To determine the frequency of breast cancer (BC) patients with hereditary risk features in a wide retrospective cohort of patients in Spain.Sporadic breast cancer group (R0); Individual risk group (IR); Familial risk group (FR); Individual and familial risk group (IFR) with both individual and familial risk criteria.a retrospective analysis was conducted from 10,638 BC patients diagnosed between 1998 and 2001 in the GEICAM registry “El Álamo III”, dividing them into four groups according to modified ESMO and SEOM hereditary cancer risk criteria: 7,641 patients were evaluable. Of them, 2,252 patients (29.5%) had at least one hereditary risk criteria, being subclassified in: FR 1.105 (14.5%), IR 970 (12.7%), IFR 177 (2.3%). There was a higher frequency of newly diagnosed metastatic patients in the IR group . In contrast, in RO were lower proportion of big tumors (> T2) , nodal involvement  and lower histological grades (20.9% G3 for the R0 vs 29.8%) when compared to patients with any risk criteria.Almost three out of ten BC patients have at least one hereditary risk cancer feature that would warrant further genetic counseling. Patients with hereditary cancer risk seems to be diagnosed with worse prognosis factors. Breast cancer is the most frequent malignancy in women . In SpaiIt is widely described in the literature that up to 25% of breast cancer patients have a familial/hereditary background, that can be explained through a genetic condition only in a small percentage . PopulatRecently, the Spanish Medical Oncology Society (SEOM) have suggested clinical criteria for genetic test selection of hereditary breast cancer patients through a clinical guideline . In the The implications of genetic testing are nowadays going beyond the prevention and early detection area, influencing also therapeutic decisions with the use of specific treatments, such as oral PARP inhibitors or platinum-based regimens. Currently, several clinical trials are ongoing for different clinical scenarios with these treatments, from the metastatic disease to the adjuvant setting, being in the spotlight of the oncology breast cancer community .In summary, a better understanding of the epidemiological landscape of breast cancer patients with hereditary risk features is of interest.El Álamo Project is a retrospective observational study that includes 26,658 breast cancer patients diagnosed between 1990 and 2001 across 43 Spanish Hospitals and distributed in three cohorts: El Alamo I with 4,532 patients diagnosed between 1990 and 1993, El Alamo II with 10,849 patients diagnosed between 1994 and 1997 and El Alamo III with 11,277 patients diagnosed between 1998 and 2001. El Alamo project has the aim to describe patterns of presentation, management and outcomes of breast cancer in Spain [El Álamo III, included for the first time the familial background of patients, in addition to clinical and personal features linked to hereditary risk . With more than eleven thousand invasive breast cancer patients diagnosed in 11 of the 17 Spanish regions [ regions , this isThe objectives of this study are to analyze the frequency and clinical/pathological characteristics of Spanish invasive breast cancer patients with hereditary risk features.All procedures performed in this study were in accordance with the ethical standards of the participant institutions and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. “Comité Etico de Investigación Clínica del Area 1” IRB reviewed and approved the Alamo project.El Álamo III project that included 11,277 breast cancer patients. El Alamo focused on female breast cancer and only some centers recruited a small number of male patients , so they were excluded from this analysis. Non invasive carcinoma breast cancer cases  were also excluded.This is a retrospective analysis from Questionnaires including data regarding individual tumor information and familial features were completed by the clinical investigators  histology and/or bilateral (synchronous or metachronous) breast cancer or breast cancer at any age together with ovarian cancer. The familial criteria were: the presence of first or second degree relatives with the following features: 3 relatives (including the patient) with breast and /or ovarian cancer or 2 relatives (including the patient), if the relative fulfill any of the individual criteria above mentioned, regardless degree; or 2 relatives (including the patient) if is first degree and diagnosed with breast and/or ovarian cancer.Sporadic breast cancer group (R0) (Control group) without individual or familial risk criteria; Individual risk group (IR) with no familial or not determined (ND) familial risk, but with individual risk criteria; Familial risk group (FR) with no individual or ND individual risk, but with familial risk criteria; Individual and familial risk group (IFR) with both individual and familial risk criteria. Global hereditary risk group (GHR) comprises the three last categories, namely IR or FR or IFR.According to the individual and familial criteria, patients were divided into 4 different subgroups: ® version 21 (IBM corporation).Chi-square and unpaired t student/Anova were used to compare categorical and continuous variables respectively. All statistical tests had a significance level of 0.05 unless stated otherwise. Data were analysed using SPSSFrom 1998 to 2001, 10,638 women with invasive breast cancer were included in the study. Patients who had enough information to be sub-classified as one of the four risk subgroups accounted for 7,641 (71.8%). The individual and familial risk criteria for hereditary breast cancer of the global sample are described in Of these evaluable patients, 2,252 patients (29.5%) had at least one hereditary risk criteria, constituting the global hereditary risk group (GHR). The 5,389 (70.5%) remaining patients, with no risk features, were considered the R0 group . Table 3In the univariate analysis we found that R0 group presented a lower proportion of big tumors (≥ T2) than the GHR group , a lower proportion of nodal involvement  and lower histological grades . Metastases at diagnosis were present in similar proportion in both groups . As expected, a higher proportion of TNBC was found in the GHR group, given that the TN phenotype is included in the criteria to define hereditary cancer . In ordeComparing each specific GHR subtype with sporadic cases, we observed that the differences seen before are only observed for the IR group. In contrast, similar clinic-pathological features were seen between R0 and IFR and FR groups respectively . MoreoveAccording to this large and representative sample of the Spanish breast cancer landscape, we can say that three out of ten patients have, at least, one hereditary breast cancer risk feature, and, in consequence, could be candidate for genetic testing and counselling. Overall, patients with hereditary cancer risk features have larger tumors and more frequently nodal involvement in comparison to patients without hereditary cancer risk features, while both subgroups have a similar rate of distant metastases at initial diagnosis. However, these differences probably are related to the greater aggressiveness observed in patients fulfilling the individual criteria. Interestingly, when patients with TNBC were excluded for this analysis, presence of nodal involvement and higher grades, although not tumor size, remained higher in patients with hereditary risk features.Strong points of this study are the large number of patients analyzed and the representativeness’ of Spanish population, since two thirds of the regions are represented. Few studies exist in Spain analyzing the frequency of different familial cancer from a population point of view, with the exception of melanoma , pancreaAnother weakness, in order to classify patients in a given risk group, is the fact that nearly 60% of patients had an unknown HER2 status, in consequence, a substantial number of patients, could not be evaluated regarding the TN phenotype, one of the major risk factors for hereditary breast cancer. Within the time-frame of data collection (patients diagnosed from 1998 to 2001), although the role of HER2 was well known as a prognostic factor, the determination of this biomarker was not widely used, given that appropriate targeted therapy was only available for metastatic patients.Patients with hereditary cancer risk features have worse pathological risk factors, according to T and N status, and to histological grade, all well-known bad prognosis factors. Data of prognosis from patients with known BRCA 1 and 2 mutations are conflicting in literature. A recent meta-analysis did not detect differences in breast cancer specific survival rate in BRCA2 mutation carriers when compared to sporadic ones . I contrOne could think that patients concerned with their familial background are more prone to intensive surveillance, both by themselves and by their health care givers, what should be translated into earlier diagnostic presentations, something that is not reflected by our data. This is true in other familial cancers, such as melanoma, where patients at familial risk in Spain present with better prognosis pathological factors . HoweverIt is important to analyze if our data are comparable to other countries. Our results are according to what is described in general literature . HoweverFinally, the practical consequences of our findings should be taken into consideration. In general, it is estimated that, according to different institutional series in Spain and western countries, BRCA 1 or 2 mutations are present from 7% to 20% of selected and unselected patients in western countries –27. With


