Annotated Transcripts Research Articles

Nanopore sequencing unveils the complexity of the cold-activated murine brown adipose tissue transcriptome

Alternative transcription increases transcriptome complexity by expression of multiple transcripts per gene. Annotation and quantification of transcripts using short-read sequencing is non-trivial. Long-read sequencing aims at overcoming these problems by sequencing full-length transcripts. Activation of brown adipose tissue (BAT) thermogenesis involves major transcriptomic remodeling and positively affects metabolism via increased energy expenditure. We benchmark Oxford Nanopore Technology (ONT) long-read sequencing protocols to Illumina short-read sequencing assessing alignment characteristics, gene and transcript detection and quantification, differential gene and transcript expression, transcriptome reannotation, and differential transcript usage (DTU). We find ONT sequencing is superior to Illumina for transcriptome reassembly, reducing the risk of false-positive events by unambiguously mapping reads to transcripts. We identified novel isoforms of genes undergoing DTU in cold-activated BAT including Cars2, Adtrp, Acsl5, Scp2, Aldoa, and Pde4d, validated by real-time PCR. The reannotated murine BAT transcriptome established here provides a framework for future investigations into the regulation of BAT.

SUsPECT: a pipeline for variant effect prediction based on custom long-read transcriptomes for improved clinical variant annotation

Our incomplete knowledge of the human transcriptome impairs the detection of disease-causing variants, in particular if they affect transcripts only expressed under certain conditions. These transcripts are often lacking from reference transcript sets, such as Ensembl/GENCODE and RefSeq, and could be relevant for establishing genetic diagnoses. We present SUsPECT (Solving Unsolved Patient Exomes/gEnomes using Custom Transcriptomes), a pipeline based on the Ensembl Variant Effect Predictor (VEP) to predict variant impact on custom transcript sets, such as those generated by long-read RNA-sequencing, for downstream prioritization. Our pipeline predicts the functional consequence and likely deleteriousness scores for missense variants in the context of novel open reading frames predicted from any transcriptome. We demonstrate the utility of SUsPECT by uncovering potential mutational mechanisms of pathogenic variants in ClinVar that are not predicted to be pathogenic using the reference transcript annotation. In further support of SUsPECT’s utility, we identified an enrichment of immune-related variants predicted to have a more severe molecular consequence when annotating with a newly generated transcriptome from stimulated immune cells instead of the reference transcriptome. Our pipeline outputs crucial information for further prioritization of potentially disease-causing variants for any disease and will become increasingly useful as more long-read RNA sequencing datasets become available.

Transcriptional and translational landscape fine-tune genome annotation and explores translation control in cotton

IntroductionThe unavailability of intergenic region annotation in whole genome sequencing and pan-genomics hinders efforts to enhance crop improvement. ObjectivesDespite advances in research, the impact of post-transcriptional regulation on fiber development and translatome profiling at different stages of fiber growth in cotton (G. hirsutum) remains unexplored. MethodsWe utilized a combination of reference-guided de novo transcriptome assembly and ribosome profiling techniques to uncover the hidden mechanisms of translational control in eight distinct tissues of upland cotton. ResultsOur study identified P-site distribution at three-nucleotide periodicity and dominant ribosome footprint at 27 nucleotides. Specifically, we have detected 1,589 small open reading frames (sORFs), including 1,376 upstream ORFs (uORFs) and 213 downstream ORFs (dORFs), as well as 552 long non-coding RNAs (lncRNAs) with potential coding functions, which fine-tune the annotation of the cotton genome. Further, we have identified novel genes and lncRNAs with strong translation efficiency (TE), while sORFs were found to affect mRNA transcription levels during fiber elongation. The reliability of these findings was confirmed by the high consistency in correlation and synergetic fold change between RNA-sequencing (RNA-seq) and Ribosome-sequencing (Ribo-seq) analyses. Additionally, integrated omics analysis of the normal fiber ZM24 and short fiber pag1 cotton mutant revealed several differentially expressed genes (DEGs), and fiber-specific expressed (high/low) genes associated with sORFs (uORFs and dORFs). These findings were further supported by the overexpression and knockdown of GhKCS6, a gene associated with sORFs in cotton, and demonstrated the potential regulation of the mechanism governing fiber elongation on both the transcriptional and post-transcriptional levels. ConclusionReference-guided transcriptome assembly and the identification of novel transcripts fine-tune the annotation of the cotton genome and predicted the landscape of fiber development. Our approach provided a high-throughput method, based on multi-omics, for discovering unannotated ORFs, hidden translational control, and complex regulatory mechanisms in crop plants.

