Chronic kidney disease (CKD) is one of the most common diseases occurring in cats. It is characterized by renal fibrosis, which is strongly correlated with impairment of renal function. Since renal biopsy is not performed routinely in clinical practice, the non-invasive method of ultrasonographic shear-wave elastography (SWE) was used to determine renal parenchymal stiffness. Currently, urinary procollagen type III amino-terminal propeptide (uPIIINP) is a renal fibrosis biomarker in humans. Moreover, PIIINP is increasingly applied for identification of fibrosis in various organs in animals.P < 0.001). The E values of the renal cortex and medulla were significantly higher in CKD cats than in HC . The E values, especially of the cortex, showed a significant positive correlation with concentrations of plasma creatinine (P < 0.001), blood urea nitrogen (P < 0.05), while they had a negative correlation with urine specific gravity (P < 0.001) and urine osmolality per plasma osmolality ratio (P < 0.01). The uPIIINP to creatinine ratios (uPIIINP/Cr) were significantly higher in CKD cats than in HC (P < 0.01) and were highly correlated with renal cortical E values (P < 0.001).The Young’s modulus (E) value on SWE, uPIIINP, and renal function were evaluated in 23 CKD cats and 25 healthy cats (HC). The renal cortical E values were significantly higher than those of the renal medulla in both groups (SWE might be an additively useful and non-invasive diagnostic imaging tool to evaluate renal parenchymal stiffness, which correlates with renal functional impairment in CKD cats. Moreover, the uPIIINP/Cr might be a promissing biomarker for adjunctive assessing the renal fibrosis in feline CKD. Chronic kidney disease (CKD) is a common disease in cats and has been increasingly diagnosed annually, particularly in aging cats –5. RenalCats with CKD normally display non-specific signs , 11, andSeveral methods are currently used in human medicine for the determination of renal fibrosis. One of the renal fibrosis biomarkers is urinary procollagen type III amino-terminal propeptide (uPIIINP) , 18. PreIn addition, renal ultrasonographic elastography (USE) is an imaging technique that has been increasingly applied in human medicine , 25. USENa, FEK, FECl, and FEMg) in both groups; and third to determine the relationship between uPIIINP/Cr levels and blood pressure, UPC ratio or renal E values.In veterinary medicine, especially in cats, the use of uPIIINP has not been reported, and reports on the use of USE are limited and only include the use of SE on normal kidneys . TherefoThis clinical, cross-sectional study was approved by the Chulalongkorn University Animal Care and Use Committee (CU-ACUC), Faculty of Veterinary Science, Chulalongkorn University (Protocol number: 1731055). All client-owned cats, including healthy cats (HC) and CKD cats that presented to the Small Animal Teaching Hospital, Faculty of Veterinary Science, Chulalongkorn University from September to December 2017, were considered for inclusion. The cats were considered to be HC if the history, physical examination, routine blood examinations, including complete blood count (CBC) and plasma biochemistry, USG, urinalysis, UPC ratio, abdominal radiographs, and abdominal ultrasound were normal. All cats tested negative for Feline Immunodeficiency Virus (FIV) and Feline Leukemia Virus (FeLV) infection using ELISA Test Kits . The CKD cats included in this study were defined based on a history of either structural or functional abnormalities of the kidneys for more than 3 months (stable CKD patients) and were categorized into IRIS stage 2, 3 and 4 CKD according to the International Renal Interest Society (IRIS)  staging +, K−, Cl− and Mg2+). Urine was collected by voiding or catheterization for measuring the concentrations of creatinine, protein, electrolytes , PIIINP, and osmolality. Indirect blood pressure in all cats was measured three times at the proximal hind leg or distal forelimb and the results were averaged. All ultrasonographic procedures were performed within a visit day.A total of 3 ml of blood was collected from each cat and placed in an EDTA tube for complete blood count (CBC) and a heparinized tube for measurement of creatinine concentration, BUN, alanine aminotransferase (ALT), alkaline phosphatase (ALP), total protein, albumin, osmolality, and electrolytes  were calculated using the formula as previously described [Concentrations of creatinine, BUN, ALT, ALP, total protein, and albumin were determined within an hour of collection by automated analyzer . Frozen plasma and frozen urine samples (− 20 °C) were thawed to measure the osmolality and electrolytes concentration within a few weeks of collection. The plasma and urine osmolality were measured using automatic cryoscopic osmometer , the plasma concentrations of electrolytes were analyzed using automated analyzer  and the urine concentrations of electrolytes were analyzed using automated analyzer . USG was determined within an hour of collection using a refractometer . Measurement of blood pressure was performed using a Doppler blood pressure instrument . The microscopic observation of the urine sediment was performed prior to the measurement of the UPC to exclude the urinary tract infection. The UPC ratio was performed by measuring urine protein concentrations after precipitation with 3% sulphosalicylic acid . Fractioescribed . UrinaryThe ultrasonographic examinations were performed without sedation. The cats were manually restrained and positioned in right and left lateral recumbency for each ipsilateral site of kidneys. Routine preparation for ultrasonographic examination, including hair clipping and acoustic gel coupling, was performed. All cats were screened with B-mode abdominal ultrasound, and the sagittal, dorsal, and transverse planes of the kidneys were recorded using a 9 MHz-bandwidth of a linear transducer . SWE was then performed on the sagittal plane of each kidney. The elastograms were displayed using a dual-screen, consisting of a B-mode image and an SWE color quantitative elastogram overlaid on B-mode. The fixed region of interest (ROI) was adjusted as wide as possible to cover both the renal cortex and renal medulla while attempting to control the high reliability (RLB) map during the procedure. The RLB map indicates the quality of shear wave image in a number percentage. The elasticity results measured from shear wave images with higher RLB percentages are more reliable. The elastogram color scale expressed a red color to represent the hardest tissues, whereas a blue color represented the softest tissues.The E value in kilopascal (kPa) unit was selected for representation of the tissue stiffness . A stiffP-value was less than 0.05.Statistical analyses were performed by GraphPad Prism 7 software . Results were expressed as mean ± standard deviation (SD). Normality distributions were tested with the Shapiro–Wilk test. The average E value results between left and right kidneys in each group were analyzed by paired t-test. The average E values and uPIIINP/Cr levels were compared between groups by the unpaired t-test or Mann Whitney test. Pearson’s correlation coefficient and Spearman’s correlation coefficient were used to investigate the correlations between parameters. Statistical significance was considered if the A total of 25 HC and 23 CKD cats were included in this study. The mean ages of the HC and CKD cats were 4.5 ± 3.4 years  and 9.7 ± 5.1 years , respectively. There were 11 females (4 intact and 7 neutered) and 14 males (6 intact and 8 neutered) in the HC group, and there were 15 females (10 intact and 5 neutered) and 8 males (2 intact and 6 neutered) in the CKD group. The mean bodyweight of HC was 4.1 ± 0.9 kg (range 2.9–5.9 kg), while the mean body weight of CKD cats was 3.7 ± 0.9 kg . The body condition scores (BCS) of both groups were comparable and ranged from a score of 2–4 out of 5 in each group, with a mean of 3.2 ± 0.6 and 3.0 ± 0.4 for HC and CKD cats, respectively. The HC consisted of Domestic shorthair (18), Persian (5), and American shorthair (2), and the CKD cats were Domestic shorthair (22) and Persian (1). The CKD cats were belonging to IRIS stage 2 (82.6%), stage 3 (13.1%) and stage 4 (4.3%).P < 0.01 and Left kidney; P < 0.001).Ultrasonographically, the kidneys in HC had normal shape, contour, echogenicity, and echotexture, with a mean length of 3.6 ± 0.4 and 3.5 ± 0.4 cm for the right and left kidneys, respectively. In contrast, CKD cats had irregular renal outlines, increased echogenicity of the cortex and/or medulla, and decreased corticomedullary demarcation. The CKD cats also had significantly shorter renal length  than the HC . Urine collection was achieved in 39 cats, which were 19 HC, and 20 CKD cats. The functional renal parameters of both groups, including plasma creatinine concentration, BUN, USG, UPC ratio, Uosm/Posm ratio, FENa, FEK, FECl, and FEMg, are summarized in Table P < 0.001), while USG and Uosm/Posm ratio of CKD cats were significantly lower than those of HC (P < 0.001). All FE of electrolytes, except FENa, were significantly higher in CKD cats than in HC (P < 0.001).The average blood pressure of HC group was significantly lower than that of CKD cats . Moreover, the average E values of the renal cortex and medulla of CKD cats were significantly higher than those of HC  , BUN (P < 0.05), and FECl (P < 0.01), while it showed a negative correlation with USG (P < 0.001) and Uosm/Posm (P < 0.01)   was found between uPIIINP/Cr levels and average renal cortical E values  has been reported to be a highly sensitive parameter for the evaluation of tubular impairment in dogs with advanced CKD [Mg may be a useful marker of the severity of tubular cell damage, as it has been positively correlated with the stage of tubulointerstitial fibrosis in humans [The results revealed that renal cortical E values had significant positive correlations with plasma creatinine concentrations, BUN, and FEn et al.  in humannced CKD . Addition humans .Additionally, our findings indicate that the renal cortical E value was predominantly correlated with renal functions compared with that of the renal medullary E value. The reason for this could be that the renal cortex contains the glomeruli, which are responsible for plasma filtration , as welle vary depending on several exogenous and endogenous factors especially diet and hydration status [However, the urine osmolality and FEn status . In thisThe uPIIINP/Cr ratio, which was strongly correlated with the progression of interstitial fibrosis in kidney biopsies from human patients , 18, 19,Urinary transforming growth factor beta 1 (TGF-β1) is considered the most popular mediator for detecting the severity of renal fibrosis in cats . HoweverIn this study, a statistically positive and moderate correlation was found between the uPIIINP/Cr level and the average renal cortical E values, suggesting that the renal cortical E value might be one of the indicators to assist in the evaluation of renal fibrosis in CKD cats.In veterinary medicine, information concerning renal function parameters and renal elasticity in cats has not been reported. Moreover, the relationship between the uPIIINP/Cr level and renal elasticity in CKD cats has not been determined. This is the first report relating the renal elasticity, as determined with SWE, to the uPIIINP/Cr in CKD cats. This information would be useful for clinical practitioners and would be of interest to researchers in further study.e results in this study. A further limitation is that we could not collect urine samples from all cats.The major limitation of this study is that we did not perform a renal histopathological examination for comparison with the renal elasticity determined by USE and the uPIIINP/Cr results, due to the invasive nature of the biopsy. Therefore, further studies should be considered. The second limitation is that the number of healthy cats included in the study was not sufficient to evaluate the influence of demographic variables on SWE. Additionally, the HC group and CKD group were not age-matched. Further study into the effect of age and BCS on the renal elasticity would provide more reliable information. The third limitation is that other uncontrollable factors of client-owned cats, such as different types of commercial foods, might influence the Uosm/Posm ratio and FECl had a positive correlation with renal elasticity, while USG and Uosm/Posm ratio revealed a negative correlation with renal elasticity. The renal cortex in both groups had lower elasticity than the renal medulla, and the kidneys of CKD cats were stiffer than those of HC in this study. Moreover, the renal cortical E values were significantly correlated to the uPIIINP/Cr levels. The results suggest that renal SWE might be an easy-to-use diagnostic tool, which may be applied as adjunct for the detection and monitor of feline CKD. Furthermore, the uPIIINP/Cr levels are higher in CKD cats. Therefore, the uPIIINP/Cr might also be a promising biomarker for adjunctive assessing the renal fibrosis in CKD cats. However, further studies are needed to elucidate the clinical value of USE in terms of evaluation and monitoring of feline CKD and to construct a correlation between uPIIINP/Cr and degree of renal fibrosis from histopathology in cats.USE can be used an additive diagnostic imaging method for the evaluation and monitoring of feline CKD. Plasma creatinine, BUN, and FE


