Background: With the fast advances in nextgen sequencing technology, high-throughput RNA sequencing has emerged as a powerful and cost-effective way for transcriptome study. De novo assembly of transcripts provides an important solution to transcriptome analysis for organisms with no reference genome. However, there lacked understanding on how the different variables affected assembly outcomes, and there was no consensus on how to approach an optimal solution by selecting software tool and suitable strategy based on the properties of RNA-Seq data. Results: To reveal the performance of different programs for transcriptome assembly, this work analyzed some important factors, including k-mer values, genome complexity, coverage depth, directional reads, etc. Seven program conditions, four single k-mer assemblers (SK: SOAPdenovo, ABySS, Oases and Trinity) and three multiple k-mer methods (MK: SOAPdenovo-MK, trans-ABySS and Oases-MK) were tested. While small and large k-mer values performed better for reconstructing lowly and highly expressed transcripts, respectively, MK strategy worked well for almost all ranges of expression quintiles. Among SK tools, Trinity performed well across various conditions but took the longest running time. Oases consumed the most memory whereas SOAPdenovo required the shortest runtime but worked poorly to reconstruct full-length CDS. ABySS showed some good balance between resource usage and quality of assemblies. Conclusions: Our work compared the performance of publicly available transcriptome assemblers, and analyzed important factors affecting de novo assembly. Some practical guidelines for transcript reconstruction from short-read RNA-Seq data were proposed. De novo assembly of C. sinensis transcriptome was greatly improved using some optimized methods.

Background: Tea is the most popular non-alcoholic health beverage in the world. The tea plant (Camellia sinensis (L.) O. Kuntze) needs to undergo a cold acclimation process to enhance its freezing tolerance in winter. Changes that occur at the molecular level in response to low temperatures are poorly understood in tea plants. To elucidate the molecular mechanisms of cold acclimation, we employed RNA-Seq and digital gene expression (DGE) technologies to the study of genome-wide expression profiles during cold acclimation in tea plants. Results: Using the Illumina sequencing platform, we obtained approximately 57.35 million RNA-Seq reads. These reads were assembled into 216,831 transcripts, with an average length of 356 bp and an N50 of 529 bp. In total, 1,770 differentially expressed transcripts were identified, of which 1,168 were up-regulated and 602 down-regulated. These include a group of cold sensor or signal transduction genes, cold-responsive transcription factor genes, plasma membrane stabilization related genes, osmosensing-responsive genes, and detoxification enzyme genes. DGE and quantitative RT-PCR analysis further confirmed the results from RNA-Seq analysis. Pathway analysis indicated that the “carbohydrate metabolism pathway” and the “calcium signaling pathway” might play a vital role in tea plants’ responses to cold stress. Conclusions: Our study presents a global survey of transcriptome profiles of tea plants in response to low, non-freezing temperatures and yields insights into the molecular mechanisms of tea plants during the cold acclimation process. It could also serve as a valuable resource for relevant research on cold-tolerance and help to explore the cold-related genes in improving the understanding of low-temperature tolerance and plant-environment interactions.

Recent advances in next-generation sequencing technology allow high-throughput cDNA sequencing (RNA-Seq) to be widely applied in transcriptomic studies, in particular for detecting differentially expressed genes between groups. Many software packages have been developed for the identification of differentially expressed genes (DEGs) between treatment groups based on RNA-Seq data. However, there is a lack of consensus on how to approach an optimal study design and choice of suitable software for the analysis. In this comparative study we evaluate the performance of three of the most frequently used software tools: Cufflinks-Cuffdiff2, DESeq and edgeR. A number of important parameters of RNA-Seq technology were taken into consideration, including the number of replicates, sequencing depth, and balanced vs. unbalanced sequencing depth within and between groups. We benchmarked results relative to sets of DEGs identified through either quantitative RT-PCR or microarray. We observed that edgeR performs slightly better than DESeq and Cuffdiff2 in terms of the ability to uncover true positives. Overall, DESeq or taking the intersection of DEGs from two or more tools is recommended if the number of false positives is a major concern in the study. In other circumstances, edgeR is slightly preferable for differential expression analysis at the expense of potentially introducing more false positives.

