Hoplolaimus spp.) feed on the roots of a wide range of plants, some of which are agronomic crops. Morphometric values of amphimictic lance nematode species overlap considerably, and useful morphological characters for their discrimination require high magnification and significant diagnostic time. Given their morphological similarity, these Hoplolaimus species provide an interesting model to investigate hidden diversity in crop agroecosystems. In this scenario, H. galeatus may have been over-reported and the related species that are morphologically similar could be more widespread in the United States that has been recognized thus far. The main objectives of this study were to delimit Hoplolaimus galeatus and morphologically similar species using morphology, phylogeny, and a barcoding approach, and to estimate the genetic diversity and population structure of the species found. Molecular analyses were performed using sequences of the cytochrome c oxidase subunit 1 (Cox1) and the internal transcribed spacer (ITS1) on 23 populations. Four morphospecies were identified: H. galeatus, H. magnistylus, H. concaudajuvencus, and H. stephanus, along with a currently undescribed species. Pronounced genetic structure correlated with geographic origin was found for all species, except for H. galeatus. Hoplolaimus galeatus also exhibited low genetic diversity and the shortest genetic distances among populations. In contrast, H. stephanus, the species with the fewest reports from agricultural soils, was the most common and diverse species found. Results of this project may lead to better delimitation of lance nematode species in the United States by contributing to the understanding the diversity within this group.Lance nematodes ( Hoplolaimus spp.) are relatively long and robust vermiform nematodes with a distinct cephalic region and massive well-developed stylets  Thorne, 1935, H. magnistylus Robbins, H. stephanus Sher, H. seinhorsti Luc, 1958, and H. tylenchiformis von Daday, 1905 , corn (Zea mays L.) and soybean (Glycine max L.)  to estimate the genetic diversity and population structure of the species found. With this study, we expect to understand the diversity within this group and contribute to the elucidation of the delimitation of species of lance nematodes in the United States.Morphometric values of the “ancestral” species overlap considerably Table, Fig.1 , and useFortuner . In this Siddiqi  that areNematode populations were obtained from soil samples collected in 2011–2013 in agricultural fields, golf courses, and lawns of different regions in the United States Table. Lance nH. columbus, H. stephanus, H. magnistylus, and H. galeatus obtained during this study  , and 0.06 units of Taq DNA polymerase/mL), 0.5 μL of each primer (20 μmol/L), and 1 μL of DNA template. Thermal cycling conditions for the ITS marker included: initial denaturation at 95°C for 3 min, 33 cycles of 95°C for 45 sec, 59°C for 1 min 15 sec, 72°C for 2 min, and final extension at 72°C for 10 min. For the COI portion, the initial denaturation was set at 95°C for 3 min, followed by 33 cycles of 95°C for 45 sec, 50°C for 1 min 15 sec, 72°C for 2 min, and final extension at 72°C for 10 min. The amplified products were loaded onto a 1.5% agarose gel and visualized using GelRed™ . PCR products were purified using magnetic beads and sequenced in both directions with the ABI 3730 capillary sequencer (Applied Biosystems) in the DNA Laboratory (School of Life Sciences) at Arizona State University.The ITS region was amplified using forward primer Hoc-1f (5′-AACCTGCTGCTGGATCATTA-3′) and reverse primers: Hoc-2r (5′-CCGAGTGATCCACCGATAA-3′)  and Rotylenchus paravitis (JX015415) from GenBank. The original alignment for ITS consisted of 1050 bp, but several indels were detected. Therefore, divergent and ambiguously aligned positions were removed and conserved blocks selected using the software Gblocks v0.91b . All sequences were checked and edited manually, and chromatograms were inspected to confirm base calling and to identify recombination sites. Consensus DNA sequences were then aligned using ClustalW  or COI pseudogenes  in the software Modeltest v3.7 . Analysis of molecular variance (AMOVA) was conducted in Arlequin v. 3.11  networks in Network 4.5.1.0 , Florida (FL), and South Carolina (SC), on bermudagrass, St. Augustinegrass, and bentgrass, respectively. A second strongly supported clade  included specimens identified as H. magnistylus and was collected from Illinois (IL) and two localities in Tennessee (TN) on soybean (G. max) and corn (Z. mays). A third clade  comprised populations of H. stephanus from Nebraska (NE), Kansas (KS), Iowa (IA), Ohio (OH), and North Carolina (NC) collected on corn, bentgrass, and soybean. A fourth clade  was composed of individuals identified by morphology as H. concaudajuvencus and collected on bentgrass in Texas. Lastly, two specimens collected from maple tree (Acer sp.) in TN and classified according to morphological traits as H. sp. 1 (under description) formed a fifth clade  sister to all remaining clades. The NJ analysis was performed only with the COI dataset and revealed a topology mostly congruent with the ML and BI trees, with similar sequence segregation within clades. The main difference with the other trees was that the H. sp. 1 clade was placed as a sister lineage of the out-group, H. columbus.Phylogenetic reconstruction using the mtDNA sequences with ML and BI yielded trees with highly similar topologies and revealed five major clades Fig.. A firstHoplolaimus individuals were structured according to locality  for the COI region showed that ity Figs., 3. In tH. concaudajuvencus individuals were included in the H. magnistylus clade   ranged from 11.65% to 23.21% with a mean of 16.64%. The maximum interspecific distances (22.78% and 23.21%) were found between H. galeatus and H. columbus populations, and the minimum values (11.65% and 11.99%) were found between H. stephanus and H. magnistylus populations from NC and IL, and OH and IL. Within groups (clades), genetic divergence varied from 0 to 12.83% with an average of 6.26%. Therefore, a clear overlap between intra- and interspecific genetic distances was detected. The deepest levels of intragroup divergence that caused this overlap mainly occurred between populations of the H. stephanus clade: OH and NE (10.93–12.83%), NC and IA (10.55–12.83%), NC and KS (11.31–12.44%), and NE and KS (11.29–12.44%). Additional high levels of intraspecific genetic divergence (10.91–12.04%) occurred in the H. magnistylus clade between some populations from IL and TN. In general, the H. galeatus clade showed lower levels of intraspecific divergence ranging from 0 to 7.01%.Genetic distances (K2P) for COI between H. stephanus clade, distributed in three main geographic groups: one mostly composed of populations from NC and NE, which share two haplotypes among them; the second with unique haplotypes from OH populations; and the third comprised of two haplotypes from IA and one from KS populations. In the H. magnistylus network, the 12 haplotypes identified were divided into two groups: one composed of haplotypes from populations collected in IL, and the second of haplotypes from TN populations. For H. concaudajuvencus and H. galeatus, fewer haplotypes were identified . For H. concaudajuvencus, all were unique haplotypes from TX populations. Hoplolaimus galeatus was the only species that did not show correlation with geographic regions, having a single haplotype shared by several individuals from SC, AL, and FL, with the remaining haplotypes being from populations collected in SC.Haplotype networks for COI were congruent with the phylogenetic reconstructions, showing segregation of the mitochondrial haplotypes according to locality Fig.. SixteenH. stephanus was the most widespread and with the most diverse lineage, distributed from NE, KS, IA, and OH to NC  and H. magnistylus (π=0.052). Haplotype diversity (Hd) was similar for H. stephanus and H. magnistylus   Table.ST value   and very low variation within populations (5.82%). However, higher variation (76.79%) was recovered when AMOVA was performed across geographic regions, suggesting strong genetic differentiation among sampling locations. With regard to each morphospecies, the strongest genetic subdivision was found within the H. stephanus populations (85.11%), whereas populations of H. galeatus and H. magnistylus were less differentiated. The strong genetic differentiation in H. stephanus and the high intraspecific variability caused overlap between intra- and interspecific K2P genetic distances. Therefore, AMOVA was performed for H. stephanus with different combinations of populations to determine which grouping better explained the variability among groups. Results from the AMOVA showed the highest variation (83.10%) when populations of H. stephanus were partitioned as NC, NE, OH, and KS+IA. Based on this combination of populations, new K2P genetic distances were estimated considering these populations as different genetic entities (interspecific variability), and a barcoding gap was detected for this species.Results from the 112 haplotypes analyzed with AMOVA suggest strong genetic differentiation in all species (clades) as explained by the high F01) Table. AMOVA aHoplolaimus species have resolved some phylogenetic relationships within the genus using the internal transcribed spacer (ITS1) . Genetic divergence between allopatric populations depends on the timing and level of gene flow between them . These groups also showed large K2P genetic distances that overlapped with the interspecific genetic distances, and AMOVA was better explained when the populations were partitioned in the same groups. However, the fragmentation in the nuclear marker for H. stephanus was not consistent with the one for COI, ITS1 gene partitioned IA, KS and NE populations in one group, and OH and NC populations composed the other group. Therefore, additional morphological evidence and molecular markers should be considered to confirm cryptic speciation for H. stephanus. Because almost all sampling localities of H. stephanus had their private haplotypes, it is likely that unsampled regions will also have their own lineages. If so, we are confronted with a multitude of lineages which are indistinguishable based on morphology and difficult to integrate into the framework of classical taxonomy. One possibility is to interpret H. stephanus as a polytypic species with extreme population differentiation.Hoplolaimus. The COI gene resolved species in highly supported clades and showed deep variation within species, mainly correlated with geographic origin of the populations, indicating that this portion of the COI gene is adequate to define species and to study the genetic structure. Furthermore, we observed no heteroplasmy  as evidenced by clean chromatograms with the absence of double peaks. Heteroplasmy has been reported in plant-parasitic nematodes like M. chitwoodi , a conserved nuclear coding gene that can be used to investigate recent divergences due to the presence of rapidly evolving introns , currently undescribed, was collected on maple. This is the first report for H. concaudajuvencus in TX on bentgrass and for H. magnistylus on corn in IL. Ours is also the first report for H. stephanus in OH and KSon bentgrass, and in IO and NE on corn. Our group had recently published a first report of H. magnistylus in TN on soybean, corn, and cotton  and showed the shortest genetic distances among its populations. In contrast, H. stephanus, the species with the fewest reports from agricultural soils, was the most common and diverse species found in this study. Sher  host. These three publications total the extent of the research available for H. stephanus. Considering it appears to be the most widely distributed lance nematode species in agricultural soils in the United States, further work is needed to study its biology, ecology, pathogenicity, and economic thresholds.To our surprise, dy. Sher  describes et al.  publishes et al.  found th


