Cancer cell lines are amongst the most important pre-clinical models. In the context of epithelial ovarian cancer, a highly heterogeneous disease with diverse subtypes, it is paramount to study a wide panel of models in order to draw a representative picture of the disease. As this lethal gynaecological malignancy has seen little improvement in overall survival in the last decade, it is all the more pressing to support future research with robust and diverse study models. Here, we describe ten novel spontaneously immortalized patient-derived ovarian cancer cell lines, detailing their respective mutational profiles and gene/biomarker expression patterns, as well as their in vitro and in vivo growth characteristics. Eight of the cell lines were classified as high-grade serous, while two were determined to be of the rarer mucinous and clear cell subtypes, respectively. Each of the ten cell lines presents a panel of characteristics reflective of diverse clinically relevant phenomena, including chemotherapeutic resistance, metastatic potential, and subtype-associated mutations and gene/protein expression profiles. Importantly, four cell lines formed subcutaneous tumors in mice, a key characteristic for pre-clinical drug testing. Our work thus contributes significantly to the available models for the study of ovarian cancer, supplying additional tools to better understand this complex disease. Ovarian cancer is the most lethal gynaecological cancer, and fifth leading cause of malignancy-related deaths in North American women . OvarianBRCA1 or BRCA2 mutation but also, to a lesser degree, germline mutations in RAD51C, RAD51D, PALB2, and FANCI, with a higher incidence in the HGSC subtype [BRCA1/2 mutations, HGSC tumors harbor a virtually ubiquitous somatic TP53 mutation (>95%), as well as less commonly mutated genes, including CSMD3, NF1, CDK12, and FAT3 [TP53-mutated, and instead show high-frequency mutually exclusive mutations in KRAS, BRAF, NRAS, or ERBB2 [PIK3CA, ARID1A, and KRAS mutations, amongst others, as well as a frequent loss of PTEN expression [KRAS mutation, in addition to TP53, BRAF, and CDKN2A alterations [ARID1A mutations, as well as moderately frequent mutations of PIK3CA, CTNNB1, and PTEN, usually presented as loss of expression or loss of heterozygosity, with some tumors rarely harboring a TP53 mutation [The most common risk factor for EOC is a family history of ovarian cancer. An estimated 25% of all ovarian cancer cases could be due to inherited genetic mutations, the most frequent being a germline  subtype ,9,10,11. subtype . Furtherand FAT3 ,14. LGSCor ERBB2 ,16,17. Cpression ,16,18,19erations ,16,20. Emutation ,16,21. Dmutation ,23,24. Amutation . Over thmutation ,29,30,31In this context, patient tumor-derived cell lines are efficient, inexpensive, and easy to maintain, and thus make for an attractive human pre-clinical cancer model ,33. OvarTP53-mutated, whereas the MC and CCC cell lines were TP53 wild-type but harbored KRAS mutations specific to their respective subtypes. Importantly, four of these cell lines form xenograft tumors in mice, a key characteristic for pre-clinical drug testing. These 10 new cell lines contribute significantly to the EOC cell lines available for research by their diversity and molecular characteristics.Here, we present 10 novel patient-derived EOC cell lines (from 10 different patients) and their generation, and describe their in vitro and in vivo growth characteristics, molecular biology, genetic mutation profiles, and histopathology. Eight of these cell lines were identified as HGSC cells, and two were found to be of the MC and CCC subtypes, respectively. All of the HGSC cell lines were The cell lines were derived from the samples of 10 patients  treated between 2001 and 2010, whose clinical characteristics are described in None of the patients harbored a somatic BRCA mutation. Patients 2085 and 2881 had a family history of breast cancer and malignant neoplasm of the urinary tract, respectively, whereas patients 2929 and 3392 had a previous personal history of colorectal cancer of the sigmoid junction and breast cancer, respectively. Histopathology indicated that 7 of the 10 primary tumors were of the HGSC subtype, one was of the MC subtype (2414), and one was of the CCC subtype (3392). As patient 3331 did not undergo surgery, histopathology was not possible, but cytology confirmed that the patient’s tumor was an adenocarcinoma (AC).Sampling that resulted in the described cell lines for each of the 10 patients was done between 2004 and 2007. This sampling coincided with initial debulking surgery in the case of 6 of the patients  or was done at a later point during laparotomy  or ascites collection  . Four ofNine of the ten cell lines displayed homogenous morphology after 60 passages, whereas one of the cell lines, OV3291, exhibited slowed growth after 50 passages and reached growth arrest before reaching 60 passages. This cell line was thus tested after reaching 30 passages, but before reaching passage 45. For the most part, the morphology of the cell lines exhibited the characteristic flattened cobblestone-like appearance of epithelial cells . Two of TP53 mutation; most (5/8) were missense mutations with amino acid substitutions  and a splicing variant mutation (OV2978). All of these TP53 mutations are described in the IARC TP53 database [TP53 mutations  and CCC (TOV3392D) cell lines analyzed but did not detect mutations in any of the other prevalently mutated genes in these subtypes, including PIK3CA, ARID1A, BRAF, PTEN, CTNNB1, PPP2R1A, and NRAS (TP53) and OV3291 (TP53 and CDK12) cell lines  and that the MC and CCC cell lines grouped in a separate cluster, confirming the distinct molecular identity of the derived cell lines a. Cell lp < 0.0001)  d. These Due to the selection pressure inherent in establishing immortalized cell lines, it is important to verify that the cell line obtained reflects the EOC subtype of the original tumor. Therefore, we performed specific protein biomarker analyses of tumor tissue samples and cell lines by immunohistochemistry (IHC) and Western blot (WB), respectively. The tumor tissue of origin of the corresponding patient was subjected to a hematoxylin and eosin (H&E) staining, followed by IHC stains for various described epithelial ovarian cancer biomarkers  Figure . The repPrevious work has shown the H&E and IHC staining of the tumor of origin for patients 3291 and 2978 , and an TP53 is mutated in more than 95% of cases, which is reflected at the expression level either by robust overexpression (missense mutation) or complete absence (null mutation) of the p53 protein [TP53 mutations , a known p53 target [CDKN1A in the wild-type TP53 cell lines  confirmed the epithelial origin of the patient tumors  and asso protein ,56,58. Autations , Table 3ll lines , Table 3ern blot . On the 3 target ,60, as oll lines .TP53 and CDK12 mutations, as well as by their proximal gene expression clustering  is solely expressed in the HGSC tumors . Howeverustering a. Intrigoteasome , ruling The Western blot analysis of the TOV2414 cell line, on the other hand, showed a lack of PAX8 expression . This diPrimary ovarian MC and colorectal metastases to the ovary overlap on many commonalities, making them difficult to differentiate ,61. MostOvarian CCC, on the other hand, is often confused with metastatic endometrial or renal clear cell carcinoma (RCCC), due to overlapping characteristics ,67,68,69CDKN2A mRNA (p16 protein)  , which iTumor expression of ER and PR was shown to help distinguish the different subtypes of EOC ,73. Our Collectively, our protein biomarker analysis together with our gene expression and mutational profiling demonstrate the suitability of our cell lines as pre-clinical models to specific EOC subtypes.Growth characteristics were assessed by measuring doubling times  and by lt-test, p = 0.0013) but were not significantly different when compared to each other . The confluence-based proliferation curves show that TOV2414 was the fastest-growing cell line, whereas OV2085 was the slowest , whereas TOV3392D and TOV2929D had the slowest migration velocity , showing little to no ability to migrate . OV3331 migrated visibly with low velocity (9.7 µm/h), whereas TOV2835EP, TOV2881EP, OV2978, TOV3121EP, and OV3291 demonstrated similar intermediate wound-healing efficacy (32.4–42.9 µm/h)  . The mig50) of 18.4 and 11.2 µM respectively, significantly higher than all the HGSC cell lines . This chemoresistance cannot be attributed to an inherent low growth characteristic of these cell lines, since they were found to have the fastest doubling time , significantly more sensitive than the other HGSC cell lines tested . On the other hand, TOV2835EP, TOV2929D, TOV3121EP, OV3291, and OV3331 exhibited intermediate sensitivity to carboplatin (IC50 between 1 and 5 µM)  . The senn = 5 mice per injection site for each cell line) , forcing ethical interruption of the experiment and sacrifice of the mice between 53 and 68 days post-injection. Of the other tumor-forming cell lines, OV2085 grew the fastest, followed by TOV2414 and OV3331, which reached a tumor volume of 500 mm3 after an average 65, 125, and 170 days, respectively  or intraperitoneally (IP) in NOD rag gamma (NRG) mice (ll line) . Four ofectively . None ofectively .Cell lines injected IP were tested for formation of ascites, tumors at site of injection, and metastases at abdominal organs. Only TOV2414 and TOV3392D formed peritoneal tumors at the site of injection. OV3331, OV2085, and TOV2929D formed medium to large metastases in most cases, whereas TOV2414, TOV2881EP, and TOV3392D formed very small metastases. OV3331, OV2085, TOV2881EP, and TOV2929D all formed large volumes of ascites, between 2 and 8.5 mL per mouse .Epithelial ovarian cancer is a highly heterogeneous disease that poses critical challenges when choosing appropriate pre-clinical models relevant in translational science. On one hand, EOC is classified