The study of high-resolution successional processes within tightly linked microniches is rare. Using the power and relatively low cost of metabarcoding, we describe the bacterial succession and community structure in roots infected with root-knot nematodes and in the nematodes themselves. We reveal separate successional processes in galls and adjacent non-gall root sections, which are driven by the nematode’s life cycle and the progression of the crop season. With their relatively low genetic diversity, large geographic range, spatially complex life cycle, and the simplified agricultural ecosystems they occupy, root-knot nematodes can serve as a model organism for terrestrial holobiont ecology. This perspective can improve our understanding of the temporal and spatial aspects of biological control efficacy. Meloidogyne incognita have a complex life cycle, occurring sequentially in various niches of the root and rhizosphere. They are known to form a range of interactions with bacteria and other microorganisms that can affect their densities and virulence. High-throughput sequencing can reveal these interactions in high temporal and geographic resolutions, although thus far we have only scratched the surface. In this study, we have carried out a longitudinal sampling scheme, repeatedly collecting rhizosphere soil, roots, galls, and second-stage juveniles from 20 plants to provide a high-resolution view of bacterial succession in these niches, using 16S rRNA metabarcoding. Our findings indicate that a structured community develops in the root, in which gall communities diverge from root segments lacking a gall, and that this structure is maintained throughout the crop season. We describe the successional process leading toward this structure, which is driven by interactions with the nematode and later by an increase in bacteria often found in hypoxic and anaerobic environments. We present evidence that this structure may play a role in the nematode’s chemotaxis toward uninfected root segments. Finally, we describe the J2 epibiotic microenvironment as ecologically deterministic, in part, due to the active bacterial attraction of second-stage juveniles.Plant parasitic nematodes such as IMPORTANCE The study of high-resolution successional processes within tightly linked microniches is rare. Using the power and relatively low cost of metabarcoding, we describe the bacterial succession and community structure in roots infected with root-knot nematodes and in the nematodes themselves. We reveal separate successional processes in galls and adjacent non-gall root sections, which are driven by the nematode’s life cycle and the progression of the crop season. With their relatively low genetic diversity, large geographic range, spatially complex life cycle, and the simplified agricultural ecosystems they occupy, root-knot nematodes can serve as a model organism for terrestrial holobiont ecology. This perspective can improve our understanding of the temporal and spatial aspects of biological control efficacy. Meloidogyne) are among the world’s most devastating plant pathogens, causing substantial yield losses in nearly all major agricultural crops  modify the cells in order to establish a feeding site and form the characteristic knots for which they are named. Each knot contains at least one nematode that feeds from a unique cell-type (the giant cells), surrounded by a gall of dividing cortical cells  a sequencing depth of 8,828 was sufficient to capture rare taxa. The bioinformatics analysis carried out for this paper is available as Jupyter notebooks, along with input and output files, in a GitHub repository (https://doi.org/10.5281/zenodo.3731868) , was retained following sequence error correction, chimera detection, and the exclusion of organelle sequences, low-abundance variants, and low-abundance samples . This data set included 150 infected rhizosphere samples, 74 root samples, 61 gall samples, and 21 J2 samples. To describe the succession of bacteria throughout the crop season, we always selected the largest galls in the root sample and an adjacent infected root fragment lacking a gall (here referred to as “infected root”). Among the retained samples, read counts ranged between 8,828 and 107,687, with an average read count of 30,145. According to alpha rarefaction curves , Planctomycetes (18.3%), Chloroflexi (11.7%), Actinobacteria (11.4%), Firmicutes (7.7%), and Bacteroidetes (6.2%). Of all niches, the relative abundance of Proteobacteria was lowest in the rhizosphere soil. Microbiomes of infected root and gall samples contained 33 and 34 phyla, respectively, and were very similar to each other on the phylum level. In both infected root and gall samples, the most abundant phyla were Proteobacteria (42.8 and 44.5%), Planctomycetes (15.9 and 13.4%), Actinobacteria (12.5 and 10.2%), and Bacteroidetes (7.3 and 10.6%). However, differences in Firmicutes  and Verrucomicrobia  were observed between the two niches. Proteobacteria was the most abundant phylum in DNA samples from J2s as well (74.8%), almost dominating the community. However, in contrast with the rhizosphere soil, in infected-root and gall samples, Bacteroidetes (12.7%) was relatively more abundant than Actinobacteria  and Planctomycetes . Verrucomicrobia (1.7%), Firmicutes (1.6%), Chloroflexi (1.4%), Patescibacteria (0.7%), Cyanobacteria (0.5%), and Acidobacteria (0.4%) were also observed in J2s.Bacteria in the system belonged to 37 phyla and varied greatly among niches . The mosProteobacteria was the most abundant phylum in all the sample types, the subphylum Gammaproteobacteria dominated the Proteobacteria community in J2 DNA samples (55.4%), whereas Alphaproteobacteria represented the Proteobacteria in the other niches. The relative abundances of Proteobacteria decreased in all niches as time progressed, except in J2s, where they increased with time. In contrast, Planctomycetes were the most abundant phylum in the rhizosphere soil (17 to 22%) and their relative abundance increased with time. Root samples taken prior to planting, demonstrated notably higher relative abundances of Planctomycetes, which decreased after planting. In J2s, unlike other sample types, the relative abundances of Planctomycetes decreased with time.Although To study the temporal changes in alpha diversity during the growing season, we calculated the total observed ASV, Pielou’s evenness , Shannonq value = 0.008, 0.021, and 0.011 for the observed ASVs, Shannon’s diversity index, and Faith’s PD, respectively), this was likely due to an increase in relative abundance of a previously existing and phylogenetically narrow cohort of ASVs in the galls. J2s, collected from root surfaces starting at time point 2, had lower alpha diversity measures than other sample types, and they decreased further throughout the crop season. The decrease was evident in all indices, indicating that a phylogenetically narrow group of ASVs gradually took over the J2 cuticle community as time progressed.The alpha diversity in gall samples diverged from that of infected roots toward the end of the crop season. Considering all the metrics, which have decreased in time point 5 in comparison with the infected root samples , for both tests and both distance measures, but more discernible for the weighted UniFrac distances . The stronger signal received from the weighted UniFrac distance indicates that this divergence is primarily due to the few bacteria which took over the gall communities, and secondarily due to the introduction of new bacteria.Gall samples , Lechevalieria, Luteolibacter, Pseudomonas, and Saccharimonadales. Only Pseudomonas were relatively more abundant in the root samples, while the rest of the ASVs were relatively more abundant in the gall samples.To identify the ASVs responsible for the differentiation between gall and infected root samples, we repeated the PCoA and Biplot analyses, including only galls and infected root samples from the last time point . Using ti et al. , here reR]).We treated the ratio between the core ASVs and the core taxa of each niche as a relative ecological-drift measure. A core genus without a respective core ASV is represented by different ASVs in different samples of the niche, indicating that the ecological constraints favoring one species or strain over another are not strong. The larger the deficit in core ASVs compared to the core taxa they are assigned to, the lower the ratio and the larger the drift. We based this approach on the notion that ecological drift can increase the genetic diversity among samples that were obtained from one niche . We formR > 1, on average, in their 100% core microbiome , in which the ASV count was lower than the taxa count. In addition, R in the infected root samples was also significantly greater than R in the rhizosphere soil . When considering only the unique taxa in each niche . Consequently, J2s appear to provide a more selective microenvironment than the other niches, but the root and gall microenvironments have an intermediate level of stochasticity, between the rhizosphere soil and J2 niches.With this notion in mind, among all the niches, only J2 had crobiome . The R vch niche , galls aq value < 0.014), indicating that congeneric ASVs in the J2 samples are more closely related than congeneric ASVs in other niches.In addition, we compared the strength of the deterministic forces shaping the communities in the various niches using a phylogenetic approach. For each niche, we computed the pairwise patristic distances between core ASVs sharing a taxon assignment. We expected a very selective niche to sustain congeneric ASVs that are more closely related to one another than congeneric ASVs in a more stochastic niche . J2s disIn addition to the temporal dynamics of alpha and beta diversity, we investigated the temporal change of discrete features (ASVs or taxa) to