MBL2) influence the stability and serum concentration of the protein. Epidemiological studies have shown that MBL2 variant alleles are associated with susceptibility to and the course of different types of infectious and inflammatory conditions. However, it has been suggested that these alleles are maintained in different populations due to selected advantages for carriers. We investigated the MBL2 allelic variation in indigenous individuals from 12 different West Central South America localities spanning from the desert coast, high altitude Andean plates and the Amazon tropical forest within the territories of Peru (n = 249) , and Ecuador (n = 182) . The distribution of MBL2 genotypes among the populations showed that the defective variant LYPB haplotype was very common. It showed the highest frequencies in Puno (Taquile (0.80), Amantani (0.80) and Anapia (0.58) islander communities of the Lake Titicaca), but lower frequencies of 0.22 in Junin  and Ucayali , as well as 0.27 and 0.24 in the Congoma and Cayapa/Chachis populations in the Amazonian forest in Ecuador were also observed. Our results suggest that the high prevalence of the MBL2 LYPB variant causing low levels of functional MBL in serum may mainly reflect a random distribution due to a population bottleneck in the founder populations.Mannose-binding lectin (MBL) is one of the five recognition molecules in the lectin complement pathway. Common variant alleles in the promoter and structural regions of the human MBL gene ( Mannose-binding lectin (MBL) is a pattern recognition molecule that recognizes sugars such as terminal mannose and N-acetyl-glucosamine groups common on the surface of various microorganisms MBL gene is located at chromosome 10 (10q11.2-q21). In lower primates and in mammals there are 2 functional MBL genes while in higher primates and in humans there is only one functional MBL gene (MBL2) The In the general population the protein has been shown to be of particular importance in protection against bacterial and viral infections during the vulnerable period of infancy between 6 and 18 months of age prior to establishment of specific immune protection provided by the adaptive immune system A and the structural variants are called B (Gly54Asp) (rs1800450); C (Gly57Glu) (rs1800451) and D (Arg52Cys) (rs5030737) respectively. These variants are dominant in the Mendelian sense and the mutations are located at the Cys- and Gly- collagen-like domain regions and even in heterozygotes the levels of functional serum MBL are diminished 10 times because the allele hampers the oligomerization of the protein, which affects the interaction with the MASPs and the opsonization processes HYPA>LYQA>LYPA>LXPA and 3 structural variant haplotypes LYPB, LYQC and HYPDThe genetic basis of reduced serum MBL concentration has been explained at the molecular level by the identification of 3 missense variant alleles in exon 1, differentially distributed according to ethno-geographical location MBL2 alleles  in most populations studied and their association with infectious diseases has led to the hypothesis that the presence of these alleles represent a balanced genetic system with selective advantages for heterozygotes The relatively high prevalence of defective low MBL2 alleles and haplotypes in different indigenous people of South America we have investigated populations situated in different regions at the Pacific desert coast, high altitude Andean plates and the Amazonian forest within the territories of the Countries of Peru and Ecuador.To get insight to the distribution of the The level of MBL serum concentrations in the tested Peruvian samples according to the accompanying genotypes are shown in MBL2 haplotypes were detected. The exact test for observed and expected heterozygosity did not show any deviation from the Hardy–Weinberg equilibrium model (HWE) among all studied populations .In the investigated Peruvian and Ecuadorian populations we found 7 globally reported haplotypes. No new MBL2 haplotypes revealed that the LYPB was common in all of the studied populations, but that the variants LYQC and HYPD were virtually absent (LYPB haplotype ranged from 0.22 (0.10 homozygous) in the Peruvian departments of Junin  and Ucayali , as well as 0.27 (0.03 homozygous) and 0.24 (0.05) respectively in the Congoma and Cayapa/Chachis population at the Amazonian forest in Ecuador. The highest frequencies were recorded at the islands of the Lake Titicaca (3800 m over the sea level in the Andes), Taquile and Amantani with a frequency of 0.80 (0.64 of homozygous), and also at Anapia with a frequency of 0.58.Examination of y absent . The lowHYPA and LYPB are the most prevalent. Both Eskimos at the Northern, and Mapuche and Chiriguanos at the Southern extremes of the Americas have shown these haplotypes as the most represented in their population It is noticeable that all the American subpopulations analyzed here and in previous studies showed that the haplotypes MBL2 haplotype frequencies among the Peruvian and Ecuadorian populations and it showed a moderate variation between them . The population pairwise stΦ analyses showed statistically significant differentiation  was performed from ntiation  and numbMBL is a recognition molecule present in serum of importance for first line host defence. It was the first recognition molecule to be discovered in the lectin complement pathway, which now has turned out to comprise at least 4 other molecules with distinct and overlapping functions MBL2 is the presence of three missense variant alleles causing low levels and dysfunctional folding of MBL that are clustered in exon 1. Our analyses of the MBL serum concentration and the MBL oligomerization pattern in native Americans corroborate this notion  D allele is less frequent than the B and C alleles and has been found in Caucasian and North-East African populations with an allele frequency of 4–6%, respectively A striking observation with regard to s notion  and 2. TTo explain this high prevalence in some populations a possible advantageous effect of the variant alleles has been proposed, suggesting that they have been evolutionary kept by its capability to avoid certain infections or diminish the effect of complement driven inflammatory reactions. However, this assumption has mounted conflicting results when tested in different populations and is still a matter of debate B allele was present at very high frequencies in all the South American populations analyzed and propose that this pattern is extended to most populations of the continent, as already shown in Southern Argentina populations and Eskimos B was the most prevalent compared with the “normal” A allele, reaching allele frequencies up to 80% and homozygosity frequencies of around 64% in the islands of Taquile and Amantani in the Lake Titicaca.We corroborated that the MBL2 than any other population from other continent registered so far. After the observation of a major prevalence of this variant defective allele it is tempting to propose a still unknown protective effect is being exerted in these islands as well as the island of Anapia and in the Mapuche population with frequencies of LYPB reaching 0.58 and 0.46 respectively. However, it is remarkable that the island “Los Uros”, which is geographically very close to Taquile and Amantani, the LYPB haplotype has a frequency of only 0.35, which is difficult to conceal with the hypothesis of a specific selective effect. Thus, our hypothesis regarding “Los Uros” and the groups of Taquile, Amantani and Anapia is that the difference is caused by a genetic founder effect instead of a genetic advantage.We find that several South American populations have higher frequencies of a defective allele of Fst = 0.18, p<0.01). In addition we have some evidence with mtDNA and microsatellite polymorphic markers that the Los Uros community is at least partially genetically differentiated in relation to their neighbours Historical and anthropological evidence suggest that Taquile and Amantani were repopulated after the Spanish conquerors expulsed the original populations and imposed new settlers in these islands in mid XVI century virgin soil epidemics) It is conceivable that the microbial challenge that met the first settlers first in North America and then subsequently at the Central and South American continent thousands of years ago may have selected different alleles to become prevalent combined with bottleneck effects. It is known that there are at least 2 events in South America history showing bottleneck effects, first, the peopling the Americas about 18000 years ago by a small effective population size (estimated between 70 to 5000) B allele being the most prevalent in some groups. It is also interesting to corroborate that all the previous and present Native American population studied have a prevalence of both LYPB and HYPA and the presumed intermediary LYPA haplotype is rather scarce. Based on our study it is most likely that this reflects a random distribution due to population bottleneck effects in the founder population. But it cannot be excluded that part of the observed distribution could be due to a selection against specific pathogens found among the ancestors of the autochthonous Americans or due to specific exposures before, during and after the Spanish invasion. In any case, the observed genetic pattern suggest that this co-prevalence of HYPA and LYPB was built in the Asian migrants before the passage to the American continent. A comparative analysis of Pre Columbian ancient DNA and modern indigenous populations would help to solve that enigma.The South American populations studied here and probably most Native American populations, have a very high prevalence of defective variant A total of 429 individuals of allegedly autochthonous American and admixed populations from different climatic