RNA barcode segments for SARS-CoV-2 identification from HCoVs and SARSr-CoV-2 lineages.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen responsible for coronavirus disease 2019 (COVID-19), continues to evolve, giving rise to more variants and global reinfections. Previous research has demonstrated that barcode segments can effectively and cost-efficiently identify specific species within closely related populations. In this study, we designed and tested RNA barcode segments based on genetic evolutionary relationships to facilitate the efficient and accurate identification of SARS-CoV-2 from extensive virus samples, including human coronaviruses (HCoVs) and SARSr-CoV-2 lineages. Nucleotide sequences sourced from NCBI and GISAID were meticulously selected and curated to construct training sets, encompassing 1733 complete genome sequences of HCoVs and SARSr-CoV-2 lineages. Through genetic-level species testing, we validated the accuracy and reliability of the barcode segments for identifying SARS-CoV-2. Subsequently, 75 main and subordinate species-specific barcode segments for SARS-CoV-2, located in ORF1ab, S, E, ORF7a, and N coding sequences, were intercepted and screened based on single-nucleotide polymorphism sites and weighted scores. Post-testing, these segments exhibited high recall rates (nearly 100%), specificity (almost 30% at the nucleotide level), and precision (100%) performance on identification. They were eventually visualized using one and two-dimensional combined barcodes and deposited in an online database (http://virusbarcodedatabase.top/). The successful integration of barcoding technology in SARS-CoV-2 identification provides valuable insights for future studies involving complete genome sequence polymorphism analysis. Moreover, this cost-effective and efficient identification approach also provides valuable reference for future research endeavors related to virus surveillance.

Using search trends to analyze web-based users' behavior profiles connected with COVID-19 in mainland China: infodemiology study based on hot words and Baidu Index.

Background: Mainland China, the world's most populous region, experienced a large-scale coronavirus disease 2019 (COVID-19) outbreak in 2020 and 2021, respectively. Existing infodemiology studies have primarily concentrated on the prospective surveillance of confirmed cases or symptoms which met the criterion for investigators; nevertheless, the actual impact regarding COVID-19 on the public and subsequent attitudes of different groups towards the COVID-19 epidemic were neglected. Methods: This study aimed to examine the public web-based search trends and behavior patterns related to COVID-19 outbreaks in mainland China by using hot words and Baidu Index (BI). The initial hot words (the high-frequency words on the Internet) and the epidemic data (2019/12/01-2021/11/30) were mined from infodemiology platforms. The final hot words table was established by two-rounds of hot words screening and double-level hot words classification. Temporal distribution and demographic portraits of COVID-19 were queried by search trends service supplied from BI to perform the correlation analysis. Further, we used the parameter estimation to quantitatively forecast the geographical distribution of COVID-19 in the future. Results: The final English-Chinese bilingual table was established including six domains and 32 subordinate hot words. According to the temporal distribution of domains and subordinate hot words in 2020 and 2021, the peaks of searching subordinate hot words and COVID-19 outbreak periods had significant temporal correlation and the subordinate hot words in COVID-19 Related and Territory domains were reliable for COVID-19 surveillance. Gender distribution results showed that Territory domain (the male proportion: 67.69%; standard deviation (SD): 5.88%) and Symptoms/Symptom and Public Health (the female proportion: 57.95%, 56.61%; SD: 0, 9.06%) domains were searched more by male and female groups respectively. The results of age distribution of hot words showed that people aged 20-50 (middle-aged people) had a higher online search intensity, and the group of 20-29, 30-39 years old focused more on Media and Symptoms/Symptom (proportion: 45.43%, 51.66%; SD: 15.37%, 16.59%) domains respectively. Finally, based on frequency rankings of searching hot words and confirmed cases in Mainland China, the epidemic situation of provinces and Chinese administrative divisions were divided into 5 levels of early-warning regions. Central, East and South China regions would be impacted again by the COVID-19 in the future.

Comprehensive Genome-Wide Identification, Characterization, and Expression Analysis of CCHC-Type Zinc Finger Gene Family in Wheat (Triticum aestivum L.).

The CCHC-type zinc finger proteins (CCHC-ZFPs) play versatile roles in plant growth, development and adaptation to the environment. However, little is known about functions of CCHC-ZFP gene family memebers in Triticum aestivum. In the present study, we identified a total of 50 TaCCHC-ZFP genes from the 21 wheat chromosomes, which were phylogenetically classified into eight groups based on their specific motifs and gene structures. The 43 segmentally duplicated TaCCHC-ZFP genes were retrieved, which formed 36 segmental duplication gene pairs. The collinearity analyses among wheat and other eight mono/dicots revealed that no gene pairs were found between wheat and the three dicots. The promoter analyses of the TaCCHC-ZFP genes showed that 636 environmental stress-responsive and phytohormone-responsive cis-elements. The gene ontology enrichment analysis indicated that all the TaCCHC-ZFP genes were annotated under nucleic acid binding and metal ion binding. A total of 91 MicroRNA (miRNA) binding sites were identified in 34 TaCCHC-ZFP genes according to the miRNA target analysis. Based on the public transcriptome data, the 38 TaCCHC-ZFP genes were identified as differentially expressed gene. The expression profiles of 15 TaCCHC-ZFP genes were verified by the quantitative real-time PCR assays, and the results showed that these genes were responsive to drought or heat treatments. Our work systematically investigated the gene structures, evolutionary features, and potential functions of TaCCHC-ZFP genes. It lays a foundation for further research and application of TaCCHC-ZFP genes in genetic improvement of T. aestivum.