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Background Duckweeds are small, rapidly growing aquatic flowering plants. Due to their ability for biomass production at high rates they represent promising candidates for biofuel feedstocks. Duckweeds are also excellent model organisms because they can be maintained in well-defined liquid media, usually reproduce asexually, and because genomic resources are becoming increasingly available. To demonstrate the utility of duckweed for integrated metabolic studies, we examined the metabolic adaptation of growing Lemna gibba cultures to different nutritional conditions. Results To establish a framework for quantitative metabolic research in duckweeds we derived a central carbon metabolism network model of Lemna gibba based on its draft genome. Lemna gibba fronds were grown with nitrate or glutamine as nitrogen source. The two conditions were compared by quantification of growth kinetics, metabolite levels, transcript abundance, as well as by 13 C-metabolic flux analysis. While growing with glutamine, the fronds grew 1.4 times faster and accumulated more protein and less cell wall components compared to plants grown on nitrate. Characterization of photomixotrophic growth by 13 C-metabolic flux analysis showed that, under both metabolic growth conditions, the Calvin-Benson-Bassham cycle and the oxidative pentose-phosphate pathway are highly active, creating a futile cycle with net ATP consumption. Depending on the nitrogen source, substantial reorganization of fluxes around the tricarboxylic acid cycle took place, leading to differential formation of the biosynthetic precursors of the Asp and Gln families of proteinogenic amino acids. Despite the substantial reorganization of fluxes around the tricarboxylic acid cycle, flux changes could largely not be associated with changes in transcripts. Conclusions Through integrated analysis of growth rate, biomass composition, metabolite levels, and metabolic flux, we show that Lemna gibba is an excellent system for quantitative metabolic studies in plants. Our study showed that Lemna gibba adjusts to different nitrogen sources by reorganizing central metabolism. The observed disconnect between gene expression regulation and metabolism underscores the importance of metabolic flux analysis as a tool in such studies.

Background The phytoflagellated protozoan, Euglena gracilis , has been proposed as an attractive feedstock for the accumulation of valuable compounds such as β-1,3-glucan, also known as paramylon, and wax esters. The production of wax esters proceeds under anaerobic conditions, designated as wax ester fermentation. In spite of the importance and usefulness of Euglena , the genome and transcriptome data are currently unavailable, though another research group has recently published E.gracilis transcriptome study during our submission. We herein performed an RNA-Seq analysis to provide a comprehensive sequence resource and some insights into the regulation of genes including wax ester metabolism by comparative transcriptome analysis of E.gracilis under aerobic and anaerobic conditions. Results The E.gracilis transcriptome analysis was performed using the Illumina platform and yielded 90.3 million reads after the filtering steps. A total of 49,826 components were assembled and identified as a reference sequence of E.gracilis , of which 26,479 sequences were considered to be potentially expressed (having FPKM value of greater than 1). Approximately half of all components were estimated to be regulated in a trans -splicing manner, with the addition of protruding spliced leader sequences. Nearly 40 % of 26,479 sequences were annotated by similarity to Swiss-Prot database using the BLASTX program. A total of 2080 transcripts were identified as differentially expressed genes (DEGs) in response to anaerobic treatment for 24 h. A comprehensive pathway enrichment analysis using the KEGG pathway revealed that the majority of DEGs were involved in photosynthesis, nucleotide metabolism, oxidative phosphorylation, fatty acid metabolism. We successfully identified a candidate gene set of paramylon and wax esters, including novel β-1,3-glucan and wax ester synthases. A comparative expression analysis of aerobic- and anaerobic-treated E.gracilis cells indicated that gene expression changes in these components were not extensive or dynamic during the anaerobic treatment. Conclusion The RNA-Seq analysis provided comprehensive transcriptome information on E.gracilis for the first time, and this information will advance our understanding of this unique organism. The comprehensive analysis indicated that paramylon and wax ester metabolic pathways are regulated at post-transcriptional rather than the transcriptional level in response to anaerobic conditions.

Transcriptome analysis in single cells, enabled by single-cell RNA sequencing, has become a prevalent approach in biomedical research, ranging from investigations of gene regulation to the characterization of tissue organization. Over the past decade, advances in single-cell RNA sequencing technology, including its underlying chemistry, have significantly enhanced its performance, marking notable improvements in methodology. A recent development in the field, which integrates RNA metabolic labeling with single-cell RNA sequencing, has enabled the profiling of temporal transcriptomes in individual cells, offering new insights into dynamic biological processes involving RNA kinetics and cell fate determination. In this review, we explore the chemical principles and design improvements that have enhanced single-molecule capture efficiency, improved RNA quantification accuracy, and increased cellular throughput in single-cell transcriptome analysis. We also illustrate the concept of RNA metabolic labeling for detecting newly synthesized transcripts and summarize recent advancements that enable single-cell temporal transcriptome analysis. Additionally, we examine data analysis strategies for the precise quantification of newly synthesized transcripts and highlight key applications of transcriptome and temporal transcriptome analyses in single cells.

