Synopsis of proposals on fungal nomenclature: a review of the proposals concerning Chapter F of the International Code of Nomenclature for algae, fungi, and plants submitted to the XII International Mycological Congress, 2024.

A commentary is provided on the seven formally published proposals to modify the provisions of Chapter F of the International Code of Nomenclature for algae, fungi, and plants (ICNafp) that will be dealt with by the Fungal Nomenclature Session (FNS) of the 12th International Mycological Congress (IMC12) in August 2024. The proposals deal with: fungi whose morph-names have the same epithet; the listing of synonyms under entries for protected names in the Code Appendices; the processes of protection and rejection; the use of DNA sequences as nomenclatural types; the use of genomes as nomenclatural types; and the designation of fungi known only from DNA sequences. Information is also provided on the composition and role of the Fungal Nomenclature Bureau, the operation of the FNS and the pre-Congress Guiding vote.

DNA simulation benchmarks revealed with the accumulation of high-resolution structures.

DNA carries more than the list of biochemical instructions that drive the basic functions of living systems. The sequence of base pairs includes a multitude of structural and energetic signals that determine the degree to which the long, threadlike molecule moves and how it responds to proteins and other molecules involved in its processing and packaging. The arrangements of successive base pairs in high-resolution protein-DNA crystal structures provide useful benchmarks for atomic-level simulations of double-helical DNA as well as information potentially useful in interpreting the properties of specific DNA sequences. The set of currently available structures has enough examples to characterize the conformational preferences of the DNA base-pair steps within the context of their immediate neighbors, i.e., in the context of tetramers, and reveals surprising effects of certain neighbors on local chain properties. The proteins in contact with DNA present various microenvironments that sense and/or induce the observed spatial forms. The cumulative buildup of amino-acid atoms in different protein-DNA complexes produces a binding cloud around the double helix with subtle sequence-dependent features. While the microenvironment presented by each protein to DNA is highly unique, the overall composition of amino-acid atoms within close range of DNA in a broad collection of structures is fairly uniform. The buildup of protein atoms of different types around the DNA provides new information for the improvement of nucleic acid force fields and fresh ideas for the exploration of the properties of DNA in solution.

GENet: A Graph-Based Model Leveraging Histone Marks and Transcription Factors for Enhanced Gene Expression Prediction.

Understanding the regulatory mechanisms of gene expression is a crucial objective in genomics. Although the DNA sequence near the transcription start site (TSS) offers valuable insights, recent methods suggest that analyzing only the surrounding DNA may not suffice to accurately predict gene expression levels. We developed GENet (Gene Expression Network from Histone and Transcription Factor Integration), a novel approach that integrates essential regulatory signals from transcription factors and histone modifications into a graph-based model. GENet extends beyond simple DNA sequence analysis by incorporating additional layers of genetic control, which are vital for determining gene expression. Our method markedly enhances the prediction of mRNA levels compared to previous models that depend solely on DNA sequence data. The results underscore the significance of including comprehensive regulatory information in gene expression studies. GENet emerges as a promising tool for researchers, with potential applications extending from fundamental biological research to the development of medical therapies.

The Clinical Significance of CRNDE Gene Methylation, Polymorphisms, and CRNDEP Micropeptide Expression in Ovarian Tumors.

CRNDE is an oncogene expressed as a long non-coding RNA. However, our team previously reported that the CRNDE gene also encodes a micropeptide, CRNDEP. The amino acid sequence of CRNDEP has recently been revealed by other researchers, too. This study aimed to investigate genetic alterations within the CRNDEP-coding region of the CRNDE gene, methylation profiling of this gene, and CRNDEP expression analysis. All investigations were performed on clinical material from patients with ovarian tumors of diverse aggressiveness. We found that CRNDEP levels were significantly elevated in highly aggressive tumors compared to benign neoplasms. Consistently, a high level of this micropeptide was a negative, independent, prognostic, and predictive factor in high-grade ovarian cancer (hgOvCa) patients. The cancer-promoting role of CRNDE(P), shown in our recent study, was also supported by genetic and epigenetic results obtained herein, revealing no CRNDEP-disrupting mutations in any clinical sample. Moreover, in borderline ovarian tumors (BOTS), but not in ovarian cancers, the presence of a single nucleotide polymorphism in CRNDE, rs115515594, significantly increased the risk of recurrence. Consistently, in BOTS only, the same genetic variant was highly overrepresented compared to healthy individuals. We also discovered that hypomethylation of CRNDE is associated with increased aggressiveness of ovarian tumors. Accordingly, hypomethylation of this gene's promoter/first exon correlated with hgOvCa resistance to chemotherapy, but only in specimens with accumulation of the TP53 tumor suppressor protein. Taken together, these results contribute to a better understanding of the role of CRNDE(P) in tumorigenesis and potentially may lead to improvements in screening, diagnosis, and treatment of ovarian neoplasms.