and altitudinal regions of Peru and Ecuador were investigated. The majority of samples were collected in relatively isolated villages of the native participants, who were interviewed in order to assess the birthplace and ethnicity of their parents and grandparents, and to certify that at least three preceding generations of their ancestors had been living in the same locality. Relatives to the 3rd degree were avoided. Samples were collected from individuals living in different regions of Peru: Departments of Loreto , Ucayali , Lambayeque , Junin and Ayacucho  and Puno . Samples from the Department of Puno were taken from 2 islands speaking Quechua  and from 2 islands speaking Aymara . We also collected 182 samples from the region of Esmeraldas (Río Cayapa) and Santo Domingo de los Colorados in the Amazonian forest of the Republic of Ecuador. Five ml of blood was drawn to obtain DNA using standard protocols from CGBM (USMP) and Department of Biology (Universita Tor Vergata) laboratories in the few cases where also serum was obtained which were isolated and snap frozen otherwise DNA samples were extracted from buccal swabs using standard procedures.Sampling was done after verbal and written informed consent. The consent has been recorded in data sheets for each participant. The approvals of the project and the information procedure as well as ethical approval were given by Centro de Genética y Biología Molecular (CGBM), Facultad de Medicina Humana, Universidad San Martín de Porres, Lima, Peru, local ethical committee and institutional review board.MBL2 single SNPs in the form of the structural variants named B (codon 54), C (codon 57), and D (codon 52) as well as the regulatory variants named H/L (−550), X/Y (−221), and P/Q (+4) were typed by PCR using sequence specific priming (PCR-SSP), which includes 12 reactions according to the method described in MBL2 gene. The PCRs were performed essentially as previously described LXPA, LYPA, LYQA, and HYPA , and three “novo variants” haplotypes; LYPB, LYQC, and HYPDProducts of the PCR amplification were individually loaded in a 2% agarose gel, stained with ethidium bromide, visualized over a UV transilluminator and recorded in a photodocumentation system. MBL serum concentrations and SDS-PAGE (NuPAGE 3–8%) and western blotting of 7 and 3 sera, respectively from genotyped native Peruvians were performed following standardized protocols MBL2 genotypes. Haplotype frequencies were also obtained by direct counting and tests of population structure and differentiation using Arlequin 3.5 software stΦ distances into Reynolds' coancestry coefficients in Arlequin, which were used in non-metric MDS analyses (nmMDS) calculated with PAST software (http://folk.uio.no/ohammer/past) HWE and the exact test using Markov chain was performed for


AbstractCeratitiscosyra is an important agricultural pest negatively affecting the mango crop production throughout Africa and also feeding on a variety of other wild and cultivated hosts. The occurrence of deeply divergent haplotypes, as well as extensive morphological variability, previously suggested possible cryptic speciation within Ceratitiscosyra. Here we provide the first large-scale characterisation of the population structure of Ceratitiscosyra with the main objective of verifying cryptic genetic variation. A total of 348 specimens from 13 populations were genotyped at 16 polymorphic microsatellite loci. Hardy-Weinberg equilibrium (HWE) deviations were observed in 40.4% of locus-population combinations and suggested the occurrence of genetic substructuring within populations. Discriminant Analysis of Principal Components (DAPC) showed genetic divergence between the vast majority of vouchers from Burundi and Tanzania (plus a few outliers from other African countries) and all other specimens sampled. Individual Bayesian assignments confirmed the existence of two main genotypic groups also occurring in sympatry. These data provided further support to the hypothesis that Ceratitiscosyra might include cryptic species. However, additional integrative taxonomy, possibly combining morphological, ecological and physiological approaches, is required to provide the necessary experimental support to this model.The fruit fly  Ceratitiscosyra , is possibly the most important indigenous pest of mango throughout sub-Saharan Africa. It is estimated that Ceratitiscosyra can reduce the mango crop yield between 20 and 30%, and the damage this pest causes affects the quality and market value of the fruit at both local and international markets  in recent years , see Anacardiaceae, Annonaceae, Apocynaceae and Rubiaceae among others  Hochst., as an alternative host when mango is not available (Ceratitiscosyra shifts to soursop (Annonamuricata Linnaeus) out of the mango season  and Kenya (two sampling locations) and by two Ceratitiscosyra outliers sampled at the coast of southern Kenya (Shimba Hills). Surprisingly, these two individuals, sharing the same COI haplotype, were separated from the main haplotype group by 52 mutational steps. Also on morphological grounds, Ceratitiscosyra has been the subject of confusion. Various taxa (now considered synonyms) have been described as separate species or varieties based on differences in cephalic and leg chaetotaxy and mesonotal patterns  were collected in Africa from 2000 to 2012 , observed and expected heterozygosity  and deviations from the Hardy-Weinberg equilibrium (HWE). The function genotype_curve of the R package POPR  with correlated allele frequencies  and the parameter of the Dirichlet distribution of allelic frequencies (λ) separately inferred for each population. We used STRUCTURE HARVESTER 0.6.94 (STRUCTURE 2.3.4  was usedR 0.6.94  to inferR 0.6.94  of each R 0.6.94  and visuR 0.6.94 .Ceratitiscosyra was adequately sampled by the 16 microsatellites markers used (see supplementary file SF 2: Genotype accumulation curve). The total scored number of alleles  ranged from 67 (in the Burkina Faso population) to 124 (Mozambique), with an average proportion of missing data per population ranging from 2.2%  to 30.9% . Hobs ranged from 0.372  to 0.504 (South Africa), while Hexp from 0.432  to 0.637 (Tanzania) . DAPC considered the populations as a priori defined groups and was based on 90 PCs. Stressing the ordination of points by using a prior group only allowed a better resolution of the population from Burundi and, possibly, of that from Tanzania. The latter was clearly separated from the other populations only when excluding 4 STRUCTURE outliers from DAPC (see below). Confidence ellipses of all other populations were largely overlapping  resolved specimens from South Africa (100%), Mozambique (96.9%), Malawi (93.1) and Ethiopia (84.6%) in a first group and specimens from Burkina Faso (100%), Mali (100%), Nigeria (96.2%), Sudan (87.5%) and Ivory Coast (88.9%) in a second group. Populations from Senegal and Kenya included specimens that were assigned in part to the first group  and in part to the second (60.7% and 31.3%).The STRUCTURE analysis of the entire dataset  belong to the first of these two groups, all other specimens to the second. Specimens from the two groups were also found sympatrically in a number of populations from Kenya, Senegal, Sudan, and Tanzania. Interestingly, the two Ceratitiscosyra outliers described by The morphospecies Ceratitiscosyra.Further studies are needed to verify if specimens from the two genotypic clusters are also morphologically, ecologically and / or physiologically different and to which extent the two groups are connected by gene flow. A preliminary screening of thorax patterns of the samples used in this study  did not reveal straightforward morphological differences between groups. Wing morphometrics  might prCeratitiscosyra, including Annonaceae (such as the introduced soursop) or Anacardiaceae (including the indigenous marula or the introduced mango). An intriguing hypothesis is that the two different Ceratitiscosyra types might also have different host preferences, similarly to what has been observed by Rhagoletispomonella . A separate host range characterization for the two types might provide useful information and help to understand if the observed genetic split has a recent evolutionary history (possibly related to the introduction of novel hosts in Africa) or a deeper evolutionary origin.A wide variety of hosts have been described for PageBreakthe notable exception of Sudan  and of Kenya and Senegal . Morphological differences were considered by The sequential Bayesian assignment of genotypes also helped to disentangle the effects of cryptic speciation and of population structure within each of the genotypic groups. Specimens from Burundi and Tanzania are, to a less extent, genetically divergent, and among samples from the other African countries, two groups can be further resolved. In the latter case, specimens could be roughly subdivided between Western African samples  and Eastern / Southern African samples  with Ceratitiscosyra. Additional integrative taxonomy, possibly combining morphological, ecological and physiological data (e.g., see Marked and sympatric genetic splits are compatible with the occurrence of presumptive cryptic species, within


Bufo bankorensis using mtDNA sequences among populations located in different regions of Taiwan, characterized by different climates and existing under extreme conditions when compared available sequences of related species B. gargarizans of mainland China.To comprehend the phylogeographic patterns of genetic variation in anurans at Taiwan Island, this study attempted to examine (1) the existence of various geological barriers ; and (2) the genetic variation of B. bankorensis and B. gargarizans, identified three distinct lineages. Furthermore, the network of mtDNA D-loop gene (564 bp) amplified  from Taiwan Island indicated three divergent clades within B. bankorensis , corresponding to the geography, thereby verifying the importance of the CMRs and Kaoping River drainage as major biogeographic barriers. Mismatch distribution analysis, neutrality tests and Bayesian skyline plots revealed that a significant population expansion occurred for the total population and Clade W, with horizons dated to approximately 0.08 and 0.07 Mya, respectively. These results suggest that the population expansion of Taiwan Island species B. bankorensis might have resulted from the release of available habitat in post-glacial periods, the genetic variation on mtDNA showing habitat selection, subsequent population dispersal, and co-distribution among clades.Phylogenetic analyses of the dataset with mitochondrial DNA (mtDNA) D-loop gene (348 bp) recovered a close relationship between B. bankorensis mtDNA sequences were first evident in this study. The divergent genetic clades found within B. bankorensis could be independent colonization by previously diverged lineages; inferring B. bankorensis originated from B. gargarizans of mainland