Recently, increasing natural infection cases and experimental animal challenge studies demonstrated domestic cats are susceptible to multiple subtypes influenza A virus (IAV) infections.  Notably, some subtype IAV strains could circulate in domestic cats after cross-species transmission and even infected humans, posing a threat to public health.  Host factors related to viral polymerase activity could determine host range of IAV and acidic nuclear phosphoprotein 32 (ANP32) is the most important one among them.  However, role of cat-derived ANP32 on viral polymerase activity and host range of IAV is still unknown.  In the present study, a total of 10 feline ANP32 (feANP32) splice variants (including 5 feANP32A, 3 feANP32B, and 2 feANP32E) were obtained from domestic cats by RT-PCR.  Sequence alignment results demonstrated amino acid deletions and/or insertions occurred among feANP32 variants, but all feANP32 proteins were primarily localized to cell nucleus.  Minigenome replication systems for several representative IAV strains were established and the support ability of feANP32 on IAV polymerase activity was estimated.  The results indicated that most feANP32A and feANP32B splice variants were able to support all the tested IAV strains, though the support activity of a single feANP32 protein on polymerase activity varied among different IAV strains.  In addition, the role of feANP32 in supporting H3N2 canine influenza virus was determined by investigating viral replication in vitro.  Collectively, our study systematically investigated the support activity of feANP32 on IAV, providing a clue for further exploring the mechanism of susceptibility of cats to IAV.

Lycium barbarum residue (LBR), a by-product of L. barbarum processing, is packed with bioactive components and can be potentially utilized as a feed additive in animal husbandry.  However, the fundamental understanding of its effectiveness on livestock animals is still lacking, particularly in ruminants.  To explore the effects of LBR on the growth performance, rumen fermentation parameters, ruminal microbes and metabolites of Tan sheep, sixteen fattening rams (aged 4 mon) were fed a basal diet (CON, n=8) or a basal diet supplemented with 5% LBR (LBR, n=8).  The experiment lasted for 70 d, with 10 d adaptation period and 60 d treatment period.  The results showed that the LBR enhanced the average daily feed intake, average daily gain (P<0.05), and ruminal total volatile fatty acids (P<0.01) while decreasing ammonia-nitrogen concentration and rumen pH value (P<0.05).  Additionally, the LBR improved the relative abundances of Prevotella, Succiniclasticum, Ruminococcus, Coprococcus, Selenomonas, and Butyrivibrio (P<0.05) and reduced the relative abundances of Oscillospira and Succinivibrio (P<0.05).  The LBR altered the ruminal metabolome (P<0.01) by increasing the abundances of ruminal metabolites involved in amino acids (e.g., L-proline, L-phenylalanine, L-lysine, and L-tyrosine), pyrimidine metabolism (e.g., uridine, uracil, and thymidine), and microbial protein synthesis (e.g., xanthine and hypoxanthine).  In conclusion, LBR had positive effects on the growth rate of Tan sheep as well as on rumen fermentation parameters, rumen microbiome and rumen metabolome.

Heat stress is a major constraint to current and future maize production at the global scale.  Male and female reproductive organs both play major roles in increasing seed set under heat stress at flowering, but their relative contributions to seed set are unclear.  In this study, a 2-year field experiment including three sowing dates in each year and 20 inbred lines was conducted.  Seed set, kernel number per ear, and grain yield were all reduced by more than 80% in the third sowing dates compared to the first sowing dates.  Pollen viability, silk emergence ratio, and anthesis–silking interval were the key determinants of seed set under heat stress; and their correlation coefficients were 0.89^***, 0.65^***, and –0.72^***, respectively.  Vapor pressure deficit (VPD) and relative air humidity (RH) both had significant correlations with pollen viability and the silk emergence ratio.  High RH can alleviate the impacts of heat on maize seed set by maintaining high pollen viability and a high silk emergence ratio.  Under a warming climate from 2020 to 2050, VPD will decrease due to the increased RH.  Based on their pollen viability and silk emergence ratios, the 20 genotypes fell into four different groups.  The group with high pollen viability and a high silk emergence ratio performed better under heat stress, and their performance can be further improved by combining the improved flowering pattern traits. 

