Simulating soil salinity dynamics, cotton yield and evapotranspiration under drip irrigation by ensemble machine learning

We thank the China Scholarship Council (CSC) for providing a scholarship (202206710073) to Zewei Jiang. This work was supported by the Fundamental Research Funds for the Central Universities (B220203009), the Postgraduate Research & Practice Program of Jiangsu Province (KYCX22_0669), the Water Conservancy Science and Technology Project of Jiangxi Province (201921ZDKT06, 202124ZDKT09), the National Natural Science Foundation of China (51879076), the Fundamental Research Funds for the Central Universities (B210204016), Science & Technology Specific Projects in Agricultural High-tech Industrial Demonstration Area of the Yellow River Delta, Grant No: 2022SZX01.Peer reviewedPublisher PD

H2AK121ub in Arabidopsis associates with a less accessible chromatin state at transcriptional regulation hotspots

Although it is well established that the Polycomb Group (PcG) complexes maintain gene repression through the incorporation of H2AK121ub and H3K27me3, little is known about the effect of these modifications on chromatin accessibility, which is fundamental to understand PcG function. Here, by integrating chromatin accessibility, histone marks and expression analyses in different Arabidopsis PcG mutants, we show that PcG function regulates chromatin accessibility. We find that H2AK121ub is associated with a less accessible but still permissive chromatin at transcriptional regulation hotspots. Accessibility is further reduced by EMF1 acting in collaboration with PRC2 activity. Consequently, H2AK121ub/H3K27me3 marks are linked to inaccessible although responsive chromatin. In contrast, only-H3K27me3-marked chromatin is less responsive, indicating that H2AK121ub-marked hotspots are required for transcriptional responses. Nevertheless, despite the loss of PcG activities leads to increased chromatin accessibility, this is not necessarily accompanied by transcriptional activation, indicating that accessible chromatin is not always predictive of gene expression.National Natural Science Foundation of China 31970532Ministerio de Ciencia e Innovación BIO2016-76457-P, PID2019-106664GB-I00, BIO2017-84066-

Reassortant between Human-Like H3N2 and Avian H5 Subtype Influenza A Viruses in Pigs: A Potential Public Health Risk

Human-like H3N2 influenza viruses have repeatedly been transmitted to domestic pigs in different regions of the world, but it is still uncertain whether any of these variants could become established in pig populations. The fact that different subtypes of influenza viruses have been detected in pigs makes them an ideal candidate for the genesis of a possible reassortant virus with both human and avian origins. However, the determination of whether pigs can act as a “mixing vessel” for a possible future pandemic virus is still pending an answer. This prompted us to gather the epidemiological information and investigate the genetic evolution of swine influenza viruses in Jilin, China.Nasopharyngeal swabs were collected from pigs with respiratory illness in Jilin province, China from July 2007 to October 2008. All samples were screened for influenza A viruses. Three H3N2 swine influenza virus isolates were analyzed genetically and phylogenetically.Influenza surveillance of pigs in Jilin province, China revealed that H3N2 influenza viruses were regularly detected from domestic pigs during 2007 to 2008. Phylogenetic analysis revealed that two distinguishable groups of H3N2 influenza viruses were present in pigs: the wholly contemporary human-like H3N2 viruses (represented by the Moscow/10/99-like sublineage) and double-reassortant viruses containing genes from contemporary human H3N2 viruses and avian H5 viruses, both co-circulating in pig populations.The present study reports for the first time the coexistence of wholly human-like H3N2 viruses and double-reassortant viruses that have emerged in pigs in Jilin, China. It provides updated information on the role of pigs in interspecies transmission and genetic reassortment of influenza viruses

Simulating soil salinity dynamics, cotton yield and evapotranspiration under drip irrigation by ensemble machine learning

