Synthetic spike-in standards for RNA-seq experiments

Challenges and opportunities in processing NanoString nCounter data

NanoString nCounter is a medium-throughput technology used in mRNA and miRNA differential expression studies. It offers several advantages, including the absence of an amplification step and the ability to analyze low-grade samples. Despite its considerable strengths, the popularity of the nCounter platform in experimental research stabilized in 2022 and 2023, and this trend may continue in the upcoming years. Such stagnation could potentially be attributed to the absence of a standardized analytical pipeline or the indication of optimal processing methods for nCounter data analysis. To standardize the description of the nCounter data analysis workflow, we divided it into five distinct steps: data pre-processing, quality control, background correction, normalization and differential expression analysis. Next, we evaluated eleven R packages dedicated to nCounter data processing to point out functionalities belonging to these steps and provide comments on their applications in studies of mRNA and miRNA samples.

Use of synthetic circular RNA spike-ins (SynCRS) for normalization of circular RNA sequencing data

High-throughput RNA sequencing enables the quantification of transcript abundance and the identification of novel transcripts in biological samples. These include circular RNAs (circRNAs), a family of alternatively spliced RNA molecules that form a continuous loop. However, quantification and comparison of circRNAs between RNA sequencing libraries remain challenging due to confounding errors introduced during exonuclease digestion, library preparation and RNA sequencing itself. Here we describe a set of synthetic circRNA spike-ins-termed 'SynCRS'-that can be added directly to purified RNA samples before exonuclease digestion and library preparation. SynCRS, introduced either individually or in combinations of varying size and abundance, can be integrated into all next-generation sequencing workflows and, critically, facilitate the quantitative calibration of circRNA transcript abundance between samples, tissue types, species and laboratories. Our step-by-step protocol details the generation of SynCRS and guides users on the stoichiometry of SynCRS spike-in to RNA samples, followed by the bioinformatic steps required to facilitate quantitative comparisons of circRNAs between libraries. The laboratory steps to produce the SynCRS require an additional 3 d on top of the high throughput circRNA sequencing and bioinformatics. The protocol is suitable for users with basic experience in molecular biology and bioinformatics.

Calibrated ribosome profiling assesses the dynamics of ribosomal flux on transcripts

Ribosome profiling, which is based on deep sequencing of ribosome footprints, has served as a powerful tool for elucidating the regulatory mechanism of protein synthesis. However, the current method has substantial issues: contamination by rRNAs and the lack of appropriate methods to measure ribosome numbers in transcripts. Here, we overcome these hurdles through the development of "Ribo-FilterOut", which is based on the separation of footprints from ribosome subunits by ultrafiltration, and "Ribo-Calibration", which relies on external spike-ins of stoichiometrically defined mRNA-ribosome complexes. A combination of these approaches estimates the number of ribosomes on a transcript, the translation initiation rate, and the overall number of translation events before its decay, all in a genome-wide manner. Moreover, our method reveals the allocation of ribosomes under heat shock stress, during aging, and across cell types. Our strategy of modified ribosome profiling measures kinetic and stoichiometric parameters of cellular translation across the transcriptome.

Analyzing RNA-Seq data from Chlamydia with super broad transcriptomic activation: challenges, solutions, and implications for other systems

BACKGROUND

RNA sequencing (RNA-Seq) offers profound insights into the complex transcriptomes of diverse biological systems. However, standard differential expression analysis pipelines based on DESeq2 and edgeR encounter challenges when applied to the immediate early transcriptomes of Chlamydia spp., obligate intracellular bacteria. These challenges arise from their reliance on assumptions that do not hold in scenarios characterized by extensive transcriptomic activation and limited repression.

RESULTS

Standard analyses using unique chlamydial RNA-Seq reads alone identify nearly 300 upregulated and about 300 downregulated genes, significantly deviating from actual RNA-Seq read trends. By incorporating both chlamydial and host reads or adjusting for total sequencing depth, the revised normalization methods each detected over 700 upregulated genes and 30 or fewer downregulated genes, closely aligned with observed RNA-Seq data. Further validation through qRT-PCR analysis confirmed the effectiveness of these adjusted approaches in capturing the true extent of transcriptomic activation during the immediate early phase of chlamydial infection.

CONCLUSIONS

This study highlights the limitations of standard RNA-Seq analysis tools in scenarios with extensive transcriptomic activation, such as in Chlamydia spp. during early infection. Our revised normalization methods, incorporating host reads or total sequencing depth, provide a more accurate representation of gene expression dynamics. These approaches may inform similar adjustments in other systems with unbalanced gene expression dynamics, enhancing the accuracy of transcriptomic analysis.

MicroRNAs Participate in Morphological Acclimation of Sugar Beet Roots to Nitrogen Deficiency

Nitrogen (N) is essential for sugar beet (Beta vulgaris L.), a highly N-demanding sugar crop. This study investigated the morphological, subcellular, and microRNA-regulated responses of sugar beet roots to low N (LN) stress (0.5 mmol/L N) to better understand the N perception, uptake, and utilization in this species. The results showed that LN led to decreased dry weight of roots, N accumulation, and N dry matter production efficiency, along with damage to cell walls and membranes and a reduction in organelle numbers (particularly mitochondria). Meanwhile, there was an increase in root length (7.2%) and branch numbers (29.2%) and a decrease in root surface area (6.14%) and root volume (6.23%) in sugar beet after 7 d of LN exposure compared to the control (5 mmol/L N). Transcriptomics analysis was confirmed by qRT-PCR for 6 randomly selected microRNAs, and we identified 22 differentially expressed microRNAs (DEMs) in beet root under LN treatment. They were primarily enriched in functions related to binding (1125), ion binding (641), intracellular (437) and intracellular parts (428), and organelles (350) and associated with starch and sucrose metabolism, tyrosine metabolism, pyrimidine metabolism, amino sugar and nucleotide sugar metabolism, and isoquinoline alkaloid biosynthesis, as indicated by the GO and KEGG analyses. Among them, the upregulated miR156a, with conserved sequences, was identified as a key DEM that potentially targets and regulates squamosa promoter-binding-like proteins (SPLs, 104889216 and 104897537) through the microRNA-mRNA network. Overexpression of miR156a (MIR) promoted root growth in transgenic Arabidopsis, increasing the length, surface area, and volume. In contrast, silencing miR156a (STTM) had the opposite effect. Notably, the fresh root weight decreased by 45.6% in STTM lines, while it increased by 27.4% in MIR lines, compared to the wild type (WT). It can be inferred that microRNAs, especially miR156, play crucial roles in sugar beet root's development and acclimation to LN conditions. They likely facilitate active responses to N deficiency through network regulation, enabling beet roots to take up nutrients from the environment and sustain their vital life processes.

Productive mRNA Chromatin Escape is Promoted by PRMT5 Methylation of SNRPB

Protein Arginine Methyltransferase 5 (PRMT5) regulates RNA splicing and transcription by symmetric dimethylation of arginine residues (Rme2s/SDMA) in many RNA binding proteins. However, the mechanism by which PRMT5 couples splicing to transcriptional output is unknown. Here, we demonstrate that a major function of PRMT5 activity is to promote chromatin escape of a novel, large class of mRNAs that we term Genomically Retained Incompletely Processed Polyadenylated Transcripts (GRIPPs). Using nascent and total transcriptomics, spike-in controlled fractionated cell transcriptomics, and total and fractionated cell proteomics, we show that PRMT5 inhibition and knockdown of the PRMT5 SNRP (Sm protein) adapter protein pICln (CLNS1A) -but not type I PRMT inhibition-leads to gross detention of mRNA, SNRPB, and SNRPD3 proteins on chromatin. Compared to most transcripts, these chromatin-trapped polyadenylated RNA transcripts have more introns, are spliced slower, and are enriched in detained introns. Using a combination of PRMT5 inhibition and inducible isogenic wildtype and arginine-mutant SNRPB, we show that arginine methylation of these snRNPs is critical for mediating their homeostatic chromatin and RNA interactions. Overall, we conclude that a major role for PRMT5 is in controlling transcript processing and splicing completion to promote chromatin escape and subsequent nuclear export.