characterize the bacterial succession in various niches. We focused our investigation on features that we identified as “important” or “dynamic” , based on an analysis of feature volatility . We alsoRhizobium, Devosia, Methylophilus, Herpetosiphon, Sphingomonas, Massilia, Brevundimonas, Flavisolibacter, Cellvibrio, the uncultured Verrucomicrobia IMCC26134, Sphingobium, Bacillus, Rhodocyclaceae, Acidovorax delafieldii, and Microvirga), is gradually displaced by a “late” gall community, including 12 taxa . This displacement already begins and intensifies within the primary nematode life cycle in time points 2 and 3, earlier than a similar process that occurs in the root, for many taxa.A comparison of the three heatmaps reveals largely independent sets of ASVs in each niche, which most explain temporal changes, as illustrated by the Venn diagram . Within Methylophilus, Sphingobium, and Acidovorax delafieldii . Of these, only Sphingobium persisted successfully throughout most of the crop season. Conversely, most of the genera detected in the galls emerged from the rhizosphere soil, and were sometimes displaced by congenerics at later time points. Most notably, A/N/P-Rhizobium were already present in the naive roots, but then were effectively outcompeted by rhizosphere soil congenerics, which then shared the gall A/N/P-Rhizobium community . In the late season gall community, only Luteolibacter clearly emerged from the naive roots and not from the rhizosphere soil . Luteolibacter represented ∼7% of the gall community by the end of the season. ASV 2a4f3fa50 outcompeted other congeneric ASVs to monopolize the Luteolibacter community.Another important aspect of the gall bacterial succession is the origin of taxa. Only a few taxa in the root clearly originated from the naive roots (the root community prior to planting). In the early community, these include https://doi.org/10.6084/m9.figshare.12349349.v1). Since RKN pathogens often actively attract J2s, we carried out an attraction assay, testing the attraction of J2s to each of two isolates, given the isolate and fresh root as options, or the sterile medium and a fresh root as control. The attraction of J2s to one isolate in particular was 10-fold higher than to the root. Sanger sequencing of the isolate (File S1) revealed that its V3-V4 region sequence was identical to Pseudomonas 108751f2 .In 2017, gall bearing eggplant roots were sliced and washed with PBS in an attempt to isolate RKN related bacteria , which increase occurred late in the season  was also detected on J2s in increasing densities at the end of the crop season . In the past, it has been shown that bacteria belonging to this group were able to successfully invade plant hosts by using nematodes as a transition vector  and anteria sp. –58) actihizobium ), nematoinophaga , 60), orlibacter ). Convere season . This Psematodes , 63. Thep season . This cop season . Howevern vector . TherefoRhizobium [Devosia sp. [Microvirga [Rhizobium [Devosia sp. [Microvirga [Sphingomonas [Cellvibrio [Microvirga [Bacillus [Herpetosiphon [Massilia [Verrucomicrobia [Cellvibrio [Sphingobium [Bacillus [Herpetosiphon [Sphingomonas [Massilia [Cellvibrio [Lysinibacillus [Streptomyces [Bacillus [Upon consideration of the most dynamic fractions of the bacterial communities, the processes leading to the result described above are exposed as a gradual community shift . The earhizobium , Devosiaosia sp. , and thecrovirga ), fixinghizobium , Devosiaosia sp. , 69, 70,crovirga , Sphingongomonas , and latllvibrio , Microvicrovirga . and posBacillus ) and bactosiphon , 75, MasMassilia , Verrucomicrobia , 78, Celllvibrio , Sphingoingobium , and posBacillus ). While tosiphon , 83, Sphngomonas , and MasMassilia ), time pllvibrio , Lysinibbacillus , Streptoptomyces , and posBacillus , 88), poSphingomonas, known to include facultative anaerobic species  seems to occur in hypoxic and anaerobic environments, unlike the early season representatives of the order which are aerobic, plant-related bacteria . Eight other genera, which ASVs increased during this time frame, have known anaerobic or hypoxic species  often represent already inactive galls. The most striking characteristic of the late season gall community is a rapid increase in bacteria capable of anaerobic or hypoxic growth. Only ASVs of  species , persistBacillus , 91, Rhoyclaceae , Acidovorovibrio , Pseudoxmexicana , Chitinoinophaga , Steroiddobacter , and a Pdobacter ). Lastlyptomyces –102).Cellvibrio may assist their root penetration . Twenty plants were repeatedly sampled throughout the crop season. At time point 1, root sections were collected prior to planting to represent the preexisting root endophytic community. At each subsequent time point , we collected an entire lateral root branch from each plant, leaving the plant intact for future sampling. In the lab, we collected the rhizosphere soil and identified the largest galls available at the time. We then dissected the gall fragments and additional root segments lacking a gall, which were adjacent to the collected galls. The root segments were up to 3 cm long. In addition, roots were collected from each plant, in order to extract J2s, using the Baermann tray method, following Williamson and Čepulytė  according to the manufacturer’s instructions. J2 DNA was extracted from the filters using a PowerWater DNA extraction kit (Qiagen), following the manufacturer’s instructions. Metabarcoding libraries were prepared as previously described , using a(i) Data processing, taxonomy assignment, and biodiversity analysis. All analyses carried out for the present study are available as Jupyter notebooks in a GitHub repository  Longitudinal feature volatility analysis. Qiime2 feature volatility longitudinal analysis  Core ASV/taxon ratios and tree distances. To evaluate the relative strength of ecological drift among niches, we computed ASV/taxon count ratios (R) within the core microbiome and unique microbiome of each niche and time point. The core microbiome of a given niche at a given time point  consists of either ASVs that occur in all the samples of the group (core ASVs) or genera that occur in all the samples of the group (core taxa). The unique microbiome includes the subset of the core microbiome, which occurs only in that niche, at a given time point.Because ecological drift is expected to increase the genetic diversity among samples , we reliWe therefore infer that if many genera are represented by the same set of ASVs in all the samples  then the conditions in this niche must be very limiting to genetic diversity (deterministic niche), but if many taxa are represented by different ASVs in each sample , then this niche is not limiting to genetic diversity (stochastic niche). The core taxa count to core ASV count ratio is a relative measure and is therefore unitless.R values were computed for each subset, for the core microbiome and the unique microbiome. The distribution of core and unique R values are presented in Core ASV and core taxa were determined by the Qiime2 feature-table plugin separately for several subsets, each containing samples of one niche and one time point, either time point 2, 3, 4, or 6. Only ASVs or taxa that were detected in all the samples of a given subset were included (100% core microbiome). Another data set, containing only the core ASVs and taxa that were unique to each niche, was produced. R values might be influenced by differences in sample sizes among the subsets, we repeated the analysis with a normalized sample size. To normalize the sample size, we constrained the number of samples in each time point. To do that, we identified the niche with the lowest number of samples in each time point and reduced the number of samples in the remaining niches to conform with that number. The resulting R value distributions and the pairwise Mann-Whitney U tests were similar to those obtained with the full data set.Since we suspected that the A genetic signature of congeneric ASV divergence would also be recorded in their pairwise phylogenetic distances. For each group of congeneric ASVs in the core microbiome, a phylogenetic tree was reconstructed, from which we obtained pairwise patristic distances of congeneric ASVs. Then, the distribution of congeneric ASV patristic distances was computed for each subset and presented in Rhizobiales.(iv) Isolation sources of early and late gall community  The following steps were taken to summarize the isolation sources of three Rhizobiales taxa from the gall community, including the group of uncultured Rhizobiales Amb-16S-1323, Devosia spp., and the A/N/P-Rhizobium cluster. For each taxon, all the sequences available on SILVA (https://doi.org/10.6084/m9.figshare.12349346.v1.on SILVA  were dowhttps://doi.org/10.6084/m9.figshare.12349349.v1) revealed that J2s were attracted to the volatiles of a Pseudomonas sp. isolate, which shared its V3V4 region sequence with ASV 108751f28645926db7b461f27b822162. To test the chemical attraction of J2s to the isolate’s volatiles, we carried out attraction assays, according to the method of Williamson and Čepulytė (https://doi.org/10.6084/m9.figshare.12349349.v1). The tip contained either the whole bacterial filtrate (excluding the bacterium) or one of three size determined fractions , in nine replicates per treatment. Then, 1 ml of Pluronic-F127 Tris-MES buffer gel (Sigma-Aldrich) containing ∼50 J2s was added to each well. A dissection microscope was used to record the number of J2s in each tip after 24 h , and J2s were hatched with a Baermann tray, as described by Williamson and Čepulytė  for 48 Čepulytė .PRJNA614519. Data and script are archived as a GitHub release (The data sets generated and analyzed during the present study are available from the National Center for Biotechnology Information BioProject repository under accession number  release , Zenodo  release .