Csf1r locus encodes the receptor for macrophage colony-stimulating factor, which controls the proliferation, differentiation and survival of macrophages. The 300 bp Fms intronic regulatory element (FIRE), within the second intron of Csf1r, is necessary and sufficient to direct macrophage-specific transcription. We have analysed the conservation and divergence of the FIRE DNA sequence in vertebrates. FIRE is present in the same location in the Csf1r locus in reptile, avian and mammalian genomes. Nearest neighbor analysis based upon this element alone largely recapitulates phylogenies inferred from much larger genomic sequence datasets. One core element, containing binding sites for AP1 family and the macrophage-specific transcription factor, PU.1, is conserved from lizards to humans. Around this element, the FIRE sequence is conserved within clades with the most conserved elements containing motifs for known myeloid-expressed transcription factors. Conversely, there is little alignment between clades outside the AP1/PU.1 element. The analysis favours a hybrid between “enhanceosome” and “smorgasbord” models of enhancer function, in which elements cooperate to bind components of the available transcription factor milieu.The  Despite their rapid evolution, many enhancers are sufficiently conserved to permit their identification based upon sequence conservation (phylogenetic footprinting). Comparative analysis with other mammalian genomes indicated that 3–8% of the human genome has been subject to purifying selection, most of which is not protein-coding and inferred to be regulatory4. Most enhancers contain binding sites for multiple transcription factors, and despite overall conservation, individual binding sites may be gained and lost through alterations in DNA sequence with consequential changes in gene regulation. Early comparative analysis of functional elements identified in human promoters indicated around 30–40% are lost in mouse5. One extreme example is the absolute divergence in glucorticoid-inducible gene expression between humans and mice as a consequence of the gain and loss of glucocorticoid-receptor binding to distal enhancers6. Other examples have been reviewed by Villar et al.3.Transcriptional regulation in eukaryotes involves a complex interaction between distal regulatory elements (enhancers) and proximal promoters. Most eukaryotic genes are influenced by multiple enhancers which may display a degree of redundancy and which appear to evolve more rapidly than promoters1. Such a model is favoured by the increasing recognition of the probabilistic basis of transcriptional regulation at the single cell level9. A “billboard” type enhancer may have a conserved function despite a relative lack of alignable sequence conservation3.There are two prevailing models for the function of the individual binding motifs, and the factors that bind them, within a complex enhancer. In some enhancers, the cooperative binding of multiple transcription factors in a precise array is required for activity, and each element is non-redundant. The complex of bound transcription factors has been referred to as an enhanceosome. In the alternative “billboard” model, each transcription factor binds to the enhancer, and interacts with the promoter, to some extent independently to regulate transcription11. The transcription regulation of Csf1r in mouse and human has been studied extensively12. The second intron, downstream of the first coding exon, contains a conserved 300 bp regulatory element, the Fms intronic regulatory element, or FIRE. FIRE is an unusual enhancer in that the activity is position and orientation dependent, and is associated with the generation of an antisense transcript13. The presence of FIRE is essential to the activity of a Csf1r transgenic reporter gene in mice14. A lentiviral vector containing FIRE and the Csf1r promoter was able to direct macrophage-restricted reporter gene expression in mouse, rat, human, pig, cow, sheep, and even chicken macrophages in vitro15 and in transgenic sheep16. So, FIRE is both necessary and sufficient to direct macrophage-specific transcription from the Csf1r locus. The chicken Csf1r locus contains a regulatory sequence in the same relative location as FIRE that is conserved between bird species and can direct expression of reporter genes to the macrophage lineage in transgenic chick17.The differentiation of vertebrate macrophages is controlled by signals from the macrophage colony-stimulating factor (CSF1) receptor, CSF1R  which has two ligands, CSF1 and interleukin 34 (IL34). This function of CSF1R and the two ligands in macrophage differentiation is conserved from bony fish and birds through to humans12. The rapid decline in DNA sequencing costs has increased the availability of genomic DNA sequences from many more distantly-related species which offers the opportunity to analyse the way in which FIRE has evolved across species. Here we present an analysis of the conservation and divergence of vertebrate FIRE sequences.The mouse FIRE sequence contains binding sites for numerous macrophage-expressed transcription factors, including PU.1, KLF4, RUNX1, CEBP and AP1 family membersTM  programme. Mammalian, avian and reptilian FIRE sequences were individually extracted from completed genomes and whole genome sequencing available in NCBI (https://www.ncbi.nlm.nih.gov) using “BLAST Genomes”, with mouse or human , chicken or zebra finch (for birds) and alligator or anole lizard (for reptiles) as the query. The most conserved sequence that was also specifically associated with the Csf1r locus was aligned with the query and trimmed accordingly. For the snakes, there was no initial BLAST hit using available query sequences on any snake genome draft assembly in NCBI. We therefore extracted the second intron of the annotated Csf1r locus from available snake genomic sequences, and using Pustell, identified a 300 bp conserved region in the same relative location as FIRE in birds that contained the core elements described below. That sequence was then used in BLAST to identify similar sequences in other snake genomes. All of the sequences analysed are provided in the alignments in Supplementary Figures.All analysis was carried out using the MacVectorPotorus tridactylus), Southern brown bandicoot (Isoodon obesulus), Western grey kangaroo (Macropus fuliginosus), Western quoll (Dasyurus viverrinus) and Fat-tailed dunnart, (Sminthopsis crassicaudata)18.The representation of available FIRE sequences from non-placental mammals was relatively low compared to placental mammals. Only platypus, echidna (monotremes), Tasmanian devil, koala and opossum were available. A partial FIRE sequence was detected in the Tamar Wallaby genome, interrupted by Ns. To extend the available marsupial sequences, we obtained DNA from 5 species  to amplify the sequence. PCR cycles were performed as follows: an initial denaturing step 95 °C for 3 min, followed by 30 cycles of 95 °C for 30 s, 55 °C for 30 s, 72 °C for 45 s, and an elongation step 72 °C for 3 min. PCR products obtained from these species were purified using the QIAquick PCR Purification Kit following the manufacturer’s protocol and sequenced by Sanger sequencing at the Institute for Genetics and Molecular Medicine (IGMM), University of Edinburgh. Genebank IDs are p) of nucleotide sites at which two sequences being compared are different. It is obtained by dividing the number of nucleotide differences by the total number of nucleotides compared. It does not make any correction for multiple substitutions at the same site, substitution rate biases  or differences in evolutionary rates among sites. The set of candidate regulatory motifs with the consensus sequence from each clade was identified by scanning the sequence using the Jaspar motif database (http://jaspar.genereg.net), allowing for >85% match to the position weight matrices. As noted by Sandelin & Wasserman19, the binding sites recognised by multiple members of transcription factor families can be grouped and motif analysis alone cannot distinguish which family member is likely to bind. Accordingly, we grouped the putative transcription factors identified with Jaspar by families and highlighted those with known expression in macrophages12.To generate phylogenetic trees, and consensus sequences, the sequences from each clade were trimmed to a common length, and aligned using ClustalW. Neighbour joining trees were generated using MacVector. The distance measures shown in the resulting phylogenetic trees  represent the proportion  were very divergent from the marsupials and the reptile sequences were even more divergent amongst the major groups . Indeed, the three available lizard sequences  were also very divergent from each other and there was only a weak consensus. We extracted the consensus sequences from mammals, birds, snakes, crocodiles and turtles from the ClustalW alignments. Figure Figureentary Figures 21 and support the close relationship between the crocodilians, testudines (turtles and tortoises) and birds  were clearly associated in one branch. The groupings of the placental mammals are largely consistent with conclusions based upon 447 nuclear genes in 37 species22. In this respect, FIRE is representative of the class of conserved non-exonic elements (CNEE) that have been analysed as promising phylogenetic markers in birds, and indeed the tree in Fig. 23. As suggested by these authors, FIRE, as a typical CNEE, provides a positional framework for phylogenetic analysis, anchored on blocks of substantially conserved