AFS was not associated with the other cell populations in PB. BM PC numbers correlated with PB PC numbers and showed similar HRs for AFS. A further subdivision based on relative BM and PB PC numbers showed that BM PC numbers, rather than mobilization, associated with AFS. Both PB and BM PC numbers are associated with AFS independently from traditional risk factor and show very similar risk profiles. Our data suggest that depletion of the progenitor cell reserve, rather than decreased PC mobilization, underlies the association between PB PC numbers and cardiovascular risk.Lower numbers of progenitor cells (PCs) in peripheral blood (PB) have been associated with cardiovascular events in high-risk populations. Therapies aiming to increase the numbers of PCs in circulation have been developed, but clinical trials did not result in better outcomes. It is currently unknown what causes the reduction in PB PC numbers: whether it is primary depletion of the progenitor cell reserve, or a reduced mobilization of PCs from the bone marrow (BM). In this study, we examine if PB and BM PC numbers predict Amputation-Free Survival (AFS) in patients with Severe Limb Ischemia (SLI). We obtained PB and BM from 160 patients enrolled in a clinical trial investigating BM cell therapy for SLI. Samples were incubated with antibodies against CD34, KDR, CD133, CD184, CD14, CD105, CD140b, and CD31; PC populations were enumerated by flow cytometry. Higher PB CD34The online version of this article (10.1007/s10456-019-09666-0) contains supplementary material, which is available to authorized users. Patients with peripheral artery disease (PAD) show faster functional decline and higher rates of cardiovascular events than the general population . The mosProgenitor Cells (PCs) in the circulation may represent such an endogenous repair mechanism; circulating PCs were shown to contribute to vascular repair in animal models of ischemia , 5. PB P+ or CD133+ PCs reside in the bone marrow (BM) niche [Prior to mobilization into the circulation, CD34M) niche . The redM) niche , 20. In M) niche  and thatM) niche , 23. ThuIn parallel, therapies to increase the number of progenitor cells in circulation have been developed, aiming to augment vascular repair in acute or ischemic vascular disease.+-based therapy to be more effective than placebo. This further underscores the necessity of elucidating the link between PB and BM PCs and outcomes.While pre-clinical studies and early clinical trials showed promising results, later trials with more rigorous design did not show CD34In the present study, we examine the relationship between PB and BM PCs, and Amputation-Free Survival (AFS) in SLI patients. Furthermore, we attempt to separate potential BM reserve exhaustion from a mobilization defect in determining AFS risk. To this end, we use data obtained in the JUVENTAS trial, a randomized controlled trial investigating autologous BM cell therapy for the treatment of SLI , for whiThe study population of this prospective cohort study consisted of patients included in the JUVENTAS trial; a single-center double-blind randomized placebo-controlled trial investigating repetitive intra-arterial infusion of autologous BM mononuclear cells (BMMNCs) for the treatment of SLI. Trial results of the primary analysis have been published elsewhere ; study iThe study has been approved by the Medical Ethics Committee of the UMC Utrecht (no. 06/030) and was conducted in accordance with the declaration of Helsinki. All included patients provided written and verbal informed consent prior to inclusion.Prior to treatment allocation, approximately 100 ml of BM was harvested from the right iliac crest by an experienced hematologist under local anesthesia and conscious sedation. Peripheral blood (PB) samples were obtained by venipuncture of the antecubital vein. Flow cytometry on PB and BM was performed using lyse-and-wash protocols. 100 µl of PB or BM was incubated with the following antibody panels: 1: anti-CD34-FITC , anti-KDR-PE ; 2: anti-CD133-PE ; 3: anti-CD184-PE (BD Pharmingen) and anti-CD14-ECD , 4: anti CD-105-FITC (R&D) and anti-CD14-ECD; 5: anti-CD140b-PE (BD Pharmingen), for 45 min in the dark. Erythrocytes were lysed in an ammonium chloride buffer and remaining cells were washed with PBS and analyzed by flow cytometry . All samples were processed in duplicate. Spectral compensation was performed by using IgG isotype controls for the relevant fluorophores. Flow Cytometry Data Analysis Data were analyzed using FlowJo software version 10.0.8 ; all files were analyzed by a blinded assessor. See supplementary methods and Supplementary Fig. 1 for a description of the gating strategy. To account for variations in acquisition occurring due to inconsistency in erythrocyte lysis, all cell numbers are corrected for the number of granulocytes, as this population can be most reliably identified on FSC/SSC. Colony Forming Units Myeloid precursor  and erythroid precursors  forming capacity assays of the BMMNC were performed using Methocult H4534 and H4434 , respectively, in accordance with the manufacturer’s instructions.t test for normally distributed continuous, and a Mann–Whitney U test for non-normally distributed variables. Cell counts were non-normally distributed and were transformed by taking the natural logarithm (e) of the (cell number + 1). Correlations between cell types were quantified by spearman rank coefficient (ρ). To assess the relative contribution of mobilization, patients were divided into quadrants of either high and low numbers of BM and PB PCs, based on the median values of PC numbers. Survival analysis was performed using Cox proportional hazards regression models; throughout this paper Hazard Rates (HR) are given as exp(β), where β is the slope of the regression model for one e-fold increase in PCs. In cases where regressor distribution was not known, a restricted cubic spline was fit in order to obtain an unbiased fit. Covariates to Cox regression were added as described in the relevant tables. For multivariable models, automated backward exclusion of model factors based on an AIC criterion was performed in order to derive an optimal model. The proportional hazards assumption was evaluated by plotting Schoenfeld residuals. An a priori power analysis assuming a standardized β of 1.87 as in Fadini et al. [p Values < 0.05 were considered statistically significant. The Benjamini–Hochberg method was used to limit the False Discovery Rate resulting from multiple testing in parallel evaluation of cell types. All analyses were performed in the R computing environment, version 3.1.0. [Continuous variables are presented as means ± standard deviation (SD) or as medians with Interquartile Range (IQR). Differences between patients who reached an endpoint and who did not were assessed by chi-square test for categorical variables, student’s i et al.  yielded n 3.1.0. .+ cells in the administered graft did not correlate with any outcome parameter [One hundred and sixty patients were included in the JUVENTAS trial and were followed for a median of 3.0 years at the point of the present analysis, totaling 509 patient-years of follow-up. Table arameter .+ and CD133+ PCs in PB were associated with longer AFS (Both a Hazard Ratio (HR) of 0.56, p = 0.003 and p = 0.0007, respectively) per e-fold increase in number of PCs. Division into tertiles showed a HR of 2.02 of the lowest compared to the highest tertile for PB CD34+ PCs . We observed no association between CD34+/KDR+ cells and AFS . There was a trend towards an association between CXCR4+ cells and major outcomes , but this may be due to chance, considering the multiple hypotheses tested. The other cell populations assessed, CD14+ monocytes and CD140b (PDGFRb)+ cells, were not associated with AFS. CD105+ mesenchymal cells were not detectable in PB.The univariate association of PB and BM subpopulations with AFS is presented in Table + and CD133+ were associated with longer AFS . These results were confirmed by colony-forming assays for granulocytes/monocytes ; the colony-forming assay for burst forming erythroid units showed a trend towards association with AFS . Other BM subpopulations were not associated with AFS .r = 0.72 in PB and r = 0.80 in BM, Supplemental Fig. 2). Correlations of the numbers of cells displaying either marker between PB and BM were intermediate , with absolute numbers of PCs being approximately 20-fold higher in BM aspirates. CD34+/KDR+ double-positive cells correlated poorly with other PCs and there was no correlation between PB and BM.The numbers of PCs identified by the two markers CD34 and CD133 in PB and BM were highly correlated (+/KDR+ cells (21%) compared to other PC cell types (~ 10%), indicating an increased amount of random fluctuation in the assay.Coefficients of variance (CV) were also higher for CD34+ and CD133+  BM PC numbers were correlated to CFU-GM (r ≈ 0.44).Both CD34+ and CD133+ PCs, the “Exhausted” group displayed the worst prognosis . The “Poor Mobilizers” showed a lower risk for AFS than the “Compensators” (HR 1.6 vs. 1.9 for CD34+ PCs and HR 0.84 vs. 1.7 for CD133+ PCs).To attain insight in the relative contribution of BM exhaustion and a mobilization defect towards risk of amputation and death, we examined the variation around the identity line for PB versus BM PCs. Analogous to a study by Fadini et al , we divi+ PCs (p = 0.003) but a 2.25-fold higher number of BM CD34+  PCs (p = 0.00002). In 6/17 cases, the number of BM CD34+ PCs exceeded the range of observed values in SLI patients . Numbers of PB CD133+ PCs were 1.13-fold higher in healthy controls (p = 0.6), but BM CD133+ PCs numbers were 1.7-fold higher (p = 0.003).In a comparison of the JUVENTAS cohort to a small cohort of 17 healthy BM donors, we observed that healthy controls displayed a 1.88-fold higher number of PB CD34+ cells nor CD133+ was associated with AFS .In addition to the quadrant method, we examined whether a mobilization index, the ratio between PB/BM PCs, was associated with major events. The mobilization index of neither CD34+ cells in PB, which were nearly 9% lower. PC numbers in both blood and BM were negatively correlated with age, although the effect was greater in blood (r = − 0.24 and − 0.19 for CD34+ and CD133+ PCs compared to r = − 0.14). There was a significant association of PC numbers with Glomerular Filtration Rate (GFR), which was of similar magnitude (r ~ 0.2) in both blood and BM. Total cholesterol and triglyceride levels were both positively correlated with PB PC numbers. There was an inverse association between more advanced stages of SLI (Fontaine IV vs. IIb and III) and PC numbers.Associations between the number of PB and BM PCs and traditional cardiovascular risk factors are presented in Table +: HR = 0.71, p = 0.07, CD133+: HR = 0.64, p = 0.012). In BM, the adjusted HR was 0.49 (p = 0.03) for CD34+ PCs, and 0.65 (p = 0.16) for CD133+ PCs. Prior history of CVA was most strongly associated with amputation or death, followed by disease stage (presence of ischemic ulcers). In all models, both PB and BM PCs proved to be independent predictors of major outcomes. For further details regarding adjusted and reduced models, see Supplemental Table 2.Adjusted models, correcting for sex, age, GFR, history of CVA, history of MI or Angina, presence of ulcers, higher triglyceride levels, and cholesterol levels, show higher HRs for PB PC numbers than unadjusted models , respectively, in the course of disease.Very few studies have been able to investigate BM samples in patients with CVD, and this is the first longitudinal study that examines whether BM PCs predict future cardiovascular events. Prior cross-sectional studies have shown a reduction in CFU-GM and CD34t et al.  examinedt et al. , which mOne of the most interesting aspects of the present study is that both BM and PB PC numbers were quantified, which may provide insight in the underlying mechanism behind the reduction of PC numbers. It has classically been thought that lower numbers of PB PCs reflect a defect in mobilization from the BM, due to desensitization to or reduced availability of signaling molecules such as nitric oxide . Indeed,R ~ 0.4 for CD34+ cells), which is in agreement with previous studies . This iR ~ 0.34 , and sub+ cells and AFS, even though previous studies have shown that various monocyte subsets are associated with cardiovascular events [+ cells and AFS, which proved not robust enough for multiple testing and no trend in BM CXCR4+ cells. A recent report found that BM CXCR4+ cells are associated with functional improvements over time in patients with ischemic heart disease [Other cell populations were not associated with AFS in our study. Notably, we did not find an association between CD14r events , 34. Howr events . We obse disease .