William Falconer's Manuscript Draft Poetry: An Annotated Transcription

William Falconer's Manuscript Draft Poetry: An Annotated Transcription

Assessment of a novel continuous cleaning device using metatranscriptomics in diverse hospital environments.

Despite routine implementation of cleaning and disinfection practices in clinical healthcare settings, high-touch environmental surfaces and contaminated equipment often serve as reservoirs for the transmission of pathogens associated with healthcare-associated infections (HAIs). The current study involved the analysis of high-touch surface swabs using a metatranscriptomic sequencing workflow (CSI-Dx™) to assess the efficacy of cleanSURFACES® technology in decreasing microbial burden by limiting re-contamination. This is a non-human single center study conducted in the Emergency Department (ED) and on an inpatient Oncology Ward of Walter Reed National Military Medical Center that have followed hygienic practices during the COVID-19 pandemic environment. Although there was no difference in observed microbial richness (two-tailed Wilcoxon test with Holm correction, P > 0.05), beta diversity findings identified shifts in microbial community structure between surfaces from baseline and post-intervention timepoints (Day 1, Day 7, Day 14, and Day 28). Biomarker and regression analyses identified significant reductions in annotated transcripts for various clinically relevant microorganisms' post-intervention, coagulase-negative staphylococci and Malassezia restricta, at ED and Oncology ward, respectively. Additionally, post-intervention samples predominantly consisted of Proteobacteria and to a lesser extent skin commensals and endogenous environmental microorganisms in both departments. Findings support the value of cleanSURFACES®, when coupled with routine disinfection practices, to effectively impact on the composition of active microbial communities found on high-touch surfaces in two different patient care areas of the hospital (one outpatient and one inpatient) with unique demands and patient-centered practices.

PATO: genome-wide prediction of lncRNA-DNA triple helices.

Long non-coding RNA (lncRNA) plays a key role in many biological processes. For instance, lncRNA regulates chromatin using different molecular mechanisms, including direct RNA-DNA hybridization via triplexes, cotranscriptional RNA-RNA interactions, and RNA-DNA binding mediated by protein complexes. While the functional annotation of lncRNA transcripts has been widely studied over the last 20 years, barely a handful of tools have been developed with the specific purpose of detecting and evaluating lncRNA-DNA triple helices. What is worse, some of these tools have nearly grown a decade old, making new triplex-centric pipelines depend on legacy software that cannot thoroughly process all the data made available by next-generation sequencing (NGS) technologies. We present PATO, a modern, fast, and efficient tool for the detection of lncRNA-DNA triplexes that matches NGS processing capabilities. PATO enables the prediction of triple helices at the genome scale and can process in as little as 1 h more than 60 GB of sequence data using a two-socket server. Moreover, PATO's efficiency allows a more exhaustive search of the triplex-forming solution space, and so PATO achieves higher levels of prediction accuracy in far less time than other tools in the state of the art. Source code, user manual, and tests are freely available to download under the MIT License at https://github.com/UDC-GAC/pato.

The adapted Activity-By-Contact model for enhancer-gene assignment and its application to single-cell data.