The association between thyroid differentiation score and survival outcomes in papillary thyroid carcinoma

BACKGROUND

Thyroid differentiation score (TDS), calculated based on mRNA expression levels of 16 genes controlling thyroid metabolism and function, has been proposed as a measure to quantify differentiation in PTC. The objective of this study is to determine whether TDS is associated with survival outcomes across patient cohorts.

METHODS

Two independent cohorts of PTC patients were used: 1) the Cancer Genome Atlas (TCGA) thyroid cancer study (N=372), 2) MD Anderson Cancer Center (MDACC) cohort (N=111). The primary survival outcome of interest was progression-free interval (PFI). Association with overall survival (OS) was also explored. The Kaplan-Meier method and Cox proportional hazards models were used for survival analyses.

RESULTS

In both cohorts, TDS was associated with tumor and nodal stage at diagnosis as well as tumor driver mutation status. High TDS was associated with longer PFI on univariable analyses across cohorts. After adjusting for overall stage, TDS remained significantly associated with PFI in the MDACC cohort only (aHR 0.67, 95%CI 0.52-0.85). In subgroup analyses stratified by tumor driver mutation status, higher TDS was most consistently associated with longer PFI in BRAFV600E-mutated tumors across cohorts after adjusting for overall stage (TCGA: aHR 0.60, 95% CI: 0.33-1.07; MDACC: aHR 0.59, 95% CI: 0.42-0.82). For OS, increasing TDS was associated with longer OS in the overall MDACC cohort (aHR=0.78, 95% CI:0.63-0.96), where the median duration of follow-up was 12.9 years.

CONCLUSION

TDS quantifies the spectrum of differentiation status in PTC and may serve as a potential prognostic biomarker in PTC, mostly promisingly in BRAFV600E-mutated tumors.

siqRNA-seq is a spike-in-independent technique for quantitative mapping of mRNA landscape

BACKGROUND

RNA sequencing (RNA-seq) is widely used for gene expression profiling and quantification. Quantitative RNA sequencing usually requires cell counting and spike-in, which is not always applicable to many samples. Here, we present a novel quantitative RNA sequencing method independent of spike-ins or cell counting, named siqRNA-seq, which can be used to quantitatively profile gene expression by utilizing gDNA as an internal control. Single-stranded library preparation used in siqRNA-seq profiles gDNA and cDNA with equal efficiency.

RESULTS

To quantify mRNA expression levels, siqRNA-seq constructs libraries for total nucleic acid to establish a model for expression quantification. Compared to Relative Quantification RNA-seq, siqRNA-seq is technically reliable and reproducible for expression profiling but also can sequence reads from gDNA which can be used as an internal reference for accurate expression quantification. Applying siqRNA-seq to investigate the effects of actinomycin D on gene expression in HEK293T cells, we show the advantages of siqRNA-seq in accurately identifying differentially expressed genes between samples with distinct global mRNA levels. Furthermore, we analyzed factors influencing the downward trend of gene expression regulated by ActD using siqRNA-seq and found that mRNA with m6A modification exhibited a faster decay rate compared to mRNA without m6A modification. Additionally, applying this technique to the quantitative analysis of seven tumor cell lines revealed a high degree of diversity in total mRNA expression among tumor cell lines.

CONCLUSIONS

Collectively, siqRNA-seq is a spike-in independent quantitative RNA sequencing method, which creatively uses gDNA as an internal reference to absolutely quantify gene expression. We consider that siqRNA-seq provides a convenient and versatile method to quantitatively profile the mRNA landscape in various samples.

Systematic mapping of organism-scale gene-regulatory networks in aging using population asynchrony

In aging, physiologic networks decline in function at rates that differ between individuals, producing a wide distribution of lifespan. Though 70% of human lifespan variance remains unexplained by heritable factors, little is known about the intrinsic sources of physiologic heterogeneity in aging. To understand how complex physiologic networks generate lifespan variation, new methods are needed. Here, we present Asynch-seq, an approach that uses gene-expression heterogeneity within isogenic populations to study the processes generating lifespan variation. By collecting thousands of single-individual transcriptomes, we capture the Caenorhabditis elegans "pan-transcriptome"-a highly resolved atlas of non-genetic variation. We use our atlas to guide a large-scale perturbation screen that identifies the decoupling of total mRNA content between germline and soma as the largest source of physiologic heterogeneity in aging, driven by pleiotropic genes whose knockdown dramatically reduces lifespan variance. Our work demonstrates how systematic mapping of physiologic heterogeneity can be applied to reduce inter-individual disparities in aging.

Harnessing human microbiomes for disease prediction

The human microbiome has been increasingly recognized as having potential use for disease prediction. Predicting the risk, progression, and severity of diseases holds promise to transform clinical practice, empower patient decisions, and reduce the burden of various common diseases, as has been demonstrated for cardiovascular disease or breast cancer. Combining multiple modifiable and non-modifiable risk factors, including high-dimensional genomic data, has been traditionally favored, but few studies have incorporated the human microbiome into models for predicting the prospective risk of disease. Here, we review research into the use of the human microbiome for disease prediction with a particular focus on prospective studies as well as the modulation and engineering of the microbiome as a therapeutic strategy.

Arabidopsis mRNA export factor MOS11: molecular interactions and role in abiotic stress responses

Transcription and export (TREX) is a multi-subunit complex that links synthesis, processing and export of mRNAs. It interacts with the RNA helicase UAP56 and export factors such as MOS11 and ALYs to facilitate nucleocytosolic transport of mRNAs. Plant MOS11 is a conserved, but sparsely researched RNA-binding export factor, related to yeast Tho1 and mammalian CIP29/SARNP. Using biochemical approaches, the domains of Arabidopsis thaliana MOS11 required for interaction with UAP56 and RNA-binding were identified. Further analyses revealed marked genetic interactions between MOS11 and ALY genes. Cell fractionation in combination with transcript profiling demonstrated that MOS11 is required for export of a subset of mRNAs that are shorter and more GC-rich than MOS11-independent transcripts. The central α-helical domain of MOS11 proved essential for physical interaction with UAP56 and for RNA-binding. MOS11 is involved in the nucleocytosolic transport of mRNAs that are upregulated under stress conditions and accordingly mos11 mutant plants turned out to be sensitive to elevated NaCl concentrations and heat stress. Collectively, our analyses identify functional interaction domains of MOS11. In addition, the results establish that mRNA export is critically involved in the plant response to stress conditions and that MOS11 plays a prominent role at this.

Three steps towards comparability and standardization among molecular methods for characterizing insect communities

Molecular methods are currently some of the best-suited technologies for implementation in insect monitoring. However, the field is developing rapidly and lacks agreement on methodology or community standards. To apply DNA-based methods in large-scale monitoring, and to gain insight across commensurate data, we need easy-to-implement standards that improve data comparability. Here, we provide three recommendations for how to improve and harmonize efforts in biodiversity assessment and monitoring via metabarcoding: (i) we should adopt the use of synthetic spike-ins, which will act as positive controls and internal standards; (ii) we should consider using several markers through a multiplex polymerase chain reaction (PCR) approach; and (iii) we should commit to the publication and transparency of all protocol-associated metadata in a standardized fashion. For (i), we provide a ready-to-use recipe for synthetic cytochrome c oxidase spike-ins, which enable between-sample comparisons. For (ii), we propose two gene regions for the implementation of multiplex PCR approaches, thereby achieving a more comprehensive community description. For (iii), we offer guidelines for transparent and unified reporting of field, wet-laboratory and dry-laboratory procedures, as a key to making comparisons between studies. Together, we feel that these three advances will result in joint quality and calibration standards rather than the current laboratory-specific proof of concepts. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

RNA-seq-based transcriptome profiling of early fruit development in Chieh-qua and analysis of related transcription factors