Cotton is widely used in textile, decoration, and industry, but it is also threatened by soil salinization. Drip irrigation plays an important role in improving water and fertilization utilization efficiency and ensuring crop production in arid areas. Accurate prediction of soil salinity and crop evapotranspiration under drip irrigation is essential to guide water management practices in arid and saline areas. However, traditional hydrological models such as Hydrus require more variety of input parameters and user expertise, which limits its application in practice, and machine learning (ML) provides a potential alternative. Based on a global dataset collected from 134 pieces of literature, we proposed a method to comprehensively simulate soil salinity, evapotranspiration (ET) and cotton yield. Results showed that it was recommended to predict soil salinity, crop evapotranspiration and cotton yield based on soil data (bulk density), meteorological factors, irrigation data and other data. Among them, meteorological factors include annual average temperature, total precipitation, year. Irrigation data include salinity in irrigation water, soil matric potential and irrigation water volume, while other data include soil depth, distance from dripper, days after sowing (for EC and soil salinity), fertilization rate (for yield and ET). The accuracy of the model has reached a satisfactory level, R2 in 0.78-0.99. The performance of stacking ensemble ML was better than that of a single model, i.e., gradient boosting decision tree (GBDT); random forest (RF); extreme gradient boosting regression (XGBR), with R2 increased by 0.02%-19.31%. In all input combinations, other data have a greater impact on the model accuracy, while the RMSE of the S1 scenario (input without meteorological factors) without meteorological data has little difference, which is -34.22%~19.20% higher than that of full input. Given the wide application of drip irrigation in cotton, we recommend the application of ensemble ML to predict soil salinity and crop evapotranspiration, thus serving as the basis for adjusting the irrigation schedule

Targeted Next Generation Sequencing Revealed a Novel Homozygous Loss-of-Function Mutation in ILDR1 Gene Causes Autosomal Recessive Nonsyndromic Sensorineural Hearing Loss in a Chinese Family

Hereditary hearing impairment is one of the major and common birth defects in Chinese population. Non-syndromic sensorineural hearing loss (NSHL) is the most common types of hereditary hearing impairment. Genotypically and phenotypically NSHL is extremely heterogenous and follow either autosomal dominant or autosomal recessive or X-linked mode of inheritance. Presently, 127 genes have been identified to be associated with both syndromic and (NSHL). Here, we studied a Chinese family with moderate and profound hearing impairment. The proband is a 30-year old Chinese man. The proband was born with normal hearing and at the age of 5-years, the proband was first noticed with hearing impairment. Gradually and progressively the proband was presented with loss of hearing in his both right and left ears at the age of 30 years. The clinical symptoms, age of onset or progression to loss of hearing was similar in both the proband and his younger brother. The proband’s parents are phenotypically normal and non-consanguineous. Clinical diagnosis of the proband and his younger brother has been done by classical pure tone audiogram (PTA). Computed Tomography (CT) found no abnormality in bilateral external ear, middle ear and inner ear. Targeted next generation sequencing was performed with a panel of 127 genes reported to be associated with hereditary hearing impairment. A novel homozygous single nucleotide deletion (c.427delT) in exon 4 of ILDR1 gene has been identified in proband and in his younger brother. Sanger sequencing confirmed that proband’s father and mother are carrying this mutation in a heterozygous manner. This mutation has not been identified in 100 normal healthy control individuals. This mutation (c.427delT) causes frameshift (p.Tyr143Ilefs∗19) which leads to the formation of a truncated ILDR1 protein of 162 amino acids instead of the wild type ILDR1 protein of 546 amino acids. ILDR1 associated hereditary hearing impairment is very rare and this is the first report of identifying a loss-of-function mutation in ILDR1 gene associated with hereditary hearing impairment in Chinese population. Our present study also emphasized the significance of rapid, accurate and cost-effective screening for the patient with hereditary hearing impairment by targeted next generation sequencing

Environmental Controls on Net Ecosystem CO2 Exchange Over a Reed (Phragmites australis) Wetland in the Yellow River Delta, China