into five main subtypes  with differences in morphology, etiology, pathogenesis, pathology, molecular biology, and prognosis ,20,21,44Despite their limitations, tumor-derived cell lines remain one of the most versatile pre-clinical models; they can be cultured two-dimensionally, as three-dimensional spheroids, and even in vivo as xenografts. However, concerns exist on the process of adaptation to in vitro cell culture conditions, which can be reflected on the success rate of cell line generation. The 10 novel EOC cell lines described in this publication were derived in the same time frame (2004–2011) as 16 others from our laboratory ,38,39, wTP53 mutation, and the two non-HGSC cell lines TOV2414 and TOV3392D did not. These data were confirmed by WB of whole cell lysates and IHC staining of the tumor of origin for each cell line, where cell lines with missense TP53 mutations had a robust p53 overexpression, and those with frameshift/splice TP53 mutations (null) did not express the p53 protein or mRNA. The two non-mutated cell lines, on the other hand, showed low or focal expression of p53 in IHC and moderate expression of the protein in WB. These are expected p53 phenotypes, as previously described [From the 10 novel patient-derived EOC cell lines described here, eight were identified as HGSC, one as MC, and one as CCC. Each cell line was successfully characterized as belonging to the subtype of the original patient sample by detailed protein biomarker  and mutaescribed . ConcordCDKN2A gene (p16 protein) [FAT3, CDK12, and CSMD3 genes [Further confirmation of the HGSC subtype involved the protein expression profiles of WT1, PAX8, and ER, ; the mRNprotein) ,72; and D3 genes . Most imD3 genes ,37,38,39D3 genes , the staOf the other HGSC cell lines, OV2085 and OV3331 are attractive pre-clinical models, in that they respectively show fast and slow in vivo growth when injected SC, and they both form IP tumors . These cCell lines OV2978 and OV3291 are derived from ascites, and are matched to their ovarian tumor cell lines derived from samples collected at the same time point for their corresponding patients . For theKRAS mutation, absence of SATB2 and focal expression of PAX8 [TP53 wild-type, harbours an uncommon but recurrent KRAS mutation, in addition to its cell population phenotype of clear cells and hobnail nuclei, as well as expression of Napsin A and absence of ER and PR, strongly confirming its CCC subtype rather than metastatic endometrial carcinoma [As for the MC cell line TOV2414, strong indicators for its ovarian mucinous subtype, aside from wild-type p53 and absence of WT1 expression, include the observed  of PAX8 ,55,62. Tarcinoma ,66,93,94arcinoma ,50,51,95Although several EOC cell lines were reported in the literature, a large number of these were insufficiently characterized, lacking important histological and molecular information. These include recently characterized ovarian cancer cell lines, where information regarding the tumor of origin, i.e., histology and protein biomarker analysis is not available for all the patients from which the cell lines were derived ,90,96. MTumor and ascites samples were obtained from patients from the Centre hospitalier de l’Université de Montréal (CHUM), Division of Gynaecologic Oncology, following informed consent. The stage was determined at the time of surgery by an on-site gynaecologic oncologist following the FIGO classification criteria . Histolo2, and 5% CO2 throughout the derivation process, following a previously established protocol [2, 5% CO2) and grown in complete OSE medium, consisting of OSE medium , 10% fetal bovine serum , 0.5 µg/mL amphotericin B (WISENT Inc.), and 50 µg/mL gentamycin sulfate  . Cells were passaged by trypsin 0.05%  digestion before reaching confluence, and culture medium was replaced weekly if cells were not passaged for more than seven days. All assays on these cell lines were conducted between passages 60 and 80, except in the case of OV3291, a non-immortalized cell line, which were conducted between passages 30 and 45.Ten cell lines were established from samples originating from ten patients: 2085, 2414, 2835, 2881, 2929, 2978, 3121, 3291, 3331, and 3392. All cell lines were kept in low oxygen conditions at 37 °C, 7% Ohttps://cesgq.com/). Alignment to the human genome NCBI37/hg19 was also performed by this facility to obtain BAM files of each of the 10 cell lines. BAM files were then uploaded into the public European Galaxy Network [TP53, BRCA1, BRCA2, NF1, GABRA6, RB1, CSMD3, CDK12, FAT3, ARID1A, BRAF, PTEN, PIK3CA, CTNNB1, PPP2R1A, NRAS, KRAS) was achieved using freebayes [Libraries for whole exome sequencing (WES) were prepared from 500 ng of DNA using the NimbleGen SeqCap EZ Human Exome Library v3.0 kit , followed by paired-end sequencing on the HiSeq 4000 , according to recommended protocols, at the Centre d’expertise et de services (CES) Génome Québec  according to manufacturer’s instructions. Then 2.8 µg of DNA target was hybridized on Clariom™ S Assay HT, human  and processed on the GeneTitan® Instrument  using the instrument’s Hyb-Wash-Scan automated workflow. Obtained CEL files were extracted and normalized using the Transcriptome Analysis Console (TAC) 4.0 software (Affymetrix). In this study, we performed subsequent gene expression analyses on the 10 cell lines described herein, as well as the matched TOV2978G and TOV3291G cell lines. For these 12 cell lines, unsupervised hierarchical clustering and principal component analysis (PCA) were performed using the TM4 MultiExperiment Viewer v3 software (MeV), a free, open-source tool for analyzing microarray data [RNA from 32 EOC cell lines, which includes 10 from this study and 22 previously characterized by our group ,37,38,39ray data .To demonstrate that the eight HGSC cell lines described here were clinically relevant, their microarray data (plus those from the two matched TOV2978G and TOV3291G cell lines) were compared to that of the publicly available Affymetrix U133a gene expression microarray data from 593 HGSC tumors from the TCGA cohort. The whole Affymetrix dataset was downloaded using the UCSC Xena Functional Genomics Explorer platform . To harmTissue sections (4 μm thick) were entirely stained with automated stain kit  Ventana were add® TGX™. Stain-Free 4–15% gradient Tris-glycine SDS-polyacrylamide 15-well gels (Bio-Rad Laboratories) and transferred onto 0.2 µm nitrocellulose membranes with the Trans-Blot Turbo transfer system (Bio-Rad Laboratories) using the mixed molecular weight program. Membranes were blocked with a PBS-Tween-milk solution  and incubated with primary antibodies  containing a protease and phosphatase inhibitor cocktail  on ice for three times 5 min, vortexing between each incubation. Protein concentration was measured by Bradford protein assay  using the GENESYS 10S US-Vis spectrophotometer . Then 30 µg of total protein extract were loaded and migrated at 100V in Mini PROTEANtibodies  overnigh2C and 1C respectively represent the later and earlier cell counts at two distinct time points, and Δt represents the elapsed time between cell counts 2C and 1C. Cell confluence was followed by live cell imaging using the IncuCyte® ZOOM System  and calculated using the IncuCyte® ZOOM 2016B software (Essen BioScience Inc.), where specific confluence masks were created for each individual cell line based on their morphologies , washed with PBS, and incubated in NCC. Scratches were monitored by live cell imaging using the IncuCyte® ZOOM System , and images were analyzed using the publicly available MRI Wound Healing Tool macro on ImageJ [Cells were seeded at confluence in a 96-well plate and incubated in NCC for 24 h. Wells were subsequently scratched using the IncuCyten ImageJ ,108. Resv/v methanol and 0.5% m/v methylene blue . Colonies were counted using a stereomicroscope, and the count for each concentration of treatment was reported as mean percent of control wells. Half maximal inhibitory concentration (IC50) values were calculated using the GraphPad Prism 7 software . Each individual experiment was performed in duplicate and repeated three times.Carboplatin sensitivity was determined by clonogenic survival assays, as previously described ,109. Celtm1Mom IL2rgtm1WjlRag1/SzJ  mice  at subcutaneous left gluteal injection (SC) or intraperitoneal (IP) sites, as previously described [6 cells in 100 µL of cold Dulbecco’s phosphate-buffered saline (D-PBS)  and 100 µL of either Matrigel® Matrix  for SC injections or D-PBS for IP injections. The mice were housed under sterile conditions in a laminar flow environment with unrestricted access to food and water. Formation of tumors, ascites, and metastases was evaluated twice a week for over 200 days. Animals were sacrificed before the mice reached certain limit points established by CIPA in accordance with guidelines by CCAC.All animal studies were approved by the Institutional Committee on Animal Protection (Comité institutionnel de protection des animaux-CIPA) protocol according to the Canadian Council on Animal Care (CCAC) (protocols C14008AMMs and C18010AMMs). Tumorigenic potential was assayed by injection of cells in NOD.Cg-escribed . A totalOur work reports ten novel immortalized EOC cell lines, providing well-characterized pre-clinical models for the benefit of the research, medical, and pharmaceutical communities, in order to advance therapeutic strategies for this deadly disease. Thorough analyses of protein biomarkers, somatic mutations, and gene expression demonstrate that each cell line represents critical aspects of the histological subtypes from which they were derived. These cell lines have diverse in vitro growth characteristics critical to cover the individual differences of EOC patients. Furthermore, some of the cell lines have the ability to grow as xenografts in mice, making pre-clinical in vivo experiments possible. These reliable and versatile models offer valuable tools for the study of ovarian cancer.