Chieh-qua (Benincasa hispida Cogn. var. Chieh-qua How.) fruit development starts post pollination. With the continuous expansion of the fruit, the soluble solid content of the fruit decreases. Because there are no reports on the early development of Chieh-qua fruit, this study compared fruit transcriptomes at 0-, 3-, and 7 day post pollination (dpp). 104,747 unigenes were assembled from clean reads and compared using six public databases for similarity searching. Compared with those of 0 dpp (C), there were differences in the expression of 12,982 and 6541 genes in the fruit tissue at 3 dpp and 7 dpp, respectively. Compared with 3 dpp (B), there were 14,314 differentially expressed genes in the fruit at 7 dpp (A). Based on the analysis of transcription factors, 213 nucleotides in the MYB superfamily were identified; among them, 94 unigenes of the MYB superfamily were differentially expressed at the three stages. In the pairwise comparison of differential expression, eight unigenes (Gene_id: TRINITY_DN32880_c1_g2, TRINITY_DN35142_c2_g2, TRINITY_DN32454_c11_g6, TRINITY_DN34105_c2_g7, TRINITY_DN32758_c3_g3, TRINITY_DN33604_c4_g10, TRINITY_DN34466_c3_g1, TRINITY_DN35924_c3_g2) were homologous to those of MYB59, MYB-GT3b, MYB18, MYB4, MYB108, MYB306, MYB340, and MYB-bHLH13. These unigenes differed significantly among the three stages. Furthermore, MYB59 and MYB18 exhibited higher expression at 7 dpp. MYB4, MYB-GT3b, MYB108, and MYB306 showed the highest expression levels in fruits at 3 dpp. In addition, MYB340 and MYB-bHLH13 showed higher expression levels during the unpollinated stage. MYB59, MYB-GT3b, MYB18, MYB4, MYB108, MYB306, MYB340, and MYB-bHLH13 may play crucial roles in Chieh-qua fruit development, defense, and blossoming. This study provides a basis for further investigation of MYB superfamily genes involved in early fruit expansion in chieh-qua.

Comparative transcriptomic analysis of Staphylococcus epidermidis associated with periprosthetic joint infection under in vivo and in vitro conditions

Staphylococcus epidermidis is part of the commensal microbiota of the skin and mucous membranes, though it can also act as a pathogen in certain scenarios, causing a range of infections, including periprosthetic joint infection (PJI). Transcriptomic profiling may provide insights into mechanisms by which S. epidermidis adapts while in a pathogenic compared to a commensal state. Here, a total RNA-sequencing approach was used to profile and compare the transcriptomes of 19 paired PJI-associated S. epidermidis samples from an in vivo clinical source and grown in in vitro laboratory culture. Genomic comparison of PJI-associated and publicly available commensal-state isolates were also compared. Of the 1919 total transcripts found, 145 were from differentially expressed genes (DEGs) when comparing in vivo or in vitro samples. Forty-two transcripts were upregulated and 103 downregulated in in vivo samples. Of note, metal sequestration-associated genes, specifically those related to staphylopine activity (cntA, cntK, cntL, and cntM), were upregulated in a subset of clinical in vivo compared to laboratory grown in vitro samples. About 70% of the total transcripts and almost 50% of the DEGs identified have not yet been annotated. There were no significant genomic differences between known commensal and PJI-associated S. epidermidis isolates, suggesting that differential genomics may not play a role in S. epidermidis pathogenicity. In conclusion, this study provides insights into phenotypic alterations employed by S epidermidis to adapt to infective and non-infected microenvironments, potentially informing future therapeutic targets for related infections.

A normalization method that controls for total RNA abundance affects the identification of differentially expressed genes, revealing bias toward morning-expressed responses

RNA-Sequencing is widely used to investigate changes in gene expression at the transcription level in plants. Most plant RNA-Seq analysis pipelines base the normalization approaches on the assumption that total transcript levels do not vary between samples. However, this assumption has not been demonstrated. In fact, many common experimental treatments and genetic alterations affect transcription efficiency or RNA stability, resulting in unequal transcript abundance. The addition of synthetic RNA controls is a simple correction that controls for variation in total mRNA levels. However, adding spike-ins appropriately is challenging with complex plant tissue, and carefully considering how they are added is essential to their successful use. We demonstrate that adding external RNA spike-ins as a normalization control produces differences in RNA-Seq analysis compared to traditional normalization methods, even between two times of day in untreated plants. We illustrate the use of RNA spike-ins with 3' RNA-Seq and present a normalization pipeline that accounts for differences in total transcriptional levels. We evaluate the effect of normalization methods on identifying differentially expressed genes in the context of identifying the effect of the time of day on gene expression and response to chilling stress in sorghum.

Unleashed monocytic engagement in Sézary syndrome during the combination of anti-CCR4 antibody with type I interferon

ABSTRACT

Sézary syndrome (SS) is an aggressive leukemic expansion of skin-derived malignant CD4+ T cells. Drug monotherapy often results in disease relapse because of the heterogenous nature of malignant CD4+ T cells, but how therapies can be optimally combined remains unclear because of limitations in understanding the disease pathogenesis. We identified immunologic transitions that interlink mycosis fungoides with SS using single-cell transcriptome analysis in parallel with high-throughput T-cell receptor sequencing. Nascent peripheral CD4+ T cells acquired a distinct profile of transcription factors and trafficking receptors that gave rise to antigenically mature Sézary cells. The emergence of malignant CD4+ T cells coincided with the accumulation of dysfunctional monocytes with impaired fragment crystallizable γ-dependent phagocytosis, decreased responsiveness to cytokine stimulation, and limited repertoire of intercellular interactions with Sézary cells. Type I interferon supplementation when combined with a monoclonal antibody targeting the chemokine receptor type 4 (CCR4), unleashed monocyte induced phagocytosis and eradication of Sézary cells in vitro. In turn, coadministration of interferon-α with the US Food and Drug Administration-approved anti-CCR4 antibody, mogamulizumab, in patients with SS induced marked depletion of peripheral malignant CD4+ T cells. Importantly, residual CD4+ T cells after Sézary cell ablation lacked any immunologic shifts. These findings collectively unveil an auxiliary role for augmenting monocytic activity during mogamulizumab therapy in the treatment of SS and underscore the importance of targeted combination therapy in this disease.

Analyzing RNA-Seq Data from Chlamydia with Super Broad Transcriptomic Activation: Challenges, Solutions, and Implications for Other Systems

Motivation

RNA sequencing (RNA-Seq) offers profound insights into the complex transcriptomes of diverse biological systems. However, standard differential expression analysis pipelines based on DESeq2 and edgeR encounter challenges when applied to the immediate early transcriptomes of Chlamydia spp., obligate intracellular bacteria. These challenges arise from their reliance on assumptions that do not hold in scenarios characterized by extensive transcriptomic activation and limited repression. Standard analyses using unique chlamydial RNA-Seq reads alone identify nearly 300 upregulated and about 300 downregulated genes, significantly deviating from actual RNA-Seq read trends.

Results

By incorporating both chlamydial and host reads or adjusting for total sequencing depth, the revised normalization methods each detected over 700 upregulated genes and 30 or fewer downregulated genes, closely aligned with observed RNA-Seq data. Further validation through qRT-PCR analysis confirmed the effectiveness of these adjusted approaches in capturing the true extent of transcriptomic activation during the immediate early phase of chlamydial infection. While the strategies employed are developed in the context of Chlamydia, the principles of flexible and context-aware normalization may inform adjustments in other systems with unbalanced gene expression dynamics, such as bacterial spore germination.

Availability and implementation

The code for reproducing the presented bioinformatic analysis is available at https://zenodo.org/records/11201379.

