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Background: This article concerns the identification of gene pairs or combinations of gene pairs associated with biological phenotype or clinical outcome, allowing for building predictive models that are not only robust to normalization but also easily validated and measured by qPCR techniques. However, given a small number of biological samples yet a large number of genes, this problem suffers from the difficulty of high computational complexity and imposes challenges to the accuracy of identification statistically. Results: In this paper, we propose a parsimonious model representation and develop efficient algorithms for identification. Particularly, we derive an equivalent model subject to a sum-to-zero constraint in penalized linear regression, where the correspondence between nonzero coefficients in these models is established. Most importantly, it reduces the model complexity of the traditional approach from the quadratic order to the linear order in the number of candidate genes, while overcoming the difficulty of model nonidentifiablity. Computationally, we develop an algorithm using the alternating direction method of multipliers (ADMM) to deal with the constraint. Numerically, we demonstrate that the proposed method outperforms the traditional method in terms of the statistical accuracy. Moreover, we demonstrate that our ADMM algorithm is more computationally efficient than a coordinate descent algorithm with a local search. Finally, we illustrate the proposed method on a prostate cancer dataset to identify gene pairs that are associated with pre-operative prostate-specific antigen. Conclusion: Our findings demonstrate the feasibility and utility of using gene pairs as biomarkers. [ABSTRACT FROM AUTHOR]

Background: Metastasis remains the leading cause of mortality in patients diagnosed with colorectal cancer (CRC). The pivotal contribution of the immune microenvironment in the initiation and progression of CRC metastasis has gained significant attention., Methods: A total of 453 CRC patients from The Cancer Genome Atlas (TCGA) were included as the training set, and GSE39582, GSE17536, GSE29621, GSE71187 were included as the validation set. The single-sample gene set enrichment analysis (ssGSEA) was performed to assess the immune infiltration of patients. Least absolute shrinkage and selection operator (LASSO) regression analysis, Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analysis were used to construct and validate risk models based on R package. CTSW and FABP4-knockout CRC cells were constructed via CRISPR-Cas9 system. Western-blot and Transwell assay were utilized to explore the role of fatty acid binding protein 4 (FABP4) / cathepsin W (CTSW) in CRC metastasis and immunity., Results: Based on the normal/tumor, high-/low-immune cell infiltration, and metastatic/non-metastatic group, we identified 161 differentially expressed genes. After random assignment and LASSO regression analysis, a prognostic model containing 3 metastasis- and immune-related gene pairs was constructed and represented good prognostic prediction efficiency in the training set and 4 independent CRC cohorts. According to this model, we clustered patients and found that the high-risk group was associated with stage, T and M stage. In addition, the high-risk group also shown higher immune infiltration and high sensitivity to PARP inhibitors. Further, FABP4 and CTSW derived from the constitutive model were identified to be involved in metastasis and immunity of CRC., Conclusion: In conclusion, a validated prognosis predictive model for CRC was constructed. CTSW and FABP4 are potential targets for CRC treatment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Pan, Yue, Ding, Sun, Xu and Wang.)

Tuberculosis is a chronic infectious disease caused by Mycobacterium tuberculosis (Mtb). Due to the extensive use of anti-tuberculosis drugs and the development of mutations, the emergence and spread of multidrug-resistant tuberculosis is recognized as one of the most dangerous threats to global tuberculosis control. Some single mutations have been identified to be significantly linked with drug resistance. However, the prior research did not take gene-gene interactions into account, and the emergence of transmissible drug resistance is connected with multiple genetic mutations. In this study we use the bioinformatics software GBOOST (The Hong Kong University, Clear Water Bay, Kowloon, Hong Kong, China) to calculate the interactions of Single Nucleotide Polymorphism (SNP) pairs and identify gene pairs associated with drug resistance. A large part of the non-synonymous mutations in the drug target genes that were included in the screened gene pairs were confirmed by previous reports, which lent sound solid credits to the effectiveness of our method. Notably, most of the identified gene pairs containing drug targets also comprise Pro-Pro-Glu (PPE) family proteins, suggesting that PPE family proteins play important roles in the drug resistance of Mtb. Therefore, this study provides deeper insights into the mechanisms underlying anti-tuberculosis drug resistance, and the present method is useful for exploring the drug resistance mechanisms for other microorganisms. [ABSTRACT FROM AUTHOR]