sequences (the transcription factor binding sites), between which base substitutions/inclusions/deletions are not constrained and their drift can provide indications of evolutionary relationships.Based upon the ClustalW alignments we generated neighbor-joining trees for each Clade based solely upon the FIRE sequences. Although there was a clear link between the reptile and bird sequences, for ease of visualization, the reptiles are shown separately, with two bird sequences (chicken and zebrafinch) included for comparison Fig. . The avi12. Combinations of ChIP-seq and in vivo footprinting indicate that the conserved sequences with FIRE in both species are occupied by transcription factors including PU.1, AP1, CEBPA/B, STAT1, IRF8, KLF4 and RUNX112.The conserved sequence blocks are clearly constrained by the binding affinity of the transcription factors that bind them. The precise regulation of mouse and human FIRE by myeloid-specific transcription factors has been reviewed recentlySPI1 gene) determined by ChIP-seq analysis of human monocytes and monocyte-derived macrophages24 and mouse macrophages25. The FIRE PU.1 site is occupied in mouse macrophage progenitor cells26 and PU.1 is essential for Csf1r expression in cytokine-dependent granulocyte-macrophage progenitors27. Several quite divergent species, including mouse and platypus shown in Fig. Csf1r genes also vary in the number of PU.1 binding sites, with evidence of cooperative activity of different Ets family members28. The ChIP-seq analysis of PU.1 binding in mouse and human also revealed strong enrichment for AP1 (Fos/Jun) consensus motifs in the immediate vicinity of PU.1 binding sites25. The core of the FIRE element also contains a conserved consensus AP1 site that is essential for the enhancer and promoter activity of mouse FIRE in vitro13. The precise apposition and orientation suggests that there might be cooperative binding to this motif. Combinatorial interactions between JUN and PU.1 have been noted in the regulation of other macrophage-specific enhancers31 and there have been multiple reports of direct physical interaction between PU.1 and JUN family members (Reviewed in ref.32). Comparative analysis of variations in PU.1 binding amongst mouse strains indicated that strain-specific PU.1 binding often involved variation in adjacent AP1 motifs25. One surprising feature of the AP1 element (TGAWTCA) is that the central base (A/T) is consistent from lizards to humans, and the motif is distinct from the classical AP1 consensus (TGASTCA). The one exception is in snakes, where the AP1 element is the consensus, TGAGTCA, and it is displaced by around 6–7 bp from the PU.1 element. We speculate that the variant AP1 element might either bind AP1 complexes with relatively low affinity (therefore requiring cooperativity with PU.1), or might bind specific members of the Fos/Jun/ATF family selectively, promoting effective interaction. This core AP1/Ets element resembles the distal regulatory element that has been characterised in detail in the mouse urokinase plasminogen activator (Plau) gene that responds to tyrosine kinase-Ras-Raf-Map kinase signals34. In the Plau enhancer the AP1 site (TGAGGTCA) is also distinct from the consensus. Growth factor signals in progenitor cells acting on the weak AP1 element within FIRE could form part of the initial chromatin remodelling allowing the binding of PU.1 and other factors. The CSF1/CSF1R regulatory mechanism and macrophage-restricted expression of Csf1r is conserved in Xenopus35. Although we could not confirm function or conservation of a FIRE-like element in amphibia, having access to only the xenopus sequence, a BLAST search of the Xenopus Csf1r locus revealed a candidate AP1/PU.1 motif in the same relative location as FIRE in other species, suggesting that this basic mechanism may have arisen very early in evolution. The sequence of this region is shown in Fig. Csf1r locus is duplicated; one copy, Csf1ra, appears to be expressed in macrophages and mutations compromise early macrophage development in zebrafish36. A macrophage-expressed Csf1r cDNA has been isolated in several other fish species37. However, we have not detected any aligned regions, nor any AP1 motifs within the introns of available fish Csf1ra genomic sequences, nor any sequences matching the conserved PU.1/AP1 element anywhere in the genomes of cartilaginous fish. Hence, it appears that this core element arose in the land vertebrates.In Fig. 38 is conserved only in murids. In other rodent species, this element has base substitutions that would most likely abolish Runx1 binding . The precise location and indeed the identity of the transcription factor motifs varies between clades. As we have noted previously, the same motifs exist in the Csf1r promoter, and point mutations in adjacent functional Runx1 and CEBP elements identified in the human promoter produce a loss of binding in the mouse promoter42. In mammals, there is an extensive conserved STAT/IRF8 motif within FIRE, and binding of STAT1 and IRF8 has been confirmed in ChIP-seq analysis of mouse macrophages12. The extended STAT/IRF motifs present in mammalian FIRE are not obvious in avian FIRE , nor are the AT-rich (FOX family) sequences in avian FIRE present in mammals, but the mouse FIRE sequence is functional as an enhancer in chicken macrophages15. The conservation of sequence within clades suggest that the gain and loss of motifs has been constrained within each clade on the basis that the loss of any one site produces a significant reduction in transcriptional activity, as observed in the IFNB1 enhanceosome. That is certainly the case for the core AP1 element, and for RUNX1 binding sites that we have assayed directly38. By analogy, the loss of a single transcription factor binding site in the conserved long range enhancer of the Shh1 locus is associated with the loss of limb development in snakes43.The pattern of motif shuffling that we observe Fig.  amongst Csf1r transcription . Interestingly, and despite the fact that CSF1 signaling down-regulates Csf1r mRNA by acting on the anti-sense promoter activity of FIRE42 a heterozygous knockout of Csf1r in mice44 and rats  is not dosage-compensated and produces a 50% reduction in Csf1r mRNA. Accordingly, a heterozygous loss of function of FIRE could produce an impact on macrophage biology that might produce a selective advantage or disadvantage.The evolutionary conservation of core elements of FIRE suggests that there would be a phenotype associated with a loss of function. We are currently analysing the knockout of this element in mice, which does indeed impact on In summary, the FIRE sequence alone can be amplified using generic primers, and provides approximate indications of phylogenetic relationships amongst species. The core AP1/PU.1 sequence arose early in vertebrate evolution, and in different clades this element has associated with a cohort of binding sites that sample the myeloid transcription factor landscape.Supplementary Figures and Tables


Halichoerus grypus). From 2013 to 2015, we sampled 345 pups and 57 adults from Cape Cod, MA, USA and Nova Scotia, Canada consistently detecting IAV infection across all groups. There was an overall viral prevalence of 9.0% : 6.4%–12.5%) in weaned pups and 5.3% (CI: 1.2%–14.6%) in adults, with seroprevalences of 19.3% (CI: 15.0%–24.5%) and 50% (CI: 33.7%–66.4%), respectively. Positive sera showed a broad reactivity to diverse influenza subtypes. IAV status did not correlate with measures of animal health nor impact animal movement or foraging. This study demonstrated that Northwest Atlantic gray seals are both permissive to and tolerant of diverse IAV, possibly representing an endemically infected wild reservoir population.Influenza A virus (IAV) has been associated with multiple unusual mortality events (UMEs) in North Atlantic pinnipeds, frequently attributed to spillover of virus from wild-bird reservoirs. To determine if endemic infection persists outside of UMEs, we undertook a multiyear investigation of IAV in healthy, live-captured Northwest Atlantic gray seals ( Harbor seals (Phoca vitulina) appear particularly susceptible to mass mortalities associated with diverse influenza infections, as evidenced by periodic outbreaks along the northeast coast of the United States in 1979 (H7N7), 1982 (H4N5 and H4N6), 1991 (H3N3) and 2011 (H3N8).10 Most recently (2014), H10N7 was associated with a mass mortality event in harbor seals of the North Sea.13Since 1972, there have been several reports of influenza A virus (IAV) in seals around the globe, including multiple locations in the Americas and Eurasia, representing several seal species.14 An in vivo study using experimental infection with a seal-derived H7N7 found that while harbor seals developed disease, gray seals and harp seals (Pagophilus groenlandicus) were resistant to disease,7 reminiscent of the low pathogenicity seen in avian natural reservoirs.15 Analyses of archived serology samples from many of the seals with an Arctic distribution  and hooded seals (Cystophora cristata)) were seropositive without apparent signs of morbidity, again suggesting the possibility of endemic IAV infection.9 Most recently, gray seals in the North Sea were found to have antibodies against H10N7 despite a lack of morbidity, and predating the H10N7-associated mortality event that followed soon after in harbor seals in the same region.16Although influenza-associated seal UMEs demonstrate that seals can serve as a spillover host, there are suggestions that the virus could be endemic in seal species.19 As a reservoir host does not typically