Deciphering Tumor Cell Evolution in Cutaneous T-Cell Lymphomas: Distinct Differentiation Trajectories in Mycosis Fungoides and Sézary Syndrome

Cutaneous T-cell lymphomas are a heterogeneous group of neoplasms originating in the skin, with mycosis fungoides (MF) and Sézary syndrome (SS) representing the most common variants. The cellular origin of cutaneous lymphomas has remained controversial owing to their immense phenotypic heterogeneity that obfuscates lineage reconstruction on the basis of classical surface biomarkers. To overcome this heterogeneity and reconstruct the differentiation trajectory of malignant cells in MF and SS, TCR sequencing was performed in parallel with targeted transcriptomics at the single-cell resolution among cutaneous samples in MF and SS. Unsupervised lineage reconstruction showed that Sézary cells exist as a population of CD4+ T cells distinct from those in patch, plaque, and tumor MF. Further investigation of malignant cell heterogeneity in SS showed that Sézary cells phenotypically comprised at least 3 subsets on the basis of differential proliferation potentials and expression of exhaustion markers. A T helper 1-polarized cell type, intermediate cell type, and exhausted T helper 2-polarized cell type were identified, with T helper 1- and T helper 2-polarized cells displaying divergent proliferation potentials. Collectively, these findings provide evidence to clarify the relationship between MF and SS and reveal cell subsets in SS that suggest a possible mechanism for therapeutic resistance.

Improved RNA stability estimation through Bayesian modeling reveals most Salmonella transcripts have subminute half-lives

RNA decay is a crucial mechanism for regulating gene expression in response to environmental stresses. In bacteria, RNA-binding proteins (RBPs) are known to be involved in posttranscriptional regulation, but their global impact on RNA half-lives has not been extensively studied. To shed light on the role of the major RBPs ProQ and CspC/E in maintaining RNA stability, we performed RNA sequencing of Salmonella enterica over a time course following treatment with the transcription initiation inhibitor rifampicin (RIF-seq) in the presence and absence of these RBPs. We developed a hierarchical Bayesian model that corrects for confounding factors in rifampicin RNA stability assays and enables us to identify differentially decaying transcripts transcriptome-wide. Our analysis revealed that the median RNA half-life in Salmonella in early stationary phase is less than 1 min, a third of previous estimates. We found that over half of the 500 most long-lived transcripts are bound by at least one major RBP, suggesting a general role for RBPs in shaping the transcriptome. Integrating differential stability estimates with cross-linking and immunoprecipitation followed by RNA sequencing (CLIP-seq) revealed that approximately 30% of transcripts with ProQ binding sites and more than 40% with CspC/E binding sites in coding or 3' untranslated regions decay differentially in the absence of the respective RBP. Analysis of differentially destabilized transcripts identified a role for ProQ in the oxidative stress response. Our findings provide insights into posttranscriptional regulation by ProQ and CspC/E, and the importance of RBPs in regulating gene expression.

Transcriptome analysis of polyploid giant cancer cells and their progeny reveals a functional role for p21 in polyploidization and depolyploidization

Polyploid giant cancer cells (PGCC) are frequently detected in tumors and are increasingly recognized for their roles in chromosomal instability and associated genome evolution that leads to cancer recurrence. We previously reported that therapy stress promotes polyploidy, and that acid ceramidase plays a role in depolyploidization. In this study, we used an RNA-seq approach to gain a better understanding of the underlying transcriptomic changes that occur as cancer cells progress through polyploidization and depolyploidization. Our results revealed gene signatures that are associated with disease-free and/or overall survival in several cancers and identified the cell cycle inhibitor CDKN1A/p21 as the major hub in PGCC and early progeny. Increased expression of p21 in PGCC was limited to the cytoplasm. We previously demonstrated that the sphingolipid enzyme acid ceramidase is dispensable for polyploidization upon therapy stress but plays a crucial role in depolyploidization. The current study demonstrates that treatment of cells with ceramide is not sufficient for p53-independent induction of p21 and that knockdown of acid ceramidase, which hydrolyzes ceramide, does not interfere with upregulation of p21. In contrast, blocking the expression of p21 with UC2288 prevented the induction of acid ceramidase and inhibited both the formation of PGCC from parental cells as well as the generation of progeny from PGCC. Taken together, our data suggest that p21 functions upstream of acid ceramidase and plays an important role in polyploidization and depolyploidization.

A universal molecular control for DNA, mRNA and protein expression

The expression of genes encompasses their transcription into mRNA followed by translation into protein. In recent years, next-generation sequencing and mass spectrometry methods have profiled DNA, RNA and protein abundance in cells. However, there are currently no reference standards that are compatible across these genomic, transcriptomic and proteomic methods, and provide an integrated measure of gene expression. Here, we use synthetic biology principles to engineer a multi-omics control, termed pREF, that can act as a universal molecular standard for next-generation sequencing and mass spectrometry methods. The pREF sequence encodes 21 synthetic genes that can be in vitro transcribed into spike-in mRNA controls, and in vitro translated to generate matched protein controls. The synthetic genes provide qualitative controls that can measure sensitivity and quantitative accuracy of DNA, RNA and peptide detection. We demonstrate the use of pREF in metagenome DNA sequencing and RNA sequencing experiments and evaluate the quantification of proteins using mass spectrometry. Unlike previous spike-in controls, pREF can be independently propagated and the synthetic mRNA and protein controls can be sustainably prepared by recipient laboratories using common molecular biology techniques. Together, this provides a universal synthetic standard able to integrate genomic, transcriptomic and proteomic methods.

Early assessment of fungal and oomycete pathogens in greenhouse irrigation water using Oxford nanopore amplicon sequencing

Water-borne plant pathogenic fungi and oomycetes are a major threat in greenhouse production systems. Early detection and quantification of these pathogens would enable us to ascertain both economic and biological thresholds required for a timely treatment, thus improving effective disease management. Here, we used Oxford nanopore MinION amplicon sequencing to analyze microbial communities in irrigation water collected from greenhouses used for growing tomato, cucumber and Aeschynanthus sp. Fungal and oomycete communities were characterized using primers that amplify the full internal transcribed spacer (ITS) region. To assess the sensitivity of the MinION sequencing, we spiked serially diluted mock DNA into the DNA isolated from greenhouse water samples prior to library preparation. Relative abundances of fungal and oomycete reads were distinct in the greenhouse irrigation water samples and in water samples from setups with tomato that was inoculated with Fusarium oxysporum. Sequence reads derived from fungal and oomycete mock communities were proportionate in the respective serial dilution samples, thus confirming the suitability of MinION amplicon sequencing for environmental monitoring. By using spike-ins as standards to test the reliability of quantification using the MinION, we found that the detection of spike-ins was highly affected by the background quantities of fungal or oomycete DNA in the sample. We observed that spike-ins having shorter length (538bp) produced reads across most of our dilutions compared to the longer spikes (>790bp). Moreover, the sequence reads were uneven with respect to dilution series and were least retrievable in the background samples having the highest DNA concentration, suggesting a narrow dynamic range of performance. We suggest continuous benchmarking of the MinION sequencing to improve quantitative metabarcoding efforts for rapid plant disease diagnostic and monitoring in the future.

Validation of the VirCapSeq-VERT system for differential diagnosis, detection, and surveillance of viral infections

IMPORTANCE

Broad range assay for accurate and sensitive diagnostics.

Internal and external normalization of nascent RNA sequencing run-on experiments

In experiments with significant perturbations to transcription, nascent RNA sequencing protocols are dependent on external spike-ins for reliable normalization. Unlike in RNA-seq, these spike-ins are not standardized and, in many cases, depend on a run-on reaction that is assumed to have constant efficiency across samples. To assess the validity of this assumption, we analyze a large number of published nascent RNA spike-ins to quantify their variability across existing normalization methods. Furthermore, we develop a new biologically-informed Bayesian model to estimate the error in spike-in based normalization estimates, which we term Virtual Spike-In (VSI). We apply this method both to published external spike-ins as well as using reads at the [Formula: see text] end of long genes, building on prior work from Mahat (Mol Cell 62(1):63-78, 2016. https://doi.org/10.1016/j.molcel.2016.02.025 ) and Vihervaara (Nat Commun 8(1):255, 2017. https://doi.org/10.1038/s41467-017-00151-0 ). We find that spike-ins in existing nascent RNA experiments are typically under sequenced, with high variability between samples. Furthermore, we show that these high variability estimates can have significant downstream effects on analysis, complicating biological interpretations of results.