N-Carbamyl) glutamate (NCG) but not aspartic acid and citrulline on fetal/birth weight. However, no effects were reported when an isonitrogenous control diet was included. BCAA and methyl donor supplementation did not affect fetal/birth weight. Arginine family supplementation, in particular arginine and NCG, improves fetal growth in complicated pregnancies. BCAA and methyl donor supplementation do not seem to be as promising in targeting fetal growth. Well-controlled research in complicated pregnancies is needed before ruling out AA supplements or preferring arginine above other AAs.Aberrant fetal growth remains a leading cause of perinatal morbidity and mortality and is associated with a risk of developing non-communicable diseases later in life. We performed a systematic review and meta-analysis combining human and animal studies to assess whether prenatal amino acid (AA) supplementation could be a promising approach to promote healthy fetal growth. PubMed, Embase, and Cochrane libraries were searched to identify studies orally supplementing the following AA groups during gestation: (1) arginine family, (2) branched chain (BCAA), and (3) methyl donors. The primary outcome was fetal/birth weight. Twenty-two human and 89 animal studies were included in the systematic review. The arginine family and, especially, arginine itself were studied the most. Our meta-analysis showed beneficial effects of arginine and ( Divergence in fetal growth—both under- and overgrowth—remains a leading cause of perinatal mortality and morbidity ,2. FetalNormal fetal growth requires adequate amino acid (AA) supply during all trimesters, which depends on the placental capacity to transfer AAs from the maternal to fetal side . SeveralA disruption in fetal supply of AAs might contribute to fetal under- or overgrowth. The major cause of fetal growth restriction (FGR) is placental insufficiency, which often co-occurs with hypertensive disorder during pregnancy. Decreased utero-placental blood flow could result in reduced placental transfer of AAs and consequently FGR. Lower circulating levels of AAs of the arginine family and branched chain AAs (BCAA) and reduced expression or activity of placental AA transporters are indeed observed in FGR pregnancies ,14,15,16Oral supplementation of AAs during pregnancy could be an effective—and relatively safe—therapeutic or prophylactic solution to improving perinatal and long-term health. The arginine family, BCAAs, and methyl donors form three interesting supplementation groups by virtue of their influence on fetal growth. The arginine family plays a key role in placental growth and development through nitric oxide (NO) and polyamine syntheses and through the mammalian target of rapamycin (mTOR) pathway ,21,22,23This systematic review and meta-analysis evaluates the effect of oral supplementation of the three AA groups on fetal growth in complicated and normal-growth pregnancies. Considering the altered circulating levels of the specific AAs, the activity of placental transporters, and the hypothesized mechanism of action, we speculate that AAs from the arginine family or BCAAs normalize fetal undergrowth, while methyl donors normalize fetal overgrowth. By including different AAs in animal and human studies in one meta-analysis, we aim to identify the most effective AA (group) and other modifiable factors . This will contribute towards future study designs aimed at developing an AA-based supplementation strategy to prevent fetal growth divergence and its sequels.https://www.crd.york.ac.uk/PROSPERO). The sparse amendments to the review protocol that were made post hoc are reported in the Appendix. This review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines [This systematic review was conducted according to a prespecified protocol registered at PROSPERO for animal studies  and humidelines . No langOn 25th July 2018, we searched Pubmed, Embase (via OVID), and the Cochrane Library database to identify animal and human studies reporting on prenatal supplementation of 14 AAs falling within the following three groups: (1) arginine family: arginine, citrulline, glutamate, glutamine, asparagine, aspartate, proline, and ornithine; (2) BCAA: leucine, iso-leucine, and valine; and (3) methyl donors: cysteine, methionine, and the AA derivate choline. Search strings are provided .Two independent investigators (F.T. and A.T.) screened articles for inclusion using predefined inclusion and exclusion criteria in Early Review Organizing Software ), as described in detail in the Appendix. To be eligible for inclusion, studies needed to (1) to be performed in mammals with a normal-growth pregnancy or a complicated pregnancy resulting in fetal growth divergence: FGR, pre-eclampsia (PE), pregnancy-induced hypertension (PIH), GDM/diabetes mellitus, or prematurity; (2) to study the effects of oral supplementation with one of the 14 AAs for more than one day (at lib) or at least twice (as bolus) during pregnancy; and (3) to report one of the following outcomes: fetal/birth weight; maternal blood pressure (BP); maternal glucose or insulin levels; gestational weight gain; or development of pregnancy complications in human risk population including FGR, PE, PIH, GDM, prematurity, and neonates born small or large for gestational age (SGA or LGA). For human studies, we only included randomized controlled trials. The complete list of exclusion criteria is reported in the Appendix.Data were extracted in duplicate by F.T. and A.T. We extracted data on study characteristics, such as supplementation strategy and the  day of measurement, and for each outcome mean, SD, and number of subjects per experimental group were noted (see Appendix for more details).Risk of bias was assessed in duplicate by F.T. and A.T. using the risk of bias tools from SYRCLE for animal studies  and fromMeta-analyses were performed separately for normal-growth versus complicated pregnancies versus pregnancies at-risk of complications. All animal species were pooled together, and the analyses were performed for each AA group for each outcome only when more than five studies could be included. Fetal/birth weight (primary outcome) was compared between groups as a ratio of means (ROM) and, in humans, additionally presented as a mean difference (MD). Maternal BP, blood glucose or insulin levels, and gestational weight gain were presented as an MD, and development of pregnancy complication was presented as an odds ratio (OR). Pooled effect size estimates are presented with their 95% confidence intervals (95% CI). Data were analyzed using random- or mixed effects models, using nesting if multiple cohorts from one study were included .Meta-regression analyses were performed to study effects of modifiable factors in the complicated pregnancy group only, and were only performed if at least two studies per category were present. When studies reported data on multiple cohorts , then these were included in the meta-analysis as independent comparisons. Meta-regression was performed on species, type of pregnancy complications, administration timing (full pregnancy vs. partly), and scheme , intervention type (prevention or treatment), and control diet (isonitrogenous vs. not isonitrogenous in arginine family). For BP analysis, we used mean arterial pressure and, when not available, systolic BP. For the dose–response curves, a metabolic weight conversion was applied by a linear scaling exponent of 0.75 to correct for interspecies pharmacokinetic conversion .p-value below 0.05 was considered significant. Potential publication bias was visually examined in funnel plots and tested by Egger’s regression when over twenty studies reported an outcome. Heterogeneity (I2) among studies > 50% was considered significant. An influential case analysis was performed by examining residuals, weights, and Cook’s distances of model fits. A sensitivity analysis was executed by removing influential cases and by shifting cut-outs for meta-regression of MD or ROM. R software  and the Metafor package were used for all statistical analyses [A two-sided analyses .The search resulted in 17.329 hits. The majority of exclusions during the full-text screen was based on no in vivo studies on pregnant animals or humans followed by no supplementation of the amino acids of interest and resulted in 501 studies for full-text screening, of which we included 111 studies in our systematic review . We inclWe performed meta-analyses on fetal/birth weight following supplementation with AA in the arginine family, BCAA, and methyl donors. Regarding maternal BP and development of SGA, the arginine family was the only AA group for which a meta-analysis could be performed. A meta-analysis on the development of other pregnancy complications was not possible. Data for gestational weight gain were not pooled because, (1) without individual participant data, we had to estimate the mean weight gain and SD for studies that did report gestational weight at two different time points during pregnancy per group; (2) studies reported gestational weight gain over different gestational time periods, which did not consistently match the supplementation periods; and (3) gestational periods are very different between species. Too few studies reported on glucose levels to pool these data. No data on insulin resistance (HOMA-IR) were found. Results on glucose and gestational weight gain are described in the Appendix.n = 47) [n = 10) [n = 3) [n = 2) [n = 1) [n = 1) [N-Carbamyl) glutamate (NCG) [n = 4) [n = 2) [n = 1) [n = 1) [n = 1) [n = 1) [n = 1) [n = 1) [Data were extracted on fetal growth in response to prenatal supplementation of arginine family AA from 47 animal studies  ,87,88,89[n = 10) ,65,66,77 [n = 3) ,39,44, g [n = 2) ,67, prol [n = 1) , and asp [n = 1) ; 7 studite (NCG) ,57,63,77 [n = 4) ,85,86,87 [n = 2) ,83, Norw [n = 1) , Mexico  [n = 1) , USA (n  [n = 1) , China ( [n = 1) , and IndSupplementation of prenatal AA from the arginine family increases birth weight by 6% ) in complicated pregnancies . No effep-value correction for the 7 modifiers (p = 0.05/7 = 0.007). A dose–response relation for birth weight was absent with an effective daily dose already reached at the lowest tested dose .The sensitivity analysis identified the rat study by Sharkey et al.  as a senion bias . Howevern = 15) [n = 1 [The effect on BP was reported in ten rat ,90,91,92n = 15)  or citru) [n = 1  (Table A) [n = 1 , Italy [) [n = 1 , Norway ) [n = 1 , Poland ) [n = 1 , USA [94) [n = 1 .p = NS) [While prenatal supplementation with AAs from the arginine family did not affect BP in normal-growth pregnancies or the risk population, it reduced BPs, with 25 mmHg −34; −17) in complicated pregnancies . However in complp = NS) . Meta-ren = 8) [n = 3) [n = 2) [n = 1) [n = 4) [n = 2) [n = 2) [Prevention of pregnancy complications in human risk populations was mostly studied after arginine supplementation (n = 8) ,87,95,96n = 8)  assessed [n = 3) ,79,83 an [n = 2) ,79 and n [n = 1) , but the [n = 4) ,86,87,95p = 0.002) ; = 0.002) . The tre= 0.002) .n = 7) [n = 1) [n = 2) [n = 9) [n = 4) [n = 3) [Most studies reporting on fetal growth after BCAA supplementation were performed in rats (n = 7) ,101,102, [n = 1)  and pigs [n = 2) ,105; no  [n = 9) ,105, fol [n = 4) ,98,104,  [n = 3) ,98,99. T [n = 3) , Matsued [n = 3) , and Morp = 0.24, I2 = 69%; Prenatal BCAA supplementation did not improve fetal/birth weight in normal-growth ) or complicated pregnancy , p < 0.01), but did reduce I2 to 30%.Sensitivity analysis showed that Viana et al. , the onln = 3 [n = 14 [n = 4 [n = 3 [n = 5 [n = 2) [n = 1) [n = 2) [n = 1) [We included 30 animal studies 3 [n = 5 ,137,138 3 [n = 5 ,130,131 3 [n = 5 ,134,137 3 [n = 5 ,136,138.3 [n = 5  and only [n = 2) ,137 and  [n = 2) ,136 and p = 0.46; I2 = 96%; p-value was corrected for the 6 modifiers (p = 0.05/7 = 0.008). There was no clear publication bias