Effect of prior drought and heat stress on Camellia sinensis transcriptome changes to Ectropis oblique (Lepidoptera: Geometridae) resistance.

Tea plants are continuously confronted with a wide range of biotic and abiotic stressors in the field, which can occur concurrently or sequentially. To elucidate the molecular mechanisms in responses to such individual and combined stresses, we used RNAseq to compare the temporal changes in the transcriptome of Camellia sinensis to Ectropis oblique Prout alone or in combination with exposure to drought and heat. Compared with the individual stress, tea plants exhibit significant differences in transcriptome profiles under the combined stresses. Additionally, many unique genes exhibited significant differences in expression in individual and combined stress conditions. Our research showed novel insights into the molecular mechanisms of E. oblique Prout resistance in tea plants and provided a valuable resource for developing tea varieties with broad spectrum stress tolerance.

Transcriptomic analysis of tea plant (Camellia sinensis) revealed the co-expression network of 4111 paralogous genes and biosynthesis of quality-related key metabolites under multiple stresses.

The tea plant is an essential economic plant in many countries. However, its growing season renders them vulnerable to stresses. To understand the transcriptomic influences of these stresses on tea plants, we sequenced and analyzed the transcriptomes under drought, high-temperature, and pest. Paralogs were identified by comparing 14 evolutionarily close genomes. The differentially expressed paralog (DEPs) genes were analyzed regarding single or multiple stresses, and 1075 of the 4111 DEPs were commonly found in all the stresses. The co-expression network of the DEPs and TFs indicated that genes of catechin biosynthesis were associated with most transcription factors specific to each stress. The genes playing a significant role in the late response to drought and pest stress mainly functioned in the early response to high-temperature. This study revealed the relationship between stress and regulation of QRM synthesis and the role of QRMs in response to these (a)biotic stresses.

The differential expression patterns and co-expression networks of paralogs as an indicator of the TNM stages of lung adenocarcinoma and squamous cell carcinoma.

Cancers constitute a severe threat to human health. Elucidating the association between the expression patterns of the paralogous genes and transcription factors (TF) and the progression of cancers by comprehensively investigating the expression patterns and co-expression networks will contribute to the in-depth understanding of the pathogenesis of cancers. Here, we identified the paralogous gene pairs and systematically analyzed the expression patterns of these paralogs and the known TFs to elucidate the associations with Tumor, Node, Metastasis (TNM) staging information across ten cancers. We found that the expression of ~60% paralogs was cancer-dependent, and more than 50% of the differentially expressed TFs pairs showed positive expression correlations. The down-regulation patterns of paralogs and TFs were closely associated with the M and N developmental stages of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Our results will help to understand the roles of paralogs and TFs in cancer progression and to screen prognostic biomarkers for early cancer diagnosis.

The differential expression patterns of paralogs in response to stresses indicate expression and sequence divergences.

BACKGROUND: Theoretically, paralogous genes generated through whole genome duplications should share identical expression levels due to their identical sequences and chromatin environments. However, functional divergences and expression differences have arisen due to selective pressures throughout evolution. A comprehensive investigation of the expression patterns of paralogous gene pairs in response to various stresses and a study of correlations between the expression levels and sequence divergences of the paralogs are needed. RESULTS: In this study, we analyzed the expression patterns of paralogous genes under different types of stress and investigated the correlations between the expression levels and sequence divergences of the paralogs. We analyzed the differential expression patterns of the paralogs under four different types of stress (drought, cold, infection, and herbivory) and classified them into three main types according to their expression patterns. We then further analyzed the differential expression patterns under various degrees of stress and constructed corresponding co-expression networks of differentially expressed paralogs and transcription factors. Finally, we investigated the correlations between the expression levels and sequence divergences of the paralogs and identified positive correlations between expression level and sequence divergence. With regard to sequence divergence, we identified correlations between selective pressures and phylogenetic relationships. CONCLUSIONS: These results shed light on differential expression patterns of paralogs in response to environmental stresses and are helpful for understanding the relationships between expression levels and sequences divergences.

Integrated transcriptomics and metabolomics analysis of catechins, caffeine and theanine biosynthesis in tea plant (Camellia sinensis) over the course of seasons.

