Single Nucleotide Polymorphism (SNP) panels recently developed for the assessment of genetic diversity in wheat are primarily based on elite varieties, mostly those of bread wheat. The usefulness of such SNP panels for studying wheat evolution and domestication has not yet been fully explored and ascertainment bias issues can potentially affect their applicability when studying landraces and tetraploid ancestors of bread wheat. We here evaluate whether population structure and evolutionary history can be assessed in tetraploid landrace wheats using SNP markers previously developed for the analysis of elite cultivars of hexaploid wheat.We genotyped more than 100 tetraploid wheat landraces and wild emmer wheat accessions, some of which had previously been screened with SSR markers, for an existing SNP panel and obtained publically available genotypes for the same SNPs for hexaploid wheat varieties and landraces. Results showed that quantification of genetic diversity can be affected by ascertainment bias but that the effects of ascertainment bias can at least partly be alleviated by merging SNPs to haplotypes. Analyses of population structure and genetic differentiation show strong subdivision between the tetraploid wheat subspecies, except for durum and rivet that are not separable. A more detailed population structure of durum landraces could be obtained than with SSR markers. The results also suggest an emmer, rather than durum, ancestry of bread wheat and with gene flow from wild emmer.SNP markers developed for elite cultivars show great potential for inferring population structure and can address evolutionary questions in landrace wheat. Issues of marker genome specificity and mapping need, however, to be addressed. Ascertainment bias does not seem to interfere with the ability of a SNP marker system developed for elite bread wheat accessions to detect population structure in other types of wheat. Triticum aestivum ssp. aestivum) is, together with rice and maize, one of the main staple food crops of the world; in 2012 some 675 million tones were produced worldwide [Bread wheat , arose as an allotetraploid 300,000–500,000 years ago [de novo domestication of durum from wild emmer has not yet been ruled out [Aegilops tauschii[The progenitor species of all domesticated wheat, wild emmer , the most widely grown tetraploid wheat, is cultivated to a far lesser extent than hexaploid bread wheat. The cultivation of other domesticated tetraploid wheats, such as emmer (T. turgidum ssp. dicoccum) and rivet (T. turgidum ssp. turgidum), is very limited. These relict crops have little agricultural importance, which has also lead to them being studied to a lesser extent than bread wheat. However, some SSR [Durum wheat  and two rivet landraces  were genotyped with 5386 SNPs in a panel developed by Allen et al. . DNA wasOf the SNPs assayed, 444 SNPs produced clear calls in at least five of the six accessions and were chosen for further analysis  were estimated according to Nei [ST, significance values were determined by permutation tests (1000 permutations). Principal component analysis (PCA) was carried out with R software  using the prcomp command. In the PCA, data was analysed on an accession level where the number of copies of each allele at each locus were treated as independent variables.Genetic diversity  and Wright’s Fg to Nei  using pug to Nei . For theK = 1) to 20 (K = 20) clusters were used to test different datasets, using 50,000 MCMCs and 20,000 burn-in runs with the “admixture” model. Ten replicate runs were performed for each value of K. The best-fit model was determined by calculating ΔK[K < 4, whereas the Greedy algorithm was used for K = 4 to K = 6 and the LargeKGreedy algorithm for higher Ks. We also evaluated the “no admixture” model using the same settings. CLUMPP was further used to compare the output of Structure analysis of durum SNP and SSR data. Graphical representation of results of CLUMPP runs was obtained using the DISTRUCT software v 1.1 [Publicly available wheat SNP data for both tetraploid and hexaploid accessions , was addlating ΔK and fromlating ΔK. In CLUMre v 1.1 . We alsore v 1.1   was used to fit a non-linear regression line to the LD between pairs of linked SNPs in order to explore the decay of LD over distance.Linkage disequilibrium (LD), measured as D’ and retic map ) map disThe full SNP panel developed by the Functional Genomics Group at the University of Bristol and collaborators  was assaSince these results were generated, many of the SNPs in the Allen et al.  panel haOf the 5386 SNPs assayed in the six test individuals, 444 were chosen for further genotyping. These were genotyped in an additional 99 tetraploid wheats creating a dataset consisting of 105 tetraploid wheats . Of the 444 SNPs assayed seven were later revealed to map to the D genome and were subsequently removed from further analyses . This could be due to either variation among individuals within an accession , heterozygous individuals or a combination of the two. Among the different wheat types, durum and rivet exhibited more heterozygous loci (6.4 and 5.7% respectively) than landrace emmer and wild emmer (3.4 and 1.2% respectively)  was still only 50.2% of that of the 369 SNPs used for the extended set of accessions.It has been suggested that the effects of ascertainment bias can be alleviated by combining SNPs into haplotypes . To inve2. As both measures gave similar results only the latter is reported below. For pairs of unlinked loci (only pairs of loci on different chromosomes were used) the r2 values for most pairs showed fairly low levels of LD with a skewed tail of higher values of LD , located on different chromosomes but in complete LD was detected.LD was measured both as D’ and r2 of more than 0.4 could be detected over several tens of cM  while CLUMPP H’ values were similarly high for K = 2 to K = 4 (highest for K = 3 for the “no admixture” model). Neither the PCA nor any level of clustering showed a strong geographic structure. Instead, different accessions from the same country or region clustered together already at K = 2 in the Structure analysis  from all other accessions along the first PC  and CLUMMP H’ values (supporting K = 2 and K = 9), mainly introduced mixed ancestry to the accessions . The degree to which accessions were assigned to a Structure cluster was highly correlated at K = 2  but with marked differences for some accessions. For example, the accession CItr15519 was assigned almost completely to one group based on SNP markers, but to the opposite group based on SSRs. A PCA of the SSR data showed lower explanatory power of the two first PCs (6.0 and 4.4% for SSRs compared to 8.3 and 7.8% for SNPs).Many accessions, such as most of those included in the Italian cluster described above, clearly demonstrated similar clustering using the two marker systems; however, this was not the case for all accessions .Seventy-one SNPs mapping to the D genome were successfully genotyped in the test panel of six tetraploid wheats, where only the A and B genomes occur. This is a cause of concern as it suggests some markers may have been incorrectly mapped or are not genome specific. To minimize the number of such markers, we excluded all markers mapping to the D genome. We also removed putative cross-amplifying markers showing within-accession heterozygosity in five genotyped improved durum varieties, since these accessions can be expected to be genetically monomorphic. High heterozygosity in SNP loci in wheat lines selfed for many generations has also been noted by Würschum et al.  as an unOur background level of LD was lower than that previously detected in bread wheat using other marker systems, but with LD between linked loci decaying on a similar scale as in previous studies of bread wheat -38 and dPopulation structure studies based on SNP data can potentially be affected by ascertainment bias when the SNP panel used has been developed for populations or species other than those analysed ,22. HübnIn this study we find strong support for independent evolutionary trajectories for tetraploid and hexaploid wheats. Structure analysis first separates hexaploid wheats from durums and rivets, with intermediate clustering of wild and landrace emmers Figure a as woulMore surprisingly, along the third PC, wild emmer assumes an intermediate location compared to bread wheats and domesticated emmer landraces, tentatively suggesting gene flow from wild emmer into the progenitor of hexaploid wheat or directly to the A and B genomes of hexaploid wheat. The location of durum along the third PC likewise suggests a role of wild emmer in the formation of the durum gene pool. Further studies directly targeted at clarifying the evolutionary origin of domesticated wheat and the role of gene flow between different types of wheat are needed.ST value between the two was the lowest of the pairwise FST values calculated . As in Oliveira et al. [Durum and rivet have traditionally been classified as different taxa, based on different ear morphology and by the latter’s broader tolerance to moist and cold environments. Neither the PCAs presented here nor the Structure analysis separate durum and rivet from each other. The Fa et al.  no genetGiven the number of markers used in this study it is unlikely that our genome-wide values of Tajima’s D are caused by selection acting on all the different markers. More likely they reflect components of population history that affect the whole genome equally, such as population subdivision or population growth for example following a bottleneck. Ascertainment bias resulting from the marker selection in this study should lead to an underrepresentation of rare alleles . As a laAlthough the Tajima’s D of landrace durum was not significantly positive, it was markedly higher than those of the other types of wheat. This, together with the somewhat higher LD found in durum wheats compared to the complete set of tetraploid wheats, suggests that a certain level of population subdivision is present in the landrace durum analysed here, possibly resulting in the observed genetic structuring. The increased number of markers allowed for the detection of higher levels of genetic structuring than those found by Oliveira et al.  . Markers that were removed before the final analysis are highlighted in red.ed from ). MarkeClick here for fileAccessions used in this study. Tetraploid landrace accessions were originally screened for this work. The remaining accessions were screened by the Crop Improvement Research Club, as described in [ribed in  and in [ribed in  and genoClick here for fileList of SNPs mapping to the D genome that successfully amplified in some or all of the tetraploid test panel accessions described in this work.Click here for fileDistribution of linkage disequilibrium values calculated between pairs of loci located on different chromosomes. a) All values of r2, b) Values of r2 from 0.2 and higher.Click here for fileLinkage disequilibrium (r2) between linked markers plotted against genetic distance with a non-linear regression line fitted to the values. a) All tetraploid wheats; b) all durum landraces.Click here for fileResults of Structure analysis of wheat accessions based on 369 SNPs using the “admixture” option (top panel) and the “ no admixture” option (bottom panel) for a) K = 2 model with the durum accessions; b) K = 4 model with durum accessions; c) K = 2 model with the complete set of accessions; d) K = 5 model with the complete set of accessions.Click here for fileResults of Structure analysis of the K = 3 model for the tetraploid wheat set.Click here for fileResults of Structure analysis of the set of durum accessions for the K = 2 model based on a) 369 SNPs and b) 29 SSRs respectively.Click here for fileResults of Principal Component Analysis of the complete set of wheat accessions. The distinctiveness of Yumai 34, Anahuac 75 and Ukrainka is evident (top left corner). Black = wild emmer; purple = landrace emmer; red = durum; orange = rivet; blue = landrace bread wheat; green = commercial bread wheat.Click here for fileResults of Structure analysis of the complete set of wheat accessions for the a) K = 8 model and b) K = 9 model.Click here for file