Numerous studies have analyzed associations between apparent diffusion coefficient (ADC) and histopathological features such as Ki-67 proliferation index in breast cancer (BC), with mixed results. The purpose of this study was to perform a multicenter analysis to determine relationships between ADC and expression of Ki-67 and tumor grade in BC.U test where the p values are adjusted for multiple testing (Bonferroni correction). The association between ADC and Ki-67 values was calculated by Spearman’s rank correlation coefficient. Sensitivity, specificity, negative and positive predictive values, accuracy, and AUC were calculated for the diagnostic procedures. ADC thresholds were chosen to maximize the Youden index.For this study, data from six centers were acquired. The sample comprises 870 patients . In every case, breast magnetic resonance imaging with diffusion-weighted imaging was performed. The comparison of ADC values in groups was performed by Mann-Whitney − 3 mm2 s− 1. ROC analysis showed that it is impossible to differentiate high/moderate grade tumors from grade 1 lesions using ADC values. Youden index identified a threshold ADC value of 1.03 with a sensitivity of 56.2% and specificity of 67.9%. The positive predictive value was 18.2%, and the negative predictive value was 92.4%. The level of the Ki-67 proliferation index was available for 845 patients. The mean value was 12.33 ± 21.77%. ADC correlated with weak statistical significant with expression of Ki-67 . ROC analysis was performed to distinguish tumors with high proliferative potential from tumors with low expression of Ki-67 using ADC values. Youden index identified a threshold ADC value of 0.91 .Overall, data of 870 patients were acquired for this study. The mean ADC value of the tumors was 0.98 ± 0.22 × 10ADC cannot be used as a surrogate marker for proliferation activity and/or for tumor grade in breast cancer. However, ADC values of the subgroups overlapped significantly  and high Ki-67 expression (≥ 25%). Tumors with low expression of Ki-67  differed from those with low levels of Ki-67 (< 25%), the calculated specificity and sensitivity were too low. This applied also for several alternative thresholds of Ki-67 expression ranging from 10% to 50%. Similar results were also observed for distinguishing low-grade and intermediate/high-grade tumors. Statistical analysis identified that grade 1 lesions had higher ADC values than grades 2 and 3 tumors. However, the ROC analysis showed that a possible use of ADC for discrimination of tumor grade in BC has very low specificity and sensitivity. Furthermore, we found that DCIS had statistically significant higher ADC values than IDC and ILC. However, ADC values also overlapped also overlapped distinctly in these subtypes. Therefore, use of ADC does not provide specific information regarding tumor biology in BC that can be used reliably in clinical practice.r = 0.035, p = 0.892) reported by Onishi et al. [The present study is the largest to date on this topic, to our knowledge. However, it has some limitations. The involved patients were investigated with use of different MRI equipment with different technical parameters, such as field strength, DWI sequences, and b-values. This may broaden the range of ADC values in the study and may have influenced our results. Furthermore, the patient samples consisted predominantly of only three tumor subgroups, namely DCIS, IDC, and ILC. Our study identified that associations between ADC and Ki-67 were different in several subtypes of BC. Moreover, the calculated correlation coefficients for IDC, DCIS, and ILC in our study differed significantly from those for mucinous carcinoma (i et al. . PresumaOur multicenter study shows that ADC cannot be used as a reliable surrogate marker for proliferative activity and/or for tumor grade in BC.


Panax quinquefolius L.) is severely limited by the replant disorders in China. Crop rotation with maize might reduce the replant problems, but little information is available on the effect of maize rotation on soil cultivated with ginseng. In this study, we analyzed nutrients, phenolic acids, and microbial communities in soils from the fields with continuous maize, mono-culture ginseng, and 1-, 3-, and 5-year maize rotation after ginseng. Pot experiments were also conducted to evaluate the performance of replanting ginseng in these soils. The results showed that Mn, Cu, and 5 phenolic acids in ginseng-cultivated soil were significantly decreased by maize rotation. A 5-year maize rotation significantly increased the relative abundance of beneficial soil bacteria, such as Arthrobacter, rather than decreasing the abundances of potential pathogenic genera. Clustering analysis revealed that the physicochemical properties and microbial communities of 3- and 5-year maize rotation soil were more similar to CM than to G soil. The biomass of replanted ginseng root was improved, and root disease was reduced over 3 years of maize rotation. Overall, the results showed that at least a 3-year maize rotation is needed to overcome the replant failure of American ginseng.The production of American ginseng ( Panax quinquefolius L.) is known for its pharmacological functions, such as anti-oxidation, anti-diabetes, and anti-cancer activities, as well as enhancement of the central nervous system, and it has been consumed in China for more than 300 years4. Originating in the eastern part of North America1, American ginseng was introduced to China in the 1980s. At present, ginseng planting area covers over 10,000 ha in northern China. American ginseng is a perennial plant requiring shade, which usually grows in fields for four years with high inputs  before harvesting. In crop fields, this plant’s growth is hampered by replanting failure, which reduces the root yield dramatically due to replant disease. Consequently, farmers never plant ginseng in the same field due to the crop failure concern; thus, the fields used by farmers for ginseng production have been decreasing dramatically over time. For example, the Huairou District of Beijing was a major ginseng-growing region in China with an area of 700 ha in the 2000s but currently a ginseng planting area less than 2 ha. It has been reported that ginseng replanting failure and diseases have also occurred in North America5. It is evident that replant disorders have seriously restricted sustainable American ginseng development.American ginseng  reported a remarkable decrease in soil pH and exchangeable calcium, ammonium, and total organic carbon with time in soils with Panax ginseng growth8. He et al. (2009) reported that autotoxic phenolic acids in surface soil of fields cultivated with American ginseng inhibited the growth of the next ginseng crop9. The biotic factors often refer to the change in microbial communities or the accumulation of soilborne pathogens after years of monoculture11. Most fungal pathogens of American ginseng root rot (such as Fusarium spp. and Cylindrocarpon spp.) can survive in soil for many years12. Dong et al. (2016) reported that in soils cropped with three years of notoginseng, which belongs to the same genus as American ginseng and suffers from replant failure, fungal diversity was significantly decreased, while the relative abundance of pathogens, such as Fusarium oxysporum, was significantly increased, which were highly correlated with the notoginseng death rate13.Replant failure in some crops or fruit trees is attributed to abiotic and biotic factors15. Studies have shown that crop rotation can increase the nutrient availability and soil organic matter18. Furthermore, this approach may accelerate the degradation of autotoxic chemicals, thereby weakening autotoxicity19. Additionally, rotation with nonhost crops can alter the microbial community structure or break the persistence of pathogens that build up in the monoculture of cucumber and grass, among others21. However, only a portion of microorganisms could be detected in previous studies using culture-dependent or molecular analyses, such DGGE and q-PCR, thereby precluding an understanding of the whole picture of soil microbes24. Recently, the development of high-throughput sequencing has helped to fully elucidate the soil microorganisms and better understand their relationship with plant disease; however, only a small number of studies to date have been reported on Rehmannia glutinosa25, Panax notoginseng13, Pseudostellaria heterophylla26, vanilla27, and cucumber20, among others. In a study of replanted Panax ginseng, Lee et al. (2015) screened out several suitable rotation crops, such as perilla and potato, from 18 plant species, which could reduce root rot disease and promote ginseng growth28. However, the mechanism underlying soil improvement by rotation is lacking. To date, data concerning the suitable rotation crop for American ginseng have been lacking, as well as the number of years of planting required to overcome the replant failure of American ginseng.Crop rotation, a traditional effective method for improving soil quality, alleviating replant diseases, and boosting yields, has been reported in variety of cropsAfter American ginseng harvesting, spring maize or wheat is usually planted as the following crop in ginseng-growing regions in China. Maize, in particular, is the major rotational crop cultivated broadly as a food, feed and forage crop. However, it is not clear whether the maize rotation could reduce the replant failure in soils cultivated with American ginseng. To help farmers achieve successful replanting of American ginseng, we conducted this study with the objectives of exploring the effect of maize rotations on the chemical and biological properties of soils in which American ginseng were grown and identifying the appropriate intervals before American ginseng replanting. The details of the study included (1) the evaluation of soil nutrients, phenolic acids, fungal and bacterial communities, and relative abundances of pathogenic fungi in ginseng soils, as affected by maize rotations, and (2) investigation of the growth and occurrence of root disease in replanted American ginseng in soils immediately after ginseng cultivation or after maize rotation in different years. Our results will help to gain a better understanding of the physicochemical characteristics of the rotation crop and the establishment of microbial communities in soil and provide sustainable cultivation solutions for American ginseng-growing regions.Figure P < 0.05), including p-hydroxybenzoic, syringic, ferulic, salicylic, and p-coumaric acids   Fig. . No obvi05) Fig. . Cluster05) Fig. .Figure 2In all 15 soil samples, 28013–64010 internal transcribed spacer (ITS) final tags were obtained and grouped into 814–1316 fungal operational taxonomic units (OTUs), whereas 37699–58512 16S final tags were obtained and grouped into 2932–3712 bacterial OTUs. The Good’s coverage estimates for all soil samples were >0.970, representing good sequencing depth. The fungal OTUs were assigned into 8 phyla, 20 classes, 60 orders, 109 families, or 264 genera, while the bacterial OTUs were assigned into 40 phyla, 88 classes, 151 orders, 272 families, or 389 genera.Mortierella, Fusarium, Humicola, Pseudallescheria, Cryptococcus, Guehomyces, Monographella, Wardomyces, Schizothecium and Nectria, among