Drosophila americana (SC and NE) and one population of D. novamexicana, and dissect its underlying phenotypic and genetic mechanisms. Mating trials revealed strong sexual isolation between Drosophila novamexicana males and SC Drosophila americana females, as well as more moderate bi‐directional isolation between D. americana populations. Mating behavior data indicate SC D. americana males have the highest courtship efficiency and, unlike males of the other populations, are accepted by females of all species. Quantification of cuticular hydrocarbon (CHC) profiles—chemosensory signals that are used for species recognition and mate finding in Drosophila—shows that the SC D. americana population differs from the other populations primarily on the basis of compound carbon chain‐length. Moreover, manipulation of male CHC composition via heterospecific perfuming—specifically perfuming D. novamexicana males with SC D. americana males—abolishes their sexual isolation from these D. americana females. Of a set of candidates, a single gene—elongase CG17821—had patterns of gene expression consistent with a role in CHC differences between species. Sequence comparisons indicate D. novamexicana and our Nebraska (NE) D. americana population share a derived CG17821 truncation mutation that could also contribute to their shared “short” CHC phenotype. Together, these data suggest an evolutionary model for the origin and spread of this allele and its consequences for CHC divergence and sexual isolation in this group.Because sensory signals often evolve rapidly, they could be instrumental in the emergence of reproductive isolation between species. However, pinpointing their specific contribution to isolating barriers, and the mechanisms underlying their divergence, remains challenging. Here, we demonstrate sexual isolation due to divergence in chemical signals between two populations of  Sensory signals can act as sexual cues that are critical for intraspecific mate evaluation and reproductive success. Moreover, because they are frequently among the most rapidly evolving species differences —a broad group of carbon‐chain compounds important for many essential functions including sex pheromone signaling, but also environmental adaptation  species—D. novamexicana and D. americana—that occupy distinct geographic and environmental habitats  and one western —here we use a combination of mating and behavioral studies, chemical analysis, and manipulation, and gene expression and sequence variation analyses to assess the role of CHCs in reproductive isolation. Together, our data suggest that evolution of a male sexual signal—an overall shift in the relative abundance of longer versus shorter cuticular hydrocarbons, due to novel mutation in an elongase gene—has produced complete premating isolation between derived males and females from species that retain the ancestral trait and preference, as proposed in classical models  = 8.99, P = 0.012), but not male identity  = 0.80, P = 0.67), significantly affected success. Post‐hoc comparisons confirmed no pairwise differences in male mating rate between any populations  and D. novamexicana (P‐adj = 0.042), whereas NE D. americana and D. novamexicana females did not differ (P‐adj = 0.15). Together, these results indicate that SC D. americana females discriminate against heteropopulation males more strongly than do females of the other two populations, with the greatest discrimination against D. novamexicana males. This discrimination produces strongly asymmetric sexual isolation between SC D. americana and D. novamexicana, while premating isolation between the two D. americana populations is bi‐directional and more moderate. Importantly, this strong asymmetric isolation reiterates results documented by Spieth   = 3.76, P = 0.03) and tap‐rate  = 4.76, P = 0.017), but only marginally for lick‐rate  = 2.67, P = 0.083). For all three behaviors, this difference is due to SC D. americana males exhibiting higher rates  = 1.83, P = 0.18; tap‐rate F = 0.58, P = 0. 56; lick‐rate: F = 0.43, P = 0.65), or any female × male interactions  = 0.72, P = 0.58; tap‐rate F = 0.45, P = 0.77; lick‐rate: F = 0.65, P = 0.63). Because behavior rates are dependent on copulation latency, and not simply the total number of behavioral events, these rates approximate the efficiency with which each courtship behavior results in a mating. Taken together, our results indicate that SC D. americana males have greater courtship efficiency (in terms of display and tap rates), and that males do not significantly vary these behavioral rates depending on female population identity.We video‐recorded single‐pair matings for each cross combination to evaluate population differences in courtship strategies and whether these differed in interpopulation pairings. Three male courtship behaviors were quantified from these 1×1 trials—display rate, tapping rate, and licking rate. All three behaviors showed similar patterns of among‐population variation, when each was evaluated for the effect of male population, female population, or their interaction, using two‐way ANOVAs. Males significantly differed with respect to display‐rate  = 2.97, P = 0.28; females: χ2(2) = 2.52, P = 0.23; males*females: χ2(4) = 12.67, P = 0.013)—a difference from 4×4‐mating trials where female population identity was the primary predictor of mating rate. This variation between the assays appears to be driven by female NE D. americana accepting fewer D. novamexicana males in 1×1 trials (20%) compared to 4×4 trials  = 3.14, P = 0.055) and the male by female interaction (F(4) = 2.48, P = 0.062), but did not differ based on female species identity (F(2) = 0.68, P = 0.5147). Post‐hoc tests suggest that the marginal male population effect is likely due to lower copulation latency in SC D. americana males relative to D. novamexicana males  we detected 8 alkene compounds (2 of which are sex‐specific) and 4 methyl‐branched alkane compounds present in at least one population. A principal component analysis of profiles from unmanipulated flies (unmanipulated‐PCA or “U‐PCA”) summarizing the primary axes of CHC profile composition found that 95.3% of compound variation across all samples was explained by the first three principal components (U‐PC1 to 3). Of these, CHC composition varied significantly for both population and sex for U‐PC1 , P < 0.0001; sex: F, P < 0.0001), and U‐PC2 , P = 0.00043; sex: F, P < 0.0001), but had no sex or population effect for U‐PC3 , P = 0.737; sex: F, P = 0.458; Figure D. americana of both sexes differed from the other two populations along the U‐PC1 axis , which also explains most of the CHC variation between samples (69.9%). U‐PC1 was positively loaded for most of the shorter carbon chain length compounds in both alkene and methyl‐branched alkane classes of compounds, and negative values were strongly loaded for the compounds with longer carbon chain length . Furthermore, we find that abundance of the individual male‐specific compound C21:1 differs between NE D. americana and males of the other two populations, but not between D. novamexicana and SC D. americana . , and the D. americana population pair (“NE‐SC pair”)— because SC D. americana shows the strongest sexual isolation from the two other populations, and the largest differences in CHC composition. Within each perfuming experiment, we generated four combinations of target and donor male identities: each population perfumed by same‐population males (control) and each population perfumed by hetero‐population males. Each class of perfumed males was evaluated for mating rate specifically with SC D. americana females, because these females were the most discriminating against heteropopulation males in our previous mating assays .  but differs from the complete mating isolation observed in unperfumed trials, possibly because of changes in behavior due to male‐male co‐housing during the perfuming manipulation.) The reciprocal treatment also showed a significant effect of perfume source: male SC D. americana perfumed with D. novamexicana males displayed copulation success of 19%, significantly lower success compared to conspecific‐perfumed SC D. americana . For NE‐SC pairings, SC D. americana male mating rate was also significantly reduced when perfumed with NE D. americana males (50%), compared to same‐population perfumed SC D. americana males . In contrast, mating rate of NE D. americana males perfumed with SC D. americana males increased slightly (56%), but did not significantly differ from the control (same‐population‐perfumed) males .We found that patterns of sexual isolation could be modified by specifically changing the CHC profiles of males of different populations. To do this, we used perfuming assays to manipulate the pheromone profile of males by co‐housing them with either intra‐ or inter‐population males, and then evaluated how this manipulation influenced mating rates among populations. For these analyses, we focused on two pairings in two separate, analogous experiments—ys Table . The obste Table . In stroD. americana females. SC D. americana males perfumed with profiles of either D. novamexicana or NE D. americana had significantly reduced mating rates with their own females. Conversely, perfuming D. novamexicana males with SC D. americana males significantly increased their mating rate with D. americana females, almost completely reversing the pattern of sexual isolation observed for unmanipulated males. This large shift in mating rate for heteropopulation‐perfumed D. novamexicana indicates that differences in male CHC profiles play a critical role in sexual isolation in the Nov‐SC pair. In contrast with the three other classes of heteropopulation‐perfumed males, perfuming NE D. americana with SC D. americana males did not significantly change their mating rate. It possible that this manipulation might have been less effective at altering the CHC profile of NE D. americana males (see next section), and/or that mating isolation in the NE‐SC pair might depend on more complex factors than a simple shift in CHC composition alone (see Discussion).Overall, these results indicate that perfuming males with heteropopulation CHCs influences the frequency of successful copulation with SC D. novamexicana males perfumed with SC D. americana males significantly differed in CHC composition from control (D. novamexicana) perfumed samples (N‐PC1) (t(5.9) = −2.8, P = 0.031); however, heteropopulation‐perfumed SC D. americana did not differ from same‐population SC D. americana‐perfumed samples along the same axis (t(3.53) = 1.91, P = 0.14). In contrast, in the NE‐SC pair, SC D. americana perfumed with NE D. americana showed a significant shift in A‐PC1 (t(4.85) = 4.23, P = 0.0088), but there was no significant shift for SC‐perfumed NE D. americana compared to same‐population‐perfumed controls (t(4.68) = 0.055, P = 