Identification of the novel HLA-DQA1*02:32 allele by next-generation sequencing.

HLA-DQA1*02:32 differs from DQA1*02:01:01 by one nucleotide substitution in codon 210 in exon 4.

Characterisation of the novel HLA-C*15:274 allele using short and long-read sequencing technologies.

The novel HLA-C*15:274 allele, first described in a potential bone marrow donor from Brazil.

IL-2RG as a possible immunotherapeutic target in CRC predicting poor prognosis and regulated by miR-7-5p and miR-26b-5p.

Despite advances in treatment strategies, colorectal cancer (CRC) continues to cause significant morbidity and mortality, with mounting evidence a close link between immune system dysfunctions issued. Interleukin-2 receptor gamma (IL-2RG) plays a pivotal role as a common subunit receptor in the IL-2 family cytokines and activates the JAK-STAT pathway. This study delves into the role of Interleukin-2 receptor gamma (IL-2RG) within the tumor microenvironment and investigates potential microRNAs (miRNAs) that directly inhibit IL-2RG, aiming to discern their impact on CRC clinical outcomes. Bioinformatics analysis revealed a significant upregulation of IL-2RG mRNA in TCGA-COAD samples and showed strong correlations with the infiltration of various lymphocytes. Single-cell analysis corroborated these findings, highlighting IL-2RG expression in critical immune cell subsets. To explore miRNA involvement in IL-2RG dysregulation, mRNA was isolated from the tumor tissues and lymphocytes of 258 CRC patients and 30 healthy controls, and IL-2RG was cloned into the pcDNA3.1/CT-GFP-TOPO vector. Human embryonic kidney cell lines (HEK-293T) were transfected with this construct. Our research involved a comprehensive analysis of miRPathDB, miRWalk, and Targetscan databases to identify the miRNAs associated with the 3' UTR of human IL-2RG. The human microRNA (miRNA) molecules, hsa-miR-7-5p and hsa-miR-26b-5p, have been identified as potent suppressors of IL-2RG expression in CRC patients. Specifically, the downregulation of hsa-miR-7-5p and hsa-miR-26b-5p has been shown to result in the upregulation of IL-2RG mRNA expression in these patients. Prognostic evaluation of IL-2RG, hsa-miR-7-5p, and hsa-miR-26b-5p, using TCGA-COAD data and patient samples, established that higher IL-2RG expression and lower expression of both miRNAs were associated with poorer outcomes. Additionally, this study identified several long non-coding RNAs (LncRNAs), such as ZFAS1, SOX21-AS1, SNHG11, SNHG16, SNHG1, DLX6-AS1, GAS5, SNHG6, and MALAT1, which may act as competing endogenous RNA molecules for IL2RG by sequestering shared hsa-miR-7-5p and hsa-miR-26b-5p. In summary, this investigation underscores the potential utility of IL-2RG, hsa-miR-7-5p, and hsa-miR-26b-5p as serum and tissue biomarkers for predicting CRC patient prognosis while also offering promise as targets for immunotherapy in CRC management.

18S rDNA sequence-structure phylogeny of the eukaryotes simultaneously inferred from sequences and their individual secondary structures.

OBJECTIVE: The eukaryotic tree of life has been subject of numerous studies ever since the nineteenth century, with more supergroups and their sister relations being decoded in the last years. In this study, we reconstructed the phylogeny of eukaryotes using complete 18S rDNA sequences and their individual secondary structures simultaneously. After the sequence-structure data was encoded, it was automatically aligned and analyzed using sequence-only as well as sequence-structure approaches. We present overall neighbor-joining trees of 211 eukaryotes as well as the respective profile neighbor-joining trees, which helped to resolve the basal branching pattern. A manually chosen subset was further inspected using neighbor-joining, maximum parsimony, and maximum likelihood analyses. Additionally, the 75 and 100 percent consensus structures of the subset were predicted. RESULTS: All sequence-structure approaches show improvements compared to the respective sequence-only approaches: the average bootstrap support per node of the sequence-structure profile neighbor-joining analyses with 90.3, was higher than the average bootstrap support of the sequence-only profile neighbor-joining analysis with 73.9. Also, the subset analyses using sequence-structure data were better supported. Furthermore, more subgroups of the supergroups were recovered as monophyletic and sister group relations were much more comparable to results as obtained by multi-marker analyses.