others . However, Fusarium and Schizothecium were reduced, while Guehomyces and Wardomyces were increased, in G compared with CM soil. Additionally, no significant differences were observed among all five soil groups in the relative abundances of fungal functional groups, including potential pathogenic genera, such as Alternaria and Cylindrocarpon, antagonistic genera, such as Penicillium and Trichoderma, and mycorrhizae, such as Glomus , while Nitrospira and Sphingobium were increased significantly . No significant difference was observed in the relative abundance of other nitrifying bacteria, such as Nitrolancea, Nitrosococcus and Nitrosomonas, among all of the soil treatments . Both values tended to increase to similar levels to those in CM after 5-year maize rotations  in G and CM was similar but significantly lower than in G + 1 M (P < 0.05). The ratio of Fusarium spp. (TRF of 148 bp) in G + 5 M and CM was similar but significantly higher than other groups (P < 0.05). No differences in the ratio of F. solani (TRF of 130 bp), C. destructans (TRF of 132 bp), B. cinerea (TRF of 143 bp), and R. solani (TRF of 325 bp) were observed among the groups , while other treatments fell between these values .We further performed a Pearson’s correlation to evaluate the relationship between the replanted ginseng root disease severity and the dominant microbial genera. Among the top 20 abundant fungal and bacterial genera, Pearson’s correlation coefficients showed that the replanted ginseng root disease severity index was not correlated with the relative abundances of the top 20 fungal genera  were found to be rich in such soil nutrients as AN, AP, AK, available Mn, Cu, and Fe. We speculated that the enrichment of these soil available nutrients resulted from the higher chemical fertilizer inputs and the application of massive amounts of organic fertilizer , the growth of replanting ginseng cultivated in G + 1 M soil was still not as good as other soils, suggesting that soil phenolic acids were not restrictive for replanting American ginseng.Higher contents of phenolic acids, such as Fusarium, Alternaria, and Cylindrocarpon, did not change significantly among all of the soil groups. Moreover, the relative abundances of the root pathogens Fusarium solani, Cylindrocarpon destructans and Rhizoctonia solani showed a similar trend based on T-RFLP analysis. However, some soil bacteria, such as the Arthrobacter, Gaiella, Microvirga, Skermanella, Roseiflexus, and Candidatus Entotheonella genera, were increased by maize rotation. Among these bacteria, previous studies have shown that some genera are beneficial. Li et al. (2017) reported that some species of Arthrobacter can degrade allelochemicals32. Ardley et al. (2012) reported that Microvirga can fix nitrogen33, and Zhao et al. (2017) reported that several Microvirga isolates show strong resistance to plant pathogens34. Our correlation regression analysis further demonstrated that the disease severity of replanted ginseng root was significantly related to the relative abundance of these beneficial bacteria rather than pathogenic fungi. Previous studies reported that even though virulent pathogens were present in healthy soils, the occurrence of soil-borne plant disease was low because of the interactions and restrictions existing among soil phytopathogenic, beneficial, and commensal microbes36. Zhao et al. (2017) found that maize cultivation could enhance the soil microenvironment for the growth of beneficial microorganisms rather than F. oxysporum, to improve soil functions and overcome the replant problem of P. notoginseng37, consistent with our results.Soil microorganisms play an important role in the soil environment. Our sequencing results showed that ginseng potential pathogenic fungal genera, such as et al. (2016) reported that the death rate of notoginseng and the soil fungal diversity were significantly negatively correlated13. Xiong et al. (2017) reported that the suppressive soil of vanilla Fusarium wilt disease harbored a higher fungal diversity but a lower bacterial diversity than the conducive soil, and the microbial diversity indices were correlated with the soil pH27. Birgander et al. (2014) reported that soil fertility affected fungal communities along a grassland gradient, and pH was one of the main factors controlling the microbial communities38. Wu et al. (2015) reported that a phenolic acid mixture could promote mycelial growth, sporulation, and toxin production of pathogenic Fusarium oxysporum while inhibiting the growth of beneficial Pseudomonas sp., suggesting that phenolic acids have varying effects on soil fungi39.Our results implied that the root disease of American ginseng was related to soil fungal diversity, which was likely affected by soil physicochemical properties. In concert with our findings, Dong 22. Specifically, the initial soil microbial communities are shaped by the preceding crops, but they become more specific to subsequent crops in a rotation system40. The establishment of the soil microbiota for a plant is a dynamic process. It takes time for the soil microbial community to shift from one host to another. Our findings suggested that three or more years are needed for the microbial community in ginseng cultivated soil to become similar to maize soil. Combining the change pattern in soil physical and chemical properties and the microbial communities, we suggest that to eliminate the inhibitory factors of G soil, the suitable time for replanting ginseng by maize rotation is likely more than 3 years. Our findings provide useful information for the establishment of the American ginseng-maize-American ginseng rotation system.Our pot experiment results indicate that maize rotation over 3 years may improve growth of replanted American ginseng. American ginseng growth in the soil with three or five years of maize rotations was not significantly different than that in CM soil. The cluster analysis of soil nutrients, autotoxic phenolic acids, and fungal and bacterial communities showed that G + 3 M, G + 5 M, and CM soil were mostly grouped together. Plants can shape the specific microbial community structure in the soil environmentArthrobacter, and the degradation of phenolic acids, such as p-hydroxybenzoic and ferulic acids, but not to the soil nutrients and abundance of pathogenic fungi. The maize rotation substantially alleviated the replant disorders of ginseng, and at least three years of maize rotation provided an effective break period before ginseng replanting. Our research findings provide new insights to sustain ginseng productivities that will benefit farmers in ginseng production regions. Future studies are needed to explore the interactions among soil nutrients, phenolic acids, and soil microbes to improve our understanding of the complicated ginseng replant problems.Our study demonstrates that maize rotation can change the physicochemical and biological properties of American ginseng cultivated soil, including soil nutrients, phenolic acid contents, and soil fungal and bacterial communities. The improvement of soil by maize rotation was mainly related to the alteration of the soil microbial community structure, such as an increased relative abundance of beneficial bacteria −1 and were kept fallow during winter. Afterwards, the fields were grown with American ginseng for four years continuously, and then the fields were again used for maize crops (Table Field investigation was conducted in loam soil (mollic gleysols) in Huairou District, Beijing . Depending on the years with maize rotations after ginseng cultivation, we selected the following groups for soil samplings: continuous maize (CM), ginseng (G), ginseng plus 1-year maize (G + 1 M), ginseng plus 3-year maize (G + 3 M), and ginseng plus 5-year maize (G + 5 M). Originally, these fields were used for annual spring maize with a production of 6.0–6.8 t haps Table . Each gret al.41 and the Chinese Ministry of Environmental Protection42. Available nitrogen (AN), available phosphorus (AP), and available potassium (AK) were determined by chemical analytical methods, as described by Liu et al.43, Murphy et al.44, and Hanway et al.45. Soil organic matter (SOM) was assayed according to the Walkley-Black method46. Soil pH was determined at a soil:water ratio of 1:2 using a combination glass electrode. The exchangeable calcium (Ca), magnesium (Mg), and available sulfur (S), boron (B), iron (Fe), manganese (Mn), copper (Cu), and zinc (Zn) were extracted and determined using an inductively coupled plasma optical emission spectrometer  according to Chinese Agricultural Standards47. Soil moisture content was determined after oven-drying at 105 °C for 6 h.Approximately 100 g of soil samples was sieved through a 20-mesh sieve (0.84-mm opening diameter) to determine the soil-available nutrients and through a 100-mesh sieve (0.15-mm opening diameter) to determine the total nutrients and soil organic matter (SOM). The total nitrogen (TN) and total phosphorus (TP) were analyzed following the procedure of Fawcett p-hydroxybenzoic acid, vanillic acid, syringic acid, vanillin, p-coumaric acid, ferulic acid, and salicylic acid, were extracted from the soil after passing through a 0.3-mm mesh and assessed by high-performance liquid chromatography , following the method of Zhang et al.48. These compounds were separated by a YMC-Pack ODS-A column  and identified and quantified by comparison to their corresponding standards   Table .49. The bacterial universal V3-V4 region of the 16S rRNA gene was amplified with the primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′ -GGACTACHVGGGTWTCTAAT-3′)50. PCR volumes were 50 μL, containing 30 ng template DNA, 0.3 μL DNA polymerase , 2 μL of 10 μM of each primer, 5 μL 10× Pyrobest Buffer, and 4 μL 2.50 mM dNTP. PCR amplification was carried out using the following protocol: 95 °C for 5 min, followed by 35 cycles  or 28 cycles  at 95 °C for 45 s, annealing at 55 °C for 50 s, 72 °C for 45 s and a final extension at 72 °C for 10 min. Three PCR products per sample were pooled, purified, and quantified by real-time PCR. Parallel-tagged sequencing was performed on an Illumina MiSeq platform  according to standard protocols52. Specifically, split reads were merged using FLASH V1.2.11 and sorted into each sample by the unique barcodes using QIIME (V1.7.0). The raw data were first screened, and sequences were removed by considering whether their quality scores <20 contained ambiguous bases or did not exactly match the primer sequences and barcode tags. Raw tags with <200 bp were removed using Mothur (V1.37.0). Chimeras were removed with USEARCH (V8.1.1861) against the Gold and UNITE reference database. The high-quality sequences were clustered into operational taxonomic units (OTUs) at a threshold of 97% similarity using the UPARSE pipeline. Singletons that occur only once in the entire data set were removed from subsequent analyses to reduce overprediction of rare OTUs. The representative OTU sequences were aligned and annotated using the Ribosomal Database Project (RDP) classifier (V14). Alpha diversities such as the observed species and Shannon diversity index were analyzed using QIIME (V1.7.0).The microbial community was analyzed following a procedure of DNA extraction, PCR amplification and Illumina MiSeq sequencing. DNA was extracted from 0.4 g of soil sample using the MOBIO PowerSoil® DNA Isolation Kit . The fungal universal ITS1 region was amplified with the primers ITS1-F (5′-CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2 (5′-TGCGTTCTTCATCGATGC-3′)54. PCR products were digested with HinfI or HaeIII according to Dickie et al.55. Digested PCR products were electrophoresed on an automated sequencer  and then analyzed using Peak scanner software 1.0 . Ten species of pathogenic fungi were identified through comparison of the T-RFLP patterns between soil samples and a database of pure hypha (Table HaeIII digestion and HEX-labeled primer (ITS1F), while the ratio of R. solani (325 bp) was calculated from the results with HinfI and HEX  and ITS4 labeled with FAM (5-FAM [5-Carboxyfluorescein]) according to previous methodsha Table . The ratEX Table .A pot experiment was conducted with the soils from the fields of CM, G, G + 1 M, G + 3 M, and G + 5 M. The soils from the triplicate field plots of each group were mixed thoroughly, and approximately 25 kg