Identifying regulatory regions in the genome is of great interest for understanding the epigenomic landscape in cells. One fundamental challenge in this context is to find the target genes whose expression is affected by the regulatory regions. A recent successful method is the Activity-By-Contact (ABC) model which scores enhancer-gene interactions based on enhancer activity and the contact frequency of an enhancer to its target gene. However, it describes regulatory interactions entirely from a gene's perspective, and does not account for all the candidate target genes of an enhancer. In addition, the ABC model requires two types of assays to measure enhancer activity, which limits the applicability. Moreover, there is neither implementation available that could allow for an integration with transcription factor (TF) binding information nor an efficient analysis of single-cell data. We demonstrate that the ABC score can yield a higher accuracy by adapting the enhancer activity according to the number of contacts the enhancer has to its candidate target genes and also by considering all annotated transcription start sites of a gene. Further, we show that the model is comparably accurate with only one assay to measure enhancer activity. We combined our generalized ABC model with TF binding information and illustrated an analysis of a single-cell ATAC-seq dataset of the human heart, where we were able to characterize cell type-specific regulatory interactions and predict gene expression based on TF affinities. All executed processing steps are incorporated into our new computational pipeline STARE. The software is available at https://github.com/schulzlab/STARE. marcel.schulz@em.uni-frankfurt.de. Supplementary data are available at Bioinformatics online.

SMRT and Illumina sequencing provide insights into mechanisms of lignin and terpenoids biosynthesis in Pinus massoniana Lamb

Wood and oleoresin are important industrial raw materials with high economic value; however, their molecular formation and biosynthesis mechanisms in different tissues of Pinus massoniana remain unexplored. Therefore, we used single-molecule real-time sequencing technology (SMRT) and Illumina RNA sequencing to establish a transcriptome dataset and explore the expression pattern of genes related to secondary metabolites involved in wood formation and oleoresin biosynthesis in six different P. massoniana tissues. In total, 63.58 Gb of polymerase reads were obtained, including 41,407 isoforms with an average length of 1822 bp. We identified 3939 and 8785 isoforms and 161 and 481 transcription factors with tissue expression specificity and in the reproductive and vegetative organs, respectively. Eighty isoforms were annotated as cellulose synthases and 224 isoforms involved in lignin biosynthesis were enriched. Additionally, we identified 217 isoforms involved in the terpenoid biosynthesis pathway, with needles having the most tissue-specific genes for terpenoid biosynthesis. Some isoforms related to lignin biosynthesis were highly expressed in the xylem, according to the results of transcriptome sequencing and real-time quantitative reverse-transcription polymerase chain reaction. Our research confirmed the advantages of SMRT sequencing and provided valuable information for the transcriptional annotation of P. massoniana, which will be beneficial for producing better raw wood and oleoresin materials.

Comparative transcriptomic analysis of long noncoding RNAs in Leishmania-infected human macrophages.

It is well established that infection with Leishmania alters the host cell's transcriptome. Since mammalian cells have multiple mechanisms to control gene expression, different molecules, such as noncoding RNAs, can be involved in this process. MicroRNAs have been extensively studied upon Leishmania infection, but whether long noncoding RNAs (lncRNAs) are also altered in macrophages is still unexplored. We performed RNA-seq from THP-1-derived macrophages infected with Leishmania amazonensis (La), L. braziliensis (Lb), and L. infantum (Li), investigating a previously unappreciated fraction of macrophage transcriptome. We found that more than 24% of the total annotated transcripts and 30% of differentially expressed (DE) RNAs in Leishmania-infected macrophage correspond to lncRNAs. LncRNAs and protein coding RNAs with altered expression are similar among macrophages infected with the Leishmania species. Still, some species-specific alterations could occur due to distinct pathophysiology in which Li infection led to a more significant number of exclusively DE RNAs. The most represented classes among DE lncRNAs were intergenic and antisense lncRNAs. We also found enrichment for immune response-related pathways in the DE protein coding RNAs, as well as putative targets of the lncRNAs. We performed a coexpression analysis to explore potential cis regulation of coding and antisense noncoding transcripts. We identified that antisense lncRNAs are similarly regulated as its neighbor protein coding genes, such as the BAALC/BAALC-AS1, BAALC/BAALC-AS2, HIF1A/HIF1A-AS1, HIF1A/HIF1A-AS3 and IRF1/IRF1-AS1 pairs, which can occur as a species-specific modulation. These findings are a novelty in the field because, to date, no study has focused on analyzing lncRNAs in Leishmania-infected macrophage. Our results suggest that lncRNAs may account for a novel mechanism by which Leishmania can control macrophage function. Further research must validate putative lncRNA targets and provide additional prospects in lncRNA function during Leishmania infection.