Parus major) as a model species. We used mark–recapture models to analyze the effect of hatching date, temperatures experienced during the nestling period, fledging size and body mass on first‐year postfledging survival probability of great tit juveniles. We used data from 5192 nestlings of first clutches ringed between 1993 and 2010. Mean first‐year postfledging survival probability was 15.2%, and it was lower for smaller individuals, as well as for those born in either very early or late broods. Our results stress the importance of choosing an optimum hatching period, and raising large chicks to increase first‐year local survival probability in the studied population.Survival of juveniles during the postfledging period can be markedly low, which may have major consequences on avian population dynamics. Knowing which factors operating during the nesting phase affect postfledging survival is crucial to understand avian breeding strategies. We aimed to obtain a robust set of predictors of postfledging local survival using the great tit ( Variation in juvenile survival has profound effects on avian population dynamics , whereas survival of juvenile brown thornbills  and lark buntings  increased as the season progressed  hatchlings might experience a reduced postfledging survival  fledglings, Monrós et al. . Based on previous studies, we predicted that (1) both relatively high and relatively low ambient temperatures experienced during vulnerable periods of nestling development will have negative effects on juvenile survival, irrespective of dates; (2) the effect of dates per se will depend on the year ; and (3) large and/or heavier fledglings would have more postfledging survival probabilities.We used data collected during a long‐term study of a great tit population breeding in nest boxes within an extensive orange monoculture in Sagunto , Eastern Spain . Wooden nest boxes were placed each year for the birds to breed, and were visited with the periodicity necessary  to record basic breeding parameters  and bias of the estimates p(t). The validity of this simple model to the data was assessed by goodness‐of‐fit tests of program RELEASE in MARK . Results of TEST 3  suggested possible age effects on survival probabilities. Given that an individual's first‐year survival is likely to differ from that of older birds, we built a model incorporating two age classes: a1  and a2 . In this model, we considered first‐year postfledging survival to be time dependent, and adult survival to be constant, as the analysis of time effects on older age classes was outside the objectives of our study. Recapture probability was considered to be time dependent. The goodness‐of‐fit of this new model, Фp(t), was tested using the parametric bootstrap approach implemented in MARK. The parameter estimates from the model were used to simulate data according to the assumptions of CJS models . This process was repeated 1000 times, and the deviance of each model was calculated to determine whether the deviance of the observed model exceeded that of simulated data. The probability of obtaining by chance a deviance value as large as or larger than the one observed was given by the ratio between the number of simulations with deviance larger than the one observed in our general model divided by the total number of simulations. We established a significance level P < 0.05 for rejecting the null hypothesis. The bootstrap goodness‐of‐fit test indicated that the model had a good fit (P = 0.74), so we selected it as our reference model, and compared it with simpler nested models, using AICc values for model selection.We created a series of general models incorporating time‐dependent effects on survival and recapture probabilities. These models were constructed using the sin link function. Our initial model considered time dependence in both survival and recapture probabilities, Ф. On the other hand, models including mass and average maximum temperature during days 10–15 received higher AICc scores than the reference model, and therefore, we considered these covariates to have no significant direct effect on first‐year postfledging survival probability. The inclusion of quadratic effects improved nonsignificantly the fit of the model in the case of maximum temperature , and did not improve model fit in the case of mass . Of the two biometrical covariates, a model including the effect of tarsus length on first‐year postfledging survival explained data 462 times better than a model including the effect of mass.To determine which of the studied covariates had a significant effect on first‐year survival probability, we created separate models including the effect of each individual covariate on first‐year postfledging survival , and consequently the model with the fewer parameters  was used to explain the effect of covariates on first‐year postfledging survival. In addition, we tested for a possible interaction between tarsus length and hatching date on first‐year survival, but the resulting model  received no convincing support, as its ∆AIC was 4.74 and the 95% confidence interval of the β‐parameter of the interaction term included zero. Moreover, as the adverse effect of high temperatures on chick fitness may be aggravated during the late nestling stage depending on their size and overall ability to dissipate heat in excess  have a significant impact on first‐year postfledging survival probability. Smaller individuals, as well as those pertaining to either too‐early or late broods would have lower survival prospects. The effect of other potential covariates affecting first‐year survival, such as fledgling mass or temperatures experienced during the nestling stage, has not received convincing support. This way, of the two possible descriptors of body condition, fledgling size has proven to be a better predictor of first‐year postfledging survival than fledgling mass, and we have been unable to show the existence of carryover effects of either maximum or minimum ambient temperatures experienced during vulnerable periods of nestling development on first‐year survival probability.The effect of hatching date on first‐year local survival was nonlinear, suggesting there being an optimal range of breeding dates leading to a maximum first‐year postfledging survival probability, and that both positive and negative deviations from this range are not beneficial.Birds have a limited period each year in which conditions for growth and reproduction are most suitable. In this sense, timing of breeding is essential, and individuals capable of adjusting their breeding schedule to match nestling development with the seasonal peak of prey availability will likely be able to raise larger fledglings of higher quality (van Noordwijk et al. The seasonal decline in breeding productivity is a common trend among avian populations Perrins . It is aOn the other hand, Greño et al.  took intJuvenile size at fledging had a positive effect on first‐year postfledging survival probability. Larger individuals may be less vulnerable to diseases, parasites and predators during their first months of life (Ragusa‐Netto The relationship between size and postfledging survival has been documented in numerous studies, although it is common to express body size in terms of fledgling mass Garnett . In our In conclusion, we highlight the importance of hatching date and body size as determinants of first‐year survival in a Mediterranean great tit population. Large fledglings hatched between April 21 and May 15 have greater first‐year postfledging survival probabilities, most likely as a result of superior fitness and competitive skills, as well as more favorable environmental conditions at fledging.None declared.


PMP) is a neoplastic syndrome characterized by peritoneal tumor implants with copious mucinous ascites. The standard of care for PMP patients is aggressive cytoreductive surgery performed in conjunction with heated intraperitoneal chemotherapy. Not all patients are candidates for these procedures and a majority of the patients will have recurrent disease. In addition to secreted mucin, inflammation and fibrosis are central to PMP pathogenesis but the molecular processes that regulate tumor‐stromal interactions within the peritoneal tumor microenvironment remain largely unknown. This knowledge is critical not only to elucidate PMP pathobiology but also to identify novel targets for therapy. Here, we report the generation of patient‐derived xenograft (PDX) mouse models for PMP and assess the ability of these models to replicate the inflammatory peritoneal microenvironment of human PMP patients. PDX mouse models of low‐ and high‐grade PMP were generated and were of a similar histopathology as human PMP. Cytokines previously shown to be elevated in human PMP were also elevated in PDX ascites. Significant differences in IL‐6 and IL‐8/KC/MIP2 were seen between human and PDX ascites. Interestingly, these cytokines were mostly secreted by mouse‐derived, tumor‐associated stromal cells rather than by human‐derived PMP tumor cells. Our data suggest that the PMP PDX mouse models are especially suited to the study of tumor‐stromal interactions that regulate the peritoneal inflammatory environment in PMP as the tumor and stromal cells in these mouse models are of human and murine origins, respectively. These mouse models are therefore, likely to be useful in vivo surrogates for testing and developing novel therapeutic treatment interventions for PMP.Pseudomyxoma peritonei ( Pseudomyxoma peritonei (PMP) is a mucinous neoplasm that is characterized by multifocal, tumor implants in the peritoneal cavity with excessive accumulation of “jelly‐like” ascites PMP is biologically heterogeneous and can range from indolent tumors with excessive production of ascites to aggressive tumors with high‐grade pathology similar to those seen in peritoneal carcinomatosis of colorectal origin. Ronnett et al. classified PMP into three categories correlating histological grade with disease severity: (1) disseminated peritoneal adenomucinosis (DPAM) consisting of peritoneal lesions with bland histology and abundant mucin, (2) peritoneal mucinous carcinomatosis (PMCA) consisting of abundant gland‐forming mucinous epithelium with cytological atypia, and 3) PMCA intermediate/discordant with predominantly bland histology but with focal areas of well‐differentiated mucinous carcinoma  PMCA intPMP can be fatal if left untreated. But treatment options for PMP patients are limited. Aggressive surgical cytoreduction in conjunction with hyperthermic intraperitoneal chemotherapy  is the only treatment option that has been showed to improve patient outcomes In our previous studies, we have measured the levels of several chemokines and cytokines in PMP patient ascites and sera Discarded tumor specimens and ascites collected from PMP patients at the time of surgery were used for this study. Collection of these samples was approved by the Creighton Institutional Review Board and all patients provided written consent for participation in research.nu) . Mice were monitored for tumor growth by assessment of increase in girth or body weight. After ~2–6 months, mice were sacrificed, dissected and intraperitoneal tumors and ascites were collected for subsequent passage. Tumors from multiple mice were pooled to reduce clonal variance and were serially passaged in nude mice by intraperitoneal injections as described above. After successful passaging for 3–5 generations, tumor samples were harvested, preserved in Roswell Park Memorial Institute (RPMI) 1640  complete medium containing 10% fetal bovine serum and penicillin/streptomycin and frozen in liquid nitrogen for future passage. At each passage, gross invasion of organs and spread of cancer beyond the diaphragm were assessed.All the mouse studies described here were approved by the Institutional Animal Care and Use Committee at Creighton University. PMP