0.96). The difference between these pairs might be attributed to high variation seen among samples in some groups (in particular same‐population perfumed SC D. americana). Regardless, it is clear from these results that this perfuming assay can produce significant, detectable differences in CHC profiles after heteropopulation perfuming, most notably in D. novamexicana males.Using CHCs extracted from an additional set of perfumed males (see Methods), we confirmed that our heteropopulation perfuming manipulation produced quantitative changes in composite male CHC profiles in both the Nov‐SC and NE‐SC pairs, by shifting male CHCs closer to the donor male profile. PCAs were performed separately for each pairing , as were analyses of differences among classes of perfumed males. In both cases, of the first three PCs of CHC composition, PC1  varied by both donor and target male identity Table , indicatD. americana compared to the other two populations; this pattern was observed in both sexes but is more pronounced in females . Lamb et al. D. americana stock and another D. novamexicana line (species stock center 15010‐1031.04). The profile for the D. novamexicana line had no long compounds (>C30), a low abundance of C29 compounds, and presence of multiple short alkenes (<C27), consistent with the “short” CHC profile we observe for our D. novamexicana line. Likewise, the IN D. americana profile they observed is broadly consistent with the “long” profile we observed in SC D. americana, as both show presence of compounds longer than 30 carbons, a high abundance of C29 length alkenes, and absence of compounds shorter than 27 carbons. In addition, using a genome assembly from the same IN D. americana stock  line share an identical derived allele at CG17821, indicating an evolutionary history at this locus that disagrees with expected phylogenetic relationships among these three taxa . Gene trees for each of our 23 candidate genes confirmed that CG17821 has a topology that is discordant with the expected species relationships, placing NE D. americana as sister to D. novamexicana rather than grouping it with SC D. americana  population—as determined by Patterson's D‐statistic , 13,372 SNPs grouped D. novamexicana and NE D. americana, and 6167 grouped D. novamexicana with SC D. americana. The significant excess of shared variants between D. novamexicana and our NE D. americana line , is consistent with a history of introgression between the progenitors of these two populations. Second, gene tree topologies at and around CG17821 also indicate this specific genomic region shares recent ancestry between D. novamexicana and NE D. americana due to introgression. CG17821, the adjacent downstream CHC candidate CG18609, and the next nearest gene  all display shared derived SNPs between D. novamexicana and the NE D. americana line, and discordant gene tree topologies that group these two lines as sister taxa. In contrast, topologies for the next two nearest up‐ or down‐stream genes in this region reflect the species tree, indicating that recent shared ancestry between D. novamexicana and the NE D. americana extends across a genomic window between 18 and 68 kB long around the specific region containing CG17821  decreases to <0.1 within a 1 kB window  to the exclusion of NE D. americana, D. novamexicana, and D. virilis, and therefore could not be responsible for the patterns of discordant variation we observe for these genes here. Coupled with genetic and phenotypic evidence above, these results indicate introgression of these genes between D. novamexicana and western D. americana—and not ILS—is most likely responsible for their shared allele at CG17821 and therefore potentially for their similarity in “short” CHC phenotypes.The observation of phylogenetically discordant sites can be due to several factors, notably incomplete lineage sorting (ILS) or post‐speciation introgression . Two lines of evidence strongly support introgression. First, evidence from SNP variants, across the whole transcriptome and specifically at CG17821, is more consistent with introgression between 1 Figure . EstimatdN/dS) at these loci, compared to a genome‐wide average rate estimated from our transcriptome‐wide dataset (see Methods). For 4397 genes transcriptome‐wide, the median and mean dN/dS were 0.065 and 0.0991, respectively (± 0.133 s.d.)  and CG18609 (dN/dS = 0.249)—as well as CG6660 (dN/dS = 0.38714)(full results in Table dN/dS > 1), only nine genes in the whole dataset met this criterion. Of the three candidate loci that exhibit elevated protein evolution, CG6660 does not show patterns of genealogical, allelic, or gene expression variation that match our observed CHC phenotypic variation  even when this branch was removed—indicating CG17821 has experienced consistently elevated protein evolution across the whole clade. In contrast, CG18609 protein evolution is estimated to be lower (dN/dS = 0.147) when just considering divergence between D. virilis and SC D. americana, suggesting that most of the accelerated protein evolution in this gene occurred after the split of the D. novamexicana/NE D. americana lineage. The timing of elevated protein evolution in CG18609 therefore also generally coincides with CHC profile differences observed here and, like CG17821, CG18609 is also an elongase. However, CG18609 does not show patterns of gene expression that match the “long” versus “short” CHC phenotypes we observe —to be among the fastest evolving loci in our transcriptome‐wide dataset: the orthologs of Obp99d , and Obp56g . OBPs are thought to facilitate olfactory processing by chaperoning odorants to the olfactory receptor neurons or terminating neuron activity by clearing odorants form the surrounding  populations of D. americana recapitulates patterns of isolation described in this group more than 70 years ago , female choice , or a combination of these factors. Disentangling these alternatives is critical for identifying the specific trait and corresponding preference variation responsible for the emergence of prezygotic species barriers. Here we showed that female choice of a male sensory signal results in strong sexual isolation among o Spieth , indicatDrosophila species  and the CHC elongase eloF has been demonstrated to inhibit interspecific mating in the same species  compared to an enrichment of longer compounds for SC D. americana (“long” phenotype). These differences in abundance of shorter‐ versus longer‐chain compounds were observed across both sexes, and across both alkenes and methyl‐branched alkanes  trees  D. novamexicana and  SC D. americana male CHC phenotypes, while SC D. americana females discriminate against derived “short” CHC phenotypes. Interestingly, this model for the evolution of asymmetric sexual isolation is broadly consistent with Kaneshiro's  pheromone phenotype . Prior evidence , and a genomic region of at least 18 kB of shared recent ancestry surrounding CG17821/CG18609 that accompanies a similar shift to the “short” CHC phenotype in western D. americana, support this inference. Note also that while D. novamexicana and D. americana are reported to be allopatric, limited and sporadic field collections of D. novamexicana mean there is an incomplete understanding of the density and extent of this species’ historical range. As a result, this species could have been in closer geographical contact with western D. americana populations during the period since their initial split , which could help explain evidence for introgression after speciation inferred here. Recent work  across the range of D. americana, plus variable genomic background effects on the expression of CHC loci, could contribute to the more complex mating relationships observed here, and elsewhere, among D. americana populations. For example, Spieth's mating analyses  is testable with work examining mating success between geographically diverse D. americana populations—particularly between eastern and western populations—and its covariation with CHC phenotypic and genotypic variation.Given the effect of the “short” CHC phenotype on sexual isolation between s Figure . A diffees Table  identifiD. americana populations, our data clearly support the role of divergent cuticular hydrocarbon profiles—specifically a general shift in carbon chain length—in sexual isolation between our D. novamexicana and SC D. americana populations. They also implicate a potentially causal role for the gene CG17821 in determining CHC phenotype via a global change in CHC elongation activity early in the generation of these compounds. These data provide a strong example of how a recently derived allele in a single gene with large phenotypic effects on a sexual signal could underpin asymmetric sexual isolation between closely related species. Moreover, they suggest multiple  lines of evidence that chemosensory processes are evolving rapidly and dynamically across this group.Regardless of the collateral consequences for isolation among Drosophila novamexicana stock from San Antonio, NM (15010‐1031.08); and two D. americana stocks, one from Chadron, NE ; and one from Jamestown, SC, . All stocks were originally collected between 1946 and 1953. D. americana has sometimes been divided into two subspecies according to presence (D. americana americana) or absence (D. a. texana) of a chromosomal fusion of the X‐ and 4‐chromosomes that shows a distinct latitudinal cline : a We performed trials in which four virgin males and four virgin females were paired and observed for mating behavior, following the design used by Spieth  that allTo quantify and evaluate differences in courtship behaviors between cross types, flies were observed in single pair (no‐choice) mating assays. We used a modified FlyPi setup—that combines a Raspberry Pi , pi camera, and 3D printed parts —to record courtship behaviors. Assays were performed in a modified cell culture plate consisting of six 3 cm‐diameter culture wells, each with a small amount of cornmeal media in the bottom, that allowed six total crosses to be recorded simultaneously. For each assay, individual virgin male and female flies of a given cross were aspirated without anesthetization to a cell culture well; after six total crosses were set up, the plate was videotaped for a contiguous 3‐h period. The six cross combinations assessed in any particular video trial were randomized to account for variance that might otherwise be explained by date. As in the 4×4 mating assay, we performed five replicates of all possible population combinations in reciprocal.Behavioral features were analyzed and scored manually by the same individual to avoid subjective variation among researchers. Three courtship behaviors—male display events, male tapping events, and male licking events—in addition to copulation were scored in each 1×1 trial using the following criteria. A male “display” was counted when a