+, a marker for Mesenchymal Stromal Cells (MSCs) [+ cells in PB. The lack of association between CD105+ cell numbers in BM and AFS or disease severity is in agreement with a previous study with culture-expanded MSCs in this cohort [Lastly, we did not observe associations with AFS and numbers of BM cells positive for CD105s (MSCs) . MSCs cos (MSCs) ; congrues cohort , in whic+ cells indicate the general disease state which also predisposes to CVD. A plausible explanation may be that lower progenitor cell numbers reflect increased senescence on a cellular level and frailty on the level of the patient. It has been shown that CVD patients generally have shorter telomeres than healthy controls, which has been associated with lower CD34+ numbers [The question remains how the link between PC numbers and cardiovascular outcomes should be interpreted. Had the results shown that the number of (mobilized) cells in circulation determined risk of AFS, this would have supported the hypothesis of a causal role of circulating progenitor cells in vascular repair. The data show, however, that circulating cell numbers and mobilization are of minor importance (if not a nuisance variable) compared to PC numbers in BM. The most parsimonious interpretation is therefore that a lower number of BM and consequently PB CD34 numbers , 39. Alt numbers , 41.Lastly, the reduced PC numbers might be closely related to the outcome of vascular disease itself. In a previous study, we have shown that CLI patients have decreased BM vascularization and innervation, which might also affect the PC compartment . SimilarThe findings presented in this study may also have a bearing on the rationale of BM MNC therapy in cardiovascular disease, and SLI in particular. Autologous cell therapy using BMMNCs or BM PCs is increasingly proposed as a treatment for SLI patients , based oIn summary, we have demonstrated that lower numbers of both PB and BM PCs are associated with a worse prognosis in SLI patients. Moreover, BM PC numbers correlated with PB PCs and show a similar risk profile with regard to cardiovascular outcomes. Our findings imply that a depletion of the BM niche, rather than a defect in PC mobilization, underlies the association between PB PC numbers and cardiovascular risk.Below is the link to the electronic supplementary material.Supplementary material 1 (PDF 492 KB)


In this study, the association between high-risk human papillomavirus (hrHPV) infection and the vaginal microbiome in pregnant women was evaluated in Chinese cohorts.n = 38), pregnant women without HPV infection , nonpregnant women with hrHPV infection  and nonpregnant women without HPV infection , was characterized by deep sequencing of barcoded 16S rRNA gene fragments (V3–4) using Illumina MiSeq.The vaginal bacterial composition of four groups, 38 hrHPV-infected pregnant women  III, mainly composed of Lactobacillus iners. Both pregnancy and hrHPV infection were accompanied by an increased proportion of CST I (dominated by Lactobacillus crispatus), as opposed to CST III. Bifidobacterium, Bacillus, Megasphaera, Sneathia, Prevotella, Gardnerella, Fastidiosipila and Dialister were found to be biomarkers for hrHPV-infected women, though different genera  were associated with hrHPV-infected pregnant women.The results revealed that both pregnancy and HPV infection can increase vaginal bacterial microbial richness and diversity, with the bacterial composition being most influenced by pregnancy. This work uncovered a probable synergistic effect of hrHPV infection and pregnancy on the vaginal microbial composition. HPV infection in pregnant women was associated with a more complex and diverse microbial environment.The online version of this article (10.1186/s12879-019-4279-6) contains supplementary material, which is available to authorized users. Human papillomavirus (HPV), a type of DNA virus, is associated with cervical intraepithelial neoplasia (CIN) and cervical adenocarcinoma. Indeed, HPV infection is closely related with cervical cancer and it is also present in other anogenital, head and neck cancers. According to their oncogenic potential, more than 100 types of HPV were classified as high-risk, probable high-risk, and low-risk types –4.Lactobacillus lowers bacterial richness and diversity, indicating a healthy vaginal status. A healthy microbial biofilm may prevent or hinder many urogenital diseases, such as Candida infection [A large number of microorganisms inhabit the female genital tract, and hundreds of studies have revealed that a dominance of nfection , 6, sexunfection , urinarynfection , 9 and hnfection . Some stnfection –14 and Cnfection –17.Lactobacillus is especially present during pregnancy [Pregnancy is a unique physiological state, and the composition of the vaginal microbiota changes when women become pregnant due to fluctuations in hormone levels , 19. It regnancy –20. Howeregnancy , 21, 22,regnancy , though regnancy . Overallregnancy –28. HencTherefore, the aim of this study is to investigate the association between the vaginal microbial composition and high-risk HPV infection in pregnant women. We attempt to distinguish a different microbial profile of HPV-infected pregnant women from that of nonpregnant women.n = 38) and 48 pregnant women without HPV infection  and with an uncomplicated pregnancy were recruited for this study at their first antenatal care visit at the Department of Obstetrics, Renji Hospital of Shanghai, Jiao Tong University School of Medicine. The inclusion criteria for this cohort study were as follows: age ranging from 25 to 40 years; gestational age between 16 and 30 weeks; and no obvious medical problems or adverse outcomes during any previous pregnancy, such as preterm delivery, diabetes, autoimmune disease or malignant tumors. Participants who had participated in sexual activity or vaginal lavage within 72 h of sampling, reported cervical disease or genital HPV infection, reported vaginal bleeding in the preceding weeks, or used probiotics, antibiotics or corticoids in the preceding 2 weeks were excluded. Two other nonpregnant groups with the same age range and a normal medical history were established as control groups: nonpregnant women with hrHPV infection  and nonpregnant women without HPV infection .Between May 2016 and September 2016, 38 hrHPV (high-risk human papillomavirus)-infected pregnant women . HPV detection and genotyping were performed using a commercial HPV genotyping kit for 21 HPV types : 15 high-risk HPV types  and 6 low-risk HPV types . Pap smears of cervical exfoliated cells were evaluated by two experienced pathologists. Cytological cell samples were categorized according to Bethesda System criteria .Samples for vaginal microbial analysis were collected from the lateral and posterior fornix using a sterile swab under direct visualization during a speculum examination. The vaginal swab samples were immediately frozen and stored at − 80 °C until extraction.The swabs obtained were thawed on ice, and cells were suspended in transport buffer by vortexing and transferred to a sterile DNase/RNase-free 2.0 mL tube for enzymatic lysis. The lysate was purified using a QIAamp DNA Mini Kit (Qiagen®) according to the manufacturer’s recommendations. The total genomic DNA quality was assessed by 1% agarose gel electrophoresis, and the DNA concentration was measured using a Nanodrop ND-2000 (Nanodrop®).The V3–4 hypervariable regions of the 16S rRNA gene were amplified using primers 338F (ACTCCTACGGGAGGCAGCA) and 806R (GGACTACHVGGGTWTCTAAT). An 8-bp barcode sequence was added to the ends of both the forward and reverse primers. Amplification was performed in 50-μl reactions with TransStart Fast Pfu DNA Polymerase (TransGen Biotech®), 200 nM of each primer and 2 μl of template. The reactions were performed using a GeneAmp PCR System 9700 (Applied Biosystems®) under the following thermal profile: 94 °C for 2 min, followed by 30 cycles of 94 °C for 30 s, 57 °C for 30 s, and 72 °C for 30 s, and one cycle of 72 °C for 10 min and a 4 °C hold. Three PCR products per sample were pooled to reduce reaction-level PCR bias. PCR products were examined by 2% agarose gel electrophoresis and then purified using an AxyPrep DNA Gel Extraction Kit (AXYGEN®). Amplicons were quantified using the QuantiFluor-ST™ system (Promega®). All sequencing was performed using the Illumina MiSeq platform at Majorbio Biopharm Technology Company (Shanghai).http://www.arb-silva.de). Chimeric sequences and singletons were removed prior to taxonomic assignments.Low-quality sequences with an average quality score less than 20, a length shorter than 50 bp, or any mismatches to the primers or barcode containing chimeras were removed by Trimmomatic . Operatip-value < 0.05 was considered significant in all statistical analyses mentioned above.The Chao richness estimator and Shannon alpha-diversity index were calculated using mothur (version v.1.30.1) . CompariThe average ages of each group  were 30.13 ± were, 29.77 ± 29., 33.53 ± 364 and 34.90 ± 4.17 years, respectively. The main genotype of HPV in both pregnant and nonpregnant women was HPV-16 . After removing singletons (the OTUs contained less than 2 reads), 320 OTUs were identified, ranging from 10 OTUs in sample 4398 (NPN group) to 199 OTUs in sample 142_HH (PHR group) .At the OTU level, microbial richness and diversity were estimated using Chao and Shannon indices, respectively, as shown in Fig. R = − 0.0062, p = 0.545) , but no influence was found for HPV infection . There were no differences among the different groups with regard to the proportion of Actinobacteria . HPV infection also decreased the relative percentage of Proteobacteria, from 2.61% in the PN group to 0.98% in the NPHR group (p < 0.05), though HPV infection did not change the dynamics of Proteobacteria during pregnancy .Overall, 22 bacterial phyla were recovered across all samples   . It was surprising to find that the abundance of Bifidobacterium was increased in HPV-infected patients    than in the NPN group (0.10%)  also influenced the abundance of Streptococcus , as opposed to CST III. The abundances of various genera were differentially influenced by