RNA-seq Methods Research Articles

Super-delta2: an enhanced differential expression analysis procedure for multi-group comparisons of RNA-seq data.

We developed super-delta2, a differential gene expression analysis pipeline designed for multi-group comparisons for RNA-seq data. It includes a customized one-way ANOVA F-test and a post-hoc test for pairwise group comparisons; both are designed to work with a multivariate normalization procedure to reduce technical noise. It also includes a trimming procedure with bias-correction to obtain robust and approximately unbiased summary statistics used in these tests. We demonstrated the asymptotic applicability of super-delta2 to log-transformed read counts in RNA-seq data by large sample theory based on Negative Binomial Poisson (NBP) distribution. We compared super-delta2 with three commonly used RNA-seq data analysis methods: limma/voom, edgeR and DESeq2 using both simulated and real datasets. In all three simulation settings, super-delta2 not only achieved the best overall statistical power, but also was the only method that controlled type I error at the nominal level. When applied to a breast cancer dataset to identify differential expression pattern associated with multiple pathologic stages, super-delta2 selected more enriched pathways than other methods, which are directly linked to the underlying biological condition (breast cancer). In conclusion, by incorporating trimming and bias-correction in the normalization step, super-delta2 was able to achieve tight control of type I error. Because the hypothesis tests are based on asymptotic normal approximation of the NBP distribution, super-delta2 does not require computationally expensive iterative optimization procedures used by methods such as edgeR and DESeq2, which occasionally have convergence issues. Our method is implemented in a R-package, 'superdelta2', freely available at: https://github.com/fhlsjs/superdelta2. Supplementary data are available at Bioinformatics online.

In vitro transcriptomes analysis identifies some special genes involved in pathogenicity difference of the Beauveria bassiana against different insect hosts

Typical entomopathogenic filamentous fungi such as Beauveria bassiana infect susceptible hosts via penetration of insect cuticle. The pathogenicity of B. bassiana strain to diverse insect hosts is different. While the molecular mechanisms of B. bassiana adapt to different insects are not well clear. B. bassiana GXsk1011 is a hyper-virulent strain from silkworm, which was investigated on the metabolic responses to three cuticle extracts of Bombyx mori, Helicoverpa armigera and Clanis bilineata at 24 h by RNA-seq method. A total of 638 up- and 400 down-regulated differentially expressed genes (DEGs) were identified in B. bassiana grown on H. armigera compared with B. mori, and 910 up- and 401 down-regulated genes for C. bilineata compared with B. mori. Functional categorization showed that DEGs are mainly involved in metabolic processes, localization, catalytic activity and transporter activity. Analysis of 20 highest fold change genes in DEGs showed that when B. bassiana transferred to non-original hosts as H. armigera and C. bilineata, the adhesion (Mad1), protease (Pr2) and cell surface protein (BBA_09174), etc. were down-regulated. While the class III chitinase ChiA2 (BBA_05353, Bbchi-17), major allergen Asp f 2-like protein (BBA_05395, Bb-f2) and nonribosomal peptide synthase, etc. were up-regulated. The secretory lipase that responded to H. armigera and the phosphate permease responded to C. bilineata were also up-regulated in the Top 20 DEGs. These special expressed genes indicate when the B. bassiana transferred to non-original hosts (or called as non-natural hosts), the strain appeared the changes of metabolic response and infection strategies to adapt to new hosts, and implied the key actions of infected adaptation were to break the barrier of different cuticle chitin component and against the immune stress of hosts. This study provided an insight into the B. bassiana that with wide host ranges how to adapt to infect different insect hosts, which will help us to further understand the pathogenesis of B. bassiana infection.

Regulation of mating genes during arbuscular mycorrhizal isolate co-existence-where is the evidence?

A recent study published by Mateus et al. [1] claimed that 18 "mating-related" genes are differentially expressed in the model arbuscular mycorrhizal fungus (AMF) Rhizophagus irregularis when genetically distinct fungal strains co-colonize a host plant. To clarify the level of evidence for this interesting conclusion, we first aimed to validate the functional annotation of these 18 R. irregularis genes using orthology predictions. These analyses revealed that, although sequence relationship exists, only 2 of the claimed 18 R. irregularis mating genes are potential orthologues to validated fungal mating genes. We also investigated the RNA-seq data from Mateus et al. [1] using classical RNA-seq methods and statistics. This analysis found that the over-expression during strain co-existence was not significant at the typical cut-off of the R. irregularis strains DAOM197198 and B1 in plants. Overall,wedo notfind convincing evidence that the genes involved have functions in mating, or that they are reproducibly upor downregulated during co-existence in plants.

