Karenia brevis (K. brevis) pose a serious threat to coastal Southwest Florida. These blooms discolor water, kill fish and marine mammals, contaminate shellfish, cause mild to severe respiratory irritation, and discourage tourism and recreational activities, leading to significant health and economic impacts in affected communities. Despite these issues, we still lack standard measures suitable for assessing bloom severity or for evaluating the efficacy of modeling efforts simulating bloom initiation and intensity. In this study, historical cell count observations along the southwest Florida shoreline from 1953 to 2019 were used to develop monthly and annual bloom severity indices (BSI). Similarly, respiratory irritation observations routinely reported in Sarasota and Manatee Counties from 2006 to 2019 were used to construct a respiratory irritation index (RI). Both BSI and RI consider spatial extent and temporal evolution of the bloom, and can be updated routinely and used as objective criteria to aid future socioeconomic and scientific studies of K. brevis. These indices can also be used to help managers and decision makers both evaluate the risks along the coast during events and design systems to better respond to and mitigate bloom impacts. Before 1995, sampling was done largely in response to reports of discolored water, fish kills, or respiratory irritation. During this timeframe, lack of sampling during the fall, when blooms typically occur, generally coincided with periods of more frequent-than-usual offshore winds. Consequently, some blooms may have been undetected or under-sampled. As a result, the BSIs before 1995 were likely underestimated and cannot be viewed as accurately as those after 1995. Anomalies in the frequency of onshore wind can also largely account for the discrepancies between BSI and RI during the period from 2006 to 2019. These findings highlighted the importance of onshore wind anomalies when predicting respiratory irritation impacts along beaches.Nearly all annual blooms of the toxic dinoflagellate  Karenia brevis occur along the Florida Gulf coast almost every year. This organism produces brevetoxins (PbTx), neurotoxins that accumulate in shellfish necessitating large-scale closures of shellfish beds. Consumption of shellfish containing elevated PbTx concentrations causes neurotoxic shellfish poisoning (NSP). Unlike many other marine algal toxins, brevetoxins become aerosolized when K. brevis cells break open in high turbulence  and are subsequently transported onshore by winds. These aerosolized toxins cause respiratory irritation and pose a significant risk to beachgoers with chronic respiratory illnesses such as asthma [K. brevis blooms in Florida caused mass mortalities of endangered manatees [K. brevis blooms moved inshore during winter and spring and persisted for weeks to months. Severe bloom years were also frequently associated with bottlenose dolphin mortalities, massive fish kills, and death of sea turtles [Blooms of the toxic dinoflagellate s asthma –5, and hs asthma . Reportss asthma –9. Severmanatees , 10–14.  turtles , 15–18.K. brevis was identified as the cause of “red tides” off the Southwest coast of Florida in the 1940s [K. brevis were identified as long ago as 1528 but it was not until 1875 that fish kills were first linked to reports of human respiratory irritation [he 1940s . As a rehe 1940s –22. Drawhe 1940s , 23–25. ritation .K. brevis concentrations over space (extent) and time (duration) is necessary in order to objectively evaluate the mechanisms and environmental factors most affecting initiation, growth, size, and demise of blooms. To date, the study coming closest to providing this type of record was by Feinstein [K. brevis bloom dynamics [K. brevis bloom phenology in this region.Establishing a multi-year record of bloom magnitude that examines einstein . She estdynamics –36. DespK. brevis bloom severity index (BSI) to quantify the intensity of blooms through time. A bloom severity index will help assess impacts of the blooms and can be used to evaluate models of the factors causing severe, or negligible, blooms. Two existing robust data sets allowed the development of severity indices for these blooms and their respiratory irritation impacts. The first consists of K. brevis cellular abundance from the FWC-FWRI HAB monitoring database (1953–2019), and the second of respiratory irritation reports collected by the Beach Conditions Reporting System .K. brevis, starting in 2006 with the development and implementation of the BCRS, has enabled quantification of this impact at coastal beach sites in Sarasota and Manatee Counties. As noted previously, aerosolized brevetoxins brought onshore by wind during bloom periods cause people to cough and experience sore throats, rhinorrhea and other respiratory irritation [The second goal of this study was to develop a respiratory irritation index (RI). Routine reporting of respiratory irritation caused by ritation , 38.K. brevis cells and the occurrence and intensity of respiratory irritation [K. brevis reliably produces PbTxs, so the presence of cells indicates toxin presence [-1 can cause slight to moderate respiratory irritation, and cell counts exceeding 1,000,000 cells L-1 are often associated with more severe and common irritation [A further argument for using the cell count and respiratory irritation data sets is the demonstrated association between the occurrence and concentration of ritation , 37, 38.presence , 40. In ritation .K. brevis blooms could constitute a third dataset to inform development of the bloom severity index. Satellite monitoring has been used routinely since 1999 [K. brevis blooms, the use of satellites for quantification has several concerns. The key concern is that the algorithms are not specific to K. brevis. They are based on the optical properties of phytoplankton , detection of which depends on optically-deep water (too deep for light to reflect off the bottom) and low concentration of suspended sediments. Any time of the year, these algorithms can inadvertently identify non-Karenia blooms as K. brevis. Detection of K. brevis is more reliable in late summer and fall, when it is the most common bloom species [K. brevis [K. brevis blooms is most successful when suspected bloom features are confirmed by field sampling. This is the approach that the National Oceanic and Atmospheric Administration (NOAA) has used in its monitoring program [K. brevis. However, they did not evaluate for the presence or frequency of false positives, which would be caused by fluorescence from blooms of other algal species.It would be logical to assume that satellite surveillance methods currently used to monitor nce 1999 –45. Thou species . The cho species . Suspend species . Resuspe. brevis . As a re program , 43, 48. program  did a tiKarenia blooms throughout the seasons is needed. Another concern with using satellites is the length of record. No evaluation is possible before 1997 (OrbView-2 satellite), the start of the era of routine ocean color satellites, and chlorophyll fluorescence can only be used after 1999 (launch of Terra satellite). One area where satellite surveillance of blooms has proven useful is in assessing the long-term presence of freshwater cyanobacterial blooms, due to their distinctive spectral patterns and ability to produce surface scums . Fo Baltic, –67.The role wind plays in modulating respiratory irritation relative to bloom severity was also a focus of this study. Because respiratory distress is higher when onshore winds prevail  it was lKarenia brevis cell counts for all of Florida were obtained from the HAB Monitoring Database of the Florida Fish and Wildlife Conservation Commission, the Fish and Wildlife Institute (FWC-FWRI) [K. brevis cell counts in cells L-1, and county where samples were taken, if relevant. Offshore sampling was highly variable in time and space, and heavily dependent on short-term research projects. To ensure a consistent data set, cell counts collected within about 5 km (3-miles) of the coast were extracted in ArcGIS. Bays and estuaries were excluded by a straight line across their entrances (WC-FWRI) . FWC-FWRntrances , as baysntrances , which hK. brevis cell counts were mainly collected in response to a specific event such as a large fish kill in coastal waters, seawater discoloration, or respiratory irritation of beachgoers or boaters [The FWRI data set started in August 1953 and consisted of cell abundance to 2019 with concentrated sampling between Collier and Pinellas counties  along the coast during each month over the course of the time series. The latitudinally binned monthly data set is available as Once the base-line cell counts within 5 km of the coastline were established, they were next binned by 0.2 latitudinal degrees, which covers about 25 km along the mostly north-south oriented coast. Finer resolution would have led to increasingly gappy data prior to 2005 e.g.,  Figs, ane patchy , 69, ande patchy , 70. To  impacts , 71. Shel people . ConsequAs some sampling gaps (empty bins) still occurred, particularly before 1994, the impacts were mitigated by using limited infilling of gaps  Figs. If-1, >5,000 cells L-1, > 50,000 cells L-1, >100,000 cells L-1, or >1,000,000 cells L-1) were color coded to represent the intensity of the bloom occurring in each monthly latitudinal bin. Light blue indicated 0 to 5,000 cells, and a graduation in color from pale to dark red was used for the categories ranging from >5,000 cells L-1 to >1,000,000 cells L-1. Bins shown in white indicate no samples were taken.The categorized monthly cell count data for each 0.2° latitudinal bin from 1953–2019 were next plotted against latitude from 25.4º to 28.4º N in the form of Hovmöller diagrams see . The ass-1, the bin was assigned a value of zero. The number of latitudinal bins falling into each of the four remaining categories for a given month were then tallied. These tallies were totaled for each month. Months without any field observations were indicated by black Xs on the X-axis. Next, the month with the maximal number of 0.2° latitudinal bins exceeding 5,000 cells L-1 was identified. This occurred in February 2016, when 13 latitudinal bins exceeded the 5,000 cells L-1 threshold and represents the greatest spatial