The RNA modification N⁶-methyladenosine (m⁶A) influences mRNA stability and cell-type-specific developmental programming, and is highly abundant in the adult brain. However, it has not been determined whether m⁶A is dynamically regulated by experience. Based on transcriptome-wide profiling of m⁶A, we report that the level of m⁶A increases in the medial prefrontal cortex (mPFC) of mice in response to behavioral experience. The modulation was enriched near the stop codon of mRNAs, including genes related to neuronal plasticity. In primary cortical neurons, in vitro, modulation of m⁶A by the RNA demethylase FTO influenced the degradation profiles of a subset of transcripts with modulated sites. In vivo, the expression of Fto and the m⁶A methyltransferase, Mettl3 correlated with the observed increase in m⁶A levels post-training. Furthermore, targeted knockdown of FTO in the mPFC led to enhanced consolidation of cued fear memory. Thus, together with its role in early development, the dynamic regulation of m⁶A in the adult brain serves as an important epitranscriptomic mechanism associated with behavioral adaptation. SIGNIFICANCE STATEMENTN⁶-methyladenosine (m⁶A) is the most prevalent internal modification on RNA, however, its cellular dynamics in vivo remains elusive. Here we provide the first demonstration of m⁶A upregulation in the mouse medial prefrontal cortex (mPFC) following behavioral training. Knocking down the m⁶A demethylase FTO in the mPFC, which increases total m⁶A level, results in enhanced consolidation of fear memory. Our findings suggest that m⁶A is regulated in an activity-dependent manner in the adult brain, and may function to fine-tune mRNA turnover during memory-related processes.

Significance: We have discovered a critical role for ten-eleven translocation 3-mediated hydroxylation of 5-methycytosine in the adult prefrontal cortex in mediating rapid behavioral adaptation. 5-hydroxymethylcytosine (5-hmC) is highly dynamic in response to fear extinction training, and rather than simply reflecting a functional intermediary of active DNA demethylation, the learning-induced intergenic accumulation of 5-hmC creates an epigenetic state that promotes experience-dependent gene expression and behavioral adaptation.

Major secondary metabolites, including flavonoids, caffeine, and theanine, are important components of tea products and are closely related to the taste, flavor, and health benefits of tea. Secondary metabolite biosynthesis in Camellia sinensis is differentially regulated in different tissues during growth and development. Until now, little was known about the expression patterns of genes involved in secondary metabolic pathways or their regulatory mechanisms. This study aimed to generate expression profiles for C. sinensis tissues and to build a gene regulation model of the secondary metabolic pathways. RNA sequencing was performed on 13 different tissue samples from various organs and developmental stages of tea plants, including buds and leaves of different ages, stems, flowers, seeds, and roots. A total of 43.7 Gbp of raw sequencing data were generated, from which 347,827 unigenes were assembled and annotated. There were 46,693, 8446, 3814, 10,206, and 4948 unigenes specifically expressed in the buds and leaves, stems, flowers, seeds, and roots, respectively. In total, 1719 unigenes were identified as being involved in the secondary metabolic pathways in C. sinensis, and the expression patterns of the genes involved in flavonoid, caffeine, and theanine biosynthesis were characterized, revealing the dynamic nature of their regulation during plant growth and development. The possible transcription factor regulation network for the biosynthesis of flavonoid, caffeine, and theanine was built, encompassing 339 transcription factors from 35 families, namely bHLH, MYB, and NAC, among others. Remarkably, not only did the data reveal the possible critical check points in the flavonoid, caffeine, and theanine biosynthesis pathways, but also implicated the key transcription factors and related mechanisms in the regulation of secondary metabolite biosynthesis. Our study generated gene expression profiles for different tissues at different developmental stages in tea plants. The gene network responsible for the regulation of the secondary metabolic pathways was analyzed. Our work elucidated the possible cross talk in gene regulation between the secondary metabolite biosynthetic pathways in C. sinensis. The results increase our understanding of how secondary metabolic pathways are regulated during plant development and growth cycles, and help pave the way for genetic selection and engineering for germplasm improvement.