Flexible comparison of batch correction methods for single-cell RNA-seq using BatchBench.

As the cost of single-cell RNA-seq experiments has decreased, an increasing number of datasets are now available. Combining newly generated and publicly accessible datasets is challenging due to non-biological signals, commonly known as batch effects. Although there are several computational methods available that can remove batch effects, evaluating which method performs best is not straightforward. Here, we present BatchBench (https://github.com/cellgeni/batchbench), a modular and flexible pipeline for comparing batch correction methods for single-cell RNA-seq data. We apply BatchBench to eight methods, highlighting their methodological differences and assess their performance and computational requirements through a compendium of well-studied datasets. This systematic comparison guides users in the choice of batch correction tool, and the pipeline makes it easy to evaluate other datasets.

Expression of NKG2D ligands is downregulated by β-catenin signalling and associates with HCC aggressiveness

The NKG2D system is a potent immunosurveillance mechanism in cancer, wherein the activating NK cell receptor (NKG2D) on immune cells recognises its cognate ligands on tumour cells. Herein, we evaluated the expression of NKG2D ligands in hepatocellular carcinoma (HCC), in both humans and mice, taking the genomic features of HCC tumours into account. The expression of NKG2D ligands (MICA, MICB, ULBP1 and ULBP2) was analysed in large human HCC datasets by Fluidigm TaqMan and RNA-seq methods, and in 2 mouse models (mRNA and protein levels) reproducing the features of both major groups of human tumours. We provide compelling evidence that expression of the MICA and MICB ligands in human HCC is associated with tumour aggressiveness and poor patient outcome. We also found that the expression of ULBP1 and ULBP2 was associated with poor patient outcome, and was downregulated in CTNNB1-mutated HCCs displaying low levels of inflammation and associated with a better prognosis. We also found an inverse correlation between ULBP1/2 expression levels and the expression of β-catenin target genes in patients with HCC, suggesting a role for β-catenin signalling in inhibiting expression. We showed in HCC mouse models that β-catenin signalling downregulated the expression of Rae-1 NKG2D ligands, orthologs of ULBPs, through TCF4 binding. We demonstrate that the expression of NKG2D ligands is associated with aggressive liver tumorigenesis and that the downregulation of these ligands by β-catenin signalling may account for the less aggressive phenotype of CTNNB1-mutated HCC tumours. The NKG2D system is a potent immunosurveillance mechanism in cancer. However, its role in hepatocellular carcinoma development has not been widely investigated. Herein, we should that the expression of NKG2D ligands by tumour cells is associated with a more aggressive tumour subtype.

Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

BackgroundElucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation.ResultsHere, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures.ConclusionOverall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

Single-cell mapper (scMappR): using scRNA-seq to infer the cell-type specificities of differentially expressed genes.

RNA sequencing (RNA-seq) is widely used to identify differentially expressed genes (DEGs) and reveal biological mechanisms underlying complex biological processes. RNA-seq is often performed on heterogeneous samples and the resulting DEGs do not necessarily indicate the cell-types where the differential expression occurred. While single-cell RNA-seq (scRNA-seq) methods solve this problem, technical and cost constraints currently limit its widespread use. Here we present single cell Mapper (scMappR), a method that assigns cell-type specificity scores to DEGs obtained from bulk RNA-seq by leveraging cell-type expression data generated by scRNA-seq and existing deconvolution methods. After evaluating scMappR with simulated RNA-seq data and benchmarking scMappR using RNA-seq data obtained from sorted blood cells, we asked if scMappR could reveal known cell-type specific changes that occur during kidney regeneration. scMappR appropriately assigned DEGs to cell-types involved in kidney regeneration, including a relatively small population of immune cells. While scMappR can work with user-supplied scRNA-seq data, we curated scRNA-seq expression matrices for ∼100 human and mouse tissues to facilitate its stand-alone use with bulk RNA-seq data from these species. Overall, scMappR is a user-friendly R package that complements traditional differential gene expression analysis of bulk RNA-seq data.

