Genes & genomics最新文献

Background: In this study, blockage of transition from vegetative to reproductive growth was observed in short-day maize (Zea mays L.) varieties under long-day conditions.

Methods: Two short-day varieties, namely, CML116 and CML493, were cultivated under long-day conditions at various time points of short-day treatments of seedlings. Notably, short-day treatment was started at the three-leaf stage and ended at the five- (5 L), seven- (7 L) and nine-leaf (9 L) stages. Moreover, transcriptomic analysis (RNA-seq) was carried out to examine the gene expression profiles.

Results: The results of gene functional analysis showed that DEGs related to light stimulation and circadian rhythm had different expression patterns among various groups. Additionally, ZmCO, ZmSOC1, ZmFT and ZmHY5 acted as the key regulators of the transition process from vegetative to reproductive growth. Furthermore, the expression of most CO transcripts reached a peak at 5 L in both CML493 and CML116 but decreased in the subsequent short-day treatment.

Conclusions: It is possible that accumulation of CO and FT at the seedling stage facilitated transition from vegetative to reproductive growth. In addition, long-day conditions were not conducive to the accumulation of CO and FT as well as their downstream target, SOC1. Moreover, accumulation of the HY5 protein promoted photomorphogenesis, which played a positive role in promoting the normal development of maize plants.

Background: The NAC family (consisting of NAM, ATAF1/2, and CUC2) represents a crucial plant-specific transcription factor family, contributing significantly to various aspects of plant growth, development, and reactions to abiotic stresses. Yet, the underlying mechanism of NAC regulation in Acer paxii has not been discussed.

Objectives: Identification of NAC genes (ApNACs) in the genome of Acer paxii and exploring the regulatory network of NACs in mediating leaf senescence.

Methods: A thorough genome-wide analysis of the NAC gene family in the Acer paxii genome was performed.

Results: We identified 117 ApNACs from the Acer paxii genome database, which were irregularly distributed across 13 chromosomes. Phylogenetic analysis revealed that ApNAC genes were partitioned into 16 subgroups. There are four kinds of cis-regulatory elements in the promoter region of the ApNACs gene. We compared the expression levels of ApNAC genes at different times using transcriptome data and selected six ApNAC genes for qRT-PCR, which the results showed basic consistency with the transcriptome results. Six ApNACs and 187 TFs from different families were selected, and it was found that the TF families with the highest correlation were WRKY, MYB, bZIP, and ERF, and these TF families were reported to participate in the regulation function in senescence.

Conclusion: This study provides important data support for identifying the NAC gene family of Acer paxii and the regulatory function of the ApNAC genes on plant senescence, which will help to understand the NAC-mediated regulatory network in Acer paxii.

Background: Ulcerative colitis (UC) is a complex, chronic inflammatory disease that primarily impacts the colon mucosa. One of the key pathological contributors to the development and progression of inflammatory bowel disease (IBD) is oxidative stress, which results in reactive oxygen species (ROS)-induced mucosal damage. This stress leads to dysfunction of the intestinal barrier.

Objectives: The purpose of this study is to examine the expression levels of genes involved in various inflammatory pathways, including autophagy, unfolded protein response (UPR), ubiquitination, metabolic pathways, and immune responses in the colon mucosa of patients with UC.

Material and methods: Patients diagnosed with UC at Çukurova University, Balcalı Hospital, Gastroenterology Department between December 2023 and January 2024 were included in this prospective study. A total of 40 participants were included in the study: 27 ulcerative colitis patients and 13 controls. To isolate high-quality RNA, colon biopsy material obtained during colonoscopy was immediately placed in stabilization solution and stored at - 80 degrees Celsius. The relative quantification of target gene mRNA was determined using a Light Cycler. Subsequently, differences in gene expression between patients and the control group were evaluated using the Mann-Whitney U and Kruskal-Wallis tests.

Results: In our study, FOXO4 gene expression increased in UC patients during both active and remission phases compared to the control group. The high expression of this gene is associated with its role in inflammation and cell death processes. Additionally, the high expression of ALDOB and SLC26A genes is linked to increased inflammation and energy demand. Lastly, the elevated expression of the SOD2 gene can be considered a response to oxidative stress-related inflammatory processes in the disease.

Conclusion: These findings propose that these genes could serve as potential biomarkers for genomic identification and understanding the pathogenesis of UC.

Background: Coinfections involving multiple diarrheal viruses have gained increasing recognition as a significant cause of acute gastroenteritis in recent years. Understanding the genetic diversity and evolutionary relationships of these viruses is crucial for effective outbreak identification and tracking.

Objective: To report two cases of HAdV and SaV coinfections and elucidate the genetic diversity and evolutionary patterns of these viruses through whole-genome sequencing (WGS) and phylogenetic analysis.