hrHPV infection and pregnancy. Overall, more anaerobic bacteria were associated with hrHPV infection and pregnancy.Our study addressed an undetermined topic about the association between the vaginal microbiota and hrHPV infection in pregnant women. We observed that both pregnancy and hrHPV infection were accompanied by increased vaginal bacterial richness and diversity. Lactobacillus spp. on the upper layer of the vaginal epithelium, and leading to an increased abundance of Lactobacillus spp. in the vagina, thus decreasing overall bacterial richness and diversity. In this study, we observed a reduced abundance of Lactobacillus during pregnancy, which might lead to the growth of other bacteria, increasing bacterial diversity and richness in pregnant women. A similar result was reported in another study of a Chinese cohort, whereby Huang et al. found higher vaginal bacterial diversity in pregnant women, especially in the first trimester [According to our results, pregnancy increased vaginal bacterial richness and diversity, though some previous studies have reported lower vaginal microbial diversity during pregnancy , 20, 37.rimester . A reasoLactobacillus [Lactobacillus, which may contribute to increased bacterial richness and diversity, it is clear that the underlying mechanisms responsible are different. Changes in physiological hormones and the immunosuppressive state that occurs during pregnancy might lead to a fragile balance of the vaginal microbiome, which should be further explored in future studies.HPV infection can increase vaginal bacterial richness and diversity and lower the percentage of bacillus , 12, andbacillus . Howeverbacillus , 40, evebacillus . As we dbacillus . Interesbacillus . HoweverL. iners and L. crispatus are the two most abundant Lactobacillus species found in pregnant women [L. iners-dominant VMB . Conversely, an L. crispatus-dominant VMB has been associated with a low-stress environment and an adequate level of autophagy by vaginal epithelial cells to remove harmful cytoplasmic components, as well as bacteria, in pregnant women [L. iners-dominant VMB [Regarding community state types, the most abundant CST among nonpregnant reproductive-age women (NPN) was CST III, which was in accordance with the results from an Asian population in the study by Ravel et al. . The mosnt women , 41–43. nt women , whereasnant VMB . It shounant VMB , 44.Bifidobacterium, Bacillus, Megasphaera, Sneathia, Prevotella, Gardnerella, Fastidiosipila and Dialister were identified as significant taxa in nonpregnant hrHPV-infected populations; in previous studies, anaerobic bacteria such as Bacillus, Megasphaera, Sneathia, Prevotella, Gardnerella and Dialister have been associated with HPV infection [Lactobacillus spp. is more susceptible to HPV infection. A surprising finding was that Bifidobacterium, a type of lactic acid-producing probiotic [Bifidobacterium might be able to guarantee a healthy vaginal balance by the production of lactic acid, in the lack of Lactobacillus. However, there are several cases reporting Bifidobacterium species as pathogens in various infectious conditions [Bifidobacterium predominated the VMB [Megasphaera and Bacillus) and lactic acid-producing bacteria (Bifidobacterium and Lactococcus) were identified in these samples. Moreover, we found novel vaginal bacterial taxa, i.e., Acidovorax and Oceanobacillus, which were also associated with HPV infection in pregnant women. Nevertheless, the roles of these microorganisms are not clear and should be investigated further. These findings support our hypothesis that hrHPV infection and pregnancy have a dual effect on increasing vaginal bacterial diversity, leading to a differentially altered vaginal microbiota in HPV-infected pregnant women compared to nonpregnant HPV-infected women.HPV infection and pregnancy equally influenced the vaginal microbial composition, but different specific genera were enriched in hrHPV-infected or pregnant women. nfection , 45, 46.robiotic , was enrrobiotic . It has nditions , 50, and the VMB . Hence, The strength of this study is that it addressed still-unresolved issues regarding the association between the VMB and HPV infection in pregnant women. We found high diversity and richness for the vaginal microbiome during pregnancy in a Chinese cohort and uncovered that pregnancy and HPV infection have a probable synergistic effect on altering the VMB, which caused a more complicated vaginal bacterial environment in pregnant women with hrHPV infection. The limitations of this study were that it was a small, cross-sectional study, and thus we could not determine any causation between the VMB and HPV infection or pregnancy. Further studies with longitudinal sampling are needed to assess correlations between the dynamics of the VMB microbiome and the transition of HPV at early, mild, and late gestational stages as well as postpartum and to investigate its relationship with different subtypes of HPV.This work uncovered a probable synergistic effect of hrHPV infection and pregnancy on the vaginal microbial composition. Despite not having measured hormone level in our patients, pregnancy status seems to be a bigger driver of the vaginal diversity in our cohort, as other studies demonstrated that HPV alone does not lead to changes in it , 40. HPVAdditional file 1:Table S1. HPV genotyping and distribution in pregnant women. (DOCX 18 kb)Additional file 2:Table S2. HPV genotyping and distribution in not pregnant women. (DOCX 17 kb)Additional file 3:Table S3. Characteristics of study population. (DOCX 20 kb)Additional file 4:Table S4. Sequences information. (DOCX 24 kb)Additional file 5:Figure S1. Heat map of relative abundance for the 22 most abundant bacterial phyla found in the vaginal bacterial communities of 4 groups. (PDF 173 kb)Additional file 6:Figure S2. Heat map of relative abundance for the 20 most abundant bacterial genus found in the vaginal bacterial communities of 4 groups. (PDF 142 kb)Additional file 7:Table S5. The comparison of the bacterial structure between two groups tested by ANOSIM test. (DOCX 34 kb)


Reverse transcription quantitative PCR (RT-qPCR) is widely used for gene expression analysis in various organisms. Its accuracy largely relies on the stability of reference genes, making reference gene selection a vital step in RT-qPCR experiments. However, previous studies in mollusks only focused on the reference genes widely used in vertebrates.Mizuhopecten yessoensis based on 60 transcriptomes covering early development, adult tissues and gonadal development. A total of 964, 1210 and 2097 candidate reference genes were identified, respectively, resulting in a core set of 568 genes. Functional enrichment analysis showed that these genes are significantly overrepresented in Gene Ontology (GO) terms or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to ribosomes, energy production, etc. Six genes  were selected from the candidate genes for RT-qPCR validation, together with 6 commonly used reference genes . Stability analyses using geNorm, NormFinder and the comparative delta-Ct method revealed that the new candidate reference genes are more stable than the traditionally used genes, and ACT and CYTC are not recommended under either of the three circumstances. There was a significant correlation between the Ct of RT-qPCR and the log2(TPM) of RNA-Seq data (Ct = − 0.94 log2(TPM) + 29.67, R2 = 0.73), making it easy to estimate the Ct values from transcriptome data prior to RT-qPCR experiments.In this study, we conducted the transcriptome-wide identification of reference genes in the bivalve mollusk Our study represents the first transcriptome-wide identification of reference genes for early development, adult tissues, and gonadal development in the Yesso scallop and will benefit gene expression studies in other bivalve mollusks.The online version of this article (10.1186/s12864-019-5661-x) contains supplementary material, which is available to authorized users. Reverse transcription quantitative PCR (RT-qPCR) is the most frequently used method in gene expression analysis due to its high sensitivity, specificity, reproducibility and broad dynamic range . To obtaDespite the awareness of the importance of reference genes, most previous studies directly applied commonly used reference genes for gene expression quantification without validation or conducted reference gene selection from a few traditionally used reference genes –6. HowevACT and CYTC  < 1; (III) no exceptional expression in any single tissue or developmental stage by requiring no log2(TPM) differed from the mean log2(TPM) by two or more; and (IV) medium to high expression level by requiring mean [log2(TPM)] > 5. The stability of the candidate reference genes was further evaluated according to the coefficient of variation (CV = stdev/mean). Here, all candidate reference genes have a mean [log2(TPM)] > 5 and a standard-deviation [log2(TPM)] < 1, so their CV values are always less than 0.2.The reference genes were detected using the method provided by Eisenberg and Levanon , with miTo better understand the function of the reference genes, GO and KEGG enrichment analyses were performed. The Swiss-Prot Blast results for all genes were imported into Blast2GO, and GO terms at level 3 were assigned to produce a broad overview of the groups of genes for biological processes, cellular component, and molecular function categories. The KEGG annotation was conducted by the KEGG automatic annotation server (KAAS). The significance of GO and KEGG enrichment was determined by using the algorithm implemented in GOstats with an FDR cutoff of 0.05 .18. Finally, the cDNA products were diluted 20-fold with nuclease-free water for RT-qPCR and kept at − 20 °C until further use.For all samples, total RNA was extracted using the conventional guanidinium isothiocyanate method, and potential DNA contamination was eliminated by DNase I  digestion. The obtained RNA samples were then assessed on 1.5% agarose gel electrophoresis and determined by using Nanovue Plus  to detect the RNA concentration and purity. cDNA synthesis was carried out using MMLV Reverse Transcriptase  and oligo(dT)Twelve genes, including 6 new candidate and 6 commonly used reference genes, were selected for RT-qPCR validation. Their primers were designed using Primer Premier 5.0 software. Two additional criteria need to be met, including PCR products between 80 and 120 bp in size and an annealing temperature of approximately 63 °C. The primer sequences are listed in Table RT-qPCR reactions were conducted in a 384-well plate using a Light Cycler 480 Real-time PCR System . Each reaction contained 2 μl 20-fold diluted cDNA, 10 μl Light Cycler 480 SYBR Green I Master and 4 μl 2 μM primers. The cycling conditions were 95 °C for 10 min, followed by 40 cycles of 95 °C for 15 s and 63 °C for 1 min. Each RT-qPCR analysis was performed in triplicate. For each gene, the melting curve and gel picture were analyzed to confirm that a single PCR product had been amplified.The expression stabilities of the twelve reference genes were assessed using three statistical approaches, geNorm , NormFin2(TPM) values for these genes are approximately 5 for all three datasets  value higher than 5, resulting in 964 (3.65%), 1210 (4.58%) and 2097 (7.94%) candidate reference genes for early development, adult tissues, and gonadal development, respectively  values ranging from 5.48 to 10.72 and CV values between 0.016 and 0.027. Six genes