of the soil was added to one clay pot . There were three replicates for each treatment. All the pots were placed randomly without fertilizer and pesticide amendments. Fifty American ginseng seeds were sown in each pot. The pot experiment was conducted with regular irrigation and artificial shade with a double-sunshade cloth to reduce solar radiation to an optimal 15% to 25% of full sunlight. The weeds were removed manually once a week. The seedling emergence rate was examined 60 days after sowing. All plants were harvested 5 months after sowing. The relative survival rate of seedlings, dry weight of individual roots, root disease severity index, and number of lateral roots were measured.P value < 0.05. Soil nutrient and phenolic acid data were further analyzed by cluster analysis using the between-group linkage method and squared Euclidean distance measure. Clustering analyses of soil microbes were calculated with unweighted UniFrac distance matrices, with the arithmetic mean (UPGMA) clustering procedure to establish the dendrogram using R software (Version 2.15.3) based on the OTU information from each sample. Pearson’s correlation coefficient was used to evaluate the relationships between the replanted ginseng root disease severity and top 20 fungal or bacterial genera. The root disease severity observed in pot experiment was assessed by the presence of surface lesions, which were quantified from 0 to 4, where 0 = no lesions, 1 ≤ 10%, 2 = 10–33%; 3 = 33–67% and 4 ≥ 67% of the total surface area with rot.All data were analyzed using analysis of variance (ANOVA) with SPSS19.0 . Differences between groups were compared by Fisher’s least significant difference test. One-way ANOVA was performed with a 56. Multilinear regression analysis was conducted using SPSS19.0, and all data were transformed in scientific notation.Similarity analysis of the growth index of American ginseng among groups was analyzed using non-metric multi-dimensional scaling (MDS) based on data Log(X + 1) transformation. Following 100 random restarts, the ordinations in our analyses were computed with the best final configuration, based on the number of times that a minimum stress was obtained over the course of the random restartsSupplementary table


Pyrus pyrifolia) after bagging and bag removal. We investigated transcriptional and metabolic changes and gene-metabolite correlation networks. Correlation tests of anthocyanin content and transcriptional changes revealed that 1,530 transcripts were strongly correlated with 15 anthocyanin derivatives , with the top 130 transcripts categorized as being associated with flavonoid metabolism, transcriptional regulation, and light signaling. The connection network revealed a new photosensitive transcription factor, PybZIPa, that might play an important role during light-induced anthocyanin accumulation. The overexpression of PybZIPa promoted anthocyanin accumulation in pear and strawberry fruit as well as tobacco leaves. Dual luciferase and Y1H assays further verified that PybZIPa directly activated the expression of PyUFGT by binding to tandem G-box motifs in the promoter, which was key to differential anthocyanin accumulation in debagged pear skin, and the number of G-box motifs affected the transcriptional activation of PyUFGT by PybZIPa. The results indicate that the light-induced anthocyanin biosynthesis regulatory mechanism in pear differs from that described in previous reports suggesting that a bZIP family member co-regulates anthocyanin biosynthesis with other transcription factors in apple and Arabidopsis. It was found that, in response to light, PybZIPa promoted anthocyanin biosynthesis by regulating important transcription factors  as well as structural genes (PyUFGT) via binding to G-boxes within promoters. This activation was amplified by the self-binding of PybZIPa to activate its own promoter. Overall, we demonstrate the utility of a multiomics integrative approach for discovering new functional genes and pathways underlying light-induced anthocyanin biosynthesis.To gain insight into how anthocyanin biosynthesis is controlled by light in fruit, transcriptome and metabolome analyses were performed in the Chinese sand pear cultivar “Mantianhong” ( Litchi chinensis)1, grape2, waxberry (Myrica rubra)3, huckleberry (Vaccinium spp.)4, raspberry (Rubus idaeus)5, and many other species. In Rosaceae plants such as strawberry6, peach8, pear11, and apple14, the effect of light on anthocyanin biosynthesis is significant. Researchers have made progress in exploring the mechanism of the activation of light-induced anthocyanin biosynthesis. In Arabidopsis, Constitutively photomorphogenic 1 (COP1) is a “central regulator” of light signal transduction pathways that repress plant light-induced morphogenesis in the dark and interacts with upstream light receptor proteins  and downstream target proteins (ubiquitin/26S proteasome system)17. The ubiquitination of COP1 is important during photomorphogenesis, including anthocyanin accumulation. Among its downstream target proteins/transcription factors, the transcript abundance of LONG HYPOCOTYL 5  is directly related to photosensitive morphology, UV-B resistance and anthocyanin biosynthesis19. Recently, it has been shown that HY5 interacts with B-Box proteins (BBXs) to regulate anthocyanin biosynthesis. The relationships between HY5 and BBXs are diverse, and they both transcriptionally regulate each other and form HY5-BBX complexes to modulate activity23.Red-skinned pear germplasm resources are relatively rare, yet the red skin trait has high commercial and breeding value. Asian red pear coloration is greatly affected by environmental factors, such as light and temperature. The environmental influence results in unstable coloration, which affects the value of red pears. Red skin in pears is the result of anthocyanin accumulation, as determined by the biosynthesis levels and distribution of anthocyanin. Anthocyanins among the most studied plant compounds, and their metabolic mechanisms have been widely reported. Light is an important environmental factor affecting anthocyanin biosynthesis according to the photoperiod, light intensity and light quality. Light effects on anthocyanin levels have been reported in litchi  can provide an effective strategy for identifying potential genes regulating light-induced anthocyanin biosynthesis in red Chinese sand pear.Numerous metabolic pathways of plants are influenced by light;ANS, DFR, UFGT) and some regulatory transcription factors  involved46. However, fewer studies have shown the differential expression of genes or metabolites during light-affected anthocyanin biosynthesis. Here, we explored the regulatory pathways of light-induced anthocyanin biosynthesis in pear at the transcriptional and metabolic levels. We focused on the differentially accumulated anthocyanin metabolites in fruit and their related regulatory genes between the time of bagging and bag removal. Connection networks were generated based on correlation analyses between anthocyanin metabolites/derivatives and transcripts associated with the anthocyanin metabolic pathway. Our findings provide new information about light-induced anthocyanin biosynthesis and its regulatory mechanisms in pear and highlight the significance of an integrated multiomics approach for understanding plant physiological processes.The anthocyanin biosynthesis mechanism of pear has been described, including the genes encoding the biosynthetic enzymes . The debagged and bagged samples from different stages were well distinguished and well clustered by the model. There was a difference between each group ) appeared yellow-white without subsequent debagging and light re-exposure. The fruit after bag removal showed red coloration, and this was more obvious in the fruit skin after light re-exposure in the debagged group Fig. . Metaboloup Fig. , and theoup Fig. , which coup Fig. . Among tWe found that 3,390, 3,075, and 2,625 genes were significantly upregulated, while 2,654, 2,537, and 2,046 genes (new transcripts included) were significantly downregulated in B1/A1, B2/A2, and B3/A3, with 1,658 DEGs being common to all three comparisons Fig. . HierarcCOP1) and other light-responsive genes (SPA1 and UVR8) were also included.The common DEGs were involved in flavonoid and phenylalanine metabolic pathways and comprised light response-related genes. These genes included 11 anthocyanin biosynthesis genes and several light response center genes Fig. , two thaP-value < 0.05) with 15 metabolites. Among the biosynthesis genes, the gene with the highest correlation coefficient (Pearson r = 0.999) between its expression pattern and anthocyanin content was Pbr003128.1, which encodes a F3′H, followed by Pbr003752.1 and Pbr001279.1, which encode a Chalcone isomerase and UFGT, respectively, with correlation coefficients of 0.978 and 0.966. In addition, members of the light response complex  exhibited expression levels that correlated well with anthocyanin biosynthesis. This further supported the role of light in anthocyanin regulation. Ten transcripts were selected for each anthocyanin derivative  (Table COP1) and other light-responsive genes . The top 130 transcripts for the 15 anthocyanin derivatives were subjected to KEGG pathway enrichment analysis, showing that phenylalanine metabolism; flavonoid biosynthesis; porphyrin, and chlorophyll metabolism; metabolic pathways; and Fructose and mannose metabolism were differentially enriched  Table  and visus) Table . The methed Fig. .Fig. 3InbZIP gene, PybZIPa). This gene was highly correlated with Cy in group I, and its expression level in the debagged groups was significantly higher than that in the bagged groups (with a log2 fold-change between the debagged and bagged groups of nearly 5). There are 89 bZIP genes in pear (according to the family assignment rules from PlantTFDB) and 74 bZIP genes were expressed in pear skin after bag removal, with the PybZIPa expression level being much higher than those of other bZIP homologous genes in the debagged groups  annotated as PyHY5 (Long Hypocotyl 5) were located on Chr15  were transferred to Nicotiana benthamiana by Agrobacterium-mediated transformation. The green fluorescence signal from PybZIPa-GFP in epidermal cells was detected specifically in the nucleus. However, the signal from the empty GFP vector was detected throughout the cell -type transcription factor and was considered an anthocyanin-associated ups Fig. . PybZIPar15 Fig. . To deteell Fig. . These rArabidopsis thaliana and other Rosaceae fruits showed that PybZIPa differed from the annotated PyHY5 in pear  were analyzed   Table , suggestPybZIPa in pear, strawberry fruit, and tobacco leaves increased pigmentation in these tissues ), while there was no significant increase in PyF3′H expression, which indicated that there was no direct regulatory relationship between PybZIPa and PyF3′H. Therefore, we inferred that PyUFGT was most likely of these genes to be regulated by PybZIPa.The overexpression of ues Fig. . TobaccoIPa Fig. . PyUFGT PyUFGT by PybZIPa, the PyUFGT promoter and other coexpressed genes were analyzed by using the PlantCARE database. The results indicated that the PyUFGT promoter contained tandem repeats of G-boxes   Table ; therefoter Fig. . To veriifs Fig. . At the PybZIPa and anthocyanin biosynthesis-related transcription factors , there was at least one G-box motif present in their promoters. PybZIPa showed different degrees of activation of these promoters in the dual-luciferase assay  and undergoes self-binding (PybZIPa activates its own promoter) to amplify the activation effect.Moreover, yeast one-hybrid screens showed that ter Fig. . This reWe identified 89, 94, and 71 differentially accumulated metabolites in B1/A1, B2/A2, and B3/A3, respectively. According to the abundance and composition of the differentially accumulated metabolites, intermediate product accumulation occurred at the early stage (B1/A1) of light-induced anthocyanin accumulation, after which an increase in anthocyanin biosynthesis by the structural genes and regulatory genes involved in anthocyanin biosynthesis occurred in the later stages (B2/A2 and B3/A3). The KEGG pathway analysis results for the differentially accumulated metabolites showed similar results; the TCA cycle, starch and sucrose metabolism, and the biosynthesis of phenylpropanoids for intermediate