Integrated analysis of the transcriptome and metabolome reveals the molecular mechanism regulating cotton boll abscission under low light intensity.

BACKGROUND: Cotton boll shedding is one of the main factors adversely affecting the cotton yield. During the cotton plant growth period, low light conditions can cause cotton bolls to fall off prematurely. In this study, we clarified the regulatory effects of low light intensity on cotton boll abscission by comprehensively analyzing the transcriptome and metabolome. RESULTS: When the fruiting branch leaves were shaded after pollination, all of the cotton bolls fell off within 5 days. Additionally, H2O2 accumulated during the formation of the abscission zone. Moreover, 10,172 differentially expressed genes (DEGs) and 81 differentially accumulated metabolites (DAMs) were identified. A KEGG pathway enrichment analysis revealed that the identified DEGs and DAMs were associated with plant hormone signal transduction and flavonoid biosynthesis pathways. The results of the transcriptome analysis suggested that the expression of ethylene (ETH) and abscisic acid (ABA) signaling-related genes was induced, which was in contrast to the decrease in the expression of most of the IAA signaling-related genes. A combined transcriptomics and metabolomics analysis revealed that flavonoids may help regulate plant organ abscission. A weighted gene co-expression network analysis detected two gene modules significantly related to abscission. The genes in these modules were mainly related to exosome, flavonoid biosynthesis, ubiquitin-mediated proteolysis, plant hormone signal transduction, photosynthesis, and cytoskeleton proteins. Furthermore, TIP1;1, UGT71C4, KMD3, TRFL6, REV, and FRA1 were identified as the hub genes in these two modules. CONCLUSIONS: In this study, we elucidated the mechanisms underlying cotton boll abscission induced by shading on the basis of comprehensive transcriptomics and metabolomics analyses of the boll abscission process. The study findings have clarified the molecular basis of cotton boll abscission under low light intensity, and suggested that H2O2, phytohormone, and flavonoid have the potential to affect the shedding process of cotton bolls under low light stress.

Associations of combined exposures to ambient temperature, air pollution, and green space with hypertension in rural areas of Anhui Province, China: A cross-sectional study.

Hypertension (HTN) was a major preventable cause of cardiovascular disease (CVD), contributing to a huge disease burden. Ambient temperature, air pollution and green space were important influencing factors of HTN, and few studies have assessed the effects and interactions of ambient temperature, air pollution and green space on HTN in rural areas. In this study, we selected 8400 individuals randomly in rural areas of Anhui Province by a multi-stage stratified cluster sampling. A total of 8383 individuals were included in the final analysis. We collected particulate pollutants and meteorological data from the local air quality monitoring stations and National Center for Meteorological Science from January 1 to December 31, 2020, respectively. The normalized differential vegetation index (NDVI) of Anhui Province in 2020 was produced and processed by remote sensing inversion on the basis of medium resolution satellite images. The average annual mean exposure concentrations of air pollution, meteorological factors, and NDVI were calculated for each individual based on the geocoded residential address. HTN was defined according the Chinese Guidelines for Prevention and Treatment of HTN. The effects and interactions of ambient temperature, air pollution and green space on HTN were evaluated by generalized linear model and interaction model, respectively. In this study, the prevalence of HTN was 24.14%. The adjusted odd ratio of HTN for each 1 µg/m3 increasing in PM2.5 and PM10, 1 °C of ambient temperature, and 0.1 of NDVI were:1.276 (1.013, 1.043), 1.012 (1.006, 1.018), 0.862 (0.862, 0.981) and 0.669 (0.611, 0.733), respectively. The results showed that air pollutants were positively correlated with HTN, while ambient temperature and green space were negatively correlated with HTN. Meanwhile, the negative associations of green space on HTN could decrease with the increasing concentrations of air pollution, but increase with the rising of ambient temperature.

Physical mapping and candidate gene prediction of fertility restorer gene of cytoplasmic male sterility in cotton.