show signs of disease, it provides a mechanism for the pathogen to be maintained and evolve, and from which spillover into new populations can occur. In contrast, a spillover host is typically exemplified by strong and acute immune activation, disease progression and morbidity or mortality.17 Ongoing endemic infection is a key indicator of a reservoir host, particularly when coupled with asymptomatic infection and minimal long-term fitness costs. Mammalian reservoir hosts are of particular importance in that they can provide a mixing vessel and/or source of mammalian adaptation for IAV. When avian-specific variants acquire the ability to infect mammalian hosts, either through incremental mutations, or genomic reassortments brought about by coinfection with multiple viruses, there is a risk for human pandemic infection.22 As epizootic instances become more frequent, understanding the dynamics involved in interspecies transmission becomes increasingly important.Reservoir hosts are often defined as being a long-term host for a pathogen in which infection is well tolerated and maintained at a subclinical level.28 Host populations that occur at high density are associated with an increase in infection risk, a pattern consistent across wildlife species.29 Second, gray seals appear to be fairly resistant to infectious disease caused by viral agents, in contrast to the harbor seals that share much of their range.31 The absence of discernable morbidity brought about by infection is expected to enhance the probability of the virus being maintained within the population. Third, gray seals are highly social and interact with one another regularly and intimately, hauling out on top of one another, engaging in open mouth aggression, competing for mates, and hissing and spitting at one another, all interactions expected to favor pathogen transmission.33 Finally, there is mounting evidence to suggest that gray seals attack other gray seals,34 harbor seals,35 harbor porpoises37 and seabirds,39 interactions that provide opportunities for cross-species transmission. If gray seals serve as an underappreciated natural reservoir for IAV, increasing populations may result in amplification and dissemination of virus along the coast to other mammals, coastal birds and potentially seeding of novel human infections.The changing ecology of gray seals possesses several factors that make them an intriguing species to investigate as a potential influenza reservoir host. First, gray seal numbers declined in both eastern and western Atlantic waters, largely due to human interactions. Recently, their populations have rebounded, due in large part to the Marine Mammal Protection Act (1972), leading to re-colonization and increased population density across the North Atlantic, with steady increases noted in New England waters, Sable Island, Nova Scotia (NS), the United Kingdom and the Wadden Sea.The largest gray seal colonies in North America were targeted for longitudinal sampling and included breeding colonies in Canada and the United States (US) . All US P>0.1) during the 2015 season; the data from that year was therefore pooled for analysis. Muskeget is an uninhabited island located just west of Nantucket and Tuckernuck islands off Cape Cod, MA, USA. It comprises 292 acres of sand dunes, marsh, and two fresh water ponds, and is both the southernmost and largest US breeding colony of gray seals.25 Monomoy NWR is located on the southeast corner of Cape Cod near Chatham, MA and encompasses 7604 acres of sand dunes, marsh and freshwater ponds that provide critical habitat to numerous migratory and endangered birds. A gray seal breeding colony became established on the South Monomoy Island in the early 1990s and has continued to grow, currently representing the second largest gray seal breeding site in the United States after Muskeget Island. In addition to gray seals, harbor, harp and occasional hooded seals haul out on the island. Monomoy is also home to additional mammals, such as coyotes, deer, muskrats and voles, provides habitat to over 300 bird species and is an important nesting area for migratory shorebirds including federally protected piping plovers and roseate terns. Muskeget and Monomoy are ~18 nautical miles apart.Weaned gray seal pups were sampled on Muskeget Island in 2013, 2014 and 2015, and on Monomoy Island, Cape Cod in 2015. There was no significant difference between the two sites in the number of animals found to be IAV positive by either serology or quantitative real-time polymerase chain reaction   and kept chilled for up to 8 h in the field before being stored below −80 °C. Approximately 10 mL of blood (<1 mL/kg) was collected using standard aseptic techniques from the extradural intravertebral vein using a 20G 1.5 in to 3.5 in needle. Blood samples were stored chilled for up to 8 h until further processing. Serum tubes were centrifuged to separate serum and stored below −80 °C. EDTA-treated blood was collected from a subset of pups from 2013 and analyzed for complete blood cell counts (CBCs) using a Veterinary Hematological System . Hematocrit was determined using a standard clinical microhematocrit centrifuge . Total white blood counts (WBCs) were measured and used to calculate the mean corpuscular volume, mean corpuscular hemoglobin and mean corpuscular hemoglobin concentration.Weaned gray seal pups were captured on land and were physically restrained during sampling and monitored for signs of distress. Adult gray seals at Cape Cod were captured by purse seine, carefully pulled ashore and sampled under sedation; adult seals on Sable island were captured on land using a hinged pole net and restrained for ~15 min without sedation. Morphometrics were taken on each animal, including weight, straight length, axial girth and flipper length. As a proxy for age, pups were coded for molt stage ranging from II (youngest) to V (oldest): stage II, weaned with complete lanugo; stage III, molted around face and flippers; stage IV, molting on body; stage V, completed molting.41 In each of 2013 and 2014, 12 adult gray seals were tagged on Sable Island, NS. Each seal was fitted with a Mk10-AF Fastloc GPS tag  programmed to transmit Advanced Research and Global Observation Satellite (ARGOS) and GPS data and to archive GPS data that were downloaded on recovery of the tag.42 The tags possessed a variety of sensors to collect high-resolution movement and dive behavior, and were attached to the dorsal neck/head region of the animal's fur using an epoxy-based adhesive.41 Each tag measured 10 cm × 7 cm × 4 cm and weighed 370 g (in air). GPS tags: GSM/GPRS devices  Instrumentation, St Andrews, Scotland) archive the data during at-sea periods and transfer using available GSM mobile phone networks upon return to the beach and haul out. Satellite tags: transmit data to the ARGOS System in Largo, MD, USA whenever an animal surfaces.In 2013, nine adult gray seals were tagged in June at Chatham, MA, USA: seven using global positioning system (GPS) tags and two using satellite tags, one of which was provided through whalenet.org ) and the other provided by the Northeast Fisheries Science Center (NEFSC).43 and mammalian isolates.44 Samples were batch processed with each 96-well plate containing two positive and eight negative controls. Any sample with a cycle threshold (Ct) value <45 was considered positive, as recommended by the United States Department of Agriculture (USDA) for influenza screening in wild birds.45 An animal was considered positive for active viral shedding if any of the three swabs  were avian influenza (AI) matrix positive. The average Ct value of positive swab samples was 38.21 (range 32.45–42.0). Only one sample had a Ct <35, the cutoff frequently required for potential virus isolation.49 Despite high Ct values, all AI matrix positive samples were passaged in embryonated chicken eggs (ECEs)  and a subset were tested in Madin–Darby canine kidney (MDCK) cells. As expected with high Ct values, the majority of samples failed to grow; those that grew remained at a low concentration (Ct >35) and failed to generate sequence by both Sanger and next-generation sequencing.Viral RNA was extracted from 50 μL of VTM sample using the Omega Mag-Bind Viral DNA/RNA Kit  and a KingFisher Magnetic Particle Processor . RNA was screened using qScript XLT One-Step RT-qPCR ToughMix  and analyzed for fluorescence on an ABI 7500 real-time PCR System . A conserved region of the matrix gene was targeted using two separate primer sets optimized for avian isolates51Serum collected from seals were screened for influenza antibodies using an enzyme-linked immunosorbent assay (ELISA) kit  following the manufacturer's instructions. Each sample was run in duplicate using 10 μL per well, diluted 1:10 with sample buffer. Positive and negative controls were run on each plate. Absorbance values were measured with an Epoch Spectrophotometer  and the average for each sample was used to calculate the sample to negative ratio. Samples with a ratio ≤0.6 were considered positive for influenza antibodies.54 Serum was diluted 1:4 with receptor destroying enzyme (RDE), incubated 18–20 h at 37 °C, then 30 min at 56 °C. Positive control reference sera was obtained from the Influenza Research Database and Centers of Excellence for Influenza Research and Surveillance (CEIRS) proficiency panel sera. Treated sera was serially diluted two-fold in phosphate-buffered solution and incubated with four hemagglutination units (HAU) of virus for 60 min at room temperature (RT). To verify effective RDE treatment and the absence of nonspecific hemagglutination, each treated