product accumulation were significantly enriched in B1/A1, while the phenylpropanoid and flavonoid metabolism pathways were significantly enriched during the extremely high anthocyanin biosynthesis stage (B3/A3) in particular Fig. .PyCOP1, PyDET1, PyPIF and PyHY5 are responsive to light after bag removal in a light-sensitive pear variety. Additionally, the expression of the anthocyanin-related biosynthesis genes PyDFR, PyANS, and PyUFGT and the transcription factor genes PyMYB10, PybHLH33, and PyWD40 show a positive correlation with light-induced anthocyanin accumulation50. The expression patterns and GO categories of the above genes were analyzed in the current study ” category; “cell”, “cell part” and “membrane” in the “Cellular Component (CC)” category; and “binding”, “catalytic activity” and “transporter activity” in the “Molecular Function (MF)” category Fig. . These Gudy Fig. . They weudy Fig. , and theudy Fig. .HY5, a typical bZIP transcription factor, is a photoresponsive gene that has been reported to regulate anthocyanin biosynthesis through certain transcription factors49. In Arabidopsis, AtHY5 is directly activated by AtBBX2151. Similar findings in rice showed that anthocyanin biosynthesis is regulated by OsBBX14 together with OsHY547. The promotion of anthocyanin biosynthesis has also been found to occur through an increase in MYB75/PAP1 transcriptional activity in Arabidopsis49. Similarly, MdHY5 from apple accelerates anthocyanin accumulation by upregulating the expression of the MdMYB10 transcription factor48. In this study, according to correlation analysis between the transcriptome and metabolome, another PybZIP transcription factor was shown to be highly correlated with Cy, which showed a strong response to light. In comparison to HY5, PybZIPa was more sensitive to light. The overexpression of PybZIPa promoted anthocyanin accumulation in pear, strawberry fruit, and tobacco leaves. Dual luciferase reporter and Y1H assays further confirmed that PybZIPa activated the transcription of the coexpressed genes PyUFGT, PyMYB114, PyMYB10, and PyBBX22 by binding to G-box motifs in the promoters of these genes. In addition, PybZIPa activated its own promoter.52. To gain an accurate understanding of biological networks, information from biological-omics data should be integrated. Multiomics analysis has established the foundation for new strategies for subsequent research. Correlation analysis between the transcriptome and metabolome reveals differentially accumulated metabolites that are related to phenotypic change and the DEGs that cause the changes in metabolites. This integrative analysis approach makes it easier to identify key regulatory metabolic pathways and reliable key regulatory genes37.Along with the development and improvement of sequencing strategies and technology, a systems approach for different levels of omics analyses of the mechanisms underlying a physiological phenomenon has become possible. A large number of DEGs and annotated metabolic pathways can be obtained with transcriptome sequencing technology. However, there is not a simple connection between the transcriptome and phenotype. Metabolites are the final products of whole metabolic pathways; hence, the metabolome can serve as an important bridge between the genome and phenotypePybZIPa gene that promotes anthocyanin accumulation by binding to the promoter of PyUFGT, the anthocyanin biosynthesis-associated transcription factors PyMYB10, PyMYB114, and PyBBX22, and its own promoter. Based on this and previous studies, we propose a regulatory network for anthocyanin biosynthesis in pear  and transcriptomic analysis (based on high-throughput sequencing) of bagged and debagged pear fruit. Cyanidin and its derivatives were the main anthocyanin compounds involved in light-induced coloration. The integrated analysis of the transcriptome and metabolome showed that a novel photosensitive Pyrus pyrifolia Nakai) were collected from the Anning experimental station of the Yunnan Academy of Agricultural Sciences. The fruits were bagged in double-layered paper bags (yellow-black) 35 DAFB. The bags were randomly removed at 10 days before commercial maturity, and the fruits were re-exposed to sunlight. The fruits were randomly sampled at 4 (B1), 8 (B2), and 10 (B3) days after bag removal, and fruits from which the bags were not removed were sampled at the same time  as a control. For each sample, three biological replicates were performed. All the fruits were peeled and immediately placed in liquid nitrogen, and the pericarp was then stored at −80 °C for the subsequent experiment.Fruits of “Mantianhong” pear (a red Chinese sand pear variety)  , which was vortexed for 10 s. Then, 1 mL of methanol/water  solution was added to the tube. After being placed at −80 °C for 3 min, the samples were homogenized at 60 Hz for 2 min. Then, the mixture was subjected to ultrasonic treatment for 30 min (25–28 °C), placed at −20 °C for 20 min, and centrifuged for 10 min at 14,000 rpm in precooled centrifuges (4 °C). An 800 μL aliquot of the supernatant was used for LC-MS analysis.High-performance liquid chromatography-grade acetonitrile, methanol, and An Agilent 1290 Infinity UHPLC coupled with an Agilent 6538 UHD and Accurate-Mass Q-TOF/MS system (Agilent Technologies) was used for metabolic profiling analysis in positive- and negative-ion modes. In positive- and negative-ion modes, metabolite separation was conducted in a Waters ACQUITY UPLC@HSS T3 column , and the mobile phase consisted of A and B . The following program was used for the linear elution gradient: 5% B for 2 min, then a linear increase to 95% B at 13 min, followed by holding for 2 min. Each run took 15 min. The column temperature was kept at 40 °C, and the flow rate remained at 0.4 mL/min, with a 3 μL injection volume. Mass spectrometry detection was carried out according to the following procedures: gas temperature: 350 °C; nitrogen flow: 11 L/min; capillary voltage: 4 kV and 3.5 kV for positive- and negative-ion modes respectively; nozzle voltage: 750 V; and mass scanning from 50 to 1,100 Da.Quality control samples (QC samples) were obtained by mixing aliquots of all samples. The QC samples were injected regularly while the analytical program was being run to obtain a dataset to be used for repeatability assessment. Before pattern recognition, the LC-MS data files were converted into the available general format by Agilent MassHunter Qualitative analysis software. The converted data were further analyzed by XCMS for peak integration and correction, which produced a three-dimensional data matrix composed of the peak intensity, mass-to-charge ratio and retention time. The resulting data from the positive- and negative-ion modes were normalized and merged into a new matrix.p value < 0.05  and a fold change > 1.5 were considered differentially accumulated metabolites. The METLIN database (https://metlin.scripps.edu/) was used to identify differentially accumulated metabolites.The converted data were submitted to the SIMCA-P software package, v14.0 , in which unsupervised principal component analysis (PCA) and (O)PLS-DA [ partial least-squares discriminant analysis] of data from 49 samples  were performed to investigate the metabolic composition changes after bag removal. The metabolites with a VIP value  > 1, a Total RNA from each sample  was isolated and then detected on an agarose gel (1%), and the concentration and RNA integrity number (RIN) values of the RNAs were also assessed. After enrichment and purification, 3 µg RNA of each sample was used for sequencing. The NEBNext® Ultra™ RNA Library Prep Kit for Illumina®  was used for sequencing library construction. After mRNA enrichment and purification, the sequences were fragmented to short lengths. These fragments were used as templates for first- and second-strand cDNA synthesis. With the help of exonuclease/polymerase activities, the remaining overhangs were transformed into blunt ends. The NEBNext Adaptor (a hairpin loop structure included) was ligated to the 3’ ends of the DNA fragments for hybridization after adenylation. AMPure XP beads  were used for segment size selection. Before PCR, the adaptor-ligated cDNA was treated at 37 °C (15 min) and then at 95 °C (5 min). Phusion High-Fidelity DNA polymerase was used for PCR. Then, the AMPure XP system was used for PCR product purification, and the Agilent Bioanalyzer 2100 system was used for library quality assessment.53. For false discovery rate (FDR) control, the Benjamini and Hochberg approach was used for P-value adjustment. An adjusted P-value < 0.05 was used to define differentially expressed genes between the bagged and debagged groups.Differential expression analysis between the bagged and debagged groups  was implemented with the DESeq R package (1.18.0). DESeq determines differential expression by using a negative binomial distribution-based modelP-value was used to define the significantly enriched terms (<0.05). The KEGG pathway enrichment analysis of the DEGs was accomplished with KOBAS software.The GOseq R package was used for the GO (Gene Ontology) enrichment of differentially expressed genes (DEGs), and the corrected P-values < 0.05 were considered to indicate a significant correlation, and the top 10 transcripts for each anthocyanin derivatives were identified and visualized using Cytoscape (version 3.4.0). The top 10 transcripts for the anthocyanin derivatives were subjected to KEGG pathway enrichment analysis.Pearson correlation coefficients were calculated for the integration of the metabolome and transcriptome information. The mean metabolite content according to the metabolome data and the mean expression of each transcript according to the transcriptome data were used for coefficient calculation. The fold changes in each group  were calculated for both the metabolome and transcriptome data. Pearson correlation coefficients > 0.9 and Nicotiana tabacum and Nicotiana benthamiana (grown in a greenhouse at 22 °C with 16 h of light a day) can be used for infection54. Diploid strawberry (Fragaria vesca) “Yellow Wonder” 5AF7 was grown in a glasshouse at 23 °C with 12 h of light per day, 2 or 3 weeks after anthesis 46, and the fruits could be infected. Pear (Pyrus bretchneideri cv. Zaosu) fruits for infection were collected at 20 days before harvest.Six-leaved plants  of PybZIPa were followed Xue et al.55 with little modification. The recombinant plasmid PybZIPa-GFP was used for Agrobacterium transformation (Agrobacterium tumefaciens strain GV3101) via the freeze-thaw method. The leaves of Nicotiana benthamiana plants (~3–4-weeks-old) with uniform growth were infiltrated through their abaxial surfaces , and then the infiltrated plants were cultured in a greenhouse At 72 h after infiltration, the infiltrated leaf tissues were collected and stained in a DAPI (fluorescent dye) working solution. After vacuum treatment, the green fluorescence and nuclear DNA signals were observed using a Leica TCs SP2 spectral confocal microscope . The microscope settings  were kept consistent between different samples to obtain comparable images. ZEN 2012 (blue edition)  and Adobe Photoshop Version 14.0  were used for image processing.The vector construction and experimental procedures for determining the subcellular localization of N. tabacum, F. vesca and P. bretchneideri cv. Zaosu were performed as previously described46. The full-length coding sequence (CDs) of PybZIPa was amplified and inserted into the pSAK277 transient expression vector with the 35 S promoter, and the recombinant plasmid was then transformed into Agrobacterium strain GV3101. The Agrobacterium strain was infiltrated on the tobacco abaxial leaf surface, strawberry fruitlets and pear peels for phenotype investigation, while Agrobacterium cultures carrying the empty vector served as the negative control. To control variability, at least two leaves or fruitlets were infiltrated. The leaves or fruitlets were harvested and photographed approximately ten days after infiltration.The transient assays in PybZIPa, the promoter sequences of PyCHI and PyANS, PyUFGT, PyMYB114, PyMYB10, PybZIPa, and PyBBX22 were inserted into the pGreen 0800-LUC vector (reporter vector). Vector construction for the transient expression and dual-luciferase assay was performed according to Hellens et al.54. G-box mutations were introduced into the PyUFGT promoter to verify the importance of the tandem G-box according to the instructions of the Mut Express® MultiS Fast Mutagenesis Kit V2 . Then, the correct recombinant plasmids were transformed into Agrobacterium strain GV3101 (with pSoup). The GV3101 Agrobacterium strain bacteria carrying PybZIPa and each promoter recombinant plasmid were cotransformed to N. benthamiana leaves54. LUC (Firefly luciferase) and REN (Renilla luciferase) activity was assayed according to the instructions of the Dual-Luciferase® Reporter Assay System .To detect the transcriptional activation of coexpressed genes by PybZIPa and the cloned promoter fragments of PyUFGT and PyMYB114, PyMYB10, PybZIPa and PyBBX22 were inserted into the pGADT7 vector and the pABAi vector, respectively. The primers for promoter fragment amplification are listed in Table http://www.clontech.com) containing the correct recombinant pABAi vectors was grown on SD/-Ura screening medium (with different AbA concentrations). Then, the interactions between PybZIPa and the promoter fragments were detected on SD/-Leu medium with the optimal AbA concentration. Empty pGADT7 with the corresponding recombinant pABAi was used as a negative control, and p53-AbAi was used as a positive control.The CDs of Supplementary TableSupplementary Figure


