Sequence Similarity Research Articles

Coat-protein Gene Based Identification and Characterization of Yellow Mosaic Virus Infecting Blackgram in Northern Karnataka, India

Aims: Coat-protein (CP) based identification and characterization of yellow mosaic virus infecting blackgram. Place and Duration of Study: The study was carried out during Kharif 2023 at College of Agriculture, Vijayapur. Methodology: The whole genomic DNA was isolated from the leaf tissues of both healthy blackgram plants and plants infected with the yellow mosaic virus by using a modified CTAB method. Specific primers for YMV were tried to amplify coat protein region of blackgram YMV. Results: Sequence analysis revealed that the CP gene of the begomovirus under study shared 99.8 per cent similarity with MYMV Shivamogga isolate (OM106035.1) at the nucleotide level. When comparing the deduced amino acid sequences of individual proteins from YMV infecting blackgram at Vijayapur with those of other begomoviruses, the highest identity was found with the MYMV Shivamogga isolate (OM106035.1), showing 84.59 per cent similarity. A phylogenetic tree constructed based on the full-length coat protein gene sequence of MYMV, along with 37 other Geminivirus sequences, formed two major clusters in which MYMV-Vijayapur isolate appeared in Cluster I. Conclusion: The results of the current study, based on similarities in coat protein sequence at both the nucleotide and amino acid levels, as well as phylogenetic analysis, confirmed the prevalence of MYMV strain rather than MYMIV, HgYMV and DoYMV in blackgram in northern parts of Karnataka.

Proposal of Lactococcus intestinalis Sun et al. 2024 as a Later Heterotypic Synonym of Lactococcus muris Afrizal et al. 2023.

Lactococcus muris was published in Cell Host & Microbe in November 2022 and validated in validation list no. 213 in October 2023. Lactococcus intestinalis was published in Antonie van Leeuwenhoek in May 2023 and validated in validation list no. 216 in March 2024. Both of them were isolated from the mouse gut. Previous studies indicated that L. muris DSM 109779T had the highest 16S rRNA gene sequence identity to Lactococcus garvieae (96.7%), and that L. intestinalis M2458T had the highest 16S rRNA gene sequence similarities to Lactococcus formosensis NBRC 109475T (97.6%) and L. garviae NBRC 100934T (97.1%). However, the taxonomic relationship between L. muris and L. intestinalis has not yet been investigated and therefore is the focus of the present study. In the present study, the relationship between L. muris and L. intestinalis was evaluated. The type strains of L. muris and L. intestinalis shared 100% 16S rRNA gene sequence similarity, 100% pheS sequence similarity, 100% rpoA sequence similarity, 99.9% average nucleotide identity (ANI) value and 98.5% digital DNA-DNA hybridization (dDDH) value, indicating that they represented the same species. On the basis of the results present here, we propose L. intestinalis Sun et al. 2024 as a later heterotypic synonym of L. muris Afrizal et al. 2023.

Thalassotalea aquiviva sp. nov., and Thalassotalea maritima sp. nov., Isolated from Seawater of the Coast in South Korea.

Two novel bacterial strains, 273M-4T and Sam97T, were isolated from seawater in the Yellow Sea, Muan-gun, South Korea, and identified as members of the genus Thalassotalea. Both strains were Gram-stain-negative, aerobic, rod-shaped, non-motile, non-flagellated, and oxidase- and catalase-positive. Phylogenetic analysis based on 16S rRNA gene sequences showed that strains 273M-4T and Sam97T were most closely related to Thalassotalea ponticola KCTC 42155T, with sequence similarities of 97.5% and 98.3%, respectively. Optimal growth for strain 273M-4T occurred at 25-30°C, pH 7.0, and 2% NaCl, while strain Sam97T grew optimally at 30°C, pH 8.0, and 2% NaCl. Genome sizes of strains 273M-4T and Sam97T were 3.37 and 3.31Mb, with DNA G + C contents of 41.0mol% and 42.9mol%, respectively. The orthologous average nucleotide identity (OrthoANI) and digital DNA-DNA hybridization (dDDH) values between the two strains were 71.6% and 24.4%, respectively, indicating that they are distinct species. Further genomic analyses of these two strains revealed OrthoANI values of < 73.5% and dDDH values of < 26.7% within the genus Thalassotalea, suggesting their distinctiveness from other Thalassotalea species. The predominate fatty acids of strains 273M-4T and Sam97T were summed feature 3 (consisting of C16:1 ω7c/C16:1 ω6c) and C16:0. All strains contained phosphatidylethanolamine and phosphatidylglycerol as the major polar lipids and ubiquinone-8 (Q-8) as the primary respiratory quinone. Based on phenotypic, phylogenetic, genotypic, and chemotaxonomic data, strains 273M-4T (= KCTC 8644T = LMG 33695T) and Sam97T (= KCTC 8645T = LMG 33694T) represent novel species of the genus Thalassotalea, named Thalassotalea aquiviva sp. nov. and Thalassotalea maritima sp. nov..