extent of any bloom observed in a given month. Dividing the monthly tallies for all latitudinal bins where cells exceeded 5,000 cells L-1 by 13 bins (monthly maximum in February 2016), and multiplying by 10 produced the normalized bloom severity index (BSI) with a range of 0–10 over the study period  was developed . The indy period . BSI = 0-1) were indicated in the form of stacked plots. The relative contribution to the total BSI by each cell concentration category was indicated using a gradation of different colors ranging from pale to dark red. The greater the proportion of any bar within the BSI graph represented by a darker color, the more coastline impacted in a given month by higher concentration blooms . The greater the proportion of each bar in the annual BSI graph shown in darker colors, the more coastline was impacted by the higher cell concentrations. The Xs on the X-axis indicate years where no samples were taken .The tallies of maximum concentration categories observed for all the 0.2° latitudinal bins over each bloom year were normalized by the greatest number of bins in any single year exceeding 5,000 cells Lnual BSI . The max-1 in every 0.2° latitudinal bin , maintained by Mote Marine Laboratory, provided respiratory irritation reports, based on the intensity of coughing, a good indicator of brevetoxin aerosol impact . RespiraA monthly respiratory irritation impact (RI) index, shown in The resultant monthly RI time-series for the three categories is presented in An annual respiratory irritation impact index (RI) was calculated using a method analogous to the annual BSI (Section 2.3). The beach-days of respiratory irritation classes were accumulated over the bloom year (August to next July). These summed values were normalized by the largest annual proportion of the “irritation present” class observed in any single year. The maximum proportion of beach-days (0.29) occurred in the 2018 bloom season, with 856 of 2,920 annual beach-days (365 days multiplied by 8 beaches) . The proK. brevis blooms  Station at Venice Pier, FL  was calculated from these two time series using the following procedure. First, the hourly VENF1 and 3-h NARR winds were decomposed into onshore and alongshore components. The monthly time series of OWF was calculated by the total number of hours within each month when winds blew onshore, divided by the total number of hours in that month for which wind observations were available. This yielded the fraction of the time each month when winds blew onshore. OWF anomalies (OWFA) were computed by taking the OWF for each month of the time series and subtracting the long-term-average OWF for that month. Positive (or negative) OWFA indicated that the onshore winds were more (or less) frequent than average for that month. The OWFA monthly data sets for NARR and for VENF1 are available as As discussed earlier, prior to 1994, K. brevis blooms and sampling frequency along south Florida are presented . Based on this criterion, 2001 would be the most severe bloom year. If the potential for severe respiratory and other impacts, such as fish kills are considered  the most intense blooms occurred in 1994, 1995, 2012, and 2018  averaging 4.1 from June through November.The annual BSI provides a more direct measure of bloom severity for the entire bloom year, but it does not capture potential intense short-term impacts during the bloom revealed by the monthly BSI. For example, Feb 2016 was not only the peak month for BSI, but nearly all latitudinal bins in southwest Florida that month had bloom concentrations >100,000 cells L-1 . The 201Karenia brevis cell counts are typically low at the end of the bloom year in June and July. However, there are instances where blooms from the previous fall do not abate by June and July and continue into the subsequent bloom year (which starts in August) , June 1995 (3.1), July 1971 (3.1), June 1954 (1.5), July 2006 (1.5), June 1995 (0.8), July 1980 (0.8), July 1991 (0.8), June-July 2005 (0.8). When July blooms continued into August, such as in 1995, 2005 and 2018, they may have exacerbated the development of the typical fall blooms, resulting in the unusually intense fall blooms observed in each of these years. August) . These J-1. The longest blooms reported by the state of Florida match this data set for the southwest Florida coast. Their longest blooms were 1994–1997 (30 months), 2002–2004 (21 months), 1953–1955 (18 months), 2004–2006 (17 months), 2017–2018 (15 months). The dataset presented here has nearly continuous blooms along the southwest Florida coast during all of these periods, indicating that blooms consistently impact this section of coast. The Florida table [The state of Florida has produced a table of presence of blooms each month from 1878 to the present for west Florida [Karenia brevis blooms typically initiate in the fall of most years, and sometimes last through the winter, a result consistent with previous work [-1) generally occurring in individual bins from 40% to 68% of the years . Sampling decreased substantially in December, when OWFA turned negative, and stopped in January. Sampling restarted in March after a return to strongly positive OWFA. Sampling of the early bloom in July 1991 coincided with a change to strongly positive OWFA, which was preceded by a negative OWFA in the spring and weakly positive in June, neither of which were sampled. In 1993, limited sampling showed there was no bloom despite strong positive OWFA, suggesting that there was no bloom in 1993. In fall 1994, the start of sampling (and the observed bloom) occurred after a shift from negative to positive OWFA. In summary, before routine sampling started in 1995, increased onshore wind frequency (positive OWFA) appeared to be a catalyst for increased sampling in Southwest Florida, and that under-sampling of the bloom was consistent with periods of reduced onshore winds (negative OWFA).In most years between 1979 and 1994, sampling started in conjunction with positive OWFA, and often did not occur during times when OWFA was negative. In fall 1979, there was a consistent positive OWFA before the bloom started . In 1980Respiratory irritation impact (RI) generally corresponded with the size and intensity of the blooms represented by BSI . The larK. brevis cells. A minimum offshore wind speed may be required to transport dense aerosols away from the beach during the strongest blooms. Most of the months when RI fell below the correlation line (milder impacts than expected for a given BSI) were associated with negative OWFAs (offshore winds). These results indicate high BSI blooms will have more severe respiratory impacts during positive OWFAs, and milder impacts during negative OWFAs.The influence of wind on the discrepancies between RI and BSI are illustrated in K. brevis bloom severity (BSI) and respiratory irritation impact (RI). These indices were, respectively, applied to southwest Florida and to Sarasota and Manatee Counties; areas that consistently suffer from the adverse impacts of these blooms [K. brevis blooms in terms of spatial extent, duration, and cell concentrations. As such it has the potential to serve as a reference dataset for validating the accuracy of various models relating variations in bloom severity to environmental conditions. Feinstein [This study developed long-term, objectively-derived indices of e blooms , 27, 78.einstein . The RI Both indices are straightforward to update monthly or annually and can inform the public and resource managers of the relative severity of current or recent blooms. Similar indices were effectively used to provide severity information regarding the toxic cyanobacterial bloom in western Lake Erie  and for K. brevis bloom ‘indices’ [K. brevis after 1994, defining bloom presence by averaging for each week the top five maximal bloom concentration values found anywhere on the west Florida shelf. The index is useful for showing the bloom presence/absence in southwest Florida, but it did not capture extent or magnitude. For example, the bloom during fall 2007 was rather weak along the southwest coast of Florida  (-1) over several bins of latitude, for example 1994, 2001, 2006, 2009, 2012, 2015, 2016, 2017. The blooms typically expand northward and southward in the months immediately after initiation, which is also evident in monthly frequency plots  . In manycy plots . Howevercy plots .While blooms most often initiate from August into the fall months, there are exceptions. Continuation of previous year’s blooms through the summer and into the next fall occurred in 1954, 1987, 1995, 2002, 2003, 2005 and 2018 . In mostThere are periods with consecutive years having either severe blooms or mild blooms. The recent years 2015–2018 all experienced intense blooms , as did K. brevis blooms  and drifted southward in November and December. Though covering a large geographic region, the bloom never reached inshore waters . The lar-1 were present in >50% of the years sampled  . Yet oveK. brevis blooms to date. They used daily cell counts from two stations during blooms as a proxy for brevetoxin exposure in their analysis of changes in frequency of respiratory visits to emergency departments (ED). Though they recognized that onshore winds should be a factor in increasing exposure, they were unable to find a correlation between wind speed, direction, and ED visits. The results presented here indicate that more sophisticated analysis for wind impacts on brevetoxin exposure is required; that anomalies in onshore winds best describe respiratory impacts. Expanding the respiratory irritation sampling would provide more data for use in models designed to understand people’s response to blooms. Unfortunately, the respiratory irritation data set post-dates the Hoagland et al. study [Hoagland et al.  conductel. study . Analysel. study .Karenia brevis blooms pose significant threats to the coast of Florida, yet to date there has not been a standard metric of bloom severity that is sufficiently flexible to accommodate spotty historical data and capture bloom dynamics at varied spatiotemporal scales. In this study, quantitative monthly and annual indices for K. brevis bloom severity (BSI) from 1953–2019 along the coast of Southwest Florida and associated respiratory irritation index (RI) in Manatee and Sarasota Counties from 2006–2019 are presented. The bloom severity and respiratory irritation indices consider not only the intensity (of cells or irritation), but also duration and extent along the coast relative to the most severe events on record, providing both spatial and temporal information not previously considered. These indices can directly benefit both environmental models of bloom dynamics and socio-economic assessments of K. brevis bloom impacts. The metrics and approach used here are not specific to SW Florida, and can be applied to any location that has routine sampling.The recurring, toxic K. brevis blooms.The BSI was based on the state cell count database from 1953–2019 and can provide an objective reference for evaluating models that attempt to determine bloom magnitude , 35, 36.K. brevis. These indices can help managers and decision makers evaluate the risks along the coast during a bloom but also within an interannual context, and help them plan ways to better respond to and mitigate bloom impacts.Both BSI and RI developed in this study have shown the blooms and their respiratory impacts are not monolithic in time and space. While some locations might be affected for several consecutive months during severe blooms, the entire coast is not constantly impacted from initiation to termination Click here for additional data file.S2 DataRow is for each month, column is for BSI at each category . NaN means there are no observations for that month.