tumors removed at the time of surgery were washed in sterile phosphate‐buffered saline, finely chopped, mechanically disrupted by passing through an 18G needle several times and suspended in saline. This suspension was then injected intraperitoneally into 3–4 homozygous female nude mice (Crl:NU (NCr)‐Foxn1μm), and stained with hematoxylin and eosin.PMP tumors from PDX mice were harvested, fixed in 10% neutral‐buffered formalin, dehydrated, embedded in paraffin, sectioned . Human cytokines that were assayed using anti‐human and anti‐mouse antibodies are listed in Table Immunohistochemistry (IHC) on formalin‐fixed, paraffin‐embedded sections was performed as described previously P < 0.05 (two tailed) was considered significant. Median values with interquartile ranges have been plotted on the graphs.Cytokine and chemokine expression levels in ascites and sera from PMP patients and PDX models were compared using GraphPad Prism 5.04 . Cytokines and chemokines that were measured showed a broad range of concentrations in ascites and in sera and therefore, in order to minimize outlier effects, the median, instead of the mean, was used as a measure of central tendency. Also, as the normality of distributions could not be ascertained, we have taken a conservative approach and used the nonparametric Mann–Whitney test (which compares means of rank sums) to assess significance. A PMP PDX mouse models were generated by intraperitoneal injections of human PMP tumor samples resected at the time of surgery Table . Thirteeα were significantly elevated in PMP patient ascites P < 0.05) between PMP human and PDX mouse ascites  suggesting that the cytokines that show increased expression in PDX ascites are restricted to the peritoneal tumor microenvironment. In addition, no significant elevation in the levels of the chemokines was seen in the sera of PDX models compared to ungrafted mice (data not shown) suggesting that none of the measured chemokines/cytokines could be used as a biomarker to track PMP tumor growth in these mouse models. C‐reactive protein (CRP), a biomarker commonly used in clinical practice to monitor disease progression, was also measured. As CRP is made by the liver, and is therefore, expected to be of murine origin in PDX mouse models, an anti‐mouse CRP antibody was used. CRP levels in PDX serum samples were not significantly different from endogenous CRP levels in mouse sera (data not shown). These results preclude the use of CRP as a biomarker to monitor PMP growth in PDX models.Previous reports of generation of PDX mouse models of PMP described the close histopathological similarities between human PMP and PDX PMP Mesothelial cells on the serosal surface of organs generate fluid that lubricates the movement of visceral organs against the peritoneal surface. This fluid is generally cleared through lymphatic drainage. In cancers that show a propensity to disseminate to the peritoneal cavity such as ovarian cancers and PMP, there is increased accumulation of peritoneal fluid (ascites) α are seen in PDX mouse models as in human ascites. Our results suggest that these cytokines are not only produced by human‐derived PMP tumor cells, but also by mouse‐derived stromal cells.In a recently published study, we reported the expression of a number of chemokines and cytokines in the ascites and sera from PMP patients. The resultant profile of the inflammatory peritoneal tumor microenvironment in PMP turned out to be distinct from that associated with pathogens (pathogen‐associated molecular pattern) or injury (danger‐associated molecular pattern) Although many of the cytokines were elevated in ascites, none of them showed significant elevation in sera of PMP PDX mouse models. These results are consistent with what was seen in human PMP patients; all the cytokines/chemokines that were assessed showed significant enrichment in patient ascites but not in sera. These results, considered together, suggest that the peritoneal tumor microenvironment in PMP is partitioned from systemic circulation. The reasons for, or the nature of, this partition  is not clear. PMP tumors are derived from mucin‐producing goblet cells of the appendix and the mucin to cell ratio can be as high as 1000 to 1 A number of different stromal cell types have been identified and shown to alter tumor hallmark capabilities such as sustained proliferation, and initiation of angiogenesis, invasion and metastasis and evasion of (1) growth suppressors, (2) immune surveillance, (3) replicative senescence, and (4) cell death β, TNFα, and MIP1α detected using antibodies raised against these human antigens. The fact that the fold differences in median levels of all these cytokines/chemokines were reduced when mouse antibodies were used support the notion that these cytokines were mostly produced by murine tumor‐associated stromal cells.The human tumors that were implanted in the peritoneal cavities of mice are expected to contain tumor‐associated stromal components. Therefore, it is possible that some of these stromal cells of human origin may have contributed to the elevation of cytokines such as IL6, IL8 and GRO. This remains unlikely due to two reasons. First, tumor‐associated stromal cells are not expected to survive the serial passaging procedures that we have adopted as these cells are not transformed or immortalized as the tumor cells. Second, in the unlikely event of the survival of human stromal cells, the cytokines secreted by these cells would have cross‐reacted with human antibodies. If so, this would be at odds with the large difference in median values between PDX‐ and human PMP‐derived IL6, IP10, IL8, IL10, MCP1, MIP1β have all been shown to perform autocrine and paracrine functions and regulate tumor–stromal cross talk. Colon cancer cells can stimulate macrophages to secrete IL6 which in turn, activates the IL6 receptor and STAT3 in tumor cells The cytokines that show elevated expression in human PMP and PDX ascites such as IL6, IP10, IL8, IL10, MCP‐1, and MIP‐1Future studies will focus on defining the identities of stromal cell types in the peritoneal microenvironment and the relative contributions of these cell types to PMP pathobiology. Coculture studies of stromal components and PMP cell lines that we have generated in our laboratory  will be useful in these investigations. In addition, the PMP PDX models will be excellent preclinical tools for testing the efficacy of anticancer agents and developing novel treatment interventions for PMP.None declared.


Dear EditorWe have recently read with great interest the article published in your most valuable journal entitled “Hepatitis C virus infection rate among seronegative hemodialysis patients screened by two methods: HCV core antigen and polymerase chain reaction” by Moini et al. . This stWe agree that patients on long-term HD are at higher risk of acquiring HCV infection , 3. DespWe totally concur with the authors that HCV core Ag may be an accurate marker for early detection and virological monitoring of HCV infection in patients on HD. Owing to the low cost and its technical easiness, this assay can be employed for routine screening of patients on HD; however, more studies with larger sample size are still required to effectively establish HCV core Ag test as a preferred assay for the early diagnosis of HCV infection in patients on HD.


MSCs). Unlike differentiated melanocytes, undifferentiated MSCs do not produce melanin. They serve as a source of differentiated melanocytes for the hair follicle and contribute to the interfollicular epidermis upon wounding, exposure to ultraviolet irradiation or in remission from vitiligo, where repigmentation often spreads outwards from the hair follicles. It is unknown whether these observations reflect the normal homoeostatic mechanism of melanocyte renewal or whether unperturbed interfollicular epidermis can maintain a melanocyte population that is independent of the skin's appendages. Here, we show that mouse tail skin lacking appendages does maintain a stable melanocyte number, including a low frequency of amelanotic melanocytes, into adult life. Furthermore, we show that actively cycling differentiated melanocytes are present in postnatal skin, indicating that amelanotic melanocytes are not uniquely relied on for melanocyte homoeostasis.Hair follicles and sweat glands are recognized as reservoirs of melanocyte stem cells ( The ability of interfollicular epidermis to carry a resident melanocyte population independently of the hair follicles indicates that cutaneous melanocyte populations are maintained by distinct mechanisms. This potential heterogeneity should be taken into account in research efforts to stimulate repigmentation and in addressing the origins and behaviours of melanomas.During embryonic development, hair follicles are colonized by melanoblasts, the precursors of differentiated, pigment‐producing melanocytes. In the adult, hair follicles lose differentiated melanocytes at the end of each hair cycle and maintain quiescent, non‐pigment‐producing melanocytes in a region known as the bulge. These stem cells give rise to progeny which repopulate the hair bulb with active melanin‐producing melanocytes during each hair cycle. The stem cells can also be stimulated by wound healing, ultraviolet irradiation or ectopic expression of the survival factor Kit‐ligand to migrate to the interfollicular epidermis where they differentiate and transfer pigment to their surrounding keratinocytes , which lack development of hair follicles on the tail . In the absence of hair follicles, melanin production and transfer to keratinocytes occur as in wild type, where it is restricted to the scale plates and not the interscale hinges  to green (EGFP) in cells which have undergone Cre‐mediated recombination  skin of approximately 1.5% of the total melanocyte population (Figure We quantified the frequency of amelanotic melanocytes in the epidermis, finding similar values in haired and hairless (wild type and n Figure C,D. In tn Figure , while in Figure . HoweverTyr::Cre mice with R26Fucci2aR animals containing a Cre‐inducible bicistronic Fucci2a reporter to identify cell cycle stage in melanocytes (Mort et al., Tyr::Cre; R26Fucci2aR skin at postnatal day 19. We found that cells displaying green fluorescence at the start of the culture went on to divide over the following hours (Figure in vivo. Imaging revealed that proliferating melanocytes contained pigment throughout the process of cell division, indicating that the amelanotic melanocytes that we detect are not simply at a different cell cycle phase than their neighbours but rather likely represent a stable population.To further investigate melanocyte homoeostasis, we crossed s Figure  and as is Figure , that acEmbryonic skin is initially colonized by melanoblasts derived from the neural crest. A subset of these cells goes on to enter the developing hair follicles where they both pigment the first hair growth and form the stem cell population that will replenish the pigment‐producing melanocytes in subsequent hair cycles. In human skin, and some regions of mouse skin, interfollicular epidermal melanocytes also persist and pigment the surrounding keratinocytes. This study addresses whether hair follicles are an essential source of interfollicular melanocytes as the skin grows postnatally and into adulthood, and finds that they are not. We also observe that melanin‐producing melanocytes of the interfollicular epidermis are capable of proliferation in the postnatal period. In addition, we have identified an amelanotic population of melanocytes in the interfollicular epidermis distinct from the melanocyte stem cells of the hair follicle and sweat glands. These amelanotic melanocytes may serve as a reserve that is used for repopulation upon large‐scale melanocyte loss, analogous to the putative population identified in the interfollicular epidermis of both vitiliginous and healthy skin in humans (Seleit et al., Video S1. Live imaging of cell cycle progression in differentiated melanocytes.Click here for additional data file.