Insomnia is a common, recurrent, and tenacious sleep problem, especially the chronic insomnia. Repetitive transcranial magnetic stimulation (rTMS) at right dorsolateral prefrontal cortex (r-DLPFC) is used in chronic insomnia, and repetitive magnetic stimulation (rMS) at Shenmen (HT7) acupoint may be an alternative approach. However, the efficacy and mechanism of rMS at HT7 acupoint for chronic insomnia has not been confirmed.This is a 3-armed randomized positive-controlled noninferiority clinical trial. We will allocate 45 subjects aged between 18 and 65 years old, diagnosed with initial chronic insomnia over 3 months to 3 groups randomly in a ratio of 1:1:1. Patients in the experimental group will be treated with rMS at HT7 acupoint while the others in the control group will be treated with rTMS at r-DLPFC or waiting treatment. All will be given rMS at HT7 or rTMS at r-DLPFC or no treatment for 10 days, and then received 20-day follow-up. Patients will be evaluated with the insomnia severity index and Pittsburgh sleep quality index for sleep state, Beck Depression Inventory-2nd edition scores for the depression state, Beck anxiety inventory scores for the anxiety state, and Montreal Cognitive Assessment scores for the cognition state before and the 10th day of treatment, 30th day of follow-up; study on mechanisms of rMS will be revealed through the resting motor threshold diversity of the motor cortex before and the 10th day of treatment, 30th day of follow-up. Baseline characteristics of patients will be summarized by groups and compared with Chi-squared for categorical variables, and analysis of variance or Kruskal–Wallis test for the continuous variables. Primary and secondary outcomes according to the measurement times are applicable to univariate repetitive measurement deviation analysis or analysis of variance, or Kruskal–Wallis test.The present study is designed to preliminarily investigate short-term efficacy and mechanism of rMS at HT7 acupoint therapy on chronic insomnia, also to explore the correlation between motor cortex excitability and chronic insomnia. With this research, we are looking forward to find out an appropriate alternative and easy therapy for chronic insomnia individuals compared with rTMS at r-DLPFC.http://www.chictr.org.cn/index.aspx) with the ID ChiCTR1900026844 on October 24, 2019.The trial was registered on Chinese Clinical Trial Registry ( Besides, it may cause daytime fatigue, cognitive impairments , negative emotions, and affect the individuals quality of life.–7 It indicates that hyperarousal is one of the main pathologic mechanisms of CI.Insomnia is a common, recurrent and tenacious sleep problem, adults incidence in the range of 10% to 15%, especially the chronic insomnia (CI).,10 Due to the lack of cultural background and diplomats in China, the implementation of cognitive behavioral therapy in basic hospitals and general hospitals is rarely used at present. Thus, it is essential to select an effective, safe, no side effects, and no addiction sleep method. Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive neuroregulatory technique in line with the above characteristics, which has been widely used in clinic by reducing cortical excitability in CI patients. Low-frequency (1 Hz) rTMS at bilateral frontal or parieooccipital regions is recommended for sleep disorders in the Chinese experts consensus on rTMS (level of evidence: level II/III). However, the rTMS for patients with intracranial metal implants, stents, glaucoma, and hypertension is limited. In traditional Chinese medicine (TCM), insomnia is an appropriate disease in the acupuncture spectrum of diseases. Shenmen acupoint (HT7) is the yuan acupoint of Heart-Channel, the most frequently selected for insomnia. Acupuncture at HT7 acupoint can activate related brain regions highly associated with improving sleep, emotional, and cognition.,15 Thus, the problem of acupuncture therapy is that its manipulations are difficult to replicate, and some patients cannot tolerate repeated pain stimulation. Studies have shown that the effects of repetitive magnetic stimulation (rMS) at acupoints can be quantified, similar to acupuncture effect, noninvasive and painless. In particular, low frequency (1 Hz) rMS at HT7 acupoint can make brain activity in good order and reduce brain excitability for the healthy. Furthermore, low frequency (1 Hz) rMS at HT7, PC6 and SP6 can be also good for the subhealth insomnia ones in enhancing interaction between brain regions, increasing transmission speed and efficiency between brain networks, and improving brain cognitive function. However, there are few clinical studies on low frequency (1 Hz) rMS at HT7 acupoint for CI.The short-term efficacy of sleep agents has been proved, but they often lead to a series of side effects, like daytime dysfunction, sleep driving, abnormal behavior, and depression deterioration. Moreover, it does exist addiction, which might make patients resistance and low compliance for long-term users.However, compared with rTMS at right dorsolateral prefrontal cortex (r-DLPFC), no sufficient clinical trial data and solid evidence could confirm whether acupoint could yield certain efficiency in treating CI and how it works. It is necessary to verify the effectiveness and mechanism of rMS at acupoint on the sleep quality and cortical excitability from senior quality studies. Now, the evidence about low-frequency rMS at HT7 acupoint for CI is inadequate and must apply further strictly design clinical studies.The primary objectives of this study are to evaluate the short-term efficacy and mechanism of rMS at HT7 acupoint and follow-up on CI preliminarily.22.1This is a single-center, randomized, positive-controlled, noninferiority clinical pilot trial. A total of 54 participants will be randomized into 3 groups at a ratio of 1:1:1. Participants in the treatment group will be treated with rMS at HT7 acupoint. Participants in the control group will be treated with rTMS at r-DLPFC or waiting treatment.The whole study period is 35 days, including 5-day baseline observation, 10-day treatment, and 20-days follow-up. Subjects will be evaluated with scales for clinical efficacy before and the 10th day of treatment, 30th day of follow-up, and monitored by rMS/rTMS for therapeutic mechanism before and the 10th day of treatment, 30th day of follow-up , and registered on 2.32.3.11. according to the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-V), F51.01;Subjects, diagnosed with primary insomnia, insomnia severity index (ISI) scores >7 points,2.;Subjects, diagnosed with initial CI (course of the disease ≥3 months and frequency ≥3 times/week)3.Subjects, aged between 18 and 65 years old, right-handed, male or female;4.Cooperation during examination, without aphasia and severe cognitive disorders;5.Sign the informed consent.2.3.21.Subjects, diagnosed with secondary insomnia, such as mental disorders  or physical diseases  or other nonpathologic factors ;2. high risk of sleep apnea (>3 items in the Stop Bang questionnaire), aphasia and severe cognitive dysfunction (MMSE scores <17 points);With severe depression and anxiety ,3.With severe heart disease, malignancy, kidney, and liver function insufficiency;4.Dependence or abuse of alcohol or drugs;5.With metal foreign bodies  at the treatment sites within 30 cm depth under the skin;6.Participation in any other clinical trial or taking benzodiazepines in recent 2 weeks or receiving TMS, transcranial direct current stimulation, electroconvulsivetherapy, acupuncture and other treatments regularly over the last 1 month;7.Pregnant or lactating women.2.3.31.Violation of the inclusion criteria and clinical trial protocol or fulfillment of the exclusion criteria;2.Do not receive 10 consecutive treatment days or receipt of <20 rMS sessions;3.Serious adverse events;4.Loss to follow-up;5.Withdrawal of consent by the subject or a legal representative;6.Self-replacement of the treatment package that could affect the study results without permission from the investigator.2.4The present study will be conducted in the Shaanxi Province Hospital of Traditional Chinese Medicine.Participants with the diagnosis of CI will be recruited at above-mentioned hospital, who mainly come from hospital wards and clinics. Besides, posters, leaflets, and the routine free clinics will be also helpful. Sure, except these, the hospital websites, WeChat, and Microblogging are powerful advocacy media.2.5Forty-five participants who meet the criteria with informed consents will be selected. The subjects will be randomly divided into 3 groups in a 1:1:1 ratio, namely the experimental group, positive-control group and waiting list control group, 15 cases in each group.2.6This clinical study will be conducted from August 1, 2019 to August 1, 2021.2.7Interventions are selected base on the theory of TCM and expertise. The physicians involved have received their practitioners’ license from China's National Health and Family Planning Commission as well as acupuncture and rTMS clinical skill training, who have worked for more than 3 years. Subjects in experimental group will receive rMS at HT7, and others in control group will receive rTMS at r-DLPFC or waiting treatment. Besides, if the symptoms were severe or do not improve during the treatment or the waiting period, Eszopiclone tablets (3 mg Qn) would be allowed.2.7.12.7.1.1shenmen) acupoint according to the TCM theory. After preparation, test the resting motor threshold (RMT): the participants will take the sitting position, keep the mood stable and the muscles relaxed. During stimulating M1 region, the coil will be tangent to the scalp, and it will be advisable to adjust the coil to get the maximum amplitude and the best