The successes and future prospects of the linear antisense RNA amplification methodology

Laser microdissection and fluorescence in situ hybridization reveal the tissue-specific gene expression in the ovules of P. tabulaeformis Carr

Ovules are important carriers for seed plant reproduction, and ovules of gymnosperms are composed mainly of female gametophyte (FG) and adjacent diploid tissue (ADT). To investigate tissue-specific genes in the ovules of Pinus tabulaeformis Carr., we used laser microdissection (LMD) to separate FGs and ADTs, and performed linear amplification to construct cDNA libraries, obtaining a total of 156 expressed sequence tags (EST). Furthermore, some differentially expressed genes between FG and ADT of P. tabulaeformis ovule were screened by the analysis of EST. In addition, the expression levels of key genes in fertile line (FL) and sterile line (SL) ovules during development were verified by RT-qPCR, and we found that both PtRPL7a and PtDHN4 were more highly expressed in FL in each period (at least 1.7 times that of SL). Finally, fluorescence in situ hybridization (FISH) was used to reveal the temporal and spatial expression patterns of PtRPL7a and PtDHN4 in the ovules of P. tabuliformis during ovule development between FL and SL. Our results indicate that the expression levels and the locations of PtRPL7a and PtDHN4 show significant differences in different tissues during ovule development between FL and SL. This study further elucidates the molecular mechanism of the ovule abortion of P. tabulaeformis and provides a theoretical basis for the germplasm optimization of gymnosperms.

LINCATRA: Two-cycle method to amplify RNA for transcriptome analysis from formalin-fixed paraffin-embedded tissue

Whole transcriptome analysis (WTA) using RNA extracted from Formalin Fixed Paraffin Embedded (FFPE) tissue is an invaluable tool to understand the molecular pathology of disease. RNA extracted from FFPE tissue is either degraded and/or in very low quantities hampering gene expression analysis. Earlier studies described protocols applied for cellular RNA using poly-A primer-based linear amplification. The current study describes a method, LINCATRA (LINear amplifiCAtion of RNA for whole TRAnscriptome analysis). It employs random nonamer primer based method which can amplify short, fragmented RNA with high fidelity from as low as 5 ng to obtain enough material for WTA. The two-cycle method significantly amplified RNA at ∼1000 folds (p < 0.0001) improving the mean read lengths (p < 0.05) in WTA. Overall, increased mean read length positively correlated with on-target reads (Pearson's r = 0.71, p < 0.0001) in both amplified and unamplified RNA-seq analysis. Gene expression analysis compared between unamplified and amplified group displayed substantial overlap of the differentially expressed genes (DEGs) (log2 fold change cut-off < -2 and >2, p < 0.05) identified between lung cancer and asthma cohorts validating the method developed. This method is applicable in clinical molecular pathology field for both diagnostics and elucidation of disease mechanisms.

Deep scRNA sequencing reveals a broadly applicable Regeneration Classifier and implicates antioxidant response in corticospinal axon regeneration

Despite substantial progress in understanding the biology of axon regeneration in the CNS, our ability to promote regeneration of the clinically important corticospinal tract (CST) after spinal cord injury remains limited. To understand regenerative heterogeneity, we conducted patch-based single-cell RNA sequencing on rare regenerating CST neurons at high depth following PTEN and SOCS3 deletion. Supervised classification with Garnett gave rise to a Regeneration Classifier, which can be broadly applied to predict the regenerative potential of diverse neuronal types across developmental stages or after injury. Network analyses highlighted the importance of antioxidant response and mitochondrial biogenesis. Conditional gene deletion validated a role for NFE2L2 (or NRF2), a master regulator of antioxidant response, in CST regeneration. Our data demonstrate a universal transcriptomic signature underlying the regenerative potential of vastly different neuronal populations and illustrate that deep sequencing of only hundreds of phenotypically identified neurons has the power to advance regenerative biology.