Differentially expressed platelet activation-related genes in dogs with stage B2 myxomatous mitral valve disease

BACKGROUND

Peripheral blood carries a reservoir of mRNAs that regulate cardiac structure and function potential. Although it is well recognized that the typical symptoms of Myxomatous Mitral Valve Disease (MMVD) stage B2 are long-standing hemodynamic disorder and cardiac structure remodeling caused by mitral regurgitation, the transcriptomic alterations in blood from such dogs are not understood.

RESULTS

In the present study, comparative high-throughput transcriptomic profiling of blood was performed from normal control (NC) and naturally-occurring MMVD stage B2 (MMVD) dogs. Using Weighted Gene Co-expression Network Analyses (WGCNA), Gene Ontology (GO), and Kyoto Encyclopedia of Gene and Genomes (KEGG), we identified that the turquoise module was the most highly correlated with echocardiographic features and found 64 differentially expressed genes (DEGs) that were significantly enriched in platelet activation related pathways. Therefore, from the turquoise module, we selected five DEGs (MDM2, ROCK1, RIPK1, SNAP23, and ARHGAP35) that, according to real-time qPCR, exhibited significant enrichment in platelet activation related pathways for validation. The results showed that the blood transcriptional abundance of MDM2, ROCK1, RIPK1, and SNAP23 differed significantly (P < 0.01) between NC and MMVD dogs. On the other hand, Correlation Analysis revealed that MDM2, ROCK1, RIPK1, and SNAP23 genes negatively regulated the heart structure parameters, and followed the same trend as observed in WGCNA.

CONCLUSION

We screened four platelet activation related genes, MDM2, ROCK1, RIPK1, and SNAP23, which may be considered as the candidate biomarkers for the diagnosis of MMVD stage B2. These findings provided new insights into MMVD pathogenesis.

Transcriptome-wide profiling of acute stress induced changes in ribosome occupancy level using external standards

Acute cellular stress is known to induce a global reduction in mRNA translation through suppression of cap dependent translation. Selective translation in response to acute stress has been shown to play important roles in regulating the stress response. However, accurately profiling translational changes transcriptome-wide in response to acute cellular stress has been challenging. Commonly used data normalization methods operate on the assumption that any systematic shifts are experimental artifacts. Consequently, if applied to profiling acute cellular stress-induced mRNA translation changes, these methods are expected to produce biased estimates. To address this issue, we designed, produced, and evaluated a panel of 16 oligomers to serve as external standards for ribosome profiling studies. Using Sodium Arsenite treatment-induced oxidative stress in lymphoblastoid cell lines as a model system, we applied spike-in oligomers as external standards. We found our spike-in oligomers to display a strong linear correlation between the observed and the expected quantification, with small ratio compression at the lower concentration range. Using the expected fold changes constructed from spike-in controls, we found in our dataset that TMM normalization, a popular global scaling normalization approach, produced 87.5% false positives at a significant cutoff that is expected to produce only 10% false positive discoveries. In addition, TMM normalization produced a systematic shift of fold change by 3.25 fold. These results highlight the consequences of applying global scaling approaches to conditions that clearly violate their key assumptions. In contrast, we found RUVg normalization using spike-in oligomers as control genes recapitulated the expected stress induced global reduction of translation and resulted in little, if any, systematic shifts in the expected fold change. Our results clearly demonstrated the utility of our spike-in oligomers, both for constructing expected results as controls and for data normalization.

Development of constitutively synergistic nanoformulations to enhance chemosensitivity in T-cell leukemia

Advances in multiagent chemotherapy have led to recent improvements in survival for patients with acute lymphoblastic leukemia (ALL); however, a significant fraction do not respond to frontline chemotherapy or later relapse with recurrent disease, after which long-term survival rates remain low. To develop new, effective treatment options for these patients, we conducted a series of high-throughput combination drug screens to identify chemotherapies that synergize in a lineage-specific manner with MRX-2843, a small molecule dual MERTK and FLT3 kinase inhibitor currently in clinical testing for treatment of relapsed/refractory leukemias and solid tumors. Using experimental and computational approaches, we found that MRX-2843 synergized strongly-and in a ratio-dependent manner-with vincristine to inhibit both B-ALL and T-ALL cell line expansion. Based on these findings, we developed multiagent lipid nanoparticle formulations of these drugs that not only delivered defined drug ratios intracellularly in T-ALL, but also improved anti-leukemia activity following drug encapsulation. Synergistic and additive interactions were recapitulated in primary T-ALL patient samples treated with MRX-2843 and vincristine nanoparticle formulations, suggesting their clinical relevance. Moreover, the nanoparticle formulations reduced disease burden and prolonged survival in an orthotopic murine xenograft model of early thymic precursor T-ALL (ETP-ALL), with both agents contributing to therapeutic activity in a dose-dependent manner. In contrast, nanoparticles containing MRX-2843 alone were ineffective in this model. Thus, MRX-2843 increased the sensitivity of ETP-ALL cells to vincristine in vivo. In this context, the additive particles, containing a higher dose of MRX-2843, provided more effective disease control than the synergistic particles. In contrast, particles containing an even higher, antagonistic ratio of MRX-2843 and vincristine were less effective. Thus, both the drug dose and the ratio-dependent interaction between MRX-2843 and vincristine significantly impacted therapeutic activity in vivo. Together, these findings present a systematic approach to high-throughput combination drug screening and multiagent drug delivery that maximizes the therapeutic potential of combined MRX-2843 and vincristine in T-ALL and describe a novel translational agent that could be used to enhance therapeutic responses to vincristine in patients with T-ALL. This broadly generalizable approach could also be applied to develop other constitutively synergistic combination products for the treatment of cancer and other diseases.

Determining the Contribution of Micro/Nanoplastics to Antimicrobial Resistance: Challenges and Perspectives

Microorganisms colonizing the surfaces of microplastics form a plastisphere in the environment, which captures miscellaneous substances. The plastisphere, owning to its inherently complex nature, may serve as a "Petri dish" for the development and dissemination of antibiotic resistance genes (ARGs), adding a layer of complexity in tackling the global challenge of both microplastics and ARGs. Increasing studies have drawn insights into the extent to which the proliferation of ARGs occurred in the presence of micro/nanoplastics, thereby increasing antimicrobial resistance (AMR). However, a comprehensive review is still lacking in consideration of the current increasingly scattered research focus and results. This review focuses on the spread of ARGs mediated by microplastics, especially on the challenges and perspectives on determining the contribution of microplastics to AMR. The plastisphere accumulates biotic and abiotic materials on the persistent surfaces, which, in turn, offers a preferred environment for gene exchange within and across the boundary of the plastisphere. Microplastics breaking down to smaller sizes, such as nanoscale, can possibly promote the horizontal gene transfer of ARGs as environmental stressors by inducing the overgeneration of reactive oxygen species. Additionally, we also discussed methods, especially quantitatively comparing ARG profiles among different environmental samples in this emerging field and the challenges that multidimensional parameters are in great necessity to systematically determine the antimicrobial dissemination risk in the plastisphere. Finally, based on the biological sequencing data, we offered a framework to assess the AMR risks of micro/nanoplastics and biocolonizable microparticles that leverage multidimensional AMR-associated messages, including the ARGs' abundance, mobility, and potential acquisition by pathogens.