Unveiling three novel actinobacterial species (Streptomyces cavernicola sp. nov., Streptomyces solicavernae sp. nov. and Streptomyces luteolus sp. nov.) in soil samples in Phu Pha Phet Cave, Thailand.

Three strains of actinobacteria, designated as B-S-A6T, B-S-A8T and B-S-A12T, were isolated from soil samples collected in the Phu Pha Phet Cave located in the Satun UNESCO Global Geopark, Satun Province, Thailand. A comprehensive polyphasic approach was used to describe these strains. Strains B-S-A6T, B-S-A8T and B-S-A12T were identified within the genus Streptomyces based on a comparative examination of 16S rRNA gene sequences. Strains B-S-A8T and B-S-A12T showed a high genetic similarity to Streptomyces spectabilis NBRC 13424T (99.0%, for both) and to Streptomyces deserti C63T (98.6 and 98.7 %, respectively). Meanwhile, strain B-S-A6T exhibited 98.6% sequence similarity with S. spectabilis NBRC 13424T and Streptomyces koyangensis VK-A6 T. However, upon further comparison, the 16S rRNA gene sequence of strain B-S-A6T showed a similarity of 99.6% to B-S-A8T and 99.7% to B-S-A12T. Contrastingly, B-S-A8T showed a very high similarity of 99.8% with B-S-A12T. The use of digital DNA-DNA hybridization, along with the analysis of average nt identities and aa identities, comparing the three strains to their closest known type strains, validated that each of these strains represents a new and distinct species. Three newly identified strains exhibited phenotypic characteristics and chemotaxonomic properties consistent with the members of the genus Streptomyces. The primary menaquinones identified in these strains were MK-9(H6) and MK-9(H8). The major fatty acids were iso-C15 : 0 and anteiso-C15 : 0. Their polar lipid profiles included diphosphatidylglycerol, phosphatidylethanolamine, hydroxy-phosphatidylethanolamine, phosphatidylinositol and phosphatidylinositol mannoside. The comprehensive phenotypic and genomic analyses of the Streptomyces strains strongly suggest that strains B-S-A6T, B-S-A8T and B-S-A12T represent three new species for which the names Streptomyces cavernicola sp. nov. (type strain B-S-A6T =TBRC 17074T =NBRC 116118T), Streptomyces solicavernae sp. nov. (type strain B-S-A8T =TBRC 17072T =NBRC 116117T) and Streptomyces luteolus sp. nov. (type strain B-S-A12T =TBRC 17060T =NBRC 116116T) are proposed.

Genome Sequencing and Metabolic Potential Analysis of Irpex lacteus

Irpex lacteus is an edible and medicinal macrofungus with significant biological activity and broad pharmaceutical prospects that has received increasing attention in recent years. Although it is an important resource for macrofungi, knowledge of it remains limited. In this study, we sequenced, de novo assembled, and annotated the whole genome of I. lacteus using a PacBio Sequel II sequencer. The assembled 41.83 Mb genome contains 13,135 predicted protein-coding genes, 83.44% of which have searchable sequence similarity to other genes available in public databases. Using genome-based bioinformatics analysis, we identified 556 enzymes involved in carbohydrate metabolism and 103 cytochrome P450 proteins. Genome annotation revealed genes for key enzymes responsible for the biosynthesis of secondary metabolites, such as terpenoids and polyketides. Among them, we identified 14 terpene synthases, 8 NRPS-like enzymes, and 4 polyketide synthases (PKS), as well as 2 clusters of biosynthetic genes presumably related to terpene synthesis in I. lacteus. Gene family analysis revealed that the MYB transcription factor gene family plays an important role in the growth and development of I. lacteus. This study further enriches the genomic content of I. lacteus, provides genomic information for further research on the molecular mechanism of I. lacteus, and promotes the development of I. lacteus in the fields of drug research and functional food production.