Leading the pack: Best practices in comparative canine cancer genomics to inform human oncology

Pet dogs develop spontaneous cancers at a rate estimated to be five times higher than that of humans, providing a unique opportunity to study disease biology and evaluate novel therapeutic strategies in a model system that possesses an intact immune system and mirrors key aspects of human cancer biology. Despite decades of interest, effective utilization of pet dog cancers has been hindered by a limited repertoire of necessary cellular and molecular reagents for both in vitro and in vivo studies, as well as a dearth of information regarding the genomic landscape of these cancers. Recently, many of these critical gaps have been addressed through the generation of a highly annotated canine reference genome, the creation of several tools necessary for multi-omic analysis of canine tumours, and the development of a centralized repository for key genomic and associated clinical information from canine cancer patients, the Integrated Canine Data Commons. Together, these advances have catalysed multidisciplinary efforts designed to integrate the study of pet dog cancers more effectively into the translational continuum, with the ultimate goal of improving human outcomes. The current review summarizes this recent progress and provides a guide to resources and tools available for comparative study of pet dog cancers.

Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq

Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug repositioning. Initially, microarrays are used to study the bulk transcriptome; but now short-read RNA sequencing (RNA-seq) predominates. Positioned as a superior technology, that makes the discovery of novel transcripts routine, most RNA-seq analyses are in fact modeled on the known transcriptome. Limitations of the RNA-seq methodology have emerged, while the design of, and the analysis strategies applied to, arrays have matured. An equitable comparison between these technologies is provided, highlighting advantages that modern arrays hold over RNA-seq. Array protocols more accurately quantify constitutively expressed protein coding genes across tissue replicates, and are more reliable for studying lower expressed genes. Arrays reveal long noncoding RNAs (lncRNA) are neither sparsely nor lower expressed than protein coding genes. Heterogeneous coverage of constitutively expressed genes observed with RNA-seq, undermines the validity and reproducibility of pathway analyses. The factors driving these observations, many of which are relevant to long-read or single-cell sequencing are discussed. As proposed herein, a reappreciation of bulk transcriptomic methods is required, including wider use of the modern high-density array data-to urgently revise existing anatomical RNA reference atlases and assist with more accurate study of lncRNAs.

Circular RNA Expression Profiling by Microarray-A Technical and Practical Perspective

Circular RNAs, as covalently circularized RNA loops, have many unique biochemical properties. Many circRNA biological functions and clinical indications are being continually discovered. Increasingly, circRNAs are being used as a new class of biomarkers, which are potentially superior to linear RNAs due to the unusual cell/tissue/disease specificities and the exonuclease-resistant stabilized circular form in the biofluids. Profiling circRNA expression has been a common step in circRNA research to provide much needed insight into circRNA biology and to facilitate rapid advances in the circRNA field. We will review circRNA microarrays as a practical and effective circRNA profiling technology for regularly equipped biological or clinical research labs, share valuable experiences, and highlight the significant findings from the profiling studies.

Subcellular omics: a new frontier pushing the limits of resolution, complexity and throughput

We argue that the study of single-cell subcellular organelle omics is needed to understand and regulate cell function. This requires and is being enabled by new technology development.

Future of Digital Assays to Resolve Clinical Heterogeneity of Single Extracellular Vesicles

Extracellular vesicles (EVs) are complex lipid membrane vehicles with variable expressions of molecular cargo, composed of diverse subpopulations that participate in the intercellular signaling of biological responses in disease. EV-based liquid biopsies demonstrate invaluable clinical potential for overhauling current practices of disease management. Yet, EV heterogeneity is a major needle-in-a-haystack challenge to translate their use into clinical practice. In this review, existing digital assays will be discussed to analyze EVs at a single vesicle resolution, and future opportunities to optimize the throughput, multiplexing, and sensitivity of current digital EV assays will be highlighted. Furthermore, this review will outline the challenges and opportunities that impact the clinical translation of single EV technologies for disease diagnostics and treatment monitoring.

Maximizing transcription of nucleic acids with efficient T7 promoters

In vitro transcription using T7 bacteriophage polymerase is widely used in molecular biology. Here, we use 5'RACE-Seq to screen a randomized initially transcribed region of the T7 promoter for cross-talk with transcriptional activity. We reveal that sequences from position +4 to +8 downstream of the transcription start site affect T7 promoter activity over a 5-fold range, and identify promoter variants with significantly enhanced transcriptional output that increase the yield of in vitro transcription reactions across a wide range of template concentrations. We furthermore introduce CEL-Seq⁺ , which uses an optimized T7 promoter to amplify cDNA for single-cell RNA-Sequencing. CEL-Seq+ facilitates scRNA-Seq library preparation, and substantially increases library complexity and the number of expressed genes detected per cell, highlighting a particular value of optimized T7 promoters in bioanalytical applications.