Keep Fingers on the CpG Islands.

The post-genomic era has ushered in the extensive application of epigenetic editing tools, allowing for precise alterations of gene expression. The use of reprogrammable editors that carry transcriptional corepressors has significant potential for long-term epigenetic silencing for the treatment of human diseases. The ideal scenario involves precise targeting of a specific genomic location by a DNA-binding domain, ensuring there are no off-target effects and that the process yields no genetic remnants aside from specific epigenetic modifications (i.e., DNA methylation). A notable example is a recent study on the mouse Pcsk9 gene, crucial for cholesterol regulation and expressed in hepatocytes, which identified synthetic zinc-finger (ZF) proteins as the most effective DNA-binding editors for silencing Pcsk9 efficiently, specifically, and persistently. This discussion focuses on enhancing the specificity of ZF-array DNA binding by optimizing interactions between specific amino acids and DNA bases across three promoters containing CpG islands.

Endogenous fungal endophthalmitis caused by Cladophialophora devriesii: report of a case and literature review.

PURPOSE: To report a case of endogenous endophthalmitis caused by the dematiaceous fungus Cladophialophora devriesii. METHODS: Observational case report and literature review. CASE PRESENTATION: A 73-year-old female with a history of chronic obstructive pulmonary disease presented with a red and painful left eye. Examination revealed anterior segment inflammation and vitritis, indicative of endophthalmitis. She underwent core vitrectomy and intravitreal injection of vancomycin and amphotericin B. The vitreous sample showed inflammatory cells and fungal hyphae, and systemic amphotericin B and itraconazole were commenced for fungal endophthalmitis. Targeted amplification of the sample for bacterial DNA (V2-V3 region of 16 S rDNA) was negative, but fungal DNA targets (ITS1 and ITS2) were present, and their sequences were consistent with Cladophialophora devriesii. Phenotypic characterisation and sequencing of ITS1 and ITS2, carried out on cultured fungus from the sample, also revealed Cladophialophora devriesii. She received repeated intravitreal injections of voriconazole, and based on the antifungal susceptibility results, her systemic medication was changed to posaconazole. After 12 months, the eye showed no signs of inflammation, and posaconazole therapy was discontinued. After 3 months without antifungal medication, the inflammation recurred, and she was restarted on antifungal therapy for an additional 20 months. Another recurrence occurred 3 months after discontinuation of treatment, and a repeat vitreous sample confirmed the presence of Cladophialophora devriesii. She was started on isavuconazole, but developed seclusio pupillae and painful secondary glaucoma. Due to the duration and severity of the infection, the eye was enucleated. Histopathology revealed persistent fungal elements at the ciliary processes and the posterior lens surface. CONCLUSIONS: This second reported case of endogenous endophthalmitis caused by Cladophialophora devriesii illustrates the role of vitreous sampling and molecular methods in diagnosis and treatment of fungal endophthalmitis. Despite early diagnosis and prolonged local and systemic antifungal therapy, it was not possible to achieve long-term control of the fungal infection.

Bi-allelic variants in MYH3 cause recessively-inherited arthrogryposis.

Arthrogryposis is a clinical feature defined by congenital joint contractures in two or more different body areas which occurs in between 1/3000 and 1/5000 live births. Variants in multiple genes have been associated with distal arthrogryposis syndromes. Heterozygous variants in MYH3 have been identified to cause the dominantly-inherited distal arthrogryposis conditions, Freeman-Sheldon syndrome, Sheldon-Hall syndrome, and multiple pterygium syndrome. In contrast, MYH3 variants underlie both dominantly and recessively inherited Contractures, Pterygia, and Spondylocarpotarsal Fusion syndromes (CPSFS) which are characterized by extensive bony abnormalities in addition to congenital contractures. Here we report two affected sibs with distal arthrogryposis born to unaffected, distantly related parents. Sequencing revealed that both sibs were homozygous for two ultra-rare MYH3 variants, c.3445G>A (p.Glu1149Lys) and c.4760T>C (p.Leu1587Pro). Sequencing and deletion/duplication analysis of 169 other arthrogryposis genes yielded no other compelling candidate variants. This is the first report of biallelic variants in MYH3 being implicated in a distal arthrogryposis phenotype without the additional features of CPSFS. Thus, akin to CPSFS, both dominant and recessively inherited distal arthrogryposis can be caused by variants in MYH3.