Characterisation of the novel HLA-C*08:275 allele, first identified in a Brazilian individual.

The novel HLA-C*08:275 allele, first described in a potential bone marrow donor from Brazil.

Discovery of the novel HLA-C*12:02:53 allele in a Taiwanese individual.

Nucleotide substitution in codon 238 of HLA-C*12:02:02:01 results in a novel allele, HLA-C*12:02:53.

Enzyme-assisted high throughput sequencing of an expanded genetic alphabet at single base resolution.

With just four building blocks, low sequence information density, few functional groups, poor control over folding, and difficulties in forming compact folds, natural DNA and RNA have been disappointing platforms from which to evolve receptors, ligands, and catalysts. Accordingly, synthetic biology has created "artificially expanded genetic information systems" (AEGIS) to add nucleotides, functionality, and information density. With the expected improvements seen in AegisBodies and AegisZymes, the task for synthetic biologists shifts to developing for expanded DNA the same analytical tools available to natural DNA. Here we report one of these, an enzyme-assisted sequencing of expanded genetic alphabet (ESEGA) method to sequence six-letter AEGIS DNA. We show how ESEGA analyses this DNA at single base resolution, and applies it to optimized conditions for six-nucleotide PCR, assessing the fidelity of various DNA polymerases, and extending this to AEGIS components with functional groups. This supports the renewed exploitation of expanded DNA alphabets in biotechnology.

Characterisation of the novel HLA-B*35:593 allele using short and long-read sequencing technologies.

The novel HLA-B*35:593 allele, first described in a potential bone marrow donor from Brazil.

The HLA-DRB1*12:92 and HLA-DRB1*12:101 alleles were identified by next-generation sequencing.

Compared with HLA-DRB1*12:02, the alleles HLA-DRB1*12:92 and HLA-DRB1*12:101 each show one nucleotide substitution respectively.

Identification of the novel HLA-DQB1*06:466 allele by next-generation sequencing in a Chinese cord blood donor.

HLA-DQB1*06:466 differs from HLA-DQB1*06:01:01:01 by a single nucleotide substitution at position 571G→A.

A novel HLA-C*03 variant, HLA-C*03:620, identified in a Chinese individual.

HLA-C*03:620 differs from the HLA-C*03:04:01:02 allele by one nucleotide substitution in the exon 3.

The novel HLA-DPB1*05:01:20 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-DPB1*05:01:20 differs from HLA-DPB1*05:01:01:01 by one nucleotide in exon 3.

The novel HLA-B*15:659 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-B*15:659 differs from HLA-B*15:02:01:01 by one nucleotide in exon 2.

Genomic full-length sequence of the HLA-B*37:46 allele was identified by full length group-specific sequencing.

Genomic full-length sequence of HLA-B*37:46 was identified by a group-specific sequencing approach in a Chinese individual.

The novel HLA-B*15:02:15 allele, identified by Sanger dideoxy nucleotide sequencing in a Chinese individual.

HLA-B*15:02:15 differs from HLA-B*15:02:01:01 by one nucleotide in exon 2.

Characterisation of two new HLA-A alleles: HLA-A*01:454 and HLA-A*31:229.

HLA-A*01:454 and HLA-A*31:229, two novel HLA-A alleles detected during routine typing by next-generation sequencing.

DEBFold: Computational Identification of RNA Secondary Structures for Sequences across Structural Families Using Deep Learning.