male performed a combination of back and forth movements and occasional wing flicks while maintaining sustained orientation in front of and facing the female. “Tapping” events were defined when a male used his tarsus to touch the abdomen of the female when oriented behind her. “Licking” events were defined when the male's mouthparts contacted the female genital arch. For male display, tapping, and licking events, individual events were scored separately only if a different behavior  was observed between instances of the defined behavior. This criterion minimized overcounting of discrete behavioral events, especially those with difficult to view aspects such as number of times a male extruded mouthparts during a contiguous licking event. In addition to these behaviors, copulation success and latency to copulation were also recorded for each trial. Note that females also engage in tapping and other behaviors, but because these appear to be less consistent and are more difficult to observe and score, they were not addressed in this study.Cuticular hydrocarbons were extracted from pooled samples by placing five 7‐day old virgin flies of a single sex and species identity in a 1.8 mL glass vial  with 120 μL of hexane  spiked with 10 μg/mL of hexacosane (Sigma Aldrich). After 20 min, 100 μL of the solution was removed to a sterilized 1.8 mL glass vial  and allowed to evaporate overnight under a fume hood. Extracts were stored at −20°C until analysis. Five replicate samples consisting of five flies per sample  were prepared for each sample type, and all replicates were extracted on the same day.m/z 33 to 500. For analysis of samples from perfuming trials, the parameters were modified to increase resolution and sensitivity for less abundant compounds: the column was set at 40°C and held for 3 min, increased to 200°C at a rate of 35°C/min, then increased to 280°C at a rate of 3°C/min and held for 15 min. Chromatograms and spectra were analyzed using MSD ChemStation . CHCs were identified on the basis of retention time and electron ionization fragmentation pattern. Compounds are identified in this study as: CXX:Y for alkenes or Me‐CXX for methyl‐branched alkanes, where XX indicates the length of the carbon chain, and Y indicates number of double bonds, e.g., C21:1 is a 21‐carbon alkene with a single double bond.Gas chromatography–mass spectrometry (GC/MS) analysis was performed on a 7820A GC system equipped with a 5975 Mass Selective Detector  and a HP‐5ms column ((5%‐Phenyl)‐methylpolysiloxane, 30 m length, 250 μm ID, 0.25 μm film thickness; Agilent Technologies, Inc.). Electron ionization (EI) energy was set at 70 eV. One microliter of the sample was injected in splitless mode and analyzed with helium flow at 1 mL/ min. Two different temperature gradients were used depending on the sample type. For CHC analysis of unmanipulated males and females of each species, the following parameters were used: column was set at 50°C for 0 min, increased to 210°C at a rate of 35°C/min, then increased to 280°C at a rate of 3°C/min. The MS was set to detect from The abundance of each compound was quantified by normalizing the area under each CHC peak to the area of the hexacosane signal using homebuilt peak selection software .D. americana. Within each experiment , we ran one trial of each perfuming condition  in parallel on the same day .“Perfuming” involves co‐housing target flies in vials filled predominantly with flies of a desired donor identity, so that the CHC profile of the target flies is altered via physical transfer of CHCs from donor flies  were co‐housed with 15–18 donor males, enabling two parallel perfuming vials to generate five target male flies per identity, for each individual CHC extraction. This was then replicated four times for each identity to reach N = 4 biological replicates for this analysis.Drosophila melanogaster genes with one of the protein‐coding domains (as identified by InterProt) that have known functions in CHC synthesis  generated by Kim et al. Our candidate list was generated by searching Flybase (Flybase.org) for annotated nd Moyle  dataset.RI1 for prezygotic barriers as defined by Sobel and Chen (RI1 = 1 – (heterospecific success)/(conspecific success).All statistical analyses and figure construction in this study was performed with R version 3.4.3. For the unperfumed 4×4 mating dataset, we used Kruskal‐Wallis tests to compare copulation success within 3 h of observation with male or female species identity (one test for each sex). In addition, we used Wilcoxon rank sum tests to perform post hoc pairwise comparisons for each sex to evaluate which species differed from one another in female acceptance of males or in male courtship success of females. We also calculated the reproductive isolation index and Chen . This inIn 1×1 mating trials, mating rate was evaluated using a logistic regression with a chi‐square test. For copulation latency, a two‐way ANOVA was performed with latency in minutes as the dependent variable, to test for the effects of male identity, female identity, and their interaction. This was followed by a post hoc Tukey HSD in which we assessed which male identities (populations) were specifically different for copulation latency. For each of the three courtship behaviors , we converted the count data for each trial to a rate per unit time within a trial, by dividing the recorded counts for each trait by the latency to copulation (in minutes) or, if no copulation occurred, the maximum amount of observed time (180 minutes). Describing male behaviors in terms of rates accounts for differences among males in their courtship efficiency; for example, it allows us to differentiate males that performed fewer courtship behaviors because they were rapidly accepted by a female, from males that displayed lower courtship intensity across the total 3 h monitored period. For each of the three behavior rates  as dependent variables, we performed an ANOVA with male identity, female identity, and their interaction as independent variables.D. americana females. This enabled us to specifically assess the effects of donor perfume variation on mating success of a given target male species. Each pairwise test was performed using a non‐parametric Mann‐Whitney U test.The perfumed 4×4 mating experiment was analyzed using planned contrasts that compared the mating success of males that had the same target identity but different (con‐ versus hetero‐specific) donor perfumes, when paired with SC Our primary analyses of differences in CHC composition were done after summarizing major axes of variation in CHC phenotypes using a set of Principal Component Analyses (PCA). Separate PCAs were performed on each CHC experiment within this study: one PCA for the initial (unperfumed) parental populations (denoted U‐PCA), and one PCA for each of the perfumed experimental pairs—Nov‐SC (N‐PCA) and NE‐SC , and therefore is normalized within each sample. Here, we analyzed datasets separated by sex, as Davis and Moyle  showed tdN/dS) for 4397 genes in this transcriptome‐wide dataset, to quantify molecular evolution transcriptome‐wide in this group and to evaluate evidence for positive selection specifically in candidate loci. We used a pipeline for obtaining genome‐wide estimates of dN/dS modified from Wu et al. D. virilis reference genome  to identify loci with expression in the populations studied here. Then, for each gene with transcripts present in all populations and coding sequence (CDS) annotated in the D. virilis reference, a consensus fasta was generated for each line (population) for the longest splice variant of a given gene. These consensus fasta sequences were then aligned to each other using PRANK  for the 100 loci with the highest estimated rates of protein evolution.We also estimated rates of nonsynonymous to synonymous substitutions , novamexicana), virilis)figure  top treeThe authors have declared no conflict of interest.https://doi.org/10.5061/dryad.jsxksn09c. Video recordings, code, as well as raw GCMS output are available upon request.The data that support the findings of this study are openly available in Dryad at Table S1: Mating rate data from Table 3 of Spieth 1951.Table S2: Posthoc comparisons for differences in male courtship success (based on proportion mated) between male populations regardless of female identity.P‐values between male identities for each behavior.Table S3: Posthoc comparisons of pairwise species differences in male behavior rates. Tukey HSD post‐hoc mean differences and P‐values between male identities reported.Table S4: Posthoc comparisons of pairwise species differences for copulation latency based on male population identity. Tukey HSD post‐hoc mean differences and Table S5: Loadings for principal component (U‐PC) axes for each individual compound detected from GC/MS analysis of unmanipulated (unperfumed) samples.Table S6: Analyses of individual cuticular hydrocarbon compounds in unmanipulated (unperfumed) samples, from two‐way ANOVAs testing for population or sex differences.Table S7: Analyses of the first three PCs of CHC compound variation from each perfuming pair, from one‐way ANOVAs examining the effects of donor and target male identity on each PC.dN/dS values for 23 candidate genes associated with CHC function. For genes with elevated clade‐wide dN/dS, we evaluated dN/dS between D. virilis and SC D. americana only to determine if accelerated evolution is limited to the most derived pairs.Table S8: Clade‐wide D. virilis ortholog).Table S9: List of candidate genes and presence/absence of transcript expression in transcriptomes of each population used here  axes for each individual compound detected from GC/MS analysis.Table S11: NE‐SC perfume sample loadings for principal component (A‐PC) axes for each individual compound detected from GC/MS analysis.D. novamexicana C21:1 tests the difference between C21:1 values in D. novamexicana target males perfumed with D. novamexicana or SC D. americana donor males. Compound abundance values were log‐transformed for analysis.Table S12: Analyses of individual cuticular hydrocarbon compounds in perfumed samples, from t‐tests comparing target males with con‐ and hetero‐specific donor perfumes. For example, F‐value and un‐adjusted P‐value of ANOVA test.Table S13: Species differences in quantitative gene expression for 23 candidate genes associated with CHC function, analyzed separately by sex, with n = 4 for all bars).Figure S1: Relative log‐scale abundance of compounds for perfumed males from NE‐SC (left) and Nov‐SC (right) experimental pairs for each major compound type  and the NE‐SC pair (panel B).dN/dS values from 4397 genes. The median dN/dS value was 0.065, while the mean and standard deviation were 0.0991 ± 0.133.Figure S3: Distribution of clade‐wide Click here for additional data file.Supporting InformationClick here for additional data file.


