible HSP70. We found that HSP70 is upregulated in astrocyte endfeet after ischemia, coinciding with an increase in ubiquitination across the proteome. These findings suggest a robust proteostasis response to proteotoxic stress in the endfoot translatome after ischemia. Modulating proteostasis in endfeet may be a strategy to preserve endfeet function and BBB integrity after ischemic stroke.

Long-read RNA sequencing reveals allele-specific N6-methyladenosine modifications

Long-read sequencing technology enables highly accurate detection of allele-specific RNA expression, providing insights into the effects of genetic variation on splicing and RNA abundance. Furthermore, the ability to directly sequence RNA promises the detection of RNA modifications in tandem with ascertaining the allelic origin of each molecule. Here, we leverage these advantages to determine allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNA. We utilized human and mouse cells with known genetic variants to assign allelic origin of each mRNA molecule combined with a supervised machine learning model to detect read-level m6A modification ratios. Our analyses revealed the importance of sequences adjacent to the DRACH-motif in determining m6A deposition, in addition to allelic differences that directly alter the motif. Moreover, we discovered allele-specific m6A modification (ASM) events with no genetic variants in close proximity to the differentially modified nucleotide, demonstrating the unique advantage of using long reads and surpassing the capabilities of antibody-based short-read approaches. This technological advancement promises to advance our understanding of the role of genetics in determining mRNA modifications.

RNaseH-based ribodepletion of total planarian RNA improves detection of longer and non-polyadenylated transcripts

The overwhelming majority of RNA species isolated from cells or tissues using organic extraction are ribosomal RNAs (rRNA), whereas a relatively small percentage are messenger RNAs (mRNA). For studies that seek to detect mRNA transcripts and measure changes in their expression, this lopsided ratio of desired transcripts to undesired transcripts creates a significant challenge to obtaining sensitive and reproducible results. One method for improving mRNA detection is to selectively amplify polyadenylated (polyA) mRNA molecules when generating RNA-seq libraries, a strategy that is generally very successful in many species. However, this strategy is less effective when starting with total RNA from some species e.g., the planarian species Schmidtea mediterranea (S.med), as it generates libraries that still contain significant and variable amounts of rRNA reads. Further, commercially available ribodepletion kits do not efficiently deplete rRNAs from these samples because their sequences are divergent from mammalian rRNAs. Here we report a customized, optimized, and economical ribodepletion strategy than allows the generation of comprehensive RNA-seq libraries with less than one percent rRNA contamination. We show that this method improves transcript detection, particularly for those without polyA tails (e.g., core histones) and those that are relatively long (e.g., microtubule motor proteins). Using this custom ribodepletion approach, we also detected many transcripts that are not represented in the most recent set of S.med gene annotations, including a subset that are likely expressed transposable elements (TEs). To facilitate future differential expression analyses of these newly identified loci, we created both an annotation file of the new loci we identified and a bioinformatic pipeline for generating additional annotations from future libraries. As significant recent research shows that TE activation is regulated and functionally important, the resources provided here will provide a starting point for investigating such mechanisms in planarians and other species with less conserved rRNA sequences.

Comprehensive assessment of mRNA isoform detection methods for long-read sequencing data

The advancement of Long-Read Sequencing (LRS) techniques has significantly increased the length of sequencing to several kilobases, thereby facilitating the identification of alternative splicing events and isoform expressions. Recently, numerous computational tools for isoform detection using long-read sequencing data have been developed. Nevertheless, there remains a deficiency in comparative studies that systemically evaluate the performance of these tools, which are implemented with different algorithms, under various simulations that encompass potential influencing factors. In this study, we conducted a benchmark analysis of thirteen methods implemented in nine tools capable of identifying isoform structures from long-read RNA-seq data. We evaluated their performances using simulated data, which represented diverse sequencing platforms generated by an in-house simulator, RNA sequins (sequencing spike-ins) data, as well as experimental data. Our findings demonstrate IsoQuant as a highly effective tool for isoform detection with LRS, with Bambu and StringTie2 also exhibiting strong performance. These results offer valuable guidance for future research on alternative splicing analysis and the ongoing improvement of tools for isoform detection using LRS data.