repeatability of motor evoked potential. The stimulus intensity will begin from 30% and gradually increase at a rate of 2.5%. The minimum stimulus intensity (RMT) will be the abdominal contraction in the abductor pollicis brevis muscles of contralateral thumb in 5 out of 10-times consecutive stimuli; locate the stimulus area: the stimulation coil will be placed at the left HT7 acupoint   were used. rTMS is applied to treat CI according to the modern neuro-rehabilitation theory. Acupoint is only left HT7 (2.7.22.7.2.1Chinese experts consensus on rTMS (level of evidence: level II/III) and Guidelines for The Diagnosis and Treatment of Insomnia in China. After preparation, test RMT: the measurement is same as the experimental group; locate the stimulus area: the stimulation coil will be placed tangent to the scalp on the r-DLPFC ; set the stimulus parameters: the intensity is selected 100% RMT. Other parameters are same as the experimental group. Participants will be treated 2 sessions per day for 10 consecutive days.Low-frequency (1 Hz) rTMS at r-DLPFC is recommended for sleep disorders in the 2.7.3The participants in the waiting group will not be treated within 10 days during the study period, and then treated same as the positive control group from the 11th day.2.8It could be that patients with epilepsy or headache, scalp discomfort, and tinnitus at stimulating are more likely related to rTMS. Regional skin numbness around the HT7 acupoint occur in patients is probably connected to rMS at HT7 acupoint. With the patients’ diary, all adverse events are to be recorded and measured during treatment and the follow-up period. Serious adverse events should be reported to the principal investigator immediately. All details will be documented, coil location and stimulus intensity adjustment , as well as appropriate medical care will be given at once. For the participants with severe CI during study, they would be administered with Eszopiclone tablets (3 mg Qn). However, if the subjects cannot tolerate the 80% RMT intensity and/or take Eszopiclone tablets more than twice a week, they will be considered as drop outs.2.9The ISI scores for the severity of CI before and the 10th day of treatment, 30th day of follow-up. The RMT for excitability of the motor cortex before and the 10th day of treatment, 30th day of follow-up.2.10 scores for the sleep quality of CI patients, Beck Depression Inventory-2nd edition scores for the depression state, Beck anxiety inventory scores for the anxiety state, and Montreal Cognitive Assessment scores for the cognition state before and the 10th day of treatment. Patients’ diary for tracking their mood, sleep, diet, adverse events, and others during the research. All the dropouts and causes will be documented in case report form.Pittsburgh sleep quality index2.11This study is just a pilot study, which designed for efficacy evaluation and mechanism investigation of targeted therapy preliminarily before and after treatment as well as follow-up period. We will plan to enroll a total of 45 participants in this study.2.12After recruitment, the patients who meet the eligibility criteria would be randomly and equally divided into 3 groups at a ratio of 1:1:1 with random number table method. Each subject will be registered with a unique ID. After the clinical screening and getting the informed consent forms, subjects will be assigned to experimental group (rTMS at HT7), positive-control group (rTMS at r-DLPFC), and waiting-list control group (no treatment) randomly. Each subject will receive the different stimulation forms, even no stimulating, whereas all subjects will be aware of the grouping.2.13Data analysis will be based on intention-to-treat analysis and/or per-protocol analysis principle in the light of data missingness. We will also evaluate the group effect by comparing the analysis results between the above 2 data sets to evaluate robustness of our analytical results.P value <.05 will be considered as significant. Descriptive statistics will be performed with mean, standard deviation, maximum, minimum, and so on by groups and time.All data will be analyzed using SPSS23.0  by 3rd-party statistician. A Baseline characteristics of patients will be summarized by groups and compared with Chi-squared for categorical variables, and analysis of variance (ANOVA)  or Kruskal–Wallis test  for the continuous variables. Primary and secondary outcomes according to the measurement times are applicable to univariate repetitive measurement deviation analysis or ANOVA or Kruskal–Wallis test. If there is a violation of distribution assumption, appropriate transformation will be used.2.13.1We will use univariate repetitive measurement deviation analysis with ISI scores and RMT before and the 10th day of treatment, 30th day of follow-up as the outcomes. A significant effect of group indicates that the ISI scores and RMT are different between groups after intervention.2.13.2Continuous outcome variables including Pittsburgh sleep quality index scores, Beck Depression Inventory-2nd edition scores, Beck anxiety inventory scores and Montreal Cognitive Assessment scores before and the 10th day of treatment will be analyzed with ANOVA or Kruskal–Wallis test. Categorical outcome variables in the patients’ diary, Chi-squared test will be used for comparison between groups.2.13.3Adverse events recorded in the patients’ diary will be analyzed as a multiply variable. The number and percentage of patients with AE will be calculated and compared using Chi-squared test.2.14The reasons of dropouts or withdrawals throughout the treatment and follow-up periods will be fully recorded. To ensure trial quality, the quality monitors will verify all the process details at regular intervals and check the authenticity of the data. Moreover, a 3rd party, scientific research department of Shaanxi Province Hospital of Traditional Chinese Medicine, will be invited to manage the data independently.Since differences among physicians can cause bias, the evaluation of the rating scales in every time will be executed by one assigned physician who has been trained with the same criterion of evaluating. Two physicians responsible for treatment will receive special training about the study and manipulations including TMS use and locations of acupoints before recruitment. To record the attendance and compliance, we make record cards for patients which cover date of treatment, personal information, and their signatures after every treatment.3 The onset of CI is affected by many factors involving age, gender, medical history, stress events, personality traits, inheritance, mental disorders, physical diseases, and so on. Refer to the diagnostic criteria of CI, CI patients who are long-term subjected to insomnia problem, will bring direct or indirect harm to the society. Therefore, according to patients symptoms combined with rating scale, we hope to obtain high quality study data from this preliminary clinical trial that could provide reliable basis to future multicenter research.The CI is a persistent insomnia disease, which the course of the disease is >3 months and frequency more than 3 times/wk. As a noninvasive stimulation technique, rTMS can test changes in motor evoked potential, brain electrical activity, cerebral blood flow, metabolism, and brain functional status from the changes in neural activity. Besides, DLPFC plays an important role in our cognition, decision, and memorization, which is always as an effective stimulating target for the treatment of insomnia and depression, especially low-frequency (1 Hz) rTMS at DLPFC. However, rTMS on the static head directly might be limited with some potential risks like scalp tingling and burning, hearing impairment, even seizure, especially for the ones with metal implants in skull or body. Moreover, it is inconvenient for insomnia patients to receive continuing care in daily life with rTMS at DLPFC. For this, rMS at acupoint on CI may be a promising alternative therapy. Acupoints have been widely used and received in clinical practice in China. Patients in China are usually familiar with acupuncture, and expect to receive acupuncture treatments. Thus, since acupuncture is often regarded as an invasive operation, it is difficult to replicate its manipulations in clinic and design a nonpenetrating sham acupuncture in trial. Hence, aim to improve subjects compliance and achieve acupoint effect, we choose rMS at HT7 acupoint in the experimental group in a high-quality randomized controlled trial. Although studies have showed the efficacy of rTMS for CI,,33 it is still lack rMS at acupoint randomized controlled trial, as well as the relevant mechanism research.The rTMS at r-DLPFC which is chosen as a positive controlled therapy for CI in this study has been recommend by experts consensus.Our protocol is just a pilot study with several limits including the small sample size, open-blinding, and short period of observation time. However, we try our best to attempt to minimize the biases that may influence study results. Finally we intend to demonstrate the hypothesis that rMS at HT7 acupoint as an alternative may be validated for CI.Jie Yuan and Jie Chen designed this study together. Jie Yuan and Hui Wang drafted the protocol. Zhaoxin Wan performed the statistical analysis. Yaling Lei was responsible for the writing revision. All authors read and approved the final manuscript.Data collection: Pei Wang, Fan Luo, Yuan Wang.Formal analysis: Zhaoxin Wan, Yuan Zhao.Funding acquisition: Jie Chen, Jie Yuan.Investigation: Yue Cao.Methodology: Jie Yuan, Yuan Zhao.Project administration: Zucheng Han, Dongling Liu.Writing – original draft: Jie Yuan and Jie Chen.Writing – review & editing: Yaling Lei, Jie Chen.