sera was also tested for hemagglutination in the absence of virus. A final concentration of 0.25% chicken erythrocytes was added for an additional 20–60 min at RT. The hemagglutination inhibition (HI) titer was recorded as the last dilution where complete inhibition occurred, as evidenced by the presence of buttoned erythrocytes. Serum was defined as negative for HI titers below 1:8, moderate for HI 1:16–1:64, and strong for HI titers >1:128. The virus panel included human-derived isolate: pH1N1 (A/Netherlands/2629/2009/H1N1pdm), harbor seal-derived isolate H3N8  and avian-derived isolates H2N3 (A/duck/Interior Alaska/11PG00459/2011/H2N3), H3N8 , H4N6 , H6 (A/goose/Interior Alaska/11PG00149/2011), H7N3 , H8N4 (A/northern pintail/Interior Alaska/9BM11643/2009/H8N4), H9N2 , H10N6 , H11N9 (A/glaucous-winged gull/Southeastern Alaska/10JR01856/2010/H11N9), H12N5 , H13N6 (A/ring-billed gull/Massachusetts/12DC00060/2012/H13N6) and H16N2 . All viral stocks were grown in ECEs and avian allantoic fluid was titered to obtain HAU. The following serum positive samples were analyzed: 2013 pups (n=9), 2014 pups (n=11), 2015 pups (n=8), 2013 adults from Cape Cod (n=6) and 2013 adults from Sable island (n=6).Seropositive samples were tested for the ability to inhibit hemagglutination from a panel of influenza A isolates in a protocol adapted from.p=prevalence and n=individuals sampled. Each sampling group represented <10% of the total population. To identify whether infection of seals was influenced by age , sex , sampling location , year  or season , partial least squares (PLS) regression was performed. PLS was selected as the model for testing due to the highly correlated nature of the predictor variables. Correlation matrices indicated that age and season, in particular, were highly correlated. Three infection metrics were tested with PLS that were defined by two or four outcomes: virus shedding (positive/negative), seroprevalence (seropositive/seronegative) and infection status . Infection metrics were treated as the nominal response variable. Age classes were pooled into immature  and mature (adults) to reflect breeding maturity of seals. PLS indicated which ecological variables were important in explaining variation observed in each of the three response variables. If an ecological variable had a small variable importance projection (VIP) of <0.8,55 it was considered a weak predictor of seal infection. The relative importance of each variable was assessed by ranking the total effect size of each parameter. Variable importance estimates assessed whether variability of the dependent/response factor was a function of variability associated with each parameter.56 This process relied on Monte Carlo resampling of observed values due to the assumption of non-uniformity of seal sampling across space and time. All statistics were performed using JMP Pro 12.1 for Macintosh.For each prevalence estimate, standard error was calculated as A total of 402 Northwest Atlantic gray seals were sampled from both Sable Island, NS, Canada and Cape Cod, MA, USA. The majority of animals (340/402) were sampled on Cape Cod and comprised predominantly pups (345/402) from the January breeding seasons of 2013 to 2015. Sampling effort based on season, year, age and location are shown in Overall, 9.0% : 6.4%–12.5%) of the gray seal pups and 5.3% (CI: 1.2%–14.6%) of the adults were AI matrix positive. Prevalence varied across years, with pup prevalence levels in 2014 trending lower than both 2013 and 2015, though not statistically significant. The difference across sampling years suggests inter-annual variability .The majority of animals were also screened for IAV-specific antibodies directed against a conserved epitope of the IAV nucleoprotein (NP). Combined data across the three years of sampled pups on Cape Cod showed 19.3% (CI: 15.0%–24.5%) were seropositive, a level consistent throughout the three winters sampled . A small40  showed evidence of IAV infection (current or past) from one or both screening methods. Grouping the animals by age class revealed distinct trends in group infection status associated with location (USA or Canada) and age , and while both mature populations showed evidence of past exposure , only those on Sable Island had any viral shedding . PLS analyses identified season, age and location as important variables .F ratio=0.7057, P =0.55, In order to approximate whether or not IAV infection had an impact on the overall health of the animal, a Smirnov body condition index was applied (girth × 100/length). There were no significant differences in body condition associated with any of the four infection statuses .57In 2013, blood samples from a subset of animals were analyzed for CBCs. Of the 25 animals screened, five were seropositive by ELISA, and of those five, two also had detectable viral RNA. The seropositive animals were matched to seronegative animals according to gender and molt stage; the seropositive animals had evidence of slightly elevated WBC as compared with matched seronegative animals . However, all samples fell within the normal healthy range for gray seal pups and the observed difference was not statistically significant .Adult gray seals were tagged in Chatham, MA, USA near the Monomoy NWR headquarters . Similar59 No significant differences were observed.On Sable Island, 12 adult gray seals were tagged in 2013 and 12 additional animals were tagged in 2014. Seven individuals were positive for influenza, including four animals that were seropositive but virus negative, one seropositive animal that was also virus positive, and two animals actively shedding virus that had not yet seroconverted. Because of the limited number of virus positive animals, animals with any evidence of IAV infection past or present were grouped as positive for the purpose of mapping. Overall, there was a surprisingly broad response in the 28 pups and 12 adults tested for the ability to inhibit hemagglutination against the panel of influenza A viruses . All vir60 Similarly, as with wild-bird reservoirs, the presence of IAV in gray seals does not appear to readily cause morbidity or mortality and IAV has never been reported in association with a dead stranded gray seal. However given that live virus was not recovered from the animals in this study, the extent to which virus is actively replicating remains unclear.Three years of data spanning two geographic locations, breeding and non-breeding seasons, and immature and mature animals, demonstrate that Northwest Atlantic gray seals are at a minimum repeatedly infected by influenza A virus, and could also potentially act as a reservoir host. Approximately 5%–12% of animals were consistently found to have detectable viral RNA, with seroprevalence ranging from 19% in pups to 50% in adults. The degree of infection and exposure seen within this population is comparable to that seen in some of the wild birds that are widely accepted as reservoir hosts.In a reservoir population, the young immunologically naive animals experience the highest percentage of acute infections, while mature animals benefit from an immunological memory response and demonstrate a high percentage of immunity. This trend was observed in the gray seal population, wherein acute infection was primarily detected in pups while the adult gray seals had a higher percentage of seropositive animals. Pups estimated to be only a few weeks to two months old were already showing acute infection, suggesting possible vertical transmission. However, horizontal transmission is also highly probable within the population, particularly in the older pups that are largely segregated from their mothers and other adults. A number of recently weaned pups presumed to be within a month of age had detectable antibodies, but no active viral shedding. As it is unlikely that the pups acquired virus and cleared infection within such a short time span, this likely reflects maternal antibody transfer. Such an interpretation is also consistent with our observation that 50% of adults were seropositive.As predicted for a reservoir host, we found no evidence of pathogenicity within the IAV positive wild capture gray seals identified in this study. Body condition index is frequently used as an overall measure of animal health, with the Smirnov index providing a reasonable, albeit imperfect, metric for pinnipeds. We found no difference in the body condition of animals that were positive for IAV. We also found no difference in total white blood cells based on infection status, and all animals tested were found to be within the normal range for this species. However, the sample size for these analyses were small and the body condition metric can be difficult to interpret, particularly with pups that are fasting.61 and have been observed to travel between the two locations, with juveniles believed to exhibit a greater dispersal than adults. In May of 2015, a juvenile seal tagged in the Gulf of St Lawrence, Canada was reported ~800 miles away on Nantucket Island, Cape Cod. In addition, the Northwest Atlantic Seal Research Consortium recently constructed a database to report sightings of tagged animals (http://main.who.edu); multiple gray seals branded on Sable Island have been reported through this mechanism in Maine and around Cape Cod. To determine if IAV infection impacted regional or long-term movements, we opportunistically utilized GPS and satellite telemetry from a subset of animals. These animals were monitored prior to, during and after the breeding season. IAV infection status had no impact on how far the animals traveled nor the