TEQUILA-seq: a versatile and low-cost method for targeted long-read RNA sequencing

Long-read RNA sequencing (RNA-seq) is a powerful technology for transcriptome analysis, but the relatively low throughput of current long-read sequencing platforms limits transcript coverage. One strategy for overcoming this bottleneck is targeted long-read RNA-seq for preselected gene panels. We present TEQUILA-seq, a versatile, easy-to-implement, and low-cost method for targeted long-read RNA-seq utilizing isothermally linear-amplified capture probes. When performed on the Oxford nanopore platform with multiple gene panels of varying sizes, TEQUILA-seq consistently and substantially enriches transcript coverage while preserving transcript quantification. We profile full-length transcript isoforms of 468 actionable cancer genes across 40 representative breast cancer cell lines. We identify transcript isoforms enriched in specific subtypes and discover novel transcript isoforms in extensively studied cancer genes such as TP53. Among cancer genes, tumor suppressor genes (TSGs) are significantly enriched for aberrant transcript isoforms targeted for degradation via mRNA nonsense-mediated decay, revealing a common RNA-associated mechanism for TSG inactivation. TEQUILA-seq reduces the per-reaction cost of targeted capture by 2-3 orders of magnitude, as compared to a standard commercial solution. TEQUILA-seq can be broadly used for targeted sequencing of full-length transcripts in diverse biomedical research settings.

spinDrop: a droplet microfluidic platform to maximise single-cell sequencing information content

Droplet microfluidic methods have massively increased the throughput of single-cell sequencing campaigns. The benefit of scale-up is, however, accompanied by increased background noise when processing challenging samples and the overall RNA capture efficiency is lower. These drawbacks stem from the lack of strategies to enrich for high-quality material or specific cell types at the moment of cell encapsulation and the absence of implementable multi-step enzymatic processes that increase capture. Here we alleviate both bottlenecks using fluorescence-activated droplet sorting to enrich for droplets that contain single viable cells, intact nuclei, fixed cells or target cell types and use reagent addition to droplets by picoinjection to perform multi-step lysis and reverse transcription. Our methodology increases gene detection rates fivefold, while reducing background noise by up to half. We harness these properties to deliver a high-quality molecular atlas of mouse brain development, despite starting with highly damaged input material, and provide an atlas of nascent RNA transcription during mouse organogenesis. Our method is broadly applicable to other droplet-based workflows to deliver sensitive and accurate single-cell profiling at a reduced cost.

Effect of Fibroblast Growth Factor 10 and an Interacting Non-Coding RNA on Secondary Hair Follicle Dermal Papilla Cells in Cashmere Goats' Follicle Development Assessed by Whole-Transcriptome Sequencing Technology

Cashmere, a keratinised product of secondary hair follicles (SHFs) in cashmere goats, holds an important place in international high-end textiles. However, research on the complex molecular and signal regulation during the development and growth of hair follicles (HFs), which is essential for the development of the cashmere industry, is limited. Moreover, increasing evidence indicates that non-coding RNAs (ncRNAs) participate in HF development. Herein, we systematically investigated a competing endogenous RNA (ceRNA) regulatory network mediated by circular RNAs (circRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) in skin samples of cashmere goat embryos, using whole-transcriptome sequencing technology. We obtained 6468, 394, and 239 significantly differentially expressed mRNAs, circRNAs, and miRNAs, respectively. These identified RNAs were further used to construct a ceRNA regulatory network, mediated by circRNAs, for cashmere goats at a late stage of HF development. Among the molecular species identified, miR-184 and fibroblast growth factor (FGF) 10 exhibited competitive targeted interactions. In secondary HF dermal papilla cells (SHF-DPCs), miR-184 promotes proliferation, inhibits apoptosis, and alters the cell cycle via the competitive release of FGF10. This study reports that FGF10 and its interaction with ncRNAs significantly affect SHF-DPCs, providing a reference for research on the biology of HFs in cashmere goats and other mammals.

Identification of inhibitors for the transmembrane Trypanosoma cruzi eIF2α kinase relevant for parasite proliferation

The TcK2 protein kinase of Trypanosoma cruzi, the causative agent of Chagas disease, is structurally similar to the human kinase PERK, which phosphorylates the initiation factor eIF2α and, in turn, inhibits translation initiation. We have previously shown that absence of TcK2 kinase impairs parasite proliferation within mammalian cells, positioning it as a potential target for treatment of Chagas disease. To better understand its role in the parasite, here we initially confirmed the importance of TcK2 in parasite proliferation by generating CRISPR/Cas9 TcK2-null cells, albeit they more efficiently differentiate into infective forms. Proteomics indicates that the TcK2 knockout of proliferative forms expresses proteins including trans-sialidases, normally restricted to infective and nonproliferative trypomastigotes explaining decreased proliferation and better differentiation. TcK2 knockout cells lost phosphorylation of eukaryotic initiation factor 3 and cyclic AMP responsive-like element, recognized to promote growth, likely explaining both decreased proliferation and augmented differentiation. To identify specific inhibitors, a library of 379 kinase inhibitors was screened by differential scanning fluorimetry using a recombinant TcK2 encompassing the kinase domain and selected molecules were tested for kinase inhibition. Only Dasatinib and PF-477736, inhibitors of Src/Abl and ChK1 kinases, showed inhibitory activity with IC50 of 0.2 ± 0.02 mM and 0.8 ± 0.1, respectively. In infected cells Dasatinib inhibited growth of parental amastigotes (IC50 = 0.6 ± 0.2 mM) but not TcK2 of depleted parasites (IC50 > 34 mM) identifying Dasatinib as a potential lead for development of therapeutics for Chagas disease targeting TcK2.

Fixation and Laser Capture Microdissection of Plant Tissue for RNA Extraction and RNASeq Library Preparation

To study the transcriptome of individual plant cells at specific points in time, we developed protocols for fixation, embedding, and sectioning of plant tissue followed by laser capture microdissection (LCM) and processing for RNA recovery. LCM allows the isolation of individual cell types from heterogeneous tissue sections and is particularly suited to plant processing because it does not require the breakdown of cell walls. This approach allows accurate separation of a small volume of cells that can be used to study gene expression profiles in different tissues or cell layers. The technique requires neither separation of cells by enzymatic digestion of any kind nor cell-specific reporter genes, and it allows storage of fixed and embedded tissue for months before capture. The methods for fixation, embedding, sectioning, and capturing of plant cells that we describe yield high-quality RNA suitable for making libraries for RNASeq. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Tissue Preparation for Laser Capture Microdissection Basic Protocol 2: Tissue Sectioning Basic Protocol 3: Laser Capture Microdissection of Embedded Tissue Basic Protocol 4: RNA Extraction from Laser Capture Microdissection Samples.

Foreign RNA spike-ins enable accurate allele-specific expression analysis at scale

MOTIVATION

Analysis of allele-specific expression is strongly affected by the technical noise present in RNA-seq experiments. Previously, we showed that technical replicates can be used for precise estimates of this noise, and we provided a tool for correction of technical noise in allele-specific expression analysis. This approach is very accurate but costly due to the need for two or more replicates of each library. Here, we develop a spike-in approach which is highly accurate at only a small fraction of the cost.

RESULTS

We show that a distinct RNA added as a spike-in before library preparation reflects technical noise of the whole library and can be used in large batches of samples. We experimentally demonstrate the effectiveness of this approach using combinations of RNA from species distinguishable by alignment, namely, mouse, human, and Caenorhabditis elegans. Our new approach, controlFreq, enables highly accurate and computationally efficient analysis of allele-specific expression in (and between) arbitrarily large studies at an overall cost increase of ∼5%.

AVAILABILITY AND IMPLEMENTATION

Analysis pipeline for this approach is available at GitHub as R package controlFreq (github.com/gimelbrantlab/controlFreq).