China, then dispersal followed by isolation within Taiwan Island. Highly divergent clades between W and E of B. bankorensis, implies that the CMRs serve as a genetic barrier and separated the whole island into the western and eastern phylogroups.The multiple origins (different clades) of  Organisms and populations commonly vary in a highly regular fashion with geographic gradients of latitude and altitude, and population differentiation is the result of vicariance and dispersal Bufo bankorensis  is widely dispersed across all of Taiwan Island at altitudes between 0 and 3000 m B. bankorensis belongs to the family Bufonidae, which is one of the most species rich (with more than 350 species) and widely distributed amphibian families. According to previous studies, the classification of B. bankorensis has been generally debated. Some authors have recognized it as a distinct species B. gargaizans, which is distributed throughout mainland China B. gargarizans and B. bankorensis were classified as two subspecies present in Taiwan by Kawamura B. bankorensis was reclassified as a distinct endemic species of Taiwan Island by analysis of numerous morphometric characters B. bankorensis has been included in the B. gargarizans species complex  as related species were also collected and analyzed , Yangmingshan National Park (permission number 20110118) and Yushan National Park (permission number 1010210), respectively. analyzed . SamplesGAG CCT TCC CTT GGT TTA AGA GTA) and reverse (Bu-con-16582R: CCA GGT TAA GGT CTT TAA GGT ACC AG) (designed in this study). PCR amplifications were carried out in a 25 µl reaction volume through 35 cycles of denaturing at 94°C for 30–45 sec; annealing at 56°C for 30–45 sec, and 72°C extension for 30–45 sec. The reaction products were mixed with Novel juice  and separated via gel electrophoresis in 1.5% agarose gels. The gels were stained with ethidium bromide, and the desired DNA band was excised and eluted using an agarose gel purification kit . The PCR products were then subjected to cycle sequencing reactions conducted by Genomics Biotec Co., Ltd. (Taiwan) using an ABI PRISM 3730XL sequencer with the BigDye Terminator kit (Applied Biosystems). All sequences have been deposited in GenBank under the following inclusive accession numbers: KF692208-KF692283.Total DNAs were extracted using genomic QuickExtract DNA Extraction Solution  following the manufacturer's manual. A section of the mtDNA control region (D-loop) was sequenced following PCR amplification with the following primers: forward . The haplotype genealogy of B. bankorensis was separately reconstructed by maximum likelihood (ML) tree, neighbor-joining (NJ) tree and Bayesian analysis using PhyML 3.0 Partial sequences of the mtDNA D-loop gene were aligned using the program Clustal X v1.81  GenBank , Table 2B. bankorensis from 27 populations in Taiwan and 4 individuals of B. gargarizans from Shanghai (mainland China) were analyzed. The numbers of haplotypes (N) and the values of haplotype diversity  was significantly higher than the global GST (0.312), providing evidence of the existence of phylogeographic structure because closely related haplotypes would be detected more frequently than that are less closely related in the same area GST and NST was carried out using DnaSP v5.0 The second dataset was limited to the samples collected of this study. Partial sequences (564 bp) of 279 individuals of rsity h;  and nuclrsity h;  were calrsity h; . The numB. bankorensis, Tajima's D statistic Fs test Fs and Tajima's D values were evaluated using the coalescent algorithm in DnaSP v5.0 To analyze the population demographic history of FST values and their statistical significance between population pairs, i.e., the significance of population differentiation, with the following settings: 1000 permutations for significance and 10,000 steps in the Markov chain. When multiple comparisons were performed, the P values were adjusted using the sequential Bonferroni procedure FCT). These analyses were performed based on 1000 simulated annealing steps, and comparisons with the maximum indicators of differentiation  were conducted when the program was instructed to identify K  =  2–10 partitions for each sampling area within each analysis. The Mantel test B. bankorensis was calculated using AIS. Using geographic data  and the genetic distance scores calculated in AIS, a three-dimensional landscape, with genetic distance indicated by the z dimension was created. The output 3-dimensional values were projected onto a map of Taiwan Island to perform comparisons between the topographic and simulated genetic landscape.The program Arlequin v3.5 Asymmetrical gene flow was observed among three regions: the western region, including localities 1–18; the eastern region, including localities 20–27; and the southern region, including locality 19. To estimate contemporary and historical gene flow among the three regions, maximum likelihood inference was performed using MIGRATE software, v 3.2.6 Bufo mtDNA, and absolute TMRCA values were subsequently obtained The software BEAST v1.7.5 B. gargarizans in mainland China retrieved from NCBI GenBank  Lineage II, including B. gargarizans from the Shanghai, Hubei, and Shandong in mainland China and B. bankorensis form Clade W in Taiwan; (3) Lineage III, including B. gargarizans from the Fujiang and Jiangxi in mainland China and B. bankorensis form Clade E and S in Taiwan. B. gargarizans from mainland China were split into two lineages (II & III) approx. 1.349 million years apart. B. bankorensis was also found in these two lineages. The second dataset was limited to the samples collected for this study. The mtDNA D-loop (564 bp length) of 279 individuals of B. bankorensis from 27 localities in Taiwan and 4 individuals of B. gargarizans from Shanghai (mainland China) were analyzed. The alignment of all D-loop sequences revealed 80 unique haplotypes and the minimum-spanning network was reconstructed based on mutational changes   .h) within each population are presented in h) among the 279 samples was estimated to be 0.973, and the mean nucleotide diversity (π) was 0.026  and haplotype diversity . Most of the pairwise FST values were significant (P < 0.05). The overall standardized FST value among all samples was 0.790. In the hierarchical analysis, all localities were separated into two groups and tested via AMOVA. In the first group was tested CMRs geographic division, most of the molecular variance (80.10%) was corresponded to variation between groups, while 12.50% was attributed to variation within populations, and 7.40% of the molecular variance was related to variation among populations within groups. In the second group was tested five biogeographic zones, most of the variation was attributed to between group variation (75.37%), while 18.36% corresponded to the variation within populations, and 6.27% of the molecular variance was related to the variation among populations within groups : KT  was assigned to one group, and the remaining populations formed two groups, corresponding to the western region  and the eastern region . Most of the remaining variation was found within populations (12.57%) or among populations within groups (4.88%). All of the variance components were significant (P  =  0.000). The Mantel test  was detected a very weak correlation between genetic distances and geographic distances. This result indicated that localities within the same region are comparatively homogenous and that localities in different regions present high genetic differentiation. An analysis of the shape of the genetic landscape for B. bankorensis was calculated using AIS The genetic variation of n groups . The spaW→E  =  106.63, MW→S  =  87.87) than it was in the opposite direction . Furthermore, the similar asymmetrical direction and strength of individual migration toward the south was also detected in southeast Taiwan . Accordingly, the mtDNA evidence, characterized by a distinct inheritance mode, indicated that the western region acts as a source, while the populations of the eastern and southern regions act as a sink  calculated using MIGRATE indicated asymmetrical gene flow among regions over the long term at both sides of CMRs. The results revealed that the degree of historical gene flow from the western region to the eastern and southern regions was greater  than has been found in other studies on Bufo species from mainland China based on D-loop sequences, e.g., B. gargarizans (mean π =  0.047) h and relatively high π value (0.973 and 0.026) in the total population appears to reflect the mixing of differentiated clades analyzed together h and π values  obtained for the western region  were similar to those for the eastern region  (0.919 and 0.009)  . ConcernB. bankorensis formed a monophyletic clade with B. gargarizans samples from northern China , while the clades E and S of B. bankorensis in the linage III clustered together with B. gargarizans samples from southern China (Fujiang and Jiangxi) composed another monophyletic lineage. Accordingly, this result suggested a colonization history of B. bankorensis in Taiwan that could be explained by two distinct origins: populations on the west side of CMRs originated from northern China, while populations on the east side of CMRs initiated from southern China , which indicates a high degree of genetic differentiation among populations of B. bankorensis. The genetic differentiation among B. bankorensis populations showed a weak pattern of isolation by distance , as expected for a toad separated by the CMRs, revealing that the isolation by distance pattern might not be the driving force for the differentiation of the identified clades. Although isolation by distance is typically considered to be a consequence of restricted contemporary gene flow, differentiation over distance can also result in an interplay between modern and vicariant forces, because particularly historical events are more likely to be detected at larger geographical scales B. bankorensis are nested with B. gargarizans lineages from mainland China. Furthermore, the fact that Clades E and W of B. bankorensis are not closely related indicates that they represent distinct evolutionary origins. The divergent genetic clades were found within B. bankorensis thus represent species polyphyly as a result of independent colonizations by previously diverged lineages of B. gargarizans complex. This is consistent with our recent study of genetic structure of B. bankorensis cyt bBamHI and cut by TspRI) is most likely B. gargarizans, a second one  is B. bankorensis, and a third one  may be a new subspecies. B. bankorensis has been historically recognized as one endemic species B. gargarizans and is restricted to Taiwan, however the molecular evolutionary relationships fail to support this taxonomy. Hence, the taxonomic status of B. bankorensis and B. gargarizans is still unclear and needs further exploration.The average