Privacy-Preserving Sequential Recommendation with Collaborative Confusion

Sequential recommendation has attracted a lot of attention from both academia and industry, however the privacy risks associated with gathering and transferring users’ personal interaction data are often underestimated or ignored. Existing privacy-preserving studies are mainly applied to traditional collaborative filtering or matrix factorization rather than sequential recommendation. Moreover, these studies are mostly based on differential privacy or federated learning, which often lead to significant performance degradation, or have high requirements for communication. In this work, we address privacy-preserving from a different perspective. Unlike existing research, we capture collaborative signals of neighbor interaction sequences and directly inject indistinguishable items into the target sequence before the recommendation process begins, thereby increasing the perplexity of the target sequence. Even if the target interaction sequence is obtained by attackers, it is difficult to discern which ones are the actual user interaction records. To achieve this goal, we introduce a novel sequential recommender system called CLOUD ( C o L laborative-c O nfusion seq U ential recommen D er), which incorporates a collaborative confusion mechanism to modify the raw interaction sequences before conducting recommendation. Specifically, CLOUD first calculates the similarity between the target interaction sequence and other neighbor sequences to find similar sequences. Then, CLOUD considers the shared representation of the target sequence and similar sequences to determine the operation to be performed: keep, delete, or insert. A copy mechanism is designed to make items from similar sequences have a higher probability to be inserted into the target sequence. Finally, the modified sequence is used to train the recommender and predict the next item. We conduct extensive experiments on three benchmark datasets. The experimental results show that CLOUD achieves a maximum modification rate of 66.57% on interaction sequences, and obtains over 99% recommendation accuracy compared to the state-of-the-art sequential recommendation methods. This proves that CLOUD can effectively protect user privacy at minimal recommendation performance cost, which provides a new solution for privacy-preserving for sequential recommendation. Our implementation is available at https://github.com/weiwang0927/CLOUD .

Genome-wide identification, gene cloning, subcellular location and expression analysis of the OPR gene family under salt stress in sweetpotato

BackgroundThe 12-oxo-phytodienoic acid reductase (OPR) enzyme is crucial for the synthesis of jasmonates (JAs), and is involved in the plant stress response. However, the OPR gene family in sweetpotato, an important horticultural crop, remains unidentified.ResultsIn this study, we employed bioinformatics techniques to identify nine IbOPR genes. Phylogenetic analysis revealed that these genes could be divided into Group I and Group II. Synteny analysis indicated that IbOPR evolution was driven by tandem duplication, whole-genome duplication (WGD), and segmental duplication events. The promoter sequences of IbOPRs were found to be associated with stress and hormonal responses. Additionally, we successfully cloned four IbOPRs from "Haida HD7791" and "Haida HD7798" using homologous cloning technology. These sequences were 1203 bp, 1200 bp, 1134 bp, and 1137 bp in length and encoded 400, 399, 377, and 378 amino acids, respectively. The protein sequence similarity between the salt-tolerant variety "Haida HD7791" and the salt-sensitive variety "Haida HD7798" was determined to be 96.75% for IbOPR2, 99.75% for IbOPR3, 92.06% for IbOPR6, and 98.68% for IbOPR7. Phylogenetic analysis categorized IbOPR2 and IbOPR3 proteins into Group II, while IbOPR6 and IbOPR7 proteins belonged to Group I. Subcellular localization experiments showed IbOPR2 protein present in the peroxisome, while IbOPR3, IbOPR6, and IbOPR7 proteins were found in the cytoplasm and nucleus. Salt stress induction experiments demonstrated that IbOPR2, IbOPR3, and IbOPR7 were significantly upregulated only in 'Haida HD7791' after 6 h. In contrast, IbOPR6 was induced in 'Haida HD7798' at 6 h but inhibited in 'Haida HD7791' at later time points (12, 24, 48, and 72 h), highlighting functional differences in salt stress responses.ConclusionsOur findings suggest that IbOPR2 may play a crucial role in sweetpotato's response to salt stress by participating in JAs synthesis. These results provide a foundation for future functional analyses of OPR genes in sweetpotato.