Oxidative stress (OxS) and mitochondrial dysfunction are implicated as causative factors for aging. Older adults (OAs) have an increased prevalence of elevated OxS, impaired mitochondrial fuel‐oxidation (MFO), elevated inflammation, endothelial dysfunction, insulin resistance, cognitive decline, muscle weakness, and sarcopenia, but contributing mechanisms are unknown, and interventions are limited/lacking. We previously reported that inducing deficiency of the antioxidant tripeptide glutathione (GSH) in young mice results in mitochondrial dysfunction, and that supplementing GlyNAC (combination of glycine and N‐acetylcysteine [NAC]) in aged mice improves naturally‐occurring GSH deficiency, mitochondrial impairment, OxS, and insulin resistance. This pilot trial in OA was conducted to test the effect of GlyNAC supplementation and withdrawal on intracellular GSH concentrations, OxS, MFO, inflammation, endothelial function, genotoxicity, muscle and glucose metabolism, body composition, strength, and cognition.A 36‐week open‐label clinical trial was conducted in eight OAs and eight young adults (YAs). After all the participants underwent an initial (pre‐supplementation) study, the YAs were released from the study. OAs were studied again after GlyNAC supplementation for 24 weeks, and GlyNAC withdrawal for 12 weeks. Measurements included red‐blood cell (RBC) GSH, MFO; plasma biomarkers of OxS, inflammation, endothelial function, glucose, and insulin; gait‐speed, grip‐strength, 6‐min walk test; cognitive tests; genomic‐damage; glucose‐production and muscle‐protein breakdown rates; and body‐composition.GlyNAC supplementation for 24 weeks in OA corrected RBC‐GSH deficiency, OxS, and mitochondrial dysfunction; and improved inflammation, endothelial dysfunction, insulin‐resistance, genomic‐damage, cognition, strength, gait‐speed, and exercise capacity; and lowered body‐fat and waist‐circumference. However, benefits declined after stopping GlyNAC supplementation for 12 weeks.GlyNAC supplementation for 24‐weeks in OA was well tolerated and lowered OxS, corrected intracellular GSH deficiency and mitochondrial dysfunction, decreased inflammation, insulin‐resistance and endothelial dysfunction, and genomic‐damage, and improved strength, gait‐speed, cognition, and body composition. Supplementing GlyNAC in aging humans could be a simple and viable method to promote health and warrants additional investigation. This study found that compared to healthy young adults, older humans have severely elevated oxidative stress, glutathione deficiency, impaired mitochondrial function, increased inflammation, insulin resistance and endothelial dysfunction, and lower muscle strength and mental cognition. We tested and found that supplementing GlyNAC (combination of glycine and N‐acetylcysteine) improved all these defects, and that stopping GlyNAC resulted in a loss of benefits. The results of this trial suggests that GlyNAC supplementation could be a simple, safe and effective nutritional strategy to boost cellular defenses to protect against oxidative stress, correct mitochondrial defects to improve energy availability, increase muscle strength and cognition, and thereby promote healthy aging in humans. However, mitochondrial function is impaired in OA.22.1An open‐label 36‐week clinical trial was approved by the Institutional Review Board at Baylor College of Medicine and registered with clinicaltrials.gov (NCT02348762) Figure .2.2Eight OA  and eight gender‐matched young adults (YAs) (21–30 years) who volunteered to participate in the study were recruited and enrolled after meeting inclusion/exclusion eligibility criteria. YAs were aged 24 ± 1.0 years, and OAs were aged 74 ± 1.0 years.Inclusion criteria: Age range 70–80 years (OA), 20–30 years (YA). Exclusion criteria: Diabetes , abnormal thyroid function tests, untreated thyroid or heart disease, active malignancy, liver or kidney impairment , anemia (hemoglobin < 11 g/dl), fasting triglycerides > 500 mg/dl, or inability to walk.Non‐vitamin nutritional supplements or acetaminophen were stopped from 4 weeks prior to laboratory tests until the end of the 36‐week study. All participants were non‐smokers and asked to avoid consuming alcohol during the study. Participants were also asked to continue their usual habitual diets during the 36‐week period of the study. Because our exclusion criteria included individuals with cancer, diabetes, heart, liver, and renal diseases, medications were not a significant burden on these patients. None of the patients were taking any steroids or anti‐inflammatory agents.2.32H2‐glucose initiated at 21.6 μmol/kg, maintained at 21.6 μmol/kg/h for 5‐h; 2H3‐methylhistidine initiated at 0.06 μmol/kg, maintained at 0.03 μmol/kg/h for 3‐h). Blood was drawn during the final hour during steady‐state, centrifuged immediately and red‐blood cells (RBC) and plasma stored at −80°C for later analyses. Indirect calorimetry was performed for 45 min in the 5th h. Urine was collected for 6 h during the visit. Participants were discharged home after a meal. The YAs were not supplemented with GlyNAC and were released from the study. OAs were studied again at 12 weeks (midpoint of supplementation) to understand the impact of GlyNAC supplementation on GSH, OxS, MFO, physical and cognitive function, plasma biomarkers, and body‐composition, but tracer studies were not done at this time. At the end of the 24 weeks of supplementation, the full protocol (including tracer studies) was repeated. To determine the effects of stopping GlyNAC for 12 weeks on GSH, OxS, MFO, physical and cognitive function, and plasma biomarkers, OAs were studied again at 36‐weeks but participants did not have tracer infusions or DEXA scans at this time.Studies were conducted at the Metabolic Research Unit (MRU) at Baylor College of Medicine. There were two pre‐supplementation visits. Study participants first came to the MRU after an overnight fast for blood draws  and physical function assessment and were provided oral deuterated water (4 g/kg body weight) to be taken the night before the second visit. The participants then returned a few days later to undergo cognitive testing, dual‐energy x‐ray absorptiometry (DEXA) scan and metabolic studies. Intravenous catheters were placed in the dorsum of both hands. After basal blood sampling, tracers were infused (2.4OAs were provided capsules of glycine (1.33 mmol/kg/day) and cysteine  prepared by a licensed pharmacist, and replenished every 4‐weeks for 24‐weeks. Compliance with GlyNAC supplementation was assessed with phone calls and capsule‐counting every 4‐weeks when OA returned to collect GlyNAC capsules for the next 4‐weeks, and to have blood drawn for monitoring renal (creatinine) and liver function (as ALT and AST).2.52.5.1RBC total and reduced GSH concentrations were measured by liquid chromatography (Waters ACQUITY UPLC System), and concentrations of oxidized glutathione (GSSG) calculated as the difference between total and reduced GSH. TBARS , and 8‐Iso‐Prostaglandin‐F2a  in plasma were measured as markers of OxS.2.5.2MFO was measured by calorimetry  and reported as respiratory quotient, mitochondrial fatty‐acid, and glucose oxidation.2.5.3Fasting plasma glucose concentrations were measured with an automated glucose analyzer  and insulin concentrations by ELISA kit . Insulin resistance was calculated as HOMA‐IR using fasting plasma glucose and insulin concentrations, as reported by us previously.2.5.4These biomarkers were measured using high‐sensitivity ELISA kits with measurement of IL6 human, TNFα, sICAM1, sVCAM1, and E‐selectin  and human C‐reactive protein . The oxidative genomic (DNA/RNA) damage was measured using a high‐sensitivity ELISA Kit .2.5.52H3]‐3‐methylhistidine was purchased from Cambridge Isotopes Laboratories , dissolved in saline, and infused after sterility testing. Blood samples were centrifuged, and plasma was frozen until analysis.(a) Muscle protein breakdown rate (MPBR): Stable isotope preparation: Sterile [2H3]‐3‐methylhistidine were monitored. Instrumental control, data acquisition, and analysis were performed by the Xcalibur (version 2.1) software package . Serum 3‐methylhistidine concentration was measured in the basal sample by an isotope dilution method using [2H3]‐3‐methylhistidine as an internal standard. The samples were then analyzed as described above.Isotopic Analyses: serum isotope enrichment of 3‐methylhistidine was measured by liquid‐chromatography tandem mass‐spectrometry after conversion into its DANS  derivative and analyzed using a Synergi Fusion‐RP 2.5μ 100 × 2.0 mm column  on a triple quadrupole mass‐spectrometer . Ions m/z 403 and 406 to product ion m/z 170 for 3‐methylhistidine and [Calculations: 3‐methylhistidine (3MH) flux = F x [(IEi/IEp)‐1]; where F = isotope infusion rate; IEi = isotopic enrichment of the infusate in mol percent excess (MPE); IEp = isotopic enrichment at steady state in MPE.MPBR: Because 3‐MH is released only from the breakdown of myofibrillar protein present in skeletal muscle, its flux is used to estimate MPBR based on a 3‐MH concentration of 3.64 μmol/g of muscle protein, that is, MPBR = 3MH flux/3.64.2H2O), 2H and  glucose was purchased from Cambridge Isotopes Laboratories .  glucose was dissolved in isotonic water, filtered, and infused after sterility testing. Blood samples were centrifuged, and plasma was frozen.(b) Rates of appearance of glucose, glucose production rate, gluconeogenesis, and glycogenolysis: Stable isotope preparation: Sterile and pyrogen free deuterium oxide  using the penta‐acetate derivative. The incorporation of deuterium in glucose from 2H2O was determined using the average deuterium enrichment in glucose carbons 1, 3, 4, 5, and 6.46 Deuterium enrichment in plasma water was determined by Isotope Ratio Mass Spectrometry .Isotopic Analyses: The isotopic enrichment of ‐glucose, where F = isotope infusion rate; IEi = isotopic enrichment of the infusate in mol percent excess (MPE); IEp = isotopic enrichment at steady state in MPE.Calculations: Rate of appearance of glucose (Ra glucose) = F x [(IEi/IEp)‐1], calculated during steady‐state from the M+2 enrichment of plasma  [m/z 170/169] /6) / IE2H2O; where (M+1)(2H) (m/z 170/169) is the M+1 enrichment of deuterium in glucose measured using m/z 170/169, and "6" is the number of 2H labeling sites on the m/z 170/169 fragment of glucose ; IE2H2O is the deuterium enrichment in plasma water.Fractional gluconeogenesis (GNG%) = , grip strength (best of 3 readings using a Jamar dynamometer), and exercise capacity .2.5.7Participants in this study did not have a known diagnosis of abnormal cognition. The cognitive status of participants was assessed using tests which are commonly used in the clinical outpatient setting to test cognition in OA and include the Montreal cognitive assessment (MoCA), trail‐making tests A and B, verbal fluency test, and the digital‐symbol substitution test (DSST).2.5.8Total body fat and truncal fat were measured by DEXA scans. Height and weight were measured using a stadiometer and calibrated weighing scale, respectively and used to calculate body mass index. Waist circumference was measured using a tape measure, and the same sites were used for repeat measurements.2.5.9Fasting plasma concentrations of liver profile, lipid profile, Creatinine, BUN, HbA1c, cortisol, Free T4, and TSH were measured at the Clinical Pathology Labs.2.6t‐test was used to compare OA and YAs in the pre‐supplemented state. A general linear mixed model was used to test for changes in outcomes across time points for OA. The model included fixed effects for study time (discrete) and the matrix of correlated residuals assumed an unstructured format. The mixed model is used to estimate means with 95% confidence intervals, and test the null hypothesis that there is no difference in means between time points. All hypothesis tests were assessed at the 0.05 level (two‐sided). p‐values were not adjusted for multiple hypothesis testing due to the small sample size of this pilot study.Baseline characteristics are summarized by means with standard deviations. An unpaired 33.1All participants completed the study, and there were no withdrawals from the study. An adverse event (AE) was defined as any side effect of GlyNAC. Any event that was reported to either the study team or research nurse by the