(CSV)Click here for additional data file.S3 DataRespiratory Irritation  conditions were reported for each beach. Row is for each month, column is each beach, first set is "present", second set is "moderate", third set is "high". NaN means there are no observations for that month.(CSV)Click here for additional data file.S4 DataRow is for each month, column is for RI at each category . NaN means there are no observations for that month.(CSV)Click here for additional data file.S5 DataThe columns are the NARR onshore wind frequency anomalies (OWFA) as proportion of winds having a positive or negative anomaly used in (CSV)Click here for additional data file.S6 Data-1) as seen in Onshore Wind Frequency Anomalies- OWFA as proportions for the VENF1 meteorological station  for the (CSV)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 Fig-1. Lower panels (C and D) normalized bloom index for cell counts for the same period (as described in Section 2.2), with (C) as after neighbor infilling, and (D) as before the filling. Black Xs on the X-axis indicate months with no observations available. Markers for the years are for January 1.(A) after filling to reduce missing data, and (B) data prior to the filling process. If a bin did not contain a sample, but the bins immediately adjacent in time and/or space did have samples, the empty bin was assigned (filled with) the average concentration of the adjacent bins. Color-coding represents maximum cell concentrations observed within each month in the grouped 0.2° latitudinal bins. Blooms were classified into 5 categories, <5,000 (light blue gray), >5,000, >50,000, >100,000, and >1,000,000 cells L(TIFF)Click here for additional data file.S3 FigA-D labels are the same as for (TIFF)Click here for additional data file.S4 FigAnalogous to the bloom year index, the annual calendar bloom index was normalized by the maximum of the calendar year blooms and scaled to be 0–10 . Black Xs on the X-axis stand for bloom years with no available observations.(TIFF)Click here for additional data file.S5 Fig-1 and (B) shows >1,000,000 cells L-1. Color coding represents the percentage of years that the latitudinal bin had a concentration above the respective threshold . Numbers in each bin are the number of years (maximum 25). Gray indicates samples collected, but below the threshold. White with an X indicates no samples were ever collected in that latitudinal bin during that month of the year. X-axis runs from August to July to correspond to the bloom year.(A) shows the frequency for > 50,000 cells L(PNG)Click here for additional data file.S6 FigThe respiratory irritation index was defined by station days for each irritation condition . This is an analog to the bloom-year respiratory irritation of (TIF)Click here for additional data file.S1 TableThe indices were calculated from the data sets in the table using the following formula: 10 × sum of latitudinal bins or beach-days / Maximal value of latitudinal bins or beach-days. Detectable concentration of cells refers to “low”, “moderate”, and “high” as described in the text. As an example, if a month had 3 bins in low, 2 in moderate, and 1 in high, the index  for the month would be 4.6, namely 10 × (3+2+1)/13, and the value for each category would be 2.3 (low), 1.5 (moderate), and 0.8 (high).(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


Zea mays) mutant, endosperm breakdown1 (enb1), in which the typically persistent endosperm (PE) was drastically degraded during kernel development. ENB1 encodes a cellulose synthase 5 that is predominantly expressed in the basal endosperm transfer layer (BETL) of endosperm cells. Loss of ENB1 function caused a drastic reduction in formation of flange cell wall ingrowths (ingrowths) in BETL cells. Defective ingrowths impair nutrient uptake, leading to premature utilization of endosperm starch to nourish the embryo. Similarly, developing wild-type kernels cultured in vitro with a low level of sucrose manifested early endosperm breakdown. ENB1 expression is induced by sucrose via the BETL-specific Myb-Related Protein1 transcription factor. Overexpression of ENB1 enhanced development of flange ingrowths, facilitating sucrose transport into BETL cells and increasing kernel weight. The results demonstrated that ENB1 enhances sucrose supply to the endosperm and contributes to a PE in the kernel.Development of the endosperm is strikingly different in monocots and dicots: it often manifests as a persistent tissue in the former and transient tissue in the latter. Little is known about the controlling mechanisms responsible for these different outcomes. Here we characterized a maize ( Cell wall ingrowths of maize basal endosperm transfer layer cells are synthesized by a cellulose synthase complex containing ENB1 that enhances sucrose import, sustaining a persistent endosperm. Zea mays), the endosperm is a persistent tissue that accumulates large amounts of nutrient reserves, primarily starch, and ultimately occupies the largest portion of the mature seed , the endosperm is a transient tissue and is largely consumed during embryo development, leaving one layer of cells at maturation  that increase the surface area of the plasma membrane (PM), creating a high rate of transport flux . Cytologendosperm breakdown1 (enb1), a novel maize mutant showing endosperm breakdown during kernel development. We report positional cloning of enb1 and show it encodes a ZmCESA5. Cytological and biochemical analyses showed the nonfunctional ZmCESA5 decreased nutrient uptake from maternal tissue, creating a degraded endosperm (DE) in the kernel. Moreover, overexpression of wild-type (WT) ZmCESA5 increased kernel weight, suggesting it as a potential target for yield improvement.Here we characterized 5512K was obtained from the Maize Genetics Cooperation Stock Center. This stock was crossed into the W22 inbred line, where F2 ears displayed 1:3 segregation for mutant versus WT kernels . In WT, both the endosperm and embryo enlarged progressively during kernel development  exhibits a higher expression level than that of ZmCESA4 and ZmCESA9 throughout kernel development  of developing kernel and found ENB1 was expressed in all of them, with higher expression in the endosperm and pericarp than the embryo   using 15 DAP W22 kernels. A remarkably strong hybridization signal was detected in BETL cells, while weak signals were detected in other endosperm cells (Reverse transcription-quantitative PCR (RT-qPCR) analysis indicated e kernel . We exame embryo . During –30 DAP) . To inverm cells .Allium cepa) epidermal cells. The two signals highly overlapped  affects UDP-Glc binding. Serial concentrations of UDP-Glc were titrated against 100-nM of ENB1G780R CatD, and the interaction signals of the ENB1G780R CatD and UDP-Glc were detected (G780R CatD increased the equilibrium dissociation constant (dK) with UDP-Glc , BETL9, and Transfer Cell Response Regulator1 (TCRR1) by RT-qPCR. The decreased expression levels of these genes are consistent with a defective BETL cell phenotype in enb1  were identified  analysis showed downregulated DEGs correspond to four major GO terms . In maiz in enb1 . By tranb1  and Sucrose Transporter1 (SUT1)  . We randnterface , indicatmeasured . The res with WT . Intriguand enb1  and 6, Eat of WT .enb1 exhibited deeper and more extensive staining, especially at 18 DAP, indicating endosperm cells of enb1 manifested more widespread cell death /ZmYUC1, encoding a rate-limiting enzyme in auxin synthesis , MAPK3, MAPKK2, and SNF1-related protein kinase β1 were substantially increased in enb1 embryos  or 3% sucrose , encoding a key transcription factor involved in the differentiation and phenotypic maintenance of BETL cells . DNA mobility shifts were detected by EMSA  transient transcriptional activity assay in maize leaf protoplasts. We used the 35S cauliflower Mosaic Virus (CaMV) promoter to drive expression of ter gene . A signiter gene , indicatng motif . These rENB1 driven by its native promoter  to investigate the effects of elevated expression of ENB1 on endosperm development. ENB1 expression in OE endosperms was elevated both in RNA and protein levels compared with WT  impairs binding of UDP-Glc and reduces cellulose content in enb1 endosperm , auxin induces the deposition of reticulate ingrowths, making adaxial epidermal cells of cotyledons trans-differentiate into transfer cells  predicts that the promoter of ENB1 contains auxin responsive cis-elements (“TGTCGG” and “TGTCTC”) for auxin response factors  adjacent to the scutellum (Sc) of the embryo is enriched with putative sugar transporters  for ARFs, suggesting that they could be regulated by auxin. Therefore, we speculate that enhanced auxin signaling from the enb1 embryo may act at the embryo/endosperm interface, upregulating the expression of sugar transporters