Hepatitis B virus (HBV) is considered highly prevalent in West Africa. However, major gaps in surveillance exist in Sierra Leone. Although healthcare workers (HCWs) are at high risk for HBV infection, little is known about the prevalence and knowledge of hepatitis B among HCWs in Sierra Leone.A cross-sectional study of all HCWs at the No. 34 Military Hospital located in Freetown, Sierra Leone, was conducted from March 20 to April 10, 2017. Whole blood was collected and screened for HBV markers using a one-step rapid immunochromatographic test with positive samples tested for HBV DNA. Additionally, questionnaires assessing self-reported knowledge of HBV infections were administered to all participants. Data were processed and analyzed using SPSS (version 17.0) software.p = 0.046). In addition, only 14 (6.6%), 73 (34.6%) and 82 (38.9%) participants in this survey had adequate knowledge about the clinical outcome, routes of transmission, and correct preventive measures of HBV infection, respectively.A total of 211 HCWs were included in this study with a median age of 39.0 years (range: 18–59). Of the participating HCWs, 172 (81.5%) participants were susceptible , 21(10.0%) were current HBV (HBsAg positive) and nine (4.3%) were considered immune because of past infection . Additionally, nine (4.3%) participants displayed immunity to the virus as a result of prior hepatitis B vaccination (only anti-HBs positive). Of the 21 HCWs with positive HBsAg, 13 (61.9%) had detectable HBV DNA. There was a significantly lower risk for current HBV infection among HCWs older than 39 years  contains supplementary material, which is available to authorized users. Hepatitis B virus (HBV) infection is a major threat to public health globally. According to the World Health Organization (WHO), approximately 257 million people are infected with chronic HBV . InfectiHealthcare workers (HCWs) are considered a high-risk group for HBV infection due to occupational exposure to blood-borne pathogens. Previous studies in Africa found high HBV infection and exposure rates (roughly 10%) in HCWs in South Africa and Nigeria. Worldwide, approximately 2 million HCWs are infected with HBV through sharp injury –9. This A cross-sectional study was conducted at the No. 34 Military Hospital in Freetown, Sierra Leone from March 20 to April 10, 2017. This hospital serves as a medical center for the Republic of Sierra Leone Armed Forces in addition to also being a teaching and general hospital. A total of HCWs, including medical doctors, nurses and other non-clinical health workers, were studied and written, informed consent was obtained from each subject.Blood samples were drawn from the antecubital vein of the 211 participants by phlebotomists of the No. 34 Military Hospital clinical laboratory then centrifuged for 5 min at 12,000 g at room temperature. Serological tests were performed to detect five markers including HBsAg, anti-HBs, HBeAg, anti-HBe and anti-HBc, by using a one-step rapid immunochromatographic test . Test results were interpreted and reported as positive or negative based on the manufacturer’s instructions.Viral deoxyribonucleic acid (DNA) was extracted using the QIAamp DNA Blood Mini Kit  according to the manufacturer’s instructions. HBV DNA was amplified using real-time PCR (qPCR)  HBV DNA assay kits  in all HBsAg positive samples.Data were collected using a self-administered questionnaire, which was developed after reviewing relevant research –12. The p value was < 0.05.The data obtained from the questionnaire and the results of the laboratory test were analyzed using SPSS . The response for each question was given a score of one and zero indicating a right or wrong answer was provided, respectively. Then we summed and graded the total scores as ‘poor’, ‘intermediate’ or ‘adequate’ level for each study participant based on the distribution located in the tri-sectional quantiles of the grouped data array. The Pearson Chi-square test was used to determine the relationships between participant characteristics and HBV marker detection rates. Multivariable factor analysis for current HBV infection was carried out for seven possible risk factors, including age, gender, working experience years, education background, occupation, vaccination, and sharp injury history. Differences were considered statistically significant when the The median age of the 211 HCWs who participated in the study was 39.0 years (range:18–59). Roughly half of participants were male (51.2%), over the age of 39 (46.9%), and had spent less than 9 years in their current job (46.4%). The majority of HCWs had a middle education level   (Table p = 0.018) (Table p = 0.046)  Table . Multivap = 0.017) and medical doctors were more knowledgeable about the consequences of HBV infection (p = 0.05)  of staff were not aware of clinical outcomes of HBV infection, while 63 (29.9%) and 93(44.1%) had a poor knowledge on transmission routes and preventive measures of HBV, respectively. The survey also revealed that working experience was associated with greater knowledge of preventive measures for HBV was observed in this study. Additionally, multivariable analysis of possible risk factors suggests a lower risk for current HBV infection among those HCWs aged > 39 years . This finding may be due to differences in lifestyle or behavior between the two groups, however a larger sample size is needed to adequately study this risk factor. As expected, we also found that HBV vaccination was a protective factor for anti-HBs positive (immune status due to vaccination), as demonstrated elsewhere [A significant difference in current infection rate between participants younger than 39 years old (lsewhere . Before lsewhere . In Sierlsewhere  and Ethilsewhere . Howeverp = 0.007). Furthermore, medical doctors had more knowledge of the consequences of HBV infection (p = 0.05), as expected compared to other occupations. It is generally assumed that education level and departments correlate with overall knowledge levels of the infection. However, this was not the case as these factors were not significant across all categories of knowledge, which is likely due to the small sample size of specific departments and education levels.The present study also found that there was poor knowledge of HBV, including the clinical outcome of infection, route of transmission and preventive measures of HBV, among HCWs. Therefore, HCWs in Sierra Leone will continue to be at risk of HBV infections until training and vaccination programs are strengthened. Our study also demonstrates that HCWs with longer working experience had more knowledge about preventive measures as compared to those with less work experience


The association of ABO blood groups with gastric cancer risk was proposed decades ago, but the results have been inconsistent.We used two single nucleotide polymorphisms to determine ABO genotype in 4932 gastric cancer cases and 6158 controls of Chinese descent, and evaluated the associations of ABO blood groups and genotypes with risk of gastric cancer using multivariable logistic regression models. We also systematically reviewed published literature and performed a meta-analysis of all relevant studies.AO and AB with risk of gastric cancer compared with OO genotype. Consistent with the case-control study, meta-analysis of 40 studies including 33,613 cases and 2,431,327 controls demonstrated that blood group A  and AB  were associated with increased risk of gastric cancer.In the case-control study, compared with blood group O, both blood group A and AB were associated with increased gastric cancer risk  = 1.13, 95% confidence interval (CI): 1.02–1.24; for group AB, OR = 1.18, 95% CI: 1.02–1.36, respectively). Analyses of ABO genotypes revealed associations of Our analyses validated the association of blood group A with risk of gastric cancer, and suggested that blood group AB was also associated with gastric cancer risk. Functional investigations are warranted to elucidate the exact mechanism of ABO blood groups in gastric carcinogenesis.The online version of this article (10.1186/s12885-019-5355-4) contains supplementary material, which is available to authorized users. Helicobacter pylori infection [Gastric cancer is the fifth most frequently diagnosed cancer and the third leading cause of cancer death worldwide, with estimated 1,033,701 new cases and 782,685 deaths in 2018 [nfection , drinkinABO, which encodes a glycosyltransferase that modifies the carbohydrate content of the red blood cell antigens. The role of ABO blood types in gastric cancer was initially suggested in more than 60 year ago, with the clinical observation that patients with gastric cancer were more likely to have blood group A than controls [The ABO blood group system was discovered by Karl Landsteiner in 1900 , and it controls . Since tTherefore, in the current study, we performed a large genetic study to evaluate the associations of ABO blood groups and genotypes with risk of gastric cancer in Chinese populations. In addition, we systematically reviewed published literature and conducted a meta-analysis of all relevant studies.https://www.ncbi.nlm.nih.gov/) (study accession number phs000361.v1.p1). Participants were from two separate studies conducted in Shanxi  and Linxian . Cohort III was a case-control study conducted in Jiangsu (1615 cases and 1053 controls) and Ningxia (737 cases and 801 controls) provinces. Gastric cancer cases were collected from local hospitals and were histopathologically confirmed, and controls were cancer-free individuals selected from local residents.Data were derived from three cohorts: Cohort I, the Nanjing/Beijing genome-wide association study (GWAS); Cohort II, the United States National Cancer Institute (NCI) GWAS, and Cohort III, a case-control study conducted in Jiangsu and Ningxia provinces. Among them, Cohort I and II have been described in detail previously , 10. BriAll the study participants were unrelated individuals of Chinese descent. There was no overlap of participants between these studies. Written informed consent was obtained from all the study participants. The study protocols were approved by the relevant Institutional Review Boards.ABO to infer phased haplotypes for each participant with > 99% posterior probability [O allele. rs8176746 encodes exon 7 C796A, which is one of the seven standard ABO variants distinguishing A alleles from B alleles. Haplotype phase determination was required to distinguish B and O alleles from the more rare A and O-variant alleles [A and O-variant alleles represent a minority in Chinese populations, we assumed that these participants were of the BO blood group for the following analyses. For Cohort III, custom probes and primers were specifically designed for rs8176746 and rs687289 and genotyping was performed using TaqMan PCR-based assay , following the manufacturer’s instructions. The sequences of primers and minor groove binder (MGB) probes for rs8176746 were 5’-ACCGACCCCCCGAAGAA-3′ and 5’-CCAAGGACGAGGGCGATT-3′, and FAM-CCCCCAGGTAGTAGA and VIC-CCCCCATGTAGTAGAA. The primers