Evolution of sequence, structural and functional diversity of the ubiquitous DNA/RNA-binding Alba domain

The DNA/RNA-binding Alba domain is prevalent across all kingdoms of life. First discovered in archaea, this protein domain has evolved from RNA- to DNA-binding, with a concomitant expansion in the range of cellular processes that it regulates. Despite its widespread presence, the full extent of its sequence, structural, and functional diversity remains unexplored. In this study, we employed iterative searches in PSI-BLAST to identify 15,161 unique Alba domain-containing proteins from the NCBI non-redundant protein database. Sequence similarity network (SSN) analysis clustered them into 13 distinct subgroups, including the archaeal Alba and eukaryotic Rpp20/Pop7 and Rpp25/Pop6 groups, as well as novel fungal and Plasmodium-specific Albas. Sequence and structural conservation analysis of the subgroups indicated high preservation of the dimer interface, with Alba domains from unicellular eukaryotes notably exhibiting structural deviations towards their C-terminal end. Finally, phylogenetic analysis, while supporting SSN clustering, revealed the evolutionary branchpoint at which the eukaryotic Rpp20- and Rpp25-like clades emerged from archaeal Albas, and the subsequent taxonomic lineage-based divergence within each clade. Taken together, this comprehensive analysis enhances our understanding of the evolutionary history of Alba domain-containing proteins across diverse organisms.

Rational engineering of a highly active and resilient α-carbonic anhydrase from the hydrothermal vent speciesPersephonella hydrogeniphila.

Carbonic anhydrases (CAs) are ideal catalysts for carbon dioxide sequestration in efforts to alleviate climate change. Here, we report the characterisation of three α-CAs that originate from the thermophilic bacteria Persephonella hydrogeniphila (PhyCA), Persephonella atlantica (PaCA), and Persephonella sp. KM09-Lau-8 (PlauCA) isolated from hydrothermal vents. The three α-Cas, showing high sequence similarities, were produced in Escherichia coli, purified and characterised. Surprisingly, they revealed very different behaviours with regards to their thermostability profiles. PhyCA presented a more stable thermostability profile amongst the three, thus we chose it for rational engineering to improve it further. PhyCA's residue K88, a proton transfer residue in α-CAs, was mutated to His, Ala, Gln and Tyr. A 4-fold activity improvement was noted for variants K88H and K88Q at 30 °C, owing to the higher proton transfer efficiency of the replacement proton transfer residues. K88Q also proved more stable than PhyCA. K88Y did not increase activity, but notably increased thermal stability, with this enzyme variant retaining 50% of its initial activity after incubation for 1 h at 90 °C. Removal of the two main proton shuttles (variant H85A_K88A) resulted in diminished activity of the enzyme. Molecular dynamics simulations performed for PhyCA and all its variants revealed differences in residue fluctuations, with K88A resulting in a general reduction in root mean square fluctuation (RMSF) of active site residues as well as most of the CA's residues. Its specific activity and stability in turn increased compared to the wild type.

Dominance of recombinant DWV genomes with changing viral landscapes as revealed in national US honey bee and varroa mite survey

Honey bees are essential pollinators for global agriculture. The viromes of US commercial apiaries and their ectoparasitic mites are poorly characterized at a strain level and there is a need to integrate genomics into pathogen surveillance. We sequenced RNA viromes from 383 adult bees and 173 mites pooled samples from 11 major US beekeeping hubs in 2021, assembling 45 complete and 1702 partial genomes. Protein sequence similarity networks and recombinant genome identification revealed a new viral landscape. Sinaivirus (n = 312), Iflavirus sacbroodi (n = 280), and Iflavirus aladeformis (DWV, n = 135) genomes were common. Recombinant DWV genomes with high nucleotide identity were widespread, and DWV type A master variants were rare, with an indication that RT-PCR surveillance may over-detect type A due to the prevalence of recombinant DWV genomes. Future work should use genomic strategies to avoid misidentification of common honey bee virus genomes and their impact on colony health.