【Objective】To explore the potential of UAV remote sensing in nitrogen efficiency classification and recognition, a nitrogen efficiency classification method for wheat varieties was constructed, so as to provide the theoretical basis and technical support for nitrogen efficient variety screening.【Method】Six agronomic indicators related to nitrogen efficiency at maturity stage (yield, plant nitrogen accumulation, nitrogen physiological use efficiency, plant dry biomass, total nitrogen uptake of grains, and N harvest index) were used to construct the principal component synthesis value, and K-Means cluster analysis was performed on them. The 121 wheat varieties were divided into three types: high, medium, and low nitrogen efficiency types. A UAV remote sensing platform equipped with a multi-spectral camera was used to obtain remote sensing images of wheat at the jointing, booting and flowering stages, and 34 vegetation indices were extracted to analyze the correlation between vegetation index and nitrogen efficiency comprehensive value. The accuracy of nitrogen efficiency classification models of support vector machine (SVM), random forest (RF), and K-nearest neighbor (KNN) classification methods were compared, and the overall classification accuracy (OA) and Kappa coefficient were used to compare the classification and recognition ability of wheat varieties in different growth periods. Three different feature set screening methods(ReliefF algorithm, Boruta algorithm and RF-RFE algorithm) were used to comprehensively evaluate the optimized feature subsets, and an appropriate classification and recognition method for wheat varieties nitrogen efficiency was established.【Result】With the progress of wheat growth stage, the correlation between vegetation index and the comprehensive value of nitrogen efficiency gradually increased, which reached the highest correlation coefficient at flowering stage (r=0.502). The full feature set of vegetation indices was used to classify the nitrogen efficiency of wheat varieties. For the data of single growth stage, SVM model had the best classification accuracy at flowering stage (OA=77.1%, Kappa=0.591), and the worst classification accuracy at jointing stage (OA=65.6%, Kappa=0.406). In general, the classification accuracy of nitrogen efficiency of varieties with multi-growth stage data fusion was higher than that of single growth stage, among which SVM model with jointing stage + booting stage + flowering stage had the best classification accuracy (OA=80.6%, Kappa=0.669). In order to reduce the number of feature set variables in multi-growth period data fusion, the feature optimization effects of RF-RFE, Boruta and ReliefF algorithms were compared and analyzed. The optimal feature subset based on RF-RFE algorithm had the highest classification accuracy, and its OA and Kappa coefficients were 4.0% and 10.1% higher than those of the full feature set classification model, respectively. Among them, the data fusion of three growth stages had the best classification accuracy (OA=85.4%, Kappa=0.749).【Conclusion】The nitrogen efficiency evaluation method with six nitrogen efficiency indexes - principal component analysis -K-Means were established in this study. The RF-RFE algorithm effectively optimized the number of characteristic subsets of the multi-growth period combination, and obtained high classification accuracy. A nitrogen efficiency classification model of wheat varieties based on the fusion of multi-growth period combination and RF-RFE-SVM technology was established, which provided the theoretical basis and technical support for the rapid and accurate classification and identification of wheat varieties with nitrogen efficiency.