Background Intermuscular bones (IBs) are segmental intramembranous ossifications located within myosepta. They share similarities with tendon ossification, a form of heterotopic ossification (HO). The mechanisms underlying IB formation remain incompletely understood. Results In this study, we systematically analyzed transcriptome data across multiple tissues, species, time points, and resolutions in teleosts. First, we identified IB-specific expression genes using the tau index method. Through cross-species comparisons of the tendon development process, we discovered that candidate genes were primarily enriched in extracellular matrix organization, ossification, regulation of angiogenesis, and other related processes. We also revealed that some of these candidate genes are abnormally expressed in runx2b −/− zebrafish, which lack IBs. To clarify the trajectory of cell differentiation during IB formation, we demonstrated that myoseptal stem cells differentiate into osteoblasts, fibroblasts, and tenocytes in runx2b +/+ zebrafish. However, in runx2b −/− zebrafish, the differentiation of myoseptal stem cell into osteoblast was inhibited, while differentiation into clec3bb  + tenocyte and fibroblast was enhanced. Additionally, runx2b deficiency led to the upregulation of clec3bb expression in the clec3bb  + tenocyte cluster. Notably, a compensatory effect was observed in cell differentiation and gene expression in runx2b −/− zebrafish, suggesting that runx2b and the candidate genes, such as clec3bb , were involved in the gene network of IB development. Conclusions The results elucidate cell differentiation process during tendon ossification in teleosts and identify the key factor clec3bb involved in this process. These findings provide a foundation for understanding tendon ossification in teleosts and for further research on tendon ossification in mammals.

Cotton fibers, derived from the epidermis of the ovule, provide a sustainable natural fiber source for the textile industry. Traits related to fiber yield are predominantly determined by molecular regulations in the epidermis of the outer integument (OI) region of the cotton ovule. Here, we identify an R2R3 MYB transcription factor coding gene GhLPF1 within the QTL‐LP‐ChrA06 locus for lint percentage (LP, percentage of lint to seed cotton) through constructing the 1‐Day Post Anthesis Cotton Ovule Spatial Transcriptome Atlas. GhLPF1 is subjected as a downstream target of miR828 during fiber development. The direct downstream genes (DDGs) of GhLPF1 are biased to increased expression in GhLPF1‐CR, and are preferentially expressed in OI, so that GhLPF1 is primarily a transcriptional repressor to its DDGs. Population‐wide transcriptome analysis confirms that expression variation of GhLPF1‐DDGs is significantly biased to negative correlation with LP, among which a type I homeobox protein‐coding gene GhHB6 is further validated to be the directly downstream gene of GhLPF1. Given these data, it is demonstrated that GhLPF1 mediates a regulation network in LP as a transcriptional repressor, which makes it a valuable functional marker for fiber‐trait improvement application from QTL‐LP‐ChrA06. Utilizing spatial transcriptome analysis, a novel R2R3 MYB coding gene GhLPF1 is identified as a key regulator within the QTL‐LP‐ChrA06 interval. Phenotypic analysis of GhLPF1 transgenic cotton plants further supports its crucial function in fiber development. Additionally, an integrative analysis of CUT&Tag‐Seq and RNA‐Seq data demonstrates that GhLPF1 acts as a transcriptional repressor for its directly downstream target genes.

Keratinization is one of lung squamous cell cancer’s (LUSC) hallmark histopathology features. Epithelial cells produce keratin to protect their integrity from external harmful substances. In addition to their roles as cell protectors, recent studies have shown that keratins have important roles in regulating either normal cell or tumor cell functions. The objective of this study is to identify the genes and microRNAs (miRNAs) that act as key regulators of the keratinization process in LUSC. To address this goal, we classified LUSC samples from GDC-TCGA databases based on their keratinization molecular signatures. Then, we performed differential analyses of genes, methylation, and miRNA expression between high keratinization and low keratinization samples. By reconstruction and analysis of the differentially expressed genes (DEGs) network, we found that TP63 and SOX2 were the hub genes that were highly connected to other genes and displayed significant correlations with several keratin genes. Methylation analysis showed that the P63, P73, and P53 DNA-binding motif sites were significantly enriched for differentially methylated probes. We identified SNAI2, GRHL3, TP63, ZNF750, and FOXE1 as the top transcription factors associated with these binding sites. Finally, we identified 12 miRNAs that influence the keratinization process by using miRNA–mRNA correlation analysis.