Hum Brain Mapp 36:1755–1771, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.Blood oxygenation level‐dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) is a widely used technique to map brain function, and to monitor its recovery after stroke. Since stroke has a vascular etiology, the neurovascular coupling between cerebral blood flow and neural activity may be altered, resulting in uncertainties when interpreting longitudinal BOLD signal changes. The purpose of this study was to demonstrate the feasibility of using a recently validated breath‐hold task in patients with stroke, both to assess group level changes in cerebrovascular reactivity (CVR) and to determine if alterations in regional CVR over time will adversely affect interpretation of task‐related BOLD signal changes. Three methods of analyzing the breath‐hold data were evaluated. The CVR measures were compared over healthy tissue, infarcted tissue and the peri‐infarct tissue, both sub‐acutely (∼2 weeks) and chronically (∼4 months). In this cohort, a lack of CVR differences in healthy tissue between the patients and controls indicates that any group level BOLD signal change observed in these regions over time is unlikely to be related to vascular alterations. CVR was reduced in the peri‐infarct tissue but remained unchanged over time. Therefore, although a lack of activation in this region compared with the controls may be confounded by a reduced CVR, longitudinal group‐level BOLD changes may be more confidently attributed to neural activity changes in this cohort. By including this breath‐hold‐based CVR assessment protocol in future studies of stroke recovery, researchers can be more assured that longitudinal changes in BOLD signal reflect true alterations in neural activity.  Over recent decades, functional magnetic resonance imaging (fMRI) has become a useful tool when studying the recovery of brain function following a stroke or other focal brain injury. Interpretations of fMRI findings should take into account the limitations of this technique, and factors that influence the fMRI‐derived blood oxygenation action level‐dependent (BOLD) signal . This can explain why less voxels passed threshold in GlobOpt analysis versus the VoxOpt analysis ; it does not account for delays between the model and a voxel's BOLD response; the model is an average over voxels that may have differing delays, and will, therefore, represent a more dispersed HRF; and finally, the CVR measures are biased towards the mask from which the regressor is derived, in this case R‐Hemi, and so may not be reliable across the entire brain.The VoxOpt and RHsig analyses were investigated further. Comparisons of the responses in healthy unaffected tissue in the PT group with responses in the HV group showed no differences  on both the stroke‐affected left hemisphere and the contralesional right hemisphere. It is possible that this represents a reduction in CVR due to the anatomical location of the masks. However, since the lesions are in largely heterogeneous locations . A lack of CVR differences in healthy tissue between patients and controls in this cohort suggests that task‐related BOLD signal changes in these regions should be unaffected by the stroke and be more representative of task‐related oxygen metabolism. In contrast, since CVR is reduced in the stroke peri‐infarct tissue, a lack of BOLD signal in that area compared with controls may not accurately reflect neural deficits. However, the CVR in the peri‐infarct tissue remains unchanged over time, suggesting that any group‐level BOLD increases in this region over time in a longitudinal fMRI study are less likely to be due to an improvement in vascular reactivity, and may be more confidently attributed to changes oxygen metabolism caused by altered neural function. This study provides a framework for stroke researchers to account for CVR‐related confounds in BOLD fMRI stroke studies. By including a similar breath‐hold protocol in longitudinal studies of stroke recovery and performing similar analyses, researchers can more confidently interpret BOLD signal changes by disentangling vascular and neural influences using this method.


NGS). No single mutation detection technique is however perfect in identifying all mutations. Therefore, we wondered to what extent inconsistencies between Sanger sequencing and NGS affect the molecular diagnosis of patients. Since mutations in SCN1A, the major gene implicated in epilepsy, are found in the majority of Dravet syndrome (DS) patients, we focused on missed SCN1A mutations.Sanger sequencing, still the standard technique for genetic testing in most diagnostic laboratories and until recently widely used in research, is gradually being complemented by next‐generation sequencing (SCN1A testing.We sent out a survey to 16 genetic centers performing SCN1A mutation‐negative, both due to technical limitations and human errors.We collected data on 28 mutations initially missed using Sanger sequencing. All patients were falsely reported as SCN1A mutations are an even more frequent cause of DS than already anticipated.We illustrate the pitfalls of Sanger sequencing and most importantly provide evidence that  SCN1A gene (OMIM: #152389) in Dravet syndrome (DS), one of the genetically most homogeneous epilepsy syndromes.When it comes to genetic screenings, Sanger sequencing has long been considered the gold standard and is still widely performed. However, next‐generation sequencing (NGS) is becoming steadily implemented nowadays, both in research and in clinical diagnostic settings. Whereas Sanger sequencing targets only one gene at a time, making it a very time and cost‐consuming method, NGS technologies can analyze a set of genes, an exome, or even a genome in a single sequencing run. This enormous advantage has led to the widespread implementation of different NGS platforms in genetic centers Sisodiya . It is wDS is among the best defined and most extensively studied entities within the epileptic encephalopathies. Clinically, the disease is characterized by a seizure onset in the first year of life, usually around six months. Seizures at onset are fever sensitive, and mostly consist of generalized or unilateral, often prolonged, clonic, and tonic–clonic seizures. As the disease progresses, afebrile seizures co‐occur, and other seizure types such as myoclonic seizures, atypical absences, and focal seizures become more prominent Dravet . SeizureSCN1A, encoding the alpha subunit of the neuronal voltage‐gated sodium channel Nav1.1. About 70% to 80% of DS patients are shown to carry an SCN1A mutation of which 90% occur de novo  and genetic epilepsy with febrile seizures plus (GEFS+). The mutation yield in these syndromes is however much lower, ranging from a few percent up to 10%  on 31 DS trios . This observation shows the limitations of Sanger sequencing, but most importantly indicates that SCN1A mutations are an even more frequent cause of DS than is generally accepted.Despite the significant contribution of genetic alterations in SCN1A mutations and explored why all these mutations were originally missed.After our prospective EuroEPINOMICS‐RES consortium study we conducted an additional retrospective study to collect additional information on missed The study was approved by the local ethics committees of participating centers. The protocol and procedures employed were reviewed and approved by the appropriate institutional review committee. Informed consent was obtained for the patients described in this study. The followed procedures were in accordance with the ethical standards of the responsible committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.SCN1A screening on a diagnostic and/or research basis, to collect information on SCN1A mutations (RefSeq NM_001165963.1) that were searched for by Sanger sequencing, but were only subsequently identified by NGS. This study was broader than DS and included all phenotypes related to SCN1A. In order to compare the results of these genetic tests, we decided to only analyze detection errors of point mutations or small insertions or deletions. Partial/whole gene deletions and occasionally duplications of SCN1A are also a well‐documented cause of DS. These structural alterations can be missed by Sanger sequencing and may undoubtedly contribute to the group of SCN1A false‐negative cases. This was confirmed in the EuroEPINOMICS‐RES cohort where testing with array‐CGH detected two deletions in the remaining 23 SCN1A‐negative patients (unpublished data). In the retrospective study, we did not include copy number variants since calling these variants from NGS data is still challenging and clear comparisons between the results of the techniques can thus not be made. With the questionnaire, we specifically asked for information on the sequencing techniques, the reasons for missing the mutation, the setting (diagnostic vs. research), and the date of the screening. All mutations have been submitted to the SCN1A database (http://www.gzneurosci.com/scn1adatabase/index.php).We sent out a survey to 16 genetic centers performing SCN1A mutation that was missed by Sanger sequencing but confirmed by NGS and one patient in whom an SCN1A mutation was detected by Sanger sequencing that was missed in a WES study looking for modifiers  failed to identify the mutation. Reasons for missing these mutations can be classified into three categories . In retrospect, for nine patients, the mutation was present in the Sanger traces, but was simply overlooked by the person performing the initial analysis. Problems with primer design led to false‐negative results in four patients. The medical report of one patient erroneously stated that he was sequenced although he never was; a sample switch occurred for one patient; one patient was assigned the wrong sequencing data; for one the Sanger sequencing results were of bad quality so the sequencing should have been repeated; and for another patient, the mutation was positioned eight base pairs into the intron and was therefore considered not significant and thus not mentioned in the diagnostic report. Finally, one patient had an intronic deletion leading to misalignment of the reads and consequently uninterpretable data.In three patients (10%), technical problems led to missing the mutations. One mutation was not identified in the Sanger traces due to the use of an excessively high primer annealing temperature, but was detected by WES and confirmed in a second Sanger sequencing run at a lower temperature. For one patient, the peak of the mutation in the electropherogram was too low to be called as a variant by the analysis software. A first WES run on this sample suggested mosaicism (49 reference reads vs. 18 variant reads), and this was confirmed by a second WES run (169 reference reads vs. 81 variant reads). The mutation detected by Sanger but subsequently missed by WES was an A>T substitution lying in a stretch of adenine nucleotides, creating a long homopolymer knowing to cause problems in variant calling  using NGS sequencing.For the remaining seven patients, we could not trace the original sequencing reports and were thus unable to identify the exact reason for mutation detection failure.When comparing sequencing techniques, our data show that Sanger sequencing resulted in 28 false‐negative results while NGS missed one mutation. First of all, it should be noted that these numbers probably give an incorrect impression of the reliability of the different techniques, since our retrospective analysis creates an ascertainment bias toward patients initially screened by Sanger sequencing. Although NGS is the logical next step when Sanger sequencing is negative, few patients will undergo Sanger sequencing after a negative NGS screening, unless there is evidence of low coverage of a particular gene or a particularly convincing phenotype.Both techniques clearly have their own technical limitations, as illustrated in this study. NGS is known to be superior to Sanger sequencing for the detection of low levels of mutant allele, as seen in mosaicism. A probable mosaic mutation was indeed first missed by Sanger sequencing, but subsequently detected by WES in one patient in this study (patient 21). The importance of germline and somatic mosaicism is well established in a broad range of diseases, including DS  of mutations were missed due to human errors, which in most cases could have been prevented by applying rigorous quality controls. Sample handling and allocation remain error‐prone steps independent of the sequencing technology. In this context, the use of a well‐functioning laboratory information management system (LIMS) is crucial. Keeping track of all the processes and logging every detail may seem very labor intensive, but might eventually save the costs of a potential redundant NGS experiment. In recent years, strict quality control procedures and criteria, including the use of LIMS, have been developed for diagnostic genetic laboratories, and are expected to result in a reduction of human errors. Also the analysis/interpretation process is prone to errors that are more difficult to eradicate. Errors resulting from visual inspection of Sanger traces can be circumvented by using automated variant calling. Errors related to primer design can be overcome by a more careful control of parameters used in software for primer design. Recent years have also brought us more sophisticated 9/29 of mSCN1A mutations in patients supposed to be SCN1A‐negative is not a unique observation of our study but has been described previously. Carvill et al. reported three mutations in 13 patients with DS in whom a previous SCN1A screening turned out negative  of DS patients from our “SCN1A‐negative” EuroEPINOMICS‐RES consortium study clearly shows that DS is even more genetically homogenous than previously anticipated. That 13 of the 16 participating centers contributed false‐negative cases indicates that missing SCN1A mutations occurs regularly. However, the exact frequency could not be determined as in the prospective EuroEPINOMICS‐RES study. Given the variability in data storage procedures of the different genetic centers involved in this study, we were unable to retrieve information on the total number of SCN1A‐negative patients that underwent a genetic screening with a second technology.In total, we collected 29 SCN1A mutation. Whether this is performed using Sanger sequencing or NGS  seems to be of lesser importance as no technique is perfect in identifying all the mutations. In case of a negative SCN1A test in a patient with a convincing clinical suspicion of DS, we recommend clinicians to discuss the need to use a second genetic technique and analyze SCN1A in depth to be absolutely sure that no mutation is present. It should however be noted that despite the clear genotype–phenotype correlation between SCN1A mutations and DS, mutations in several other genes have also been associated with a DS phenotype (Depienne et al. SCN1A and possibly also epigenetic factors affecting the gene might play a role in the pathogenesis of DS. A negative SCN1A screening should therefore not be considered as an exclusion factor for DS.Given the high genetic homogeneity of DS, first‐line testing for DS should be the search for an Finding a mutation and thus providing a clear etiological diagnosis has major implications for the patient and his/her family comprising not only issues related to prognosis and family planning but also interventions toward a more tailored treatment.None declared.