to enhance the sugar supply from the endosperm to the growing embryo (Rosa hybrid), auxin also regulates sucrose transport through a RhARF7–RhSUC2 module in the abscission zone  5512k (enb1) mutant was obtained from the Maize Genetics Cooperation Stock Center. enb1 was crossed into the W22 genetic background, and kernels were harvested from self-pollinated +/enb1 ears. Root, stem, the third leaf, tassel, silk, husk, and ear tissues were harvested from at least three W22 plants at the V12 stage as previously described (The maize (2O [v/v]), substituted with xylene, and eventually embedded in Paraplast Plus . The 8-μm sections were stained with 0.1% (m/v) toluidine blue  and imaged with the digital microscope Pannoramic MIDI .Developing kernels were freshly collected and prepared for paraffin sectioning. Briefly, these kernels were fixed with 3.7% FAA (3.7% (v/v) formalin, 50% (v/v) ethanol, and 5% (v/v) acetic acid), dehydrated with gradient ethanol  strain EHA105, and maize transformation was performed using immature zygotic embryos of the Hi-II hybrid (pApB) as described previously  nonredundant protein sequences database. AA sequences were aligned by the MUSCLE method, and a phylogenetic tree was constructed by the neighbor-joining method in the MEGA-X software package. The evolutionary distances were computed using the Poisson correction analysis. The bootstrap method with 1,000 replicates was used for testing the reliability of the interior branches of the phylogenetic tree.ENB1 was used for designing the probe. For the SWEETs and SUT1, the fragments including the part 3′-UTR sequence were used for designing the probe. These antisense and sense probes were synthesized and labeled using the DIG RNA Labeling Kit (SP6/T7)  according to the manufacturer’s instructions. The 15 DAP kernels of the W22 inbred line were collected and prepared for paraffin sectioning. The 8 μm sections were hybridized with the probes, and then reacted with Anti-Digoxigenin-AP , and ultimately detected with NBT/BCIP . Relevant primer sequences are given in mRNA ISH was performed as described previously with minor modifications . The CESENB1 was cloned into the transient expression vector pSAT6-EYFP-N1. Transient expression assays in onion (A. cepa) were performed as described previously (The full-length open reading frame (ORF) of eviously . The fluThe 15 DAP W22 kernels were freshly collected and quickly cut into small pieces (1–2 mm × 1–2 mm). Approximately a 300-mg sample was used for the fractionation with the Minute PM Protein Isolation Kit for Plants  according to the manufacturer’s instructions. All fractions were examined using the corresponding marker antibodies to confirm the success of fractionation.ENB1 ORF corresponding 81–250 aa was cloned into the pGEX-4T-1 vector  for antibody production. The recombinant glutathione S-transferase (GST)-ENB1 was expressed in Escherichia coli Rosetta (DE3) cells by adding 0.5 mM of isopropylthio-β-galactoside (IPTG) when the optical density at 600 nm (OD600) of these cells reached 0.6. The GST-ENB1 was purified with the ÄKTA purification system . The anti-ENB1 was produced in rabbits according to the standard protocols of ABclonal Technology.The 241- to 750-bp region of the + ATPase antibody  was used at 1:5,000, and the anti-BIP antibody  was used at 1:1,000.Proteins extracted from developing endosperms were separated by sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS–PAGE) and then transferred to a polyvinylidene difluoride (PVDF) membrane . Primary and secondary antibodies were used to recognize the target protein attached to the PVDF membrane. The signals were visualized with the SuperSignal West Dura Extended Duration Substrate  at the Tanon 5200 chemiluminescence imaging system . Purified anti-ENB1 antibody was used at 1:1,000, the anti-Tubulin antibody  was used at 1:5,000, the anti-Histone H3 antibody  was used at 1:5,000, the anti-HG780R (enb1), as described previously with minor modifications  that contains an N-terminal His tag and a soluble tag of trigger factor (TF) chaperone. The recombinant His-TF-ENB1 CatD or His-TF-ENB1G780R CatD was expressed in E. coli Rosetta (DE3) cells by adding 0.5 mM of IPTG when OD600 reached 0.8. Recombinant proteins were purified with the BeaverBeads IDA-Nickel  and then labeled with the Monolith Protein Labeling Kit RED-NHS 2nd Generation . The microscale thermophoresis assays were conducted using a Monolith NT.115  machine. The serial concentrations of UDP-Glc were titrated against 100 nM of His-TF-ENB1 CatD or His-TF-ENB1G780R CatD protein in the optimized buffer . Each protein was labeled 3 times for three independent tests. All data were analyzed using the MO. Affinity Analysis version 2.3 software. Relevant primer sequences are given in The CatD of ENB1 or ENB1Ten developing endosperms were dried and ground as one biological replicate, then 20 mg powder was used for preparing alcohol-insoluble residues (AIRs) of the CWs. De-starched AIR samples were produced as described previously . Crystal−1 of 2, 4-dichlorophenoxyacetic acid. All medium was adjusted to pH 5.8 before the addition of 3% (m/v) or 15% (m/v) sucrose as well as the agar (5.5 g L−1). About 10 mg L−1 Streptomycin sulfate was filter-sterilized into all media after autoclaving. The kernels were cultured in a dark chamber at 28°C for 10 and 20 days.Developing kernel in vitro culture was performed as described previously with minor modifications . Briefly13C-sucrose , which was prepared as described previously . The samples were freeze-dried, ground, and analyzed for the 13C/12C-isotope ratio using isotope ratio mass spectrometry Isoprime 100 . 13C-labeling abundance was calculated for the embryos and endosperms, respectively.The developing kernels were cultured in a nutrient solution including g for 5 min at room temperature, then the ethanol supernatant was dried and re-dissolved in the sterile H2O for ion chromatography analysis. The sugar concentrations were determined using the Dionex ICS-5000+ chromatography system . The diluted samples were filtered through a 0.1-μm syringe filter and then separated on a Dionex CarboPac PA10 BioLC column (4 × 250 mm) . The flow rate was 1-mL min−1 and the column temperature was 35°C.Sugars  from developing endosperms were extracted as described previously with minor modifications . Brieflyenb1 were pooled for extracting total RNA with an RNAprep Pure Plant Kit . Three biological replicates were made from the kernels of three independent ears. cDNA libraries were constructed following the Illumina standard protocols and sequenced using an HiSeq X Ten platform  by Annoroad Gene Technology. Differential gene expression analysis was performed essentially as described previously (Q < 0.05) were identified as significant DEGs. The DEGs were functionally annotated and enriched using GO analysis  was used as an internal control. Relevant primer sequences are given in RT-qPCR was conducted using SuperReal PreMix Plus  with an ABI 7500 Real-Time PCR System  or a CFX96 Real-Time PCR System . Three independent RNA samples from the kernels of three F2 ears were used as biological replicates. The expression of maize enb1 kernels were obtained from the same segregating ear at 15 and 18 DAP, respectively. The kernels were cut along the longitudinal axis by hand, and the center sections were stained in 0.1% (w/v) Evans blue for 2 min. After washing the stained sections with water for 30 min, the consistently stained sections were observed using a light microscope SZX7 .Viability staining was performed as described previously with minor modifications . Fresh WMRP1 was cloned into the pCold-TF DNA Vector . Recombinant His-TF-MRP1 was expressed in E. coli BL21 (DE3) cells by adding 0.1 mM IPTG when OD600 reached 0.8. His-TF-MRP1 and His-TF (negative control) were purified with BeaverBeads IDA-Nickel  and used for EMSA. EMSA was performed as previously described with minor modifications (The full-length ORF of MRP1 was constructed into the pHB overexpression vector to generate the effector. The WT or mutated promoter of ENB1 (–565 bp from the transcription start site) was constructed in the pGreen II 0800-LUC vector that contains the firefly LUC coding sequence to generate the reporter, respectively. The Renilla LUC (REN) gene driven by the CaMV 35S promoter in the pGreen II 0800-LUC vector was used as the internal control. Mesophyll protoplasts of maize leaves were isolated from 12-day-old etiolated W22 seedlings as described previously ; MRP1 ; MN1 ; SWEET4c ; BAP2 ; BETL9 ; TCRR1 ; SWEET4b ; SWEET6a ; SWEET16 ; SUT1 . RNA-Seq data that support the findings of this study have been deposited in the NCBI SRA database under the accession number PRJNA681735.The following materials are available in the online version of this article. Phenotypic features of the maize enb1 mutant. CRISPR/Cas9-based mutant of ENB1. Phylogenetic relationships and expression pattern of maize CESAs. mRNA ISH of the ENB1 using the sense probe. Substrate binding assay of His-TF (negative control) to substrate UDP-Glc. enb1 impairs the development of BETL cells. enb1 reduces starch synthesis in the endosperm. enb1 upregulates the expression of genes encoding hydrolase, sugar transporter, and ROS-related protein. Low sucrose supply downregulates the expression of genes involved in starch and auxin synthesis. ENB1 overexpression enhances the endoreduplication of endosperm cells.. List of gene annotation information of all eight genes in the mapping interval.. Alignment file used for the phylogenetic analysis shown in . Newick format of the phylogenetic tree shown in . Alignment file used for the phylogenetic analysis shown in . Newick format of the phylogenetic tree shown in . Significantly DEGs of enb1 endosperms compared with WT endosperms at 15 DAP.. GO terms of downregulated DEGs in enb1 endosperms.. GO terms of upregulated DEGs in enb1 endosperms.. Significantly DEGs of enb1 embryos compared with WT embryos at 15 DAP.. GO terms of upregulated DEGs in enb1 embryos.. List of primer sequences used in this study.. List of methods and parameters of statistics used in this study.. Mobility of ENB1-EYFP particles.. Observation of SWEET4c-EYFP fluorescence signals.koab312_Supplementary_DataClick here for additional data file.