B. bankorensis can be best partitioned into three groups. These three groups correspond to topological barriers plus the major mtDNA clades identified in B. bankorensis. A large proportion (82.5%) of the genetic variability found in B. bankorensis can be explained by variance among groups , which is similar to the previous results of B. bankorensis populations, which is a pattern that could occur following population expansion B. bankorensis contains signatures of demographic expansion consistent with Pleistocene glacial retreat. Specifically, the demographic and genetic variation analyses of total populations and Clade W provide a strong support for the existence of recent population expansions, represented by significantly negative Fs values and unimodal mismatch distributions with a low Rg index  than populations in western Taiwan (B. bankorensis, ranging from the sea level to above 3,000 m in altitude, population expansion is expected to have occurred according to habitat release during the glaciated period, especially in the western Taiwan is associated with a significant decline of the sea level. In contrast, the eastern Taiwan is surrounded by the Mariana Trench, where a dramatic decline in depth would further constrain the rapid outward colonization of B. bankorensis, hence greatly reducing the probability of typical population dynamics occurring during glacial-interglacial periods. The CMRs of Taiwan approach to an elevation of nearly 4,000 m, rising steeply from the eastern coast and giving way to a broad western plain. The land mass on the eastern side of Taiwan, which faces the margin of the Pacific Ocean, was not considerably altered during glacial–interglacial periods, resulting in limited range expansion for the eastern clade. In contrast, the decrease in sea level on the western side of the island caused the Taiwan Strait to dry up. Consequently, the habitat of B. bankorensis was reconnected with the mainland China, giving rise to new ecosystem through gene flow by means of re-migration and/or population expansion.Nucleotide and haplotype diversities can provide information on evolutionary histories. Our results revealed high haplotype diversity and low nucleotide diversity in the tested Rg index , and theRg index . In contn Taiwan , which i


Pagophilus groenlandicus Erxleben, 1777) have a biogeographic distribution based on four discrete trans-Atlantic breeding and whelping populations located on “fast ice” attached to land in the White Sea, Greenland Sea, the Labrador ice Front, and Southern Gulf of St Lawrence. This East to West distribution provides a set of a priori phylogeographic hypotheses. Outstanding biogeographic questions include the degree of genetic distinctiveness among these populations, in particular between the Greenland Sea and White Sea grounds. We obtained complete coding-region DNA sequences  for 53 seals. Each seal has a unique mtDNA genome sequence, which differ by 6 ~ 107 substitutions. Six major clades / groups are detectable by parsimony, neighbor-joining, and Bayesian methods, all of which are found in breeding populations on either side of the Atlantic. The species coalescent is at 180 KYA; the most recent clade, which accounts for 66% of the diversity, reflects an expansion during the mid-Wisconsinan glaciation 40 ~ 60 KYA. FST is significant only between the White Sea and Greenland Sea or Ice Front populations. Hierarchal AMOVA of 2-, 3-, or 4-island models identifies small but significant ΦSC among populations within groups, but not among groups. A novel Monte-Carlo simulation indicates that the observed distribution of individuals within breeding populations over the phylogenetic tree requires significantly fewer dispersal events than random expectation, consistent with island or a priori East to West 2- or 3-stepping-stone biogeographic models, but not a simple 1-step trans-Atlantic model. Plots of the cumulative pairwise sequence difference curves among seals in each of the four populations provide continuous proxies for phylogenetic diversification within each. Non-parametric Kolmogorov-Smirnov (K-S) tests of maximum pairwise differences between these curves indicates that the Greenland Sea population has a markedly younger phylogenetic structure than either the White Sea population or the two Northwest Atlantic populations, which are of intermediate age and homogeneous structure. The Monte Carlo and K-S assessments provide sensitive quantitative tests of within-species mitogenomic phylogeography. This is the first study to indicate that the White Sea and Greenland Sea populations have different population genetic histories. The analysis supports the hypothesis that Harp Seals comprises three genetically distinguishable breeding populations, in the White Sea, Greenland Sea, and Northwest Atlantic. Implications for an ice-dependent species during ongoing climate change are discussed.Phylogenomic analysis of highly-resolved intraspecific phylogenies obtained from complete mitochondrial DNA genomes has had great success in clarifying relationships within and among human populations, but has found limited application in other wild species. Analytical challenges include assessment of random versus non-random phylogeographic distributions, and quantification of differences in tree topologies among populations. Harp Seals ( Gadus morhua) have a much more ancient species structure than previously suspected, with coalescence during the Wisconsinan glacial, and major clade differentiation at the peak of the Sangamon / Würm interglacial rather than subsequent to the last Recent glacial [Gadus chalcogrammus), includes geographically isolated populations originally supposed to be of recent origin that are shown by mitogenomic analysis to be ancient [Coregonus) are discrete genomic clades [Orcinus) correspond to discrete geographic populations including some assignable to subspecies [Balaenoptera) to what appear to be recognizable species [Analyses of multiple complete intraspecific mtDNA genomes were first applied to humans to clarify the historical emergence of modern humans and their subsequent migrations Out of Africa . The acc glacial . The maj ancient . In contc clades . Major pbspecies , and in  species .per se is uninformative, as the entire variance occurs among individuals with respect to the total (FST = 1.0). AMOVA based on nucleotide divergences between haplotypes (ϕST < 1.0) may partition variance among populations  or groups (ϕCT > 0.0), but does not capture phylogenetic structure within and among populations. Similarly, row by column tests of the relative abundances of major clades across populations cannot take into account phylogenetic relationships either within or among those clades [a priori hypotheses.Standard methods of phylogenetic analysis and (or) quantitative assessment of within-species mtDNA population structure founder when every individual is a distinct branch. Hierarchal analysis of molecular variance (AMOVA) among haplotypes e clades . Evaluate clades ,8 or nese clades , but NCAe clades . We requPagophilus groenlandicus Erxleben 1777) are endemic to the North Atlantic and adjacent Arctic waters  at Jan Mayen Island versus those in the Northwest Atlantic [Relationships among the four populations have been examined by means of cranial measurements, underwater vocalizations, and a variety of genetic methods including allozyme and minisatellite analysis (reviewed in ). CollecAtlantic .a priori hypotheses of phylogeographic relationships. With mitogenomic data that distinguish each individual as a discrete “twig” in the intraspecific family tree, it is possible to evaluate these hypotheses quantitatively. The results show that fine distinctions among populations can be made with mitogenomic data, which with respect to AMOVA methods offer an improved view of relationships among breeding areas that bears on biological and ecological questions of genetic connectivity among populations.Besides a conventional AMOVA, we introduce here two novel methods for analysis of intraspecific gene trees, as applied to an examination of the mitogenomic structure of Harp Seal breeding areas. These are a Monte Carlo simulation of phylogeographic distribution, and a non-parametric analysis of cumulative pairwise mismatch distributions between populations. The discrete, ordered geographic distribution of the Harp Seal breeding and whelping areas provides several Each of the 53 seals had a unique 15,825 bp genome sequence, which differed by 7 to 106 substitutions (mean = 50.9 ± 19.8) among 588 variable sites . We desiA, B, C, D, E, and F) and a further nine sub-groups or pairs within these at ≥95% , five subgroups designated A1-A5 are supported in 84 ~ 99% of replicates, as are two subgroups each in D and E. Parsimony analysis based on 243 phylogenetically informative sites identified n = 57 minimum-length trees of length L = 808, and bootstrap analysis identified the same 34 groups in the NJ analysis as clades, including the six primary groups in 87 ~ 99% of replicates (results not shown). Unresolved relationships in the topology of the phenetic and cladistic trees occur only within the A clade, in particular basal relationships within A3 and A4 and the relative branching order of A2 and A3 with respect to A4 / A5. In general, NJ relationships supported in <67% are unresolved in the strict-consensus of the 57 L = 808 MP trees. A Bayes analysis also produces the same topology, with posterior probabilities > 0.95 supporting the nodes above, as well as among designated subgroups within clade A  again identifies the same topology as the NJ and MP analyses, with nodes A-F and A1-A5 all supported at >95%, again with unresolved relationships only within A4 , where T = time in KY and d = ML-corrected substitutions . We calculated AMOVAs based on nucleotide distances (ϕ statistics) among haplotypes for all pairwise combinations of breeding grounds  but significant (p <0.05), except in Model IV. None of the hierarchal Models II ~ IV has a significant among-group ϕCT. Among-group variance components are dominated by the relative distinctness of WS, but even in Model IV with ϕCT > 0.10 this does not approach significance (p > 0.25).Because every seal has a distinct haplotype sequence, hierarchal AMOVA based on haplotypic diversity  grounds , and forc models . These aa priori hypotheses corresponding to the east-to-west arrangement of Harp Seal breeding grounds. Where the AMOVA is based on pairwise distances, it also cannot capture phylogenetic differences among breeding groups in their distributions as haplotypes across a gene tree topology. We therefore developed a novel Monte Carlo analysis that accommodates island and stepping-stone models, as well as topological heterogeneity among groups. The logic of our approach is illustrated in Because the hierarchal groups within AMOVA models are intrinsically unordered, they can capture island models but not linear stepping-stone models