【Objective】To evaluate the drought resistance of synthetic wheat germplasm based on multi-source images collected by unmanned aerial vehicle (UAV) and yield data, explore high-throughput indices for drought resistance evaluation, and identify synthetic wheat germplasm resources with drought resistance. This provides technical support and germplasm materials for accelerating the expansion of drought-resistant genetic resources for wheat and enhancing the level of breeding for dryland wheat.【Method】Eighty synthetic wheat germplasm and the control variety Xin Chun 37 were used as plant materials, which were sown in the field and treated with a water regime of drought stress and irrigation. Multi-source images of test materials during filling stage were collected by multi-spectral and thermal infrared cameras equipped with unmanned aerial vehicle, and the spectral index of each test material was extracted by threshold segmentation. The analyses of Pearson’s correlation and principal component were performed to identify drought resistance-related spectral indices, and the drought resistance of each synthetic wheat germplasm was determined by single index and comprehensive evaluation methods. 【Result】The drought resistance coefficients of 19 spectral indices of 80 synthetic wheat germplasm were calculated based on multisource imagery data obtained from unmanned aerial vehicles. The correlation analysis between the spectral indices and the yield-based drought index (DRI) showed that among the drought resistance coefficients of the 19 spectral indices, OSAVI exhibited the highest correlation with the drought index, while NDVI, CI_re, and NDRE demonstrated relatively strong associations with the drought index. However, the different drought indices showed a high correlation, resulting in redundant information. The drought resistance coefficients of the 19 spectral indices were transformed into three independent comprehensive indicators through principal component analysis, with contribution rates of 59.6%, 12.0% and 9.6%, respectively. The comprehensive drought resistance index (D) for each synthetic wheat germplasm were calculated by aggregating the three independent comprehensive indicators using the weighted membership function method. 6 and 5 synthetic wheat germplasms with strong drought resistance were identified based on DRI and D, respectively. Among them, 2 germplasms (SW004 and SW009) with high drought resistance were detected based on both DRI and D. Furthermore, the drought resistance of the 80 synthetic wheat germplasms was graded based on the drought resistance coefficient of OSAVI, and the grading results were found to be consistent with that based on the D value. Among the six strongly drought-resistant germplasms identified based on the drought resistance coefficient of OSAVI, five of them were also classified as strongly drought-resistant germplasms based on comprehensive drought resistance evaluation.【Conclusion】The spectral indices NDVI, OSAVI, CI_re and NDRE extracted from UAV-based multi-source images, as well as the drought resistance comprehensive evaluation value can be used to assist in the identification of drought resistance of wheat germplasm.

【Objective】Drought is one of the most destructive environmental stresses limiting wheat production. The novel germplasm with excellent drought tolerance as well as their candidate loci were identified and characterized to enrich the genetic basis of drought tolerance and lay a material foundation for wheat genetic improvement in China. 【Method】In this study, the drought tolerance of 198 wheat accessions introduced from International Dry Area Agriculture Research (ICARDA) were investigated at seedling stage through hydroponic method with PEG6000 simulating drought. Drought tolerance index (DTI) was calculated using the shoot fresh weight, root fresh weight, total biomass and root-shoot ratio, respectively. Genome-wide association analysis was performed using 660K SNP array genotyping to obtain the SNP loci and chromosome regions associating with drought tolerance index. Combined with the expression patterns in root and other tissues, the potential candidate genes were identified, and then they were further verified by qRT-PCR approach with the most drought-tolerant accession IR214 and the most drought-sensitive accession IR36 as materials. Finally, the excellent haplotypes of key candidate genes were analyzed. 【Result】Compared to normal control condition, the growth and development of wheat were significantly impaired under drought treatment. There were also significant phenotypic variations among different accessions with all of the four traits displayed normal distribution. The coefficient of variation ranged from 0.363 to 0.760 with genetic diversity from 0.310 to 0.400. Using the weighted membership function value (D value), the drought tolerance of these accessions was evaluated. Results showed that accession IR214 had the highest D value with 0.851, followed by IR92, IR213, IR235, and IR218, which could be considered as the novel excellent drought-tolerance germplasm. Furthermore, through genome-wide association study (GWAS) analysis, a total of 102 loci were significantly associated with the DTI values based on these four traits, with the phenotypic variation explained value (PVE) from 1.07% to 38.70%, of which 60 loci were associated with above-ground fresh weight, 1 locus associated with underground fresh weight, 36 loci associated with biomass and the remaining 5 loci associated with root-shoot ratio. Then, 31 candidate genes were predicated based on genomic annotation information and LD block. Combined with the expression patterns of them in roots and other tissues, 4 candidates displaying differential expression between CK and drought conditions were obtained. Finally, the expression levels of these 4 candidates were further verified by qRT-PCR method with the most drought- tolerant accession IR214 and the most drought-sensitive accession IR36 as materials to obtain two key candidates associating with drought tolerance. Additionally, their haplotype effects were investigated. It was found that the different genotypes of AX-86174509 locus in TraesCS6A02G048600 gene showed significant differences in drought tolerance, which might be considered as a causal locus.【Conclusion】Totally, 102 loci and 2 key candidate genes (TraesCS5B02G053500 and TraesCS6A02G048600) underlying drought tolerance at seedling stage were detected in ICARDA-introduced wheat, and AX-86174509 in TraesCS6A02G048600 was a potential functional locus.