Recognition of Handwritten Chinese Text by Segmentation: A Segment-Annotation-Free Approach

Online and offline handwritten Chinese text recognition (HTCR) has been studied for decades. Early methods adopted over-segmentation-based strategies but suffered from low speed, insufficient accuracy, and high cost of character-level segmentation annotations. Recently, segmentation-free methods based on hidden Markov model (HMM), connectionist temporal classification (CTC), and attention mechanism, have dominated the field of HCTR. However, people actually read texts character by character, especially for ideograms like Chinese. This raises a question, are segmentation-free strategies really the best solution to HCTR To explore this issue, we propose a new segmentation-based method for recognizing handwritten Chinese text that is implemented using an efficient fully convolutional network. A novel weakly supervised learning method is proposed to enable the network to be trained using only transcript annotations; thus, the expensive character-level segmentation annotations required by previous segmentation-based methods can be avoided. Owing to the lack of context modeling in fully convolutional networks, we further propose a contextual regularization method to integrate contextual information into the network during the training stage, which can further improve the recognition performance. Extensive experiments on four widely used benchmarks, namely CASIA-HWDB, CASIA-OLHWDB, ICDAR2013, and SCUT-HCCDoc, show that our method significantly surpasses existing methods on both online and offline HCTR, and exhibits considerably higher inference speed than CTC/attention-based approaches.

A legal deed in Irish, 1622

This paper presents an annotated transcription and translation of a legal deed in Irish, dated 1622, recording an agreement between Cairbre Ó Conchubhair and Richard Lane, pertaining to lands in Co. Roscommon. Historical background is provided as an introduction.

Transcriptome Profiling and Bioinformatic Analysis of the Fourth-Stage Larvae of Angiostrongylus cantonensis.

To explore the transcriptome profiling of the fourth-stage larvae of Angiostrongylus cantonensis. Two groups of fourth-stage larvae were collected to extract total RNA in Zhejiang, China 2020. Then, mRNA was separated and reverse transcribed into cDNA. Next-generation sequencing was used to explore the transcriptome information. Finally, to obtain the biological annotation information, the transcriptome information was run against the related databases, including Nr, GO, COG, KOG and ORF. Overall, 128667 unigenes and 193059 transcripts were obtained. The Nr annotations of unigenes and transcripts showed that A. cantonensis was the 5th and 4th most related species, respectively. Meanwhile, the annotation of unigenes and transcripts by querying GO, COG, KOG and ORF showed that L4 was extremely active in gene expression, concerning signal transduction, transcription, posttranslational modification, metabolism, etc. The fourth-stage larvae of A. cantonensis have their own profiling in the transcriptome, which is related to signal transduction, transcription, posttranslational modification, metabolism, etc.