Characterization of the brain virome in human immunodeficiency virus infection and substance use disorder

Viruses can infect the brain in individuals with and without HIV-infection: however, the brain virome is poorly characterized. Metabolic alterations have been identified which predispose people to substance use disorder (SUD), but whether these could be triggered by viral infection of the brain is unknown. We used a target-enrichment, deep sequencing platform and bioinformatic pipeline named "ViroFind", for the unbiased characterization of DNA and RNA viruses in brain samples obtained from the National Neuro-AIDS Tissue Consortium. We analyzed fresh frozen post-mortem prefrontal cortex from 72 individuals without known viral infection of the brain, including 16 HIV+/SUD+, 20 HIV+/SUD-, 16 HIV-/SUD+, and 20 HIV-/SUD-. The average age was 52.3 y and 62.5% were males. We identified sequences from 26 viruses belonging to 11 viral taxa. These included viruses with and without known pathogenic potential or tropism to the nervous system, with sequence coverage ranging from 0.03 to 99.73% of the viral genomes. In SUD+ people, HIV-infection was associated with a higher total number of viruses, and HIV+/SUD+ compared to HIV-/SUD+ individuals had an increased frequency of Adenovirus (68.8 vs 0%; p<0.001) and Epstein-Barr virus (EBV) (43.8 vs 6.3%; p=0.037) as well as an increase in Torque Teno virus (TTV) burden. Conversely, in HIV+ people, SUD was associated with an increase in frequency of Hepatitis C virus, (25 in HIV+/SUD+ vs 0% in HIV+/SUD-; p=0.031). Finally, HIV+/SUD- compared to HIV-/SUD- individuals had an increased frequency of EBV (50 vs 0%; p<0.001) and an increase in TTV viral burden, but a decreased Adenovirus viral burden. These data demonstrate an unexpectedly high variety in the human brain virome, identifying targets for future research into the impact of these taxa on the central nervous system. ViroFind could become a valuable tool for monitoring viral dynamics in various compartments, monitoring outbreaks, and informing vaccine development.

Quantification of Poly(A) Tail Length and Terminal Modifications Using Direct RNA Sequencing

Poly(A) tail metabolism is critical for various biological processes, including early embryogenesis and cell differentiation. While traditional biochemical methods to measure poly(A) tail length allow for the study of selected transcripts, the advent of long-read sequencing technologies enabled the development of simple and robust protocols to measure poly(A) tail length at the transcriptome level. Here, we describe a direct RNA sequencing protocol to capture poly(A) tail terminal additions based on the splint ligation of barcoded oligos compatible with terminal guanylation and uridylation. We cover how to prepare the libraries and perform the bioinformatics analysis to simultaneously determine the length of the transcripts' poly(A) tails and detect the presence of terminal guanylation and uridylation.

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets

Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding disease pathologies. However, several experimental and computational challenges impede transcriptomics-based deconvolution approaches using single-cell/nucleus RNA-seq reference atlases. Cells from the brain and blood have substantially different sizes, total mRNA, and transcriptional activities, and existing approaches may quantify total mRNA instead of cell type proportions. Further, standards are lacking for the use of cell reference atlases and integrative analyses of single-cell and spatial transcriptomics data. We discuss how to approach these key challenges with orthogonal "gold standard" datasets for evaluating deconvolution methods.

Leptospira transcriptome sequencing using long-read technology reveals unannotated transcripts and potential polyadenylation of RNA molecules

IMPORTANCE

Leptospirosis, caused by the spirochete bacteria Leptospira, is a zoonotic disease of humans and animals, accounting for over 1 million annual human cases and over 60,000 deaths. We have characterized operon transcriptional units, identified novel RNA coding regions, and reported evidence of potential posttranscriptional polyadenylation in the Leptospira transcriptomes for the first time using Oxford Nanopore Technology RNA sequencing protocols. The newly identified RNA coding regions and operon transcriptional units were detected only in the pathogenic Leptospira transcriptomes, suggesting their significance in virulence-related functions. This article integrates bioinformatics, infectious diseases, microbiology, molecular biology, veterinary sciences, and public health. Given the current knowledge gap in the regulation of leptospiral pathogenicity, our findings offer valuable insights to researchers studying leptospiral pathogenicity and provide both a basis and a tool for researchers focusing on prokaryotic molecular studies for the understanding of RNA compositions and prokaryotic polyadenylation for their organisms of interest.