Updated understanding of the protein-DNA recognition code used by C2H2 zinc finger proteins.

C2H2 zinc-finger (ZF) proteins form the largest family of DNA-binding transcription factors coded by mammalian genomes. In a typical DNA-binding ZF module, there are twelve residues (numbered from -1 to -12) between the last zinc-coordinating cysteine and the first zinc-coordinating histidine. The established C2H2-ZF "recognition code" suggests that residues at positions -1, -4, and -7 recognize the 5', central, and 3' bases of a DNA base-pair triplet, respectively. Structural studies have highlighted that additional residues at positions -5 and -8 also play roles in specific DNA recognition. The presence of bulky and either charged or polar residues at these five positions determines specificity for given DNA bases: guanine is recognized by arginine, lysine, or histidine; adenine by asparagine or glutamine; thymine or 5-methylcytosine by glutamate; and unmodified cytosine by aspartate. This review discusses recent structural characterizations of C2H2-ZFs that add to our understanding of the principles underlying the C2H2-ZF recognition code.

H-ACO with Consecutive Bases Pairing Constraint for Designing DNA Sequences.

DNA computing is a novel computing method that does not rely on traditional computers. The design of DNA sequences is a crucial step in DNA computing, and the quality of the sequence design directly affects the results of DNA computing. In this paper, a new constraint called the consecutive base pairing constraint is proposed to limit specific base pairings in DNA sequence design. Additionally, to improve the efficiency and capability of DNA sequence design, the Hierarchy-ant colony (H-ACO) algorithm is introduced, which combines the features of multiple algorithms and optimizes discrete numerical calculations. Experimental results show that the H-ACO algorithm performs well in DNA sequence design. Finally, this paper compares a series of constraint values and NUPACK simulation data with previous design results, and the DNA sequence set designed in this paper has more advantages.

Classification of DNA Sequence Based on a Non-gradient Algorithm: Pseudoinverse Learners.

This chapter proposes a prototype-based classification approach for analyzing DNA barcodes that uses a spectral representation of DNA sequences and a non-gradient neural network. Biological sequences can be viewed as data components with higher non-fixed dimensions, which correspond to the length of the sequences. Through computational procedures such as one-hot encoding, numerical encoding plays an important role in DNA sequence evaluation (OHE). However, the OHE method has some disadvantages: (1) It does not add any details that could result in an additional predictive variable, and (2) if the variable has many classes, OHE significantly expands the feature space. To address these shortcomings, this chapter proposes a computationally efficient framework for classifying DNA sequences of living organisms in the image domain. A multilayer perceptron trained by a pseudoinverse learning autoencoder (PILAE) algorithm is used in the proposed strategy. The learning control parameters and the number of hidden layers do not have to be specified during the PILAE training process. As a result, the PILAE classifier outperforms other deep neural network (DNN) strategies such as the VGG-16 and Xception models.

DSNetax: a deep learning species annotation method based on a deep-shallow parallel framework.

Microbial community analysis is an important field to study the composition and function of microbial communities. Microbial species annotation is crucial to revealing microorganisms' complex ecological functions in environmental, ecological and host interactions. Currently, widely used methods can suffer from issues such as inaccurate species-level annotations and time and memory constraints, and as sequencing technology advances and sequencing costs decline, microbial species annotation methods with higher quality classification effectiveness become critical. Therefore, we processed 16S rRNA gene sequences into k-mers sets and then used a trained DNABERT model to generate word vectors. We also design a parallel network structure consisting of deep and shallow modules to extract the semantic and detailed features of 16S rRNA gene sequences. Our method can accurately and rapidly classify bacterial sequences at the SILVA database's genus and species level. The database is characterized by long sequence length (1500 base pairs), multiple sequences (428,748 reads) and high similarity. The results show that our method has better performance. The technique is nearly 20% more accurate at the species level than the currently popular naive Bayes-dominated QIIME 2 annotation method, and the top-5 results at the species level differ from BLAST methods by <2%. In summary, our approach combines a multi-module deep learning approach that overcomes the limitations of existing methods, providing an efficient and accurate solution for microbial species labeling and more reliable data support for microbiology research and application.

Enhancer-MDLF: a novel deep learning framework for identifying cell-specific enhancers.