were annotated, of which four  encode proteins related to energy production. In contrast, the 10 most stable genes in adult tissues possess higher expression levels, with log2(TPM) values ranging from 11.15 to 12.08. All of these genes were annotated as ribosomal proteins. The ten most stable genes in gonadal development showed a wide range of expression, with log2(TPM) values ranging from 5.76 to 13.74. All of these genes were annotated, of which 5  function in protein synthesis.A total of 60 RNA-Seq datasets from scallop embryos/larvae and adult tissues were used to select candidate reference genes for early development, adult tissues and gonadal development. As shown in Fig. To obtain a core set of reference genes, we compared the three candidate reference gene sets. As shown in Fig. RS23, EF1A, NDUS4, and SELR1. The other two genes, EIF3F, and OLA1, were selected from the less stable candidates. The 6 commonly used reference genes include ACT, CYTC, HEL, EF1B, GAPDH and RPL16  values of the twelve genes in the three RNA-Seq datasets are shown in Fig. ACT, CYTC, GAPDH and RPL16, are highly unstable during early development. In adult tissues, the expression of ACT is most variable, and during gonadal development, CYTC is most unstable. EF1B is relatively stable compared to the other commonly used reference genes in all three datasets, and the only gene that falls within the core set candidate reference gene list.The logACT, CYTC and GAPDH, are relatively unstable during early development. Two genes, ACT and CYTC, are unstable in adult tissues. These two genes are also unstable during gonadal development, with ACT exhibiting higher expression variation than CYTC. Although stability rankings are different among methods for the highly and medium stable genes, the candidate reference genes tend to have higher comprehensive ranking values than those of the commonly used reference genes. Among the twelve genes, the most stable gene for early development is RS23, and EIF3F is the most stable in adult tissues and during gonadal development.To validate the results, RT-qPCR was conducted, and the expression stability of the twelve genes was evaluated using three methods . As shown in Fig. ACT and CYTC. As shown in Fig. 2(TPM) values mainly range from 4 to 14, and the Ct values of RT-qPCR fall between 14 and 29. There is a significantly negative correlation between the two values , with the formula Ct = − 0.94 log2(TPM) + 29.67.To facilitate an estimation of the Ct of RT-qPCR based on RNA-Seq data, we further evaluated the relationship of the gene expression levels between RNA-Seq and RT-qPCR data using the 10 reference genes, excluding In this study, an improved method for the systematic identification of reference genes is proposed. Compared with the study by Eisenberg and Levanon , there aRS23), most of these genes are involved in protein synthesis. In contrast, 4 of the top 10 most stable genes for early development are unannotated. This result is not expected because housekeeping genes are supposed to play important roles in the maintenance of basal cellular functions, and most of these genes are well studied. We assume these unannotated genes in the top stable gene list could be novel genes that are critically important for the early development of scallops, bivalves or mollusks but not for other animals. Among the six annotated genes, four are related to energy production. This result is different from the function of the top reference genes for adult tissues and gonadal development, suggesting that embryos/larvae and adults may emphasize different biological processes or pathways. Consistent with the function of the top stable genes, the 568 core set reference genes are enriched in GO terms and KEGG pathways related to ribosomes, energy production, etc. Similar results are also reported for housekeeping or reference genes identified by genome-wide analysis in other organisms, such as humans , th, th64], In this study, by taking advantage of 60 transcriptomes of the Yesso scallop, we identified candidate reference genes for early development, adult tissues, and gonadal development and found a core set of 568 reference genes. We also conducted stability comparisons of 6 candidate and 6 commonly used reference genes based on RNA-Seq data and RT-qPCR validation and found several traditionally used reference genes that were inappropriate as internal controls. Our study will benefit gene expression studies in bivalve mollusks.Additional file 1:Table S1. Detailed information on the RNA-Seq datasets (XLSM 9 kb)Additional file 2:Table S2. Detailed information on the expression variability and annotation of the candidate reference genes in early development, adult tissues and gonadal development of the Yesso scallop (XLSM 330 kb)Additional file 3:Figure S1. The expression levels of CYTC and GAPDH during the early development of the Yesso scallop (PDF 33 kb)


Cardiovascular disease (CVD) is the primary cause of death worldwide, accounting for 31.0% of all deaths and more than 18 million deaths annually. The 2008 World Health Report indicated that 144 (35%) of the 413 deaths per 100,000 in 2002 in the Kingdom of Saudi Arabia (KSA) were due to CVD. Primary prevention is an important focus of most of the cardiovascular prevention guidelines around the world. In this study, we aimed to describe the prevalence of extrinsic risk factors for CVDs in a high-risk population attending general practice in Jeddah, KSA.We conducted a cross-sectional survey at King Abdulaziz University Hospital in Jeddah. Patients started on lipid-lowering and/or antihypertensive and/or antidiabetes treatments without a history of established cardiovascular disease were interviewed. The questionnaire was adopted from the EUROASPIRE III study.p = 0.007), unhealthy diet (p = 0.034), being overweight (p = 0.018), and high blood cholesterol (p = 0.002). We observed significantly greater prevalence of hypertension (p = 0.073), unhealthy diet (p = 0.015), being overweight (p = 0.018), and high blood cholesterol (p = 0.000) in those patients with dyslipidemia.Two hundred and fifty high-risk individuals  were interviewed. Overall, 72% of the patients had been diagnosed with hypertension, 61.2% of patients had dyslipidemia, and approximately two-thirds of patients had diabetes mellitus. Most of the patients (88%) were non-smokers. The mean waist circumference of patients was 101.6 ± 14.1 cm, which suggests most were clinically obese. About 54.8% of the patients followed an unhealthy diet and 52.0% were physically inactive. There were significant differences between women and men in relation to dyslipidemia (Our study presents novel findings in the KSA. Women were more likely to have high-risk CVD risk factors compared with their male counterparts in this sample. Gender-specific prevention programs in the KSA should be considered to more appropriately target at-risk individuals, to reduce preventable morbidity and mortality associated with CVDs. Cardiovascular diseases (CVDs) include coronary heart disease (CHD), cerebrovascular disease, peripheral arterial disease, rheumatic heart disease, congenital heart disease, deep vein thrombosis, and pulmonary embolism , 2. CVD According to the latest World Health Organization (WHO) statistics, chronic, noncommunicable diseases account for the majority of fatalities in the Kingdom of Saudi Arabia (KSA) , 11. TheStudies have shown that primary prevention for people without established CVD is as important as secondary prevention , 17. IndThis study was approved by Biomedical Ethics Committee of King Abdulaziz University (Reference No. 322–17). Written consent was obtained from all participants before the interview.We conducted a cross-sectional survey at King Abdulaziz University Hospital (KAUH) in Jeddah, the second largest city in Saudi Arabia after the capital city, Riyadh. We selected a random sample of 250 patients attending the General Practice at KAUH. The inclusion criteria were: male and female patients aged > 40 years and currently on antihypertensive and/or lipid-lowering and/or anti-diabetes drug treatment regimens. The exclusion criteria were: patients with established cardiovascular disease .Data were collected using both anonymous interview-administered questionnaires and physical measurements. The questionnaire was adopted from the EUROASPIRE III study  and modip-value < 0.05 was regarded as statistically significant.The statistical analysis in this research was performed using SPSS, version 21.0 . Descriptive statistics such as frequency, percentage, mean, and standard deviation were used to describe the data. A Mann-Whitney test was performed to analyze non-parametric differences in the risk factors for CVD among men and women. A The demographic characteristics of the 250 patients are shown in Table As shown in Tables Most of the patients  had been informed by a healthcare professional that they had high blood pressure and 181 were taking drugs specifically prescribed to lower their blood pressure. Ninety (43.1%) patients were following a special diet prescribed by a healthcare professional to lower their blood pressure level. One hundred and seventy-nine (71.6%) of the patients had been informed by a healthcare professional that they had high blood cholesterol and 111 (52.4%) were following a special diet prescribed by a healthcare professional to lower their blood cholesterol level. One hundred and seventy-two (69.9%) of the patients had been informed by a healthcare professional that they had diabetes mellitus. The treatment methods for diabetes varied among patients, with oral anti-diabetic drugs (83.3%) being the most commonly used treatment regimen.Table Family history of CVD was investigated and is reported in Table p = 0.007), unhealthy diet (p = 0.034), being overweight (p = 0.018), and high blood cholesterol (p = 0.002); women were more likely to have the aforementioned CVD risk factors compared with their male counterparts in this sample.The differences in CVD risk factors between men and women are shown in Table p = 0.073), unhealthy diet (p = 0.015), being overweight (p = 0.018), and high blood cholesterol (p = 0.000) in those patients with dyslipidemia. Furthermore, we also determined that those patients without diabetes were significantly more likely to have been diagnosed with hypertension (p = 0.001) compared with diabetic patients.We explored whether there were differences in CVD risk factors among patients with hypertension, dyslipidemia, and diabetes Table . We obseCVD is the primary cause of death worldwide . In deveInitial prevention, early detection, and robust health-promotion strategies have all been successful in lowering the global burden of CVD , 28. The2], or abdominal obesity) [A high prevalence of dyslipidemia (61.2%) and hypertension (72%) was notable in this sample. In contrast, the prevalence of dyslipidemia (71.1%) was found to be higher than that of hypertension (43.9%) in a Nigerian study ; the levobesity) . The maiobesity) . Similarobesity) . The majobesity) . HoweverIn the present study, the mean waist circumference of the sample was 101.6 ± 14.1 cm. This is a significant cause for concern, since such large individuals are at very high risk of developing CVD, especially when they have several other risk factors present. The prevalence of obesity, as defined by waist circumference, was also high (68%) in the study by Alsheikh-Ali et al. . Such fip = 0.007), unhealthy diet (p = 0.034), being overweight (p = 0.018), and high blood cholesterol (p = 0.007) compared with men in the sample. The majority of these women did relatively little exercise or were unable to do so. Gender-specific prevention programs in the KSA should be considered to more appropriately target at-risk individuals, in order to reduce preventable morbidity and mortality associated with CVDs. Interventions to reduce patient risk in our sample could include changes in drug treatment (including drug(s) used and dosages), education about lifestyle factors, improved diet, and exercise.Several studies have reported gender differences in acute coronary syndrome (ACS) with respect to its presentation, diagnosis, clinical management and outcomes. The results of some studies have found that women have higher mortality rates than men; however, gender was not found to be a factor related to the presentation or mortality of patients with ACS in other studies , 34. SevOur study does have several limitations. This was a relatively small, single-center cross-sectional study, which may be susceptible to recall bias. Furthermore, the inclusion criteria may not be broadly representative of those at risk of developing CHD. Finally, we did not collect data on socioeconomic status, which would potentially focus prevention efforts in areas where they are most needed.Our study presents novel findings in comparison to previous studies within the KSA. Women were more likely to have CVD risk factors including dyslipidemia, unhealthy diet, being overweight, and high blood cholesterol compared with their male counterparts in this sample. Gender-specific prevention programs in the KSA should be considered to more appropriately target at-risk individuals, in order to reduce preventable morbidity and mortality associated with CVDs.Additional file 1. Description: Questionnaire.


PPAR) gene Pro12Ala polymorphisms and risk of hypertension. However, the number of available studies was extremely limited. We updated this evidence and gave more significant results. We performed comprehensive computer-based searches in the PubMed, Web of Science, Embase, Google Scholar, the Cochrane library, Wanfang database, China National Knowledge Infrastructure, and China Biological Medicine Database. All studies that reported the association between the PPARγ2Pro12Ala polymorphisms and hypertension were identified. Twenty-one studies were finally included in the present study. In the domain model, the PPARγ1Pro12Ala polymorphism was not associated with hypertension (odds ratio (OR) = 0.85, 95% confidence interval (CI): 0.71–1.03, P=0.108). The significant relationship was found in the recessive model , in the additive model , and in the allele genetic model . Subgroup analysis indicated that the PPARγ1Pro12Ala polymorphism from the all gene models was also not related to the risk of hypertension in Caucasians. In Asians, however, the results  suggested a significant relationship between PPARγ1Pro12Ala and hypertension in the domain model , in the recessive model , in the additive model , and in the allele model . The PPARγ1Pro12Ala polymorphism could affect the risk of primary hypertension amongst Asians. The A allele gene was a protective genotype for primary hypertension. The PPARγ1Pro12Ala polymorphism was not associated with hypertension amongst Caucasians.Previous studies investigate the relationship between peroxisome proliferator-activated receptor γ-2 ( Cardiovascular disease is the leading cause of death for adults in developed or developing countries, including China . HypertePeroxisome proliferator-activated receptor-γ (PPARγ) belongs to member of the steroid hormone receptor superfamily. Human PPARγ gene is located in the chromosome of 3p25 with 479 amino acid resides . Recent This meta-analysis was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Cochrane Handbook for Systematic Reviews.We performed comprehensive computer-based searches in the PubMed, Web of Science, Embase, Google Scholar, the Cochrane Library, Wanfang database, China National Knowledge Infrastructure, and China Biological Medicine Database from the inception to 28 December 2018. All studies that reported the association between the PPARγ2Pro12Ala polymorphisms and hypertension were identified. The following keywords were used for searching: peroxisome proliferator-activated receptor-γ, PPAR-γ, Pro12Ala, genotype, polymorphism, mutation, single nucleotide polymorphism  variant, hypertension. The search language was restricted to Chinese and English. We also reviewed the references lists of reviews and relevant studies for the potential studies as possible as we can.The included studies have to meet the following criteria: (i) study is from a case–control or cohort study design about relationship between PPAR-γ2Pro12Ala polymorphism and the risk of hypertension; (ii) the diagnostic of hypertension is clear: systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg without antihypertension medications or antihypertension medications were used ; (iii) sTwo authors [M.Z. and Q.W.] independently extracted the data. Disagreement was resolved by consensus. If these two authors could not reach a consensus, the result was reviewed by a third author [L.F.]. The extracted data consisted of the follow items: the first author’s name, publication year, country, methods of genotype, sample size of cases and controls, the gene frequency  of case group and control group, Hardy–Weinberg equilibrium (HWE) test results, and scores of quality assessment.To determine the methodological quality of each study, we used the Newcastle–Ottawa Scale, which uses a ‘star’ rating system to judge the quality of observational studies . The NOSP<0.1) and the 2I test (greater than 50% as an evidence of significant inconsistency). Pooled effect sizes were determined using a fixed-effects model (the Mantel–Haenszel method) when heterogeneity was negligible (2I < 50%) or a random-effects model (the DerSimonian and Kacker method) when significant heterogeneity was present (2I ≥ 50%) [2 test in the controls. Subgroup analysis was also performed amongst different populations (Caucasian vs. Asian). We performed the sensitivity analysis by omitting one study each time. To study the relevance of such publication bias, funnel plots were constructed by plotting the trial results against their precision. Begg’s and Egger’s tests were also used to assess the publication bias [P-value less than 0.05 was considered statistically significant throughout the analyses.We assessed the association between PPAR gene Pro12Ala polymorphisms and risk of hypertension using the following gene model: dominant (AA/PA vs. PP), recessive (AA vs. PA/PP), additive (AA vs. PP), and allele gene model (A vs. P). The odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to assess the relationship between gene models and risk of hypertension. Heterogeneity was assessed using the Chi-square test (significance level of 2 ≥ 50%) . HWE wasion bias . A P-valThis meta-analysis belonged to secondary analysis based on the studies published previously, the patients’ informed consent; and the ethical approval was not necessary.The flow of study selection was presented in The general characteristics of the studies included in the meta-analysis are shown in The score of each domain was presented in the Supplementary Material S1. The mean score of included studies was 7.04. The overall quality of studies was high. The main issues were that some studies selected a control population from a hospitalized one. Either cases and controls were not matched in the design and/or confounders were not adjusted for in the analysis. Besides, some studies did not report the non-response rate.P=0.000; 2I = 64.8%). We used the random-effect model to pool the data, which suggested that the PPARγ1Pro12Ala polymorphism was not associated with hypertension . To explore the population differences, we performed the subgroup analyses amongst different populations . We found that the PPARγ1Pro12Ala polymorphism was also not related to the risk of hypertension. In Asians, however, the results from random-effect model  indicated significant relationship between PPAR-γ1Pro12Ala and hypertension .To quantitatively assess the association between PPAR-γ1Pro12Ala and hypertension, we first pooled 21 studies in the domain model (AA/AP vs. PP). The results indicated there was significant heterogeneity .The sensitivity analysis result is presented in In the present study, our results based on larger sample sizes and more study number indicated that (i) PPAR-γ1Pro12Ala gene polymorphism was associated with the risk of hypertension. The AA genotype and A allele could decrease the risk of hypertension in the overall population compared with PP genotype and P allele, respectively. (ii) The population difference was source of heterogeneity within studies. Furthermore, (iii) the subgroup analysis suggested that the PPARγ1Pro12Ala gene polymorphism affects the risk of hypertension amongst Asians. However, no significant relationships were found amongst Caucasians. Our results provided more strong evidence support for the confirmation of relationship between PPARγ1Pro12Ala polymorphism and the risk of primary hypertension. Previous studies also assessed the relationship between common polymorphism (rs1801282) in the PPAR-γ2 gene and hypertension susceptibility ,33. HoweIn vitro, high-salt diet can make the SHR blood pressure significantly increased (185 + 6) mmHg vs. (128 ± 5) mmHg, and this process can be blocked by Rosiglitazone block (126 + 4 mmHg). Ang II synthetic process and glomerular mesangial cell proliferation was also inhibited, which indicated that the role in antihypertensive and protecting renal was associated with Ang II. Diep et al. [Our results found that the A allele appears to have a protective effect against hypertension. This result is similar to previous several studies. Lu et al.  found thp et al.  found thp et al. . During p et al. . The dirThe present study has several strengths. Compared with previous studies, our study consisted of a larger sample size (5503 cases and 7862 controls), which improved the statistical power and provided more accurate results. We also conducted subgroup analysis that were not reported in previous study. Besides, the present study followed the PRISMA and Cochrane Handbook for Systematic Reviews. Several study limitations should be addressed. First, the present pooled results were from unadjusted data, and some potential confounding factors may affect the results. We confirm that the population difference was one of the potential confounding factors. Second, we can see publication bias may exist though the Egger’s and Begg’s tests gave no significant results. Maybe it was related to search language because we only performed search in English and Chinese. Third, the study number and sample size in Caucasians was very limited. Studies with larger sample sizes are needed. Finally, future study should take the gene–environment effects into consideration.In conclusion, the PPAR-γ2 Pro12Ala polymorphism could affect the risk of primary hypertension amongst Asians. The A allele gene was a protective genotype in primary hypertension. The PPAR-γ1Pro12Ala polymorphism was not associated with hypertension amongst Caucasians. Study with more sample size is needed, especially for Caucasians. The future research should pay attention on the molecular mechanisms behind this.