Using the Eddy Covariance (EC) technique, we analyzed temporal variation in net ecosystem CO2 exchange (NEE) and determined the effects of environmental factors on the balance between ecosystem photosynthesis and respiration in a reed (Phragmites australis) wetland in the Yellow River Delta, China. Our results indicated that diurnal and seasonal patterns of NEE and its components (ecosystem respiration (R (eco)), gross primary production (GPP)) varied markedly among months for the growing season (May to October). The cumulative CO2 emission was 1,657 g CO2 m(-2), while 2,612 g CO2 m(-2) was approximately accumulated as GPP, which resulted in the reed wetland being a net sink of 956 g CO2 m(-2). The ratio of R (eco) to GPP in reed wetland was 0.68, which was close to other temperate wetlands. Soil temperature and soil moisture exerted the primary controls on R (eco) during the growing season. Daytime NEE values during the growing season were strongly correlated with photosynthetically active radiation. Aboveground biomass showed significant linear relationships with 24-h average NEE, daytime GPP, and R (eco), respectively. Thus, we conclude that the coastal wetland acted as a carbon sink during the growing season despite the variations in environmental conditions, and long-term flux measurements over these ecosystems are undoubtedly necessary.Using the Eddy Covariance (EC) technique, we analyzed temporal variation in net ecosystem CO2 exchange (NEE) and determined the effects of environmental factors on the balance between ecosystem photosynthesis and respiration in a reed (Phragmites australis) wetland in the Yellow River Delta, China. Our results indicated that diurnal and seasonal patterns of NEE and its components (ecosystem respiration (R (eco)), gross primary production (GPP)) varied markedly among months for the growing season (May to October). The cumulative CO2 emission was 1,657 g CO2 m(-2), while 2,612 g CO2 m(-2) was approximately accumulated as GPP, which resulted in the reed wetland being a net sink of 956 g CO2 m(-2). The ratio of R (eco) to GPP in reed wetland was 0.68, which was close to other temperate wetlands. Soil temperature and soil moisture exerted the primary controls on R (eco) during the growing season. Daytime NEE values during the growing season were strongly correlated with photosynthetically active radiation. Aboveground biomass showed significant linear relationships with 24-h average NEE, daytime GPP, and R (eco), respectively. Thus, we conclude that the coastal wetland acted as a carbon sink during the growing season despite the variations in environmental conditions, and long-term flux measurements over these ecosystems are undoubtedly necessary

Winter Soil Respiration from Different Vegetation Patches in the Yellow River Delta, China

Vegetation type and density exhibited a considerable patchy distribution at very local scales in the Yellow River Delta, due to the spatial variation of soil salinity and water scarcity. We proposed that soil respiration is affected by the spatial variations in vegetation type and soil chemical properties and tested this hypothesis in three different vegetation patches (Phragmites australis, Suaeda heteroptera and bare soil) in winter (from November 2010 to April 2011). At diurnal scale, soil respiration all displayed single-peak curves and asymmetric patterns in the three vegetation patches; At seasonal scale, soil respiration all declined steadily until February, and then increased to a peak in next April. But, the magnitude of soil respiration showed significant differences among the three sites. Mean soil respiration rates in winter were 0.60, 0.45 and 0.17 mu mol CO2 m(-2) s(-1) for the Phragmites australis, Suaeda heteroptera and bare soil, respectively. The combined effect of soil temperature and soil moisture accounted for 58-68 % of the seasonal variation of winter soil respiration. The mean soil respiration revealed positive and linear correlations with total N, total N and SOC storages at 0-20 cm depth, and plant biomass among the three sites. We conclude that the patchy distribution of plant biomass and soil chemical properties (total C, total N and SOC) may affect decomposition rate of soil organic matter in winter, thereby leading to spatial variations in soil respiration.Vegetation type and density exhibited a considerable patchy distribution at very local scales in the Yellow River Delta, due to the spatial variation of soil salinity and water scarcity. We proposed that soil respiration is affected by the spatial variations in vegetation type and soil chemical properties and tested this hypothesis in three different vegetation patches (Phragmites australis, Suaeda heteroptera and bare soil) in winter (from November 2010 to April 2011). At diurnal scale, soil respiration all displayed single-peak curves and asymmetric patterns in the three vegetation patches; At seasonal scale, soil respiration all declined steadily until February, and then increased to a peak in next April. But, the magnitude of soil respiration showed significant differences among the three sites. Mean soil respiration rates in winter were 0.60, 0.45 and 0.17 mu mol CO2 m(-2) s(-1) for the Phragmites australis, Suaeda heteroptera and bare soil, respectively. The combined effect of soil temperature and soil moisture accounted for 58-68 % of the seasonal variation of winter soil respiration. The mean soil respiration revealed positive and linear correlations with total N, total N and SOC storages at 0-20 cm depth, and plant biomass among the three sites. We conclude that the patchy distribution of plant biomass and soil chemical properties (total C, total N and SOC) may affect decomposition rate of soil organic matter in winter, thereby leading to spatial variations in soil respiration