Methods: A total of 873 diarrheal stool samples were collected from sentinel hospitals in Shenzhen, China, in 2021. The collected stool samples were identified using RT-PCR and positive samples were subjected to WGS on the NovaSeq platform. phylogenetic trees were constructed using MEGA to analyze genetic relationships.

Results: The sequencing results showed that both samples were human adenovirus type 41, which clustered in two distinct evolutionary clades. Additionally, we also retrieved the complete genome of sapovirus (GI.1 genotype) from the same sample. Phylogenetic analysis revealed that they were similar to previously reported strains, belonging to the clade predominating in China.

Conclusions: This study reveals the genetic diversity of epidemic strains involved in coinfections of human adenovirus and sapovirus. The findings establish a groundwork for the identification and traces of acute gastroenteritis outbreaks.

Background: A dominant mutant, green root-dominant (grt-D), which exhibits a green-root phenotype, was identified using the GAL4-UAS activation tagging system in the Q2610 enhancer trap line of Arabidopsis thaliana (Arabidopsis).

Objective: To identify the gene responsible for the grt-D phenotype and investigate whether its ectopic expression induces green petal formation.

Methods: The gene responsible for the grt-D phenotype was identified via thermal asymmetric interlaced-polymerase chain reaction (PCR). The cloned gene and its homolog were expressed under the control of the Q2610 enhancer for root tip expression and the APETALA3 (AP3) or PISTILLATA (PI) promoter for petal-preferential expression.

Results: The 5 × UAS tag in grt-D was located 111 base pairs upstream of the start codon of AtMYB115. Ectopic expression of AtMYB115 or its closest homolog, AtMYB118, under the Q2610 enhancer recapitulated the grt-D green-root phenotype, indicating functional equivalence between the two genes. To examine their effect on petal development, AtMYB115 and AtMYB118 were expressed under the AP3 and PI promoters. The resulting transgenic lines (AP3 >  > AtMYB115, AP3 >  > AtMYB118, PI >  > AtMYB115, and PI >  > AtMYB118) developed short, pale green petals and sterile stamens. The green petals exhibited reduced expression of STAY-GREEN 1, which encodes Mg-dechelatase, a key enzyme involved in chlorophyll degradation, suggesting that the green-petal phenotype results from impaired chlorophyll breakdown.

Conclusion: These findings demonstrate that the ectopic expression of AtMYB115 and AtMYB118 induces green tissue development in non-green organs of Arabidopsis.

Background: RNA-binding proteins (RBPs) are key regulators of cellular transcription and are associated with the occurrence and development of diseases.

Objective: This study aimed to validate the biological characteristics and clinical value of RBPs in testicular cancer, and then construct prediction models for testicular cancer metastasis and treatment outcome.

Methods: RNA sequencing data from 150 testicular tumors and 6 normal tissues were obtained from the cancer genome atlas (TCGA). Additionally, RNA sequencing data from 165 normal testicular tissues were downloaded from the genotype-tissue expression (GTEx) portal. The chemotherapy sensitivity of testicular tumor was evaluated based on the genomics of drug sensitivity in cancer (GDSC) and cancer therapeutics response portal (CTRP) databases. RNA sequencing data was analyzed and predicted for tumor metastasis and treatment outcomes through machine learning models such as artificial neural networks (ANN), random forests (RF), support vector machines (SVM), and logistic regression models (LR).

Results: A RBP risk-score model was developed with the genes: GAPDH, APOBEC3G, KRT18, NOSIP, KCTD12, ENO1, HMGA1, LDHB, ANXA2, ELOVL6, TCF7, BICD1. Those biomarkers were enriched in growth factor activity, hormone receptor binding, and cell killing signaling pathway. Risk-score model can predict the progress free interval (PFI), disease free interval (DFI), and metastasis status of patients with testicular cancer. Patients with high risk-score tumor had an increased tumor infiltrating M2 macrophage, and were more likely to progress after anti-PD-L1 immunotherapy. High risk patients seemed to benifit more from cisplatin-based chemotherapy, but less from bleomycin chemotherapy. Machine learning models basing on RBPs were able to predict tumor metastasis and the effects of chemotherapy and radiotherapy. ANN model achieved the highest accuracy in predicting tumor lymph node metastasis and radiotherapy sensitivity.

Conclusion: RBP signature genes can serve as biomarkers for testicular cancer and play a role in predicting tumor metastasis and therapeutic efficacy.

Background: Mitral valve prolapse (MVP) is a common valvular disorder with a complex genetic basis. While familial MVP-related genes have been identified, the genetic determinants of sporadic MVP remain unclear.

Objective: This study aims to identify causative genes associated with sporadic MVP and analyze genotype-phenotype correlations in a southern Chinese population.

Methods: Whole-exome sequencing (WES) was performed on 80 patients with sporadic MVP. Pathogenic variants were screened using population databases and bioinformatic tools. Gene enrichment and genotype-phenotype correlation analyses were conducted.