Lathyrus cicera transcriptome was analysed in response to rust (Uromyces pisi) infection to develop novel molecular breeding tools with potential for genetic mapping of resistance in this robust orphan legume species. One RNA-seq library each was generated from control and rust-inoculated leaves from two L. cicera genotypes with contrasting quantitative resistance, de novo assembled into contigs and sequence polymorphisms were identified. In toto, 19,224 SNPs differentiate the susceptible from the partially resistant genotype’s transcriptome. In addition, we developed and tested 341 expressed E-SSR markers from the contigs, of which 60.7% varied between the two L. cicera genotypes. A first L. cicera linkage map was created using part of the developed markers in a RIL population from the cross of the two genotypes. This map contains 307 markers, covered 724.2 cM and is organised in 7 major and 2 minor linkage groups, with an average mapping interval of 2.4 cM. The genic markers also enabled us to compare their position in L. cicera map with the physical position of the same markers mapped on Medicago truncatula genome, highlighting a high macrosyntenic conservation between both species. This study provides a large new set of genic polymorphic molecular markers with potential for mapping rust resistances. It represents the first step towards genomics-assisted precision breeding in L. cicera.The  Lathyrus cicera, or ‘chickling pea’, a plant most commonly cultivated for animal feed, identified DNA polymorphisms that may be associated to resistance to the fungal disease known as rust. Researchers in Europe led by Maria Carlota Vaz Patto at the NOVA University of Lisbon, Portugal, discovered thousands of genetic differences between plants that were either susceptible to or at least partially resistant to the rust fungus Uromyces pisi. They created a ‘genetic linkage map’, which reveals the likelihood that different genetic characteristics will be inherited together through the generations. This map can now serve as a tool to help geneticists and plant breeders understand and promote resistance to rust and potentially other fungal diseases in L cicera. The results may also be applied to other legumes, including peas and beans more commonly cultivated for human consumption.Genetic analysis of  Lathyrus cicera L., the chickling pea, is an annual legume belonging to the tribe Fabeae2. It is mainly grown as feedstock, both as fodder and grain3. However, as far as human consumption is concerned, L. cicera is eaten uncooked as green snack4. L. cicera adapts well to harsh environments. It is resistant to drought, waterlogging5 and to several important legume pathogens. Sources for resistance to rust6, powdery mildew7, bacterial blight8 and crenate broomrape9 have been identified. Thus, L. cicera is a good option for cropping systems in marginal lands and can function also as a source of resistance genes for transfer to related species such as pea10.L. cicera will be crucial to identify and locate the genes and genomic regions responsible for the resistance traits, paving the way to marker assisted selection (MAS) in this orphan species. Indeed, limited genomic resources exist for this plant species, hampering its potential exploitation in legume breeding. In January 2018, the NCBI database contained only 126 sequences (considering DNA and RNA data) with almost no relevance for breeding. However, molecular tools from related species were useful in this legume. Actually, 138 molecular markers of different types previously developed for other legume species, were successfully cross-amplified in L. cicera11.A linkage map of Uromyces cause important legume diseases. Uromyces pisi (Pers.) Wint. causes pea rust12 and is also capable of infecting other species in the genera Lathyrus13, Vicia and Lens15.Rust fungi and particularly those from the genus Lathyrus sativus is the species most closely related to L. cicera and may even be derived from it16. These two species might, therefore, share many physiological/genetic stress-response mechanisms. We have recently characterised in more detail the response of L. sativus transcriptome to inoculation with U. pisi17. Differences in the reaction to infection between the resistant and susceptible genotypes investigated appeared to be mainly due to the activation of the salicylic acid (SA) pathway and expression of several pathogenesis-related (PR) genes. Indeed, in previous studies both species, L. sativus and L. cicera, showed a compatible reaction to U. pisi. Also, similar defence mechanisms were present, although L. sativus genotypes were more resistant than the L. cicera genotypes investigated13.L. cicera genotypes, with contrasting quantitative resistance to rust, to achieve several aims, such as the following: (i) to develop novel expressed simple sequence repeat (E-SSR) and single-nucleotide polymorphism (SNP)-based molecular markers for future mapping and diversity studies in L. cicera, (ii) to examine the differential expression of allelic variants in the two contrasting genotypes after rust inoculation and, based on the SNP information within candidate alleles, (iii) to develop appropriate assays for future quantitative trait loci (QTL)/expression QTL analysis for rust resistance in L. cicera. Finally, we used the developed L. cicera molecular markers to construct the first L. cicera linkage map and perform a comparative/synteny study of L. cicera with other legume species. This map was developed using a recombinant inbred line (RIL) population resulting from the cross of the two contrasting L. cicera genotypes previously analysed.In the present work, we investigate the transcriptomes of control and rust-inoculated leaves from two The RNA-seq library of the susceptible genotype BGE008277 comprised 18,395,860 sequencing reads, which were assembled into 66,210 contigs, ranging in size from 150 to 8664 bp, with a mean contig length of 537 bp. The respective library from the partially resistant genotype BGE023542 comprised 30,320,831 reads, which assembled into 64,382 contigs, with a size range of 150 to 9694 bp and a mean contig length of 571 bp.de novo reference assembly combining the RNA-seq reads from both genotypes and from all treatments comprised 145,985 contigs, ranging in size from 150 to 13,916 bp, with a mean contig length of 485 bp. BUSCO analysis indicated that our assembly is 86% complete, showing only 4.9% of fragmented BUSCOs. In more detail, a total of 1440 BUSCO groups were found: 1238 complete BUSCOs (86%), from which 1206 single-copy BUSCOs (83.8%) and 32 duplicated BUSCOs (2.2%); fragmented BUSCOs: 70 (4.9%) and missing BUSCOs: 132 (9.1%). The mapping and quantification of both genotypes’ libraries to the reference assembly allowed the analysis of their differential expression in response to U. pisi infection. A total of 20,362 contigs were unique to the partially resistant and 12,114 contigs were unique to the susceptible genotype. This de novo Transcriptome Shotgun Assembly project has been deposited at DDBJ/EMBL/GenBank under the accession PRJNA264792.The L. cicera contigs from the susceptible and partially resistant genotype, respectively that were differentially expressed in response to rust inoculation were grouped into eight expression pattern groups (A-H) based on their up- or down-regulation , considering only the transcripts present in all libraries. The number of differentially expressed contigs and description of each group is summarised in Table U. pisi sequences.From the 111,287 contigs detected in all libraries, 46,588 (41.9%) were matched via BLAST to entries in plant databases. A total of 622 (0.6%) contigs matched only to fungal databases and were present only in the inoculated libraries. In addition to these, 688 (0.6%) other contigs, that were also absent in non-inoculated samples, had a higher hit-score in fungal databases than in plant databases. Thus, a total of 1.2 % of all contigs most probably correspond to Medicago truncatula , Cicer arietinum , Glycine max , Pisum sativum , Phaseolus vulgaris  and Lotus japonicus  were the best matching legume species. Vitis vinifera , Hordeum vulgare , Zea mays  and the model Arabidopsis thaliana  were the best matching non-legume species.As indicated in Fig. As depicted in Fig. 18. Although a detailed description of these differentially expressed transcripts is not under the main scope of this study that focus on the identification of potential molecular markers useful for mapping, we emphasise those upregulated in response to rust infection only in the partially resistant genotype. This group included transcripts involved in hormone metabolism, cell wall degradation, secondary metabolism, ROS production and in signalling and regulation of transcription of defence responses. Particularly important for signalling, this group harboured ten receptor kinases, one calcium receptor and a ‘WRKY family transcription factor’. Also related to signalling, but in the group of transcripts upregulated in the susceptible and downregulated in the partially resistant genotype, a MLO-like transcript  was identified. The complete set of transcripts and its expression profiles can be found in Supplementary Table The analysis of the identified functional categories revealed transcripts that are potentially involved in several layers of defence against pathogens2 −1.8 to + 2.4 in the two genotypes. Primer sequences are listed in Supplementary Table R = 0.71 for the resistant and R = 0.70 for the susceptible genotype) was observed between the log2 fold changes measured by RNA-seq and qRT-PCR.To validate the RNA-seq results, the expression of 8 selected genes  was analysed by qRT-PCR using three biological replicates. Genes were selected according to their level of differential expression which ranged from logA total of 19,224 Single-Nucleotide Polymorphisms (SNPs) were detected in 5,152 of the 43,590 transcripts present in both the susceptible and the partially resistant inoculated genotypes . In five cases only one of the two alleles could be unambiguously amplified . For four SNP sites, neither allele could be amplified in both genotypes   amplicons were polymorphic between genotypes BGE008277 and BGE023542, and 44 (12.9%) were monomorphic. Thirty-one (9.1%) primer pairs produced a complex pattern and the remaining 59 (17.3%) primer pairs failed to produce any fragment. E-SSR primer