The characteristic secondary metabolites in tea  are important factors contributing to unique tea flavors. However, there has been relatively little research on molecular markers related to these metabolites. Thus, we conducted a genome-wide association analysis of the levels of these tea flavor-related metabolites in three seasons. The theanine, caffeine, and catechin levels in Population 1 comprising 191 tea plant germplasms were examined, which revealed that their heritability exceeded 0.5 in the analyzed seasons, with the following rank order (highest to lowest heritabilities): (+)-catechin > (−)-gallocatechin gallate > caffeine = (−)-epicatechin > (−)-epigallocatechin-3-gallate > theanine > (−)-epigallocatechin > (−)-epicatechin-3-gallate > catechin gallate > (+)-gallocatechin. The SNPs detected by amplified-fragment SNP and methylation sequencing divided Population 1 into three groups and seven subgroups. An association analysis yielded 307 SNP markers related to theanine, caffeine, and catechins that were common to all three seasons. Some of the markers were pleiotropic. The functional annotation of 180 key genes at the SNP loci revealed that FLS, UGT, MYB, and WD40 domain-containing proteins, as well as ATP-binding cassette transporters, may be important for catechin synthesis. KEGG and GO analyses indicated that these genes are associated with metabolic pathways and secondary metabolite biosynthesis. Moreover, in Population 2 (98 tea plant germplasm resources), 30 candidate SNPs were verified, including 17 SNPs that were significantly or extremely significantly associated with specific metabolite levels. These results will provide a foundation for future research on important flavor-related metabolites and may help accelerate the breeding of new tea varieties. Because they are used to produce one of the three major nonalcoholic beverages worldwide (the other two being coffee and cocoa), tea plants are economically valuable crops that significantly affect society and culture. Similar to other plants, tea can synthesize its own primary metabolites, such as sugars, proteins, lipids, and nucleotides, which can then be used to synthesize secondary metabolites unique to tea plants, including caffeine (CAF), theanine (TN), and catechin components. On the basis of the number of hydroxyl groups on the B ring, the 2,3 isomer on the C ring, and whether the 3 isomer on the C ring is attached to the gallate group, the catechins can be further divided as (+)-gallocatechin (GC), (−)-epigallocatechin (EGC), (+)-catechin (C), (−)-epicatechin (EC), (−)-epigallocatechin-3-gallate (EGCG), (−)-gallocatechin gallate (GCG), (−)-epicatechin-3-gallate (ECG), and catechin gallate (CG). These characteristic substances are responsible for the unique flavors of tea3. Theanine, CAF, and catechins affect the quality of tea, but according to zoological studies, they also have diverse physiological functions. For example, TN has a calming effect and positively influences cognition, CAFs enhance bone metabolism and function as a stimulant, and catechins can protect against liver cirrhosis, lower blood pressure, and function as antimicrobial and antioxidative compounds4.Tea originated in southwestern China and has been cultivated for more than 5000 years5. Because tea is a highly heterozygous woody plant species, breeding new varieties using conventional methods is time consuming and relatively inefficient, which has resulted in a failure to satisfy the public demand for new tea products. Molecular marker-assisted selection for breeding is based on the fact that molecular markers are closely linked to target trait genes. By identifying molecular markers, the presence of genes responsible for target traits can be detected. This process is fast, accurate, and unaffected by material development. Thus, it may be applicable for selecting new tea varieties and improving tea breeding efficiency.Because of the important effects of TN, CAF, and catechins on tea quality and their physiological functions, studies on their synthesis and regulatory pathways are crucial for the development and selection of tea plants with specific TN, CAF, and catechin levels. Previous studies on the metabolic pathways associated with these compounds involving enzymology and omics techniques  have identified some genes related to their synthesis and regulation. However, limitations to the available methods for generating transgenic tea plants have made it difficult to verify and thoroughly analyze the identified functional genes in tea plants and improve tea varieties. Currently, tea plant breeders basically select new varieties through conventional breeding methods, such as by selecting elite plants from wild populations and hybrid progenies for developing new varieties9, and they have been used to investigate tea yield, leaf shape, stress resistance, and secondary metabolite levels. Among these genetic maps, two are related to catechins7, one is related to CAF8, and one is related to TN9. Most of the constructed genetic maps do not include quantitative trait loci (QTLs), which may be related to the size of the maps, the accuracy of QTL mapping, and the time required for phenotypic analyses. Genome-wide association studies (GWASs) have been conducted on major food crops, but relatively few have involved tea plants. Hazra et al. completed an association analysis of 21 agronomic characteristics and the flavor-related components of 23 Dajiling tea resources, ultimately detecting 57 single-nucleotide polymorphisms (SNPs), of which 12 were related to EGCG, 8 were related to flavor, 3 were related to phenolics, 8 were related to reactive oxygen species scavenging, 6 were related to the stomatal index, 5 were related to tannins, and 7 were related to yield10. Wang et al. included 151 resources in an association analysis, which resulted in the identification of 26 molecular markers related to the timing of spring bud flush11. Zhang et al. combined RNA sequencing results for 176 resources and data regarding the levels of catechin components in a correlation analysis, which revealed that CsANR, CsF3′5′H, and CsMYB5 may influence catechin levels12. These studies involving natural populations examined the linkage disequilibrium between marker genes to correlate phenotypic traits with genotypes and detect marker gene loci closely related to the phenotype of interest14. Unlike QTL mapping, this method does not require the construction of a genetic map, there are no significant differences in the parental genotypes when QTLs are mapped, and multiple allelic variations in the same locus can be detected simultaneously. Additionally, genetic analyses are highly precise, even reaching the single-gene level6. To a certain extent, this can compensate for the disadvantage of the genetic linkage mapping method. In the current study, 289 tea plant resources, including two natural populations in a field gene bank, were analyzed. Population 1 was used for the preliminary association study to obtain candidate SNP loci associated with tea flavor-related metabolites. The detected candidate SNPs were verified in Population 2. The data presented herein may provide the foundation for future investigations on the synthesis and regulation of secondary metabolites and for the breeding of new tea varieties.Molecular markers related to specific traits are currently most often obtained via genetic linkage mapping and genome-wide association analyses, with the molecular markers in tea plants primarily identified by genetic linkage mapping. To date, 19 genetic maps have been constructed for teaIn 2017, the levels of 10 flavor-related metabolites in tea buds and leaves (each bud with two leaves) from 191 tea plant resources in Population 1 Table  were mea15. The sequencing resulted in 397.62 Gb of data, with an average of 2.07 Gb. The average volume was 0.67-fold that of the reference genome and 8.2-fold that of the reduced-representation genome (Table GVM000090).Population 1, comprising 191 tea plant germplasm resources, was used to construct sequencing libraries based on the amplified-fragment single-nucleotide polymorphism and methylation (AFSM) methodme Table . On the Camellia sinensis var. sinensis; these samples were collected from southeastern coastal areas, including Fujian and Zhejiang provinces. The Subgroup P2 resources were mainly Baimao tea plants (C. sinensis var. pubilimba Chang), including Lingyun Baihao tea plants from Guangxi and Lechang Baimao tea plants from northern Guangdong. Baimao tea plants have unique features, including buds and leaves that are densely covered with fuzz. By tracing the source of the analyzed germplasms, we determined that all of the Subgroup P3 resources or their parents were associated with the Yunnandaye species lineage. Subgroup P4 mainly contained the Maoye arbor population from Guangdong. These plants had large and leathery leaves. Subgroup P5 mostly comprised landraces from Guangdong, including Hakka lobular and Chaozhou Dancong resources. These landraces were collected from geographically adjacent regions, and they were characterized by small or moderately sized leaves. Subgroup P6 mainly included C. sinensis var. assamica (Masters) Kitamura arbor or semiarbor resources with large leaves as well as their natural hybrid progenies. The resources in Subgroup P7 were mixed, but most were improved cultivars, possibly because of extensive genetic recombination.The group structures of the obtained high-quality SNPs were analyzed with Admixture. The maximum cluster subgroup number (K) was 1–8, and the cross-validation error (CV error) of the corresponding K value was calculated. The CV error initially decreased before increasing. Because the CV error was smallest when K = 3, the group was divided into three subgroups Fig. . The res16. In general, the decay distance of linkage disequilibrium refers to the physical distance between SNPs in the genome when r2 = 0.1 or 0.2. In the current study, when r2 = 0.1, the genetic distance between SNPs for the analyzed tea plant population was 1.8 kb  (Tables A mixed linear model (compressed MLM) was used to assess the correlation between 10 tea flavor-related biochemical components and 35,972 high-quality SNPs, with ) Tables  and S5. ) Tables . These 2) Tables  and S3, ) Tables  and S4, ) Tables  and S5, ) Tables  and S6, ) Tables  and S7, ) Tables  and S8, ) Tables  and S9.FSome of the molecular markers were associated with multiple metabolites Table . For exaThe genes detected in each significant locus as well as the genes located upstream or downstream of the loci were designated candidate genes, which were then functionally annotated. The genes detected in more than two seasons were used for subsequent analyses. The 180 functionally annotated genes Table  were invEight metabolic pathways were associated with TN, most of which were related