CFA: An explainable deep learning model for annotating the transcriptional roles of cis-regulatory modules based on epigenetic codes

Metazoa gene expression is controlled by modular DNA segments called cis-regulatory modules (CRMs). CRMs can convey promoter/enhancer/insulator roles, generating additional regulation layers in transcription. Experiments for understanding CRM roles are low-throughput and costly. Large-scale CRM function investigation still depends on computational methods. However, existing in silico tools only recognize enhancers or promoters exclusively, thus accumulating errors when considering CRM promoter/enhancer/insulator roles altogether. Currently, no algorithm can concurrently consider these CRM roles. In this research, we developed the CRM Function Annotator (CFA) model. CFA provides complete CRM transcriptional role labeling based on epigenetic profiling interpretation. We demonstrated that CFA achieves high performance (test macro auROC/auPRC = 94.1%/90.3%) and outperforms existing tools in promoter/enhancer/insulator identification. CFA is also inspected to recognize explainable epigenetic codes consistent with previous findings when labeling CRM roles. By considering the higher-order combinations of the epigenetic codes, CFA significantly reduces false-positive rates in CRM transcriptional role annotation. CFA is available at https://github.com/cobisLab/CFA/.

Genomic Characteristics of Elite Maize Inbred Line 18-599 and Its Transcriptional Response to Drought and Low-Temperature Stresses

Elite inbred line 18-599 was developed via triple test cross from introduced hybrid P78599 and used as parents of dozens of maize hybrids adapting to the diverse ecological conditions of the maize ecological region in Southwest China. In this study, its genomic DNA was resequenced and aligned with the B73 genome sequence to identify single nucleotide polymorphism (SNP), and insertion (In) and deletion (Del) loci. These loci were aligned with those between B73 and 1020 inbred lines in the HapMap database to identify specific variation loci of 18-599. The results showed that there were 930,439 specific SNPs and 358,750 InDels between 18-599 and the 1020 lines. In total, 21,961 of them showed significant impacts on the functions of 12,297 genes, such as frameshift, change of splicing site, stop gain, change of start site, and stop loss. Phylogenetic analysis showed that 18-599 was closely related to inbred lines ZEAxujRAUDIAAPE and 2005-4, but far from some inbred lines directly isolated from P78599. This result indicated that 18-599 not only pyramided the elite genes of P78599, but also acquired genetic divergence during the repetitive backcrosses of triple test cross to confer its elite agronomic characteristics. Subsequently, the RNA of 18-599 was sequenced. The aligned 9713 and 37,528 of the 165,098 unigenes were screened and aligned with annotated transcripts of the B73 genome differentially expressed under drought and low-temperature stress, respectively, and their functions were involved in the responses to these stresses. The quantitative PCR results of fourteen random genes verified the RNA sequencing results. These findings suggest that the transcriptional responses of many resistance-related genes were an important mechanism for 18-599 to adapt to diverse ecological conditions.

GENCODE: reference annotation for the human and mouse genomes in 2023.

GENCODE produces high quality gene and transcript annotation for the human and mouse genomes. All GENCODE annotation is supported by experimental data and serves as a reference for genome biology and clinical genomics. The GENCODE consortium generates targeted experimental data, develops bioinformatic tools and carries out analyses that, along with externally produced data and methods, support the identification and annotation of transcript structures and the determination of their function. Here, we present an update on the annotation of human and mouse genes, including developments in the tools, data, analyses and major collaborations which underpin this progress. For example, we report the creation of a set of non-canonical ORFs identified in GENCODE transcripts, the LRGASP collaboration to assess the use of long transcriptomic data to build transcript models, the progress in collaborations with RefSeq and UniProt to increase convergence in the annotation of human and mouse protein-coding genes, the propagation of GENCODE across the human pan-genome and the development of new tools to support annotation of regulatory features by GENCODE. Our annotation is accessible via Ensembl, the UCSC Genome Browser and https://www.gencodegenes.org.

The combination of SMRT sequencing and Illumina sequencing highlights organ-specific and age-specific expression patterns of miRNAs in Sika Deer.