Most of current gene expression signatures for cancer prognosis are based on risk scores, usually calculated as some summaries of expression levels of the signature genes, whose applications require presetting risk score thresholds and data normalization. In this study, we demonstrate the critical limitations of such type of signatures that the risk scores of samples will change greatly when they are normalized together with different samples, which would induce spurious risk classification and difficulty in clinical settings, and the risk scores of independent samples are incomparable if data normalization is not adopted. To overcome these limitations, we propose a rank-based method to extract a prognostic gene pair signature for overall survival of stage I non-small-cell lung cancer. The prognostic gene pair signature is verified in three integrated data sets detected by different laboratories with different microarray platforms. We conclude that, different from the type of signatures based on risk scores summarized from gene expression levels, the rank-based signatures could be robustly applied at the individualized level to independent clinical samples assessed in different laboratories. [ABSTRACT FROM AUTHOR]

The non-coding RNA (ncRNA) regulation appears to be associated to the diagnosis and targeted therapy of complex diseases. Motifs of non-coding RNAs and genes in the competing endogenous RNA (ceRNA) network would probably contribute to the accurate prediction of serous ovarian carcinoma (SOC). We conducted a microarray study profiling the whole transcriptomes of eight human SOCs and eight controls and constructed a ceRNA network including mRNAs, long ncRNAs, and circular RNAs (circRNAs). Novel form of motifs (mRNA-ncRNA-mRNA) were identified from the ceRNA network and defined as non-coding RNA's competing endogenous gene pairs (ceGPs), using a proposed method denoised individualized pair analysis of gene expression (deiPAGE). 18 cricRNA's ceGPs (cceGPs) were identified from multiple cohorts and were fused as an indicator (SOC index) for SOC discrimination, which carried a high predictive capacity in independent cohorts. SOC index was negatively correlated with the CD8+/CD4+ ratio in tumour-infiltration, reflecting the migration and growth of tumour cells in ovarian cancer progression. Moreover, most of the RNAs in SOC index were experimentally validated involved in ovarian cancer development. Our results elucidate the discriminative capability of SOC index and suggest that the novel competing endogenous motifs play important roles in expression regulation and could be potential target for investigating ovarian cancer mechanism or its therapy., (Copyright © 2022. Published by Elsevier Ltd.)

Background: Transcriptional interactome of chromatin is one of the important mechanisms in gene transcription regulation. By chromatin conformation capture and 3D FISH experiments, several chromatin interactions cases among sequence-distant genes or even inter-chromatin genes were reported. However, on genomics level, there is still little evidence to support these mechanisms. Recently based on Hi-C experiment, a genome-wide picture of chromatin interactions in human cells was presented. It provides a useful material for analysing whether the mechanism of transcriptional interactome is common. Results: The main work here is to demonstrate whether the effects of transcriptional interactome on gene co-expression exist on genomic level. While controlling the effects of transcription factors control similarities (TCS), we tested the correlation between Hi-C interaction and the mutual ranks of gene co-expression rates (provided by COXPRESdb) of intra-chromatin gene pairs. We used 6,084 genes with both TF annotation and co-expression information, and matched them into 273,458 pairs with similar Hi-C interaction ranks in different cell types. The results illustrate that co-expression is strongly associated with chromatin interaction. Further analysis using GO annotation reveals potential correlation between gene function similarity, Hi-C interaction and their co-expression. Conclusions: According to the results in this research, the intra-chromatin interactome may have relation to gene function and associate with co-expression. This study provides evidence for illustrating the effect of transcriptional interactome on transcription regulation. [ABSTRACT FROM AUTHOR]