Integrated multi-omics analyses reveal homology-directed repair pathway as a unique dependency in near-haploid leukemia

Whole chromosome losses resulting in near-haploid karyotypes are found in a rare subgroup of treatment-refractory acute lymphoblastic leukemia. To systematically dissect the unique physiology and uncover susceptibilities that can be exploited in near-haploid leukemia, we leveraged single-cell RNA-Seq and computational inference of cell cycle stages to pinpoint key differences between near-haploid and diploid leukemia cells. Combining cell cycle stage-specific differential expression with gene essentiality scores from a genome-wide CRISPR-Cas9-mediated knockout screen, we identified the homologous recombination pathway component RAD51B as an essential gene in near-haploid leukemia. DNA damage analyses revealed significantly increased sensitivity of RAD51-mediated repair to RAD51B loss in the G2/M stage of near-haploid cells, suggesting a unique role of RAD51B in the homologous recombination pathway. Elevated G2/M and G1/S checkpoint signaling was part of a RAD51B signature expression program in response to chemotherapy in a xenograft model of human near-haploid B-ALL, and RAD51B and its associated programs were overexpressed in a large panel of near-haploid B-ALL patients. These data highlight a unique genetic dependency on DNA repair machinery in near-haploid leukemia and demarcate RAD51B as a promising candidate for targeted therapy in this treatment-resistant disease.

High-Quality Chromosome-Level Genome Assembly of the Corsac Fox (Vulpes corsac) Reveals Adaptation to Semiarid and Harsh Environments

The Corsac fox (Vulpes corsac) is a species of fox distributed in the arid prairie regions of Central and Northern Asia, with distinct adaptations to dry environments. Here, we applied Oxford-Nanopore sequencing and a chromosome structure capture technique to assemble the first Corsac fox genome, which was then assembled into chromosome fragments. The genome assembly has a total length of 2.2 Gb with a contig N50 of 41.62 Mb and a scaffold N50 of 132.2 Mb over 18 pseudo-chromosomal scaffolds. The genome contained approximately 32.67% of repeat sequences. A total of 20,511 protein-coding genes were predicted, of which 88.9% were functionally annotated. Phylogenetic analyses indicated a close relation to the Red fox (Vulpes vulpes) with an estimated divergence time of ~3.7 million years ago (MYA). We performed separate enrichment analyses of species-unique genes, the expanded and contracted gene families, and positively selected genes. The results suggest an enrichment of pathways related to protein synthesis and response and an evolutionary mechanism by which cells respond to protein denaturation in response to heat stress. The enrichment of pathways related to lipid and glucose metabolism, potentially preventing stress from dehydration, and positive selection of genes related to vision, as well as stress responses in harsh environments, may reveal adaptive evolutionary mechanisms in the Corsac fox under harsh drought conditions. Additional detection of positive selection for genes associated with gustatory receptors may reveal a unique desert diet strategy for the species. This high-quality genome provides a valuable resource for studying mammalian drought adaptation and evolution in the genus Vulpes.

Transcriptional-translational conflict is a barrier to cellular transformation and cancer progression

We uncover a tumor-suppressive process in urothelium called transcriptional-translational conflict caused by deregulation of the central chromatin remodeling component ARID1A. Loss of Arid1a triggers an increase in a nexus of pro-proliferation transcripts, but a simultaneous inhibition of the eukaryotic elongation factor 2 (eEF2), which results in tumor suppression. Resolution of this conflict through enhancing translation elongation speed enables the efficient and precise synthesis of a network of poised mRNAs resulting in uncontrolled proliferation, clonogenic growth, and bladder cancer progression. We observe a similar phenomenon in patients with ARID1A-low tumors, which also exhibit increased translation elongation activity through eEF2. These findings have important clinical implications because ARID1A-deficient, but not ARID1A-proficient, tumors are sensitive to pharmacologic inhibition of protein synthesis. These discoveries reveal an oncogenic stress created by transcriptional-translational conflict and provide a unified gene expression model that unveils the importance of the crosstalk between transcription and translation in promoting cancer.

Applying causal discovery to single-cell analyses using CausalCell

Correlation between objects is prone to occur coincidentally, and exploring correlation or association in most situations does not answer scientific questions rich in causality. Causal discovery (also called causal inference) infers causal interactions between objects from observational data. Reported causal discovery methods and single-cell datasets make applying causal discovery to single cells a promising direction. However, evaluating and choosing causal discovery methods and developing and performing proper workflow remain challenges. We report the workflow and platform CausalCell (http://www.gaemons.net/causalcell/causalDiscovery/) for performing single-cell causal discovery. The workflow/platform is developed upon benchmarking four kinds of causal discovery methods and is examined by analyzing multiple single-cell RNA-sequencing (scRNA-seq) datasets. Our results suggest that different situations need different methods and the constraint-based PC algorithm with kernel-based conditional independence tests work best in most situations. Related issues are discussed and tips for best practices are given. Inferred causal interactions in single cells provide valuable clues for investigating molecular interactions and gene regulations, identifying critical diagnostic and therapeutic targets, and designing experimental and clinical interventions.

Sex-Biased Expression Is Associated With Chromatin State in Drosophila melanogaster and Drosophila simulans

In Drosophila melanogaster and D. simulans head tissue, 60% of orthologous genes show evidence of sex-biased expression in at least one species. Of these, ∼39% (2,192) are conserved in direction. We hypothesize enrichment of open chromatin in the sex where we see expression bias and closed chromatin in the opposite sex. Male-biased orthologs are significantly enriched for H3K4me3 marks in males of both species (∼89% of male-biased orthologs vs. ∼76% of unbiased orthologs). Similarly, female-biased orthologs are significantly enriched for H3K4me3 marks in females of both species (∼90% of female-biased orthologs vs. ∼73% of unbiased orthologs). The sex-bias ratio in female-biased orthologs was similar in magnitude between the two species, regardless of the closed chromatin (H3K27me2me3) marks in males. However, in male-biased orthologs, the presence of H3K27me2me3 in both species significantly reduced the correlation between D. melanogaster sex-bias ratio and the D. simulans sex-bias ratio. Male-biased orthologs are enriched for evidence of positive selection in the D. melanogaster group. There are more male-biased genes than female-biased genes in both species. For orthologs with gains/losses of sex-bias between the two species, there is an excess of male-bias compared to female-bias, but there is no consistent pattern in the relationship between H3K4me3 or H3K27me2me3 chromatin marks and expression. These data suggest chromatin state is a component of the maintenance of sex-biased expression and divergence of sex-bias between species is reflected in the complexity of the chromatin status.

Foreign RNA spike-ins enable accurate allele-specific expression analysis at scale

Motivation

Analysis of allele-specific expression is strongly affected by the technical noise present in RNA-seq experiments. Previously, we showed that technical replicates can be used for precise estimates of this noise, and we provided a tool for correction of technical noise in allele-specific expression analysis. This approach is very accurate but costly due to the need for two or more replicates of each library. Here, we develop a spike-in approach that is highly accurate at only a small fraction of the cost.

Results

We show that a distinct RNA added as a spike-in before library preparation reflects technical noise of the whole library and can be used in large batches of samples. We experimentally demonstrate the effectiveness of this approach using combinations of RNA from species distinguishable by alignment, namely, mouse, human, and C.elegans . Our new approach, controlFreq , enables highly accurate and computationally efficient analysis of allele-specific expression in (and between) arbitrarily large studies at an overall cost increase of ~ 5%.

Availability

Analysis pipeline for this approach is available at GitHub as R package controlFreq ( github.com/gimelbrantlab/controlFreq ).

Contact

agimelbrant@altius.org.

The ETS transcription factor ETV6 constrains the transcriptional activity of EWS-FLI to promote Ewing sarcoma

Transcription factors (TFs) are frequently mutated in cancer. Paediatric cancers exhibit few mutations genome-wide but frequently harbour sentinel mutations that affect TFs, which provides a context to precisely study the transcriptional circuits that support mutant TF-driven oncogenesis. A broadly relevant mechanism that has garnered intense focus involves the ability of mutant TFs to hijack wild-type lineage-specific TFs in self-reinforcing transcriptional circuits. However, it is not known whether this specific type of circuitry is equally crucial in all mutant TF-driven cancers. Here we describe an alternative yet central transcriptional mechanism that promotes Ewing sarcoma, wherein constraint, rather than reinforcement, of the activity of the fusion TF EWS-FLI supports cancer growth. We discover that ETV6 is a crucial TF dependency that is specific to this disease because it, counter-intuitively, represses the transcriptional output of EWS-FLI. This work discovers a previously undescribed transcriptional mechanism that promotes cancer.