TGIRT-seq Protocol for the Comprehensive Profiling of Coding and Non-coding RNA Biotypes in Cellular, Extracellular Vesicle, and Plasma RNAs.

High-throughput RNA sequencing (RNA-seq) has extraordinarily advanced our understanding of gene expression and disease etiology, and is a powerful tool for the identification of biomarkers in a wide range of organisms. However, most RNA-seq methods rely on retroviral reverse transcriptases (RTs), enzymes that have inherently low fidelity and processivity, to convert RNAs into cDNAs for sequencing. Here, we describe an RNA-seq protocol using Thermostable Group II Intron Reverse Transcriptases (TGIRTs), which have high fidelity, processivity, and strand-displacement activity, as well as a proficient template-switching activity that enables efficient and seamless RNA-seq adapter addition. By combining these activities, TGIRT-seq enables the simultaneous profiling of all RNA biotypes from small amounts of starting material, with superior RNA-seq metrics, and unprecedented ability to sequence structured RNAs. The TGIRT-seq protocol for Illumina sequencing consists of three steps: (i) addition of a 3' RNA-seq adapter, coupled to the initiation of cDNA synthesis at the 3' end of a target RNA, via template switching from a synthetic adapter RNA/DNA starter duplex; (ii) addition of a 5' RNA-seq adapter, by using thermostable 5' App DNA/RNA ligase to ligate an adapter oligonucleotide to the 3' end of the completed cDNA; (iii) minimal PCR amplification, to add capture sites and indices for Illumina sequencing. TGIRT-seq for the Illumina sequencing platform has been used for comprehensive profiling of coding and non-coding RNAs in ribodepleted, chemically fragmented cellular RNAs, and for the analysis of intact (non-chemically fragmented) cellular, extracellular vesicle (EV), and plasma RNAs, where it yields continuous full-length end-to-end sequences of structured small non-coding RNAs (sncRNAs), including tRNAs, snoRNAs, snRNAs, pre-miRNAs, and full-length excised linear intron (FLEXI) RNAs. Graphic abstract: Figure 1.Overview of the TGIRT-seq protocol for Illumina sequencing.Major steps are: (1) Template switching from a synthetic R2 RNA/R2R DNA starter duplex with a 1-nt 3' DNA overhang (a mixture of A, C, G, and T residues, denoted N) that base pairs to the 3' nucleotide of a target RNA, and upon initiating reverse transcription by adding dNTPs, seamlessly links an R2R adapter to the 5' end of the resulting cDNA; (2) Ligation of an R1R adapter to the 3' end of the completed cDNA; and (3) Minimal PCR amplification with primers that add Illumina capture sites (P5 and P7) and barcode sequences (indices 5 and 7). The index 7 barcode is required, while the index 5 barcode is optional, to provide unique dual indices (UDIs).

Transcriptomic Changes of Murine Visceral Fat Exposed to Intermittent Hypoxia at Single Cell Resolution.

Intermittent hypoxia (IH) is a hallmark of obstructive sleep apnea (OSA) and induces metabolic dysfunction manifesting as inflammation, increased lipolysis and insulin resistance in visceral white adipose tissues (vWAT). However, the cell types and their corresponding transcriptional pathways underlying these functional perturbations are unknown. Here, we applied single nucleus RNA sequencing (snRNA-seq) coupled with aggregate RNA-seq methods to evaluate the cellular heterogeneity in vWAT following IH exposures mimicking OSA. C57BL/6 male mice were exposed to IH and room air (RA) for 6 weeks, and nuclei from vWAT were isolated and processed for snRNA-seq followed by differential expressed gene (DEGs) analyses by cell type, along with gene ontology and canonical pathways enrichment tests of significance. IH induced significant transcriptional changes compared to RA across 14 different cell types identified in vWAT. We identified cell-specific signature markers, transcriptional networks, metabolic signaling pathways, and cellular subpopulation enrichment in vWAT. Globally, we also identify 298 common regulated genes across multiple cellular types that are associated with metabolic pathways. Deconvolution of cell types in vWAT using global RNA-seq revealed that distinct adipocytes appear to be differentially implicated in key aspects of metabolic dysfunction. Thus, the heterogeneity of vWAT and its response to IH at the cellular level provides important insights into the metabolic morbidity of OSA and may possibly translate into therapeutic targets.