Enhancers, noncoding DNA fragments, play a pivotal role in gene regulation, facilitating gene transcription. Identifying enhancers is crucial for understanding genomic regulatory mechanisms, pinpointing key elements and investigating networks governing gene expression and disease-related mechanisms. Existing enhancer identification methods exhibit limitations, prompting the development of our novel multi-input deep learning framework, termed Enhancer-MDLF. Experimental results illustrate that Enhancer-MDLF outperforms the previous method, Enhancer-IF, across eight distinct human cell lines and exhibits superior performance on generic enhancer datasets and enhancer-promoter datasets, affirming the robustness of Enhancer-MDLF. Additionally, we introduce transfer learning to provide an effective and potential solution to address the prediction challenges posed by enhancer specificity. Furthermore, we utilize model interpretation to identify transcription factor binding site motifs that may be associated with enhancer regions, with important implications for facilitating the study of enhancer regulatory mechanisms. The source code is openly accessible at https://github.com/HaoWuLab-Bioinformatics/Enhancer-MDLF.

The First Iranian Case of Unstable Hemoglobin Santa Ana.

In this report, we describe a 6-year-old girl with a medical history of pallor, mild icterus, anemia, blood transfusion and abnormal hemoglobin variant analysis on capillary electrophoresis. She was referred for further analysis. DNA sequencing of the proband revealed a de novo mutation in Codon 88 (CTG > CCG) of the ß-globin gene (HBB: c.266T > C) in a heterozygous state compatible with hemoglobin Santa Ana, an unstable hemoglobin. This is the first case of Hb Santa Ana from Iran associated with moderate to severe anemia who underwent splenectomy with clinical improvement.

Staphylococcus aureus small colony variants: A potentially underestimated microbiological challenge in peritoneal dialysis.

INTRODUCTION: Peritonitis remains the major infectious complication in the setting of peritoneal dialysis (PD). Despite known only moderate pathogenicity, the most frequently detected pathogens in PD-related peritonitis are surprisingly coagulase-negative staphylococci. However, this could be explained, at least in part, by Staphylococcus aureus small colony variants (SCVs) induced by PD fluids (PDFs) and misidentified by routinely used microbiological methods. MATERIAL AND METHODS: Bacteria were exposed to commonly used PDFs in various regimens designed to simulate daily use as closely as possible. Wild-type isolates and SCVs were subsequently used to determine minimum inhibitory concentrations (MICs), in vitro biofilm formation capacities, and auxotrophies. Underlying genetic alterations were investigated using whole-genome sequencing, and various microbial identification methods were tested to determine their performance for wild-types and SCVs. RESULTS: Stable SCVs could be isolated most successfully after exposure to glucose-containing PDFs alone. The reading of MICs was significantly affected by the reduced growth of SCVs, resulting in lower MIC values in 44% of all tests. Nonsynonymous mutations were found in all but one SCV, while only two isolates showed typical auxotrophic responses. While MALDI-TOF, PCR and Pastorex Staph-Plus correctly identified all S. aureus SCVs, API-Staph and VITEK-2 yielded identification rates of only 40% and 10%, respectively. CONCLUSIONS: Overall, the present study has shown that commercially available PDFs induce S. aureus SCVs in vitro, which are difficult to identify and test for antimicrobial susceptibility and can potentially lead to recurrent or persistent infections. Thus, they represent a potentially underappreciated challenge not only for microbiologists, but also for clinicians.

Genetic diversities in wild and cultivated populations of the two closely-related medical plants species, Tripterygium Wilfordii and T. Hypoglaucum (Celastraceae).