Due to the lack of high-quality Sika Deer (Cervus nippon) transcriptome and sRNAome across multiple organs or development stages, it is impossible to comprehensively analyze the mRNA and miRNA regulatory networks related to growth, development and immunity response. In this study, we used single molecule-real time sequencing (SMRT-seq) and Illumina sequencing methods to generate transcriptome and sRNAome from ten tissues and four age groups of Sika Deer to help us understand molecular characteristics and global miRNA expression profiles. The results showed that a total of 240,846 consensus transcripts were generated with an average length of 2,784 bp. 4,329 Transcription factors (TFs), 109,000 Simple Sequence Repeats (SSRs) and 18,987 Long non-coding RNAs (LncRNAs) were identified. Meanwhile, 306 known miRNAs and 143 novel miRNAs were obtained. A large number of miRNAs showed organ-specific and age-specific differential expression patterns. In particular, we found that the organ-specific miRNAs were enriched in the brain, some of which shared only between the brain and adrenal. These miRNAs were involved in maintaining specific functions within the brain and adrenal. By constructing miRNA96mRNA interaction networks associated with Sika Deer immunity, we found that miRNAs (miR-148a, miR-26a, miR-214, let-7b, etc.) and mRNAs (CD6, TRIM38, C3, CD163, etc.) might play an important role in the immune response of Sika Deer spleen. Together, our study generated an improved transcript annotation for Sika Deer by SMRT-seq and revealed the role of miRNA in regulating the growth, development and immunity response of Sika Deer.

Nutritional and metabolic process of the dung beetle Phelotrupes auratus depends on the plant ingredients that the herbivores eat

BackgroundThe dung beetle Phelotrupes auratus is a holometabolous insect belonging to the order Coleoptera, and it is widely distributed in Japan. The P. auratus habitat depends on herbivores. P. auratus eats the dung of the herbivores and carries it underground for its young. In this process, herbivore droppings disappear from the ground, not only keeping the ground hygienic but also maintaining good soil conditions for plant growth. In this way, a rich ecosystem is maintained. In recent years, the population of P. auratus has decreased, and the main cause has been the decrease in grazing land. It seems that Japanese dung beetles are mainly dependent on herbivores for nutrient sources. However, the physiological relationship between herbivores and P. auratus has not been well investigated. Here, we investigated the nutritional metabolism system of P. auratus by performing whole gene expression analysis of individuals collected from two areas where the ecosystem is occupied by different herbivores.ResultsWe obtained 54,635 transcripts from P. auratus from Nara Park and Cape Toi and identified 2,592 differentially expressed genes in the fat bodies of the Nara Park and Cape Toi groups. We annotated P. auratus transcripts using Homo sapiens and Drosophila melanogaster genes as references; 50.5% of P. auratus transcripts were assigned to H. sapiens genes, and 54.0% of P. auratus transcripts were assigned to D. melanogaster genes. To perform gene set enrichment analysis, we chose H. sapiens genes for P. auratus transcript annotation. Principal component analysis and gene set enrichment analysis revealed that the nutritional metabolism of P. auratus from Cape Toi might differ from that of P. auratus from Nara Park.ConclusionWe analyzed the nutritional metabolism system of P. auratus from Cape Toi and Nara Park and found that the characteristics of the nutritional metabolism process might depend on the plants consumed by the herbivores. Our findings will contribute to elucidating the relationships among habitat plants, herbivores, and dung decomposers and may aid in the maintenance of sustainable land health cycles.

Improving Infinium MethylationEPIC data processing: re-annotation of enhancers and long noncoding RNA genes and benchmarking of normalization methods