regions that they visited. Both seronegative and seropositive animals were found to make extensive regional movements and visit multiple haulout sites. Each of the tagged females within this study spent a prolonged period of time on Muskeget Island during the expected pupping period, suggesting these females were breeding/pupping, regardless of IAV status. There was one provisioned animal with restricted movements, and one animal that fell prey to a great white shark. However, both of these animals tested seronegative, so IAV infection did not influence the outcome.An additional metric of a pathogen-associated fitness burden is animal behavior and movement. Seals forage throughout the Gulf of Maine and visit multiple haul-out sites within their range. Both the Cape Cod and Sable Island populations reported in this study are of the same genetic stock62 As these animals appeared healthy at the time of sampling, it is possible that the viral load was too low for sustained viral shedding at a concentration required to propagate and sequence the virus, or that seal-derived IAV is poorly adapted to growth in ECEs. It is also possible that the strain(s) of virus circulating within the gray seal population are sufficiently divergent from avian isolates that the standardly used primers directed against untranslated regions of IAV are inadequate in this context. Alternatively, the inability to recover high concentrations of live virus could suggest that gray seals are a dead-end host that are frequently infected through avian cross-species transmission; as such they would not replicate nor shed high concentrations of virus.We were unable to obtain sufficient viral RNA for sequencing. The inability to grow and sequence virus isolates is often a significant challenge for influenza surveillance in wild reservoirs and can be attributed to multiple factors.Mirounga angustirostris) in California.2 Although this could be through direct interactions on coastal beaches, a more probable explanation postulated was that runoff from densely populated urban areas may contaminate coastal waters frequented by seals. The striking difference that we observed between a densely populated urban area (Eastern Massachusetts and Cape Cod) versus a remote island (Sable Island), lends further support to such an interpretation. Finally the observation that gray seals recognize H13 and H16 isolates is an intriguing one. The subtypes have almost exclusively been associated with Anseriformes (gulls and terns), with the one notable exception of a pilot whale  H16N2 infection. The detection of these gull associated subtypes within gray seals suggests that the virus is competent for mammalian infection.63 It also highlights the potential connectivity between birds and coastal mammals in exchanging influenza.As an alternative to molecular characterization, we utilized HI assays against sera from seropositive animals to subtype viruses. The HI assay provides a reasonable proxy of exposure based on antigenic cross-reactivity. Using this approach, we found that the gray seals in this study had a remarkably broad and diverse serologic profile against IAV, with some evidence of regional and temporal variations. The most frequently recognized subtypes were pH1N1, seal H3N8, H13 and H16. However, a large proportion of seropositive pups recognized H6, adults frequently recognized H2N3, and animals from Sable Island had a strong response to H4N6. Nearly all animals tested recognized the seal-derived H3N8 that was identified during the 2011 UME in harbor seals in the Gulf of Maine. This strongly suggests that although gray seals were not impacted by the UME, they were likely exposed and either H3N8 specific antibodies have been maintained for 4 years or more, or the virus continues to circulate. Also of particular interest, all groups of animals sampled on Cape Cod showed a moderate to strong reactivity against human pandemic H1N1; however animals from Sable Island did not. This is reminiscent of the recent report of the human population established pH1N1 infection found within northern elephant seals (Significant effort and resources are directed toward understanding IAV as it is an infectious agent that has caused, and continues to cause, substantial human morbidity and mortality. It is well established that IAV is maintained in wild bird populations and undergoes rapid and dramatic evolutionary changes through individual mutations and reassortment. Such changes occasionally result in viruses that are competent for mammalian transmission and can lead to threats of novel pandemic strains. The presence of a wild mammalian host that is repeatedly infected by IAV and potentially maintains virus at an endemic level could have a significant impact on how the virus evolves and adapts and is a critical component in understanding the overall disease ecology of IAV. The data reported here support the possibility that gray seals may serve as such a host, and warrants expanded analyses on these populations.


S-methyl-11C]-L-methionine ([11C]MET) uptake in the pancreas might be a central indicator of beta cell function. Since gastric emptying was recently shown to influence glycemic control in subjects after pancreaticoduodenectomy , we looked for imaginable relationships between gastric emptying, pre- and postprandial insulin concentrations, and [11C]MET uptake.[11C]MET were administered and the activity  over the pancreas was measured at 15, 30, and 60 minutes after injection. Total integrated SUVmax (area under the curve [AUC]) and incremental SUVmax were calculated.Nineteen tumor-free survivors after PD  and 10 healthy controls  were given a mixed test meal. One gram of paracetamol was ingested with the meal to evaluate the speed of gastric emptying. Insulin, glucose, and paracetamol plasma concentrations were measured before and over 180 minutes after ingestion. Beta cell function was calculated from fasting glucose and insulin plasma concentrations. Simultaneously, 800 MBq of [11C]MET in the pancreas was significantly higher (p < 0.0001) in controls compared to the PD group. Gastric emptying was significantly slower in controls compared to pancreatectomy subjects (p < 0.0001). Paracetamol AUC30 correlated with the SUVmax increment between 15 and 30 minutes , suggesting a relationship between gastric emptying and the uptake of [11C]MET. Total integrated SUVmax correlated with insulin AUC60  in patients after PD. Multivariate regression analysis revealed insulin AUC60 and beta cell function, calculated from the fasting insulin to glucose ratio, as independent predictors of 11C-methionine uptake, i.e. total integrated SUVmax, in patients after PD .The uptake of [11C]MET uptake may represent basal and postprandial beta cell function. The findings suggest a possible usefulness of this imaging procedure for further studying beta cell function.Postprandial [ S-methyl-11C]-L-methionine ([11C]MET), a PET tracer, radiolabeled with short-lived carbon-11 without any alteration to the molecular structure, is an universal donor of transmethyl reactions that participates in the synthesis of DNA and RNA. Methionine is mainly incorporated in the liver, brain, pancreas, and in tumors, where its main metabolic pathway is protein incorporation [11C]MET PET imaging for the examination of the pancreas in 1976 [11C]MET uptake and protein incorporation in duodenal aspirate in patients with chronic pancreatitis, and observed a diminished uptake and incorporation of the tracer. Tracer uptake and amylase output after secretin stimulation were closely correlated MET uptake in type I diabetics, showing a lower tracer uptake as compared to healthy controls. Moreover, in pancreas transplantation, a relationship was found between tracer uptake in the donor pancreas and the duration of insulin independence after transplantation. The authors also suggested this nuclear medical approach to evaluate prospective pancreas donors MET uptake seems to be a central indicator of beta cell function. Therefore, we looked for factors associated with the postprandial uptake in PD. We focused on possible relationships between gastric emptying, pre- and postprandial insulin concentrations, and [11C]MET uptake.MET was prepared on-site for a maximum of three consecutive patients [11C]MET and underwent the first of three PET-CTs after 15 minutes of accumulation. The process required three to five minutes per image. To reduce radiation exposure, only one primary CT scan was obtained to be fused with the subsequent PET scans. To obtain the best possible imaging quality, subjects remained in a supine position, moving as little as possible, until the last scan was recorded. At 15, 30, and 60 minutes after tracer application, PET scans were recorded.MET uptake: AUC60 = (C15 + C30)*15/2 + ((C30 + C60)*30/2). Delta represents the incremental growth over time and is the difference between concentrations of a measured parameter at two different time points.The area under the curve (AUC) was calculated using the trapezoid rule to retrieve integrated values of the measured parameters. Therefore, AUC over 30 minutes (AUC11C]MET pancreas to liver ratio (PLR) was calculated. Regions of interest were the body and tail of the gland. Tracer uptake increments (delta-SUVmax) were calculated between 15–30 and 15–60 minutes. AUC60 of SUVmax was calculated as a measure of total uptake.Maximum tissue standardized uptake values (SUVmax) were obtained manually, based on regions of interest over the pancreas and over the liver. The [The homeostasis model assessment (HOMA) was applied to calculate beta cell function and insulin