based on ϕST = 0.0580, p << 0.01). The one-step Trans-Atlantic Model B is roughly equivalent to the group partition in AMOVA Model II , except that Model B pools seals within the NWA and NEA groups, whereas Model II separates them within groups.For the Monte Carlo dispersal analysis, models and matrices for each of four main models as shown graphically in D = 0.522, p << 0.01), whereas those for the NL and SG samples are not , although those for the replicate Front sample and SG are . The curve for the NL+GS samples combined . All four trans-Atlantic comparisons are significant. The same comparisons are significant, with slightly reduced p values, if Da is calculated from (n-1)(n-2)/2. None are significant if Da is calculated from n.Results of the non-parametric Kolmogorov-Smirnov (K-S) test are given in combined  is signiwithin 2-, 3-, or 4-island models, but not among these model groups. In contrast, the Monte Carlo simulation and K-S tests taken together support a non-random distribution of seals, across stepping-stone as well as among island phylogeographic models in which the breeding areas comprise three distinct populations. These correspond to separate populations in the White Sea and Greenland Sea, each with distinctive phylogeographic and temporal structures, and a more homogeneous population in the Northwest Atlantic with intermediate but variable temporal structure. This is the first demonstration of genetic differentiation between the two breeding grounds in the Northeast Atlantic.The AMOVA models identify small but significant structures among the four breeding grounds b gene identified a common haplotype “A” in four out of ten seals from each of the two Northeast Atlantic areas and eight out of ten from each of the two Northwest Atlantic areas [Analysis of a 307bp segment of the mtDNA cytochrome ic areas . A row bGadus morhua), inspection of whole-genome sequences of the most common haplotype for the same gene region was a symplesiomorphic assemblage of unrelated lineages from different distantly related clades [E clade and comprises seals from the D, C, B  and A clades as well. We previously suggested that focal genotypes in many other ‘star phylogenies’ [In Atlantic Cod  time range [Pagophilus, and the lineage divergence times are relatively well dated though highly debated. The best linear fit has a slope of 4.5 Kyr / substitution, as compared with coding-region rates in Homo of 5.1 Kyr / substitution [Gadus spp. codfish [Pagophilus and its closest relative, the endemic Pacific ribbon seal (Histriophoca fasciata) gives a date of 3.7 ~ 4.1 MYA, which slightly antedates the most recent opening of the Bering Strait 3.5 MYA [Gadus spp. The Strait has opened and closed several times over the Pleistocene [Pagophilus x Histriophoca divergence may date to one of those earlier episodes.In the absence of a suitably recent biological or geological reference point for calibration of an intraspecific molecular clock in me range , we constitution , a linea codfish . Other c codfish . Extrapo 3.5 MYA . This ge 3.5 MYA  clocks fistocene , and thePagophilus is dominated by clade A, which originated and diversified as part of a population expansion 53 KYA . All stepping-stone models fall within the shortest 5% tail of all distributions, except for the one-step, two-population Model B. The models that depart mostly strongly from random are the four- and three-step trans-Atlantic stepping-stones, where the observed distribution falls within the 1.3% and 2.1% tails, respectively. The four-island AMOVA Model I also identifies significant ϕThe program DnaSP see  uses theA clade, such that the modal difference is smaller and the curved shifted leftward (>50% of differences < 40), with the exception of the basal subclade F1, which shifts the last ~40% of differences closer to the East curve. The structure of GS  is consistent with an older population with a relatively recent bottleneck in numbers such that the numbers of the minority clades B, C, D & E have been severely diminished, and only the plurality A clade survives alongside the basal F1. The historical catch records indicate that the population was severely depleted by the 1870s and remained low until the 1960s when it began to recover [In  recover . In conti.e., almost all component seals are in the A clade, with outliers in the more basal clades. However, the NL’ and GS curves are distinct, the former with a cumulative 50% reached at 42 differences, and the latter with a cumulative 50% at only 33 differences, and the two curves crossing at ~55% / 45 differences. This seems to indicate, within the A clade, a more recent modal relationship among GS seals than among NL’ seals. The Front curve also crosses the Gulf curve at 30% and again at 80%: the latter seems to reflect its inclusion of basal individuals that are absent in the Front and Gulf samples. D is evaluated, although this maximum is typically part of a continuous trend in cumulative differences: it would be useful to identify significant ranges.Comparison of relative ranks among populations across the horizontal pairwise difference axis clarifies the phylogeography of the replicate Front samples. Differences among the four main samples are consistently ranked GS < SG < NL < WS, but the replicate NL (NL’) curve crosses the others at several points. Inspection of An understanding of the relationships among the various Harp Seal whelping areas is critical for proper science-based management during the present period of climate change in the North Atlantic ,38,39,40Currently, the Northwest Atlantic is managed as a single population with quotas allocated between the Front and Gulf based upon the relative historical number of pups in each area. However, is some years, very little pupping occurs in the southern Gulf and Gulf animals move northward where they may mix with animals that normally breed at the Front ,47. A paa priori hypotheses. A novel Monte Carlo method shows that different biogeographic models have greater or lesser departures from random expectation, and thus represent stronger or weaker hypotheses of structure. In other, more continuously distributed species, mitogenomic data offer the potential for population structures to be detected in more dispersed collections of individual genome-types. Our non-parametric analysis assesses cumulative mismatch curves as proxies for intra-specific genomic trees, by converting a complex branching topology to a continuous curve approximation of phylogenetic diversity over time. Although the K-S D statistic assesses the single maximum difference between curves, the maxima seen here are typically the high point on trending differences between curves. The method is shown here to be sensitive to subtle differences in temporal structure of populations of mixed phylogenetic composition.Whole-mitogenome sequences offer fully-resolved phylogenetic trees within species that are literal “family trees” for maternal lineages. This raises new opportunities and challenges for data analysis. Assessments that differences among phylogenetic trees drawn from different populations or geographic segments are ‘different’ is elusive, not least because of the multiple ways in which such trees may be ‘different’. AMOVA partitions nucleotide variance but does not capture phylogenetic structure. We address two aspects of differentiation, first whether phylogeographic distribution is structured or random, and second whether temporal phylogenetic patterns among populations are distinguishable. Harp Seals are an ideal species in which to test ideas about biogeography and intraspecific mitogenomic phylogeny, because the discrete geographic distribution among a limited number of breeding areas provides several Seal DNA samples include 37 out of 40 of those analyzed in  from theComplete 15,825 bp mitogenomes (without the D-Loop Control Region) were generated by the polymerase chain reaction with a set of 20 primer pairs that amplify the mitochondrial genome in fragments of 750~1400 bp, with overlaps between adjacent fragments of 80~300 bp. Of the 53 genomes, 45 were sequenced on a custom-designed multi-species iterative re-sequencing microarray, the “ArkChip” (Affymetrix) . The remFor the genomic data, a neighbor-joining (NJ) tree was identified from the absolute number of nucleotide differences  (MEGA5 ). A maxiPagophilus molecular clock [U of macrohaplogroup N. These are Fr2 in Haplogroup A1 of macrohaplogroup M [L1 [Pagophilus mitogenome alignment.In the absence of any well-defined recent biological or geological reference point for calibration of an intra-specific ar clock , we estiogroup M , San2 inup M [L1 , and a Dup M [L1 . The calST values among populations based on nucleotide distances among haplotypes. We tested three partitions of within- and among-group variance  [a priori east-to-west groupings of breeding grounds. We also tested a fourth a posteriori two-island model with the eastern-most White Sea breeding ground separated from the other three, based on the observation of significant ϕST between WS versus NL, and versus GS.We used Arlequin v.3.5  to calcuctively) , correspa priori models suggested by the geographic distribution of breeding populations, relative to the random distribution expected for such models. We performed a series of Monte Carlo randomizations of population assignments over the tree topology in L) required to explain the observed tree, versus each of the random assignments over that same topology. We finally ask where L of the observed tree falls relative to the distribution of L over the random assignments. Different phylogeographic models can be represented encoded as a set of 4x4 Character Type matrices that count the stepwise cost of dispersal events among populations.We developed two new analytical methods and applied to the intraspecific phylogeographic tree. We first sought to determine how well the observed phylogeography fit various We tested four models : (a) an D) between the cumulative frequency distribution over the range of observed differences. Here, the cumulative curves are the cumulative numbers of pairwise differences in each sample, and D is the vertical offset between curves. The significance of D is evaluated by the critical value Da, which calculation includes counts of the number of comparisons within each population as a measure of the degrees of freedom. For pairwise data this would ordinarily be (n)(n-1)/2, however because the contributions of each individual to the set of pairwise difference comparisons are not independent, Da may more accurately be estimated from the total number of individuals n within both populations  or by (n-1)(n’-1)/2 for an n x n’ matrix. We evaluated D on all three criteria.Differences between population-specific cumulative pairwise difference curves were evaluated with a non-parametric, two-sample Kolmogorov-Smirnov (K-S) test procedure . For a cS1 Table(DOCX)Click here for additional data file.