BACKGROUND: Catechins, caffeine, and theanine as three important metabolites in the tea leaves play essential roles in the formation of specific taste and shows potential health benefits to humans. However, the knowledge on the dynamic changes of these metabolites content over seasons, as well as the candidate regulatory factors, remains largely undetermined. RESULTS: An integrated transcriptomic and metabolomic approach was used to analyze the dynamic changes of three mainly metabolites including catechins, caffeine, and theanine, and to explore the potential influencing factors associated with these dynamic changes over the course of seasons. We found that the catechins abundance was higher in Summer than that in Spring and Autumn, and the theanine abundance was significantly higher in Spring than that in Summer and Autumn, whereas caffeine exhibited no significant changes over three seasons. Transcriptomics analysis suggested that genes in photosynthesis pathway were significantly down-regulated which might in linkage to the formation of different phenotypes and metabolites content in the tea leaves of varied seasons. Fifty-six copies of nine genes in catechins biosynthesis, 30 copies of 10 genes in caffeine biosynthesis, and 12 copies of six genes in theanine biosynthesis were detected. The correlative analysis further presented that eight genes can be regulated by transcription factors, and highly correlated with the changes of metabolites abundance in tea-leaves. CONCLUSION: Sunshine intensity as a key factor can affect photosynthesis of tea plants, further affect the expression of major Transcription factors (TFs) and structural genes in, and finally resulted in the various amounts of catechins, caffeine and theaine in tea-leaves over three seasons. These findings provide new insights into abundance and influencing factors of metabolites of tea in different seasons, and further our understanding in the formation of flavor, nutrition and medicinal function.

Small design from big alignment: engineering proteins with multiple sequence alignment as the starting point.

Multiple sequence alignment (MSA) is a fundamental way to gain information that cannot be obtained from the analysis of any individual sequence included in the alignment. It provides ways to investigate the relationship between sequence and function from a perspective of evolution. Thus, the MSA of proteins can be employed as a reference for protein engineering. In this paper, we reviewed the recent advances to highlight how protein engineering was benefited from the MSA of proteins. These methods include (1) engineering the thermostability or solubility of proteins by making it closer to the consensus sequence of the alignment through introducing site mutations; (2) structure-based engineering proteins with comparative modeling; (3) creating paleoenzymes featured with high thermostability and promiscuity by constructing the ancestral sequences derived from multiple sequence alignment; and (4) incorporating site-mutations targeting the evolutionarily coupled sites identified from multiple sequence alignment.

Intrachromosomal colocalization strengthens co-expression, co-modification and evolutionary conservation of neighboring genes.

BACKGROUND: Gene order and location in chromosomes of species are non-random. Neighboring gene pairs tend to display some similarities, such as co-expression and co-modification. However, the contribution of linear proximity, spatial proximity, and evolutionary proximity to these similarities remain unclear, together with whether the presence of several types of proximity can strengthens the similarities. RESULTS: In this study, we investigated the properties of three kinds of colocalized gene pairs: intrachromosomal colocalized gene pairs, always-neighboring gene pairs, and evolutionary neighboring gene pairs. Our analysis showed that (1) Different types of colocalized genes differentially contribute to co-expression, co-modifications and conservation across species; (2) Intrachromosomal colocalization can strengthen co-expression and co-modification of neighboring gene pairs and their conservation across species; (3) The combination of the three kinds of colocalization can lead to the strongest co-modification and is most strongly conserved across species. (4) Colocalized gene pairs are indicative of phylogenetic relationships and whole genome duplications (WGDs). CONCLUSIONS: These results provide valuable clues for future efforts to understand the characteristics of colocalized gene pairs and how the neighborhood affects their interactions.

The co-expression networks of differentially expressed RBPs with TFs and LncRNAs related to clinical TNM stages of cancers.

BACKGROUND: RNA-binding proteins (RBPs) play important roles in cellular homeostasis by regulating the expression of thousands of transcripts, which have been reported to be involved in human tumorigenesis. Despite previous reports of the dysregulation of RBPs in cancers, the degree of dysregulation of RBPs in cancers and the intrinsic relevance between dysregulated RBPs and clinical TNM information remains unknown. Furthermore, the co-expressed networks of dysregulated RBPs with transcriptional factors and lncRNAs also require further investigation. RESULTS: Here, we firstly analyzed the deviations of expression levels of 1,542 RBPs from 20 cancer types and found that (1) RBPs are dysregulated in almost all 20 cancer types, especially in BLCA, COAD, READ, STAD, LUAD, LUSC and GBM with proportion of deviation larger than 300% compared with non-RBPs in normal tissues. (2) Up- and down-regulated RBPs also show opposed patterns of differential expression in cancers and normal tissues. In addition, down-regulated RBPs show a greater degree of dysregulated expression than up-regulated RBPs do. Secondly, we analyzed the intrinsic relevance between dysregulated RBPs and clinical TNM information and found that (3) Clinical TNM information for two cancer types-CHOL and KICH-is shown to be closely related to patterns of differentially expressed RBPs (DE RBPs) by co-expression cluster analysis. Thirdly, we identified ten key RBPs (seven down-regulated and three up-regulated) in CHOL and seven key RBPs (five down-regulated and two up-regulated) in KICH by analyzing co-expression correlation networks. Fourthly, we constructed the co-expression networks of key RBPs between 1,570 TFs and 4,147 lncRNAs for CHOL and KICH, respectively. CONCLUSIONS: These results may provide an insight into the understanding of the functions of RBPs in human carcinogenesis. Furthermore, key RBPs and the co-expressed networks offer useful information for potential prognostic biomarkers and therapeutic targets for patients with cancers at the N and M stages in two cancer types CHOL and KICH.