We analyzed edible potato starch and observed the interaction between its granular structure and water molecules. We studied the changes caused by gelatinization during heating and stirring using microscopy, micro‐FT‐IR spectroscopy, and X‐ray scattering techniques. A wide range of spatial scales was revealed using these various techniques. The rate of gelatinization varied significantly and was dependent on the starch concentration. The process of adsorption of water on starch molecules was studied using the humidity‐controlled FT‐IR spectroscopy technique. Furthermore, by comparing the X‐ray scattering profiles of dry and wet granules, the 9‐nm repeat “cluster” structure was studied. A gradual collapse of the granules occurred during the processes of heating and stirring. A clustered smectic structure and a smectic‐like structure were observed in the opaque gel after gelatinization. Upon further heating, a transparent gel was obtained after the melting of the cluster. We analyzed edible potato starch and observed the interaction between its granular structure and water molecules. A wide range of spatial scales was revealed using various techniques such as X‐ray scattering and FT‐IR measurements. We could succeed gelatinization and gelation process with a wide spatial scale. At the atomic level, the packing of the crystal structure of starch can be classified as either monoclinic (A‐type) or hexagonal (B‐type) packing of double helices of amylopectin or amylose chains , to better understand the process of starch gelatinization.In this study, the evolution of the nanocrystalline structure of native potato starch granules was revealed using the simultaneous small/wide‐angle X‐ray scattering (SAXS/WAXS), ultra‐small‐angle X‐ray scattering (USAXS), and Fourier transform‐infrared (FT‐IR) spectroscopy techniques. The results were quantitatively correlated with the corresponding changes in the characteristics.22.1® films for X‐ray scattering measurements. First, to quantitatively evaluate the process of gelatinization, potato starch dispersions of various concentrations were prepared, and the changes in shape, hardness, and transparency with temperature and time were recorded using various techniques.Native starch powder  samples were purchased from a local supermarket. Distilled water was used to prepare the samples. The powder samples were used at various humidity levels. The dry powder and hydrated slurries under excess water were placed in a 0.5‐mm‐thick sample cell sandwiched between KaptonFigure 2.2The optical microscopy technique was used to study the samples using a Keyence VW‐5000 microscope  equipped with a high‐speed CCD camera . The camera lengths were 750 and 110 mm for SAXS and WAXS, respectively. A Pilatus 1 M  detector was used, with a q range of 0.15 to 1.5 nm‐1 for SAXS and 3.5 to 25 nm‐1 for WAXS; q is the magnitude of the scattering vector and is defined as follows:SAXS and WAXS measurements were performed on a Nano‐viewer system  at a wavelength of 0.154 nm  with a q range of 3.5 to 23 nm‐1 for WAXS were used.The time‐resolved SAXS and WAXS measurements were performed using the BL40B2 beamline  at a wavelength of 0.10 nm  was used. The maximum wavenumber resolution was 0.0063 cm‐1. An in‐house humidity control cell connected to a humidity generator  was installed in the IR microscope of the BL43IR beamline. A 1‐mm‐thick barium fluoride was used as the IR window , nonuniform aggregates are not observed, and gelatinization occurs directly from the suspension state. In this case, expanded amylopectin chains might have difficulty in overlapping with each other. When the networks overlap, gelatinization occurs. This network structure can spread throughout the entire system. The opaque glue (sol state) could be observed. Further heating resulted in the formation of transparent glue, that is, the micron‐scaled density fluctuations disappeared. At low starch concentrations, slow gelatinization ensues, which can be attributed to the slow diffusion of the amylopectin molecules. Therefore, gelatinization significantly helps in the diffusion of the amylopectin molecular chains and network formation. Furthermore, the heating and stirring times of the transparent glue (the other sol state) increased at lower starch concentrations. The transparent glue is formed by diffusion. For a more detailed analysis of gelatinization from starch granules, their structural formation from water swelling is analyzed using the wide‐scaled structural analysis method.Figure Figure q values of 4.0, 7.9, 10.7, 12.1, 14.0, 15.8, 17.0, and 18.6 nm‐1; these values agree with those reported in a previous study  decreased  is observed, with a corresponding correlation length of 8.27 nm (the 9‐nm repeat structure that is a cluster in the amylopectin molecules). After swelling, the peak shifted to the low‐q region  in the wet starch sample. The peak became clearer and the peak intensity increased. This suggested that the water molecules could be absorbed into the amorphous region between the crystal lamellae. Furthermore, we attempted to evaluate the shape of the amylopectin molecules  from the slope. The scattering intensity decreases with increasing q, in accordance with the power‐law formula expressed below in Equation  ~ q−3.9. The scattering profile originates from the smooth interface as ds = 2.1. This interface is believed to be derived from micron‐scale aggregates of amylopectin, such as those in dry granular samples.When 3 ≤ Analysis of the results obtained using the SAXS technique revealed that the granular starch samples expanded by ~114% from the 9‐nm repeat structure. Moisture content obtained using a heat drying type moisture meter  was found to be ~50% after 24 hr of absorption at 25°C. This is consistent with the moisture content evaluated based on the changes in the long period length in rice starch  was used for sample analysis.3.2‐1 .We analyzed the structural features of varying concentrations of starch suspensions, aggregates, and gels. Initially, we focused on the evolution of the WAXS and SAXS profiles with the heating and stirring times because they can be measured for crystals and higher‐order structures. Figure q = 4.0 and 12.4 nm‐1 are observed. In other words, the starch gel has a crystalline structure at room temperature, and the crystallinity decreases with increasing heating and stirring times. These results suggest that the amylopectin crystals are likely in their molten form during heating and stirring. In Figure q = 0.67 nm‐1 and L = 9.38 nm  and 180 s (nonuniform aggregates), as shown in Figure q, in accordance with the power‐law formula expressed in Equation  and the opaque gel state (240 s), the k‐value becomes approximately 2.4. At this stage, the collapse of starch powder is initiated. After the powder disappears, the gel becomes transparent, and the k‐value becomes 1.6 . In our study, we have focused on the scattering profiles of the gel state. The k‐value was assumed to depend on the scattering of molecular networks, which might be the diffusion‐limited aggregation cluster. For example, the formation of a 2D diffusion‐limited aggregation cluster presented by Anitas ‐linked glucose linear chains and α(1–6)‐linked branch points. Amylopectin molecules have many branches , measures the total mass of the object. Rg is a size parameter and may have a simple relationship with the geometric size. Analysis of the fit curve  through Rg2=R22, where R = 90.2 nm.Here, the forward scattering, e Figure  reveals 3 . This result suggests that an amylopectin molecule exhibits 100‐nm‐scaled fluctuations. A smaller correlation length, ξ, was observed under conditions of low starch concentration (0.024 g/cm3) because under conditions of high starch concentration (0.167 g/cm3), the 9‐nm repeat structure would be not observed due to scattering derived from the cross‐linked points (as the network structure grows due to gelatinization).The additional terms involving 3.5Figure 4Edible potato starch was studied to understand the interaction present between the granular structure and water molecules. The study was also conducted to understand the changes in the gelation of amylopectin over a wide spatial scale. The dependence of gelation on the potato starch concentration was studied. The gelation rate decreased as the concentration decreased. To evaluate the interaction of amylopectin with water, the humidity dependence of the starch grains was evaluated using the humidity‐controlled FT‐IR spectroscopy technique. The adsorption of water resulted in an increase in the intensities and a shift to a lower wavenumber region for the adsorption of amylopectin molecules. Furthermore, the results obtained using the SAXS technique (during the study of the suspensions) revealed that the phase of the 9‐nm repeat structure changed from nematic‐like to smectic‐like. This can be attributed to the presence of large amounts of water molecules in the amorphous region of the interlamellar amylopectin crystals. Further heating of the starch granules resulted in the gradual collapse and change of nonuniform aggregates and the opaque gel. Further heating and stirring resulted in the formation of a transparent gel. Analysis of the SAXS profiles revealed that immediately after heating, a highly disordered surface structure was formed for the suspension. The grains started to break up from the nonuniform aggregates. In this case, the 9‐nm repeat structure was observed on the nonuniform aggregates and the opaque gel, which indicated the correlation of the lamellar crystals even in the opaque gel state. The correlation length did not change with heating. In other words, only the size of the lamellar crystal width decreased. In the case of the transparent gel, the scattering exponent was 1.59 and the structure was a 2D diffusion‐like cluster. The structure was precisely determined using the USAXS technique. The 13‐nm‐size clusters were observed to form a network of a 2D diffusion‐like cluster structure of size 180 nm. Thus, the gelation of starch was efficiently studied.The authors have no conflicts of interest directly relevant to the content of this article.Supplementary MaterialClick here for additional data file.