BACKGROUND: Cytoplasmic male sterility (CMS) is a maternally inherited trait failing to produce functional pollen. It plays a pivotal role in the exploitation of crop heterosis. The specific locus amplified fragment sequencing (SLAF-seq) as a high-resolution strategy for the identification of new SNPs on a large-scale is gradually applied for functional gene mining. The current study combined the bulked segregant analysis (BSA) with SLAF-seq to identify the candidate genes associated with fertility restorer gene (Rf) in CMS cotton. METHODS: Illumina sequencing systematically investigated the parents. A segregating population comprising of 30 + 30 F2 individuals was developed using 3096A (female parent) as sterile and 866R (male parent) as a restorer. The original data obtained by dual-index sequencing were analyzed to obtain the reads of each sample that were compared to the reference genome in order to identify the SLAF tag with a polymorphism in parent lines and the SNP with read-associated coverage. Based on SLAF tags, SNP-index analysis, Euclidean distance (ED) correlation analysis, and whole genome resequencing, the hot regions were annotated. RESULTS: A total of 165,007 high-quality SLAF tags, with an average depth of 47.90× in the parents and 50.78× in F2 individuals, were sequenced. In addition, a total of 137,741 SNPs were detected: 113,311 and 98,861 SNPs in the male and female parent, respectively. A correlation analysis by SNP-index and ED initially located the candidate gene on 1.35 Mb of chrD05, and 20 candidate genes were identified. These genes were involved in genetic variations, single base mutations, insertions, and deletions. Moreover, 42 InDel markers of the whole genome resequencing were also detected. CONCLUSIONS: In this study, associated markers identified by super-BSA could accelerate the study of CMS in cotton, and as well as in other crops. Some of the 20 genes' preliminary characteristics provided useful information for further studies on CMS crops.

A novel Gossypium barbadense ERF transcription factor, GbERFb, regulation host response and resistance to Verticillium dahliae in tobacco.

Ethylene-responsive factors (ERFs) are commonly considered to play an important role in pathogen defense responses. However, only few of ERF members have been characterized in Sea island cotton (Gossypium barbadense). Here, we reported a novel AP2/ERF transcription factors gene, named GbERFb which was cloned and identified from Sea island cotton by RACE. The expression of GbERFb was significantly induced by treatments with ethylene, Methyl jasmonate, salicylic acid, wounding, H2O2 and Verticillium dahliae (V. dahliae) infection. Bioinformatics analysis showed that GbERFb protein containing a conserved ERF DNA binding domain and a nuclear localization signal sequence, belonged to IXb subgroup of the ERF family. Further experiments demonstrated that GbERFb could bind the GCC box cis-acting element and interact with GbMAPKb (MAP kinase) directly in yeast. Over-expression of GbERFb in tobacco could increase the disease resistance to V. dahliae. The results suggest that the GbERFb, a new AP2/ERF transcription factor, could enhance the resistance to V. dahliae and be useful in improvement of crop resistance to pathogenes.

Combined small RNA and degradome sequencing to identify miRNAs and their targets in response to drought in foxtail millet.

BACKGROUND: Foxtail millet (Setaria italica) is a diploid C4 panicoid species. Because of its prominent drought resistance, small genome size, self-pollination, and short life cycle, foxtail millet has become an ideal model system for studying drought tolerance of crops. MicroRNAs (miRNAs) are endogenous, small RNAs that play important regulatory roles in the development and stress response in plants. RESULTS: In this study, we applied Illumina sequencing to systematically investigate the drought-responsive miRNAs derived from S. italica inbred An04-4783 seedlings grown under control and drought conditions. Degradome sequencing was applied to confirm the targets of these miRNAs at a global level. A total of 81 known miRNAs belonging to 28 families were identified, among which 14 miRNAs were upregulated and four were downregulated in response to drought. In addition, 72 potential novel miRNAs were identified, three of which were differentially expressed under drought conditions. Degradome sequencing analysis showed that 56 and 26 genes were identified as targets of known and novel miRNAs, respectively. CONCLUSIONS: Our analysis revealed post-transcriptional remodeling of cell development, transcription factors, ABA signaling, and cellar homeostasis in S.italica in response to drought. This preliminary characterization provided useful information for further studies on the regulatory networks of drought-responsive miRNAs in foxtail millet.