Glioblastoma multiforme (GBM) is the most common infiltrating lethal tumor of the brain. Tumor heterogeneity and the precise characterization of GBM remain challenging, and the disease-specific and effective biomarkers are not available at present. To understand GBM heterogeneity and the disease prognosis mechanism, we carried out a single-cell transcriptome data analysis of 3389 cells from four primary IDH-WT (isocitrate dehydrogenase wild type) glioblastoma patients and compared the characteristic features of the tumor and periphery cells. We observed that the marker gene expression profiles of different cell types and the copy number variations (CNVs) are heterogeneous in the GBM samples. Further, we have identified 94 differentially expressed genes (DEGs) between tumor and periphery cells. We constructed a tissue-specific co-expression network and protein–protein interaction network for the DEGs and identified several hub genes, including CX3CR1, GAPDH, FN1, PDGFRA, HTRA1, ANXA2 THBS1, GFAP, PTN, TNC, and VIM. The DEGs were significantly enriched with proliferation and migration pathways related to glioblastoma. Additionally, we were able to identify the differentiation state of microglia and changes in the transcriptome in the presence of glioblastoma that might support tumor growth. This study provides insights into GBM heterogeneity and suggests novel potential disease-specific biomarkers which could help to identify the therapeutic targets in GBM.

GTF (Gene Transfer Format) and GFF (General Feature Format) are popular file formats used by bioinformatics programs to represent and exchange information about various genomic features, such as gene and transcript locations and structure. GffRead and GffCompare are open source programs that provide extensive and efficient solutions to manipulate files in a GTF or GFF format. While GffRead can convert, sort, filter, transform, or cluster genomic features, GffCompare can be used to compare and merge different gene annotations. Availability and implementation: GFF utilities are implemented in C++ for Linux and OS X and released as open source under an MIT license  ( https://github.com/gpertea/gffread , https://github.com/gpertea/gffcompare ).

The ciliate Paramecium bursaria harbors several hundred cells of the green-alga Chlorella sp. in their cytoplasm. Irrespective of the mutual relation between P. bursaria and the symbiotic algae, both cells retain the ability to grow without the partner. They can easily reestablish endosymbiosis when put in contact with each other. Consequently, P. bursaria is an excellent model for studying cell-cell interaction and the evolution of eukaryotic cells through secondary endosymbiosis between different protists. Despite the importance of this organism, no genomic resources have been identified for P. bursaria to date. This investigation compared gene expressions through RNA-Seq analysis and de novo transcriptome assembly of symbiont-free and symbiont-bearing host cells. To expedite the process of gene discovery related to the endosymbiosis, we have undertaken Illumina deep sequencing of mRNAs prepared from symbiont-bearing and symbiont-free P. bursaria cells. We assembled the reads de novo to build the transcriptome. Sequencing using Illumina HiSeq2000 platform yielded 232.3 million paired-end sequence reads. Clean reads filtered from the raw reads were assembled into 68,175 contig sequences. Of these, 10,557 representative sequences were retained after removing Chlorella sequences and lowly expressed sequences. Nearly 90% of these transcript sequences were annotated by similarity search against protein databases. We identified differentially expressed genes in the symbiont-bearing P. bursaria cells relative to the symbiont-free cells, including heat shock 70 kDa protein and glutathione S-transferase. This is the first reported comprehensive sequence resource of Paramecium - Chlorella endosymbiosis. Results provide some keys for the elucidation of secondary endosymbiosis in P. bursaria. We identified P. bursaria genes that are differentially expressed in symbiont-bearing and symbiont-free conditions.

Isoflavones and soyasaponins are major specialized metabolites accumulated in soybean roots and secreted into the rhizosphere. Unlike the biosynthetic pathway, the transporters involved in metabolite secretion remain unknown. The developmental regulation of isoflavone and soyasaponin secretions has been recently reported, but the diurnal regulation of their biosynthesis and secretion still needs to be further studied. To address these challenges, we conducted transcriptome and metabolite analysis using hydroponically grown soybean plants at 6‐hr intervals for 48 hr in a 12‐hr‐light/12‐hr‐dark condition. Isoflavone and soyasaponin biosynthetic genes showed opposite patterns in the root tissues; that is, the former genes are highly expressed in the daytime, while the latter ones are strongly induced at nighttime. GmMYB176 encoding a transcription factor of isoflavone biosynthesis was upregulated from ZT0 (6:00 a.m.) to ZT6 (12:00 a.m.), followed by the induction of isoflavone biosynthetic genes at ZT6. The isoflavone aglycone content in the roots accordingly increased from ZT6 to ZT18 (0:00 a.m.). The isoflavone aglycone content in root exudates was kept consistent throughout the day, whereas that of glucosides increased at ZT6, which reflected the decreased expression of the gene encoding beta‐glucosidase involved in the hydrolysis of apoplast‐localized isoflavone conjugates. Co‐expression analysis revealed that those isoflavone and soyasaponin biosynthetic genes formed separate clusters, which exhibited a correlation to ABC and MATE transporter genes. In summary, the results in this study indicated the diurnal regulation of isoflavone biosynthesis in soybean roots and the putative transporter genes responsible for isoflavone and soyasaponin transport.