Neighboring genes are closely related to whole genome duplications after their separation.

BACKGROUND: The gene order in a eukaryotic genome is not random. Some neighboring genes show specific similarities, while others become separated during evolution. Whole genome duplication events (WGDs) have been recognized as an important evolutionary force. The potential relationship between the separation of neighboring genes and WGDs needs to be investigated. In this study, we investigated whether there is a potential relationship between separated neighboring gene pairs and WGDs, and the mechanism by which neighboring genes are separated. Additionally, we studied whether neighboring genes tend to show intrachromosomal colocalization after their neighborhood was disrupted and the factors facilitating the intrachromosomal colocalization of separated neighboring genes. RESULTS: The separation of neighboring gene pairs is closely related to whole genome duplication events. Furthermore, we found that there is a double linear relationship between separated neighboring genes, total genes, and WGDs. The process of separation of neighboring genes caused by WGDs is also not random but abides by the double linear model. Separated neighboring gene pairs tend to show intrachromosomal colocalization. The conservativism of separated neighboring genes and histone modification facilitate the intrachromosomal colocalization of neighboring genes after their separation. CONCLUSIONS: These results provide new insight into the understanding of evolutionary roles of locations and the relationship of neighboring gene pairs with whole genome duplications. Furthermore, understanding the proposed mechanism for intrachromosomal colocalization of separated genes benefits our knowledge of chromosomal interactions in the nucleus.

A Complete and Accurate Ab Initio Repeat Finding Algorithm.

It has become clear that repetitive sequences have played multiple roles in eukaryotic genome evolution including increasing genetic diversity through mutation, changes in gene expression and facilitating generation of novel genes. However, identification of repetitive elements can be difficult in the ab initio manner. Currently, some classical ab initio tools of finding repeats have already presented and compared. The completeness and accuracy of detecting repeats of them are little pool. To this end, we proposed a new ab initio repeat finding tool, named HashRepeatFinder, which is based on hash index and word counting. Furthermore, we assessed the performances of HashRepeatFinder with other two famous tools, such as RepeatScout and Repeatfinder, in human genome data hg19. The results indicated the following three conclusions: (1) The completeness of HashRepeatFinder is the best one among these three compared tools in almost all chromosomes, especially in chr9 (8 times of RepeatScout, 10 times of Repeatfinder); (2) in terms of detecting large repeats, HashRepeatFinder also performed best in all chromosomes, especially in chr3 (24 times of RepeatScout and 250 times of Repeatfinder) and chr19 (12 times of RepeatScout and 60 times of Repeatfinder); (3) in terms of accuracy, HashRepeatFinder can merge the abundant repeats with high accuracy.

A de novo genome assembly algorithm for repeats and nonrepeats.

BACKGROUND: Next generation sequencing platforms can generate shorter reads, deeper coverage, and higher throughput than those of the Sanger sequencing. These short reads may be assembled de novo before some specific genome analyses. Up to now, the performances of assembling repeats of these current assemblers are very poor. RESULTS: To improve this problem, we proposed a new genome assembly algorithm, named SWA, which has four properties: (1) assembling repeats and nonrepeats; (2) adopting a new overlapping extension strategy to extend each seed; (3) adopting sliding window to filter out the sequencing bias; and (4) proposing a compensational mechanism for low coverage datasets. SWA was evaluated and validated in both simulations and real sequencing datasets. The accuracy of assembling repeats and estimating the copy numbers is up to 99% and 100%, respectively. Finally, the extensive comparisons with other eight leading assemblers show that SWA outperformed others in terms of completeness and correctness of assembling repeats and nonrepeats. CONCLUSIONS: This paper proposed a new de novo genome assembly method for resolving complex repeats. SWA not only can detect where repeats or nonrepeats are but also can assemble them completely from NGS data, especially for assembling repeats. This is the advantage over other assemblers.