GhFB15 is an F-box protein that modulates the response to salinity by regulating flavonoid biosynthesis.

An exposure to extremely saline conditions can lead to significant oxidative damage in plants. Flavonoids, which are potent antioxidants, are critical for the scavenging of reactive oxygen species caused by abiotic stress. In the present study, the cotton F-box gene GhFB15 was isolated and characterized. The expression of GhFB15 was rapidly induced by salt as well as by exogenous hormones (ETH, MeJA, ABA, and GA). An analysis of subcellular localization revealed GhFB15 is mainly distributed in nuclei. Overexpression of GhFB15 adversely affected the salt tolerance of transgenic Arabidopsis plants as evidenced by decreased seed germination and seedling growth, whereas the silencing of GhFB15 improved the salt tolerance of cotton plants. Furthermore, we analyzed the gene expression profiles of VIGS-GhFB15 and TRV:00 plants. Many of the differentially expressed genes were associated with the flavonoid biosynthesis pathway. Moreover, lower flavonoid contents and higher levels of H2O2 and O2- were observed in the transgenic Arabidopsis plants. Conversely, the VIGS-GhFB15 cotton plants had relatively higher flavonoid contents, but lower H2O2 and O2- levels. These results suggest that GhFB15 negatively regulates salt tolerance, and silencing GhFB15 results in increased flavonoid accumulation and improved ROS scavenging.

Identification of Crucial Modules and Genes Associated with Bt Gene Expression in Cotton.

The expression of Bacillus thuringiensis (Bt) toxins in transgenic cotton confers resistance to insect pests. However, it has been demonstrated that its effectiveness varies among cotton cultivars and different tissues. In this study, we evaluated the expression of Bt protein in 28 cotton cultivars and selected 7 cultivars that differed in Bt protein expression for transcriptome analysis. Based on their Bt protein expression levels, the selected cultivars were categorized into three groups: H (high Bt protein expression), M (moderate expression), and L (low expression). In total, 342, 318, and 965 differentially expressed genes were detected in the H vs. L, M vs. L, and H vs. M comparison groups, respectively. And three modules significantly associated with Bt protein expression were identified by weighted gene co-expression network analysis. Three hub genes were selected to verify their relationships with Bt protein expression using virus-induced gene silencing (VIGS). Silencing GhM_D11G1176, encoding an MYC transcription factor, was confirmed to significantly decrease the expression of Bt protein. The present findings contribute to an improved understanding of the mechanisms that influence Bt protein expression in transgenic cotton.

Association of exposure to multiple serum metals with the risk of chronic kidney disease in the elderly: a population-based case-control study.

In the world, chronic kidney disease (CKD) has been recognized as one of the critical public health problems, and the prevalence is higher in the elderly people. However, there are few studies on the association between exposure to multiple serum metal levels and CKD. A case-control study, we established, for elderly people in Anhui Province, China, to explore the effects of different metals and analyze the effect of mixed exposure on CKD. In this study, 287 cases of CKD and 287 controls were selected in the elderly health physical examination project in Tongling City, Anhui Province. Questionnaire survey, physical examination, and blood collection were conducted. Graphite furnace atomic absorption spectrometry (GFAAS) and inductively coupled plasma optical emission spectrometry (ICP-OES) were used to measure the concentration of serum metals. After selecting by least absolute shrinkage and selection operator (LASSO), 5 metals were brought into the multi-metal model. After adjusting all potential covariates additionally, the concentrations of lead (Pb), cadmium (Cd), cobalt (Co), and manganese (Mn) were significantly associated with CKD risk, whereas Pb, Se, and Cd had significant non-linearity with CKD. Besides, patients with highest quartiles of cobalt (Co), lead (Pb), and manganese (Mn) were 1.64, 1.39, and 0.64 times more possible to have CKD, respectively, as compared with the lowest levels. In the Bayesian kernel machine regression (BKMR) model, cadmium (Cd) had a combined effect with lead (Pb) possibly. This study suggested that the CKD risk was associated with exposure of multiple metals in elderly people. The underlying mechanisms of serum metals and CKD need more experimental and prospective studies to elucidate.