【Objective】Drought is a major environmental factor limiting global wheat production, and breeding drought-tolerant varieties is a key challenge faced by wheat breeders worldwide. Spring wheat, which has a short growth period, plays a vital role for national food security and planting structure, therefore, it is of great importance to identify and select drought tolerance of spring wheat varieties for breeding of high-yielding and drought-tolerant wheat.【Method】In this study, 244 spring wheat varieties (lines) from 10 different regions were used to assess the drought tolerance of spring wheat varieties during the seedling stage, this study used the controlled water content method to impose drought stress during the seedling stage, 5 seedlings with uniform and consistent growth were selected during the trefoil stage. Thirteen seedling stage indicators including maximum root length (MRL), first leaf length (FLL), first leaf width (FLW), coleoptile length (CL), shoot fresh weight (SFW) and root fresh weight (RFW) were measured. Comprehensive evaluation of drought resistance of various spring wheat varieties (lines) was conducted through methods such as using descriptive statistics, membership function, principal component analysis, cluster analysis, and correlation analysis. 【Result】The drought tolerance of spring wheat varieties (lines) exhibits a large variation. The coefficient of variation of the measured traits under drought treatment conditions ranges from 2.1% to 32.9%, while the coefficient of variation of the control group ranges from 1.0% to 29.3%. Compared with the control, the coleoptile length, root dry weight, fresh weight root to shoot ratio, and dry weight root to shoot ratio under drought treatment were all greater than those under the control treatment. The original 13 indexes were summarized into 5 principal components, and the contribution rate reached 79.56%, and the D value of the comprehensive drought resistance coefficient was calculated according to the characteristic vector of each principal component and the drought resistance coefficient of each trait index, then the D value was clustered and analyzed, which could be divided into 5 subgroups. Therefore, the root biomass (underground fresh weight and dry weight) was screened as an effective comprehensive index for the identification of drought resistance at the seedling stage. We conducted correlation analysis between the seedling stage drought index and the agronomic traits of maturity stage showed that the coleoptile length, first leaf length was significantly positively correlated with flag length, plant height, spike length, the number of spike and grain length. Additionally, and the seedling biomass was significantly positively correlated with thousand-grain weight.【Conclusion】Twenty-two highly drought-tolerant varieties were screened, and root biomass (both fresh and dry weight of the underground part) was identified as an effective comprehensive indicator for evaluating seedling stage drought tolerance.

Wheat is the most important cereal crop, and drought is the most significant abiotic stress factor that severely affects wheat growth and development. Plant root system, as a primary organ for crops to acquire water and nutrients, directly determines the efficiency of soil water utilization. In recent years, increasing evidence has shown that plant root system architecture (RSA) plays an important role in plant tolerance to drought stress. This review summarizes the current research progress on the regulation of wheat drought tolerance determined by RSA. First, we present how root tropism especially root gravitropism shapes the RSA, summarize the relevant genes and molecular regulatory mechanism involved in root gravitropic growth, and explain how the root tropism-regulated RSA is implicated in wheat adaptation to drought stress. In addition to root tropic growth, the root development also participates in the RSA formation and the plant adaptability to drought stress. Therefore, this review further summarizes how wheat regulates root development to alter its root system morphology (including increasing root length, modifying lateral root number and root hair density, etc.), thereby enhancing its water acqusition from the soil and its adaption to drought environment. The identified genes involved in wheat root development under drought stress conditions are also systematically summarized. Furthermore, as the underground part of plants, the revelation of RSA has always been a challenging task, which hinders our understanding of the relationship between RSA and plant drought tolerance. Therefore, this review also summarized the available techniques used to analyze the RSA at two- and three-dimension levels. These techniques can measure and analyze wheat root length, density, growth direction, and morphology parameters, laying technical support for an insightful understanding of the relationship between wheat RSA and drought resistance. Finally, we discuss the prospect of the improvement of RSA in breeding wheat drought-resistant varieties, as well as provide an outlook for how to identify genes regulating wheat RSA and pinpoint their regulatory mechanism. In summary, the relationship between wheat RSA and drought resistant is closely associated. The continuous development of sequencing techniques, along with the deepening research on the regulatory mechanism of wheat RSA, will provide new means and strategies for the further breeding of drought-tolerance wheat varieties.