subject was documented as such. The following grading scale for AEs was used:0 = No AE; 1 = Mild AE requiring no intervention; 2 = Moderate AE requiring treatment; 3 = Severe AE requiring admission to a hospital; 4 = Life‐threatening AE; 5 = Death. The AE score was 0 as there were no AEs reported. Monitoring plasma creatinine, alanine transaminase, and aspartate transaminase every 4‐weeks did not show any elevations or abnormalities.3.2Participants had normal pre‐supplementation laboratory results as shown in Table 3.3Compared to YA controls, RBC concentrations of reduced‐GSH in OA were 76% lower, and plasma TBARS and F2‐isoprostane concentrations were 845% and 318% higher, respectively  versus older adults (OA) at baseline (0 week), midpoint (12 weeks), completion of supplementation (24 weeks), and after 12 weeks of stoppage (36 weeks). (A) RBC‐total glutathione concentrations; (B) plasma TBARS concentrations; (C) mitochondrial fatty‐acid oxidation (whole‐body); (D) mitochondrial glucose oxidation (whole‐body); (E) plasma high‐sensitivity Interleukein‐6 (hsIL6) concentrations; (F) plasma soluble vascular cell adhesion molecule 1 (sVCAM1) concentrations; (G) insulin resistance (as HOMA‐IR); (H) gait speed; (I) trail‐making test B (TMT‐B); (J) plasma BDNF concentrations3.4Compared to fasting YAs, fasting OA had a significantly higher respiratory quotient and abnormal mitochondrial fuel oxidation, with a significant 54% lower mitochondrial fatty‐acid oxidation and 51% higher MGO Table  Figure . GlyNAC 3.5Compared to YAs, OA had significantly elevated plasma levels of pro‐inflammatory cytokines  and decreased levels of an anti‐inflammatory cytokine interleukin‐10 (IL‐10) Table  Figure . Fasting3.6Compared to YAs, the rate of muscle protein breakdown in OA was 35% higher, and this declined by 21% with GlyNAC supplementation Table . Rates o3.7OA had significantly higher total body weight (8.7% higher), BMI (10.6% higher), total body fat (47.7% higher), and waist circumference (12 cm higher) Table . GlyNAC 3.8OA had significantly impaired cognition scores on the Montreal cognitive‐assessments, trail making tests A and B, verbal‐fluency test and DSST, together with lower fasting plasma brain derived neurotropic factor (BDNF) level Table  Figure . OA also4The key findings of this trial are that (1) compared to YAs, OA have GSH deficiency, elevated OxS, impaired MFO, higher inflammation, endothelial dysfunction, insulin resistance, muscle‐protein breakdown, elevated body fat and lower cognitive function, gait speed, muscle strength and exercise capacity, (2) supplementing GlyNAC as GSH precursors for 24‐weeks significantly improved these defects, and (3) accrued benefits receded on stopping GlyNAC for 12‐weeks.4.1GlyNAC supplementation for 24 weeks was well tolerated without any elevation in plasma concentrations of creatinine, alanine transaminase, or aspartate transaminase. On questioning, participants reported no gastrointestinal or any other adverse effects. There were no participant withdrawals from the study.4.2GSH levels have been reported to be inversely related to multimorbidity in OA.2O2). This process requires complete detoxification of H2O2 to water, and GSH is necessary for this to occur as depicted in the detoxification reaction H2O2 + 2GSH → 2H2O + GSSG. Thus, GSH adequacy is critically necessary for cellular protection from the ravages of OxS. We reported earlier that GSH deficiency in OA occurs due to diminished synthesis, and this is caused by decreased availability of its precursor amino‐acids glycine and cysteine.During the process of cellular protection from the harmful effects of OxS, the highly toxic superoxide radical is converted by superoxide dismutase to the less toxic hydrogen peroxide . In an earlier study in OA, we found and reported that GlyNAC supplementation for 2 weeks improved mitochondrial fatty‐acid oxidation.4.4Chronic, elevated inflammation, and endothelial dysfunction are linked to OxS and to many diseases of aging,Because inflammation, endothelial dysfunction, insulin resistance, mitochondrial dysfunction, and increased waist circumference are linked to an elevated risk of metabolic syndrome and cardiovascular disease in aging humans, improvements in these defects with GlyNAC supplementation suggest the possibility of promoting cardiovascular and cardiometabolic health. Evidence to support this comes from our recent publication where GlyNAC supplementation in aged mice was found to correct defective cardiac mitochondrial energetics, lower cardiac inflammation, and improve diastolic dysfunction.4.5GlyNAC supplementation significantly lowered insulin resistance in OA. Elevated OxS has adverse effects on insulin signaling4.6Aging is the greatest risk factor for cognitive decline and dementia affecting millions of OA and results in impaired learning, memory, executive function, attention, language, perceptual motor function, and social cognition,63 improvements in these defects with GlyNAC supplementation could also have contributed to cognitive improvement in this study. GlyNAC could also be having a direct effect in the brain as seen by a significant increase in the diminished levels of the brain biomarker BDNF. BDNF is involved in the preservation of memory, synaptic plasticity, and maintenance of neuronal networks,Glucose is the primary fuel for the brain. In this study, we found two paradoxical observations regarding whole‐body MGO and cognition as measured by testing performance: (1) prior to starting GlyNAC supplementation, OA had impaired cognition (compared to YA) despite increased whole‐body MGO and (2) after GlyNAC supplementation their whole‐body MGO decreased, but cognition improved. The most parsimonious explanation for these opposing and paradoxical findings is as follows: In the fasting state, glucose provides energy for the brain, and fatty‐acids provide energy for non‐brain tissues. GSH adequacy is essential for optimal mitochondrial fatty‐acid oxidation.4.7Maintaining optimal muscle mass depends on a balance between muscle protein synthesis and breakdown. In the fasting state, muscle protein breakdown exceeds synthesis,4.8Increasing age is associated with physical decline and diminished exercise capacity, both of which are components of sarcopenic obesity in OA. Although a key meta‐analysis in OA has shown that lower gait speed is linked to decreased survival,4.9Although impaired MFO is a risk factor for weight gain,4.10Aging is associated with genomic damage, which is an aging hallmark, and is linked to cancer. In this study we measured and found that compared to YA, OA had significantly higher levels of plasma 8‐OHdG (8‐hydroxy‐deoxyguanosine), a validated biomarker of DNA (deoxyribonucleic acid) damage. Both increased ROS (which induce OxS) and 8‐OHdG have been linked to increased risk of developing colon, prostate, and breast cancer.4.11Because cysteine and glycine are gluconeogenic amino‐acids, could they be used for increasing gluconeogenesis to support the abnormally elevated fasting MGO? Tracer data refute this as glucose production rates were not increased in OA, therefore glycine and cysteine were not being used for glucose production. The most parsimonious explanation is that due to a severe defect in MFO, amino‐acids (including glycine and cysteine) were being diverted toward energy generation. This explanation could also account for the elevated muscle protein breakdown seen in OA and its recovery with GlyNAC supplementation in OA.4.12The field of geroscience has identified at least nine hallmark defects of aging which are believed to contribute to the aging process.4.13all of these defects. We speculate that GlyNAC represents three forces which could be operating simultaneously to result in such widespread improvements: (1) Correction of GSH deficiency, which results in correction of OxS and mitochondrial dysfunction. GSH is the most abundant endogenous, intracellular antioxidant. Any intervention to correct GSH needs to necessarily correct intracellular GSH concentrations, and GlyNAC does this efficiently and effectively. However, correction of GSH alone is insufficient to explain the magnitude and extent of improvements, suggesting that there may be other factors in play; (2) GlyNAC contains glycine, an important methyl‐group donor. Methyl groups are abundant in DNA and are important components of multiple cellular reactions. Glycine is also important for normal brain function. Hence providing glycine could improve multiple defects as seen in this trial; (3) GlyNAC contains N‐acetylcysteine, which functions as a cysteine donor. Cysteine is critically important in energy metabolism by contributing the sulfhydryl (SH) group needed for energy generation. For example, coenzyme A (CoA‐SH) is an important component of reactions governing energy generation and depends on the availability of a SH group for its normal functioning. Cysteine and its donated SH groups also play key roles in multiple additional cellular reactions and function.This is an important question because of the breadth and depth of improvements in multiple parameters, especially when a single nutritional intervention appears to correct Thus, it can be seen that the combination of glycine, cysteine, and GSH could be acting in combination to result in powerful improvement, recovery, and correction of multiple abnormalities and defects as seen in this trial in older humans, and results in increased strength and improved cognition. This could explain why GlyNAC supplementation works to promote healthy aging.4.14Although the observations in this study support the impact of supplementing GlyNAC on improving several age‐associated defects, these results should be viewed with the caveat that this is a pilot trial, the study sample size was small, and that the study lacked a blinded placebo group of OA. Nevertheless, these results suggest that GlyNAC supplementation improves cellular protection, mitochondrial energy metabolism, strength, physical function, and cognitive health in OA. The rapidly increasing world population of older humans will result in an urgent need for novel strategies to promote healthy aging to prevent diseases stemming from age‐associated metabolic and mitochondrial abnormalities, and therefore the results of this open‐label trial supports the need for additional trials of GlyNAC supplementation in aging.5The results of this trial suggest that GlyNAC supplementation in OA is well tolerated and could play a novel role in improving healthy aging in OA by correcting GSH deficiency, OxS, mitochondrial dysfunction, inflammation, insulin resistance, endothelial dysfunction, body fat, muscle strength, gait speed, and cognitive function. GlyNAC supplementation also appears to improve hallmark defects in aging, which could be an exciting discovery and needs to be confirmed in future studies. Dietary supplementation of GlyNAC could improve the cellular, mitochondrial, and metabolic health of OA, improve strength and cognition, and thereby promote healthy aging. No side‐effects of GlyNAC supplementation were detected during 36‐week duration of the study. The results of this study support the need for future trials to assess the effects of GlyNAC supplementation in a larger population of OAs receiving GlyNAC supplementation for a longer duration.None of the authors have any conflicts of interest to disclose.Premranjan Kumar performed blood analyses and contributed to manuscript preparation. Chun Liu was the study coordinator and processed tracer samples. Charles Minard performed statistical analyses. Shaji Chacko designed the glucose‐tracer protocol and performed glucose‐tracer calculations. Jean W. Hsu prepared tracer solutions and performed methylhistidine‐tracer calculations. Farook Jahoor designed the methylhistidine‐tracer protocol, supervised Jean W. Hsu and Chun Liu, and contributed to the manuscript. Rajagopal V. Sekhar conceived the hypotheses, designed the trial, obtained funding, developed the GlyNAC intervention, recruited and consented subjects, supervised Premranjan Kumar and Chun Liu, interpreted data, and wrote the manuscript.This work was supported by a philanthropic gift from the McNair Medical Institute at the Robert and Janice McNair Foundation in Houston, Texas, USA.Supporting InformationClick here for additional data file.