ABSTRACT Illumina Infinium DNA Methylation (5mC) arrays are a popular technology for low-cost, high-throughput, genome-scale measurement of 5mC distribution, especially in cancer and other complex diseases. After the success of its HumanMethylation450 array (450k), Illumina released the MethylationEPIC array (850k) featuring increased coverage of enhancers. Despite the widespread use of 850k, analysis of the corresponding data remains suboptimal: it still relies mostly on Illumina’s default annotation, which underestimates enhancerss and long noncoding RNAs. Results: We have thus developed an approach, based on the ENCODE and LNCipedia databases, which greatly improves upon Illumina’s default annotation of enhancers and long noncoding transcripts. We compared the re-annotated 850k with both 450k and reduced-representation bisulphite sequencing (RRBS), another high-throughput 5mC profiling technology. We found 850k to cover at least three times as many enhancers and long noncoding RNAs as either 450k or RRBS. We further investigated the reproducibility of the three technologies, applying various normalization methods to the 850k data. Most of these methods reduced variability to a level below that of RRBS data. We then used 850k with our new annotation and normalization to profile 5mC changes in breast cancer biopsies. 850k highlighted aberrant enhancer methylation as the predominant feature, in agreement with previous reports. Our study provides an updated processing approach for 850k data, based on refined probe annotation and normalization, allowing for improved analysis of methylation at enhancers and long noncoding RNA genes. Our findings will help to further advance understanding of the DNA methylome in health and disease.

Transcriptomic complexity of the human malaria parasite Plasmodium falciparum revealed by long-read sequencing.

The Plasmodium falciparum human malaria parasite genome is incompletely annotated and does not accurately represent the transcriptomic diversity of this species. To address this need, we performed long-read transcriptomic sequencing. 5' capped mRNA was enriched from samples of total and nuclear-fractionated RNA from intra-erythrocytic stages and converted to cDNA library. The cDNA libraries were sequenced on PacBio and Nanopore long-read platforms. 12,495 novel isoforms were annotated from the data. Alternative 5' and 3' ends represent the majority of isoform events among the novel isoforms, with retained introns being the next most common event. The majority of alternative 5' ends correspond to genomic regions with features similar to those of the reference transcript 5' ends. However, a minority of alternative 5' ends showed markedly different features, including locations within protein-coding regions. Alternative 3' ends showed similar features to the reference transcript 3' ends, notably adenine-rich termination signals. Distinguishing features of retained introns could not be observed, except for a tendency towards shorter length and greater GC content compared with spliced introns. Expression of antisense and retained intron isoforms was detected at different intra-erythrocytic stages, suggesting developmental regulation of these isoform events. To gain insights into the possible functions of the novel isoforms, their protein-coding potential was assessed. Variants of P. falciparum proteins and novel proteins encoded by alternative open reading frames suggest that P. falciparum has a greater proteomic repertoire than the current annotation. We provide a catalog of annotated transcripts and encoded alternative proteins to support further studies on gene and protein regulation of this pathogen.

Dehydration response in Stylosanthes scabra: Transcriptional, biochemical, and physiological modulations.

Stylosanthes scabra, popularly known as stylo, is native to the Brazilian Caatinga semiarid region and stands out as a drought-tolerant shrub forage crop. This work provides information about the plant response during the first 48 h of water deficit, followed by a rehydration treatment. Besides root transcriptomics data, 13 physiological or biochemical parameters were scrutinized. Additionally, RNA-Seq annotated transcripts not associated with the "Viridiplantae" clade were taxonomically categorized. It was found that S. scabra quickly perceives and recovers from the oscillations of the imposed water regime. Physiologically, mechanisms that minimize evapotranspiration or protect the photosynthetic apparatus stood out. Biochemically, it was found that the root tissue invests in synthesizing compounds that can act as osmolytes (proline and sugars), emphasizing the importance of osmoregulation to water deficit acclimation. Consistently, transcriptome and qPCR analyses showed that a set of enriched biological processes with upregulated (UR) transcripts were involved in protective functions against reactive oxygen species or encoding enzymes of important metabolic pathways, which might contribute to S. scabra response to water deficit. Additionally, several UR kinases and transcription factors were identified. Finally, in an innovative approach, some naturally occurring microbial groups (such as Schizosaccharomyces, Bradyrhizobium, etc.) were identified in the S. scabra roots. This study reveals insights into the physiological, biochemical, and molecular mechanisms underlying the S. scabra response to water deficit and provides candidate genes that may be useful in developing drought-tolerant crop varieties through biotechnological applications.