Genome-wide analysis of mutations induced by carbon ion beam irradiation in cotton.

Carbon ion beam (CIB) irradiation is a powerful way to create mutations in animals, plants, and microbes. Research on the mutagenic effects and molecular mechanisms of radiation is an important and multidisciplinary issue. However, the effect of carbon ion radiation on cotton is uncertain. In this study, five different upland cotton varieties and five CIB doses were used to identify the suitable irradiation dose for cotton. Three mutagenized progeny cotton lines from the wild-type Ji172 were re-sequenced. The effect of half-lethal dose on mutation induction indicated that 200 Gy with LETmax of 226.9 KeV/µm was the most effective heavy-ion dose for upland cotton and a total of 2,959-4,049 single-base substitutions (SBSs) and 610-947 insertion-deletion polymorphisms (InDels) were identified among the three mutants by resequencing. The ratio of transition to transversion in the three mutants ranged from 2.16 to 2.24. Among transversion events, G:C>C:G was significantly less common than three other types of mutations (A:T>C:G, A:T>T:A, and G:C>T:A). The proportions of six types of mutations were very similar in each mutant. The distributions of identified SBSs and InDels were similar with unevenly distributed across the genome and chromosomes. Some chromosomes had significantly more SBSs than others, and there were "hotspot" mutation regions at the ends of chromosomes. Overall, our study revealed a profile of cotton mutations caused by CIB irradiation, and these data could provide valuable information for cotton mutation breeding.

Short-term exposure to six air pollutants and cause-specific cardiovascular mortality of nine counties or districts in Anhui Province, China.

Recently, the burden of cardiovascular disease (CVD) has attracted global attention. Meanwhile, CVD has become the leading cause of death in China. Some epidemiological studies have indicated that ambient air pollution may contribute to increased mortality from CVD diseases. Many studies have found a strong association between air pollutants and the risk of CVD deaths in some big cities, but few have focused on the effects of six pollutants in rural areas. Our study aimed to investigate the effects of six air pollutants (CO, NO2, O3, PM2.5, PM10, and SO2) on CVD deaths of rural areas in Anhui Province and to further clarify which populations were susceptible to air pollution. First, the generalized additive models were combined with the distributed lag nonlinear models to evaluate the individual effects of air pollution on CVD deaths in each area. Then, random-effects models were used to aggregate the associations between air pollutants and CVD mortality risk in nine regions. Overall, all six pollutants had a statistically significant effect on the risk of CVD deaths on the lag 07 days. The associations between PM2.5, PM10, and SO2 and daily CVD deaths were strongest, with maximum cumulative RR (lag 07) of 1.91 (1.64-2.18), 2.27 (1.50-3.05), and 2.13 (1.44-2.82). In general, we found that six air pollutants were the important risk factors for CVD and specific CVD deaths in Anhui Province. The elderly were susceptible to PM2.5, PM10, and SO2.

Six air pollutants and cause-specific mortality: a multi-area study in nine counties or districts of Anhui Province, China.

Air pollution and its negative effects on health of people have been a global concern. Many studies had found a strong association between air pollutants and risk of death, but few had focused on the effects of six pollutants and rural areas. Our study aimed to investigate the effects of six air pollutants (CO, NO2, O3, PM2.5, PM10, and SO2) on non-accidental and respiratory deaths in rural areas of Anhui Province by adjusting for confounding factors, and to further clarify which populations were susceptible to death associated with air pollution. In the first phase of the analysis, the generalized additive models were combined with the distributed lag non-linear models to evaluate the individual effects of air pollution on death in each area. In the second stage, random-effects models were used to aggregate the associations between air pollutants and mortality risk in nine areas. Overall, six pollutants had the strongest effects on the risk of death on the lag 07 days. The associations between PM2.5 and NO2 and daily non-accidental deaths were strongest, with maximum RR (lag 07): 1.63 (1.37-1.88) and 1.67 (1.37-1.96). The maximum pooled effects of association between six air pollutants and RD were PM2.5, with RR (lag 07): 1.89 (1.45-2.34). PM2.5 and PM10 had significant differences between the elderly and the non-elderly with respectively, RRR: 1.22 (1.04-1.41) and 1.26 (1.11-1.42). In general, we found that six air pollutants were the important risk factors for deaths (deaths from respiratory disease and non-accidental) in rural areas of Anhui Province. PM10 and PM2.5 had a considerable impact on the elderly.

