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.

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Background Gestational diabetes mellitus (GDM) affects the immune balance of pregnant women and their offspring. However, most studies on cord blood have not yielded satisfactory results. Most studies in the field of epigenetics have problems such as small data size, unqualified sampling, cannot be repeated verification, the results are not significant, and usually, there is no multi-omics analysis. Therefore, it is difficult to systematically reveal the critical factors of epigenetic changes in GDM on the immune function of the offspring of GDM pregnant women. Results We randomly recruited 30 pregnant women, including 20 pregnant women with GDM (experimental group) and 10 pregnant women without GDM (control group). 9327 genes in hyper-methylated DMPs, 10908 genes in hypo-methylated DMPs, 42 genes in hyper-methylated DMRs, and 209 genes in hypo-methylated DMRs were identified. Through integration analysis with multiple datasets in the GEO public database, it was found that the genes obtained by DMPs were more accurate than those obtained by DMRs. Through data analysis, we got two groups of gene sets, and functional analysis found that they were related to human immune function. After immune infiltration analysis, it was found that CD4T cells were significantly reduced in the cord blood of pregnant GDM women. To further verify the effect of GDM on cord blood immune function, the integration analysis of the two gene sets identified HIST1H1B and PRTN3 genes. Among them, the cg24587427 and cg00700007 sites of the HIST1H1B gene were significantly correlated with the amount of CD4T cells in the cord blood. Conclusions In this study, we broke the previous lack of practical results from cord blood in terms of epigenetics and confirmed that the changes in the intrauterine environment of pregnant women with GDM affect the immune function of newborns.

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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.