Differential Gene Expression of Malaria Parasite in Response to Red Blood Cell-Specific Glycolytic Intermediate 2,3-Diphosphoglycerate (2,3-DPG)

Innovative strategies to control malaria are urgently needed. Exploring the interplay between Plasmodium sp. parasites and host red blood cells (RBCs) offers opportunities for novel antimalarial interventions. Pyruvate kinase deficiency (PKD), characterized by heightened 2,3-diphosphoglycerate (2,3-DPG) concentration, has been associated with protection against malaria. Elevated levels of 2,3-DPG, a specific mammalian metabolite, may hinder glycolysis, prompting us to hypothesize its potential contribution to PKD-mediated protection. We investigated the impact of the extracellular supplementation of 2,3-DPG on the Plasmodium falciparum intraerythrocytic developmental cycle in vitro. The results showed an inhibition of parasite growth, resulting from significantly fewer progeny from 2,3-DPG-treated parasites. We analyzed differential gene expression and the transcriptomic profile of P. falciparum trophozoites, from in vitro cultures subjected or not subjected to the action of 2,3-DPG, using Nanopore Sequencing Technology. The presence of 2,3-DPG in the culture medium was associated with the significant differential expression of 71 genes, mostly associated with the GO terms nucleic acid binding, transcription or monoatomic anion channel. Further, several genes related to cell cycle control were downregulated in treated parasites. These findings suggest that the presence of this RBC-specific glycolytic metabolite impacts the expression of genes transcribed during the parasite trophozoite stage and the number of merozoites released from individual schizonts, which supports the potential role of 2,3-DPG in the mechanism of protection against malaria by PKD.

NMD targets experience deadenylation during their maturation and endonucleolytic cleavage during their decay

Premature stop codon-containing mRNAs can produce truncated and dominantly acting proteins that harm cells. Eukaryotic cells protect themselves by degrading such mRNAs via the Nonsense-Mediated mRNA Decay (NMD) pathway. The precise reactions by which cells attack NMD target mRNAs remain obscure, precluding a mechanistic understanding of NMD and hampering therapeutic efforts to control NMD. A key step in NMD is the decay of the mRNA, which is proposed to occur via several competing models including deadenylation, exonucleolytic decay, and/or endonucleolytic decay. We set out to clarify the relative contributions of these decay mechanisms to NMD, and to identify the role of key factors. Here, we modify and deploy single-molecule nanopore mRNA sequencing to capture full-length NMD targets and their degradation intermediates, and we obtain single-molecule measures of splicing isoform, cleavage state, and poly(A) tail length. We observe robust endonucleolytic cleavage of NMD targets in vivo that depends on the nuclease SMG-6 and we use the occurence of cleavages to identify several known NMD targets. We show that NMD target mRNAs experience deadenylation, but similar to the extent that normal mRNAs experience as they enter the translational pool. Furthermore, we show that a factor (SMG-5) that historically was ascribed a function in deadenylation, is in fact required for SMG-6-mediated cleavage. Our results support a model in which NMD factors act in concert to degrade NMD targets in animals via an endonucleolytic cleavage near the stop codon, and suggest that deadenylation is a normal part of mRNA (and NMD target) maturation rather than a facet unique to NMD. Our work clarifies the route by which NMD target mRNAs are attacked in an animal.

Current concepts, advances, and challenges in deciphering the human microbiota with metatranscriptomics

Metatranscriptomics refers to the analysis of the collective microbial transcriptome of a sample. Its increased utilization for the characterization of human-associated microbial communities has enabled the discovery of many disease-state related microbial activities. Here, we review the principles of metatranscriptomics-based analysis of human-associated microbial samples. We describe strengths and weaknesses of popular sample preparation, sequencing, and bioinformatics approaches and summarize strategies for their use. We then discuss how human-associated microbial communities have recently been examined and how their characterization may change. We conclude that metatranscriptomics insights into human microbiotas under health and disease have not only expanded our knowledge on human health, but also opened avenues for rational antimicrobial drug use and disease management.

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single cell RNA-sequencing datasets

Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding the pathologies of diseases. However, several experimental and computational challenges remain in developing and implementing transcriptomics-based deconvolution approaches, especially those using a single cell/nuclei RNA-seq reference atlas, which are becoming rapidly available across many tissues. Notably, deconvolution algorithms are frequently developed using samples from tissues with similar cell sizes. However, brain tissue or immune cell populations have cell types with substantially different cell sizes, total mRNA expression, and transcriptional activity. When existing deconvolution approaches are applied to these tissues, these systematic differences in cell sizes and transcriptomic activity confound accurate cell proportion estimates and instead may quantify total mRNA content. Furthermore, there is a lack of standard reference atlases and computational approaches to facilitate integrative analyses, including not only bulk and single cell/nuclei RNA-seq data, but also new data modalities from spatial -omic or imaging approaches. New multi-assay datasets need to be collected with orthogonal data types generated from the same tissue block and the same individual, to serve as a "gold standard" for evaluating new and existing deconvolution methods. Below, we discuss these key challenges and how they can be addressed with the acquisition of new datasets and approaches to analysis.