visible in the funnel plot (p = 0.67). Sensitivity analysis showed that Mori et al. [p = 0.19, I2 = 91%) in normal-growth pregnancies. We speculate that the difference in effect in this study is caused by the high dose of methyl donor.Overall, methyl donor supplementation during normal-growth ), risk population ), or complicated pregnancy ) did not alter birth weight  [n = 2, Egypt and The Netherlands) [n = 4) [n = 1) [n = 2) [n = 2) [n = 1) [n = 2) [Prevention of pregnancy complications in a human risk population was studied using choline ( Africa) ,138 and erlands) ,137 (Tab [n = 4) ,137,138, [n = 1) , preterm [n = 2) ,137, PIH [n = 2) ,138, PE  [n = 2) ,138. Thr [n = 2) ,137,138, [n = 2) ,138. HowThe items to determine the risk of bias in animal studies were poorly reported and mostly unclear . The repThis systematic review and meta-analysis are unique in providing an elaborate overview of prenatal AA supplementation on fetal growth and related pregnancy complications in both humans and animals. Almost all studies focused on the effect of supplementation to target fetal undergrowth. Although 12 of the 14 searched AAs were included, arginine was by far the most studied for all outcome parameters.None of the three AA supplementation groups affected fetal growth in normal-growth pregnancies. Specifically, the arginine family improved fetal growth by 6% in complicated pregnancies. BCAA and methyl donors did not indicate an effect on fetal undergrowth; however, these data were sparse with, for example, only one BCAA study performed in growth-restricted pregnancies and no human studies at all. Within the competent arginine family, arginine and NCG were identified as the most potent, but due to co-linearity in sheep studies, and potential confounding by total nitrogen intake, we cannot conclude this with certainty. The beneficial effect of prenatal arginine supplementation on fetal growth was also reflected by the reduced risk of SGA development in the at-risk human population.Our observed reduction of BP in hypertensive disorders during pregnancy could prolong pregnancy, thereby improving fetal growth. While there was a strong dose–response curve observed when data across species were combined, no effect or even a potential worsening of BP was observed after supplementation with arginine in women with PE and/or FGR. Arginine might therefore be indicated at low doses to prevent FGR but not as maternal indication to directly treat hypertensive disorders of pregnancy.The effects evaluated in the present studies might be related to the ability of the placenta to secure adequate essential AA supply towards the fetus, assuming that maternal protein (and nitrogen) intake is of adequate quantity and quality. This would plead for a combined intervention with multiple AAs. Beneficial effects of arginine family supplementation might be mediated through the NO pathway . HoweverWe hypothesized that methyl donors could potentially normalize overgrowth. Unfortunately, only two studies used methyl donor supplementation (and one used arginine) in overgrowth (risk) pregnancies, leaving the answer to the research question inconclusive. Methionine at (very) high doses reduced fetal growth in normal-growth pregnancies. This is potentially due to reduced maternal food intake and a reduction in ovarian steroidogenic pathway activity that could be rescued by administration of exogenous estrone and progesterone ,116,119.Very little research was performed in diabetic pregnancies regarding the possible effect of AA supplementation on glucose and insulin levels. However, oral administration of choline prior to and during pregnancy in mouse models of maternal obesity has been reported to reduce fetal overgrowth ,142, whiThe major strength of this meta-analysis involves integration of data across species. This relatively novel but increasingly used methodology has been shown to be of great value to improve translation from animal studies to humans in several fields since (1) they provide insight on the safety of interventions because of the larger range of dosages, (2) they aid in determining factors influencing the effect size, (3) they reveal biases thus leading to less misinterpretation, and (4) they clarify differences in design between animal and human studies ,144. ForHigher heterogeneity in this integrated type of meta-analysis compared to clinical meta-analyses is inevitable due to the inclusion of different experimental designs. Of note, the aim of a meta-analysis of animal studies alone or combined with human studies is not to pinpoint the effect estimated to directly drive clinical practice. Rather, their goal is to investigate factors influencing treatment efficacy, by determining sources of heterogeneity. As such, high heterogeneity provides the chance to explore its source, and the results generate new hypotheses on how to improve efficacy of the intervention or design of future (human) studies. However, the relatively high heterogeneity in our meta-analysis could not always be fully explained by the performed meta-regression. Socio-economic status taken as a surrogate for baseline nutritional status could influence in particular the results of human supplementation, but included studies were performed either in countries with a similar socio-economic status/ethnics division or that did not have a different impact on effect size. Furthermore, animal models represent a part of a complex syndrome and could influence the results, with our main concern regarding studies supplementing with arginine in compromised animal models by a manipulated NO-pathway However, we could not identify an effect on birth weight or blood pressure when excluding studies using L-NAME-induced animal models.2 value in both the overall meta-analysis and meta-regressions on the effect of arginine family supplementation and birth weight. However, we could not find any reason for the apparent atypical result found in this study .Our risk of bias tool revealed that most human and animal studies failed to report on quality items or risk of bias items. The unclear risk of bias must be taken into account when interpreting the results . As we did not exclude any studies based on their risk of bias score, this may have contributed to the high heterogeneity . One study  could beFurthermore, fetal/birth weight is an interesting direct pregnancy outcome, but it does not necessarily correlate with other important obstetric, neonatal, and developmental programming outcomes related to improved long-term health. Hence, BCAA or methyl donors could have no effect on birth weight while still having beneficial or adverse developmental programming effects ,146. ThiOverall, this systematic review gives a broad overview of the reported effects of oral prenatal AA supplementation on fetal growth and related pregnancy outcomes. We conclude that none of the AA groups had any adverse effects on fetal growth at low doses. Supplementation with AAs from the arginine family improved birth weight in complicated pregnancies, and reduced risk of SGA development in a human risk population. However, the potency on maternal BP was less clear and the arginine family might not be indicated as maternal treatment for hypertensive disorders of pregnancies. Based on this systematic review and meta-analysis, we formed recommendations for future research, which are summarized in


PML-RARA rearrangement as a consequence of the translocation t. However, this abnormality alone is not able to trigger the whole leukemic phenotype and secondary cooperating events might contribute to APL pathogenesis. Additional somatic mutations are known to occur recurrently in several genes, such as FLT3, WT1, NRAS and KRAS, whereas mutations in other common AML genes are rarely detected, resulting in a different molecular profile compared to other AML subtypes. How this mutational spectrum, including point mutations in the PML-RARA fusion gene, could contribute to the 10%–15% of relapsed or resistant APL patients is still unknown. Moreover, due to the uncertain impact of additional mutations on prognosis, the identification of the APL-specific genetic lesion is still the only method recommended in the routine evaluation/screening at diagnosis and for minimal residual disease (MRD) assessment. However, the gene expression profile of genes, such as ID1, BAALC, ERG, and KMT2E, once combined with the molecular events, might improve future prognostic models, allowing us to predict clinical outcomes and to categorize APL patients in different risk subsets, as recently reported. In this review, we will focus on the molecular characterization of APL patients at diagnosis, relapse and resistance, in both children and adults. We will also describe different standardized molecular approaches to study MRD, including those recently developed. Finally, we will discuss how novel molecular findings can improve the management of this disease. Although acute promyelocytic leukemia (APL) is one of the most characterized forms of acute myeloid leukemia (AML), the molecular mechanisms involved in the development and progression of this disease are still a matter of study. APL is defined by the  RARA) gene on chromosome 17 and the promyelocytic leukemia (PML) gene on chromosome 15 that results in a PML-RARA fusion gene . Th. ThRARA , RARA2) ,32. Howe, RARA2) . Through, RARA2) .In APL, PML-RARA alters the nuclear structure of NBs, leading to their disruption into nuclear microspeckles . This isPML-RARA functions can be restored by the administration of two drugs, commonly used in clinical practice—ATRA and ATO ,47. ThesPML-RARA mice express a myeloproliferative disease phenotype and evolve to APL with a significant period of latency (6 to 18 months) and incomplete penetrance  . Ho. HoPML g in RARA ,63. The  in RARA ,64. OpenPML-RARA isoforms, the reciprocal RARA-PML fusion is found only in 70% to 80% of them, either as RARA1- and RARA2-PML (breakpoints between exons 4 and 5), or only as RARA1-PML (breakpoints upstream of exon 4) [Although all the patients harboring the t express at least one of the  exon 4) ,66. TherPML-RARA isoforms, sporadic cases of t-positive APL patients with atypical breakpoints, resulting in rare fusion transcripts, have been described (PML exon 6 (from 8 to 146 nucleotides), or the entire exon 6, as a result of a mis-splicing event or a genomic break within PML exon 6 (rarely in PML exon 5). Likewise, atypical bcr2 are frequently associated with insertions of three to 127 extra nucleotides (1 to 42 extra amino acids) of genomic DNA from RARA intron 2 [PML exon 6 [PML-RARA transcript with exon 5 skipped [In addition to the typical escribed . Althougintron 2 ,72,73,74PML intron 6 have also been reported. In these cases, the donor splice site of exon 7a or 7b is spliced directly with RARA exon 3 [PML intron 7 or RARA intron 2, respectively [PML exon 7c complementary sequence was inserted between part of exon 7c (308 nucleotides) and RARA exon 3 [RARA exon 3 have also been observed both in atypical bcr1 as well as in bcr3 transcripts [PML exon 4, which is then commonly involved in the splicing with RARA exon 3 [PML and RARA genes [PML-RARA fusion between PML exon 4 and part of the exon 1 of RARA2. This was the first time that a fusion transcript involving the alternative isoform of RARA was found in an APL patient [Atypical cases of bcr1 with breakpoints located downstream of A exon 3 ,77,79, oectively ,74,78,80nscripts ,73,79. TA exon 3 ,82,83. IPML-RARA isoforms have been correlated with diverse prognosis and responsiveness to treatments , likely due to the different PML domains retained in the fusion protein. However, the results from the different studies are controversial, mainly because of the substantial clinical heterogeneity associated. Some reports have shown that bcr3 patients would have a poor prognosis and an aggressive disease course [PML