Effects of carbon dioxide and green space on sleep quality of the elderly in rural areas of Anhui Province, China.

Sleep quality leads to many healthy problems, which has caused global concern. Most studies have focused on the sleep quality in some large cities, ignoring the elderly in rural areas who may have more serious sleep problems. Therefore, this study aimed to understand the sleep status of the elderly in rural areas of Anhui Province and the influence of environmental factors on it. The data of carbon dioxide (CO2) concentrations for this study were obtained from the Dalhousie University atmospheric composition analysis group. The data of normalized differential vegetation index (NDVI) in 2014 was produced and processed by remote sensing inversion on the basis of medium resolution satellite images. The 2686 individuals were selected from rural areas of Anhui Province by multi-stage stratified cluster sampling. The Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. The independent, interactive, and mediating effects of CO2 and green space on sleep quality were evaluated by generalized linear model, interaction model, and mediating effect model, respectively. In this study, we found that the prevalence of sleep disturbance in the elderly was 58.40%. In the univariate model, we found that the risk of sleep disturbance increased by 1.6% for each 1 µg/m3 increase in concentrations of CO2, while decreased by 1.5% for every 0.1 increase in NDVI. In the interaction model, the negative correlation between green space and sleep quality decreased with concentrations of CO2 increased. In addition, green space was a mediating factor between CO2 and sleep quality in the mediating effect model.

Multiple environmental exposures and obesity in eastern China: An individual exposure evaluation model.

Obesity has caused a huge burden of disease. Few studies have explored individuals' environmental exposure level and the impact of multiple environmental exposures on obesity. The aim of this study was to explore individual air pollution exposure evaluation, and the association between and multiple environmental factors and obesity among adult residents in rural areas of China. In this study, 8400 residents of 14 districts and counties in eastern of China were selected by multistage stratified cluster sampling, and a total of 8377 residents were included in the final analysis. We adopted BMI (Body Mass Index) > 28 kg/m2 as the definition of obesity. First, an individual air pollution evaluation model was established based on the monitoring data of air pollution stations closest to residential address, different demographic characteristics of residents and daily living habits using generalized linear model and random forest model. Then, we used Bayesian Kernel Machine Regression (BKMR) and Quantile g-Computation (QgC) models to explore multiple environmental exposures on obesity. The results showed that six air pollutants were significantly positively associated with obesity, and green space had a significant protective effect on obesity. The BKMR model showed that the effects of different air pollutants on obesity were significantly enhanced by each other, while green space significantly reduced the positive effect of air pollution on obesity. The QgC model showed a significant positive association with obesity when all environmental factors were exposed as a whole, especially in males, higher household incomes and young people. It suggested that relevant authorities should improve regional air quality and green space to reduce the burden of disease caused by obesity.

Body mass index and weight gain after middle adulthood are associated with risk of papillary thyroid cancer: A case-control study.

BACKGROUND: It is unclear whether weight change after middle adulthood influences the risk of thyroid cancer. The aim of this study was to investigate associations between the risk of papillary thyroid cancer (PTC) and body mass index (BMI) and weight change after middle adulthood (age 35). METHODS: A matched case-control study based on three hospitals included 516 pairs of cases newly diagnosed with PTC and controls. Current height and weight after defecation in the morning were measured by trained nurses. During measurement, all subjects were requested to wear lightweight clothing and no shoes. Weight at age 35 was self-reported. BMI and weight change were modeled as continuous and categorical variables. Conditional and unconditional logistic regression models were used to estimate the odds ratio (OR) and 95% confidence interval (95%CI) for the association between BMI and weight change after middle adulthood and PTC. RESULTS: After adjustment for covariates, measured BMI at the time of current diagnosis was positively associated with PTC (OR 1.16, 95%CI 1.10-1.21). According to WHO BMI guidelines for Asia-Pacific populations, the OR (95%CI) for PTC risk in obesity was 2.99 (1.92-4.67) compared to normal weight (p-trend <0.001). Moreover, PTC was positively associated with BMI at age 35; the OR (95%CI) for PTC risk per unit increase in BMI was 1.06 (1.02-1.11). Compared to stable weight (changed <0.5 kg/year), weight gain ≥1.0 kg/year after middle adulthood was positively associated with PTC (OR 2.57, 95%CI 1.39-4.76, p-trend <0.001). Compared to maintaining non-overweight status, the PTC risk was significantly increased in those individuals who gained weight and became overweight after middle adulthood (OR 3.82, 95%CI 2.50-5.85). CONCLUSION: This study showed that high BMI and obesity were positively associated with increased risk of PTC, and weight gain after middle adulthood also could elevate the PTC risk.