Background: Recently, we identified cysteine-rich withEGF-likedomains 2 (CRELD2) as a novel endoplasmic reticulum (ER) stress-inducible gene and characterized its transcriptional regulation by ATF6 under ER stress conditions. Interestingly, the CRELD2 and asparagine-linkedglycosylation 12 homolog (ALG12) genes are arranged as a bidirectional (head-to-head) gene pair and are separated by less than 400 bp. In this study, we characterized the transcriptional regulation of the mouse CRELD2 and ALG12 genes that is mediated by a common bidirectional promoter. Results: This short intergenic region contains an ER stress response element (ERSE) sequence and is well conserved among the human, rat and mouse genomes. Microarray analysis revealed that CRELD2 and ALG12 mRNAs were induced in Neuro2a cells by treatment with thapsigargin (Tg), an ER stress inducer, in a time-dependent manner. Other ER stress inducers, tunicamycin and brefeldin A, also increased the expression of these two mRNAs in Neuro2a cells. We then tested for the possible involvement of the ERSE motif and other regulatory sites of the intergenic region in the transcriptional regulation of the mouse CRELD2 and ALG12 genes by using variants of the bidirectional reporter construct. With regards to the promoter activities of the CRELD2-ALG12 gene pair, the entire intergenic region hardly responded to Tg, whereas the CRELD2 promoter constructs of the proximal region containing the ERSE motif showed a marked responsiveness to Tg. The same ERSE motif of ALG12 gene in the opposite direction was less responsive to Tg. The direction and the distance of this motif from each transcriptional start site, however, has no impact on the responsiveness of either gene to Tg treatment. Additionally, we found three putative sequences in the intergenic region that antagonize the ERSE-mediated transcriptional activation. Conclusions: These results show that the mouse CRELD2 and ALG12 genes are arranged as a unique bidirectional gene pair and that they may be regulated by the combined interactions between ATF6 and multiple other transcriptional factors. Our studies provide new insights into the complex transcriptional regulation of bidirectional gene pairs under pathophysiological conditions. [ABSTRACT FROM AUTHOR]

Background: Gene expression regulation is still poorly documented in bacteria with highly reduced genomes. Understanding the evolution and mechanisms underlying the regulation of gene transcription in Buchnera aphidicola, the primary endosymbiont of aphids, is expected both to enhance our understanding of this nutritionally based association and to provide an intriguing case-study of the evolution of gene expression regulation in a reduced bacterial genome. Results: A Bayesian predictor was defined to infer the B. aphidicola transcription units, which were further validated using transcriptomic data and RT-PCR experiments. The characteristics of B. aphidicola predicted transcription units (TUs) were analyzed in order to evaluate the impact of operon map organization on the regulation of gene transcription. On average, B. aphidicola TUs contain more genes than those of E. coli. The global layout of B. aphidicola operon map was mainly shaped by the big reduction and the rearrangements events, which occurred at the early stage of the symbiosis. Our analysis suggests that this operon map may evolve further only by small reorganizations around the frontiers of B. aphidicola TUs, through promoter and/or terminator sequence modifications and/or by pseudogenization events. We also found that the need for specific transcription regulation exerts some pressure on gene conservation, but not on gene assembling in the operon map in Buchnera. Our analysis of the TUs spacing pointed out that a selection pressure is maintained on the length of the intergenic regions between divergent adjacent gene pairs. Conclusions: B. aphidicola can seemingly only evolve towards a more polycistronic operon map. This implies that gene transcription regulation is probably subject to weak selection pressure in Buchnera conserving operons composed of genes with unrelated functions. [ABSTRACT FROM AUTHOR]