ThyD Is a Thylakoid Membrane Protein Influencing Cell Division and Acclimation to High Light in the Multicellular Cyanobacterium Anabaena sp. Strain PCC 7120.

Cyanobacteria developed oxygenic photosynthesis and represent the phylogenetic ancestors of chloroplasts. The model strain Anabaena sp. strain PCC 7120 grows as filaments of communicating cells and can form heterocysts, cells specialized for N2 fixation. In the Anabaena genome, ORF all2390 is annotated as encoding a SulA homolog, but sequence similarity to SulA of model bacteria is insignificant. We generated strains that lacked or overexpressed all2390, both of which showed instances of increased cell size, and observed that purified All2390 protein interfered with the invitro polymerization of FtsZ. Heterocyst frequency diminished by all2390 inactivation and increased by all2390 overexpression. Overexpression retarded the dismantlement of Z-ring structures that determines commitment in the differentiating cells. Thus, All2390 can influence cell division affecting heterocyst differentiation. An All2390-GFP fusion protein localized to the thylakoid membranes including the honeycomb membranes, which harbor photosynthetic complexes, in the heterocyst polar regions. Notably, all2390 expression strongly increased under high light, conditions under which growth of the null mutant is compromised. Thus, All2390 appears essential for adaptation to high light conditions. We named All2390 ThyD to reflect its thylakoidal localization and its dual role in cell division dynamics and acclimation of thylakoid membranes to increased light intensity.

Arenicolidae (Annelida) in Norwegian waters: Species occurrence, bathymetric distribution and identification of juvenile specimens

The two species of Arenicolidae, Arenicola marina and Arenicolides ecaudata, are common along the Norwegian coast. Juveniles and anterior fragments are often encountered when grab sampling, making traditional morphological characteristics insufficient for species identification. This study examined the robustness of the characteristics and development of branchiae in juvenile specimens of Arenicolides ecaudata (n = 109) and Arenicola (n = 44) (A. marina and Arenicola sp.) and additional specimens to assess geographic and bathymetric distribution. Neuropodia were discovered to be efficient in distinguishing the species. Branchiae of A. ecaudata appear when specimens measure between 7–13 mm, while in A. marina they appear in specimens measuring between 3–5 mm. The ring formula in anterior chaetigers is a key characteristic in differentiating between Arenicola species. This characteristic alone is insufficient for reliable species identifications, as study findings corroborated error rates in identification based on the ring formula. The bathymetric range of both species has increased considerably. Arenicola marina was documented at 194 m depth and A. ecaudata at 387 m depth. DNA barcodes with the cytochrome c oxidase subunit I (COI) gene were produced for three specimens of Arenicolides ecaudata, representing the first publicly available COI barcode sequences for this species. Five specimens of Arenicola marina, with similar sequences to specimens from other north-eastern Atlantic localities were also barcoded in BOLDsystems.

Molecular Identification of Mosquitoes (Diptera: Culicidae) Using COI Barcode and D2 Expansion of 28S Gene

The purpose of this study is to improve the identification of Culicidae species from the Vale Ribeira region, São Paulo state, Brazil. Adults were collected in the municipalities of Cananeia and Pariquera-Açu and morphologically identified. Molecular analyses were performed on sequences of COI barcode and a fragment of the D2 expansion of the 28S ribosomal RNA gene generated from field collected mosquitoes. The analyses included species delimitation, phylogeny, and interspecific genetic distances using the Kimura 2-parameter model. Species included in the analyses were Aedes perventor, Aedes scapularis, Aedes serratus/Aedes nubilus, Aedes serratus s.s., Aedes terrens, Haemagogus capricornii, Haemagogus leucocelaenus, Haemagogus janthinomys, Kerteszia bellatrix, Kerteszia cruzii, Psorophora ferox, Psorophora forceps, Sabethes conditus, and Wyeomyia confusa. COI sequences from specimens collected at other localities were included in the analysis for comparison. Results of barcode RESL analysis showed that specimens of Ps. ferox and Hg. janthinomys split into three clusters for each species. Similarly, sequences of Ke. bellatrix and Ke. cruzii were recovered in two groups for each species. Distinct from other species included in analyses, Ps. ferox and Ps. forceps shared 100% similarity in the D2 fragment sequenced. Overall, the analysis of COI barcode sequences revealed the following key findings: (1) the presence of subclades within Hg. janthinomys, with its division into three groups suggests that this species may represent a species complex; (2) Ke. bellatrix from the Atlantic tropical rainforest shares 95.59% sequence similarity with a specimen from the type locality, indicating that specimens from Southeastern Brazil may belong to an unidentified species within the Ke. bellatrix complex; (3) Ke. cruzii also represents a species complex; and (4) D2 sequences successfully identified most species studied, apart from Ps. forceps and Ps. ferox.