to the synthesis and metabolism of amino acids, such as arginine biosynthesis, tryptophan metabolism, aminoacyl-tRNA biosynthesis, and selenium complex metabolism (other amino acid metabolism). Other metabolic pathways were enriched as well, including flavonoid biosynthesis, zeatin biosynthesis, inositol phosphate metabolism, and endocytosis Table . Gene onThirteen metabolic pathways were related to CAF, including biosynthesis of secondary metabolites and pathways affecting photosynthesis and photorespiration, such as ubiquinone and other terpene-quinone biosynthesis, carotenoid biosynthesis, endoplasmic reticulum protein processing, and peroxisomes. Other CAF-related metabolic pathways were associated with plant stress tolerance, namely, cutin, suberine, and wax biosynthesis, plant MAPK signaling pathway, plant hormone signaling, zeatin biosynthesis, and plant–pathogen interactions Table . The GO The 53 metabolic pathways related to C were mainly associated with the primary glucose metabolism pathway upstream of the shikimic acid pathway, the amino acid metabolic pathway related to the catechin synthesis pathway, a branch of the catechin synthesis pathway, lipid metabolism, and stress tolerance-related metabolic pathways Table . The GO Of the 180 annotated genes, 19 were related to TN metabolism, 34 were related to CAF metabolism, 103 were related to C metabolism, 17 were related to CG metabolism, 7 were related to EC metabolism, 40 were related to ECG metabolism, 2 were related to EGCG metabolism, 4 were related to GC metabolism, and 58 were related to GCG metabolism Table . Some of26.Some of the annotated genes were examined in previous studies and may directly or indirectly contribute to the synthesis or regulation of TN, CAF, and catechins Table , Fig. 5a29. Because secondary metabolites often exert their physiological effects at sites that differ from the sites of synthesis, efficient intercellular transport, and intracellular trafficking systems are required. ATP-binding cassette (ABC) transporters are associated with the transport of alkaloids and anthocyanins29. Multiple SNPs in the ABC transporter gene sequence were related to TN and C, implying that these transporters are involved in the transport of flavor-related metabolites.There is considerable evidence indicating that most plant metabolites, including flavonoids, alkaloids, and amino acids, can be modified  and transported to vacuoles or other subcellular chambers for temporary storage. Glycosyltransferase is involved in the glycosylation of metabolites related to the anthocyanin and catechin synthesis pathways, making it a regulator of the catechin content. The association analysis identified several glycosyltransferase-related genes that may be involved in the synthesis of catechins30. In this study, MYB86, MYB44, and WD40 domain-containing proteins associated with C were identified. Additionally, other genes may also influence the synthesis and regulation of TN, CAF, and catechins, including those encoding the LRR receptor-like serine/threonine-protein kinase28, Asp aminotransferase17, V-ATPase17, proteasome regulatory subunit17, Ca2+-transporting ATPase28, ammonium transporter17, cellulose synthesis-like protein21, 14-3-3-like proteins, N-terminal methyltransferase30, 3-ketoacyl-CoA synthase, glutamyl-tRNA amidotransferase, and zeatin O-xylosyltransferase , suggesting that the abundance of these metabolites is controlled by minor genes in a complex genetic background31.Tea plants originated in southwestern China but eventually spread elsewhere. Natural selection and artificial domestication have generated diverse tea germplasm resources, including cultivars, local populations, and wild species. Additionally, local populations and wild species are genetically highly variable and contain rare or unique secondary metabolites32, necessitating the analysis of the genetic background of the population being investigated. Most of the 191 resources used in this study were from tea-growing regions in southern China. The germplasms were divided into three groups based on population genetic structures, principal component analysis, and phylogenetic relationships. A combined examination of the phylogenetic relationships, geographical distributions, and biological characteristics divided the 191 resources into seven subgroups. The tea resources in Guangdong Province mainly belong to Subgroups P4, P5, and P6, whereas most of the Yunnan and Fujian species belong to Subgroups P6 and P1, respectively. We determined that most of the tea resources in Guangdong were semiarbors with moderately sized or large leaves. The tea resources in Yunnan were mainly semiarbors with large leaves, whereas the resources in Fujian and Zhejiang were primarily shrubs with small leaves. The tea resources in Guangdong and Yunnan shared similar biological characteristics, which was consistent with the phylogenetic relationships. These results are in accordance with the findings of an earlier investigation of the genetic relationships among 450 resources in China and abroad based on EST-SSR molecular markers33.The genetic diversity and population structures of tea, which are essential for association studies of this important crop, are important causes of false positives in association studies34. They have since been conducted to analyze important plants, including wheat, sorghum, Arabidopsis thaliana, maize, rapeseed, barley, and upland cotton, but not tea36. Although many candidate SNP loci have been identified by genome-wide association analyses, because of differences in sample sizes, linkage disequilibrium attenuation, number of molecular markers, population structures, and analytical models, some unrelated alleles may also be incorrectly associated with QTLs 37. Consequently, candidate SNPs must be validated. There are two verification methods that are commonly used. One involves the direct functional verification of candidate SNPs, whereas the other involves verification by reassociating candidate SNPs in multiple groups.The popularity of GWAS in plant genetics research increased after Klein et al. published an article describing their utility for investigating the human retina38. Factors that can decrease heritability include rare mutations39, structural variations40, epistatic interactions, and genetic and environmental interactions41. We also determined that some related loci have pleiotropic effects. For example, Scaffold720:596655, Scaffold720:596754, and Scaffold720:596759 were associated with five metabolites . This pleiotropism might be related to the differences in specific genomic intervals of tea resources, which expanded and contracted during evolution.In this study, 191 tea resources were included in an association analysis of flavor-related metabolites in three seasons. The molecular markers common to all three seasons were designated candidate SNPs. Wayne diagrams indicated that the number of molecular markers varied among the three seasons, implying that the metabolite levels were regulated by internal genetic factors that were unaffected by the seasons and by changes to seasonal climates. In this study, 30 SNPs were validated in a second population, and 17 SNPs were confirmed as being significantly or extremely significantly correlated with metabolite levels. Our association analysis of TN, CAF, and catechins revealed that most of the SNP-associated functionally annotated genes are related to primary metabolic pathways, including a few that are closely related to TN, CAF, and catechin synthesis, possibly because of a common loss of heritability in the association study43. The results of these investigations suggest that CsANR1, CsANR2, CsLAR, CsF3′H, CsC4H, CsF3H, CsMYB4a, CsMYB5, and CsMYB75 might be involved in the synthesis of tea polyphenols. Additionally, CsTCS contributes to the synthesis of CAF41, whereas CsTS1 and CsAAPs are involved in the synthesis and transport of TN, respectively. In the current study, 180 genes were identified in an association study and subsequently functionally annotated. These genes differ from the previously verified genes and those obtained in a recent association analysis12. However, some of the genes are located upstream or downstream of the verified genes, and some of the genes belong to the same families as these verified genes. The genes identified by our association analysis can be classified into the following four types: (1) structural genes for primary metabolism and secondary metabolite synthesis; (2) transcription factor genes regulating metabolite synthesis; (3) genes responsible for modifying and transporting metabolites; and (4) genes that coevolved with metabolite-related genes.To date, only 24 tea genes have been functionally verified by in vitro analyses of enzyme activities or by examining genetically transformed model plants44. The absorption and efficient use of nitrogen and carbon differ among tea varieties in diverse environments, thus affecting the accumulation of downstream secondary metabolites47. Additionally, secondary metabolites are regulated at some key points of specific pathways. For example, FLS, which links flavonoids and catechins, catalyzes the hydroxylation of the C3 position in flavonoids to form various flavonols. Moreover, the MYB-bHLH-WD40 complex can regulate the expression of most flavonoid pathway genes48, including CHS, CHI, ANR, and ANS, to modulate catechin synthesis17. The modification and transport of secondary metabolites influence the synthesis of catechins. The UGT enzyme catalyzes the glycosylation of flavonoids, which stabilizes the structure of the metabolites. ABC transporters mediate the distribution of flavonoids to specific subcellular chambers where they are needed. Furthermore, some genes that coevolved with metabolite-related genes affect morphological structures, such as the cell wall, stratum corneum, and waxy layer, as well as the plant MAPK signaling pathway and plant–pathogen interactions, which may be related to the adaptative mechanism of tea plants. Xia et al. sequenced and analyzed the tea plant genome and revealed a recent genome-wide replication event that increased the copy number of genes related to tea aroma, flavor, and quality but also contributed to a substantial increase in the number of genes encoding LRR-RLK and LRR-NBS proteins, which may enable tea plants to effectively resist the adverse effects of biotic and abiotic stresses49. Moreover, MYB44 was identified during our association analysis of C, ECG, and GCG. In A. thaliana, AtMYB44 is important for stress responses and for enhancing disease resistance50.Some of the pathways associated with identified genes  affect primary metabolism, including the assimilation of carbon and nitrogen, which determines the volume of plant “sources”51. Replicates were analyzed separately, and the data are presented in Tables The tea