CDK1 mRNA. Microarray and external RNA‐seq data from 664 cases of ESCC and 1733 cases of control tissues were used to verify the difference in CDK1 expression between the two groups. A comprehensive analysis of all data was performed to evaluate the difference in CDK1 between ESCC tissues and control tissues. Further, functional enrichment analyses were performed based on differentially expressed genes (DEGs) of ESCC and co‐expressed genes (CEGs) of CDK1. In addition, a lncRNA‐miRNA‐CDK1 network was constructed. The expression of CDK1 protein was obviously increased in ESCC tissues . RNA‐seq indicated that the mRNA level of CDK1 was also highly expressed in ESCC tissues . Comprehensive analysis revealed consistent up‐regulation of CDK1 . Further, functional enrichment analyses revealed that the functions of these genes were mainly concentrated in the cell cycle. A triple regulatory network of PVT1‐hsa‐miR‐145‐5p/hsa‐miR‐30c‐5p‐CDK1 was constructed using in silico analysis. In summary, overexpression of CDK1 is closely related to ESCC tumorigenesis.Cyclin‐dependent kinase 1 (CDK1) plays a significant role in certain malignancies. However, it remains unclear whether CDK1 plays a role in esophageal squamous cell carcinoma (ESCC). The aim of this study was to analyze the expression and clinical value of CDK1 in ESCC. CDK1 protein in 151 ESCC tissues and 138 normal esophageal tissues was detected by immunohistochemistry. RNA‐seq of eight pairs of ESCC and adjacent esophageal specimens was performed to evaluate the levels of  Cyclin‐dependent kinase 1 (CDK1) plays a significant role in certain malignancies. The main objectives of this study are to comprehensively evaluate the expression pattern of CDK1 in ESCC and to explore the pivotal regulatory role of CDK1 in ESCC by DEGs, CEGs, lncRNAs, and miRNAs. CDKscyclin‐dependent kinasesCDK1cyclin‐dependent kinase 1CEGsco‐expressed genesDEGsdifferentially expressed genesESCCesophageal squamous cell carcinomaEsophageal cancer is one of the most common malignant tumors in the world and is the seventh highest cause of cancer‐related death . There ain vivo experiments that the tumor volume increased significantly in overexpressed wild‐type CDK1 cells compared with vector control or kinase‐dead variant CDK1 cells  r. (2018) . These s. (2018) . The res. (2018) . It has . (2018) . Moreove. (2018) . The res. (2018) . In our  r. (2018. (2018) , which i. (2018) . Our patet al. [CDK1 in ESCC has not been reported yet. Therefore, we explored the regulatory network of upstream miRNA and lncRNA centered on CDK1 in ESCC. By further analysis of SMD and Pearson correlation, we successfully constructed two pairs of subnetworks PVT1‐hsa‐miR‐145‐5p / hsa‐miR‐30c‐5p‐CDK1. Importantly, the role of these lncRNA and miRNAs in esophageal cancer in this network has been reported in the literature. For example, it has been reported that overexpression of PVT1 is relevant to poor prognosis of esophageal adenocarcinoma [Further, gene expression is regulated by lncRNA and miRNA, which cannot be ignored , 34. Sinet al.  first pret al. . In addiet al. . Howeverarcinoma . Furtherarcinoma . The exparcinoma . More inarcinoma , 42. Thearcinoma . In otheCDK1 may be regulated by PVT1, hsa‐miR‐145‐5p, and hsa‐miR‐30c‐5p. CDK1 is involved in multifarious biological functions that play important roles in the cell cycle and cell division of ESCC. This CDK1‐centered ceRNA network may reveal the potential molecular mechanism of CDK1 regulating the cell cycle of ESCC and provide a new target for the study of ESCC.Based on the reports mentioned above and the results of this study, we hypothesize that the expression of However, this study also has a few limitations. In other words, these results require further experimental verification, and further verification of the expression pattern of CDK1 through single‐cell sequencing is necessary.CDK1) triple regulatory network. The relationship among these RNAs may provide a few key clues for the molecular mechanism of ESCC in the future.To summarize, a comprehensive analysis of the clinical significance of CDK1 expression confirmed that there was an increase in the CDK1 expression in ESCC than that in noncancer cells. In addition, we also constructed a novel lncRNA‐miRNA‐mRNA ceRNA  from Pantomics, Inc , from January 2015 to December 2018, which included 151 ESCC tissues and 138 normal esophageal tissues, from 156 men and 18 women. All samples were formalin fixed and undergone chemical/heat dehydration and paraffin‐embedding. The staining intensity and percentage of positive cancer cells in all slides were scored according to the semi‐quantitative scoring system, which was independently performed by two experienced pathologists in the absence of clinical information. The score was calculated according to the staining intensity and the percentage of positive tumor cells. The scores were as follows: A, staining intensity: 0 (no staining), 1 (light staining), 2 (moderate staining), 3 (strong staining); B, the percentage of positive cells: 0 (< 5%), 1 (5%–25%), 2 (26%–50%), 3 (51%–75%), 4 (76%–100%). The total score of immunohistochemical staining = staining intensity × percentage of positive tumor cells. Our research has been approved by the Committee of the First Affiliated Hospital of Guangxi Medical University. All patients signed a written informed consent form for the use of their samples for research. The research method complies with the standards set by the ‘Declaration of Helsinki’.ESCC tissues and adjacent normal esophageal tissues from eight patients, six women, and two men, with ESCC who received treatment at the First Affiliated Hospital of Guangxi Medical University  were collected, from April to August 2019. None of the patients had undergone preoperative chemotherapy or radiotherapy. The tissue samples were stored at −80 °C immediately after resection. Before the sequencing experiment, all the tissues were evaluated under the microscope in HE slices, and only the tissues with more than 80% ESCC tumor cells could be included. The specific methods and reagents for RNA‐seq have been described in detail by our team in previous articles . In the The TCGA database is a large cohort platform that contains over 30 human tumors. The Genotype‐Tissue Expression database (GTEx) collects the RNA‐seq data of normal tissues. The external RNA‐seq data of esophageal cancer and control group were downloaded from the TCGA database and GTEx database. The data of ESCC were subsequently extracted separately for this study. A combination of the two databases not only yields the RNA‐seq data of ESCC and control group in the TCGA database, but also obtains the RNA‐seq data of normal esophageal tissue in the GTEx database, which expands the data information of RNA‐seq. In addition, we searched the GEO database and ArrayExpress database with the following keywords: “esophagus” or “esophageal” and “carcinoma” or “tumor” or “cancer” or “neoplas”* or “maliganan”*. The inclusion criteria were as follows: (a) the CDK1 expression profiles in ESCC and non‐ESCC controls tissues could be achieved, and (b) more than three tumors and controls were enrolled in the study.The outline of this paper is depicted in Fig. spss 22.0  was used to calculate the number of samples (N), mean (M), standard deviation (SD) of ESCC and control group in each data set. Then, the difference in the expression level of CDK1 in ESCC and the control group was compared by Student's t test. The scatter plot / boxplot and receiver operating characteristic curve (ROC) were drawn using graphpad prism 8.0  to visualize the differences between the two groups. In addition, the standardized mean difference (SMD) forest plot was drawn using meta 4.15‐1 package of R3.6.3. SMD > 0, and P < 0.05 was considered as up expression; on the contrary, SMD < 0 and P < 0.05 was considered as down expression. To further evaluate the discriminating ability of CDK1 in ESCC and the control group, Metadisc 1.4  was used to draw the sROC curve and measure sensitivity, specificity, negative and positive likelihood ratio, and the diagnostic ODS ratio. Finally, the publication bias was detected using the funnel plot and the Egger’s and Begg’s tests. All statistical analyses were based on P < 0.05.After log2(x + 1) conversion of the expression spectrum data by Excel 2016, CDK1,” and the mRNA expression profile data of ESCC cell lines were downloaded. Subsequently, the scatter plot of CDK1 expression in different ESCC cell lines was constructed by Excel 2016.We searched the Cancer Cell Line Encyclopedia (CCLE) database for the keyword “limma 3.42.2 package. Subsequently, the Limma 3.42.2  package was used to process microarray data, and edger 3.28.1 (Bioconductor) package was used for RNA‐seq data. The screening criteria of differentially expressed gene was P < 0.05 and |logFC| > 1. The CEGs of CDK1 were screened according to the Pearson correlation coefficient using the R 3.6.3. When the correlation Pearson R > 0.5 and P < 0.05, it was considered as a co‐expressed gene. In addition, RobustRankAggreg (RRA) combined with artificial ranking was used to further screen the main CEGs associated CDK1. Then, VENNY2.1.0  was used to intersect the CEGs and DEGs and draw a Venn diagram.The annotation document of the corresponding platform was used to annotate the gene expression profile. If a gene corresponds to multiple probes, we took its average value as its gene expression value. The raw data were first standardized using the log2(x + 1) method and then normalized