and probes sequences for rs687289 were 5’-TCCCAGAACCAAGAGTGAAGTCA-3′ and 5’-CTGGGATATTGCTCACGTATGG-3′, and FAM-TGTTTCCAGGCCGTG and HEX-TGTTTCCAGACCGTGTC. The amplification reaction was done with 10 ng of template DNA, 2 × Hot Taq PCR reaction mix (Stegene BioTechnologies), primers and probes mix in 384-well plates using 7900 Fast Real-time PCR system (Applied Biosystems). Thermal cycling was performed under the following conditions: 50 °C for 2 min, 90 °C for 10 min, followed by 40 cycles of 95 °C for 15 s and 60 °C for 1 min. The call rates of rs8176746 and rs687289 were > 99%. Duplicate samples from 45 study participants were interspersed throughout the genotyping assays, and the concordance rate for these quality control samples were 100%.For Cohorts I and II, information of genotyping, quality control and imputation has been described in detail elsewhere , 10. ABObability . Briefly alleles . As A anWe performed a systematic literature search in the PubMed database to identify all potentially relevant articles published from database inception through June 30, 2016. The search strategy included the terms “ABO” AND (“cancer” OR “carcinoma” OR “adenocarcinoma” OR “neoplasm”) AND (“gastric” OR “stomach”) in any text field of the database, without language limitations. The search identified 324 distinct publications. Two reviewers examined the publications independently to include studies in which frequencies, odds ratios (OR), or relative risks (RR) of the ABO blood group were reported for gastric cancer cases and controls. The same two reviewers manually checked the bibliographies of all relevant publications to identify possible additional studies for inclusion. We included data from original studies, and excluded those from secondary analyses or meta-analyses. For the studies that reported adjusted OR or RR with 95% confidence intervals (CI), we used the fully adjusted risk estimates as published. For the studies with only ABO blood group frequency data, we calculated and used the unadjusted effect estimates. Two reviewers independently assessed the quality of each included study using the modified Downs and Black Quality Assessment form. The quality score ranges from 0 to 14, and a higher score indicates better study quality. The discrepancies were resolved by consensus and discussion.t test for continuous variables and Pearson’s χ2-test for categorical variables. Deviations from Hardy-Weinberg equilibrium (HWE) among controls were assessed using χ2-based test. The association of ABO blood groups with gastric cancer risk was evaluated using multivariable unconditional logistic regression models, adjusting for age, sex, and study site. We further evaluated the association between gastric cancer risk and ABO genotypes . Subgroup analyses were performed based on age, sex, study site and tumor subsite.For the case-control study, individual level data was pooled from the three cohorts. The differences in the distributions of demographic characteristics between cases and controls were assessed using Student I-squared statistics. The fixed-effects model was used when there was no significant heterogeneity; otherwise the random-effects model was applied to provide more conservative estimates. The forest plots of the associations between blood groups and gastric cancer risk were generated for group A, B, AB versus group O. Publication bias was assessed by Egger’s regression and Begg’s rank correlation. The Begg’s funnel plots were generated, of which asymmetry was equated with the existence of potential publication bias. Sensitivity analyses were performed to evaluate the influence of individual studies on the overall effects by omitting one study at each time. We also evaluated possible heterogeneity of associations according to study subgroups, including study population, sample size, source of controls, study quality score and prevalence of Helicobacter pylori infection, which was classified as low and high as discussed by Peleteiro et al. [For the meta-analysis, heterogeneity across different studies was assessed using Cochran’s Q test and o et al.  and Mento et al. .P values less than 0.05 were considered statistically significant, unless otherwise noted.All statistical analyses were performed using Plink version 1.07, R software version 3.3.0 and STATA 11.0. Two-sided P = 0.316) and rs687289 (P = 0.410), and no statistically significant associations were observed for rs8176746 or rs687289 with gastric cancer risk under the additive, recessive, dominant or co-dominant models.The present study included a total of 4932 gastric cancer cases and 6158 controls. Selected characteristics of the study participants are shown in Additional file ABO allele frequencies were 55.93% for O, 21.77% for A and 22.30% for B, which were consistent with previous publications of Chinese populations [P = 0.018; for group AB, OR = 1.18, 95% CI: 1.02–1.36, P = 0.024, respectively). Similar results were observed for ABO genotypes. As shown in Table OO genotype, the risk of gastric cancer was 1.14-fold (1.03–1.26) for those with AO genotype and 1.18-fold (1.02–1.36) for those with AB genotype. .Tables ulations –17. CompP = 0.007; for group AB, OR = 1.42, 95% CI: 1.09–1.85, P = 0.010), younger participants , Cohort II , and non-cardia cancer . In the analyses limited to cardia cancer, blood group B was associated with decreased gastric cancer risk . No apparent evidence of heterogeneity was found between sexes or across different study sites, whereas significant heterogeneity was observed between different age groups  and tumor sites .Additional file The flowchart of the literature search and study inclusion is presented in Additional file Figures P > 0.05).Sensitivity analyses showed that the pooled estimates did not change appreciably even if the most influential study was omitted. All Begg’s funnel plots appeared to be symmetrical  which was identified to be associated with Helicobacter pylori seroprevalence by GWAS [Helicobacter pylori infection and gastric carcinogenesis.The association of blood group A with gastric cancer has been observed in many previous studies, while only a few studies found significant association between blood group AB and gastric cancer risk. It has been hypothesized that the effect of group A on gastric cancer risk may be mediated by a small variety of physiological differences, which includes alterations in systemic inflammatory state, intercellular adhesion and membrane signaling, and immune surveillance for malignant cell. For example, Sievers et al. proposed that individuals with blood group A produced less free acid in their stomachs  compared with those with group O . Pare et strains . A case-od types . Ansari Secretor . In our  by GWAS  in a subAA, BB and AB was relatively low, thus, even though our meta-analysis involved large number of gastric cancer cases and controls, in some of the genotype categories subdivided by ethnicity, there were still insufficient numbers of participants to yield definitive conclusions.The strengths and potential limitations of this study deserve mention. In the case-control study, we used genotype-inferred blood groups which lowered the risk of misclassification from self-report blood type and allowed us to evaluate the associations of ABO genotypes with gastric cancer risk specifically. Because ABO blood type distribution varies considerably in different races, our study has another merit that we used an ethnically homogeneous population which mitigated ethnic differences in ABO distributions. Moreover, to the best of our knowledge, the current case-control study has the largest number of gastric cancer cases from multiple study centers. With regard to the meta-analysis, some points are worth considering. First, several studies included in the analysis involved controls from large groups of blood donors. Even through these volunteer donors are generally considered to be representative of their studies’ ethnic compositions, they may have other characteristics associated with altered risk of gastric cancer, such as younger age distribution and more prevalent in type O. However, analyses limiting studies not involving blood-donor controls did not change the effect estimates appreciably. Second, although we found significant heterogeneity among included studies for blood group A verses group O, we used random-effects models which allowed taking into account the heterogeneity among studies. Finally, because the prevalence of group In conclusion, our analyses validated the association between blood group A and increased risk of gastric cancer, and indicated that group AB was also associated with gastric cancer risk. Further functional investigations are recommended to clarity the exact role of ABO in gastric carcinogenesis.Additional file 1Table S1. Selected characteristics of the study participants. (DOCX 17 kb)Additional file 2Table S2. Subgroup analyses of the associations between ABO blood types and gastric cancer risk. (DOCX 21 kb)Additional file 3Figure S1. The flowchart of literature search and study inclusion. (Docx 26 KB) (DOCX 26 kb)Additional file 4Table S3. Summaries of the studies included in the meta-analysis of ABO blood groups and gastric cancer risk. (DOCX 21 kb)Additional file 5Figure S2. Begg’s funnel plots for ABO blood group and gastric cancer risk. Figs. A-C are funnel plots for blood group A (A), B (B), AB (C) verse group O. The vertical axis represents the log-transformed odds ratios (ORs). The horizontal axis represents the standard errors (SEs) of log-transformed ORs. The funnel plots are drawn with 95% confidence intervals. (DOCX 80 kb)Additional file 6Table S4. Subgroup analyses stratified by potential modifying factors. (DOCX 20 kb)


NAC families in this species to date.Although the genome of Chinese white pear (‘Dangshansuli’) has been released, little is known about the functions, evolutionary history and expression patterns of NAC transcription factors (TFs) in the pear genome, among which 146 pear NAC (PbNAC) members were mapped onto 16 chromosomes, and 37 PbNAC genes were located on scaffold contigs. No PbNAC genes were mapped to chromosome 2. Based on gene structure, protein motif analysis, and topology of the phylogenetic tree, the pear PbNAC family was classified into 33 groups. By comparing and analyzing the unique NAC subgroups in Rosaceae, we identified 19 NAC subgroups specific to pear. We also found that whole-genome duplication (WGD)/segmental duplication played critical roles in the expansion of the NAC family in pear, such as the 83 PbNAC duplicated gene pairs dated back to the two WGD events. Further, we found that purifying selection was the primary force driving the evolution of PbNAC family genes. Next, we used transcriptomic data to study responses to drought and cold stresses in pear, and we found that genes in groups C2f, C72b, and C100a were related to drought and cold stress response.In this study, we identified a total of 183 NAC gene family in Chinese white pear, we indentified 11 PbNAC TFs associated with abiotic stress in pear.Through the phylogenetic, evolutionary, and expression analyses of the The online version of this article (10.1186/s12870-019-1760-8) contains supplementary material, which is available to authorized users. TFs) are essential for the regulation of gene expression by binding to specific cis-acting promoter elements, thereby activating or repressing the rate of transcription of their target gene(s) . With respect to WGD/segmental and tandem duplication events in other Rosaceae plants, Chinese white pear and apple showed different trends from strawberry, plum, and peach. Our results suggest that WGD was the main driver of the expansion of the NAC gene family in both apple and Chinese white pear . We identified 98 pairs of collinear fragments  after mapping to a linear regression model was 0.99, showing that the two chromosome segments containing the NAC gene were generated by a chromosomal duplication event. The average Ks value of the 18 pairs of homologous genes was 0.04 (standard deviation: 0.03), indicating that this replication event occurred relatively recently. These results further demonstrate that recent lineage-specific WGD events resulted in the expansion of the PbNAC gene family in Chinese white pear.In order to investigate the evolutionary mechanisms responsible for the diversity in