Unveiling DNA Sequences: A Comparison of Machine Learning and Deep Learning Techniques for Prediction

&lt;div align="center"&gt;&lt;table width="590" border="1" cellspacing="0" cellpadding="0"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td valign="top" width="387"&gt;&lt;p&gt;DNA is the biological macromolecule unit that carries the information of all protein, amino acid sequences. With the help of this protein sequence, we explore the mutated gene and disease-causing mutated genomic pattern. Currently, the progression of genomic innovation is the source of DNA arrangement information developing at a dangerous rate—external factors have stimulated the volume of research into DNA genomes. Initially, the development process of DNA sequencing is accomplished with the support of the Database, data structures, and sequence similarity. The method is capable of extracting a particular property in DNA. We employ the deep learning algorithm to pull out protein sequences' features. The DNA sequence is classified based on the in-build protein structures extracted into the Fasta file. Therefore, the DNA sequence of E.coli with 106 data sets and 57 nucleotides is tested experimentally. Finally, we compared the results with the existing decision tree algorithm, KNN- Classification, random forest, and neural networks. The deep learning algorithm yields higher efficiency of 98% compared to other machine learning algorithms. This highlights the potential of deep learning in genomics research and its ability to yield superior results in classifying DNA sequences.&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;/div&gt;

Bifidobacterium apicola sp. nov., isolated from the gut of honeybee (Apis mellifera).

Two novel bifidobacteria (designated F806-1T and F814-1.1) isolated from the gut of honeybee (Apis mellifera) were characterized in the present study. 16S rRNA gene sequence analysis indicated that strains F806-1T and F814-1.1 belonged to the Bifidobacterium asteroides group and were most closely related to Bifidobacterium apousia W8102T and Bifidobacterium polysaccharolyticum W8117T, having 98.9-99.4% 16S rRNA gene sequence similarities. Strains F806-1T and F814-1.1 had the highest 16S rRNA gene sequence similarities (99.1 and 99.4 %) with B. polysaccharolyticum W8117T. Strains F806-1T and F814-1.1 had 73.2-90.5% average nucleotide identity, 21.5-40.8% digital DNA-DNA hybridization and 67.4-92.5% average amino acid identity values with type strains of all species in the B. asteroides group. Acid production from d-arabinose, l-arabinose, d-xylose, l-xylose, d-galactose, d-fructose, d-mannose and methyl-α-d-glucopyranoside; tolerance to 3% NaCl and activity of cystine arylamidase, N-acetyl-β-glucosaminidase, α-mannosidase and α-fucosidase could differentiate strains F806-1T and F814-1.1 from the type strain of B. polysaccharolyticum. Based on the data obtained in the present study, a novel species, Bifidobacterium apicola sp. nov., is proposed, and the type strain is F806-1T (=CCTCC AB 2024129T=JCM 37002T).

A new isolate of mungbean yellow mosaic India virus in Vigna mungo L. reported from a Dayalbagh field, Agra.

Black gram (Vigna mungo L.) plants showing yellow mosaic symptoms during 2019-2022 crop seasons were collected randomly from a Dayalbagh field, Agra Region of Uttar Pradesh, India. Total genomic DNA was isolated from the infected leaf samples by the Cetyltrimethylammonium bromide (CTAB) method and subjected to PCR. After viral confirmation, the viral genome was amplified by rolling circle amplification following the standard protocol. The DNA A and DNA B subgenomes were cloned individually as a PstI and BamHI fragment in the pUC18 vector. Positive clones were subjected to DNA sequencing. The results revealed that DNA A and DNA B show the closest nucleotide identity with "mungbean yellow mosaic India virus-[Mungbean], DNA-A, the complete sequence" (GeneBank Accession No AF416742.1) with 98.14% identity, and "mungbean yellow mosaic India virus isolate Mu1-Dholi segment DNA-B, the complete sequence" (GeneBank Accession No MW814723.1) with 97.94% identity, respectively. The new isolate of mungbean yellow mosaic India virus (MYMIV) shows sequence similarity with the coat protein gene of various strains of MYMIV. In the new isolate of MYMIV, a point mutation wasobserved at the 2036th nucleotide of DNA B, which disrupts the reading frame to introduce a stop codon and thus leading to a decrease in the size of the movement protein gene. In the present study we are reporting the whole genome sequence of the MYMIV Dayalbagh isolate for the first time.