In this study, we therefore evaluated alternative glucose dosing regimens for determination of the impact of glucose dosing on measures of β‐cell function in normal and diet‐induced obese (DIO) mice. The glucose dosing regimens used for the IVGTT were 0.35 mg per kg total body weight (BW) or per kg lean BW or a fixed glucose dose based on the average BW for all experimental mice. Each regimen detected a similar decrease in insulin sensitivity in DIO mice. The different glucose dosing regimens gave, however, diverging results in regard to glucose elimination and the acute insulin response. Thus, the fixed‐dose regimen was the only that revealed impairment of glucose elimination, whereas dosing according to total BW was the only regimen which showed significant increases in acute insulin response in DIO mice. The fixed‐dose glucose dosing regimen was the only that revealed a significant decline in the disposition index value in DIO mice, which is characteristic of type 2 diabetes in humans. Our results therefore show that using different glucose dosing regimens during IVGTT in DIO mice one can model different aspects of physiology which are similar to prediabetes and type 2 diabetes in humans, with the fixed‐dose regimen producing a phenotype that most closely resembles human type 2 diabetes.Insulin sensitivity declines in overweight and obese individuals and, under normal conditions, insulin secretion adaptively increases which in healthy non‐diabetic subjects maintains normal glycemia. This adaptation is best described by the disposition index derived from modeling of insulin and glucose data from an intravenous glucose tolerance testing (IVGTT). One caveat of the IVGTT is that basing the glucose dose on the individual total body weight can result in large differences in the amount of glucose given to lean and obese individuals. The effect this has on determination of insulin sensitivity and  It is unclear what effect the amount of glucose given during an intravenous glucose tolerance test has on measures of glucose tolerance in diet‐induced obese mice. We tested glucose dosing based on total body weight, lean body mass, or a body weight‐independent fixed dose. The fixed‐dose glucose dosing regimen was the only that revealed impaired insulin sensitivity, insufficient insulin secretion, and a diminished disposition index, all hallmarks of type 2 diabetes, and is thus the optimal glucose dosing regimen for intravenous glucose tolerance testing in diet‐induced obese mice. This quantification is made by the disposition index, which is based on the hyperbolic relationship between insulin sensitivity and insulin secretion and, mathematically, is described as the product of insulin sensitivity multiplied by insulin secretion  quantify insulin secretion and estimate insulin sensitivity with the aid of mathematical modeling  for 8 weeks. These mice exhibit normal and reduced insulin sensitivity, as previously reported  and kept in a temperature controlled room (22°C) on a 12‐h light–dark cycle, with food and water ad libitum. On arrival, all mice were placed on a normal rodent diet (ND) D12450B for 1 week to acclimate to hard feed and thereafter divided into two groups and fed with ND or high‐fat diet (HFD) D12492 with 60% of kcal from fat (Lard) for 8 weeks before glucose tolerance testing. All diets were from Research Diets . This study was approved by the regional animal ethical committee, Lund, Sweden.Lean body mass was determined on a cohort of mice that had been fed a ND or HFD for 1, 3, 8, 12, and 16 weeks by dual emission x‐ray absorptiometry using a PIXImus imager . The relationship between lean body mass and total body weight was analyzed with separate linear regressions for ND or HFD fed mice. The slope and y‐intercept from the linear regressions were used to estimate the lean body mass from a given total body weight and this estimate was used for glucose dosing according to lean body mass.IVGTTs were performed on 5 h fasted mice after 8 weeks of diet treatment. Blood samples were collected from anaesthetized mice  from the retrobulbar, intraorbital, capillary plexus before d‐glucose injection (0.35 g/kg bw) to the tail vein. Additional blood samples were collected at 1, 5, 10, 20, 30, and 50 min from each mouse. Plasma was separated and stored at −20°C until it was analyzed for insulin with a mouse insulin ELISA  and glucose (glucose oxidase method).G) was computed as the slope of the logarithmically transformed circulating glucose concentration between 5 and 20 min after administration of the glucose bolus. The insulin sensitivity index (SI) was estimated, as previously described  was calculated with the trapezoidal rule. The glucose elimination constant . There was a positive linear relationship between total body weight and lean body mass Fig. A and B. G derived from the IVGTT data, only the fixed glucose dose strategy detected the impairment of glucose elimination induced by HFD feeding . The fixed‐dose glucose injection resulted in hyperglycemia in the HFD fed mice with commensurate hyperinsulinemia  in the mice with each of the glucose dosing regimens. Each of the glucose dosing regimens demonstrated significant decreases in insulin sensitivity in mice fed a HFD , only the fixed glucose dose regimen was able to identify the expected impairment resulting from HFD feeding (Fig. β‐cell function was significantly improved in HFD fed mice when dosed according to total body weight, but not according to dosing by lean body mass or fixed glucose dose (Fig. Using the minimal model analysis of IVGTT data, we determined insulin sensitivity (SHFD Fig. C. As reging Fig. D. β‐cellose Fig. .β‐cell function obtained from IVGTT is described in humans by the disposition index (Kahn et al. β‐cell function in the progression from normal glucose tolerance to impaired glucose tolerance and type 2 diabetes (Bergman et al. β‐cell sensitivity to glucose was significantly greater in HFD fed mice dosed according to total body weight, but not in HFD fed mice dosed according to lean body weight or a fixed glucose dose irrespective of body weight. There was only a trend toward increased acute insulin response in the latter groups. This is important to note as when the measures are incorporated into the disposition index, it is apparent that the increase in acute insulin response may be insufficient for the corresponding level of insulin sensitivity, resulting in a significant underestimation of the info provided by the disposition index. Only the fixed‐dose glucose dosing regimen was able to make this distinction. The other glucose dosing regimens showed no differences in the disposition index between HFD fed mice and control mice. These results are similar to the results previously demonstrated for oral glucose tolerance testing in mice where different glucose doses were tested and compared to a fixed dose (Andrikopoulos et al. The natural history of type 2 diabetes is characterized by increasing insulin resistance which is normally compensated for by increasing insulin secretion to maintain normal glucose tolerance (Bonadonna et al. The results expose important differences between the glucose dosing regimens which need to be considered for how the HFD model is to be related to glucose tolerance in humans. The frequently sampled IVGTT in humans is given at a dose of 0.30 g/kg total body weight, nearly identical to the 0.35 g/kg used in the mouse study presented here (Bergman et al. β‐cell function during an IVGTT, which in turn imply that careful selection of dosing regimens is important when performing studies on glucose metabolism and islet function in animals and humans for estimating diabetes risk.We thus conclude that glucose dosing regimens influence the results of insulin sensitivity and The authors acknowledge the excellent technical assistance of Kristina Andersson and the helpful discussion of the manuscript from Ulrika Axling.None declared.