Exposure to 2,4-dichlorophenol, 2,4,6-trichlorophenol, pentachlorophenol and risk of thyroid cancer: a case-control study in China.

Thyroid cancer (TC) has inflicted huge threats to the health of mankind. Chlorophenols (CPs) were persistent organic pollutant and can lead to adverse effects in human health, especially in thyroid. However, epidemiological studies have revealed a rare and inconsistent relationship between internal exposure to CPs and TC risk. The purpose of this study was to investigate the correlation between urinary CPs and TC risk in Chinese population. From June 2017 to September 2019, a total of 297 histologically confirmed TC cases were recruited. Age- and gender-matched controls were enrolled at the same time. Gas chromatography-mass spectrometry (GC-MS) was used to determine the levels of three CPs in urine. Conditional logistic regression models were adopted to assess the potential association. Restricted cubic spline function was used to explore the non-liner association. After adjusting for confounding factors, multivariate analysis showed that, compared with the first quartile, the fourth quartile concentrations of 2,4-dichlorophenol (2,4-DCP), 2,4,6-trichlorophenol (2,4,6-TCP), and pentachlorophenol (PCP) were associated with TC risk (odds ratio (OR)2,4-DCP =2.28, 95% confidence interval (CI): 1.24-4.18; OR2,4,6-TCP =3.09, 95% CI: 1.66-5.77; ORPCP =3.30, 95% CI: 1.71-6.36, respectively), when CPs were included in the multivariate model and restricted cubic spline function as continuous variables, presenting significant dose-response relationships. Meanwhile, whether in the TC group with tumor diameter > 1 cm or metastatic TC, the changes of 2,4,6 TCP and PCP concentrations were positively correlated with the risk of TC. Our study suggests that higher concentrations of urinary CPs are associated with increased TC risks. Moreover, 2,4,6-TCP and PCP have certain effects on the invasiveness of thyroid cancer. Targeted public health policies should be formulated to reduce the CP pollution. These findings need further in-depth studies to confirm and relevant mechanism also needed to be clarified.

Associations of exposure to multiple trace elements with the risk of goiter: A case-control study.

Goiter is one of common endocrine diseases, and its etiology has not been fully elucidated. The changes in trace elements' levels have an important impact on the thyroid. We designed a case-control study, which involved 383 goiter cases and 383 matched controls. We measured these elements in the urine of participants by inductively coupled plasma optical emission spectrometry (ICP-OES), graphite furnace atomic absorption spectrometry (GFAAS) and As3+-Ce4+ catalytic spectrophotometry. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select the elements into multi-element models, conditional logistic regression models were applied to analyze the association between elements and goiter risk. Bayesian kernel machine regression (BKMR) model was used to depict elements' mixtures and evaluate their joint effects. Finally, 7 elements were included in the multi-element model. We found that the concentrations of lithium (Li), strontium (Sr) and barium (Ba) had a negative effect with goiter risk, and lead (Pb) and iodine (I) showed an extreme positive effect. Additionally, compared with the lowest levels, patients with highest quartiles of I and Pb were 6.49 and 1.94 times more likely to have goiter, respectively. On the contrary, in its second and third quartiles, arsenic (As) showed a negative effect (both OR<1). BKMR model showed a certain interaction among Pb, As, Sr and Li on goiter risk. Further large sample studies are needed to confirm these findings in the future.