using the clusterprofiler 3.14.3 package (Bioconductor). A PPI network was constructed using STRING website and cytoscape 3.7.1 . Then, the MCODE algorithm was used to determine the hub genes in the neighborhood of protein dense connection.In order to investigate the molecular mechanism of CDK1 in ESCC, GO annotations and KEGG pathway enrichment of CDK1 CEGs and DEGs were analyzed using the CDK1 were predicted on the miRwalk 2.0, and these miRNAs were intersected with down‐regulated miRNAs in VENNY2.1.0 to obtain overlapping miRNAs of both. Then, the SMD of these overlapping miRNAs was calculated, and the low‐expression miRNAs with SMD < 0 and P < 0.05 were selected. The low‐expression miRNAs were input into the miRNet 2.0 database to predict the upstream lncRNAs. Similarly, the upstream lncRNAs were overlapped with the up‐regulated lncRNAs from the microarray and RNA‐seq data. Then, the SMD of these overlapping lncRNAs were calculated. Finally, lncRNAs with SMD > 0 and P < 0.05 were collected as highly expressed lncRNAs. The above miRNAs, lncRNAs, and CDK1 were input into the cytoscape 3.7.1 software to obtain the lncRNA‐miRNA‐CDK1 ceRNA network.The miRNAs upstream of The authors declare no conflict of interest.HJZ conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft. GC, SWC, and ZWF conceived and designed the experiments, performed the experiments, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft. HFZ, ZBF, JXM, CBL, and JL conceived and designed the experiments, authored or reviewed drafts of the paper, and approved the final draft.Fig S1. The flow chart of this study. Note: DEGs, differentially expressed genes; CEGs, co‐expressed genes; GO, gene ontology; KEGG, Kyoto Encyclopedia of genes and genomes; PPI, protein interaction network; ceRNA, endogenous competitive RNA network.Click here for additional data file.Fig S2. Graphical representation of data collection process in this study. Note: GEO, Gene Expression Omnibus database; DEGs, differentially expressed genes; TCGA, The Cancer Genome Atlas Program; GTEx, The Genotype‐Tissue Expression.Click here for additional data file.Table S1. Relationship between CDK1 protein expression and clinicopathological factors in ESCC patients based on in‐house IHC.Click here for additional data file.Table S2. Relationship between CDK1 expression and clinicopathological parameters in ESCC based on external RNA‐seq data.Click here for additional data file.Table S3. The DEGs of the in‐house RNA‐seq.Click here for additional data file.Appendix S1. RScript for CEGs.Click here for additional data file.Appendix S2. RScript for DEG of microarray.Click here for additional data file.Appendix S3. RScript for DEG of RNA‐seq.Click here for additional data file.


CDAHFD with insufficient methionine induced insulin sensitivity and enhanced NASH pathology, but without obesity. In contrast, CDAHFD with sufficient methionine induced steatosis, and unlike CDAHFD with insufficient methionine, also induced obesity and insulin resistance. Gene profile analysis revealed that the disease severity in CDAHFD may partially be due to upregulation of the Rho family GTPases pathway and mitochondrial and nuclear receptor signal dysfunction. The signaling factors/pathways detected in this study may assist in future study of NASH regulation, especially its ‘nonobese’ subtype.Nonalcoholic steatohepatitis (NASH) is often associated with obesity, but some patients develop NASH without obesity. The physiological processes by which nonobese patients develop NASH and cirrhosis have not yet been determined. Here, we analyzed the effects of dietary methionine content on NASH induced in mice fed on a choline‐deficient, methionine‐lowered,  l‐amino acid‐defined high‐fat diet, but without obesity. The upregulation of the Rho family GTPases pathway, and mitochondrial and nuclear receptor signal dysfunction may be involved. The signaling factors/pathways detected in this study may assist in future study of NASH regulation, especially its ‘nonobese’ subtype.Dietary insufficiency of methionine induced nonalcoholic steatohepatitis (NASH) in mice fed on a choline‐deficient,  CCR‐2C‐C motif chemokine receptor 2CDAHFDl‐amino acid‐defined high‐fat dietcholine‐deficient, methionine‐lowered, GTTsglucose tolerance testsITTsinsulin tolerance testsNAFLnonalcoholic fatty liverNAFLDnonalcoholic fatty liver diseaseNASHnonalcoholic steatohepatitisPCAprincipal component analysisPPARperoxisome proliferator‐activated receptorTNF‐αtumor necrosis factor‐αVLDLvery low‐density lipoproteinNonalcoholic fatty liver disease (NAFLD), a common and chronic liver condition, affects numerous individuals worldwide. NAFLD is considered a hepatic manifestation of metabolic syndrome, which constellates metabolic abnormalities, such as obesity, dyslipidemia, and insulin resistance . Hepatic−2) . This diet induces NASH in mice [Whereas mice were mainly resistant to CDAA , Matsumo in mice , but itsThis study was conducted to analyze the role of dietary methionine content in the development of NASH in mice fed with CDAHFD. The results indicate that CDAHFD with insufficient methionine induces NASH without being obese (nonobese subtype), while CDAHFD with sufficient methionine only induces NAFL despite promoting obesity. We then searched for important signal pathways in the ‘nonobese’ NASH subtype by gene profile analysis using the mice liver samples.The control diet of CE‐2 was composed of 58% carbohydrate, 13% fat, and 29% protein on a caloric basis, 0.21% choline, and 0.44% methionine and were obtained from CLEA Japan Inc. . The experimental diets of CDAHFD‐0.1  and CDAHFD‐0.6  were obtained from the Research Diet Inc. . The dietary components of the experimental diets are shown in Table n = 5–6) or 26 (n = 10–11) weeks. The study design is shown in Fig. Five‐week‐old male C57BL/6J mice were purchased from Japan SLC  and acclimated for a week before the study. The mice were kept under temperature‐controlled conditions (22°C on average) in colony cages with a 12‐h light/12‐h dark cycle and given free access to food and water during the acclimation and experimental periods. At 6 weeks of age, the mice were randomly assigned to the three groups  for either 13  for CK8/18. All sections were counterstained using hematoxylin and histopathologically examined in an unaware manner. The findings were graded as normal (−), minimal (1+), moderate (2+), and severe (3+) and were assigned scores of 1, 2, 3, and 4, respectively. The numbers of CK8/18‐positive putative hepatocellular preneoplastic lesions consisting of 1, 2, 3, or more cells were counted per 10 light microscopy fields (×200).Liver samples were fixed in 10% neutrally buffered formalin, embedded in paraffin, and cut into 4‐µm‐thick sections for hematoxylin–eosin (H&E) and Sirius Red staining. Histopathological diagnosis of liver lesions was conducted by a scientist unaware of the treatment of the mice and according to the INHAND criteria . Using SPlasma was obtained from the blood samples to measure triglyceride (TG) and total cholesterol (TC) levels, and aspartate (AST) and alanine (ALT) aminotransferase activities using either an automatic analyzer  or colorimetry test kits purchased from Wako Pure Chemical Industries . Hepatic TG and TC levels were measured as previously described .−1 body weight for GTTs. For ITTs, insulin  was injected intraperitoneally at a single dose of 0.35 U·kg−1 body weight. The glucose values in the blood obtained from the tail vein were measured using a glucometer system Accu‐Chek ® Aviva  at 0, 15, 30, 60, and 120 min after the administration of glucose or insulin. Additionally, serum was prepared from the blood collected from the tail vein, and the insulin values were measured using commercial insulin ELISA kits .At 8 and 25 weeks, glucose tolerance tests (GTTs) and insulin tolerance tests (ITTs) were conducted. Following overnight fasting, glucose was administered by gavage at a single dose of 1.5 g·kgn = 3–4) were used for the library preparation. Sequencing libraries were generated using TruSeq RNA Library Preparation Kit v2 . The principal component analysis (PCA), differential expression analysis, generation of heat maps with hierarchical clustering of samples, and features and functional annotation analyses using Ingenuity Pathway Analysis (IPA) software  were conducted as previously described [Total RNA was extracted from the liver using a Sepasol reagent  and was reverse‐transcribed using PrimeScript RT Master Kit , according to the manufacturers’ instructions. Afterward, quantitative real‐time PCR (qPCR) was conducted using a SYBR Premix Ex Taq  and specific primer sets with a Thermal Cycler Dice Real‐Time System Single . The primer sequences for qPCR in this study are shown in Table escribed .P < 0.05.Numerical values were expressed as means ± standard deviations (SDs). One‐way analysis of variance (ANOVA) followed by the Tukey–Kramer multiple comparisons test was used to assess differences among groups. Differences were considered significant if All animal husbandry and experiments were conducted in compliance with the guiding principle of the Tokyo University of Agriculture and approved by the Animal Experiment Committee of the University. Consequently, this study complied with all related domestic and international laws, regulations, and guidelines. Particularly, animal experiments conducted in this study complied with the ARRIVE guidelines and were conducted according to the U.K. Animals (Scientific Procedures) Act 1986 and associated guidelines, EU