Coronary artery disease (CAD) is a complex disease and the leading cause of death in the world. Populations of different ancestry do not always share the same risk markers. Natural selective processes may be the cause of some of the population differences detected for specific risk mutations.In this study, 384 single nucleotide polymorphisms (SNPs) located in four genomic regions associated with CAD  are analysed in a set of 19 populations from Europe, Middle East and North Africa and also in Asian and African samples from the 1000 Genomes Project. The aim of this survey is to explore for the first time whether the genetic variability in these genomic regions is better explained by demography or by natural selection.The results indicate significant differences in the structure of genetic variation and in the LD patterns among populations that probably explain the population disparities found in markers of susceptibility to CAD.The results are consistent with potential signature of positive selection in the 9p21 region and of balancing selection in the 9p21 and 10q11. Specifically, in Europe three CAD risk markers in the 9p21 region  show consistent signals of positive selection. The results of this study are consistent with a potential selective role of CAD in the configuration of genetic diversity in current human populations. Coronary artery disease (CAD) is a complex disease and the main cause of death in the world. In 2007, the first genome-wide significant risk region, 9p21, was simultaneously discovered by two independent groups . Out of Most genome wide association studies (GWAS) for CAD have been performed on populations of European descent, but increasing numbers of such investigations are now performed also on populations of Asian or African ancestry. In the literature currently available, some of the genetic effects observed are shared among ethnic groups but many times genetic effects are different across populations of different ancestry. The latter is the case of the 9p21 locus, which has been documented in Europeans and also in other ethnic groups including East and South Asians, but not among African Americans . DemograConcerning CAD risk regions, in the current literature there are discrepancies regarding the role of natural selection. A recent survey proposed natural selection as a possible explanation for the observed differences between Africa, East Asia, America, and Oceania in risk allele frequencies (RAFs) for eight CAD risk single nucleotide polymorphisms (SNPs) . AnotherPopulation differences in risk loci associated to CAD were recently detected for the 1p13, 1q41, 9p13, and 10q11 regions. These genomic regions showed disparities in the specific risk markers associated with CAD between European and North African samples [The present work is centred on these four genetic regions  to explore whether the population genetic diversity is better explained by demographic or by natural selection effects.To do this, we have analysed these risk regions in a set of North European and Mediterranean populations. Several specific tests to detect positive and/or balancing selection were performed. In addition, these analyses were expanded to populations from Asia and Africa looking for signatures of selection shared across continents or belonging to a specific population group.The study has been specifically approved by the Ethical Committee of the University of Barcelona  and all the participants provided a written informed consent.Nineteen population samples from Europe, Middle East and North Africa were genetically tested. DNA samples of 868 healthy unrelated individuals of both sexes having their relatives for at least three generations born in the same geographical region were analyzed.Population details of all samples, including sample size, geographic origin and coordinates are recorded in Genomic DNA was extracted from blood cells using a Blood Midi kit  according to manufacturer's procedures. DNA samples were genotyped for a combined set of 384 SNPs using a Custom GoldenGate Panel . These polymorphisms were located in four loci previously associated and replicated in independent studies with CAD , 14, 15,2<0.8) in European populations, and iv) prioritizing markers previously associated with CAD [SNPs were selected as a representative set of the common variation in the four genomic regions, according to the following criteria: i) average coverage of 1 SNP every 1.5 kb, ii) minor allele frequency (MAF) higher than 0.05 in CEU and TSI HapMap populations, iii) given priority to markers not in linkage disequilibrium (LD)  test and F2≥0.8) were assessed using PLINK version 1.07 [Genotyping rate per SNP and individual, cryptic relatedness, and LD pruning  using Wright's F-statistics in the European and Mediterranean area and, in a broader context, in the European, African and Asian continents. Populations were clustered according to geographic criteria. Middle Eastern samples were clustered into the South European group due to affinities in their genetic distances. The samples were clustered in: 1) North Europe, South Europe, and North Africa, and 2) North Europe, South Europe, North Africa, Sub-Saharan Africa and Asia. AMOVAs were carried out using Arlequin v3.5 .Adegenet [FactoMineR R packages [Genetic relationships among populations were assessed by Reynolds genetic distance and by a principal component (PC) analysis calculated through the Adegenet  and Factpackages .2) for each pair of risk SNPs in each population analyzed were calculated through the Haploview software version 4.2 [The LD blocks based on the LD measure D′ confidence interval  were persion 4.2 .ST) were compared to a null distribution obtained by simulation samples. The P-value of each locus was estimated from the joint distribution of heterozygosity and FST using a kernel density estimation procedure. The null distribution generated was summarized by quantiles of the joint distribution. The 1% and 99% quantiles of the distribution correspond to markers potentially under balancing or directional selection, respectively, at the 1% level, without multiple-test correction and assuming one-tailed test. This method was performed using Arlequin v3.5 software [Detection of potential loci under selection was assessed using different methods. The first method used is based on the probability of observing locus by locus AMOVA statistics as a function of heterozygosity, given a null distribution generated under a hierarchically-structured island model of population differentiation . This tesoftware .Moreover, the spatial ancestry (SPA) analysis was used to detect positive signatures of selection . In thisST tests were conducted in three populations of the larger dataset of the 1000 Genomes Project  through the web tool 1000 Genome Selection Browser 1.0 [ST and the EHH tests, and the lower tail for the Tajima’s D test. The p-values were assigned on the basis of the rank score tracks. In this study, Tajima’s D, EHH average and FST scores above the 95th percentile of the top extreme genome-wide distribution were considered as significant. All p-values were corrected for multiple comparisons applying the false discovery rate (FDR) method [stats R package [Spatial distribution of mean MAF for one of the three CAD SNPs potentially positively selected across populations was mapped using the geostatistical method known as kriging from the ArcGIS software . Since anisotropy was not detected in the semivariogram, we used the ordinary spherical interpolation kriging method . Finallywser 1.0 . The Tajwser 1.0 . They we) method  by means package .2>0.8) hence, only 190 SNPs were included in population relationship analyses.After pruning, the average coverage was 1 SNP every 1.8 Kb. Genotyping rate for the 384 SNPs initially tested was 95.8%. Sixteen SNPs were not successfully genotyped and were removed from the study. One SNP showed a significant departure from Hardy-Weinberg equilibrium after Bonferroni correction. Thus, a total of 367 markers were included in the analyses after quality control: 59 SNPs in 1p13 , 37 in 1The SNP minor allele frequencies (MAF) in population samples and global heterozygosities per marker and population are presented in ST = 0.085 and FCT = 0.080 (both p<0.0001). When Sub-Sahara African and Asian data were removed and the remaining populations were grouped in North Europe, South Europe and North Africa, AMOVA estimates were FST = 0.017 and FCT = 0.012 (both p<0.0001). These values indicate a statistically significant geographic structure of genetic variation in the three continents, and also across Europe and North Africa.Hierarchical AMOVA estimates when populations were clustered in North Europe, South Europe, North Africa, Sub-Saharan Africa and Asia were FPopulation genetic distances are indicated in Concerning population relationships, in the PC analysis  of the EDifferent LD blocks were identified among populations. At first glance, Asian and Sub-Saharan African samples showed different and characteristic LD patterns when compared with other continental populations –S8 Figs.2) for each pair of risk SNPs and for each analysed population are provided in Focusing only on SNPs previously associated with CAD, LD statistics . Out of these 16 loci, seven had high FST values (FST range = 0.067–0.094) indicating potential positive selection and the other nine showed low FST values (FST range = <0.0001–0.0004) suggesting balancing selection. Regarding cross-continental analyses, 15 loci were potentially under selection, eight of which indicated potential positive selection (FST range = 0.248–0.293) and the other seven suggested balancing selection (FST range = <0.0001–0.007).The results of the locus by locus FST vs heterozygosity) were a total of 14 and were located in regions 1p13, 1q41, and 9p21. Out of these 14 SNPs, seven were found only in the context of the three continents, six only in Europe and North Africa, and one in both groups (rs2811717 in the 9p21 region)  . Fifteen region) . ConsequST/HO tests. Also, these SNPs have been associated with CAD in previous studies [In the SPA analysis, three SNPs  showed SPA scores above the 99th percentile in each one of the sample group: North Africa  and Europe (1.95) . None of studies , 35, 36 ST and the EHH average tests, performed with the CEU, CHB and YRI samples from the 1000 Genomes Selection Browser, pointed out markers in the extreme 5% of the genome-wide distribution. Markers with high FST values indicating potential positive selection (top 2.5%) were identified in the four regions analysed . Markers with extremely low FST values (bottom 2.5%), indicating potential signatures of balancing selection, were also detected in all the regions studied   are likely due to the different sets of populations included in each group  are very different comparing the 1000 Genomes data for CEU, CHB and YRI (0.57–0.59) with the 26 populations analysed (0.27–0.29). Also in this case, this is likely due to the different populations included in the analysis, mainly in the African continent . The EHH average test, used to validate the results found in the 9p21 region, showed potential signals of positive selection (p≤0.05) in the three populations analysed (grey in ST vs HO. and SPA score), is located in one of the 3-kb regions that show significant EHH values  . After ae red in . These m1 region . For thich group . Regardi grey in . It is nThe most relevant findings of positive selection regarding the 1p13, 1q41, and 9p21 genomic regions, and of balancing selection of the regions 9p21 and 10q11 are summarized in Tables This study explores for the first time the genetic diversity in four genomic regions associated with CAD  through the genotyping of a set of European and Mediterranean populations and using European, Asian and Sub-Saharan African data from the 1000 Genomes Project [ST = 0.085; p<0.0001) and also in Europe and in the Mediterranean area . The degree of genetic diversity observed in these four regions between continents is comparable to that obtained from genome-wide genotyping and sequencing studies [Diversity population indices indicate significant genetic structure in the context of the three continents  in the context of three continents. The FST value detected in the 1000 Genomes Data is in the same order of magnitude than recent positive selection signals (FST>0.5) detected in previous studies performed on the lactase gene [Even though the general patterns of genetic variation are in agreement with the genetic structure generated by demographic processes, we also observed potential signals of positive and balancing selection in some specific markers and haplotypes. Seven SNPs under potential positive selection showed association to diseases in previous studies , 46, 47,ase gene  and on gase gene .ST vs HO, SPA score, FST and LRH test). The consistency