the PbNAC gene family were estimated by Ks values. Additional file PbNAC duplicated gene pairs in syntenic regions; Ks values ranged from 0.01 to 7.18. In addition, 88 (89.80%) repeat gene pairs were distributed in two main peaks  duplicated gene pairs had even higher Ks values (2.88–7.18).Typically, the evolutionary dates of WGD or segmental duplication events are estimated by Ks values . Previous studies have determined that there are two genome-wide duplication events in the pear genome: an ancient WGD Ks~ 1.5–1.8) estimated to have taken place approximated 140 MYA , and a r–1.8 estiPbNAC gene family in Chinese white pear, coding sequences (CDS) was used to calculate the Ka/Ks ratio of homologs in the PbNAC gene family. All Ka/Ks ratios obtained from 84 gene pairs were < 1   selection is the process of accumulating new favorable mutations and then spreading throughout the population, while negative (purifying) selection is the process of removing deleterious mutations . In ordeNAC TFs to the drought stress of Chinese white pears. To study the response to drought stress in pear, transcriptomic data of PbNAC genes was analyzed in plants exposed to drought treatment. Only 109 PbNAC genes showed differential gene expression pattern; six gene clusters were identified and visualized in a heat map  are produced by evolution; ancestral genes and their functions are maintained by speciation events, and mutations may occur within the genes after species differences. In previous studies, 18 PbNAC TFs. These genes were enriched for the following GO terms: nucleic acid binding, transcription factor activity, multicellular organismal processes, hormone-mediated signaling pathways, developmental processes involved in reproduction, gene expression, post-embryonic root development, transcription regulator activity, response to stress, abscisic acid mediated signaling pathways, response to hormone stimuli, and response to carbohydrate stimuli. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that the following terms were associated with these genes: biosynthesis of secondary metabolites, phenylpropanoid biosynthesis, and isoflavonoid biosynthesis. These pathways have previously been shown to be related to abiotic stresses [We next performed a Gene Ontology (GO) analysis of Group C2f, C72b, and C100a, which were the groups with the greatest number of orthologous stresses , 56.PbNAC17, PbNAC72a, PbNAC72b, PbNAC2a, PbNAC2b, PbNAC100b, and PbNAC87b, were up-regulated 3 or 6 h after drought treatment and then down regulated 24 h of recovery. However, our qRT-PCR results for PbNAC21a and PbNAC21b differed from those shown in the heat map, as they were up-regulated after 24 h of recovery . The results of this approach depicted trends in relative gene expression that were largely consistent with the previous approach. Seven genes, including NAC TFs in response to cold stress as we did in response to drought stress. Our results suggested that 113 PbNAC genes showed differential expression and the resulting heatmap was divided into six clusters  and Cluster 6 (14 genes), most genes were up-regulated at 5 and 12 h after cold treatment, except PbNAC74a, PbNAC56a, and PbNAC91d. However, after cold treatment some genes including PbNAC91b, PbNAC2b, PbNAC83g, PbNAC2a, and PbNAC100c were down-regulated at 0 h. The genes in Cluster 4 showed no obvious expression differences in response to cold stress. We selected 26 genes which were up-regulated at least 1.5-fold after cold treatment, to survey the expression patterns in other phylogenetic groups , and enhanced drought tolerance [NAC genes responded to drought or salt stress, and overexpression of SNAC3 (ONAC003), ONAC022, OsNAC5, OsNAC2, and OsNAC6 improved drought tolerance in transgenic plants [TaNAC29, TaNAC2, TaNAC2a, and TaNAC67 was also found to increase tolerance to cold, high salinity, and drought stresses [PbNAC TFs orthologs of NAC TFs (identified as being involved in the abiotic stress response) in Arabidopsis were found to be responsive to drought and cold stresses in pear. We speculate that these PbNAC TFs may have functions in pear that are equivalent to those of their Arabidopsis orthologs. Since gene expression patterns can provide important clues for their functions, we examined the expression of selected 11 PbNAC genes in drought and cold treatments by using qRT-PCR. Interestingly, these genes are all shown to be involved in the regulation of drought and cold. In future, more researches will be needed to determine the functions of the PbNAC genes in pear.Abiotic stresses, such as drought and cold, can cause loss of yield and reduce the quality of fruit trees , 63. Thebidopsis , 64. Morolerance . In ricec plants , 65. In stresses , 67. In NAC TFs in plant growth and development, as well as their response to abiotic stresses. Therefore, the NAC TF family has become the subject of continued attention because of its potential involvement in plant tolerance engineering [PbNAC genes examined in this study play essential roles in plant responses to abiotic stress, and therefore may be suitable candidate genes for the engineering of pear plants with improved stress resistance. Overall, in this study, we provide a comprehensive analysis of the NAC family in Chinese white pear, and we discuss the relationship of this family to abiotic stress responsiveness. The results presented in this report may facilitate the functional characterization of the NAC gene family and further understand the relationship among NAC family members. Alternatively, our results could also improve our understanding of the molecular basis of important agronomic traits in pear, including fruit development and their abiotic stress response. Taken together, our results may be useful for identifying new candidate NAC family genes for genetic engineering of novel pear germplasms with enhanced stress tolerance. We will verify the cold and drought tolerance of these 11 genes in future studies.To date, many studies have investigated the important roles of ineering –72. Our PbNAC genes were identified from the pear genome. Based on the phylogenetic relationships between these genes, we divided the 183 PbNAC genes into 33 subgroups. The analyses of conserved domains suggested that PbNAC genes in the same group had similar functions. NAC genes from pear and Arabidopsis were present in most subgroups, indicating that these members had a recent common ancestor. Thus, the function of most NAC genes might be conserved during angiosperm evolution. Collinearity analysis showed that the recent WGD (30–45 MYA) may have contributed to the large-scale amplification of the NAC gene family in Chinese white pear. Purifying selection was found to be major force acting on NAC family genes; eight genes underwent positive selection after replication differentiation. Transcriptome sequencing analysis identified PbNAC genes likely to play an important role in responses to drought and cold stress. Expression and functional data for AtNAC genes supported the hypothesis that PbNAC genes possess a variety of unique functions under drought and cold stress. In conclusion, we found eleven PbNAC genes that play a key role in the response to abiotic stresses. This will facilitate further research on the biological functions of NAC TFs in pear, while the functions of these genes are an important topic for further research on this species.A total of 183 Pyrus bretschneideri) were obtained from http://peargenome.njau.edu.cn [A. thaliana were downloaded from the Arabidopsis Information Resource (TAIR) (http://www.arabidopsis.org/) [http://pfam.xfam.org/family/PF02365/). HMMER was used to search a customized database containing the proteome with the threshold set to the Pfam GA gathering cutoff [http://www.ebi.ac.uk/interpro/) [NAC genes from four other Rosaceae plants. The genome sequences of apple, peach, and strawberry were downloaded from Phytozome  and the Chinese plum genome sequence was downloaded from the Prunus mume Genome Project (http://prunusmumegenome.bjfu.edu.cn) [The complete genome, proteome sequences, and GFF of pear (u.edu.cn . The coris.org/) . In bothg cutoff . The HMMterpro/) . We used.edu.cn) .PbNAC gene from genome annotation documents [PbNAC gene was drawn by using the Gene Structure Display Server online software package (http://gsds.cbi.pku.edu.cn/) [PbNAC proteins [We obtained information on the detailed chromosome location of each ocuments . These documents . The genedu.cn/) . To inveproteins . The anaPbNAC genes was performed according to their phylogenetic relationship with corresponding Arabidopsis AtNAC genes.We performed multiple sequence alignment on the NAC domains of the protein sequences by using MUSCLE set at default parameters . And we http://chibba.agtec.uga.edu/duplication/) was used to perform synteny analysis [NAC genes. The minimum number of homologous gene pairs in synteny was 3, and the E-value of the common linear section was 0.01. The Q-value was 0.9. If the alignment of the homologous pairs between these two chromosomal segments were considered to follow a linear relationship (determined by the correlation coefficient of the linear regression), we concluded that there was a collinear relationship between the two fragments, which was presumably due to WGD or segmental duplication. MCScanX downstream analysis tools were used to annotate the Ka and Ks substitution rates of syntenic gene pairs. The average Ks value of homologous pairs in the collinear section reflected the approximate time of replication. We took Ka/Ks < 1 to be indicative of negative selection, while a value equal to 1 indicated neutral selection, and > 1 indicated positive selection. We selected collinear segments where the Ks value was < 0.3 with its sub-family as the background. A program package for phylogenetic analysis by maximum likelihood (PAML) was then used to inspect branch sites [A method similar to PGDD  and allowed to dry for 0, 1, 3 and 6 h in an ambient environment at 26 °C, followed by recovery in water at 26 °C for 24 h. For the cold treatment, the plants were transferred to 4 °C growth chambers for continuous treatment for 0, 5, 12 and 24 h, followed by recovery at 26 °C for 24 h. For each time point, at least 30 seedlings were used, and the collected samples and stored at − 80 °C until use. Total RNA from samples was isolated as described by Huang et al. (2015) [2(fold-change) ≥ 1. InterPro domains [P-values and enrichment factors [Three-month-old . (2015) . Solexa/. (2015) . There w. (2015) . An impr. (2015) . To obta. (2015) . Differe domains  were annr papers  × 90 mm  domains . GO enri domains . Enriche factors . This wan = 3). Relative expression levels were calculated by using the 2-ΔΔCt method and normalizing to expression of the pear tubulin gene (AB239681) was used as an internal control [To validate expression patterns obtained by the digital transcript abundance measurements, eleven genes were analyzed using qRT-PCR and the primers were in Additional file  control . The pro control .Additional file 1:Table S1 Basic information of NAC genes in five Rosaceae species. (XLSX 66 kb)Additional file 2:Table S2. Domains in NAC genes in Pyrus bretschneideri. (PDF 79 kb)Additional file 3:Table S3. Nineteen unique Rosaceae subgroups. (PDF 57 kb)Additional file 4:Table S4. Numbers of NAC genes from WGD/segmental duplication events in five Rosaceae genomes. (PDF 53 kb)Additional file 5:Table S5. Synteny related to genes in the NAC gene family in P. bretschneideri. (PDF 55 kb)Additional file 6:Figure S1. Coefficients of determination of PbNAC73a and PbNAC73b .Figure S2. Segmental duplication between members of PbNAC73a and PbNAC73b. (ZIP 25 kb)Additional file 7:Figure S3. Distribution of mean Ks values of PbNAC gene pairs in synteny blocks. (PDF 6 kb)Additional file 8:Table S6 Ka/Ks related to genes in the NAC gene family in P. bretschneideri. (PDF 48 kb)Additional file 9:Table S7 Positive selection of current WGD/segmental duplication using branch-site model A. (PDF 68 kb)Additional file 10:Table S8 Up-regulated genes in response to drought treatment. (XLSX 10 kb)Additional file 11:Table S9 Up-regulated genes in response to cold treatment. (XLSX 9 kb)Additional file 12:Table S10 Primer details for genes selected for quantitative real-time PCR analysis from results of digital transcript abundance measurements. (PDF 50 kb)