BACKGROUND: The sustainable supply of medicinal plants is important, and cultivating and domesticating them has been suggested as an optimal strategy. However, this can lead to a loss of genetic diversity. Tripterygium wilfordii Hook. f. is a medicinal plant commonly used in traditional Chinese medicine, but its wild populations are dwindling due to excessive harvesting. To protect the species and meet the increasing demand, it is urgent to cultivate it on a large scale. However, distinguishing between T. wilfordii and T. hypoglaucum, two similar species with different medicinal properties, is challenging. Therefore, it is crucial to understand the genetic diversity and population structure of these species for their sustainable utilization. RESULTS: In this study, we investigated the genetic diversity and population structure of the two traditional medicinal semiwoody vines plant species, Tripterygium wilfordii and T. hypoglaucum, including wild and cultivated populations using chloroplast DNA (cpDNA) sequences and microsatellite loci. Our results indicated that the two species maintain a high level of genetic divergence, indicating possible genetic bases for the different contents of bioactive compounds of the two species. T. wilfordii showed lower genetic diversity and less subdivided population structures of both markers than T. hypoglaucum. The potential factors in shaping these interesting differences might be differentiated pollen-to-seed migration rates, interbreeding, and history of population divergence. Analyses of cpDNA and microsatellite loci supported that the two species are genetically distinct entities. In addition, a significant reduction of genetic diversity was observed for cultivated populations of the two species, which mainly resulted from the small initial population size and propagated vegetative practice during their cultivation. CONCLUSION: Our findings indicate significant genetic divergence between T. wilfordii and T. hypoglaucum. The genetic diversity and population structure analyses provide important insights into the sustainable cultivation and utilization of these medicinal plants. Accurate identification and conservation efforts are necessary for both species to ensure the safety and effectiveness of crude drug use. Our study also highlighted the importance of combined analyses of different DNA markers in addressing population genetics of medicinal plants because of the contrasts of inheritance and rates of gene flow. Large-scale cultivation programs should consider preserving genetic diversity to enhance the long-term sustainability of T. wilfordii and T. hypoglaucum. Our study proposed that some populations showed higher genetic diversity and distinctness, which can be considered with priority for conservation and as the sources for future breeding and genetic improvement.

Placental TLR recognition of salivary and subgingival microbiota is associated with pregnancy complications.

BACKGROUND: Pre-term birth, the leading cause of neonatal mortality, has been associated with maternal periodontal disease and the presence of oral pathogens in the placenta. However, the mechanisms that underpin this link are not known. This investigation aimed to identify the origins of placental microbiota and to interrogate the association between parturition complications and immune recognition of placental microbial motifs. Video Abstract METHODS: Saliva, plaque, serum, and placenta were collected during 130 full-term (FT), pre-term (PT), or pre-term complicated by pre-eclampsia (PTPE) deliveries and subjected to whole-genome shotgun sequencing. Real-time quantitative PCR was used to measure toll-like receptors (TLR) 1-10 expression in placental samples. Source tracking was employed to trace the origins of the placental microbiota. RESULTS: We discovered 10,007 functionally annotated genes representing 420 taxa in the placenta that could not be attributed to contamination. Placental microbial composition was the biggest discriminator of pregnancy complications, outweighing hypertension, BMI, smoking, and maternal age. A machine-learning algorithm trained on this microbial dataset predicted PTPE and PT with error rates of 4.05% and 8.6% (taxonomy) and 6.21% and 7.38% (function). Logistic regression revealed 32% higher odds of parturition complication (95% CI 2.8%, 81%) for every IQR increase in the Shannon diversity index after adjusting for maternal smoking status, maternal age, and gravida. We also discovered distinct expression patterns of TLRs that detect RNA- and DNA-containing antigens in the three groups, with significant upregulation of TLR9, and concomitant downregulation of TLR7 in PTPE and PT groups, and dense correlation networks between microbial genes and these TLRs. 70-82% of placental microbiota were traced to serum and thence to the salivary and subgingival microbiomes. The oral and serum microbiomes of PTPE and PT groups displayed significant enrichment of genes encoding iron transport, exosome, adhesion, quorum sensing, lipopolysaccharide, biofilm, and steroid degradation. CONCLUSIONS: Within the limits of cross-sectional analysis, we find evidence to suggest that oral bacteria might translocate to the placenta via serum and trigger immune signaling pathways capable of inducing placental vascular pathology. This might explain, in part, the higher incidence of obstetric syndromes in women with periodontal disease.

Molecular investigation of Anaplasma phagocytophilum and related strains among sheep flocks from different parts of Türkiye; with a note of phylogenetic analyses of Anaplasma phagocytophilum- like 1.

Anaplasma phagocytophilum is a vector-borne zoonotic pathogen and can infect various vertebrate hosts, especially cattle, sheep, goats, horses, and dogs. Molecular-based studies have revealed that the agent has a high genetic diversity and closely related strains circulate in hosts. In this study, 618 sheep blood samples obtained from different geographic regions of Türkiye were researched for A.phagocytophilum and related strains with PCR, RFLP, and DNA sequence analyses. The DNA of these pathogens was detected in 110 (17.79%) samples. RFLP assay showed that all positive samples were infected with A.phagocytophilum-like 1, whereas A.phagocytophilum-like 2 and A.phagocytophilum were not detected. Partial parts of 16 S rRNA gene of seven randomly selected positive samples were sequenced. The phylogenetic analyses of these isolates revealed that at least two A.phagocytophilum-like 1 isolates circulate among hosts in Türkiye and around the world. A.phagocytophilum-related strains have been reported in molecular-based studies over the last few years, but there is a lack of data on the vector competence, epidemiology, clinical symptoms, and genetic diversity of these pathogens. Therefore, large-scale molecular studies are still needed to obtain detailed data on the above-mentioned topics.