Abstract: The chromosomal region 10q24 is involved in reciprocal translocations with one of the T-cell receptor loci in a significant proportion of human T-cell acute lymphoblastic leukemias. The breakpoints of these rearrangements cluster immediately upstream of the TLX1 homeobox gene and lead to its transcriptional activation. Genomic analysis using sequences located on the opposite side of the breakpoint cluster region identified a novel gene composed of three exons that is oriented in a head-to-head manner with TLX1. The novel gene, named TDI (TLX1 divergent) codes for a 1.9 kb transcript with an atypically long 5′ leader sequence. Although predicted to be a transcriptional regulator of 13.4 kDa, the TDI protein has no significant sequence similarity to any known protein. The TLX1 and TDI genes are separated by a short spacer of only 161 bp that contains numerous GC boxes and a centrally located CCAAT box embedded within a CpG island. Using luciferase as the reporter in transient transfection assays, the intergenic region was found to be a functional promoter with robust bidirectional activity. TLX1 and TDI thus appear to represent another example of a divergently transcribed gene pair whose expression is regulated by a common promoter. Our finding that TDI is transcriptionally co-activated in leukemic cells that aberrantly express TLX1, additionally suggests that it may have the potential to act as a co-operating oncogene in leukemogenesis. [Copyright &y& Elsevier]

Background: Recent evidence demonstrates that pyroptosis-derived long non-coding RNAs (lncRNAs) have profound impacts on the initiation, progression, and microenvironment of tumors. However, the roles of pyroptosis-derived lncRNAs (PDLs) in gastric cancer (GC) remain elusive. Methods: We comprehensively analyzed the multi-omics data of 839 GC patients from three independent cohorts. The previous gene set enrichment analysis embedding algorithm was utilized to identify PDLs. A gene pair pipeline was developed to facilitate clinical translation via qualitative relative expression orders. The LASSO algorithm was used to construct and validate a pyroptosis-derived lncRNA pair prognostics signature (PLPPS). The associations between PLPPS and multi-omics alteration, immune profile, and pharmacological landscape were further investigated. Results: A total of 350 PDLs and 61,075 PDL pairs in the training set were generated. Cox regression revealed 15 PDL pairs associated with overall survival, which were utilized to construct the PLPPS model via the LASSO algorithm. The high-risk group demonstrated adverse prognosis relative to the low-risk group. Remarkably, genomic analysis suggested that the lower tumor mutation burden and gene mutation frequency (e.g., TTN , MUC16 , and LRP1B ) were found in the high-risk group patients. The copy number variants were not significantly different between the two groups. Additionally, the high-risk group possessed lower immune cell infiltration abundance and might be resistant to a few chemotherapeutic drugs (including cisplatin, paclitaxel, and gemcitabine). Conclusion: PDLs were closely implicated in the biological process and prognosis of GC, and our PLPPS model could serve as a promising tool to advance prognostic management and personalized treatment of GC patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Guo, Liu, Yu, Liu, Ma, Ge, Xing, Lu, Weng, Wang, Liu, Hua, Han and Li.)

South-western screening of λgt11 expression library with a fragment of the Shrunken promoter containing the initiator element resulted in cloning of a novel maize gene. The encoded initiator-binding protein (IBP1) interacts at the transcription start site of the Shrunken promoter. Analysis of the 680 amino acid (aa) long polypeptide revealed a novel bipartite DNA-binding domain at the carboxyl terminus. In its amino-terminal part, it is weakly related to Myb R-repeats but the following basic region is also essential for DNA binding. A region of similarity to the conserved 2.1 and 2.2. motifs in bacterial σ-factors is located close to the IBP1 amino terminus. Two putative nuclear localization signals are compatible with the presence of antigenically related polypeptides in nuclear protein extracts. The IBP1 gene was mapped to the long arm of chromosome 9 (9L095); a second highly related gene IBP2 is located on the short arm of chromosome 1 (1S014). Both genes encode proteins sharing 93% similarity and are transcribed with similar activity in different plant organs. A small 82 nucleotide intron in the IBP2 transcript is found unspliced to a variable degree in different tissues. Translation of this incompletely processed transcript would result in a truncated amino-terminal polypeptide lacking the DNA-binding domain. [ABSTRACT FROM AUTHOR]