The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.Although transformation of melanocytes to melanoma is rare, the rapid growth, systemic spread, as well as the chemoresistance of melanoma present significant challenges for patient care. Here we review animal models of melanoma, including murine, canine, equine, and zebrafish models, and detail the immense contribution these models have made to our knowledge of human melanoma development, and to melanocyte biology. We also highlight the opportunities for cross‐species comparative genomic studies of melanoma to identify the key molecular events that drive this complex disease. © 2015 The Authors.  Melanocytes produce melanin that protects skin from the effects of ultraviolet light, and also reside as part of mucosal tissues at sites such as the lower bowel, anus, vulva, mouth, and upper aero‐digestive tract. Melanocytes are also found in the uvea/iris of the eye and in the inner ear.MC1R) and tyrosinase (TYR) genes. MC1R is a G‐protein coupled receptor located in the plasma membrane that plays an important role in controlling the microphthalmia‐associated transcription factor (MITF) gene  in the aforementioned MITF gene is associated with increased melanoma risk in sporadic and familial cases, and is an intermediate genetic risk factor PLA2G6 and IRF4), with common variants in or near these genes being revealed by GWAS CDKN2A) gene CDKN2A, and its binding partner, the product of the cyclin‐dependent kinase 4 (CDK4) gene, have been identified in highly melanoma‐prone families TERT) was identified in GWAS studies, and by the analysis of a familial melanoma pedigree, a −57 bp mutation creating an ETS transcription factor binding site that activates the TERT promoter was identified POT1), with mutations in the DNA binding domain of POT1 dramatically increasing telomere length and promoting telomere fragility ACD and TERF2IP, but the exact consequences of these mutations on telomere function are yet to be defined Cutaneous melanoma is largely a malignancy of fair‐skinned people with familial and sporadic genetic risk factors. Population‐based genome‐wide association studies (GWAS) have been particularly informative at defining the relevant melanoma risk regions in the sporadic disease, and to date, around 20 genome‐wide significant loci have been identified riant E31K in the BAP1 gene, encoding the BRCA1‐associated protein‐1 , a deubiquitinating enzyme, predispose to ocular melanoma, with some patients also developing cutaneous melanomas and tumours of other sites While these genetic susceptibility studies have defined the landscape of predisposition to cutaneous melanoma, less is known about the germline genetic contribution to other forms of melanoma. At present, we know that rare loss‐of‐function variants in the MC1R, few studies have addressed the genetics of predisposition to melanoma development in animal models. The studies that have been performed have again revealing an important role for genes that influence pigmentation in the cutaneous disease. In horses, for example, a 4.6 kb intronic mutation in the STX17 (syntaxin‐17) gene was found to be associated with a vitiligo‐like depigmentation phenotype and susceptibility to melanoma With the exception of mutations in CDKN2A led to the identification of somatic mutation in this gene, and also deletions of the entire gene locus PTEN) gene as being mutated in glioma led to the identification of mutations and deletions of this locus in melanoma G12VHRAS transgene was expressed in melanocytes, resulting in highly penetrant melanoma formation NRAS) gene were identified in human melanomas at a frequency of 20% BRAF mutations, most converting a valine at position 600 to a glutamic acid (BRAFV600E), generating a constitutively active kinase in around 50% of cases PPP6C), in addition to regulators of the chromatin landscape  GNAQ), the guanine nucleotide binding protein (G protein), alpha 11 (Gq class) (GNA11), and v‐kit Hardy‐Zuckerman 4 feline sarcoma viral oncogene homolog (c‐KIT) genes Most of what has been learnt about the somatic genetics of cutaneous melanoma in humans has been revealed in the last 15 years. The family studies that identified germline mutations in BRAF and NRAS mutations occurred but tumour sequencing studies have helped us to resolve their absolute prevalence, particularly at positions outside of the canonical BRAFV600 and NRASQ61 residues. Secondly, sequencing has identified new genes. For example, hotspot mutations in PPP6C and RAC1 have been identified, and represent potential sites for therapeutic targeting. We knew previously that RAC GTPase activity could contribute to melanoma development NRAS/BRAF wild‐type melanoma, which is characterized by a high C > T mutation burden, amplifications and mutation of c‐KIT, and alterations of NF1NRAS/BRAF/NF1 wild type has been proposed To date, around 500 human melanoma germline/tumour pairs have been sequenced, with these tumours being largely of cutaneous origin and a limited number of acral and mucosal origin There are multiple ways to model melanoma in the mouse, to allow the identification of key oncogenes/tumour suppressor genes involved in melanoma initiation, progression, and metastasis, as well as for the preclinical testing of therapeutics. Here we will outline the use of patient‐derived xenografts, genetically engineered mice, and melanoma cell lines.in vivo through ten rounds of tail vein injection and collection of subsequent pulmonary metastases to create the B16‐F10 line Established human and mouse melanoma cell lines continue to be workhorses for mechanistic studies, as much can be gained from their analysis. The B16 mouse melanoma model was created in the 1970s from a melanoma that developed spontaneously in a C57BL/6 mouse and was then passaged In vitro work has its limitations (such as a lack of extracellular matrix and 3D growth), and thus, the use of human cell lines in vivo is frequently used to model melanoma, usually by subcutaneous injection/engraftment into immunodeficient mice [typically non‐obese diabetic/severe combined immunodeficient (NOD/SCID) mice] that do not produce lymphocytes or NK cells. These cell line xenograft models allow melanoma cells to directly establish interactions with the stroma, the lymphatic system, and blood vessels. Cell line xenografts have been widely used in determining drug responses in vitro conditions and long‐term culture, limiting their usefulness in certain aspects of modelling human melanoma. In particular, their ability to predict clinical drug responses has been widely questioned and critiqued Patient‐derived xenograft (PDX) or ‘tumourgraft’ samples are collected under ethical approval as fresh biopsy tissue or fine needle aspirates and within hours implanted subcutaneously into immunodeficient mice PDX models, however, do have several important limitations – in particular, the absence of a fully functional immune system – although it is possible to generate partially ‘humanized mice’ using patient‐derived CD34+ haematopoietic stem cells capturing some elements of the human immune system V600EBraf or Q61RNras) and/or inactivation of key tumour suppressor genes (such as Cdkn2a or Pten). Examples of GEM models are listed in Table Cdkn2a (p16Ink4a null mice) does not result in melanoma, with these mice typically developing soft‐tissue sarcomas and lymphomas G12VHRAS on an Ink4a‐deficient background develop spontaneous cutaneous melanomas after a short latency and with a high penetrance Q61KNRAS on an Ink4a‐deficient background  has also been used to model melanoma development, tumour progression, and drug resistance Although mice rarely develop melanoma spontaneously, they can do so when genetically engineered to carry defined mutations that mimic the genetic lesions (or their consequences) found in human melanomas. These engineered mutations can result in activation of oncogenes  and generally do not carry the mutagenic load found in human tumours. Regardless of these factors, these models have made a fundamental contribution to our understanding of melanoma development.Malignant melanoma is a relatively common cancer in domestic dogs and represents a unique model of human melanoma that is highly heterogeneous and arises and metastasizes spontaneously in an immunocompetent animal. There is potential to relate the molecular character of individual tumours to clinical outcome, as pet dogs receive therapy ranging from surgery, radiation, and cytotoxic chemotherapy through to molecularly targeted therapy and immunotherapy. Here we will review the utility of canine melanoma as a comparative model and as a preclinical model of human melanoma.Many domestic animals develop spontaneous melanocytic neoplasms, including dogs, cats, horses, and pigs. Malignant melanoma is more common in the dog compared with other species and the majority of cases arise in the oral cavity , with haired skin (cutaneous), nailbed epithelium and footpad , and ocular  locations being less common V600E mutation is found in about 6% of canine oral melanomas BRAF mutations. NRAS mutations have also been found at the same location as those in human melanoma (the residue corresponding to Q61), and loss‐of‐function mutations in PTEN have been reported PTEN expression, and c‐KIT mutation, and/or overexpression of c‐KIT are common in the canine disease. Importantly, comparative copy number studies have been performed between dog and human melanomas of mucosal and acral origin, suggesting that in concordance with what is known for human melanomas, canine melanomas of the oral mucosa and cutaneous epithelium are discrete and initiated by different molecular pathways The complete canine genome sequence was first released in 2005 in vivo modelling systems described above are more likely to capture the complexity of human cancer than the less refined systems used in the past, a complementary approach is to include dogs with spontaneous cancers The overall success rate of translating cancer therapies from murine preclinical models to treatments with clinical utility in humans is estimated to be around 5% et alhttp://www.CCOGC.net), which contains a large collection of canine tumours including matched dog melanoma/normal pairs. To date, there have been relatively few large clinical trials in canine melanoma. The development of the canine melanoma vaccine introduced above involved only 58 patients A recent, excellent study by Simpson Melanocytic tumours are common tumours of horses, representing approximately 4–8% of all tumours As in other species, the terminology and classification of melanocytic tumours in horses has been inconsistent over time and has led to confusion between clinicians and pathologists STX17 (syntaxin 17) gene, which constitutes a cis‐acting regulatory mutation. Both STX17 and the neighbouring NR4A3 gene are overexpressed in melanomas from grey horses. It is known that the duplication in STX17 is strongly associated with constitutive activation of the ERK pathway in melanocytic cells from grey horses, highlighting the universal importance of the MAPK/ERK pathway in melanomagenesis STX17 sequence acts as a strong enhancer in neural crest cells and has subsequent melanophore‐specific activity during embryonic development, consistent with the phenotypic manifestation of the mutation in horses As in canine melanomas, equine melanomas are not thought to be associated with exposure to UV light. Development of the grey hair coat colour in horses with age is an autosomal dominant trait associated with a high incidence of melanoma, and also vitiligo‐like depigmentation ASIP  gene have a higher incidence of melanoma, implicating melanocortin‐1 receptor signalling in melanoma development in these animals As in other species, tumour subtype and breed/individual variation (germline genetics) are likely to influence the phenotype of the melanomas formed . In vitro cell lines of primary and metastatic horse melanomas revealed expression of p53, while expression of the tumour suppressors p16 and PTEN was absent from the metastatic line In terms of biological behaviour, grey horse melanomas usually have an extended period of benign growth, prior to malignant transformation and metastasis, in contrast to most human melanomas, which metastasize earlyIn terms of histopathology, animal‐type melanoma in humans represents a rare distinct melanoma subtype, characterized by proliferation of heavily pigmented epithelioid and spindled melanocytes, that resembles the heavily pigmented melanomas seen in grey horses in vivo imaging, chemical screens, and genetics. Zebrafish cancers, including melanoma, share many histopathological features with human cancers, and molecular signatures closely align with those of human cancer. Here we outline the use of genetically engineered zebrafish and xenograft models, and discuss how zebrafish have become instrumental for chemical screens for drug leads and repurposing for melanoma.Modelling melanoma in zebrafish provides important opportunities for N‐ethyl‐N‐nitrosourea (ENU)‐induced genetic mutations in tumour suppressor genes. However, the advent of genome editing with the clustered regularly interspaced short palindromic repeats (CRISPR) system now enables precise and tissue‐specific genetic editing that will enable more refined genetic modelling of human melanoma The zebrafish genome shares over 70% similarity with the human genome, and over 80% of human disease genes – including