Deep sequencing of the transcriptome from murine lung infected with H5N8 subtype avian influenza virus with combined substitutions I283M and K526R in PB2 gene.

H5N8 subtype highly pathogenic avian influenza viruses (HPAIVs) pose a huge threat to poultry industry and general public health. Our previous study demonstrated that synergistic effect of 283M and 526R in PB2 gene was a critical factor for viral high pathogenicity in mammals. However, the potential pathogenic mechanism of the mutant virus is still unclear. Here, RNA-seq method was used to analyze the global host response of murine lungs after infecting with parental r-JY virus and JY-PB2-I283M-K526R mutant virus. We found that both amounts and the expression levels of host differentially expressed genes (DEGs) were higher in mutant virus-infected mice compared with the group of parental virus. Furthermore, the DEGs mainly related with innate immune response by GO and KEGG analysis. Especially, PB2-I283M-K526R mutation strongly induced a sharp expression of cytokine storm-related genes, including MX1, CXCL10, and IFN-γ, performed by qRT-PCR. We also found that PB2-I283M-K526R mutation accelerated the level of cell apoptosis by heat map analysis of apoptosis-related DEGs in lungs and apoptosis assay in vitro. Taken together, our data demonstrated that PB2-I283M-K526R of H5N8 subtype HPAIV exacerbated the innate immune response and the level of cell apoptosis, which might be a key pathogenic mechanism for the enhanced pathogenicity of mutants in mammals.

Characterization of Hibiscus Latent Fort Pierce Virus-Derived siRNAs in Infected Hibiscus rosa-sinensis in China.

Although limited progress have been made about pathogen system of Hibiscus rosa-sinensis and Hibiscus latent Fort Pierce virus (HLFPV), interaction between plant host and pathogen remain largely unknown, which led to deficiency of effective measures to control disease of hibiscus plants caused by HLFPV. In this study, infection of HLFPV in Hibiscus rosa-sinensis was firstly confirmed for the first time by traditional electron microscopy, modern reverse transcription polymerase chain reaction and RNA-seq methods in China (HLFPV-Ch). Sequence properties analyzing suggested that the full-length sequences (6,465 nt) of HLFPV-Ch had a high sequence identity and a similar genomic structure with other tobamoviruses. It includes a 5′-terminal untranslated region (UTR), followed by four open reading frames encoding for a 128.5-kDa replicase, a 186.5-kDa polymerase, a 31-kDa movement protein, 17.6-kDa coat protein, and the last a 3′-terminal UTR. Furthermore, HLFPV-Ch–derived virus-derived siRNAs (vsiRNAs) ant its putative target genes, reported also for the first time, were identified and characterized from disease Hibiscus rosa-sinensis through sRNA-seq and Patmatch server to investigate the interaction in this pathogen systems. HLFPV-Ch–derived vsiRNAs demonstrated several general and specific characteristics. Gene Ontology classification revealed predicted target genes by vsiRNAs are involved in abroad range of cellular component, molecular function and biological processes. Taken together, for first time, our results certified the HLFPV infection in China and provide an insight into interaction between HLFPV and Hibiscus rosa-sinensis.

Deciphering the Early Mouse Embryo Transcriptome by Low-Input RNA-Seq.

Early preimplantation embryos are precious and scarce samples that contain limited numbers of cells, which can be problematic for quantitative gene expression analyses. Nonetheless, low-input genome-wide techniques coupled with cDNA amplification steps have become a gold standard for RNA profiling of as minimal as a single blastomere. Here, we describe a single-cell/single-embryo RNA sequencing (RNA-seq) method, from embryo collection to sample validation steps prior to DNA library preparation and sequencing. Key quality controls and external Spike-In normalization approaches are also detailed.

RNA-seq accuracy and reproducibility for the mapping and quantification of influenza defective viral genomes.