It is now known that RNAs play more active roles in cellular pathways beyond simply serving as transcription templates. These biological mechanisms might be mediated by higher RNA stereo conformations, triggering the need to understand RNA secondary structures first. However, experimental protocols for solving RNA structures are unavailable for large-scale investigation due to their high costs and time-consuming nature. Various computational tools were thus developed to predict the RNA secondary structures from sequences. Recently, deep networks have been investigated to help predict RNA structures directly from their sequences. However, existing deep-learning-based tools are more or less suffering from model overfitting due to their complicated problem formulation and defective model training processes, limiting their applications across sequences from different structural families. In this research, we designed a two-stage RNA structure prediction strategy called DEBFold (deep ensemble boosting and folding) based on convolution encoding/decoding and self-attention mechanisms to enhance the existing thermodynamic structure models. Moreover, the model training process followed rigorous steps to achieve an acceptable prediction generalization. On the family-wise reserved test sets and the PDB-derived test set, DEBFold achieves better structure prediction performance over traditional tools and existing deep-learning methods. In summary, we obtained a cutting-edge deep-learning-based structure prediction tool with supreme across-family generalization performance. The DEBFold tool can be accessed at https://cobis.bme.ncku.edu.tw/DEBFold/.

The effect of pseudoknot base pairing on cotranscriptional structural switching of the fluoride riboswitch.

A central question in biology is how RNA sequence changes influence dynamic conformational changes during cotranscriptional folding. Here we investigated this question through the study of transcriptional fluoride riboswitches, non-coding RNAs that sense the fluoride anion through the coordinated folding and rearrangement of a pseudoknotted aptamer domain and a downstream intrinsic terminator expression platform. Using a combination of Escherichia coli RNA polymerase in vitro transcription and cellular gene expression assays, we characterized the function of mesophilic and thermophilic fluoride riboswitch variants. We showed that only variants containing the mesophilic pseudoknot function at 37°C. We next systematically varied the pseudoknot sequence and found that a single wobble base pair is critical for function. Characterizing thermophilic variants at 65°C through Thermus aquaticus RNA polymerase in vitro transcription showed the importance of this wobble pair for function even at elevated temperatures. Finally, we performed all-atom molecular dynamics simulations which supported the experimental findings, visualized the RNA structure switching process, and provided insight into the important role of magnesium ions. Together these studies provide deeper insights into the role of riboswitch sequence in influencing folding and function that will be important for understanding of RNA-based gene regulation and for synthetic biology applications.

The 3' UTR of vigR is required for virulence in Staphylococcus aureus and has expanded through STAR sequence repeat insertions.

Infections caused by methicillin-resistant Staphylococcus aureus (MRSA) are alarmingly common, and treatment is confined to last-line antibiotics. Vancomycin is the treatment of choice for MRSA bacteremia, and treatment failure is often associated with vancomycin-intermediate S. aureus isolates. The regulatory 3' UTR of the vigR mRNA contributes to vancomycin tolerance and upregulates the autolysin IsaA. Using MS2-affinity purification coupled with RNA sequencing, we find that the vigR 3' UTR also regulates dapE, a succinyl-diaminopimelate desuccinylase required for lysine and peptidoglycan synthesis, suggesting a broader role in controlling cell wall metabolism and vancomycin tolerance. Deletion of the 3' UTR increased virulence, while the isaA mutant is completely attenuated in a wax moth larvae model. Sequence and structural analyses of vigR indicated that the 3' UTR has expanded through the acquisition of Staphylococcus aureus repeat insertions that contribute sequence for the isaA interaction seed and may functionalize the 3' UTR.

Detecting m6A at single-molecular resolution via direct RNA sequencing and realistic training data.

Direct RNA sequencing offers the possibility to simultaneously identify canonical bases and epi-transcriptomic modifications in each single RNA molecule. Thus far, the development of computational methods has been hampered by the lack of biologically realistic training data that carries modification labels at molecular resolution. Here, we report on the synthesis of such samples and the development of a bespoke algorithm, mAFiA (m6A Finding Algorithm), that accurately detects single m6A nucleotides in both synthetic RNAs and natural mRNA on single read level. Our approach uncovers distinct modification patterns in single molecules that would appear identical at the ensemble level. Compared to existing methods, mAFiA also demonstrates improved accuracy in measuring site-level m6A stoichiometry in biological samples.