oncogenes and tumour suppressors – have orthologs in zebrafish V600E protein expressed from the melanocyte mitfa promoter led to the generation of naevi, and a mutation in p53 (−/−p53) was required for progression to melanoma V600E mutation and was consistent with genetics in human patients whereby expression of BRAFV600E is sufficient to drive naevi, but requires additional mutations for progression of melanoma from naevi V600E;p53−/−BRAF model, Zon and colleagues generated a modified zebrafish whereby the V600EBRAF transgene was co‐expressed with one of 17 candidate genes from a recurrently amplified region in human melanoma on chromosome 1q21 hox genes In the first zebrafish melanoma model, human BRAFmitf mutation in zebrafish (vc7mitfa) has recently been used to study MITF activity in the control of melanocyte proliferation and differentiation in embryogenesis, and as a cancer gene in the development and survival of melanoma An important feature of zebrafish melanoma is the ability to study melanocyte development genes and how the lineage can become misregulated in melanoma G12V (HRAS12V) protein in kit‐expressing melanocyte progenitors is sufficient to drive rapid expansion of melanocyte numbers in the larval form and melanoma in the adult, and this is dependent on PI3K signalling V12‐driven malignant melanoma V12 melanoma studies have helped to establish melanoma models important for drug screens and cell biology studies NRAS mutations are the common RAS family melanoma mutation, and genetic models in zebrafish indicate that NRASQ61K mutations in melanocytes require co‐operation with loss of p53 to promote melanoma RAS mutations have also been modelled in zebrafish. Expression of HRASV600EBRAF models include the lengthy time for spontaneous tumour formation and that genetically engineered animals do not seem to have the diversity and number of mutations found in human melanomas V12 mutations enables melanoma to be visualized at the earliest stages in the zebrafish V12HRAS oncogene‐expressing melanocytes at the very earliest stages of neoplasia. Immune cells provide trophic support to V12HRAS oncogene‐expressing melanocytes As with mice, limitations of the zebrafish Transplantation assays are fundamental to understanding cancer cell malignancy, migration, and cancer‐initiating cells. Zebrafish provide transplantation studies at three stages: the early embryo, the larvae, and the adult animal casper, has been generated that enables visualization of transplanted melanoma cells – either by their endogenous black pigmentation or via a fluorescent transgene – at the single cell level Adult transplantation studies in zebrafish have been important for assessing tumour potential, visualizing cancer homing and metastasis, and in competitive assays for tumourigenicity. Important considerations in adult transplantation studies include the need to suppress the immune system. To get around these issues, immunosuppression can be induced by gamma irradiation prior to transplantation (eg 20–25 Gy), or dexamethasone in larval/juvenile fish, and isogenic strains have recently become available V600E;p53BRAF at the embryonic level that identified leflunomide, which is currently in clinical trials for melanoma trials.gov identifier NCT01611675). Overall, phenotypic small molecule screening in zebrafish is proving effective at multiple stages of the drug discovery pipeline including hit identification, target identification, lead optimization, and preclinical animal modelling A unique feature of the zebrafish system is the ability to treat the whole organism with drug treatments by administering chemical compounds to the water Xiphophorus models Other models of melanoma not discussed here include the Sinclair swine model BRAF, NRAS, MITF, TP53, P16/CDKN2A, BAP1, PTEN, C‐KIT, etc) can drive naevus formation and/or progression to melanoma in various combinations, while sequencing studies of human melanomas emphasize the genetic heterogeneity of the disease with potential for reclassification based on the genetic phenotype in the future. Multi‐species comparative pathology and genomics  help to identify new melanoma genes for cutaneous melanoma, mucosal melanoma, and less common melanomas at other sites, including the study of rare subtypes of melanoma. These molecular studies also shed light on melanoma progression genes that influence the stage or aggressive behaviour of the melanoma, potentially contributing to an improved molecular and mechanistic understanding of melanoma progression to metastasis in patients and serving as predictors of outcome or potential therapeutic targets. Small animal models (such as mouse or zebrafish) are informative for preclinical drug testing and investigation of mechanisms of drug resistance, as well as providing new insights into the melanoma–immune system interactions, which are of increasing relevance to patient therapy.Animal model studies in a range of species confirm the ‘naevus–melanoma’ pathway as the major sequence of pathological progression to melanocytic malignancy. They also establish naevi as neoplasms that have mutations in oncogenes and tumour suppressor genes, as opposed to the previously held pathological view of naevi as non‐neoplastic hamartomas. The experimental animal model studies demonstrate that some cancer genes (such as LvdW, EEP, GAW, and AF wrote sections of the manuscript on mouse, zebrafish, dog, and horse melanoma, respectively. TB, MJA, and DJA wrote on the genetics and pathology of human melanoma. All authors contributed to revision of the manuscript and the final published paper. All authors contributed equally.


RCW; Picoides borealis). We modeled the effects of land‐use change using multiple scenarios representing different spatial arrangements of new training areas for troops across Fort Benning. We used projected climate‐driven changes in habitat and changes in reproductive output to explore the potential effects of climate change. We summarized potential changes in habitat based on the output of the dynamic vegetation model LPJ‐GUESS, run for multiple climate change scenarios through the year 2100. We projected potential changes in reproduction based on an empirical relationship between spring precipitation and the mean number of successful fledglings produced per nest attempt. As modeled in our study, climate change had virtually no effect on the RCW population. Conversely, simulated effects of land‐use change resulted in the loss of up to 28 breeding pairs by 2100. However, the simulated impacts of development depended on where the development occurred and could be completely avoided if the new training areas were placed in poor‐quality habitat. Our results demonstrate the flexibility inherent in many systems that allows seemingly incompatible human land uses, such as development, and conservation actions to exist side by side.Climate change and land‐use change are projected to be the two greatest drivers of biodiversity loss over the coming century. Land‐use change has resulted in extensive habitat loss for many species. Likewise, climate change has affected many species resulting in range shifts, changes in phenology, and altered interactions. We used a spatially explicit, individual‐based model to explore the effects of land‐use change and climate change on a population of the endangered Red‐cockaded Woodpecker ( Climate change and land‐use change are likely to be two of the most important drivers of environmental change over the coming century  was listed as an endangered species in 1970, largely due to widespread habitat loss , but historically was likely dominated by longleaf pine . Forestry practices have varied since the founding of the installation  with three replicate landscapes for each Table . In the 2 concentrations. Following an 800‐year spin‐up period, LPJ‐GUESS was run for the years 1901–2100.The potential effects of climate change on the RCW population at Fort Benning were assessed in two ways. First, we assessed the effect of future climate change on vegetation using the outputs of an ecosystem model, LPJ‐GUESS . This relationship was used to project the effects of future climate on RCW reproduction. We extracted April precipitation from the nine future climate projections  placed randomly in the landscape. This number was selected to be far above the potential carrying capacity of the population to ensure that the simulated woodpeckers had an opportunity to become established throughout the landscape. After a 50‐year initialization period, the model stabilized at approximately 290 RCW breeding pairs on the landscape in the baseline scenario, which is similar to the current number of RCW pairs present at Fort Benning (~280 breeding pairs).The maximum age for any RCW on the landscape was 14 years, which when coupled with the adult survival rate , allowed for birds older than 10 years in the landscape, but birds in these older age classes were relatively rare. Fledgling survival was set at 45% . Target quality for establishing a cluster was set such that the spatial occupancy of the modeled population reflected current spacing and density of RCWs at Fort Benning. Any hexagon with a habitat quality of at least 1% of maximum was eligible for inclusion in RCW home ranges. Thus, RCW home ranges could include areas of low‐quality habitat, including fragmented areas, provided enough high‐quality habitat was present to meet the minimum range value. In addition, home ranges in our model can vary in size widely based on quality of available habitat, allowing for higher density in areas of high‐quality habitat. Any RCW that did not find a home range that met the minimum range quality became a floater without a home range. These floaters would move again in the next yearly cycle to try to establish a home range, following the movement routine Table . As younYearly spatial RCW population data do not exist for this population, so we were unable to compare modeled and actual population distribution as a method of model evaluation . We ran the model 20 times for each replicate development scenario (nine different series of landscapes) and climate change scenarios (nine different climate scenarios). The spatial data layers (described above) were incorporated into the simulations at 10‐year (land‐use) or 1‐year (climate) intervals to explore the effects of two factors on the RCW population.n = three per class, 20 replicate simulations per scenario) or climate scenario (n = 20 per climate scenario) using analysis of variance (ANOVA), followed by a post hoc test for least significant differences using a Tukey's HSD test. Data were assessed for normality prior to analysis using normal Q–Q plots. All analyses were conducted in R version 2.13.0  was compared among the scenario classes . Under the Conservation scenario, the population was relatively stable over the 100‐year simulation period .The effects of development of new training areas on the RCW population strongly depended on which development scenario was applied .No changes in the dominant vegetation were projected for Fort Benning under any climate model or emissions scenario. The LPJ‐GUESS model outputs suggested that the study area would remain suitable for needle‐leaved evergreen trees, the primary habitat type of RCW. Thus, as we modeled it, climate change had no impact on RCW habitat at Fort Benning. Similarly, our simulations showed little impact of changes in April precipitation on the final number of potential RCW breeding pairs at Fort Benning. Population trends resulting from the simulations using the projected future climates were not different from those resulting from simulations run with a constant (current) climate (Our findings suggest that habitat loss (modeled here through land‐use change) may be a more important threat to some species than climate change. Similar patterns have been found for birds at a global scale  for the Fort Benning study area (Shafer et al. Although we did not observe any effects of climate change on RCW as simulated here, it is important to note that our study only addressed two potential ways in which climate change could affect the population. The empirical relationship between April precipitation and reproduction from Ft. Benning that we used in our simulations has been noted elsewhere and it is hypothesized that it is driven by decreases in the number of foraging bouts by adults (Neal et al. Our findings suggest that prioritizing habitat conservation may enhance the resilience of many systems to climate change. A recent analysis found that for temperate deciduous forest and warm mixed forest biomes, land conversion due to agriculture and timber expansion is expected to have a much larger effect on biodiversity loss than climate change, while the tundra, savannas, boreal forest, and cool conifer biomes are expected to be more impacted by climate change (Sala et al. Our results stress the importance of land‐use change even in the face of large projected shifts in environmental conditions, such as those associated with climate change. Perhaps more importantly, although tempered by the caveats above, this is a positive message. Despite the fact that land‐use change is a formidable threat that has already caused the extinction of many species, it is a threat for which there are clear solutions. Climate change is a far less manageable challenge, many of the true solutions to which will require coordinated action on a global scale.None declared.