Like most RNA viruses, influenza viruses generate defective viral genomes (DVGs) with large internal deletions during replication. There is accumulating evidence supporting a biological relevance of such DVGs. However, further understanding of the molecular mechanisms that underlie the production and biological activity of DVGs is conditioned upon the sensitivity and accuracy of detection methods, that is, next-generation sequencing (NGS) technologies and related bioinformatics algorithms. Although many algorithms were developed, their sensitivity and reproducibility were mostly assessed on simulated data. Here, we introduce DG-seq, a time-efficient pipeline for DVG detection and quantification, and a set of biological controls to assess the performance of not only our bioinformatics algorithm but also the upstream NGS steps. Using these tools, we provide the first rigorous comparison of the two commonly used sample processing methods for RNA-seq, with or without a PCR preamplification step. Our data show that preamplification confers a limited advantage in terms of sensitivity and introduces size- but also sequence-dependent biases in DVG quantification, thereby providing a strong rationale to favor preamplification-free methods. We further examine the features of DVGs produced by wild-type and transcription-defective (PA-K635A or PA-R638A) influenza viruses, and show an increased diversity and frequency of DVGs produced by the PA mutants compared to the wild-type virus. Finally, we demonstrate a significant enrichment in DVGs showing direct, A/T-rich sequence repeats at the deletion breakpoint sites. Our findings provide novel insights into the mechanisms of influenza virus DVG production.

Identification of transcriptome differences in goat ovaries at the follicular phase and the luteal phase using an RNA-Seq method

The ovaries, the main female reproductive organs, directly mediate ovulation and reproductive hormone secretion. These complex physiological processes are regulated by multiple genes and pathways. However, there is a lack of research on goat ovaries, and the molecular mechanisms underlying the signaling pathways remain unclear. In this study, Illumina HiSeq 4000 sequencing was used to sequence the transcriptomes of goat ovaries. The expression patterns of differentially expressed mRNAs in goat ovaries at both the follicular and luteal phases were determined by bioinformatics analysis. A total of 1,122, 014, 112 clean reads were obtained, and 3770 differentially expressed mRNAs were identified for further analysis. There were 1727 and 2043 upregulated mRNAs in the luteal phase and follicular phase, respectively. According to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, some mRNAs that were highly expressed in ovaries during the luteal phase, such as HSD17B7, 3BHSD, and SRD5A2, may be related to the synthesis of progesterone. In addition, some mRNAs that were highly expressed in ovaries during the follicular phase, such as RPL12, RPS13 and RPL10, are related to the growth and maturation of oocytes. Taken together, the findings of this study provide genome-wide mRNA expression profiles for goat ovaries at the follicular and luteal phases and identify mRNAs associated with goat hormone secretion and follicular development. In addition, this study provides a theoretical basis for further investigation of goat reproductive regulation.

A Revised Adaptation of the Smart-Seq2 Protocol for Single-Nematode RNA-Seq.

The advancement of transcriptomic studies in plant parasitic nematodes will greatly benefit from the development of single-nematode RNA-seq methods. Since many plant parasitic nematodes are obligate parasites, it is often difficult to efficiently obtain sufficient amounts of nematodes for transcriptomic studies. Here we have adapted SMART-Seq2 for single-nematode RNA-seq requiring only an individual nematode for a sample replicate. This protocol provides a detailed step-by-step procedure of the RNA-seq workflow starting from lysis of the nematode to quantification of transcripts using a user-friendly online platform.

Abstract 4441: CS3003, an HDAC6-selective inhibitor, improves anti-PD-1 immune checkpoint blockade therapy efficacy

Abstract Background: Histone deacetylases (HDACs) are involved in diverse cellular regulatory function including histone modification and non-histone modification. Several publications have demonstrated that selective HDAC inhibitors (HDACi) can influence tumor growth and immunogenicity. In particular, the selective inhibition of HDAC6 has function of inhibiting tumor growth in several malignancies. However, the mechanism of this effect is still not clear. Methods: In this study, we evaluated CS3003, a selective HDAC6 inhibitor, inhibition profile using cell-based free assays. In vivo anti-tumor efficacy was evaluated in MM.1S xenograft mouse model. CS3003 and PD-1 blockade combination effect was evaluated in CT26 syngeneic mouse model. RNA-seq method was used to explore the transcription regulation by CS3003 compared to other pan-HDAC, Class I HDAC inhibitor and selective HDAC6 inhibitors. Results: CS3003 has distinct inhibition profile in HDAC family members. Combination of CS3003 and proteasome inhibitor synergistically enhanced anti-tumor function in human multiple myeloma mouse model (coefficient of drug interaction, CDI=0.69). In addition, CS3003 improves the anti-tumor activity of anti-PD-1 immune checkpoint blockade in solid tumor model (CDI=0.62 and 0.88 when the dosage of CS3003 was 30 and 70mg/kg, respectively). Transcriptome analysis demonstrated a unique gene expression pattern of CS3003 from other pan-HDAC and selective HDAC6 inhibitors. Conclusions: These data provide a comprehensive pre-clinical characterization of CS3003 that supports its unique HDAC inhibition profile and its capability of improving anti-PD-1 immune checkpoint blockade therapy efficacy. Citation Format: Zhenhu Li, Zhaoxiang Ren, Jingshu Ma, Liang Tang, Liang Lu, Ying Zhu, Yunfei Wu, Tiancheng Liu, Juan Zhang, Yuanwu Bao, Kangyu Zhang, Changqing Wei, Shuhui Chen, Xinzhong Jon Wang. CS3003, an HDAC6-selective inhibitor, improves anti-PD-1 immune checkpoint blockade therapy efficacy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4441.