Graph-DTI: A New Model for Drug-target Interaction Prediction Based on Heterogenous Network Graph Embedding.

In this study, we aimed to develop a new end-to-end learning model called Graph-Drug-Target Interaction (DTI), which integrates various types of information in the heterogeneous network data, and to explore automatic learning of the topology-maintaining representations of drugs and targets, thereby effectively contributing to the prediction of DTI. Precise predictions of DTI can guide drug discovery and development. Most machine learning algorithms integrate multiple data sources and combine them with common embedding methods. However, the relationship between the drugs and target proteins is not well reported. Although some existing studies have used heterogeneous network graphs for DTI prediction, there are many limitations in the neighborhood information between the nodes in the heterogeneous network graphs. We studied the drug-drug interaction (DDI) and DTI from DrugBank Version 3.0, protein-protein interaction (PPI) from the human protein reference database Release 9, drug structure similarity from Morgan fingerprints of radius 2 and calculated by RDKit, and protein sequence similarity from Smith-Waterman score. Our study consists of three major components. First, various drugs and target proteins were integrated, and a heterogeneous network was established based on a series of data sets. Second, the graph neural networks-inspired graph auto-encoding method was used to extract high-order structural information from the heterogeneous networks, thereby revealing the description of nodes (drugs and proteins) and their topological neighbors. Finally, potential DTI prediction was made, and the obtained samples were sent to the classifier for secondary classification. The performance of Graph-DTI and all baseline methods was evaluated using the sums of the area under the precision-recall curve (AUPR) and the area under the receiver operating characteristic curve (AUC). The results indicated that Graph-DTI outperformed the baseline methods in both performance results. Compared with other baseline DTI prediction methods, the results showed that Graph-DTI had better prediction performance. Additionally, in this study, we effectively classified drugs corresponding to different targets and vice versa. The above findings showed that Graph-DTI provided a powerful tool for drug research, development, and repositioning. Graph- DTI can serve as a drug development and repositioning tool more effectively than previous studies that did not use heterogeneous network graph embedding.

Mapping genetic susceptibility to spontaneous preterm birth: Analysis of Utah pedigrees to find inherited genetic factors.

Spontaneous preterm birth (SPTB) is the leading cause of neonatal morbidity and mortality. It is a final common pathway for multiple etiologies, some of which are well known while others likely remain to be identified. Despite recent advancements in identifying genetic risk factors, the mechanisms of many SPTBs remain poorly understood due to the phenotypic heterogeneity and complexity. Large family-based studies decrease heterogeneity and improve power to identify genetic causes of SPTB. To identify inherited genetic factors in SPTB etiology using large families. Using the Utah Population Database, which links a 4.5 million-person genealogy to state birth certificate and fetal death records, we identified large pedigrees containing multiple women with early SPTB (<34 weeks' gestation) and any SPTB (<37 weeks' gestation). We reviewed birth certificate data to exclude those with maternal and fetal diagnoses associated with iatrogenic preterm birth, resulting in 74 large multiplex pedigrees for early SPTB. Enrolled women with SPTB underwent comprehensive clinical phenotyping with review of primary medical records. Seven pedigrees, each containing at least 3 sampled women with SPTB, were the focus of this genetic study. High-density single-nucleotide polymorphism genotyping was conducted in maternal peripheral blood samples from women in the seven pedigrees. Shared genomic segments analysis was performed to identify genome-wide significant chromosomal regions shared in excess by women with SPTB. We identified two genome-wide significant chromosomal regions. In single-pedigree SGS analysis, a 1.75 Mega base region in chromosome 8 (8q24.23) was shared by 5 out of 6 women with SPTB in a single large pedigree (false positive rate=0.028). In duo-pedigree analysis, a 1.05 Mega base region in the same 8q24.23 locus was identified in a second pedigree (false-positive rate [duo]= 0.0019). The intersecting region at the 8q24.23 locus contains FAM135B (family with sequence similarity 135 member B) and KHDRBS3 (KH RNA binding domain containing, signal transduction associated 3) genes, which have previously been implicated in oncogenesis and ovarian cancer, respectively. Duo-pedigree SPTB analysis also identified a second genome-wide significant 67 kilo base locus in chromosome 12 (12q21.1-q21.2) that was shared by all women with SPTB in two independent pedigrees (false-positive rate [duo] =0.01). The intersecting region at the 12q21.1-q21.2 locus contains CAPS2 (calcyphosine 2) and KCNC2 (potassium voltage-gated channel subfamily C member 2) genes, both implicated in vascular-related complications of pregnancy and preterm labor. Using large SPTB families, we identified shared chromosomal regions (8q24.23 and 12q21.1-q21.2), providing evidence for inherited (segregating) risk loci in SPTB etiology. Further investigation into genes in SPTB etiology, including functional validation may provide avenues for novel therapeutic development and guide efforts for SPTB prevention to prolong pregnancy and improve outcomes.