pairs and genotyping results are listed in Supplementary Table E-SSRs with a perfect repeat unit of two to six reiterated nucleotides were identified through the Phobos software11, were screened in the parental genotypes of the F5 RIL population for mapping purposes. From these, 307 polymorphic loci were successfully mapped, namely, 189 SNPs, 113 E-SSRs and 5 ITAPs. In more detail, from the initial 163 E-SSRs screened in the RILs, 126 were selected for mapping, 125 segregated with the expected 1:1 Mendelian ratio  and one displayed slight segregation distortion (χ2 = 4.0). The remaining markers presented a high segregation distortion and were excluded from further analysis. From the 767 SNPs genotyped in the RIL population, 434 were withdrawn from the mapping due to several causes: 270 had more than 20% missing values, 162 were monomorphic and 2 were heterozygous in the parental genotypes. A total of 333 SNPs was then selected for developing the linkage map. Of these, 71 segregated severely distorted (p ≤ 0.005) and were also removed. From the remaining 262 markers, 66 were removed for having identical segregation to other markers, thus redundant for the map construction. Additionally, one RIL was removed because it had >25% of missing data. Finally, the first L. cicera linkage map was developed using data from 102 RILs screened with 327 polymorphic loci . It covered 724.2 cM of genetic distance organised in 7 major and 2 minor linkages groups (LG), with an average distance of 2.4 cM between markers. Only 5 markers could not be linked to any other LG. Eleven percent of the markers showed significant deviation from the expected 1:1 segregation ratio (segregation distortion), highlighted with asterisks in Fig. 20. In the present linkage map, these were observed in the extremity of LGs V and IX and in the centre of LG I. The smallest LG (IX) mainly contained markers with segregation distortion  markers from a previous studyInspection of χ2 values for goodness-of-fit for the individual LGs gave insight into the reliability of the obtained map. The χ2 values for all the LGs were < 1, except for LG VIII (χ2 = 1.15)  found in an Iberian germplasm collection6, is slightly more susceptible than the most susceptible L. sativus genotype (DS = 30%) in the same Iberian Lathyrus germplasm13. Future comparative studies should reveal if the same defence-related genes or QTLs are involved in L. cicera and L. sativus resistance to rust, and confirm if the similarities now detected on the phenotypic resistance components would stand at molecular level. As an example, in L. cicera a MLO-like transcript  was upregulated in the susceptible and downregulated in the partially resistant genotype  and translocations (LG II and IV). In a comparison between M. sativa and P. sativum syntenic groups35, one re-arrangement was similar to the one we observed in L. cicera: linkage group (LG II) from L. cicera was split in two chromosomes in M. truncatula (Chr. 2 and 6). Also, P. sativum’s LG IV contained M. sativa’s LG 2 and LG 6[35]. We therefore hypothesise that the reduction of the number of chromosomes in M. truncatula/M. sativa (n = 8) compared to L. cicera/P. sativum (n = 7) is caused by the fusion of M. truncatula chromosomes 2 and 636. Moreover, a translocation involving chromosomes 4 and 8 of M. truncatula that were represented by LG IV in L. japonicus was reported37.Extensive co-linearity was detected between the L. cicera in particular and in legume genomics in general. For the first time in L. cicera genic SSRs and SNPs were detected and validated for their use as genetic markers. Moreover, the first linkage map for L. cicera created with their help can now be used as a tool to localise genes governing desirable traits such as resistance to rust that segregates in the RIL population used to develop the map.In conclusion, our study provides a number of significant genetic resources for L. cicera genotypes, BGE008277 and BGE023542, have contrasting quantitative resistance to rust infection. Previous evaluation of resistance levels against U. pisi demonstrated that BGE008277 is susceptible to rust [disease severity (DS) = 80%], whereas BGE023542 is partially resistant (DS = 36%)6. These genotypes were kindly provided by the Plant Genetic Resources Centre (CRF-INIA), Madrid, Spain. The mapping population used for the development of the linkage map consisted of 103 F5 Recombinant Inbred Lines (RILs) derived by single seed descendent from a cross between the two previously described L. cicera genotypes, BGE008277 and BGE023542.The two studied U. pisi monosporic isolate UpCo-01 from the fungal collection of the Institute for Sustainable Agriculture-CSIC  was used for inoculation. Fungal spores kept at −80 °C were multiplied on plants of the susceptible P. sativum cv. Messire before use.The L. cicera seedlings were inoculated by dusting all plants at the same time with 2 mg of spores per plant, diluted in pure talk (1:10), with the help of a small manual dusting device, in a completely randomised experiment. Inoculated and control plants were then incubated for 24 h at 20 °C in complete darkness and 100% relative humidity, then transferred to a growth chamber and kept at 20 ± 2 °C under 14 h light (150 μmol m−2 s−1) and 10 h dark. Plant response to infection was visually assessed 15 days after inoculation.Twenty-four plants each per genotype (BGE008277/BGE023542) and treatment (inoculated/control) were used. Two-week-old Lathyrus genotypes13. Collected samples were immediately frozen in liquid nitrogen and stored at −80 °C. RNA was isolated using the GeneJET Plant RNA Purification Mini Kit  according to the manufacturer’s instructions. Isolated RNA was treated with Turbo DNase I , and RNA quantification was carried out using the NanoDrop device . For the E-SSR validation and linkage map development, DNA from frozen young leaves, from the two contrasting L. cicera genotypes and one individual of each RIL, was extracted using a modified CTAB protocol developed by Torres et al.38.Total RNA for RNA-seq, qRT-PCR and SNP validation, was extracted from inoculated and non-inoculated leaves, separately from each individual plant of the two contrasting genotypes. Leaves were collected 37 h after inoculation, representing a time point in which the fungal colonies are already developing in susceptible 2+ solution to obtain approximately 250 bp long RNA fragments. cDNA was synthesised by reverse transcription starting from 6(N) random hexamer oligonucleotides, followed by second strand synthesis. Barcoded Y-adapters were ligated to the cDNA and the library was amplified with 10 cycles of PCR. The libraries were paired-end sequenced on an Illumina Hiseq2000 machine.For each of the 4 combinations  total RNA was extracted individually from 24 plants per genotype and treatment and pooled in equal amounts for sequencing, in order to level out potential outliers. Five RNA-seq libraries  were generated using a proprietary protocol . In short, for each library, mRNA was captured from 20 µg of total RNA using Oligo dT(25) beads . The purified mRNA was randomly fragmented in a ZnL. cicera genotypes were united prior to assembly to generate a reference assembly, enabling the generation of contigs of maximum length. All high-quality reads were de novo assembled by the Trinity software (Version: trinityrnaseq_r2011-11-26). In order to minimise redundancy, CAP3 software39 was also used with overlap length cutoff of 30 bp and overlap percent identity cutoff of 75%. Redundancy was tested using the clustering algorithm UCLUST40, available from . A quality check for assembly completeness was assessed with BUSCO 41 against embryophyta_odb9. The resulting contigs were annotated via BLASTX to publicly available plant databases . To identify potential fungal transcripts, an additional BLASTX to public fungal databases  was performed.Raw sequence reads were passed through quality filtering, thereby also removing sequencing adapters and cDNA synthesis primers. RNA-seq libraries from control and inoculated leaves from each of the two contrasting de novo assembled contigs with novoalign . RPKM (reads per kilobase per million) were calculated as the normalised transcript expression value42. The obtained counts were subsequently passed through DEGSeq to calculate differential gene expression (R package version 1.16.0)43.The sequenced reads were quantified by mapping to our own 44, available at http://mapman.gabipd.org/web/guest/app/mercator, was used. The mapping file was created with information from the following manually curated databases: Arabidopsis TAIR proteins (release 10), SwissProt/UniProt Plant Proteins (PPAP), TIGR5 rice proteins (ORYZA), Clusters of orthologous eukaryotic genes database (KOG), Conserved domain database (CDD) and InterPro scan (IPR). The Mercator mapping file was then employed for pathway analysis by the MapMan software18, available at http://mapman.gabipd.org/web/guest/mapman.In order to classify the obtained contigs into functional categories, the Mercator pipeline for automated sequence annotation43.Differentially expressed contigs were identified and categorised in expression pattern groups by comparing their expression in leaves of the partially resistant genotype BGE023542, control vs. inoculated, and of the susceptible genotype BGE008277, control vs. inoculated, using DEGseq45. Primer sequences are listed in Supplementary Table 46, also included in Genex, was used to select the reference gene, considering the expression of γ-tubulin , Histone H2A.2  and P700 Phospholipase .To validate the RNA-seq results, expression levels of 8 selected genes were analysed by qRT-PCR. These genes were chosen to represent a broad range of differential expression and total transcript counts. 