Abstract 3637: Validation of a workflow to enable massively parallel transcriptome analysis in cryopreserved tissues

Abstract Tumor development and growth is a complex process involving interplay between stromal and neoplastic cells. Importantly, neoplastic subclones within tumors often possess different functional properties and metastatic potential, which may be obscured by traditional bulk characterization techniques such as RNA-seq. Such bulk sequencing methods are unable to capture inter-cellular heterogeneity and thus cannot reveal disease-relevant traits occurring within tissues and tumors. These limitations can be overcome by using single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq (scATAC-seq) methods, which enable a deeper understanding of cell-type specific traits and clonotype density and their contributions to carcinogenesis. However, current single cell techniques rely on obtaining fresh tissues that must be dissociated into single cell suspensions immediately after collection. Delay in processing risks changes in gene expression as well as increased cell mortality. Unfortunately, due to these intractable logistical challenges to carefully prepare single cell suspensions in an OR environment, single cell technologies currently have a modest role in translational and clinical settings despite their potential to revolutionize our understanding and treatment of cancer. To circumvent these challenges, we present here a cryopreservation workflow to preserve cells harvested from a variety of tissues for single cell sequencing. Following sample collection, tissues are processed through a simple cryopreservation protocol at which point they are amenable to short-term storage to allow batching of samples, as well as transportation to a laboratory for downstream processing. Subsequently, tissues are thawed and subjected to cellular dissociation with optional cell surface marker enrichment resulting in cell or nuclei suspensions suitable for scRNA-seq and scATAC-seq. This approach has been validated for use by analysis of a diverse range of paired fresh and cryopreserved tissues. Cell recovery and cell viability measures are comparable between fresh and cryopreserved across all tested tissues, thereby demonstrating the broad applicability of this approach. Furthermore, profiling by scRNA-seq and scATAC-seq indicates cryopreservation causes only modest effects on gene expression and chromatin accessibility across tested tissue types. Taken together, this work establishes a workflow to enable analysis of the transcriptome and epigenome in cryopreserved tissues at single cell resolution and make use of precious samples obtained in translational settings. Citation Format: David C. Corney, Yang Han, Yu Qiu, Riley Graham, Yongjun Fan, Christopher Mozdzierz, Haythem Latif, Ginger Zhou. Validation of a workflow to enable massively parallel transcriptome analysis in cryopreserved tissues [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3637.

Abstract 4276: Target enrichment to enable RNA-sequencing on FFPE samples: Application to a patient selection biomarkers in colorectal cancer