Cucumis melo var. makuwa Makino) has become a widely planted horticultural crop in China especially in recent years and has been subjected to the grafting technique for the improvement of cultivation and stress resistance. Although grafting has a long history in horticulture, there is little known about the molecular mechanisms of the graft healing process in oriental melon. This study aims to reveal the molecular changes involved in the graft healing process. In the present work, anatomical observations indicated that the 2, 6, and 9 DAG were three critical stages for the graft healing and therefore, were selected for the subsequent high-throughput RNA-seq analysis. A total of 1,950 and 1,313 DEGs were identified by comparing IL vs. CA and CA vs. VB libraries, respectively. More DEGs in the melon scion exhibited abundant transcriptional changes compared to the squash rootstock, providing increased metabolic activity and thus more material basis for the graft healing formation in the scion. Several DEGs were enriched in the plant hormone signal transduction pathway, phenylpropanoid biosynthesis, and carbon metabolism. In addition, the results showed that concentrations of IAA, GA3, and ZR were induced in the graft junctions. In conclusion, our study determined that genes involved in the hormone-signaling pathway and lignin biosynthesis played the essential roles during graft healing. These findings expand our current understandings of the molecular basis of the graft junction formation and facilitate the improvement and success of melon grafting in future production.Oriental melon ( Cucumis melo var. makuwa Makino) is a high-value horticultural crop. However, during the actual production of melon, problems such as obstacles from continuous cropping and soil-borne diseases have caused yield loss and reduced fruit quality. Plant grafting is a biological phenomenon that involves the physical connection of two plants to produce a chimeric organism , YinQuan No. 1 cultivar, was obtained from the Vegetable Research Institute, Liaoning Academy of Agricultural Science, Shenyang, China.Rootstock: Squash (C. moschata), ShengZhen No. 1 cultivar, was obtained from SHENGDIYA Agricultural High-Tech Company .The splicing method was used for grafting. Grafting was carried out when the scion’s first-true-leaf fully expanded and rootstock’s cotyledon development stage, using the one-cotyledon method . GraftedWe sampled 0.3–0.5 cm stems above and below the graft junction. The samples (2–9 d) were fixed, softened, dehydrated, infiltrated, and embedded in paraffin as described by https://www.biocloud.net/). The concentration of extracted total RNA was measured using the NanoDrop 2000 . The integrity of RNA was assessed using an RNA Nano 6000 Assay Kit for the Agilent Bioanalyzer 2100 system .Screening through paraffin sections, samples were taken from graft junctions at the IL stage (2 DAG), CA stage (6 DAG), and VB stage (9 DAG) with three biological replicates and about 0.6 g per sample. Quality of the total RNA extraction, library construction, and sequencing was verified by the Biomarker Technology Co. according to the standard operating protocols  following the manufacturer’s recommendations and index codes were added for attributing sequences to each sample. PCR was performed with a Phusion High-Fidelity DNA polymerase, Universal PCR primers, and Index (X) Primer, and the PCR products were purified (AMPure XP system) and library quality was assessed on the Agilent Bioanalyzer 2100 system . The seqhttp://cucurbitgenomics.org) to analysis the sequencing raw data of graft junction. The differential expression analysis on two conditions/groups was performed using the DEseq. The DEseq provides statistical procedures for determining the differential expression in the digital gene-expression-data using a model based on the negative binomial distribution. Benjamini and Hochberg method for controlling the false discovery rate were used to adjust the resulting P-values. Genes with an adjusted P-value < 0.01 were considered to be differentially expressed (We separately used Melon (DHL92) v3.6.1 Genome and Cucurbita moschata (Rifu) Genome (xpressed .http://www.genome.jp/kegg/) pathways.We used the GOseq R package based on Wallenius’ non-central hypergeometric distribution  to analy−ΔΔCt method and normalized to the reference actin gene.The accuracy of RNA-seq data was validated using qRT-PCR with selected DEGs. qRT-PCR was performed with three biological replicates for each sample. The first-strand cDNA synthesis was performed using a Prime-Script™ II First Strand cDNA synthesis kit  according to the manufacturer’s instructions. The primer sets for each unigene were designed with Primer Premier 5.0 . qRT-PCRSamples were taken from graft junctions at the IL stage, CA stage, and VB stage with three biological replicates. The content of IAA, ZR, GA, and ABA was measured using the Enzyme-Linked Immunosorbent Assay (ELISA). ELISA kits for these hormones were developed by the China Agricultural University. The accuracy of ELISA kits was validated by GC-MS and HPLC methods. A detailed protocol for determining the hormone content was previously described in P < 0.05. The figures were generated by using Origin 8.0 software.The data are presented as the mean ± standard deviation of three replicate samples. A one-way analysis of variance (ANOVA) was performed using the SPSS 22.0. The significance was determined using ANOVA followed by Duncan’s multiple range tests for experiments at To determine the vital stages of the healing process in oriental melon grafts, we continuously monitored histological changes in sections of the graft junction on the microscope for 8 days following grafting. The graft healing formation was divided into the following three recognizable developmental stages: isolated layer (IL) stage, callus (CA) stage, and vascular bundles (VB) stage  Moore, . At the Following sequence quality control, a total of 125.84 Gb clean data was obtained . The clevs. CA stage, CA stage vs. VB stage) were generated  at IL stage, CA stage, and VB stage. Two DEG libraries . Most DEGs were annotated into three functional categories: biological process, cellular component, and molecular function . Within vs. CA stage  and auxin/indole-3-acetic acid (AUX/IAA) were down-regulated at CA compared with IL, which were then up-regulated during the later stage of grafting. Similar AUX/IAA expression profiles were observed both in the melon scion and the squash rootstock. Furthermore, four GH3 genes  showed a downward trend at the early stage. Accordingly, the content of IAA declined at the CA stage, when the graft healing process was completed, but the IAA content increased , TF (MELO3CO26410), and GID2-encoding gene (CmoCh01G018640) were significantly up-regulated at the late stage. Furthermore, one TF (CmoCh09G007180) was induced at the early stage and then decreased at the VB stage , and Small Auxin Up RNA (SAUR)  . SeveralA (SAUR) . In our A (SAUR) –14. The A (SAUR) .Similar to the results of a previous study in hickory , the auxMELO3C015359.2 and MELO3C024439.2) was induced at the early stage of grafting  gene, however, was up-regulated at the IL stage indicating activation of GA-signaling during the graft healing process in oriental melon. Overall, these results showed that despite GAs likely involvement in the formation of graft healing, their functions could be not as crucial as auxin and cytokinin.GAs play an important role in regulating plant growth by promoting cell proliferation and differentiation . RecentlABA plays essential regulatory roles during plant developmental processes including seed maturation, germination, and stomatal aperture . A few sPAL genes in the squash rootstock and melon scion first decreased and then increased during the graft healing process. It has been previously reported that PAL genes can be regulated at the transcriptional level in response to different abiotic and biological stresses such as wounding, low temperatures, pathogen attack, and nutrient deficiency (PAL genes has been reported during graft healing development (Cellulose and lignin are two important biopolymers within the vascular bundle cell wall, and successful grafting in plants requires the development of a functional vascular system between the scion and rootstock. In a previously published grapevine graft study, cell wall precursors and lignin biosynthesis genes were also enriched in hetero-grafting compared to self-control due to differences in plant wounding and defense responses . In the ficiency . Also, telopment , suggestvs. the CA stage and the CA stage vs. the VB stage libraries. Based on our results, genes related to CTK-signaling transduction pathways in melon scion were up-regulated after grafting, maybe were essential to promote the callus formation. IAA and GA were then induced during the late stage. The activation signals may promote a successful grafting while ABA may be inhibitory for graft healing. In addition, genes related to lignin biosynthesis were up-regulated following grafting, potentially playing a vital role in graft healing formation. Taken together with findings from the transcriptome data, we demonstrated that the melon scion may take more of a leading role by participating more in metabolic activities and providing a more material basis for the graft healing process compared to the squash rootstock. The identification and analysis of key differentially expressed candidate genes will aid in the understanding of the complexity of hormone signaling and lignin biosynthesis during the graft healing process in plants.In conclusion, transcriptome analysis was performed to screen for DEGs involved in the melon/squash graft healing process. A total of 3,263 DEGs were identified from comparisons of the IL stage 10.7717/peerj.12569/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.12569/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.12569/supp-3Supplemental Information 3Click here for additional data file.10.7717/peerj.12569/supp-4Supplemental Information 4Click here for additional data file.10.7717/peerj.12569/supp-5Supplemental Information 5Click here for additional data file.10.7717/peerj.12569/supp-6Supplemental Information 6Click here for additional data file.10.7717/peerj.12569/supp-7Supplemental Information 7Click here for additional data file.10.7717/peerj.12569/supp-8Supplemental Information 8Click here for additional data file.10.7717/peerj.12569/supp-9Supplemental Information 9Click here for additional data file.10.7717/peerj.12569/supp-10Supplemental Information 10Click here for additional data file.10.7717/peerj.12569/supp-11Supplemental Information 11Click here for additional data file.10.7717/peerj.12569/supp-12Supplemental Information 12Click here for additional data file.


Structural and morphological features of graft polystyrene (PS) and polyethylene (PE) copolymers produced by post-radiation chemical polymerization have been investigated by methods of X-ray microanalysis, electron microscopy, DSC and wetting angles measurement. The studied samples differed in the degree of graft, iron(II) sulphate content, sizes of PE films and distribution of graft polymer over the polyolefin cross section. It is shown that in all cases sample surfaces are enriched with PS. As the content of graft PS increases, its concentration increases both in the volume and on the surface of the samples. The distinctive feature of the post-radiation graft polymerization is the stepped curves of graft polymer distribution along the matrix cross section. A probable reason for such evolution of the distribution profiles is related to both the distribution of peroxide groups throughout the sample thickness and to the change in the monomer and iron(II) salt diffusion coefficients in the graft polyolefin layer. According to the results of electron microscope investigations and copolymer wettability during graft polymerization, a heterogeneous system is formed both in the sample volume and in the surface layer. It is shown that the melting point, glass transition temperature and degree of crystallinity of the copolymer decreases with the increasing proportion of graft PS. It is suggested that during graft polymerization a process of PE crystallite decomposition (melting) and enrichment of the amorphous phase of graft polymer by fragments of PE macromolecules occurs spontaneously. The driving force of this process is the osmotic pressure exerted by the phase network of crystallites on the growing phase of the graft PS. Graft polymerization is one of the effective methods for modifying the colloidal–chemical, physical–chemical and performance properties of polymeric materials. Depending on the nature of the monomer, the conditions of graft polymerization and the degree of graft, it is possible to modify the surface layers of polymer material, its volume, and the uniform or gradient distribution of graft polymer over the thickness of a polymer matrix ,2,3,4.Radiation graft polymerization allows the introduction of functional groups into polymers of various kinds by the direct graft polymerization of monomers, such as acrylic acid ,5, vinylAmong various methods of graft polymerization , such as2/N2, alkane/olefin mixtures separation and proton conducting membranes for fuel cells are used.In ,14,15,16However, currently, the studies on influence of graft polymerization parameters on the distribution of graft PS over the cross section of the polymer matrix on PE films of different thicknesses irradiated in air are almost absent. Previously, such studies were carried out only for thin (up to 20 μm) PE films ,17. ThisThis work presents the results of an investigation of the effects of the phase structure, morphology and distribution of graft PS in LDPE films up to 200 µm thick on “post effect” radiation graft polymerization in a wide range of graft degrees (composition of graft polymer). The results of the studies of the phase structure of graft PS in LDPE presented in this work allow us to specify more exactly the mechanism of styrene post-polymerization in a polyethylene matrix.w of 49 kDa, Mw/Mn = 11.4 and a refractive index at 130 °C of 1.4386  were used as objects of the study. The thickness of the films varied, ranging from 20 to 200 μm, and the size of the films was 2 × 5 cm. The samples were not treated before irradiation. The inhibitor was removed from styrene by 30% aqueous solution of KOH, and then washed with water to pH 7, dried over calcium chloride and distilled twice in a vacuum ..27].A distinctive feature of post effect graft polymerization is, as it seems to us, the stepped form of PS distribution curves, which is preserved up to ΔP = 150 wt.