breakpoints downstream of intron 6 [PML-RARA isoforms [Both typical and atypical e course , as wellintron 6 ,70,75,77intron 6 ,72,78,80isoforms . RARA gene [ZBTB16 (formerly PLZF)-RARA fusion, derived from the t rearrangement [RARA gene with NPM1 [NUMA1 [STAT5B [PRKAR1A [FIP1L1 [BCOR [NABP1 (formerly OBFC2A) [TBL1XR1 (formerly TBLR1) [GTF2I [IRF2BP2 [FNDC3B [In roughly 1% to 2% of APL patients, novel translocations other than t at either the cytogenetic or molecular level have been identified. To date, 12 molecular fusion variants of APL have been described, all involving the ARA gene   , TBL1XR1y TBLR1) , GTF2I [) [GTF2I , IRF2BP2[IRF2BP2 , and FND [FNDC3B . Althoug [FNDC3B  . In the first case, RARG was fused to the nucleoporin 98 (NUP98) gene to produce the NUP98-RARG transcript [RARG was fused to the PML gene in a patient with the hypergranular subtype of APL [NUP98-RARG rearrangement might be resistant to this drug [In addition, two AML resembling APL cases with no anscript . In the e of APL . Due to his drug .PML-RARA rearrangement is the cytogenetic hallmark of APL, in vitro studies performed on transgenic mice support the hypothesis that secondary cooperating genetic events accumulated over time are essential to ultimately trigger the whole leukemic phenotype [Although henotype ,114. A whenotype ,116,117.MYC deregulation in APL cells [PML-RARA fusion gene [Almost half of pediatric and adult APL patients harbor further chromosomal alterations (ACAs) in addition to the t identified by conventional cytogenetics ,118. As PL cells  that canion gene ,122,123.ion gene ,125. Wition gene , it is aIn addition, studies carried out by single-nucleotide polymorphism array (SNP-A) tools have shown that acquired non-recurrent cytogenetic cryptic  variations are relatively common and impact negatively on the outcome of APL patients ,125. HowFLT3, NRAS, KRAS), tumor suppression (WT1), chromatin organization (ARID1B and ARID1A), oncogenes , and rarer mutations in other AML-pathways, including NPM1 mutations, DNA methylation , or epigenetic regulation (ASXL1) [DNMT3A, TET2, IDH1, IDH2, and ASXL1) jointly represent less than 6% of APL cases, these have been associated with a poor prognosis with regard to overall survival and disease free survival [The genetic features of APL have been analyzed by next-generation sequencing (NGS) approaches, showing a mutational landscape different from other myeloid malignancies ,116,128  (ASXL1) ,128. Altsurvival .FLT3-ITD and FLT3-D835 mutations in the FLT3 gene are the most frequent co-occurring events to PML-RARA both in pediatric and adult APL, representing up to 40% of cases, mainly associated with elevated white blood cell (WBC) counts [FLT3 mutations are associated with elevated WBC counts and poorer clinical outcomes [FLT3-ITD impedes retinoic acid, but no arsenic, responses in a murine model [FLT3-ITD AML cells via co-inhibition of FLT3 signaling pathway [FLT3-ITD [FLT3-oriented therapy in APL out of clinical trials [) counts ,130. Howoutcomes . It has ne model , and tha pathway ,134. OncFLT3-ITD ,134. Nevl trials . FLT3, the profile of mutations in pediatric APL is similar to adult patients, where recurrent mutations in WT1, USP9X, NRAS, and ARID1A are strongly related to de novo APL and in WT1 with relapsed APL [BRAF, KIT, PDGFRA) or transcriptional regulation  in both, adult and pediatric patients [In addition to psed APL ,64. Likepatients . Underlypatients . Therefopatients ,123,128.PML-RARA rearrangement [NRAS, RUNX1 and ARID1B, and rarely found in newly diagnosed APL, suggesting their possible role as predictive markers of relapse [PML-RARA fusion gene have been described in up to 30% of the relapsed cases [PML-RARA could contribute to 10–15% of patients who relapse or those eventually resistant to treatment by targeted therapy with ATRA and ATO [PML mutations are thought to inhibit ATO binding whereas RARA mutations could reduce the affinity to ATRA binding [PML or RARA are already present in a low burden at diagnosis, as unveiled by NGS, and expanded under treatment selection during disease evolution, acquiring, occasionally, mutations in other genes [FLT3 mutations, suggesting their different role in leukemogenesis and disease progression. Additional novel alterations have been described in both PML (A224G) and RARA  moieties. Moreover, concomitant mutation patterns have been identified in a non-recurrent manner during the evolution of the disease, affecting genes involved in pathways associated with clonal hematopoietic expansion, such as signaling pathways (JAK2), DNA methylation (DNMT3A and TET2), epigenetic regulation (ASXL1), splicing (SRSF2), transcriptional factors (ETV6), and tumor suppression (TP53) [WT1, epigenetic or kinase factor genes would be retained in the relapse, promoting the acquisition of additional aberrations, while in NRAS or FLT3 they would disappear, allowing access to new molecular subclones involved in the relapse [At diagnosis, about 70% of APL patients harbor a mean of 0.96 somatic mutations (range 0–2) additionally to angement ,128,135.angement ,128,135. relapse ,137. Mored cases   . In addi relapse . In mode relapse ,140. Ong relapse ,140. HowIRF8 driven by PML-RARA could trigger the advent and preservation of the leukemic clone in a mouse model, contributing to the acquisition of cooperative genomic events [ID1, BAALC, ERC, WT1 and KMT2E, alongside additional molecular events (such FLT3-ITD status and ∆Np73/TAp73 expression ratio), could improve the treatment outcome prediction in high-risk APL patients  potentially able to revert the transcriptional patterns of APL when properly targeted with specific drugs .PML-RARA transcript at the post-consolidation phase by modern PCR-based techniques could improve outcome prediction through the rapid accurate assessment of the response to treatment [PML-RARA transcript by PCR test with sensitivity of 10−4 [Although roughly 90% of newly diagnosed APL patients achieve long-term remission having received only targeted therapy, a considerable proportion of those patients relapsed with no evidence of predictive clinical parameters ,123,128.reatment ,144. Sevreatment ,149,150.reatment ,155,156. of 10−4 , as a va of 10−4 . PML-RARA transcript after treatment by nested RT-PCR [PML-RARA at the end of consolidation therapy [PML-RARA during treatment are of value outside of clinical trials [PML-RARA before the end of consolidation [Initial studies analyzed the presence of d RT-PCR ,160,161.d RT-PCR . A numbe therapy ,166,167.l trials . Recentllidation . Furtherlidation , MRD analidation . PML-RARA transcript, including atypical PML-RARA fusion transcripts [Although quantification using peripheral blood is an attractive option, a study comparing both sources showed that conversion to PCR positivity was detected earlier in bone marrow than in peripheral blood . Howevernscripts ,171. UsiFLT3mut, and Enasidenib for IDHmut), APL has been a pioneer, considering that this has been a reality for this neoplasm for 30 years [omic science  that we might broaden our perspective and explain the hitherto unsolved issues. This represents a great challenge for researchers in the near future, but some of the pillars seem to have already been built with the proposal, among others, of the first integrative score [In an era of medicine in which several novel cases of targeted therapy are emerging for AML (e.g., Midostaurin for 30 years ,172. It ve score .


Nicotiana tabacum is an important model plant, and its allotetraploid genome has recently been released, providing us with the opportunity to analyze the AQP gene family and its evolution. A total of 88 full-length AQP genes were identified in the N. tabacum genome, and the encoding proteins were assigned into five subfamilies: 34 plasma membrane intrinsic proteins (PIPs); 27 tonoplast intrinsic proteins (TIPs); 20 nodulin26-like intrinsic proteins (NIPs); 3 small basic intrinsic proteins (SIPs); 4 uncharacterized X intrinsic proteins (XIPs), including two splice variants. We also analyzed the genomes of two N. tabacum ancestors, Nicotianatomentosiformis and Nicotianasylvestris, and identified 49 AQP genes in each species. Functional prediction, based on the substrate specificity-determining positions (SDPs), revealed significant differences in substrate specificity among the AQP subfamilies. Analysis of the organ-specific AQP expression levels in the N. tabacum plant and RNA-seq data of N. tabacum bright yellow-2 suspension cells indicated that many AQPs are simultaneously expressed, but differentially, according to the organs or the cells. Altogether, these data constitute an important resource for future investigations of the molecular, evolutionary, and physiological functions of AQPs in N. tabacum.Aquaporins (AQPs) are a class of integral membrane proteins that facilitate the membrane diffusion of water and other small solutes.  Oryza sativa), Arabidopsis , maize (Zea mays), soybean (Glycine max), switchgrass (Panicum virgatum), foxtail millet , sorghum (Sorghum bicolor), Brachypodium distachyon, tomato (Solanum lycopersicum), poplar (Populus trichocarpa), cotton (Gossypium hirsutum), and potato (Solanum tuberosum) encode 39, 35, 36, 66, 68, 42, 38, 28, 47, 55, 71, and 41 AQP homologs, respectively [AQP genes in mammals [Aquaporins (AQPs), also known as major intrinsic proteins (MIPs), are small integral membrane proteins present in almost all living organisms ,2. Plantectively ,11,12, c mammals . Based o mammals ,15.3), antimony (Sb), arsenic (As), boron (B), glycerol, hydrogen peroxide (H2O2), silicon (Si), and urea (U) [2) and oxygen (O2) [+ and K+) channel activity [While many plant AQPs primarily function as water channels, they can also transport a wide range of substrates, such as ammonia  ,17,18,19gen (O2) ,21,22. Ractivity . AQPs fractivity ,27,28,292O2, CO2, NH3, As, Sb, and Si [The AQP structure comprises six transmembrane (TM) α-helices (TM1-TM6), which are linked by five loops (loops A–E) and two highly conserved NPA (Asn-Pro-Ala) motifs. They form homo- or hetero-tetrameric complexes in which each subunit acts as a functional water channel ,30. The , and Si ,17.Nicotiana tabacum (tobacco), a perennial herbaceous plant of the Solanaceae family, is an allotetraploid (2n = 4x = 48), which evolved by the natural hybridization of the ancestors of Nicotiana sylvestris  and Nicotiana tomentosiformis  about 200,000 years ago [N. tabacum is intensively studied as a versatile model organism for understanding genetics, functional genomics, cellular and molecular biology, biochemistry and physiology [AQP genes in the genomes of N. tabacum as well as its two ancestors, N. tomentosiformis and N. sylvestris, and analyzed the transcriptome data of N. tabacum plant and Bright Yellow-2 (BY-2) suspension cells [N. tabacum. Comparing the primary selectivity motifs, we further predicted their probable substrate transport activities. Altogether, this study provides new insights into the expression patterns in different organs and suspension cells, as well as the transmembrane transport selectivity of AQPs in N. tabacum.ears ago ,37. N. tysiology . In thison cells . We inveN. tabacum and its two ancestors, N. tomentosiformis and N. sylvestris, were searched for AQP genes, using pBLAST and AQP sequences from S. tuberosum and S. lycopersicum as queries. NtAQP protein sequences were analyzed and compared with SlAQP and StAQP for domain identification and functional annotation. Of 101 initial unique hits for NtAQPs, 13 were considered AQP pseudogenes and discarded after a manual inspection of their nucleotide and amino acid sequences and their TM domains. We finally obtained 88 genes encoding 90 full-length AQP proteins, and NtXIP1;1 and NtXIP1;2 genes encoding two splice variants (α and β), as shown in The whole genome shotgun sequence of AQP gene number in a Solanaceae plant genome. We identified 49 AQP