1 μg of total RNA from each of three randomly chosen plants , from the twenty-four plants used for the RNA-seq experiment pool, per genotype per treatment (inoculated/control), was reverse transcribed in technical duplicates, using the High Capacity cDNA Reverse Transcription Kit  following the manufacturer’s instructions, in a total of six samples per genotype and per treatment. qRT-PCR reactions were performed with an iQ™5 Real-Time PCR Detection System . Primers were designed using the Primer3 softwareL. cicera genotypes were discovered by JointSNVMix47, taking as input the mappings (bam files) from the transcriptome analysis (see section “RNA sequencing” and “Transcriptome assembly”). As reference, the contigs used were obtained according to the procedure described in section “Transcriptome assembly”. The output of the JointSNVMix analysis was furthermore processed by GenXPro’s in-house software to detect SNPs discriminating the variant alleles in the inoculated samples. A minimum coverage of 15 reads in each genotype and a probability of joint genotype BB_AA and AA_BB bigger than 0.98 was needed to call a SNP.SNPs distinguishing the transcripts of the two inoculated In order to analyse the differential expression of allelic variants, SNPs in genes of interest discriminating the genotypes BGE023542 and BGE008277 were selected, taking into account their expression patterns, for the design of allele-specific qRT-PCR assays   and their physical position in this genome to cover evenly M. truncatula’s chromosomic regions (http://www.medicagohapmap.org/tools/blastsearch), preventing unwanted clustering of markers, were screened. In addition, and for the linkage map construction also five heterologous ITAP markers selected from previous publications11, identified as polymorphic and with an 1:1 Mendelian segregation in this mapping population were used. PCR reactions and genotyping were performed as described in Almeida et al.17, with the exception of SNP markers that were genotyped using an Illumina’s custom Golden Gate genotyping assay provided by Traitgenetics GmbH, Germany.The DNA from each RIL individual in addition to the two parental lines was screened using a subset of the previously developed molecular markers. In this way, 163 E-SSR markers predicted 54, using a binary matrix including all the genotyping data as input. Markers with a severe segregation distortion (p ≤ 0.005) were removed from the original molecular data set. The determination of groups of linked markers (linkage groups-LGs) was done with a LOD score of 4. Linkage map calculations were done using all pairwise recombination estimates lower than 0.40 and a LOD score higher than 1.00, applying the Kosambi mapping function51. The reliability of the obtained map was checked by inspecting the individual LG χ2 value.Linkage analysis and segregation distortion tests were performed using JoinMap 4.0 softwareL. cicera linkage map and the information of the physical position of the same markers mapped on the M. truncatula genomic sequence (MT4.0)52 , markers were aligned in a matrix. Co-linearity was also investigated using Strudel visualisation software53. Columns from the matrix correspond to the M. truncatula genomic sequence and rows correspond to the L. cicera LGs rearranged in order to facilitate the visual estimation of co-linearity.Using the order of the genic SNP and SSR markers in the List of genes in expression pattern groups mapped to the reference assemblyList of primer sequences for the qRT-PCR experimentsLog2 fold expression results for RNA-seq and qRT-PCR experimentsList of detected polymorphic SNPs between chickling pea accessions BGE008277 and BGE023542List of detected polymorphic E-SSRs between chickling pea genotypes BGE008277 and BGE023542Description of the obtained linkage groupsTrancript information for allele-specific qRT-PCR assaysList of primer and probe sequences for the allele-specific expression analysis assayVenn diagram of the number of unique and shared contigs between the two genotypes and its expressionPercentage of contigs containing SNPs between the resistant and susceptible chickling pea genotypesL. cicera and M. truncatulaComparative plot of re-arrangement and synteny relationships between


We use a globally unique dataset that scores every individual academic’s holistic research performance in New Zealand to test several common explanations for the gender pay gap in universities. We find a man’s odds of being ranked professor or associate professor are more than double a woman’s with similar recent research score, age, field, and university. We observe a lifetime gender pay gap of ~NZ$400,000, of which research score and age explain less than half. Our ability to examine the full spectrum of research performance allows us to reject the ‘male variability hypothesis’ theory that the preponderance of men amongst the ‘superstars’ explains the lifetime performance pay gap observed. Indeed women whose research career trajectories resemble men’s still get paid less than men. From 2003–12, women at many ranks improved their research scores by more than men, but moved up the academic ranks more slowly. We offer some possible explanations for our findings, and show that the gender gap in universities will never disappear in most academic fields if current hiring practices persist. Many have noticed that fewer women make it to the top ranks of academia–3, and hRecent studies of the dearth of women at top ranks outside academia have re-examined the common explanations, of ‘women don’t ask’ for promotions, and strWithin academia, studies have examined another common explanation, called ‘demographic inertia’, in which the current preponderance of older men at the top pay grades is a hold-over from bygone eras of male-dominated universities that will fade with time,24. Yet A plethora of studies has observed many other types of gender differences in academia,24,29–54Our study stands alone in the global literature about academic gender biases and pay gaps, which are easier to posit than to quantify,74–76. WWe use this globally unique dataset that scores individual research performance for every New Zealand academic to ask whether there is a gender pay gap in NZ universities, and to decipher whether and how research performance explains it.New Zealand’s unique Performance Based Research Fund (PBRF) scores each individual’s research performance in a holistic and nuanced way to include peer esteem and research contributions, in addition to publications . Grades are strictly confidential; only the individual, his or her faculty dean or college Pro-Vice Chancellor (not head of department or school), and the Vice Chancellor (chief executive of a NZ university) and his or her Deputy know who got what grade.PBRF evaluates a research portfolio for each academic researcher in all public tertiary education institutes. There are tertiary institute staff who do not identify as researchers, particularly at polytechnics, and do not submit a portfolio; but the vast majority of university staff submit portfolios. Thus, in universities, academic researchers comprise a slightly smaller group than academic staff. We include only university researchers in our study, not researchers from polytechnics.PBRF panels have reviewed and scored a detailed research evidence portfolio for every academic researcher in the country’s eight universities  three times over nine years . At least two panel members evaluated and scored each portfolio , as well as expert advisors. To protect anonymity, we have clustered the 42 areas into 6 fields of study . There is also a moderation panel to ensure consistency across disciplinary panels, resolve inconsistencies, and advise the Tertiary Education Commission  about consistency issues.PBRF assessment emphasises quality and impact over quantity. In addition to publishing articles, PBRF research excellence includes: leading-edge knowledge, its application, public dissemination, national or global impact, and post-graduate supervision. To assep = 10-55; 2003: , p = 10-41). However, women have lower research scores  are lower than men’s. In 2012, 43.5% of men  and 21.1% of women  were ranked Associate Professor (AP) or Professor (P), yielding a significant gender odds ratio of being AP or P  of 2.9. In 2003, the gender odds ratio was 3.76  (p = 10-13). A woman’s odds of being a full Professor, rather than AP or P, are lower still (OR = 2.8. p = 10-14)  . Control= 10-14) .Breaking field into 42 subject areas shows variability amongst areas   . An equi = 0.02) .p = 0.06)  . This sup = 0.25), a vanishingly small coefficient (4 × 10-6), and has almost no effect on the gender odds ratio of 2.2 (p = 10-13) . Yet men in this group had higher odds of promotion to AP or P .We also explore promotion and salary increase patterns over time with the sub-sample of individuals who participated in both the 2003 and 2012 PBRF scoring exercises. First we consider only those at the lower ranks (L and SL) in 2003 . After cp = 0.006), more than at any other rank. Yet male Senior Lecturers had significantly higher odds of being promoted to AP or P . The gender difference in pay rise per year was $2384.5 (p = 0.02). Corresponding results are seen at the Lecturer level where the gender difference in score improvement is negligible, but men’s pay rises are higher. Only at the highest promotion level, from AP to P, are all the gender differences insignificant .Next we examine each rank and promotion separately . The mosFinally, we create a transition model with Leslie matrices to envisage the future university Click here for additional data file.S1 FigThis scale is similar in all New Zealand universities, though salaries differ.(TIF)Click here for additional data file.S2 Fig(A) The frequency of each academic rank split by gender. (B) The frequency of each research grade. (C) The expected age of the individuals at each rank. (D) The expected age of the individuals at each research grade.(TIF)Click here for additional data file.S1 TableTaken from 2018 salaries in academic collective agreements available fromwww.teu.ac.nz.(XLSX)Click here for additional data file.S2 TableThe table shows all regression models used, the gender coefficient (if included), associated p-value and corresponding odds ratio. Using the entire 2012 (or 2003) dataset the best fit model, as predicted by AIC, area under the receiver-operator curve or percentage of correct predictions, contains the gender variable. When a subset of the data is used , or we predict the probability of being a full professor, gender is still a significant predictor variable in the best fit models.(XLSX)Click here for additional data file.S3 TableThe table shows all regression models used, the gender coefficient (if included), associated p-value and corresponding odds ratio. Note that we used interactions between gender and other terms in these models, rendering the gender coefficient less explanatory in this case. The sample is the same as that in (XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.