%, on the one hand, and the distribution pattern of the graft polymer in the film volume, on the other hand. At irradiation doses of 100 kGy, the distribution pattern of the graft polymer in the sample volume changes from linear a to paraA probable reason for this evolution of the distribution profiles of the graft PS may be related both to the distribution of peroxide groups over the sample thickness and to the changes in the translational diffusion coefficients of monomer and iron(II) salt in the graft PS layer and PE matrix. Indeed, as shown above, the surface layers of PE films always possess a higher concentration of peroxide groups, and hence a higher concentration of graft polymer, regardless of the irradiation dose, styrene concentration and iron(II) sulfate concentration. It should be added that methanol is a precipitator of PS. It follows that the growing PS chains have a different conformation on the surface and in the volume of the film. On the film’s surface, they have the conformation of a coiled ball or globule with occluded growing macroradicals. While in the film volume, where the concentration of methanol is much lower, the growing macroradicals probably have the conformation of a swollen ball. In the first case, quadratic polymerization termination is difficult due to the low mobility of the growing PS chains; in contrast, inside the film, where the growing chains have high mobility, quadratic polymerization termination is possible. However, the linear nature of the macroscopic kinetics of graft polymerization allows us to speak about the occlusion of growing macroradicals throughout the volume of the graft polymer, which is associated with its glassy state.−7 cm2/s), and the near-surface layer, which is ~10 μm thick, does not resist the monomer migration. Thus, it can be assumed that, at this stage, the graft polymerization proceeds in the kinetic region with a constant rate of the process. Since the process is realized under conditions of significant monomer excess, we can assume that the concentration of peroxide radicals is constant, which confirms the above-mentioned assumption about their occlusion by the PS phase. In addition, at this stage of post-polymerization, the transverse dimensions of the samples do not change.We attribute the presence of the graft polymer concentration jump between the surface and the volume to the high value of the styrene diffusion coefficient in the PE matrix cosΘ=Indexes “1” and “2” denote PE and PS phases. Using Equations (3) and (4), as well as the surface wetting data of the graft samples , curve 1The results obtained are in good agreement with the data of structural–morphological studies. Indeed, if the curve of the surface area occupied by PS macromolecules is to be plotted onto the phase diagram of the PE-PS system, then using this dependence one can obtain information about the trajectory of the figurative point of the system during graft polymerization. Obviously, at ΔP ≥ 0.4, there is a phase reversal in the graft surface layer and a PS matrix inclusion (PE) type structure emerges, which is described above .sD—are in favor of denser packing of PS macromolecules in the region of high graft degrees ΔP ≥ 0.4, which indicates a more perfect conformational order of the macromolecules.It is interesting to note that the data on the energy characteristics of the graft layers —the dispm and a small bend in the temperature dependence of the heat capacity in the glass transition region Tg. The heat capacity jump corresponds to ∆Cp = 0.041 J/g∙K and a glass transition temperature of −24.5 °C. The beginning and end of melting correspond to 91 and 150 °C, respectively. The melting point of PE is 135.1 °C. Melting enthalpy  is 189.8 J/g, the crystallinity degree is 54.8%.Additional information about the supramolecular organization of the graft copolymers was obtained by DSC. The heat capacity jump associated with the glass transition of the polymer can be clearly identified in the temperature range of 103 ÷ 119 °C on the thermogram of the first heating of PS. The glass transition temperature of PS corresponds to 107.7 °C. The specific heat capacity jump is 0.329 J/g∙K. The thermogram of the second heating  shows that glass transition is observed in the temperature range of 92 ÷ 112 °C, the value of the glass transition temperature corresponds to 104.3 K. The heat capacity jump at this interval is 0.363 J/g∙K. The comparison of the thermograms presented in The thermograms of the PE–PS16 sample show that, at a heating rate of 5 deg/min, the glass transition is observed in the temperature range of 27 ÷ 40 °C, and the glass transition temperature is 35.2 °C. The heat capacity jump is equal to 0.426 J/g∙K. The melting point of the crystalline part of the copolymer corresponds to 105.4 °C, and the melting enthalpy is 71 J/g. At a rate of 10 deg/min the glass transition interval shifts slightly to a temperature of 22–48 °C, and the glass transition temperature is 47 °C. The heat capacity jump at this interval is 0.472 J/g∙K.PS = 0.49, and then up to 0.8 PS fraction, glass transition is observed in the temperature range of 29 ÷ 50 °C, the glass transition temperature is 42.7 °C, and the heat capacity jump is −0.262 J/g∙K. The melting temperature of the crystalline phase of the copolymer corresponds to 108 °C, the melting enthalpy is 37.33 J/g. The values of melting enthalpy for all samples are presented in With the increase of graft degree  up to ωPAccording to the results of the thermochemical tests, we obtained unusual information about the effect of the composition of graft copolymer on its degree of crystallinity and glass transition temperature. As an example, We assume that the spontaneous destruction (melting) of PE crystallites and the enrichment of the amorphous phase of graft polymer with fragments of its macromolecules occurs in the process of graft polymerization. The driving force of this process is the osmotic pressure exerted by the phase network of crystallites on the growing phase of graft PS. The value of this pressure can probably be estimated from the value of pressure (force) required to expand the sample volume by a degree of swelling and growth of the graft copolymer, which we assume to do in the future.(1)The formation of radicals and graft of styrene to the amorphous PE phase;(2)The formation of radicals and graft of styrene to the PE chains, which are on the surface of the crystallites;(3)The formation of a heterogeneous PS-PE system with a complex phase organization.Thus, based on the results obtained, we can assume that the formation of the graft PE-PS copolymer involves three processes occurring simultaneously:The first process proceeds with a constant composition of the copolymer, which is in the amorphous phase. The second leads to a decrease of the crystallinity degree, and the total degree of graft increases due to this process. The third one is accompanied by the growth of the graft copolymer phase of certain compositions.


Low temperatures (LT) in spring can have a major impact on the yields of wheat in winter. Wheat varieties with different cold sensitivities (the cold-tolerant Yannong 19 variety and the cold-sensitive Yangmai 18 variety) were used to study the responses of the wheat grain starch synthesis and dry material accumulation to short-term LT during the booting stage. The effects of short-term LT on the activities of key wheat grain starch synthesis enzymes, starch content and grain dry-matter accumulation were determined by exposing the wheat to simulated LT of from −2 to 2°C. Short-term LT stress caused a decrease in the fullness of the wheat grains along with decreased activities of adenosine diphosphate glucose pyrophosphorylase , soluble starch synthase , granule-bound starch synthase , and starch branching enzyme  at different spike positions during the filling stage. The rate of grain starch accumulation and starch content decreased with decreasing temperatures. Also, the duration of grain filling increased, the mean and the maximum filling rates were reduced and the quality of the grain dry-matter decreased. The number of grains per spike and the thousand-grain weight of the mature grains also decreased. Our data showed that short-term LT stress at the booting stage caused a decrease in the activities of key starch synthesis enzymes at the grain-filling stage. These changes reduced the accumulation of starch, decreased the filling rate, and lowered the accumulation of grain dry matter to ultimately decrease grain yields. Low temperature stress is a major limiting factor seriously affecting global wheat production and development  and the sensitive variety Yangmai 18 .The experiments were carried out at the experimental base of the Anhui Agricultural University  from November 2017 to June 2018 . The subtropical humid monsoon climate zone was selected as the test site. The mean annual temperature was between 15 and 16°C, the mean annual precipitation was 900–1,000 mm, the annual sunshine total was 2,000 h and the mean annual frost-free period was 228 d. The meteorological data of the wheat growing season in this study including the mean daily temperature and the mean monthly rainfall are summarized in −1, the total nitrogen was 0.81 g·kg−1 and the potassium, nitrogen, phosphorus, and concentrations were 102.4, 23.6, and 152.7 mg·kg−1, respectively. Each pot was filled with 10 kg of sieved soil. The plants were sown on November 2nd, 2018. Before sowing, 75 g of organic fertilizer, 2.26 g of pure nitrogen, and 7 g of compound fertilizer were added to each pot followed by the addition of 1.05 g of pure nitrogen at the jointing stage. For each variety, 120 pots were planted and subsequently buried in the experimental field so that the upper edge of the pots was flush with the ground. The seedlings were thinned so that 10 seedlings were left in each pot. All other field management measures were performed according to the requirements of high-yield cultivation.The experiment used a combination of potted and field planting methods. The pots were 30 cm high and 30 cm in diameter. The potting soil was taken from a 0 to 20 cm cultivation layer. The soil organic matter content was 14.80 g·kgWheat is sensitive to low temperature between the pistil and stamen differentiation stage and the connective stage. Based on the time of the occurrence of LT in spring and observed the stage of spike differentiation with a microscope, 90 pots of each variety were placed in an artificial climate chamber (ACC) for LT treatment on April 3rd, 2018. The plants were housed at temperatures of −2, 0 or 2°C from 19:00 to 07:00, and from 07:00 to 19:00, the temperature was set to 5°C. The processing time was 24 h and the atmospheric humidity in the climate chamber was set to 70%. At the end of the LT treatment, the pots were transferred back to the field to allow the plants to mature.After anthesis, the wheat ears were marked to indicate the same period of growth and the flowering date. From 10 days after anthesis, 15–20 equally sized wheat ears were selected every 5 days. Five of the ears were washed, quickly frozen in liquid nitrogen and stored at −80°C to determine the activity of enzymes related to starch synthesis. The remaining grains were removed from the wheat ears and fixed at 105°C for 15 min. The grains were then dried at 80°C to constant weight and the values were used to determine the starch content and accumulation of grain dry matter. The two wheat varieties tested generally contained 18–20 spikelets per ear. The central six spikelets were termed the middle spikelets, the upper six to seven spikelets were termed upper spikelets, and the basal six to seven spikelets were termed the lower spikelets.From 10 days after anthesis, fresh wheat grains from the LT treatment and control were sampled every 5 days. For each sample, 1–2 grains at the base of the middle spikelet were harvested and observed using a SZX16 stereomicroscope .