While academic‐level studies on metabolic engineering of microorganisms for production of chemicals and fuels are ever growing, a significantly lower number of such production processes have reached commercial‐scale. In this work, we review the challenges associated with moving from laboratory‐scale demonstration of microbial chemical or fuel production to actual commercialization, focusing on key requirements on the production organism that need to be considered during the metabolic engineering process. Metabolic engineering strategies should take into account techno‐economic factors such as the choice of feedstock, the product yield, productivity and titre, and the cost effectiveness of midstream and downstream processes. Also, it is important to develop an industrial strain through metabolic engineering for pathway construction and flux optimization together with increasing tolerance to products and inhibitors present in the feedstock, and ensuring genetic stability and strain robustness under actual fermentation conditions. Despite this, the number of examples of successful commercialization of microbial processes producing chemicals and fuels remains relatively small to date , the productivity (g l−1 h−1) and the product titre (g l−1). In the case of bulk chemicals and fuels, the profit margins are very narrow and it is critical that these three metrics are maximized to be competitive with traditional, petrochemical processes. In many  cases, a trade‐off has to be made between productivity and yield, as maximizing the productivity often requires high density of the producing microbes, while increasing the carbon flux directed towards cell mass inevitably lowers product yield. In an industrial‐scale fermentation, often performed in a fed‐batch mode, a productivity of typically around 2–5 g l−1 h−1 (and preferably higher) needs to be achieved depending on the product. Another strategy for increasing productivity is the use of continuous cultivation, but as these are prone to costly contamination and phage infection, the process requires more expensive equipment, and places high demand of genetic stability on the production host  into biorefineries, with the former strategy bypassing the need to first fix CO2 into plant biomass. Direct CO2 utilization has been investigated using photosynthetic microalgae or cyanobacteria, either to produce oils for further conversion or for direct production of target chemicals and fuels. This technology promises superior oil yields per cultivated area compared with conventional oil crops, but much work still remains to bring costs down to levels comparable to common vegetable oils  and insensitive to infections by for instance bacteriophages. Finally, the production host should obviously possess metabolic capacities for production of the target product at high productivities and yields.The key role of metabolic engineers in the creation of commercial microbial cell factories is engineering strains that can produce the target product efficient enough to meet the requirements for large‐scale bioprocessing as discussed above and summarized in Fig. Escherichia coli and S. cerevisiae, as these microorganisms have been relatively more studied, have well‐developed tools for various genetic manipulations and have well‐validated genome‐scale metabolic models available for genome‐scale metabolic simulations. Several other strains that have also been employed for biorefineries include Corynebacterium glutamicum Clostridium sp., Bacillus sp. and Pseudomonas sp. Nevertheless, with recent developments in inexpensive genome sequencing, more rapid construction of genome‐scale metabolic models, new genetic and genomic manipulation tools, most notably the use of clustered regularly interspersed short palindromic repeats (CRISPR) for metabolic engineering of microbes  to allow production of L‐tyrosine ; a number of examples are available, for instance knocking out the aromatic amino acid biosynthesis pathway regulator tyrosine‐activated repressor  were used to remove allosteric feedback regulation of this pathway  was developed for generating oligo sequences for tuning the translation of chromosomal genes in E. coli  that removes this substrate preference from E. coli. This deletion was recently used to enable synthesis of poly(lactate‐co‐glycolate) through simultaneous utilization of glucose and xylose . Such approaches will be more frequently employed as synthetic biology research advances rapidly.Industrial strains need to be stable over a great number of generations to allow scaling up to production scale. This is no small challenge, as cost issues and environmental concerns prohibit the use of antibiotics at production scale. Thus, it is preferable to use chromosomal pathway integration over plasmid‐based expression if possible. The invention of the CRISPR system has greatly simplified this, as exemplified by a recent report describing the integration of a five‐gene pathway in a single step using CRISPR  is important. It has also been suggested to repeatedly test strains under process‐like conditions during the strain development process, for instance using scale‐down bioreactor systems (Neubauer and Junne, In this work, we have briefly reviewed the challenges associated with the establishing industrial‐scale microbial biorefineries for the production of chemicals and fuels. As has been discussed, many different aspects need to be taken into account during the strain development by metabolic engineering. The most important lesson for successful cell factory development is thus to have an all‐encompassing view during strain development, including everything from feedstock selection, through the bioprocessing steps and to the downstream processes. It is clear that such rapid advances in the field promise successful establishment of microbial biorefineries producing chemicals and fuels from renewable non‐food biomass, allowing us to move towards a bio‐based economy.The authors declare no conflicts of interest.


The extremely high mutational load suggests that immunotherapy may be particularly effective in this disease.The past 5 years have seen a paradigm shift in the survival of patients with advanced melanoma, owed in large part to an improved understanding of the genomic complexity of the disease and the development of novel therapies. Large international efforts to systematically sequence tumours have uncovered molecularly discrete subtypes of melanoma, with mutational characteristics found to segregate with tumour histology and presentation.BRAF mutations and loss‐of‐function mutations in NF1  is a rare melanoma subtype characterised by spindled malignant melanocytes and abundant desmoplastic stroma. These melanomas are usually amelanocytic with an appearance resembling scar tissue that can often lead to delayed or occasionally missed diagnoses . In order to identify additional novel pathogenic mutations, the clustering of mutations at ‘hotspots’ was investigated.Importantly, a new study lead by researchers from the University of California, San Francisco (UCSF), and recently published in The first striking discovery made by Shain et al. was the extraordinarily high number of mutations with a median of 62 mutations per megabase being reported, substantially higher than other cutaneous melanomas (about 15/Mbp), which firmly ranks DM among the most highly mutated cancers sequenced to date. The high abundance of cytosine‐to‐thymidine (C>T) transitions, particularly at dipyrimidines, implicates UV radiation as the dominant mutagen in DM. This should not come as a surprise in a cutaneous neoplasm associated with chronic UV exposure; however, it is of interest within this particular phenotypic subtype with a predominantly intradermal presentation and, as suggested by the authors, strongly implicates a superficially located primary cell of origin. The exceptionally high mutational burden also proffers the question of whether inherited defects in DNA repair or pigmentation may contribute to susceptibility, a question that could be explored using the germline genome sequences of this cohort.The high mutational burden observed in DM is also of significance for patient management. The strong therapeutic effect of immune checkpoint blockade in some patients with melanoma has been linked to expression of neoantigens; mutant peptides presented by MHC Class 1. A higher overall mutational burden would be expected to lead to the expression of more neoantigens, with mutation number being associated with improved efficacy of immunotherapy. In keeping with this, a recent retrospective analysis of over 1000 patients receiving immunotherapy identified 23 patients with DM who received anti‐PD1/anti‐PDL1 antibodies  inhibitor epsilon gene, NFKBIE. This locus was also amplified in 14.5% of samples. Intriguingly validation of NFKBIE promoter mutations revealed that both alleles of the gene were altered in some cases. The protein (IκBε) encoded by NKFBIE inhibits the activity of proinflammatory NFκB transcription factors by sequestering them in the cytoplasm . Mutation of this hotspot region was also demonstrated in two melanoma cell lines (M257 and M375), which were both shown to express the same short isoform of NFKBIE, and showed a lack of NFκB translocation to the nucleus. NFκB mediates crosstalk between inflammatory signals and cancer at multiple levels and there is emerging in vivo evidence that inhibiting NFκB signalling can elicit an antitumour immune response and can even enhance the effects of immune checkpoint inhibitors (Hayakawa et al., NFKBIE promoter leading to attenuated NFκB signalling may participate in the recognition of DM cells by the immune system, although the exact functional role of NFKBIE in DM is yet to be explored.The second key finding by Shain et al. was that the most common mutational hotspot in DM occurs in a promoter region that regulates the expression of the nuclear factor kappa‐light‐chain enhancer of activated B cells (NFNFKBIE promoter alterations, highly focal amplifications of MAP3K1 were identified in three tumours, and two novel melanoma‐related genes were found: CBL and FBXW7. Other mutated genes included NF1, CDKN2A, ERBB2, MAP3K1, EGFR, PTPN11, MET, RAC1, SOS2, NRAS and PIK3CA. Mutations in TP53 and amplification of TERT were also observed. Importantly, TERT promoter mutations or amplifications occurred in 90% of the DMs analysed in this study. Amplification and consequent changes in expression levels of EGFR, MET, CDK4, CCND1, YAP1 and MDM2 were shown. The study of these somatic alterations not only serves to provide a better understanding of the pathogenesis of DM, but also has implications for the use of molecular pathway inhibitors in the clinic.In addition to NFKBIE in DM is also of particular interest, providing a window to a distinct mechanism driving this subtype of melanoma.This report represents a substantial leap forwards in deciphering the molecular mechanisms underlying DM and provides unequivocal evidence that DM is genomically distinct from common melanoma. The extremely high mutational load suggests that immunotherapy may be particularly effective in this disease, potentially paving the way towards a rational preselection strategy for the use of immune checkpoint blockade in patients with this disease. The finding of focal amplifications/promoter mutations of This paper highlights the benefits of large‐scale genomic analyses in rare tumours types by showing that genomic alterations that might not have otherwise been detected with small studies can be found by collaborators leveraging sample collections between centres.