plant resources used in this study were grown in the field gene bank of the Tea Research Institute of the Guangdong Academy of Agricultural Sciences . A total of 289 resources were randomly divided into two populations. Population 1 comprised 191 resources Table  used forThe 10 metabolites associated with tea flavor were detected by high-performance liquid chromatography. Specifically, TN was analyzed according to Agilent’s precolumn derivatization method, whereas CAF, GC, EGC, C, EC, EGCG, GCG, ECG, and CG were examined according to the national standard method. The range, mean, standard deviation, and coefficient of variation for each metabolite were analyzed with SPSS software. Quantitative data for the metabolites were divided into 10 grades with standard deviations of 0.5 and used to calculate the Shannon-Wiener diversity index for the metabolites. The best linear unbiased prediction method was applied to estimate the breeding value with a 1-year multipoint model while estimating the generalized heritability.15 for subsequent high-throughput sequencing with the Illumina HiSeq 2000 apparatus. The raw sequencing data were optimized with a Perl script to remove low-quality reads. The remaining clean reads were assigned to each individual based on the designed tags. Reads were compared with the C. sinensis var. sinensis Shuchazao cultivar genome sequence52, after which SNPs were identified and filtered with SAMtools and VCFtools. The conditions for filtering the SNPs were as follows: MAF ≥ 5% and missing ≤10%. The datasets described herein were submitted to the Genome Variation Map (GVM) database of the Big Data Center, Beijing Institute of Genomics, Chinese Academy of Science.Total DNA was extracted from the sprouts of the 191 tea plant resources in Population 1 according to the CTAB method. The A260/A280 of each DNA sample was confirmed to be between 1.8 and 2.0, and the concentration was greater than 100 µg/µl. The extracted DNA samples were used to construct libraries based on the AFSM methodr2 value between two molecular markers. A scatter plot of the smooth curve was drawn with the distance as the abscissa and the average r2 values as the ordinate. The abscissa of the intersection of the curve and the straight line r2 = 0.1 represented the attenuation distance of the linkage disequilibrium.The.ped and.map files of the SNP genotype data were converted to.bed files with Plink and used as input files. The GCTA program was used to estimate the genetic relationships between individuals. A principal component analysis was also completed, with the scatter plot drawn with R software. On the basis of the genetic distance matrix, the PHYLIP neighbor-joining function was applied, and the default rootless tree algorithm was used to construct a phylogenetic tree, which was drawn with Figtree software. Moreover, Plink was used to identify SNPs with high linkage disequilibrium, extract SNPs with relatively low linkage disequilibrium, and generate a binary.bed file. The subgroup number K was set between 1 and 10, and the optimal K value was determined according to the CV error. A genetic structure matrix was drawn based on the genetic component coefficient (Q) of each material in each subgroup. The filtered SNPs were used to calculate the 10(P) observed and expected values for each SNP locus. The significance threshold was set at 1/n, where n is the total number of markers.The filtered 35,972 high-quality SNPs and indels were used for the GWAS of 10 tea flavor-related metabolites over three seasons. The mixed linear model in the TASSEL program was used, with the genetic component coefficient Q value and the kinship K value applied as covariates. The genotype data were used to analyze the correlation between metabolite levels and markers. The Manhattan map and the quantile-quantile scatter plot were generated with the qqman package of R with the −log50. The KEGG pathway database (http://www.genome.jp/kegg) and the Gene Ontology Consortium database (http://geneontology.org) were then used to assign metabolic pathways to the candidate genes.The significantly associated SNP loci common to all three seasons were functionally annotated. Additionally, the genes detected at each locus or upstream or downstream of the loci were designated candidate genes. If a locus was between two genes, the nearest gene was identified as a candidate gene. The candidate genes were annotated based on the tea plant genome annotation fileThirty significantly associated loci were selected as candidate SNPs and verified in Population 2. Buds and leaves (each bud with two leaves) were collected from the tea plant resources in Population 2 for an analysis of the levels of the 10 tea flavor-related metabolites. Total DNA was extracted from the 98 samples in Population 2. The PCR amplification primers Table  and the Table S1Table S2Table S3Table S4Table S5Table S6Table S7Table S8Table S9Table S10Table S11Table S12Table S13


In this work, non-targeted approaches relying on HPLC-UV chromatographic fingerprints were evaluated to address coffee characterization, classification, and authentication by chemometrics. In general, high-performance liquid chromatography with ultraviolet detection (HPLC-UV) fingerprints were good chemical descriptors for the classification of coffee samples by partial least squares regression-discriminant analysis (PLS-DA) according to their country of origin, even for nearby countries such as Vietnam and Cambodia. Good classification was also observed according to the coffee variety (Arabica vs. Robusta) and the coffee roasting degree. Sample classification rates higher than 89.3% and 91.7% were obtained in all the evaluated cases for the PLS-DA calibrations and predictions, respectively. Besides, the coffee adulteration studies carried out by partial least squares regression (PLSR), and based on coffees adulterated with other production regions or variety, demonstrated the good capability of the proposed methodology for the detection and quantitation of the adulterant levels down to 15%. Calibration, cross-validation, and prediction errors below 2.9%, 6.5%, and 8.9%, respectively, were obtained for most of the evaluated cases. The quality of natural products is an issue of great interest in our society. Taking into account the food chain complexity and the various factors involved between food production and consumption, food handling and adulteration practices are increasing. In this sector, fraud is defined as a form of conscious deception about the quality of a food product for profit, and adulteration is defined as the partial replacement of food of certain quality by another similar with lower quality and price. Adulteration and manipulation of foods to fool final consumers is illegal worldwide, not only because of economic consequences, but also because of significant health problems. For that reason, the determination of the authenticity of the food is a very important issue in quality control and food safety ,2,3,4.Drinks are products that can be very easily adulterated through practices that include mislabeling, supplementation with flavors or aromas, and the addition of unspecified additives to increase their volume, among other practices. Drinks with higher adulteration rates are fruit juices, coffee, tea, wine, and other alcoholic beverages .Coffea from the Rubiaceae family, with more than 70 varieties, although the majority of the coffee consumed, so having major economic and commercial importance, is produced by the Coffea Arabica (Arabica) and Coffea Canephora (Robusta) varieties. The Arabica variety is the most appreciated by consumers and even considered better than the Robusta variety for its high sensorial properties. For this reason, Arabica coffee usually has a higher price in the international market [Coffee is an infusion of ground roasted coffee beans from the coffee plant with a characteristic taste and aroma. Coffee is one of the most popular beverages in all the world, consumed by millions of people every day, occupying the second position of most commercialized basic products. Some 60 tropical and subtropical countries are coffee producers (with a world coffee production of 6.3 million tons per year), being for some of them, the main agricultural export product. The coffee plant belongs to l market ,6. Coffel market ,6. The cl market ,6,7.Adulteration practices in roasted coffee are both frequent and diversified. They may be related not only to the quality of the coffee beans  ,10,11,12® C18 column  under gradient elution conditions employing 0.1% formic acid aqueous solution and methanol as mobile phase components were proposed. Three hundred and six commercially available coffee samples divided into three sets of samples changing on the production country, coffee variety, and roasting degree were analyzed with the proposed methodology. The obtained HPLC-UV fingerprints were then employed as a source of chemical information to address the characterization and classification of the analyzed coffees by principal component analysis (PCA) and partial least squares regression-discriminant analysis (PLS-DA). Besides, HPLC-UV fingerprints were also evaluated as potential chemical descriptors to detect and quantify coffee sample adulterations by partial least squares regression (PLSR). This work will focus on the thematic of fraud detection in coffee. This manuscript offers an overall strategy to deal with the topic of food authentication, starting from simpler exploratory analyses to quantification of coffee adulterant percentages. In this work, a simple and efficient high-performance liquid chromatography with UV-detection (HPLC-UV) fingerprinting method was developed for the characterization, classification, and authentication of coffee samples according to the production regions, the coffee variety, and the roasting degree. Reversed-phase mode using a KinetexAuthentication of coffee origin (production country or region), as well as coffee varieties, is highly demanded by our society as an additional quality attribute, being willing to pay higher prices for coffee varieties produced in specific regions. In this context, simple and reliable methods to prevent fraudulent practices become necessary. For that purpose, the aim of this work focused on the evaluation of a non-targeted HPLC-UV fingerprinting method to address the classification and authentication of coffee samples according to three sets of coffee samples  and formic acid (≥98%) from Sigma-Aldrich. An Elix 3 coupled to a Milli-Q system from Millipore Corporation  was used to purify the water, filtering it through a 0.22 µm nylon membrane integrated into the Milli-Q system. Mineral water obtained from Eroski  was employed for brewing the coffees. ® C18 reversed-phase column  provided by Phenomenex  was used under gradient elution conditions employing 0.1% formic acid