FAM83H regulated by glis3 promotes triple-negative breast cancer tumorigenesis and activates the NF-κB signaling pathway.

Triple-negative breast cancer (TNBC) is a highly aggressive and invasive form of breast cancer (BC) with a high mortality rate and a lack of effective targeted drugs. Family with sequence similarity 83 member H (FAM83H) is critically implicated in tumorigenesis. However, the potential role of FAM83H in TNBC remains elusive. Here, we discovered that FAM83H exhibited high expression in tumor tissues of patients with TNBC and was associated with TNM stage. Gain- or loss-of-function experiments were conducted to explore the biological role of FAM83H in TNBC. Subsequently, functional enrichment analysis confirmed that FAM83H overexpression promoted TNBC cell proliferation, invasion, migration and epithelial-mesenchymal transition (EMT), accompanied by upregulation of cyclin E, cyclin D, Vimentin, N-cadherin and Slug. As observed, FAM83H knockdown showed anti-cancer effects, such as fostering apoptosis and inhibiting tumorigenicity and metastasis of TNBC cells. Mechanistically, FAM83H activated the NF-κB signaling pathway. Moreover, a dual-luciferase reporter assay demonstrated that GLIS family zinc finger 3 (GLIS3) bound to the promoter of FAM83H and enhanced its transcription. Notably, overexpression of GLIS3 significantly stimulated TNBC cell proliferation and invasion, and all of this was reversed by rescue experiments involving the knockdown of FAM83H. Overall, FAM83H exacerbates tumor progression, and in-depth understanding of FAM83H as a therapeutic target for TNBC will provide clinical translational potential for intervention therapy.

SO-TAD: A surveillance-oriented benchmark for traffic accident detection

Automatic traffic accident detection is a crucial component of Vehicle-to-Infrastructure (V2I) systems and is gaining increasing attention from researchers due to its significant impact on road safety. However, existing datasets often suffer from issues such as data contamination, small scale, and lack of open access, which hinder the advancement of research in this field. To overcome these challenges, we introduce the high-quality, large-scale Surveillance-Oriented Traffic Accident Detection (SO-TAD) dataset, designed with long-tail distribution characteristics. The SO-TAD dataset comprises 2,186 samples, including 282 traffic accident instances, each providing spatio-temporal localization information. Furthermore, within the proposed frame prediction-based traffic accident detection framework, we designed a three-channel scene feature fusion generative adversarial network (TCFF-GAN). This network integrates scene introduction features and scene difference features to generate predictive frame features. Subsequently, traffic accidents are detected based on the stability of the cosine similarity sequence between the predicted frames and the actual frames. We validated the effectiveness of the proposed TCFF-GAN not only through public datasets but also by conducting extensive experiments on the newly introduced SO-TAD dataset. This work also establishes a new benchmark for automatic traffic accident detection research. The code and dataset are available at https://github.com/cccxy-299/so-tad.