Hidden diversity of Pestalotiopsis and Neopestalotiopsis (Amphisphaeriales, Sporocadaceae) species allied with the stromata of entomopathogenic fungi in Taiwan.

Pestalotiopsissensu lato, commonly referred to as pestalotiopsis-like fungi, exhibit a broad distribution and are frequently found as endophytes, saprobes and pathogens across various plant hosts. The taxa within pestalotiopsis-like fungi are classified into three genera viz. Pestalotiopsis, Pseudopestalotiopsis and Neopestalotiopsis, based on the conidial colour of their median cells and multi-locus molecular phylogenies. In the course of a biodiversity investigation focusing on pestalotiopsis-like fungi, a total of 12 fungal strains were identified. These strains were found to be associated with stromata of Beauveria, Ophiocordyceps and Tolypocladium in various regions of Taiwan from 2018 to 2021. These strains were evaluated morphologically and multi-locus phylogenetic analyses of the ITS (internal transcribed spacer), tef1-α (translation elongation factor 1-α) and tub2 (beta-tubulin) gene regions were conducted for genotyping. The results revealed seven well-classified taxa and one tentative clade in Pestalotiopsis and Neopestalotiopsis. One novel species, Pestalotiopsismanyueyuanani and four new records, N.camelliae-oleiferae, N.haikouensis, P.chamaeropis and P.hispanica, were reported for the first time in Taiwan. In addition, P.formosana and an unclassified strain of Neopestalotiopsis were identified, based on similarities of phylogeny and morphology. However, the data obtained in the present study suggest that the currently recommended loci for species delimitation of pestalotiopsis-like fungi do not deliver reliable or adequate resolution of tree topologies. The in-vitro mycelial growth rates of selected strains from these taxa had an optimum temperature of 25 °C, but growth ceased at 5 °C and 35 °C, while all the strains grew faster under alkaline than acidic or neutral pH conditions. This study provides the first assessment of pestalotiopsis-like fungi, associated with entomopathogenic taxa.

The adult, pupa, and larva of a new species of Gnaptorina Reitter, 1887 (Coleoptera, Tenebrionidae, Blaptini) from the Tibetan Plateau, with molecular phylogenetic inferences.

The adult, pupa and larva of a new species, Gnaptorina (Gnaptorina) lhorongica Li, sp. nov., from northeastern Xizang, China are described and illustrated. The species was identified using molecular phylogenetic analyses based on three mitochondrial fragments and one nuclear gene fragment (COI, Cytb, 16S, and 28S-D2). The taxonomic status of the new species is confirmed using a combination of molecular and morphological datasets. This study provides valuable molecular and morphological data for phylogenetic studies of the tribe Blaptini.

Deqformer: high-definition and scalable deep learning probe design method.

Target enrichment sequencing techniques are gaining widespread use in the field of genomics, prized for their economic efficiency and swift processing times. However, their success depends on the performance of probes and the evenness of sequencing depth among each probe. To accurately predict probe coverage depth, a model called Deqformer is proposed in this study. Deqformer utilizes the oligonucleotides sequence of each probe, drawing inspiration from Watson-Crick base pairing and incorporating two BERT encoders to capture the underlying information from the forward and reverse probe strands, respectively. The encoded data are combined with a feed-forward network to make precise predictions of sequencing depth. The performance of Deqformer is evaluated on four different datasets: SNP panel with 38 200 probes, lncRNA panel with 2000 probes, synthetic panel with 5899 probes and HD-Marker panel for Yesso scallop with 11 000 probes. The SNP and synthetic panels achieve impressive factor 3 of accuracy (F3acc) of 96.24% and 99.66% in 5-fold cross-validation. F3acc rates of over 87.33% and 72.56% are obtained when training on the SNP panel and evaluating performance on the lncRNA and HD-Marker datasets, respectively. Our analysis reveals that Deqformer effectively captures hybridization patterns, making it robust for accurate predictions in various scenarios. Deqformer leads to a novel perspective for probe design pipeline, aiming to enhance efficiency and effectiveness in probe design tasks.