Abstract In proof of concept clinical studies, selecting for patients that are the most likely to respond to a given therapy will increase the chance of demonstrating clinical benefit for a new investigational agent. Archived Formalin-Fixed, Paraffin-Embedded (FFPE) tissue taken at the time of first biopsy and cancer diagnosis are a ready source of material for such patient selection assays; however if the selection assay is RNA-based sequencing based assay, FFPE tumor tissues are typically refractory to standard methods. Here we describe Target Enrichment, an RNA-sequencing technique that enabled analysis of FFPE tumor tissue. The Target Enrichment technique provides the necessary, high quality gene expression data required for identifying the mesenchymal subtype of CRC. In this experiment, RNA was extracted from a set of 192 histologically characterized, archived colorectal cancer (CRC) FFPE tumor tissues with sufficient representation of all Consensus Molecular Subtypes of CRC. A major issue with FFPE tissue is that nucleic acids are not well preserved in the fixation process. The RNA extraction method was carefully optimized in advance toward improving yield and integrity of the total RNA. In order to accommodate the low FFPE RNA integrity, we used Target Enrichment, a technique derived from whole-exome sequencing that isolates and amplifies library fragments corresponding to only the transcribed regions of interest. After testing several protocols, we established a Target Enrichment technique to remove low-quality library fragments that would otherwise interfere and impair sequencing quality. This method allowed us to generate high-quality sequencing data for samples that proved challenging using traditional RNA-seq methods. Fresh-frozen tissue samples were used as a benchmark and our Target Enrichment technique showed comparable performance across multiple sequencing quality metrics including mapping rate, expression profiling efficiency, number of genes detected, also the pass rate. Furthermore, data generated using our Target Enrichment technique aligned with the known frequencies of the Consensus Molecular Subtypes of CRC. Overall, our Target Enrichment technique provides a protocol for generating high quality RNA-seq libraries from highly degraded FFPE RNA. Citation Format: Maximilian Rogers-Grazado, Joachim Theilhaber, Jack Pollard, Alexei Protopopov. Target enrichment to enable RNA-sequencing on FFPE samples: Application to a patient selection biomarkers in colorectal cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4276.

Transcriptomic profiling of germinating seeds under cold stress and characterization of the cold-tolerant gene LTG5 in rice

BackgroundLow temperature is a limiting factor of rice productivity and geographical distribution. Wild rice (Oryza rufipogon Griff.) is an important germplasm resource for rice improvement. It has superior tolerance to many abiotic stresses, including cold stress, but little is known about the mechanism underlying its resistance to cold.ResultsThis study elucidated the molecular genetic mechanisms of wild rice in tolerating low temperature. Comprehensive transcriptome profiles of two rice genotypes (cold-sensitive ce 253 and cold-tolerant Y12–4) at the germinating stage under cold stress were comparatively analyzed. A total of 42.44–68.71 million readings were obtained, resulting in the alignment of 29,128 and 30,131 genes in genotypes 253 and Y12–4, respectively. Many common and differentially expressed genes (DEGs) were analyzed in the cold-sensitive and cold-tolerant genotypes. Results showed more upregulated DEGs in the cold-tolerant genotype than in the cold-sensitive genotype at four stages under cold stress. Gene ontology enrichment analyses based on cellular process, metabolic process, response stimulus, membrane part, and catalytic activity indicated more upregulated genes than downregulated ones in the cold-tolerant genotype than in the cold-sensitive genotype. Quantitative real-time polymerase chain reaction was performed on seven randomly selected DEGs to confirm the RNA Sequencing (RNA-seq) data. These genes showed similar expression patterns corresponding with the RNA-Seq method. Weighted gene co-expression network analysis (WGCNA) revealed Y12–4 showed more positive genes than 253 under cold stress. We also explored the cold tolerance gene LTG5 (Low Temperature Growth 5) encoding a UDP-glucosyltransferase. The overexpression of the LTG5 gene conferred cold tolerance to indica rice.ConclusionGene resources related to cold stress from wild rice can be valuable for improving the cold tolerance of crops.

Transcriptome Response of Metallicolous and a Non-Metallicolous Ecotypes of Noccaea goesingensis to Nickel Excess.

Root transcriptomic profile was comparatively studied in a serpentine (TM) and a non-metallicolous (NTM) population of Noccaea goesingensis in order to investigate possible features of Ni hyperaccumulation. Both populations were characterised by contrasting Ni tolerance and accumulation capacity. The growth of the TM population was unaffected by metal excess, while the shoot biomass production in the NTM population was significantly lower in the presence of Ni in the culture medium. Nickel concentration was nearly six- and two-fold higher in the shoots than in the roots of the TM and NTM population, respectively. The comparison of root transcriptomes using the RNA-seq method indicated distinct responses to Ni treatment between tested ecotypes. Among differentially expressed genes, the expression of IRT1 and IRT2, encoding metal transporters, was upregulated in the TM population and downregulated/unchanged in the NTM ecotype. Furthermore, differences were observed among ethylene metabolism and response related genes. In the TM population, the expression of genes including ACS7, ACO5, ERF104 and ERF105 was upregulated, while in the NTM population, expression of these genes remained unchanged, thus suggesting a possible regulatory role of this hormone in Ni hyperaccumulation. The present results could serve as a starting point for further studies concerning the plant mechanisms responsible for Ni tolerance and accumulation.