genes encoding 51 and 50 full-length proteins in two N. tabacum ancestors, namely N. tomentosiformis and N. sylvestris, respectively, as shown in Physcomitrella patens [N. tabacum, we identified 34 PIPs, 27 TIPs, 20 NIPs, 3 SIPs, and 6 XIPs, including two splice variants. N. tabacum, contrary to the seven groups in Arabidopsis and soybean [Arabidopsis, rice, maize, poplar, and soybean, N. tabacum had two SIP groups, namely SIP1 and SIP2s, with two and one isoforms, respectively. Two XIP subgroups were observed in N. tabacum, and four XIP subgroups in potato [This represents the greatest a patens  were not soybean , and thr soybean ,12. SimiSubcellular localization prediction was conducted using WoLF PSORT software, and the results were as follows: NtPIPs–plasma membrane (PM) and chloroplast, as shown in N. tabacum, have two conserved NPA motifs in loops B and E, as shown in N. tabacum SIPs, the alanine in the first NPA motif is substitued by either a threonine  or a leucine (SIP2s) residue, as shown in N. tabacum genome, there are four XIP genes, including NtXIP1;1 and NtXIP1;2, which encode two splice variants (α and β) [N. tabacum XIPs in the first NPA motif (loop B), alanine is substituted by a valine residue, as shown in Like their counterparts in other plant species, all PIPs, TIPs, NIP1s, NIP2s, NIP3s, NIP4s, NIP7s, and NIP8s from α and β) . In N. tN. tabacum AQP genomic sequences were analyzed for introns and exons, as shown in AQP subfamily. NtPIP genes have two or three introns, except for NtPIP2;3, which has a single intron, and NtPIP1;5, NtPIP1;7, NtPIP1;11, and NtPIP2;8, which have no introns, as shown in NtPIP2;2 has a very long intron (~15 kb), as shown in NtTIP subfamily exhibits relatively stable gene structure in comparison with other subfamilies. The majority of them have two introns except for TIP1;2–4 and TIP1;8–9, which have a single intron and NtTIP1;1 with no intron, as shown in NtNIPs have four introns with variable intron-exon organization, as shown in NtNIP5;1 has three introns, and NtNIP3s and NtNIP6;1 have five introns, while NtNIP8;2 possesses a unique gene structure with six introns (the greatest number of introns in an AQP gene), one of which is 10 kb long, as shown in NtSIP genes have two introns, except for NtSIP2;1, which has no intron. The NtXIPs gene structure was very conserved with two introns, except for NtXIP2;1, which has a single intron, as shown in The http://prosite.expasy.org/scanprosite/), to identify the substrate specificity-determining positions (SDPs) based on the ar/R, FP, and NPA motifs, and thereby the predicted substrate(s) of each isoform, as shown in We identified the four amino acid residues at the ar/R selectivity filter and the five residues in the FPs using sequence alignments, and used them to group the NtAQPs based on the amino acid residue properties and to compare these groups with those of other species, such as tomato and potato, as shown in 2 channels and thirteen PIPs (mainly PIP2s) are predicted H2O2 channels, as shown in 2O2 channels, and TIP1s and TIP4s are predicted urea channels, as shown in 3 channels, which is in agreement with experimental evidence in other species [2O2 channels, respectively. The NtSIPs are grouped into two groups based on both the ar/R selectivity filter and FPs, as shown in 2O2 channels, as shown in 2O2, NH3, and urea, but not water [The ar/R selectivity filter in all the NtPIPs is composed of F, H, T, and R residues in TM2, TM5, LE1, and LE2, respectively, and is identical to the ar/R filter found in all the plant PIPs, as shown in  species ,42. Base species ,7,11. Ouot water ,43.NtAQPs transcript levels in roots, leaves, and flowers, as shown in NtAQPs genes, 73, 75, and 71 are expressed in mature flowers, leaves, and roots, respectively, and 68 genes are ubiquitously expressed in all analyzed organs. PIPs are expressed in flowers, leaves, and roots but differently according to the isoforms. A greater number of NtPIP1 genes are expressed in flowers and leaves than in roots—NtPIP1;1 and NtPIP1;10 being the most expressed isoforms in flowers and leaves, respectively, and NtPIP1;3–8 and NtPIP1;11 not being expressed in roots. A decreased amount of NtPIP2 transcripts is generally observed, but all NtPIP2s are expressed in the three organs with the exception of NtPIP2;9 and NtPIP2;18, which are not expressed or are expressed very little, as shown in Figure 5. NtTIP gene expression levels are often greater in the leaves compared with the other organs, even if a greater number of NtTIP genes are expressed in roots, as shown in NtNIP genes, seven  are not or very lowly expressed in the three organs in the tested conditions. The other NtNIP genes are relatively less expressed compared to the other AQP subfamily members, as shown in NtSIP genes were ubiquitously expressed in flowers, leaves, and roots, NtSIP1;2 being the most expressed NtSIP in the leaf, as shown in NtXIP1;1 was the most expressed NtXIP in the three organs with the expression of the others being very decreased. The heatmap based on FPKM values shows the N. tabacum BY-2 suspension cells are widely used to study different physiological processes, the role of specific proteins, or as a heterologous expression system to produce high value pharmaceutical antigens or antibodies [AQP genes are expressed in those cells that grow in suspension in an aqueous environment. RNA from wild-type BY-2 cells was extracted and RNA-seq data analyzed for the expression of the 88 NtAQP genes. The heatmap based on FPKM values is shown in NtAQP genes were detected in BY-2 cells growing in a standard MS medium. The most expressed NtAQP genes were 11 PIP1s, TIP1;1, the three SIPs, and XIP1;1.tibodies ,46,47,48N. tabacum genome databases, we identified 88 complete AQP genes, almost twice the number of AQP genes identified in tomato and potato [AQP homologs always varies between plant species, the dicot plant genomes usually encoding more homologs than the monocot plants, except for the 68 full-length AQP genes found in P. virgatum, a polyploid monocot species [AQP genes in the N. tabacum genome arose from an allotetraploidization event that occurred about 200,000 years ago [N. tomentosiformis and N. sylvestris, which each have 49 AQP genes. The difference between the identified gene number in N. tabacum (88) and the sum of the N. tomentosiformis and N. sylvestris AQP genes (98) suggests that some were lost after the polyploidization event. In addition, we also could not exclude the recent local duplication events in each species, as deduced by the protein phylogenetic tree, shown in NtAQP expression data analysis. For instance, the duplicated NtPIP2;1 and NtPIP2;2 showed different expression levels, which can be organ dependent. By screening the d potato ,7. The n species . The greears ago ,38 betweNicotiana species, similar to most other dicots, except for Brassicaceae and monocots, which have no XIP subfamily [N. tabacum AQPs have been characterized [2 channel permeability [2 membrane diffusion [2, was reported to be facilitated by NtPIP1;3 when expressed in yeast, and an increased NtPIP1;3 transcript level was measured in N. tabacum roots after a seven day hypoxia treatment [2 membrane permeability. NtXIP1s are the first plant XIP isoforms that have been functionally characterized [2O2, glycerol, boron, and urea, but not water [N. tabacum results in disturbed boron tissue distribution, leading to boron deficient phenotypes in meristems and young leaves [NtXIP1;1 gene contains a sequence motif in the first intron that initiates an RNA-processing mechanism that results in two splice variants (α and β), resulting in two amino acid residue differences [NtXIP1;2, NtoXIP1;1, NsXIP1;1, and NtoXIP2;1 isoforms, and also XIPs from S. tuberosum and S. lycopersicum [We identified five subfamilies  among the three ubfamily . Severalcterized ,53,54,55cterized ,22. NtAQeability . This diiffusion . More recterized . NtXIP1;ot water . NtXIP1;g leaves . Interesferences . We alsopersicum , indicat2 and H2O2 diffusion, respectively, in addition to water, as shown in 2O2 [2O2, boric acid, and urea, and were confirmed in transport assays performed with NtXIP1;1 [To elucidate the substrate specificity of NtAQPs, different signature sequences, including SDPs, NPA motifs, ar/R filter, and FPs were identified, as shown in n in 2O2 ,57,58. Nn in 2O2 . NIPs arNtXIP1;1 ,43. In aNtXIP1;1 . FinallyNtXIP1;1 . This glNtXIP1;1 . TherefoNtAQP transcript levels are dependent on the plant organs, but it is quite surprising to observe that 68 of 88 AQP genes are ubiquitously expressed in roots, young leaves, and flowers. PIP and TIP transcripts are relatively more abundant than other subfamily mRNAs, as shown in NIP expression level is low, except for NtNIP5;1, but due to their metalloid substrate specificity, a more restricted tissue/cell expression pattern in specific physiological conditions might be expected [NtAQP genes were also detected in BY-2 suspension cells growing in a standard MS medium, even if the relative expression level between them was different to what was observed in plant organs. This could be due to the dedifferentiated nature of those cells and/or the specific cell environment of the culture medium. The most expressed NtAQP genes in BY-2 cells are 11 NtPIP1s, NtTIP1;1, the three NtSIPs, and NtXIP1;1. High NtPIP gene expression was also reported in maize Black Mexican Sweet (BMS) suspension cells [PIP expression varies according to BMS cell growth stages, and this is correlated with greater cell water permeability, measured at the end of the log phase and stationary phase [PIP and TIP gene expression in BY-2 suspension cells might also be involved in the control of cell expansion. Cauliflower BobTIP26–1 overexpression in suspension cells (N. tabacum cv. Wisconsin 38) increases the cell volume [NtSIPs is also intriguing, knowing that SIPs are mostly expressed in the endoplasmic reticulum and their function is still unknown. ZmSIP1;2 is also expressed in BMS suspension cells, and its expression is not dependent on the growth stage [Agrobacterium tumefaciens or biolistics, and great cell amounts could be obtained for protein purification and reconstitution [As expected, expected ,61,62. mon cells , but in on cells ,64. We mry phase . This mil volume , cell enth stage . Suspenstitution .N. tabacum as well as in its two ancestors, N. tomentosiformis and N. sylvestris. The signature sequence for substrate selectivity and the possible biological function of NtAQPs were predicted. The transcriptomic data of N. tabacum and BY-2 suspension cells represent an excellent resource to guide further analysis of the function of any selected AQP isoform. In this comprehensive analysis, we identified a highly diverse AQP gene family in N. tabacum, N. tomentosiformis, and N. sylvestris available at the Sol Genomics Network (https://solgenomics.net/organism/Nicotiana_tabacum/genome), were searched for AQPs using BLASTp (http//http://www.ncbi.nlm.nih.gov/blast/Blast.cgi?PAGE = Proteins) tools with the protein sequences of 47 AQPs from S. lycopersium (tomato) and 41 AQPs from S. tuberosum (potato) as queries. Every sequence from each species was individually compared with functional annotations by browsing the N. tabacum databases.The genomes of S. lycopersium AQPs (SlAQPs) and S. tuberosum AQPs (StAQPs) using the Clustal Omega program  and a phylogenetic tree was built using Molecular Evolution Genetic Analysis (MEGA), version 7.0 [NtAQPs amino acid sequences were separately aligned with sion 7.0 . The phyhttp://gsds.cbi.pku.edu.cn/) using the NtAQP gene and CDS sequences as input. The TM α-helices were predicted by TMpred (http://www.ch.embnet.org/software/TMPRED_form.html) and SOSUI (http://bp.nuap.nagoya-u.ac.jp/sosui/).Gene structures were determined by the GSDS 2.0 software (http://wolfpsort.org/), TargetP (www.cbs.dtu.dk/Services/TargetP), Cello