for selection signals in the 9p21 genomic region lies in the fact that these different tests are all based on the same aspect of the data, i.e. population differentiation. Briefly, four variants showed evidence of positive selection: rs9632884, rs6475606, rs1537371 and rs1333042. These SNPs were previously associated with CAD [The 9p21 genomic region, the most complex and studied CAD risk region , showed with CAD , 36, 47 ST vs HO tests could be mainly attributed to Europeans. In fact, the European SPA scores are higher than those detected in North Africans. Additionally, the confirmation of three markers in the 9p21 genomic region  in two tests (FST vs HO and SPA score in Europe) is a good indicator of consistency across our results. As an independent replication using the 1000 Genomes dataset, the region containing one of these 3 markers (rs1333042) has shown a significant EHH value (before correction for multiple testing) in the LRH test. Moreover, this SNP, used as representative of the other two risk markers, shows a South to North gradient of increase in MAF. The gradient observed is in agreement with CAD incidence [ST tests showing FST values >0.78. In addition is noteworthy the potential positive signal detected for the rs2811717 in the 26 population studied and also in the 1000 Genomes Browser data. The FST value of this SNP in Europe (0.094) is substantially higher than 0.028, value used to identify the most prominent genome-wide candidate regions in a recent selection scan in Europe [Thanks to the high density of populations available for Europe and North Africa, we were able to do a spatial analysis of selection (SPA test) in these geographic areas. Thus, the positive signals of selection observed in the Fncidence  and withncidence , or the ncidence , both asn Europe .ST vs HO tests. Although these regions did not pass the corrections for multiple testing, it is noteworthy that regions of 15 kb (encompassing five contiguous windows in 10q11) in Asian and African samples and 24 kb (corresponding to eight contiguous windows in 9p21) in European populations showed evidence of selection. The overlap in the signals observed for Asians and Africans in the 10q11 region suggests that this locus is likely subjected to selective processes in both populations, in agreement with Wang et al. [ST and EHH tests).Regarding signatures of balancing selection, only the 9p21 and 10q11 regions showed evidence of balancing selections in the Tajima’s D and in the Fg et al. , who estThe heterogeneity observed in the potential signals of natural selection in the different populations analyzed might be correlated with environmental variables. A recent whole genome scan reported evidence for selection on two markers implicated in cardiovascular disease by identifying the SNPs with the strongest correlation between allele frequencies and climate, specifically with winter solar radiation and summer precipitation rate in African and Western Eurasian populations . AnotherRegarding CAD risk loci, the selection of harmful mutations may be due to the fact that they are in LD with a relatively strong still unknown beneficial polymorphism  that couAlthough many selection scans have highlighted potentially interesting signals using genome-wide SNP data, it is currently difficult to assess how much confidence should be placed into them in the absence of clear signals of widespread, strong selection or of biological/functional information . Recent ST, the LRH and the Tajima’s D test. The correspondence in the results across these two datasets with different marker coverage  allow us to consider the 9p21 genomic region as a potential candidate for positive and balancing selection, and the 10q11 for balancing selection.One possible limitation of this survey is related to the ascertainment bias in the selection of marker. The fact that these results were obtained by genotyping SNPs selected for specific criteria (MAF higher than 0.05 and giving priority to markers not in LD in European populations), and not through direct sequencing, could affect the found patterns of allele frequency, LD and population differentiation . SeveralIn the absence of additional functional information, our results are compatible with a potential selective role of CAD in shaping the genetic diversity observed in current human populations, but demographic processes cannot be discarded.S1 Dataset(XLSX)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 Fig(TIF)Click here for additional data file.S5 Fig(TIF)Click here for additional data file.S6 Fig(TIF)Click here for additional data file.S7 Fig(TIF)Click here for additional data file.S8 Fig(TIF)Click here for additional data file.S9 FigMarkers previously associated in Europe are highlighted in blue.(TIF)Click here for additional data file.S10 FigMarkers previously associated in Europe are highlighted in blue.(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 TableRisk SNPs in the same haplotype are highlighted in red. Risk SNPs in the same haplotype block in LD (D’ = 1) are highlighted in grey.(XLSX)Click here for additional data file.S5 TableCAD risk SNPs are highlighted in grey and their number corresponds to the risk markers in (XLSX)Click here for additional data file.S6 TableCAD risk SNPs are highlighted in grey and their number corresponds to the risk markers in (XLSX)Click here for additional data file.S7 TableCAD risk SNPs are highlighted in grey and their number corresponds to the risk markers in (XLSX)Click here for additional data file.S8 TableST with selection significance  for the three continents  and for Europe and North Africa. Global cross-continental FST scores in the CEU, CHB, and YRI samples from the 1000 Genomes Selection Browser. Significant high and low FST values  are highlighted in grey. P values were calculated on the basis of higher rank scores in the genomic distribution. SPA scores for continental European, and North African allele gradients (highlighted in grey SPA scores above 99th percentile). Tajima’s D test results in the CEU, CHB, and YRI samples of the 1000 Genomes Project. Signals of potential balancing selection  are highlighted in grey. P-values were calculated on the basis of higher rank scores in the genomic distribution of Tajima’s D values.Observed (Obs) F(XLSX)Click here for additional data file.S9 TableST values  are highlighted in grey. P values were calculated on the basis of higher rank scores in the genomic distribution. Significant FST values after applying correction for multiple testing are highlighted in red.Significant high and low F(XLSX)Click here for additional data file.S10 TableSignificant high EHH values  are highlighted in grey. The region containing the CAD risk marker rs1333042 is highlighted in grey. P values were calculated on the basis of higher rank scores in the genomic distribution.(XLSX)Click here for additional data file.


Galaxias maculatus is found mainly migrating between estuaries and rivers, but some landlocked populations have been described in lakes formed during the last deglaciation process in the Andes. In the present study we use mtDNA sequences to reconstruct the historical scenario of colonization of such a lake and evaluated the osmoregulatory shift associated to changes in habitat and life cycle between amphidromous and landlocked populations.Marine species have colonized extreme environments during evolution such as freshwater habitats. The amphidromous teleost fish, Π) and the haplotype diversity index (H) indicated that both populations were, as expected, genetically distinctive, being the landlocked population less diverse than the diadromous one. Similarly, pairwise GST and NST comparison detected statistically significant differences between both populations, while genealogy of haplotypes evidenced a recent founder effect from the diadromous stock, followed by an expansion process in the lake. To test for physiological differences, individuals of both populations were challenged with a range of salinities from 0 to 30 ppt for 8 days following a period of progressive acclimation. The results showed that the landlocked population had a surprisingly wider tolerance to salinity, as landlocked fish survival was 100% from 0 to 20 ppt, whereas diadromous fish survival was 100% only from 10 to 15 ppt. The activity of ATPase enzymes, including Na+/K+-ATPase (NKA), and H+-ATPase (HA) was measured in gills and intestine. Activity differences were detected between the populations at the lowest salinities, including differences in ATPases other than NKA and HA. Population differences in mortality are not reflected in enzyme activity differences, suggesting divergence in other processes.Standard diversity indices including the average number of nucleotide differences (G. maculatus osmoregulatory system, especially at hyposmotic environments, associated to a drastic shift in habitat and life cycle at a scale of a few thousand years.These results clearly demonstrate the striking adaptive changes of  Moreover, the residues condition index was also calculated as follows: body ma2, 200 mM dNTPs, 0.5 μL of each primer (10 pg/μL), 1 U Taq (Invitrogen), 17.5 μL double-distilled water and 5 ng of DNA. Thermal cycling parameters included an initial denaturation step at 94°C for 5 min, followed by 35 cycles at 94°C for 90 sec, 60.7°C for 90 sec and 72°C for 90 sec, and a final 10 min extension at 72°C. Double-stranded amplicons were purified using QIAquick Gel Extraction Kit (QIAGEN) and sequenced in both directions with an Automatic Sequencer ABI3730 x 1 at Macrogen Inc. . New D-loop haplotypes sequences of G. maculatus were deposited in GenBank under the Accession Numbers KX133352—KX133406.Individuals tested for physiological analyses were fixed in ethanol (95%), and DNA was extracted using a salting-out methodology previously by Aljanabi and Martinez . For comk), number of segregating sites (S), haplotype diversity (H), average number of pairwise differences (Π), and nucleotide diversity (π) for each locality and for the entire data set with DnaSP v.5.00.07 [S) for each locality and for the entire data set to estimate whether sequences deviate from expectations under a neutral model. We determined the levels of genetic differentiation between the analyzed localities using mean pairwise differences (NST) and haplotype frequencies (GST) following previous studies [D-loop sequences were edited using Proseq v. 3.5  and alig.5.00.07 . We perf studies  in Arleq studies . The staG. maculatus were constructed using Maximum Parsimony networks computed in Hapview (http://www.cibiv.at). To estimate the pattern of demographic history in the species, we compared the distribution of pairwise differences between haplotypes (mismatch distribution) of both localities to the expected distribution under the sudden expansion growth model of Rogers and Harpending [http://beast.bio.ed.ac.uk/Tracer). The uncorrelated lognormal model was the best fit for D-loop data in G. maculatus. We conducted three independent Bayesian MCMC runs using the GTR + I + G model, previously estimated using MrModeltest v. 2.3 (http://www.abc-se/~nylander), and a specific population level mutational rate estimated for G. maculatus by [6 generations (sampled every 1000 step), discarding a 10% of the trees as burn-in. The convergence of runs was confirmed with Tracer ensuring a minimum of 1000 effective sampling for each statistics (ESS). The results of the multiple runs were combined using LogCombiner [Genealogical relationships in rpending . This anrpending . For comrpending  with TRAlatus by . For eacCombiner . The med+/K+-ATPase (NKA) activity in gill homogenates was determined in microplates using a modification of McCormick’s method [+-ATPase (HA) activity was measured in the same manner as for the NKA using Bafilomycin A1 as a specific inhibitor of the V-type H+-ATPase [Oncorhynchus mykiss) [Sparus aurata) . Remaining ATPases activity was also recorded by subtracting the activities of NKA and HA. Data were expressed as μmol ADP/g prot/h.A biochemical characterization of the Nas method . Experim+-ATPase , in a fi mykiss)  and giltt-test.Data were checked for normality, independence and homogeneity of variance. A two way analysis of covariance was conducted to gills;the full model included site (estuary-lake) and salinity  as fixed effects, as well as all possible interactions between the terms. Intestine was tested by three way analysis of covariance; the full model included site (estuary-lake), salinity  and portion of intestine (anterior and posterior) as fixed effects as well as all possible interactions between the terms. All models included length as a covariate and tank as a random effect. Statistical significance was accepted at p<0.05. All data are presented as mean±standard error (S.E.). This model was chosen from Velotta et al. (2015) .Differen