in water (v/v) (solvent A) and methanol (solvent B) as mobile phase components. The gradient started increasing the methanol component (solvent B) from 3% to 75% in 30 min. After that, there was an isocratic step of 2 min. Then, methanol increased from 75% to 95% in 2 min. Finally, the elution program came back to the initial composition in 0.2 min and an isocratic step of 5.8 min guaranteed column re-equilibration. The flow rate was 0.4 mL/min and the injection volume was 5 µL. UV acquisition was carried out at 280 nm.Chromatographic fingerprints were obtained on an HPLC instrument from Agilent HPLC 1100 Series  equipped with a G1312A binary pump, a WPALS G1367A automatic sample injector, a G1315B diode-array detector, and a PC with the Agilent Chemstation software. A Kinetex® coffee samples (each one) purchased from supermarkets in Barcelona (Spain). Coffee samples differed in the coffee variety (Arabica or Robusta), the region of origin, and the roasting degree (increasing from 1 to 5). The third set of samples included a total of 66 samples obtained from Vietnam and Cambodia supermarkets, and were classified into 5 groups depending on the coffee variety and the region of origin. No information regarding the roasting degree was available. A total of 306 commercially available coffee samples, grouped in three different sets, were analyzed. The first two sets, described in Sample treatment consisted of coffee brewing with mineral water. In the case of the two first sets of samples, coffee was directly brewed by using an espresso machine (Nespresso), using in all cases the same brewing time to reach the same final volume. In the third set of samples, coffee beans were first grounded when necessary. Then, the coffees were brewed by employing an Italian coffee maker. For that purpose, ground coffee was introduced well compressed in the Italian coffee maker and 400 mL of mineral water was employed for the coffee brewing, with the help of a Bunsen burner to carry out the coffee lixiviation. All brewed coffees were then filtered with 0.45 µm nylon filters (Phenomenex) into 2 mL glass vials which were stored at −4 °C. Moreover, a quality control (QC) solution was prepared for every set of samples by mixing 50 µL of each sample extract. QCs were used to evaluate the repeatability of the method and the robustness of the chemometric results. Samples from the second and third sets were also employed for adulteration studies. For the second set, the adulteration cases proposed were Colombia vs. Ethiopia, Colombia vs. Nicaragua, and India vs. Indonesia. For the third set, the adulteration cases proposed were Vietnam-Arabica vs. Vietnam-Robusta, Vietnam-Arabica vs. Cambodia, and Vietnam-Robusta vs. Cambodia samples. For each adulteration case, two sets of samples were prepared for calibration (to build the PLSR model) and validation (for prediction purposes), with different amounts of adulterations as described in The calibration set included the 20%, 40%, 60%, and 80% adulteration levels, as well as 100% pure coffees of each class, and the validation set included 15%, 25%, 50%, 75%, and 85% adulteration levels. Besides, an additional adulterated sample at a 50% level was employed as a QC solution. Each adulteration level  was prepAfter sample treatment, all the samples were analyzed randomly with the proposed HPLC-UV method. The resulting fingerprints were used as sample chemical descriptors to build the different data matrices that were subjected to principal component analysis (PCA), partial least squares–discriminant analysis (PLS-DA), and partial least squares regression (PLSR) under SOLO 8.6 chemometric software from Eigenvector Research  . DetailsThe main objective of this section was to achieve a simple non-targeted HPLC-UV fingerprinting method for the classification and authentication of coffee samples. In this regard, an adequate chromatographic elution program to obtain good HPLC-UV fingerprints was optimized, taking into consideration that polyphenols and related compounds are quite abundant in coffee and they could serve as the basis of sample discriminations see . Their ca), an Arabica-Robusta mixture coffee from India (b), and a Robusta coffee from Uganda. A total of 306 commercially available coffee samples  consisting of the absorbance signals recorded as a function of retention time were built, with dimensions of 133 × 6001, 133 × 6001, and 72 × 6000 for sample sets 1, 2, and 3, respectively. Besides, autoscaling pretreatment was chosen to provide similar weight to all the variables. Regarding coffee distribution, samples tend to be grouped according to their region of origin, although overlapping of several groups of samples can be observed. The best discrimination was achieved with the coffee set of samples 2 b, where HPLC-UV chromatographic fingerprints were also used to address coffee classification by using PLS-DA. In this case, the classification of coffee samples was addressed as a function of three factors: the region of origin, the coffee variety (Arabica vs. Robusta), and the roasting degree. Regarding the sample distribution as a function of the coffee region of origin, the classification method generally improves in comparison to the previous PCA results, as expected, although again overlapping between some groups is observed. Considering the coffee set of samples 1 a, the ovIn a similar way, Regarding coffee sample classification according to the roasting degree , only PLThese results demonstrate that chromatographic fingerprints can be proposed as good descriptors to address coffee samples characterization and classification according to the coffee region of origin (production country), the coffee variety (Arabica vs. Robusta), and the coffee roasting degree. To demonstrate the applicability of the proposed methodology based on HPLC-UV fingerprinting, the classification rate was studied for some paired PLS-DA models: (i) Brazilian vs. Ethiopian coffees, (ii) Ethiopian vs. Uganda coffees, (iii) Indonesian vs. Indian coffees, (iv) Colombian vs. Ethiopian coffees, (v) Vietnamese vs. Cambodian coffees, and (vi) Vietnamese Arabica vs. Vietnamese Robusta coffees. For that purpose, each paired PLS-DA chemometric model studied was established using 70% of each sample group (selected randomly) as the calibration set, while the remaining 30% of the samples were employed as an “unknown” set of samples for validation purposes. This means that except for Vietnamese vs. Cambodian coffees (case v), the rest of the models were created with 24 calibration samples (14 of each class) while models were applied to assign 12 unknown samples (6 of each type). In the case v, Vietnamese and Cambodian standards were 39 and 17, respectively, and the prediction set was composed of 7 Vietnamese and 3 Cambodian coffees. As examples, As can be seen, in most cases, 100% sample classification rates for both calibrations and predictions are obtained. In the case of Brazilian vs. Ethiopian coffees a and Etha) Colombian coffee adulterated with Ethiopian coffee and (b) Vietnamese Arabica coffee adulterated with Vietnamese Robusta coffee. The distribution of these samples on LV1 and LV2 depended on both chromatographic features and adulterant concentrations which increased, in general, from the bottom-left to the top-right part. Results related to all the other adulteration cases studied are depicted in 2), are also indicated in the figures.The capability of fingerprints to quantify the extension of coffee adulterations was evaluated by PLSR. For that purpose, several adulteration cases were studied: (i) Colombian coffee adulterated with Ethiopian coffee, (ii) Colombian coffee adulterated with Nicaraguan coffee, (iii) Indian coffee adulterated with Indonesian coffee, (iv) Vietnamese Arabica coffee adulterated with Vietnamese Robusta coffee, (v) Vietnamese Arabica coffee adulterated with Cambodian coffee, and (vi) Vietnamese Robusta coffee adulterated with Cambodian coffee. For each adulteration case, two independent sets of samples were available for calibration and validation, as described in As can be seen in the PLSR models built according to the contents of the coffee acting as an adulterant, 100% pure coffee samples tend to be located in the opposite areas of the score plots, mainly showing either a positive or a negative correlation with respect LV1. The optimal numbers of LVs deduced from cross-validation were 6 and 4 for Colombian coffee adulterated with Ethiopian coffee a and Vie2 coefficients in calibration, cross-validation, and prediction models higher than 0.957, showing the good performance of the proposed methodology. There is only one exception, which is the case of the Colombian coffee adulterated with a Nicaraguan coffee , taking into consideration that these coffees are produced in very nearby countries, with very similar weather conditions. Obviously, other parameters such as the coffee variety are also contributing to this good sample prediction.In general, good results were obtained when PLSR multivariate calibration was employed for the quantitation of adulterant levels in coffee, obtaining Rn coffee , where aIn the present work, non-targeted HPLC-UV fingerprints acquired at 280 nm have proved to be acceptable sample chemical descriptors for the characterization, classification, and authentication of coffee samples according to their country of production, variety, and roasting degree, even in the cases of coffees produced in nearby countries such as Vietnam and Cambodia. HPLC-UV fingerprinting descriptors were easily obtained by reversed-phase chromatography using a conventional C18 column directly after brewing the coffee without any sample treatment other than filtration, thus reducing considerably sample manipulation. Exploratory analysis by PCA and PLS-DA using the obtained coffee HPLC-UV fingerprints showed, in general, good discrimination capabilities among the different coffee production regions, coffee varieties (Arabica vs. Robusta), and coffee roasting degrees. PLS-DA provided good classification rates for most of the studied examples, always higher than 89.3% and 91.7% for PLS-DA calibration and prediction, respectively. The capability of the proposed methodology to detect and quantify coffee frauds (down to 15% adulterant level) using PLSR multivariate calibration was evaluated by studying several adulteration cases involving coffees adulterated either with those produced in a different country or of a different coffee variety. Very acceptable calibration, cross-validation, and prediction errors, with values lower than 2.9%, 6.5%, and 8.9%, respectively, were obtained for most of the evaluated cases.Therefore, the proposed non-targeted HPLC-UV fingerprinting methodology resulted to be a feasible, simple, and cheap methodology to address coffee authentication, especially for developing coffee production countries.