−1 Tricine-NaOH extract  was added to the samples that were then ground in a mortar at 0°C and centrifuged at 10,000 × g for 10 min (4°C). The supernatants were used to determine the activities of AGPase, SSS, and SBE. The samples were centrifuged and the pellets washed once with 800 μL 100 mmol·L−1 Tricine-NaOH extract. The pellets were then suspended in 100 mmol·L−1 Tricine-NaOH extract to give a crude enzyme solution that was used to determine the GBSS enzyme activity.10–15 grains were sampled and weighed. Five mL of 100 mmol.L−1 Hepes-NaOH (pH 7.4), 1.2 mmol·L−1 ADPG, 3 mmol·L−1 PPi; 5 mmol·L−1 MgCl2, 4 mmol·L−1 DTT]. The mixture was incubated at 30°C for 20 min and the reaction was terminated by placing in boiling water for 30 s. The solution was centrifuged at 10,000 × g for 10 min, then 100 μL supernatant was added to 5.2 μL colorimetric solution . After incubation at 30°C for 10 min, the OD value at 340 nm was measured.The activity of AGPase activity was determined following the method of Nakamura et al. . 20 μL c−1 HEPES-NaOH (pH 7.4), 1.6 mmol·L−1 ADPG, 0.7 mg amylopectin, 15 mmol·L−1 DTT)] and incubated at 30°C for 20 min. The reaction was stopped by heating in boiling water for 30 s followed by cooling in an ice bath. 20 μL of reaction solution  was added and the samples incubated at 30°C for 20 min. The reaction was stopped by heating in boiling water. The samples were centrifuged at 10,000 × g for 10 min and 60 μL of supernatant was added to 40 μL of the reaction solution . The mixture was incubated at 30°C for 10 min and the OD measured at 340 nm.The activities of SSS and GBSS were measured as previously described by Nakamura et al.  and Jian−1 HEPES-NaOH (pH 7.4), 5 mmol·L−1 G-l-P, 1.25 mmol·L−1 AMP, phosphorylase (5.4 units)]. After incubation of the reaction for 30 min at 30°C, 10 μL 1 mol·L−1 HCl was used to terminate the reaction, and 100 μL dimethylsulfoxide and 140 μL of 0.1% I2 and 1% KI were added and the OD value at 540 nm was determined.The activity of SBE was determined according to the methods of Nakamura et al.  and Yangg for 15 min. The supernatant was discarded and the precipitate was dried at 60°C. Distilled water (2 mL) was added to the precipitate, the solution was boiled for 20 min and then allowed to cool before adding 2 mL of 9.2 mol·L−1 HClO4. The samples were shaken for 10 min. Six mL of distilled water was added to each sample before being centrifuged at 5,000 × g for 15 min. The supernatant was decanted into a 50-mL volumetric flask. This process was repeated three times and the volume of each sample was adjusted to a constant volume. 0.1 mL of extract was then added to 4 mL of 0.2% anthrone. The samples were boiled for 15 min and the OD measured at 620 nm.The wheat grains were dried, ground into a powder and passed through a 100-mesh sieve. Eight mL of 80% ethanol was added to 0.1 g of each sample. The samples were then heated in a water bath at 80°C for 30 min, allowed to cool and centrifuged at 5,000 × y = W/[1 + e(A+Bt)] ] was used to associate the variations in grain weight (Y) with the number of days after anthesis (t), where K is the fitted maximum grain weight, and a and b are constants . Curve fitting of starch content and grain dry-matter data were conducted with IBM SPSS Statistics 20  and relevant parameters were calculated. The Pearson's correlation coefficient was used to calculate the coefficients and p-values. Origin 8.0 was used to generate the graphical representations of the data.SPSS 10.0 software  was used to analyze the variance of the data. Data were subjected to analysis of variance (ANOVA), and Duncan's method was used for multiple comparisons among treatments (Short-term LT stress at the booting stage affected wheat grain filling . The fulP < 0.05). For the middle spikelet, the AGPase activity in the Yannong 19 and Yangmai 18 grains reached a peak around 20 days after anthesis and then rapidly declined . At 20 days after anthesis, the activity of SSS in the grains of the middle spikelet of the Yangmai 18 variety decreased by 4.27%, 5.05% and 8.12% after treatments at 2, 0, and −2°C, respectively, and in the Yannong 19 variety, the corresponding SSS activities decreased by 3.27, 4.15, and 7.48%.The activity of SSS in wheat grains at the grain-filling stage showed a single-peak curve and the peak enzyme activity appeared around 20 days after anthesis . After eFor grains at different spike positions (except for the lower spikelets of Yannong 19), the SSS activity decreased after treatment at −2°C. The peak SSS activity for grains in the upper, middle and lower spikelets of the Yangmai 18 variety decreased by 6.38, 8.12, and 2.84%, respectively, compared to the grains at the respective positions in the control group. The peak SSS activity in the upper and middle grains of the Yannong 19 variety decreased by 6.91 and 7.48%, respectively, compared to the grains in the control. The activities of SSS in the lower grains increased slightly compared to the control (1.10%). A comparison between the varieties showed that the SSS activity in Yangmai 18 grains decreased after LT stress, however, the observed changes in the SSS activity of Yannong 19 grains were irregular.P < 0.05). At 20 days after anthesis, after treatment at 2, 0, and −2°C, the GBSS enzyme activity in the grains of the middle spikelet of the Yangmai 18 variety decreased by 8.26, 11.14, and 15.05%, respectively. In the Yannong 19 variety, corresponding decreases of 7.83, 13.40, and 16.38%, were observed compared to the control group.The enzyme activity of GBSS in wheat grains at the filling stage showed a single-peak curve that reached peak activity at around 20 days after anthesis . After aP < 0.05, The GBSS activities of grains at different spike positions after treatment at −2°C were significantly lower than the control group during the whole filling period (P < 0.05). At 20 days after anthesis, the SBE activity in the grains of the middle spikelet of the Yangmai 18 decreased by 10.03, 19.78, and 23.94% at corresponding temperatures of 2, 0, and −2°C, respectively. The Yannong 19 variety showed corresponding decreases of 11.28, 17.56, and 23.77%, respectively, compared to the controls.The observed changes in the SBE activity of wheat grains during grain filling were similar to that of GBSS. The enzyme activity showed a single-peak curve that reached a peak around 20 days after anthesis . After aP < 0.05, The SBE activities in grains at different spike positions after treatment at −2°C was significantly lower than in the control group during the whole filling period (P < 0.05). These data indicated that LT stress at the booting stage reduced the accumulation of starch in wheat grains and lower temperatures had more significant impacts on starch accumulation. The rate of starch accumulation was obtained using logistic equations (P < 0.05). For example, the starch accumulation rate of grains of Yangmai 18 grains exposed to −2°C at the booting stage decreased by 17.69, 21.53, 6.55, 17.24, and 6.09% at days 10, 15, 20, 25, and 30 compared to control grains after anthesis.During wheat grain development, the starch contents gradually increased with time . The staquations  and was R2) of each fitting equation was highly significant (P < 0.01). The maximum theoretical thousand-grain weight of the wheat after short-term LT stress at the booting stage was lower than the control and the grain dry weight decreased concomitantly with the LT treatment. Exposure to short-term LT at the booting stage prolonged the period of incremental filling (T1) compared to the control and differentially affected the rapid filling (T2) and slow filling (T3) periods of the two varieties. Exposure to short-term LT at the booting stage prolonged the filling period (T), delayed the time of the maximum filling rate (Tmax) and reduced the mean filling rate (R) and the maximum filling rate (Rmax) (except for the −2°C treatment of Yangmai 18) compared to the control grains. These data indicated that the main reason for the observed decrease in the accumulation of dry matter in grains caused by short-term LT was a reduction in the rate of grain filling.The logistic equation was used to fit the dynamics of the accumulation of grain dry matter . The coeP < 0.05). However, no significant difference was observed in the number of grains per spike at 2°C compared to the control samples. Further temperature reductions to 0°C and −2°C led to significant differences in the thousand-grain weight compared to the control samples. In the Yannong 19 grains, a notable difference between LT treatments and the controls (P < 0.05), however, the only significant difference in the number of grains per spike was detected at a temperature of −2°C. A short period of LT at the booting stage greatly affected the thousand-grain weight and the impact was greater in the temperature-sensitive Yangmai 18 variety.Exposure to short-term LT stress at the booting stage decreased the final number of grains per spike and the thousand-grain weight . A signiP < 0.05). The AGPase activity was also significantly correlated with the starch content in the Yangmai 18 grains. Also, the activities of GBSS and SBE were positively correlated with starch content and thousand-grain weight. The correlation between the SBE activity in the two different grain varieties and the starch content and the thousand-grain weight was highly significant. The correlation between GBSS activity, the starch content and the thousand-grain weight was highly significant for the Yannong 19, whereas the same correlation in the Yangmai 18 was not significant.The relationships between starch accumulation rate, starch content, thousand-grain weight and the activities of enzymes related to starch synthesis were analyzed and the data presented in In the processes of starch synthesis, a variety of enzymes participate in the metabolism of carbohydrates during endosperm development in cereal  and plastidial disproportionating enzyme (DpeI) are major players in starch biosynthesis under low temperatures  decreased to varying degrees throughout the filling period, whilst the rate of starch accumulation and the starch content gradually decreased with decreases in treatment temperature. The accumulation period of grain dry matter was prolonged but the accumulation rate decreased, and the timing of the maximum accumulation rate was delayed. The number of grains per spike and the thousand-grain weight also decreased.Our data show that in wheat grains, starch synthesis and grain filling are subject to complex regulatory mechanisms during the booting stage. The influence of LT on other key enzymes for starch synthesis and starch components requires further investigation.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.WZ and ZH designed the experiment. WZ conducted the study and wrote the manuscript. YZ, LL, XX, LY, ZL, and BW performed the experiments and helped in sampling and the physiological parameter measurements. SM and YF helped in drafting the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.