resistance. The formula by Matthews et al.  is based11C]MET PET-CT scans.After an overnight fast, an indwelling catheter was inserted into the cubital vein and blood was sampled before the ingestion of a liquid test meal (described below), as well as 10, 20, 30, 60, 90, 120, 150, and 180 minutes thereafter for the measurement of insulin, glucose, and paracetamol concentrations. Blood samples were obtained alongside the MET uptake was significantly higher in controls compared to patients, at any of the three time points of measurement  and beta cell function emerged as independent predictors of 11C-methionine uptake, i.e., total integrated SUVmax  compared to controls, suggesting more rapid gastric emptying in the PD patients regardless of pylorus preservation (PPPD). The higher fasting glucose in the PD patients probably reflects the lower steady-state beta cell function. The rapid postprandial rise of plasma glucose can be explained by the more rapid gastric emptying, a relationship that is also observed after operations such as total or partial gastrectomy MET uptake was measured, were twice the value of those in controls. Since our test meal contained no glucose and only 26 g carbohydrates compared with the 75 g glucose used in the oral glucose test by Harmuth et al. MET uptake and early insulin concentrations suggest that the tracer uptake represents insulin production. Moreover, the preprandial baseline beta cell function also correlates with SUVmax. Differences in age might contribute to the difference of tracer uptake and insulin production between controls and PD subjects MET uptake of the pancreas in patients suffering from chronic pancreatitis and alcohol disease, showing a relationship between tracer accumulation and enzyme output of the pancreas as well as tracer incorporation into digestive enzymes. Chronic pancreatitis is a destructive disease that involves the exo- and endocrine pancreas; therefore, diabetes is a common complication [11C]MET PET as an appropriate tool for examining the exocrine gland, diabetes and impaired endocrine function is hardly addressed in these publications. However, beta cell function is probably also represented by methionine accumulation in the pancreas. In patients after PD, the exocrine pancreatic function is significantly impaired MET uptake and insulin production. One major limitation of this study was the younger control group of healthy subjects, which prevented us to assess the impact of age on the measurements.Unfortunately, our results do not allow us to determine the relative impact of exocrine and endocrine function, and further studies with simultaneous measurement of both functions seem to be desirable to clarify the correlation between [11C]MET uptake in combination with plasma insulin concentrations during a test meal, illustrates the relationship between tracer uptake and insulin production. The findings suggest that this imaging procedure is an appropriate tool to further study beta cell function.This study, the first to look at [


Phaseolus vulgaris, including 157 genotypes of the Mesoamerican, 77 of the southern Andean, and 12 of the Northern Peru–Ecuador gene pools, we identified five geographically distinct subpopulations. Three of these subpopulations belong to the Mesoamerican gene pool  and one each to the Northern Peru–Ecuador (PhI) and the southern Andean gene pools. The five subpopulations were distributed in different floristic provinces of the Neotropical seasonally dry forest and showed distinct distributions for temperature and rainfall resulting in decreased local potential evapotranspiration (PhI and southern Andes groups) compared with the two Mexican groups. Three of these subpopulations represent long-distance dispersal events from Mesoamerica into Northern Peru–Ecuador, southern Andes, and Central America and Colombia, in chronological order. Of particular note is that the dispersal to Northern Peru–Ecuador markedly predates the dispersal to the southern Andes (∼400 vs. ∼100 ky), consistent with the ancestral nature of the phaseolin seed protein and chloroplast sequences observed in the PhI group. Seed dispersal in common bean can be, therefore, described at different spatial and temporal scales, from localized, annual seed shattering to long‐distance, evolutionarily rare migration.The wild progenitor of common-bean has an exceptionally large distribution from northern Mexico to northwestern Argentina, unusual among crop wild progenitors. This research sought to document major events of range expansion that led to this distribution and associated environmental changes. Through the use of genotyping-by-sequencing  and geographic information systems applied to a sample of 246 accessions of wild  Phaseolus vulgaris) is one of the most important crops for human nutrition, being a source of proteins, vitamins, fibers, and essential micronutrients worldwide  and gene density (r = 0.74 P < 0.001). Nucleotide diversity (π), Tajima’s D, linkage blocks, and population differentiation (Fst) were analyzed for the entire sample and for three wild gene pools of common bean (π = 1.42e−5), twice that of the Andean gene pool (π = 6.46e−6), and only slightly higher (27%) than the Northern Peru–Ecuador gene pool (π = 1.05e−5). Regarding Tajima’s D, the Mesoamerican, and Northern Peru–Ecuador gene pools show positive values, D = 1.58 and 0.28, respectively. In contrast, the Andean gene pool showed a negative value (D = −0.45).After retaining only the wild ne pools  online. s genome  online amon bean . Among tFst) showed a strong differentiation between the three populations, with the highest value observed between the Northern Peru–Ecuador and Andean populations (Fst= ∼0.6), and the lowest between Northern Peru–Ecuador and Mesoamerican gene pools (Fst = ∼0.3). The Fst value between Andean and Mesoamerican gene pools (Fst = ∼0.34) confirmed previous estimations using whole genome sequence analysis of these populations (The Mesoamerican gene pool showed the highest number of haplotype blocks (951), with the shortest median (N50) length (246 kb). The Andean gene pool showed fewer haplotype blocks (245), but the highest N50 (921 kb). The Northern Peru–Ecuador population showed the lowest number of haplotype blocks (27) and an intermediate N50 length (694 kb) compared with the Mesoamerican and Andean groups. Population differentiation analysis  discriminated mainly between the Mesoamerican/Northern Peru–Ecuador groups and the Andean gene pool (P < 2e−16) negative correlation (r = −0.9) between these variables  was performed for the 246 ene pool A, followene pool A inset. ene pool A, suggesQ) cut-off ≥0.7 for assigning genotypes to a specific cluster. A similar threshold was used by P. vulgaris.Population structure analysis using the TESS3 program identified five subpopulations that best define our sample : three pUsing this cut-off, the majority of the individuals were clearly assigned to one specific cluster, even though some genotypes where admixed with subpopulations of either the same or another gene pool  online. Some genotypes showed to be miss-assigned, with accession G23523 from Mexico clustering with the Northern Peru–Ecuador gene pool, the MW G23508 clustering with the Andean gene pool, and the Northern Peru–Ecuador G23584 clustering with the Andean subpopulation. Clusters MW1 and MW2 showed to be composed only of accessions from Mexico, whereas cluster MW3 was composed of accessions from Guatemala, Honduras, Costa Rica, and Colombia .P. vulgaris showed similar patterns by using either neutral or coding variants . In addition, in both trees the nodes separating the Northern Peru–Ecuador and the AW/MW gene pools were both supported with a high bootstrap (>80), whereas the split between AW and MW populations was highly supported only in the phylogenetic tree built with neutral variants  variants. Despite small differences beween the two phylogenetic trees, the clustering of the major gene pools of wild variants .P. vulgaris across the genetic groups identified by TESS3. We hypothesized initially that the different genetic populations identified were subjected to similar climatic conditions and, thus, were found in similar environments. Instead, an ANOVA analysis of climatic distribution across genetic populations showed significant differences across these populations (P < 0.05), whereas there were no significant differences between the MW1 and MW2 populations located in Mexico. The Andean group showed the lowest annual rainfall, even though it was not significantly different than those of the North Peru–Ecuador group (PhI) and the MW1 population located in North Mexico  showed the highest value in the MW2 group, although no significant differences were observed between the MW1 and MW2 subpopulations B. The MWP. vulgaris wild gene pools in the collection analyzed, as observed by phylogenetic analysis, we used a constant effective population size  as a proxy for identifying the ancestral population in our demographic modeling process  clearly supported the Mesoamerican hypothesis of origin of this species, with a PP of 0.96 for the standard rejection algorithm, 1 for the mnlogistic, and 0.96 for the neural network approach . Model cAnalysis of model accuracy using cross-validation showed high predictive error (>20%) for the founder population size of the Northern Peru–Ecuador and Andean groups, whereas the times of divergence showed a lower predictive error for the Northern Peru–Ecuador (<15%) and Andean (<10%) gene pools divergence time when using the 0.5% and 1% sampled points nearest to the observed summary statistic  