Results: A total of 145 variants in 104 MVP-associated genes were identified. Five known MVP genes (COL1A2, FLNA, FLNC, TGFB1, TTN) were found in 14 patients. Three novel MVP-related genes (PRDM5, ZNF469, COL11A1) were identified, predominantly in fibroelastic deficiency cases. These patients had younger onset and higher early diastolic peak velocities.

Conclusions: Sporadic MVP exhibits genetic heterogeneity, with pathogenic mutations linked to early-onset disease and left ventricular dilation. Early genetic screening may improve diagnosis and risk assessment.

Background: Alternative splicing (AS) plays a crucial role in regulating protein function through the generation of structurally distinct isoforms.

Objective: We identify a novel splicing event in Chitinase 3-like 1 (CHI3L1) that modulates its secretion through conformational changes.

Methods: CHI3L1 alternative splicing was analyzed using the GTEx dataset. The regulation of CHI3L1 splicing was examined in response to THP-1 and BEAS-2B cells using RT-PCR. Structural modeling of CHI3L1 isoforms was conducted with AlphaFold to predict conformational changes caused by exon 8 exclusion. Protein expression and secretion levels of CHI3L1 isoforms were analyzed by Western blotting.

Results: Analysis of the GTEx dataset revealed tissue-specific regulation of CHI3L1 exon 8, with pronounced exclusion in lung tissue. The splicing pattern of CHI3L1 was dynamically regulated during THP-1 macrophage differentiation and by cell density in lung-derived epithelial BEAS-2B cells, suggesting its responsiveness to cellular context. While both full-length and exon 8-excluded CHI3L1 proteins showed cytoplasmic localization, structural analysis using AlphaFold revealed that exon 8 exclusion significantly altered the orientation of the signal peptide. Consequently, exon 8-excluded CHI3L1 exhibited minimal secretion into the culture medium compared to the full-length protein.

Conclusion: These findings demonstrate that alternative splicing-mediated exclusion of exon 8 serves as a novel regulatory mechanism controlling CHI3L1 secretion through conformational changes, providing new insights into the post-transcriptional regulation of secreted proteins.

Background: Neonatal sepsis is characterized by an excessive immune response, often leading to multiple organ failure, including cardiac injury, and is a major cause of morbidity and mortality in newborns. Understanding the molecular mechanisms of sepsis-induced cardiac injury is crucial for developing therapeutic strategies.

Objective: To investigate transcriptomic changes and identify potential altered genes associated with cardiac injury in a neonatal sepsis model.

Methods: A neonatal sepsis model was established by cecal slurry injection. RNA sequencing analysis was performed on cardiac tissues from sepsis and control groups, followed by functional enrichment analysis, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Interaction networks among mRNA, lncRNA, circRNA, and miRNA were constructed, and key regulatory genes were identified through protein-protein interaction (PPI) analysis.

Results: A total of 1537 differentially expressed mRNAs, 287 lncRNAs, and 730 circRNAs were identified. Functional analysis revealed significant involvement in immune response and inflammatory regulation. PPI network analysis identified six key genes-Ccl5, Il-6, Pole, Mcm2, Mcm5, Mcm10-that were significantly expressed in sepsis-induced cardiac tissue. Additionally, lncRNAs and circRNAs were found to participate in myocardial injury by regulating immune and inflammatory pathways.

Conclusions: This study identified six key genes involved in immune and inflammatory responses, playing critical roles in sepsis-induced cardiac injury in neonates. These findings provide new insights into the pathogenesis of sepsis-induced cardiac injury and offer potential therapeutic targets.

Bacterial 16S rRNA genes are widely used to classify bacterial communities within interesting environments (e.g., plants, water, human body) because they contain nine hyper-variable regions (V1-V9) reflecting a large number of sequence variation sites between species. Short-read sequencing platform (targeting partial region of 16S rRNA gene; approximately 150-500 bp) commonly used in the 16S-based microbiome study is favored by many researchers because it is economical and can generate highthroughput sequencing data faster than long-read sequencing platforms. However, this sequencing platform has technical limitations in that it cannot clarify bacterial classification at the species level compared to long-read sequencing technology, which can cover the unclassification issue due to sequence similarity between species by targeting the 16S full-length region. In recent microbiome research-related industries, species-level high-resolution microbial classification is considered a key challenge to secure microbial resources among institutions in the field. However, the long-read sequencing platforms currently offered are still under price adjustment (demanding higher cost than short-read sequencing platforms) and have the disadvantage of low base-calling accuracy compared to short-read sequencing platforms. Therefore, this brief communication introduces the'Molecular diagnosis-based bacterial classification' technology to predict candidate species by backtracking for unclassified bacterial taxonomy at the species level in the NGS-based 16S microbiome study.