Directive 2010/63/EU for animal experiments, and the National Institutes of Health guide for the care and use of laboratory animals . This study used only male mice because our previous studies have clearly demonstrated that female animals are resistant to CDAA [In the CDAHFD‐0.1 group, body weight decreased compared with the control group but recovered to baseline at week 26 Fig. . HoweverThe representative microscopic features of nonproliferative liver lesions and their grading scores are shown in Fig. The mRNA expressions reflected the morphological features. The expression of inflammation‐related markers, such as tumor necrosis factor‐α (TNF‐α), C‐C motif chemokine receptor 2 (CCR‐2), and the cluster of differentiation 68 (CD68), was strongly upregulated by CDAHFD‐0.1 but not CDAHFD‐0.6 Fig. . The expAt the end of week 26 in the CDAHFD‐0.1 group, fibrosis progressed Fig. A, while −1 of insulin, had to be discontinued because of a marked decrease in blood glucose levels (data not shown). As a result, the ITT test was conducted by administering a lower dose of 0.35 U·kg−1 in this second trial, which also showed decreased blood glucose in the CDAHFD‐0.1, as compared to the control group. In contrast, the glucose level was consistently elevated in the CDAHFD‐0.6 group compared with the control group  > ±1.5. The Venn diagram of these genes is shown in Fig. RNA‐Seq was conducted using liver samples obtained at the end of week 13. PCA was conducted to identify outlier samples for quality control and determine the primary causes of variation in the dataset Fig. . The CDAThis study assessed the effects of dietary methionine content on inducing NASH in mice fed with CDAHFD and to investigate important signaling pathways in the ‘nonobese’ subtype of NASH. The CDAHFD‐0.1 group with insufficient methionine content increased insulin sensitivity and induced severe ‘nonobese’ NASH characterized by inflammation, fibrosis, and the development of proliferative lesions in the liver. In contrast, the CDAHFD‐0.6 group with sufficient methionine content only developed NAFL with little to no inflammation or fibrosis despite inducing obesity and insulin resistance. This indicated that dietary methionine content may play a critical role in the manifestation of obesity and NASH in mice. Insulin resistance and obesity may not necessarily be essential as previously thought for developing NASH. Additionally, the livers of the CDAHFD‐0.1 group showed upregulation of Rho GTPases signaling, reduction in oxidative phosphorylation, and a defect in nuclear receptor signaling. It is suggested that these changes may be involved in the development of ‘nonobese’ NASH subtype.Phosphatidylcholine (PC), derived from choline, plays a vital role in the hepatic secretion of very low‐density lipoprotein (VLDL), which is rich in hydrophobic triglycerides . Impaire−/− mice had less inflammatory cell infiltration and hepatic fibrosis, suggesting that hepatic recruitment of macrophages promotes NASH through CCR‐2 [In this study, CDAHFD‐0.1 showed morphological changes in Kupffer cells and increased infiltrating macrophages. A previous study showed that infiltrated macrophages expressed CD68, CCR‐2, and Ly6c and that CCR‐2gh CCR‐2 . Additiogh CCR‐2 , 22. BecIn this study, the CDAHFD‐0.1 showed enhanced peripheral insulin sensitivity features, as indicated by lowered ITT and OGTT glucose excursion curves. A disadvantage in the MCD diet is the induction of hypophagia and hypercatabolism, resulting in significant body weight loss with a proportional loss of liver mass . This suRNA‐Seq revealed that the gene expression profile of the CDAHFD‐0.1 group was remarkably altered from those of the control and CDAHFD‐0.6 groups. Sequencing also revealed that there were minimal changes between the control and CDAHFD‐0.6 groups. As a result of canonical pathway analysis using genes with specific changes in the CDAHFD‐0.1 group, genes related to the Rho family GTPases were upregulated. GTPases of the Rho family are molecular switches that convert and amplify external signals into cellular effects, and the protein family members are divided into Rac, cdc42, Rho, and other subfamilies , 33. AddIn contrast, CDAHFD‐0.1 indicated a decrease in mitochondrial function and lipid metabolism‐related factors. In human NASH, mitochondrial dysfunction in the liver leads to reduced adenosine triphosphate (ATP)  and incrThis study also identified the downregulation of the signaling pathway involved in PPAR and liver X receptors (LXRs)/RXR activation in the CDAHFD‐0.1 group. The ligand‐activated transcription factors belonging to the PPAR family are involved in energy homeostasis and, therefore, are expected to be attractive targets for obesity, obesity‐induced inflammation, and metabolic syndrome. PPARs also have anti‐inflammatory properties via the interference of the proinflammatory transcription factors and gene expressions , 46, 47.de novo lipogenesis, and gluconeogenesis [PPARs are involved in mitochondrial metabolism, such as fatty acid oxidation, circadian control, ogenesis . Studiesogenesis , 61, andogenesis . CollectWhile CDAHFD‐0.1 mice exhibit histological hallmarks of NASH and hypercholesterolemia, the model lacks essential clinical and metabolic features in normal‐weight/BMI NASH patients, often characterized using elevated fasting blood glucose, higher rate of diabetes, and hypertriglyceridemia. However, CDAHFD‐0.1 mice are advantageous for addressing molecular features associated with NASH pathogenesis and evaluating intrahepatic effects of treatment interventions preventing the progression of NASH and development of hepatocellular carcinoma. Some of the results have already been reported in NASH in humans, as described above. Therefore, we believe that the currently revealed signal changes are helpful in elucidating mechanisms underlying human nonobese NASH with inflammation, fibrosis, and neoplastic lesions.In conclusion, dietary methionine content plays a vital role in developing obesity and NASH in mice fed with CDAHFD. Additionally, the severity of the disease in CDAHFD with insufficient methionine may partially be due to the upregulated Rho family GTPases pathway, suggesting the relevance of mitochondrial and nuclear receptor signal dysfunction. The signaling factors/pathways detected in this study may provide fundamental information serving as novel molecular targets to control NASH, especially in its ‘nonobese’ subtype.The authors declare no conflict of interest.NK designed the study. NK, AA, KU, SN, and MY acquired the data. NK, SO, AW, RS, and KM analyzed and interpreted the data. NK and DN wrote the manuscript. All authors agreed to submit the manuscript.Fig S1. Schematic overview of the experimental design. After 1 week of acclimation, mice were divided into 3 groups and fed with the control chow, CDAHFD‐0.1, and CDAHFD‐0.6 for 13 or 26 weeks. The liver samples from the 13‐week study were used for the RNA‐Seq. analysis.Click here for additional data file.Fig S2. Representative histopathology and mRNA expression levels in the liver at the end of week 26. Representative features for Sirius Red (A), and qPCR of genes involved in inflammation (B), oxidative stress (C) and fibrosis (D) in the livers of mice fed the control chow (n = 10), CDAHFD‐0.1 (n = 11) or CDAHFD‐0.6 (n = 10) for 26 weeks. The lengths of the scale bars are 100 µm. The values are presented as the means + SDs. Difference between the means was statistically determined significant when P < 0.05, using one‐way ANOVA followed by the Tukey–Kramer multiple comparisons test. *Significantly different from the control group value. +Significantly different from the CDAHFD‐0.1 group value.Click here for additional data file.Fig S3. Evaluation of insulin sensitivity. Blood glucose levels in ITT test at the end of week 8 on the control (n = 4), CDAHFD‐0.1 (n = 4) and CDAHFD‐0.6 (n = 4) groups. The values are presented as the means + SDs. Difference between the means was statistically determined significant when P < 0.05, using one‐way ANOVA followed by the Tukey–Kramer multiple comparisons test. *Significantly different from the control group value.Click here for additional data file.Fig S4. Representative proliferative changes of the liver at the end of week 13. The immunohistochemistry of PCNA (A) and CK8/18 (B). Arrows indicating positive cells. The values are presented as the means + SDs on the control (n = 5), CDAHFD‐0.1 (n = 5) and CDAHFD‐0.6 (n = 6) groups. Difference between the means was statistically determined significant when P < 0.05, using one‐way ANOVA followed by the Tukey–Kramer multiple comparisons test. *Significantly different from the control group value. +Significantly different from the CDAHFD‐0.1 group value.Click here for additional data file.Table S1. Compositions of experimental diets used in this study.Table S2. Sequence information of primers for the qPCR analyses.Click here for additional data file.Table S3. CDAHFD‐0.6 versus CDAHFD‐0.1: Canonical pathway analysis of differentially expressed genes by IPA; and CDAHFD‐0.6 versus CDAHFD‐0.1: Canonical pathway analysis of differentially expressed genes by IPA.Click here for additional data file.Table S4. Gene expression in livers of the control, CDAHFD‐0.1 and CDAHFD‐0.6 groups at the end of week 13. The following expression data are shown per sample. (1) Total counts, (2) Reads Per Kilobase of transcript per Million mapped reads (RPKM), (3) Transcripts Per Million (TPM) and (4) Counts Per Million (CPM).Click here for additional data file.