prediction system (http://cello.life.netu.edu.tw/), and MultiLoc2 (www.abi.inf.uni-tuebingen.de/Services/MultiLoc2) tools. The subcellular localization of NtAQPs was predicted by using the WoLF PSORT .The aligned NtAQP sequences were searched manually for SDPs by following the prediction explained previously ,17 and cNtAQP genes in different organs  were obtained from the Gene Expression Omnibus (GEO) repository and GenBank Sequence Read Archive (SRA) under the accession code SRP029183 . Three biological replicates were obtained from each organ. The FPKM values of the respective NtAQP genes were extracted from the databases and transformed into logarithmic (log10) values to generate the heatmap. A heatmap showing the logarithmic NtAQPs transcript levels in root, leaf, and flower was generated using Microsoft Excel conditional formatting, based on the normalized FPKM values. In our analysis, a logarithmic FPKM value > 0 was used as a threshold to consider whether a gene is expressed.Transcript levels as FPKM (Fragments per Kilobase of Transcript per Million Mapped Reads) values of N. tabacum cv. BY-2 suspension cells were grown in the dark at 25 °C with agitation on a rotary shaker (90 rpm) in liquid MS medium , 30 g/L sucrose, 0.2 g/L KH2PO4, 2.5 mg/L thiamine, 50 mg/mL myo-inositol, and 0.2 mg/L 2,4-D, pH 5.8 (KOH)). Cultures were grown in 50 mL of medium in a 250 mL Erlenmeyer flask and a 5% inoculum was transferred each week into fresh medium. BY-2 cells (100 mg) were collected three days after inoculation  and the total RNA was extracted from three biological replicates and sent to the Macrogen Company, which performed the library preparation, RNA sequencing, and data analysis. For the library preparation, the mRNA was purified from total RNA and transformed into a template molecule library, appropriate for subsequent cluster generation using the Illumina® TruSeq™ RNA Sample Preparation Kit. The first step in the workflow encompassed purifying the poly-A-containing mRNA molecules using poly-T oligo-attached magnetic beads. After purification, the mRNA was split into small pieces using divalent cations under high temperature. The cleaved RNA fragments were copied into first strand cDNA using reverse transcriptase and random primers. This was followed by the second strand cDNA synthesis using DNA polymerase I and RNase H. These cDNA fragments then went through an end repair process, the addition of a single “A” base, and then the ligation of adapters. Finally, the products were purified and enriched with PCR to generate the final cDNA library. The library was then submitted for paired-end 2 × 100 bp sequencing in Illumina HiSeq2000. Sequencing data were analyzed through the Trinity pipeline, which permitted de novo transcriptome reconstruction. The transcript abundances were calculated using RSEM (1.2.15) software [https://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM = blastx&PAGE_TYPE = BlastSearch&LINK_LOC = blasthome) was used to compare the six-frame translation products of a nucleotide query sequence against a protein sequence database (go_v20150407). Finally, the FPKM values for the respective AQP genes were identified from the annotated BY-2 cell transcriptomic data. A heatmap was generated based on the transformed logarithmic (log10) FPKM values. Similar to organ specific expression data, FPKM values > 0 were used as a threshold to consider whether a gene is expressed.software . Blast-X


Passiflora edulis Sims) is an economically valuable fruit that is cultivated in tropical and subtropical regions of the world. Here, we report an ~1341.7 Mb chromosome-scale genome assembly of passion fruit, with 98.91% (~1327.18 Mb) of the assembly assigned to nine pseudochromosomes. The genome includes 23,171 protein-coding genes, and most of the assembled sequences are repetitive sequences, with long-terminal repeats (LTRs) being the most abundant. Phylogenetic analysis revealed that passion fruit diverged after Brassicaceae and before Euphorbiaceae. Ks analysis showed that two whole-genome duplication events occurred in passion fruit at 65 MYA and 12 MYA, which may have contributed to its large genome size. An integrated analysis of genomic, transcriptomic, and metabolomic data showed that ‘alpha-linolenic acid metabolism’, ‘metabolic pathways’, and ‘secondary metabolic pathways’ were the main pathways involved in the synthesis of important volatile organic compounds (VOCs) in passion fruit, and this analysis identified some candidate genes, including GDP-fucose Transporter 1-like, Tetratricopeptide repeat protein 33, protein NETWORKED 4B isoform X1, and Golgin Subfamily A member 6-like protein 22. In addition, we identified 13 important gene families in fatty acid pathways and eight important gene families in terpene pathways. Gene family analysis showed that the ACX, ADH, ALDH, and HPL gene families, especially ACX13/14/15/20, ADH13/26/33, ALDH1/4/21, and HPL4/6, were the key genes for ester synthesis, while the TPS gene family, especially PeTPS2/3/4/24, was the key gene family for terpene synthesis. This work provides insights into genome evolution and flavor trait biology and offers valuable resources for the improved cultivation of passion fruit.Passion fruit ( Passiflora, which belongs to the Passifloraceae family in the Malpighiales order, includes more than 520 species worldwide, most of which are distributed in the Americas, including Colombia, Brazil, Ecuador, and Peru, with a few in other tropical and subtropical areas, such as southeast Asia, Australia, and New Zealand2. Based on morphology, phylogeny, simple sequence repeats (SSRs), and chloroplast genome analysis, it was concluded that the family could be divided into four subgenera: Astrophaea, Decaloba, Deidamiodes, and Passiflora4. In addition, the subgenus Passiflora is the largest genus of Passiflora and comprises ~240 species that are generally regarded as typical passion flowers. The abundant germplasm resources of the family represent a diversity of phenotypic traits. Some cultivars exhibit good cold tolerance, disease resistance, and fruit quality, providing good materials for genetic breeding and resource development.Passiflora species are widely cultivated in tropical and subtropical areas of the world due to their edible, medicinal, and ornamental value6. In terms of edible value, Passiflora ranks second in the category of edible fruits, with ~60 fruits, including those from P. edulis, P. edulis f. flavicarpa, P. ligularis, P. quadrangularis, and P. tarminiana var. mollissima7. In terms of medicinal value, many Passiflora plants have a long history of use in traditional folk medicines in some American and European countries8 as remedies for many neurogenic diseases. The extracts from the leaves, fruits, rind, and seeds have been reported to contain C-glycosyl flavonoids, including vitexin, isovitexin, orientin, isoorientin, luteolin, apigenin, kaempferol, and other active substances with sedative, antioxidant, anti-inflammatory, anxiolytic, and anticarcinogenic effects11.12. Although passion fruit is widely cultivated in the tropical and subtropical areas of the world, Brazil is the largest producer and consumer, with a cropping area of approximately 61,842 ha yielding 923,035 tons per year13. In China, passion fruit is planted on 44,466 ha with an annual output of ~590,300 tons and an output value of 3 billion yuan.In terms of ornamental value, most passion flowers have large floral organs, bright coronal filaments, fine nectariferous structures, a rich fragrance, and luxuriant branches and leaves; thus, they are used as ornamental plants, hedges, and flower racks15. The cytogenetics of the subgenus Passiflora are well established. Most Passiflora subgenera are diploid, but the number of chromosomes varies. For example, P. edulis and P. alata have 2n = 18, while P. foetida has 2n = 2016. Recently, researchers constructed a large-insert bacterial artificial chromosome (BAC) library and provided the first insight into the structure and content of the passion fruit genome. The library consisted of 82,944 clones with an average insert size of 108 kb13. This BAC library provides a new resource for genetic and genomic studies as well as a valuable tool for future whole-genome studies. However, the genome of passion fruit has not been sequenced, and species-specific molecular markers have not yet been developed. The lack of transcriptional and genomic information on passion fruit greatly limits genetic and breeding research on this species; thus, more detailed molecular and genomic resources are needed to thoroughly investigate the genetic diversity of passion fruit species.To date, genetic research on passion fruit has mainly focused on evaluating its genetic diversity through identifying molecular markers, constructing fingerprints, and determining genetic relationshipsAlthough passion fruit is an economically and ornamentally important tropical fruit, the lack of available genomic information greatly limits the study of passion fruit. In this study, we assembled a high-quality passion fruit genome and performed a detailed analysis of the genome evolution and underlying mechanism of flavor synthesis, which will lay a solid foundation for genetic studies and improvements in passion fruit.P. edulis, a cultivar of purple passion fruit  with the default parameters, 989.88 million  clean paired-end reads were obtained . A total of 3 μg of RNA was used for library preparation with insert sizes of 350 bp, and sequencing was performed on an Illumina NovaSeq 6000. The RNA-seq reads of passion fruit were obtained for gene prediction analysis.17 was performed on 516.05 million 150 bp paired-end cleaned reads, and the genome size was estimated to be 1395.76 Mb  analysis7 analysihttps://github.com/Nextomics/NextDenovo) and then used as input for Smartdenovo (https://github.com/ruanjue/smartdenovo) assembly. The parameters for read correction and assembly were as follows: read_cutoff = 1 k, seed_cutoff = 30 k; -k 21 -J 5000. This resulted in a first assembly with a total size of ~2472.5 Mb and a contig N50 of ~6.3 Mb (Supplementary Table https://github.com/Nextomics/NextPolish). Polishing was performed three times for the Nanopore reads and four times for the cleaned reads from NovaSeq 6000. The corrected genome  were anchored to nine pseudomolecules (Supplementary Table Nanopore reads were corrected using NextDenovo (19 (Embryophyta dataset) assessments on the assembly. Approximately 91.56% of the complete gene elements were found in the genome  based on a self-BLAST search. We further used RepeatMasker (v4.0.5) (http://www.repeatmasker.org/) to search for known repetitive sequences using a cross-match program with a Repbase-derived RepeatMasker library and the de novo repetitive sequences constructed by RepeatModeler. The repeat-masked genome was used as input to two categories of gene predictors.We identified de novo repetitive sequences in the passion fruit genome using RepeatModeler (v1.0.4) (22 and SNAP (v2006-07-28 https://github.com/KorfLab/SNAP) were run with the default parameters, and the training sets used were monocots and maize, respectively. For RNA-seq-based prediction, 6 Gb of RNA-seq reads from a mixed tissue sample were filtered to remove adaptors and trimmed to remove low-quality bases. Processed RNA-seq reads were aligned to the reference genome using TopHat2 (version 2.0.7)23. The transcripts were then assembled using Cufflinks (version 2.2.1)24.Protein-coding genes were predicted using a pipeline that integrated de novo gene prediction and RNA-seq-based gene models. For de novo gene prediction, Augustus (v3.0.3)25, the tRNAs were predicted using tRNA scan-SE (v1.23)26, and other ncRNA sequences were identified using the Perl program Rfam_scan.pl (v1.0.4) by inner calling using Infernal (v1.1.1)27.The rRNAs were predicted using RNAmmer (v1.2)28. The Gene Ontology (GO) terms for genes were obtained from the corresponding InterPro or Pfam entry. Pathway reconstruction was performed using KOBAS (v2.0)29 and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.Functional annotation of the protein-coding genes was carried out by performing BlastP  searches against entries in both the NCBI Nonredundant (Nr) and Swiss-Prot databases. Searches for gene motifs and domains were performed using InterProScan (v5.28)30 to identify TFs and PKs. The predicted gene sets were then used as queries in searches against the database. Finally, putative TFs belonging to 88 families and putative PKs belonging to 113 families were identified  tree using FastTree (v2.1.9)32. This ML tree was converted to an ultrametric time-scaled phylogenetic tree by r8s using the calibrated times from the TimeTree33 website.Orthologous gene clusters in passion fruit genomes and 19 other representative plants  values of the homologs within collinear blocks were calculated using the Nei-Gojobori approach implemented in PAML35, and the median Ks value was considered to be representative of the collinear blocks. The values of all gene pairs were plotted to identify putative whole-genome duplication events within passion fruit. The duplication time was estimated using the formula t = Ks/2r, which represented the neutral substitution rate and was used to estimate the divergence time between passion fruit and other species. A neutral substitution rate of 8.12 × 10−9 was used in the current study.Syntenic blocks were identified using MCScanX with the default parametersThree fruit samples  with six biological replicates were collected to extract metabolites  ≥ 1, were considered significantly differential metabolites. The identified metabolites were annotated using the KEGG compound database (http://www.kegg.jp/kegg/compound/), and the annotated metabolites were then mapped to the KEGG pathway database (http://www.kegg.jp/kegg/pathway.html).Qualitative analysis of the raw data obtained via GC-MS was performed using Qualitative Analysis Workflows B.08.00 software, and quantitative analysis was performed using MassHunter software. The internal standard was used to normalize the quantitative data. Metabolites with significant differences in content, indicated by a fold-change ≥2 or ≤0.5, a All three samples  were frozen in liquid nitrogen immediately following harvesting. Each sample had two biological replicates. RNA isolation, library construction, and sequencing were performed as described for the RNA-seq analysis for gene prediction analysis. Raw reads were trimmed to remove adaptors and enhance quality. Reads that were <100 bp in size after trimming were discarded. Overall, 94,885,772 (two replicates) to 98,420,318 (two replicates) raw reads were obtained for each sample (Supplementary Table 23 was used to map clean reads to the genome with the default parameters. Transcripts were assembled using Cufflinks (version 2.2.1)24. Gene expression was measured as fragments per kilobase of transcript per million fragments mapped (FPKM) using Cufflinks. Differentially expressed genes (DEGs) were determined using DEseq236. The false discovery rate was used to adjust the P-values. Genes with significant differences in expression, |log2Fold Change | ≥ 1, and adjusted P-value <0.05 were considered DEGs and were annotated to GO terms and KEGG pathways.The TopHat2 package (version 2.0.7)37. Hydroperoxide lyase (HPL), acyl carrier protein-acyltransferase (ACP-AT), acyl-CoA oxidase (ACX), pyruvate decarboxylase (PDC), cytochrome P450 (CYP), epoxyde hydrolase (EHL), fatty acid desaturase (FAD), fatty acid epoxidase (FAE), fatty acid hydroxylase (FAH), hydroperoxidase lyase (HPL), isopentenyl-diphosphate δ-isomerase (IDI), monoterpene synthase (MTS), carotenoid cleavage dioxygenase (CCD), farnesyl diphosphate synthase (FPS), geranylgeranyl diphosphate synthase (GGPS), geranyl-diphosphate synthase (GPS), and 4-hydroxy-3-methylbut-2-enyl diphosphate reductase (HDR) proteins were identified by BLASTP based on Arabidopsis thaliana-related proteins. We then confirmed the presence of the conserved domain within all protein sequences and removed members without a complete domain. The protein domains of these homologs were predicted by Pfam (http://pfam.xfam.org/). Only the genes with the same protein domain were considered homologs. The cis-element analysis of the ADH and TPS gene family promoters was carried out using the cis-acting regulatory elements database (PLANTCARE) (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/).To investigate the genes involved in the volatile organic compound (VOC) biosynthesis pathways, especially the fatty acid and terpene metabolic pathways, in the passion fruit genome, 21 gene families were detected from the HMM domain models and BLASTP results. Terpenoid synthase (TPS) proteins, alcohol acetyltransferase (AAT) proteins, alcohol dehydrogenase (ADH) proteins, aldehyde dehydrogenase (ALDH) proteins, and lipoxygenase (LOX) proteins were identified by screening the passion fruit genome sequences using HMMER3.0 software with domain models PF03936 and PF01397; PF07247; PF08240, and PF00107; PF00171; and PF00305 as queriesP. edulis purple passion fruit cultivar, with a large and attractive corolla  were assigned to a chromosomal location (Supplementary Tables 39. The average GC content of passion fruit (38.68%) was lower than that reported in a previous study (42%)13  followed by Brassicaceae  and was distant from other plants  were characterized in V. vinifera, H. brasiliensis, M. esculenta, and P. edulis. The peak Ks was 0.6 for homologous gene pairs , we can see the collinearity of these three species  were identified between the transcriptomes of the T1 and T2 samples , ‘biosynthesis of secondary metabolites’ (424 DEGs), ‘starch and sucrose metabolism’ (90 DEGs), and ‘fatty acid biosynthesis’ (28 DEGs) were significantly enriched , and the differential multiples of the metabolites with PCC > 0.8 in each group are shown in a nine-quadrant diagram  were high in all three stages  model, the variables with high correlations and weights in different datasets were preliminarily assessed based on the loading diagram, and the important variables affecting another omics dataset were screened out. The results showed that the top 10 metabolites affected by the transcriptome included three ketones, three esters, two benzenes, one alcohol, and one imine , hexanoic acid ethyl ester (3896-fold), butanoic acid ethyl ester (1154-fold), and butanoic acid 1-methylloctyl ester (144-fold)  Fig. , all of ld) Fig. . TherefoArabidopsis thaliana to confirm the classification of ADH family proteins in passion fruit , ACP-AP (eight proteins), PDC (four proteins), CYP (16 proteins), EHL (15 proteins), FAE (eight proteins), FAH (two proteins), and LOX (18 proteins). Expression analysis also indicated that some genes changed with fruit development, such as PeLOX5/18, PePDC3, PeFAE6, PeFAH2, PeCYP7/13, PeEHL13/15, PeACP-AP1/5/6/7, and PeAAT3. These genes, especially the ADH genes, may play an important role in the metabolism of esters.Esters are mainly synthesized by the fatty acid pathway, and we identified 13 important gene families in this pathway Fig. . Most ofnts Fig. , while tArabidopsis thaliana43, and 21 PeTPSs belonged to the TPS-a subfamily, 16 belonged to the TPS-b subfamily, and three belonged to the TPS-f subfamily  are regarded as the main precursors of ester-, alcohol-, and aldehyde volatiles55. FA-derived volatile organic compounds also make significant contributions to the flavor of many fruits and vegetables, including banana56, apple57, strawberry58, melon59, and tomato55. FAs are metabolized by β-oxidative enzymes, including LOX, HPL, ADH, AAT, and others. In addition, terpenes are important members of passion fruit VOCs, including linalool, (E) - 4,8-dimethylona-1,3,7-triene 3-buten-2-one, terpinen-4-ol, beta-ionone, and 3-carene. Terpenes are biosynthesized from the 5-carbon isoprenoid precursor isopentenyl-diphosphate (IDP) and its isomer dimethylallyl diphosphate (DMADP)60, and TPS enzymes then convert them into structurally diverse volatile monoterpenes and sesquiterpenes or semivolatile and nonvolatile diterpenes61. Terpenes are also abundant in many plants, such as the foliage of Eucalyptus62, tea tree63, coriander64 and carrot61, providing the characteristic smell of these plants. In this work, we analyzed key genes in the fatty acid and terpene metabolic pathways, and 13 and eight important gene families were identified in passion fruit, respectively. Interestingly, we found that the expression levels of ACX13/14/15/20, ADH13/26/33, ALDH1/4/21, HPL4/6, FAD13/50/52/53/55, PeLOX5/18, PePDC3, PeFAE6, PeFAH2, PeCYP7/13, PeEHL13/15, PeACP-AP1/5/6/7, and PeAAT3 in the fatty acid pathway were relatively high and changed with fruit development, and that those of PeTPS2/3/4/24, PeHDR1, PeCDD1, and PeMTS1/4 in the terpene synthesis pathway were relatively high and changed with fruit development, suggesting that these play important roles in VOC synthesis65. Notably, we found that both the ADH and TPS gene families have a total of 41 members in the passion fruit genome, tandem duplication was found to contribute to passion fruit ADH and TPS gene family expansion, and the expression patterns of ADH and TPS are different during fruit development and ripening. A phylogenetic tree generated by aligning the TPS proteins among passion and Arabidopsis thaliana revealed that 21 PeTPSs belong to the TPS-a subfamily, 16 belong to the TPS-b subfamily, and three belong to the TPS-f subfamily. The TPS-a subfamily consists of sesquiterpene and diterpene synthases, the TPS-b subfamily consists of monoterpene synthases, and the TPS-f subfamily consists of linalool synthases43. The classification of the TPS gene family was consistent with that of terpenes detected in the metabolome. Among the ADH and TPS gene families, the expression levels of PeADH13/26/33 and PeTPS2/3/4/24 increased gradually with fruit development, which is consistent with the increasing trend of ester and terpene metabolite contents. The same results were reported in studies of mango67 and pear68. These results indicated that these genes may play an important role in passion fruit flavor biosynthesis. Fruit flavor is an important index that reflects the quality of fruit and can attract consumers and enhance market competitiveness. Unfortunately, as a consequence of linkage with nearby genes, selection for alleles of genes associated with larger fruits altered metabolite profiles, altered fruit metabolite content and had strong negative effects on fruit flavor69. Passion fruit is characterized by a variety of fruit flavors; therefore, it is of great significance to study flavor metabolites and their related genes and to select and retain them in future breeding work.As a medicinal and edible plant, passion fruit contains various biologically active substances. The metabolic and synthetic pathways of these substances are unclear. The genomic, transcriptomic, and metabonomic data provided new insights into the unique biosynthetic processes of passion fruit, showing that ‘metabolic pathways’ and ‘secondary metabolic pathways’ were the main pathways used to produce these active substances. The O2PLS model combined with gene expression level analysis identified nine candidate genes, of which four functionally annotated genes were In summary, the high-quality reference genome combined with transcriptome and metabolome analysis provided insights into the genome evolution and flavor synthesis of passion fruit. The data from this study also offer valuable resources for genetic studies and the improvement of passion fruit, including genome-assisted breeding of novel cultivars with desired traits and exceptional economic fitness.Supplementary Figure 1-17Supplementary Tables 1-23