online. P. vulgaris is nothing short of extraordinary, especially among crop plants. Indeed, this distribution extends from northern Mexico  to northwestern Argentina  may get lost. In addition, genotype imputation in data sets with a relatively high percentage of missing data, such as GBS, increases the number of false heterozygous calls . Nevertheless, the lower diversity levels in the PhI and AW groups are due in part to the very narrow habitat they occupy on the western and eastern flanks, respectively, of the Andes Mountains. The other cause is, of course, the long-distance dispersal leading to genetic drift and selection.The three major gene pools showed different values for key population genetic variables. The Mesoamerican gene pool was the most diverse with a ectively . The redectively  but cannectively ; fig. 2 A similar pattern was observed in the number and size of haplotype blocks in the three wild gene pools, with the Mesoamerican having the shortest haplotype block lengths, and the Andean the longest one. Studies of haplotype blocks in human populations showed shorter haplotype blocks length in African population when compared with non-African ones, suggesting that population demography and evolution could shape the pattern of haplotype blocks length across the genome . These rP. vulgaris is located within the seasonally dry, Neotropical forest, one of the most threatened biomes on Earth . Thus, one might have expected similar environments in this habitat. Nevertheless, Banda-R et al. (2016) also documented 12 floristic groups within this dry forest, suggestive of different environments. In particular, groups MW1 and MW2 are found in the Mexican floristic province, MW3 in the Central America–Northern South America and Northern inter-Andean Valleys provinces, PhI in the Central inter-Andean Valleys province, and AW in the Piedmont and Apurimac-Mantaro provinces.Correlations between annual means of climate variables and the distribution of the five population groups , a range of ∼4 °C . The three long-distance dispersal all displayed a decrease in PET . Any need for adaptation beyond these ranges will probably require genetic diversity contained in other Phaseolus species, as illustrated by the adaptation to higher temperature provided by P. acutifolius and P. lunatus  and the A + M clade.Because the genus oamerica , it folloamerica . Howeveroamerica . In bothP. coccineus species. Based on these results, P. vulgaris and named this species Phaseolus debouckii  instead of using a set of SNPs widely distributed across the genome as in the current study. The lack of a common ancestor in the phylogenetic tree between MW and AW, along with the strong  species . This in species .Phaseolus genus , bean plants disperse their seeds through the explosive dehiscence of their pods. The dehiscence phenomenon lies at the intersection of genetic , the seeds are dispersed over a contiguous landscape composed of adjacent or sympatric suitable habitats. Although dispersal may not happen every year, it can take place relatively frequently allowing a certain degree of admixture between relatively distant populations and limit differentiation and, eventually, speciation. Potential agents of seed dispersal may be rodents, birds, and megafauna . This meP. vulgaris is the result of at least three long-distance migrations  from a core ancestral area in Mesoamerica. Other Phaseolus species have been subjected to these seed dispersal at different spatial scales. These include, for example, lima bean (P. lunatus), which has a wild progenitor distribution similar in magnitude to that of wild common bean, as it extends from Mexico to Argentina and was also domesticated twice . Our data suggest then that the current distribution of wild ed twice . They alfrijol de paloma (dove or pigeon bean) as birds damage pods to extract seeds from them .In the present study, the genotyping at a genome-wide level of some 250 individuals representative of wild common bean populations resulted in a more complete and comprehensive characterization of the genetic diversity, relatedness, and evolution of this species in comparison with previous studies. In addition, the integration of genetic and ecological data enabled the identification of patterns of dispersal and colonization leading to the extensive distribution of the wild ancestor of this crop across the Americas. It also clarifies that these migration has led to colonization of regions with different climates than that of the region of origin . Furthermore, this distribution carries the unusual distinction that it includes the descendant of a potentially extinct ancestor (the PhI group of Ecuador and northern Peru) outside the ancestral area of the genus P. vulgaris accessions covering the entire geographical distribution of common bean from Northern Mexico to Northwestern Argentina were selected. All three gene pools of common bean were represented in our panel, with 175 accession of the Mesoamerican (MW), 84 of the Andean (AW), and 12 of the ancestral (PhI) gene pool from Northern Peru and Ecuador, the latter group characterized by the ancestral type I phaseolin  were included in each of the two libraries. Specific barcodes and adapters for CviAII were designed with the GBS barcoded adapter generator . The list of the barcode sequences used for multiplexing, the relative genotypes and the SRA accession number for each library are shown in DNA extraction and GBS Illumina library preparation followed the GBS protocol developed for common bean and described in http://www.ncbi.nlm.nih.gov/sra; last accessed October 26, 2017) under the accession numbers SRX2771627 and SRX2771628.The two libraries were first evaluated in one Illumina HiSeq2500 lane each to check the effectiveness of multiplexing at the UC Davis Genome Center, and then sequenced in four other Illumina HiSeq2500 lanes each at the QB3 Vincent J. Coates Genomics Sequencing Laboratory at the University of California, Berkeley, CA. All the sequencing was performed with the 100-bp single-end Illumina protocol. Raw reads are available at the NCBI Sequence Read Archive  after the barcode sequence, were then demultiplexed allowing no mismatch on the barcode sequence. Demultiplexed reads were aligned to the P. vulgaris reference genome sequence  or the adapter contaminants, and by quality trimming using a 5-bp sliding window and a cut-off quality (averaged on the 5-bp window) of 20. Reads longer than 30 bp after the preprocessing, and containing the overhang sequence of P. vulgaris, all the other Phaseolus species and the domesticated genotypes were removed from the data set prior to SNP filtering. In the last filtering step, we removed the genotypes with <10% of genotyped positions (-mind 0.1), kept only biallelic SNPs with <20% of missing data (-geno 0.8) and with a Minor Allele Frequency (MAF) higher than 0.05 (-maf 0.05). Variant statistics were calculated using VCFtools. Nucleotide diversity, Tajima’s D  ranging from 2 to 10 and 20% of masked genotypes (for computing the cross-entropy criterion). After manual evaluation of population clustering and geographic distribution of these populations for each value of K, we selected K = 5 as the number of population best representing the collection analyzed.Molecular PCA was performed using the adegenet package  implemenP. vulgaris genome . SNPhylo has been specifically designed for reconstructing phylogeny from SNPs data; it is able to collect representative SNPs for each linkage block, based on LD, in order to reduce marker redundancy. With both of these data sets, we selected an LD threshold of 0.4 for reducing marker redundancy in SNPs analysis. For both data sets, we performed alignments with the MUSCLE algorithm (P. coccineus) was used.Phylogenetic inference was performed with SNPhylo , analyzilgorithm  and infewww.r-project.org; last accessed October 26, 2017). Based on the geographical coordinates of the genotypes analyzed, we extracted climatic variable using the dismo R package. Annual rainfall and annual mean temperature were extracted from the WorldClim database  at 30 sec resolution. Annual PET was extracted from the Global Aridity and PET database . For identifying possible variations of climatic variables within the genetic groups identified by TESS3, we performed an analysis of variance (ANOVA) using only genotypes with a membership coefficient ≥ 0.7. Post hoc multiple comparisons were performed with the Tukey’s HSD test implemented in the agricolae R package.An analysis of the climatic distribution of the final 246 individuals retained for the final analysis was performed within the R statistical environment  and DendroPy (Demographic parameters were estimated with the abc package available on R (41). Prior to parameter inferences, we evaluated the accuracy of prediction of our model by cross-validation, implemented in the R package, on a subset of 1,000 randomly sampled simulations using the standard rejection algorithm. We evaluated this accuracy on three tolerance levels, using the 0.5%, 1%, and 5% sampled points nearest to the observed summary statistic. We inferred the time of divergence between the Ancestral and the main common bean group, and between the Andean and Mesoamerican gene pools using the standard rejection algorithm and the 1% sampled points nearest to the observed summary statistics. Confidence interval and highest posterior density (HPD) of the means of this points for each divergence time were calculated using the SciPy (DendroPy  python lMolecular Biology and Evolution online.Supplementary DataClick here for additional data file.