Identification of Long Noncoding RNAs That Exert Transcriptional Regulation by Forming RNA-DNA Triplexes in Prostate Cancer

Long noncoding RNAs (lncRNAs) are involved in transcriptional regulation, and their deregulation is associated with the development of various human cancers, including prostate cancer (PCa). However, their underlying mechanisms remain unclear. In this study, lncRNAs that interact with DNA and regulate mRNA transcription in PCa were screened and identified to promote PCa development. First, 4195 protein-coding genes (PCGs, mRNAs) were obtained from the The Cancer Genome Atlas (TCGA) database, in which 1148 lncRNAs were differentially expressed in PCa. Then, 44,270 pairs of co-expression relationships were calculated between 612 lncRNAs and 2742 mRNAs, of which 42,596 (96%) were positively correlated. Among the 612 lncRNAs, 392 had the potential to interact with the promoter region to form DNA:DNA:RNA triplexes, from which lncRNA AD000684.2(AC002128.1) was selected for further validation. AC002128.1 was highly expressed in PCa. Furthermore, AD000684.2 positively regulated the expression of the correlated genes. In addition, AD000684.2 formed RNA-DNA triplexes with the promoter region of the regulated genes. Functional assays also demonstrated that lncRNA AD000684.2 promotes cell proliferation and motility, as well as inhibits apoptosis, in PCa cell lines. The results suggest that AD000684.2 could positively regulate the transcription of target genes via triplex structures and serve as a candidate prognostic biomarker and target for new therapies in human PCa.

Sex-biased expression is associated with chromatin state in D. melanogaster and D. simulans

We propose a new model for the association of chromatin state and sex-bias in expression. We hypothesize enrichment of open chromatin in the sex where we see expression bias (OS) and closed chromatin in the opposite sex (CO). In this study of D. melanogaster and D. simulans head tissue, sex-bias in expression is associated with H3K4me3 (open mark) in males for male-biased genes and in females for female-biased genes in both species. Sex-bias in expression is also largely conserved in direction and magnitude between the two species on the X and autosomes. In male-biased orthologs, the sex-bias ratio is more divergent between species if both species have H3K27me2me3 marks in females compared to when either or neither species has H3K27me2me3 in females. H3K27me2me3 marks in females are associated with male-bias in expression on the autosomes in both species, but on the X only in D. melanogaster . In female-biased orthologs the relationship between the species for the sex-bias ratio is similar regardless of the H3K27me2me3 marks in males. Female-biased orthologs are more similar in the ratio of sex-bias than male-biased orthologs and there is an excess of male-bias in expression in orthologs that gain/lose sex-bias. There is an excess of male-bias in sex-limited expression in both species suggesting excess male-bias is due to rapid evolution between the species. The X chromosome has an enrichment in male-limited H3K4me3 in both species and an enrichment of sex-bias in expression compared to the autosomes.

Monitoring Mechano-Regulation of Gene Expression by RNA Sequencing

The advent of high-throughput sequencing techniques has revolutionized biological research. One such method is RNA sequencing, which has become a relatively affordable and routine method for quantifying and comparing gene expression changes over desired experimental conditions. Along with the popularity of the method, a myriad of user-friendly, open-source computational tools have also emerged for differential gene expression analyses. Correspondingly, decades of mechanobiology research have established that mechanical cues, both alone and/or in combination with biochemical signals, can be powerful regulators of transcriptional programs and consequently cell state/fate transitions. Thus, it has become possible to investigate both universal and specific temporally resolved transcriptional responses upon mechanical stimulation genome-wide. This chapter will describe methods to analyze transcriptional changes in response to extrinsic mechanical stretch.

Standardization of Single-Cell RNA-Sequencing Analysis Workflow to Study Drosophila Ovary

Developments in single-cell technology have considerably changed the way we study biology. Significant efforts have been made over the last few years to build comprehensive cell-type-specific transcriptomic atlases for a wide range of tissues in several model organisms in order to discover cell-type-specific markers and drivers of gene expression. One such tissue is the ovary of the fruit-fly Drosophila melanogaster, which is a popular model system with wide-ranging applications in the study of both development and disease. Three independent studies have recently produced comprehensive maps of cell-type-specific gene expression that describe both spatiotemporal regulation of the process of oogenesis and unique transcriptomic profiles of different cell types that constitute the ovary. In this chapter, we outlined the wet-lab protocol that was followed in our recent study for sample preparation and reanalyze the resultant dataset to discuss the benchmarks in data analysis, which are fundamental to comprehensive curation of the single-cell dataset representing the fly ovary.

Benchmarking full-length transcript single cell mRNA sequencing protocols

BACKGROUND

Single cell mRNA sequencing technologies have transformed our understanding of cellular heterogeneity and identity. For sensitive discovery or clinical marker estimation where high transcript capture per cell is needed only plate-based techniques currently offer sufficient resolution.

RESULTS

Here, we present a performance evaluation of four different plate-based scRNA-seq protocols. Our evaluation is aimed towards applications taxing high gene detection sensitivity, reproducibility between samples, and minimum hands-on time, as is required, for example, in clinical use. We included two commercial kits, NEBNext® Single Cell/ Low Input RNA Library Prep Kit (NEB®), SMART-seq® HT kit (Takara®), and the non-commercial protocols Genome & Transcriptome sequencing (G&T) and SMART-seq3 (SS3). G&T delivered the highest detection of genes per single cell. SS3 presented the highest gene detection per single cell at the lowest price. Takara® kit presented similar high gene detection per single cell, and high reproducibility between samples, but at the absolute highest price. NEB® delivered a lower detection of genes but remains an alternative to more expensive commercial kits.

CONCLUSION

For the tested kits we found that ease-of-use came at higher prices. Takara can be selected for its ease-of-use to analyse a few samples, but we recommend the cheaper G&T-seq or SS3 for laboratories where a substantial sample flow can be expected.

Clustering Deviation Index (CDI): a robust and accurate internal measure for evaluating scRNA-seq data clustering

Most single-cell RNA sequencing (scRNA-seq) analyses begin with cell clustering; thus, the clustering accuracy considerably impacts the validity of downstream analyses. In contrast with the abundance of clustering methods, the tools to assess the clustering accuracy are limited. We propose a new Clustering Deviation Index (CDI) that measures the deviation of any clustering label set from the observed single-cell data. We conduct in silico and experimental scRNA-seq studies to show that CDI can select the optimal clustering label set. As a result, CDI also informs the optimal tuning parameters for any given clustering method and the correct number of cluster components.

Assessing and removing the effect of unwanted technical variations in microbiome data

Varying technologies and experimental approaches used in microbiome studies often lead to irreproducible results due to unwanted technical variations. Such variations, often unaccounted for and of unknown source, may interfere with true biological signals, resulting in misleading biological conclusions. In this work, we aim to characterize the major sources of technical variations in microbiome data and demonstrate how in-silico approaches can minimize their impact. We analyzed 184 pig faecal metagenomes encompassing 21 specific combinations of deliberately introduced factors of technical and biological variations. Using the novel Removing Unwanted Variations-III-Negative Binomial (RUV-III-NB), we identified several known experimental factors, specifically storage conditions and freeze-thaw cycles, as likely major sources of unwanted variation in metagenomes. We also observed that these unwanted technical variations do not affect taxa uniformly, with freezing samples affecting taxa of class Bacteroidia the most, for example. Additionally, we benchmarked the performances of different correction methods, including ComBat, ComBat-seq, RUVg, RUVs, and RUV-III-NB. While RUV-III-NB performed consistently robust across our sensitivity and specificity metrics, most other methods did not remove unwanted variations optimally. Our analyses suggest that a careful consideration of possible technical confounders is critical during experimental design of microbiome studies, and that the inclusion of technical replicates is necessary to efficiently remove unwanted variations computationally.