Analysing population genomic data from killer whale ecotypes, which we estimate have globally radiated within less than 250,000 years, we show that genetic structuring including the segregation of potentially functional alleles is associated with socially inherited ecological niche. Reconstruction of ancestral demographic history revealed bottlenecks during founder events, likely promoting ecological divergence and genetic drift resulting in a wide range of genome-wide differentiation between pairs of allopatric and sympatric ecotypes. Functional enrichment analyses provided evidence for regional genomic divergence associated with habitat, dietary preferences and post-zygotic reproductive isolation. Our findings are consistent with expansion of small founder groups into novel niches by an initial plastic behavioural response, perpetuated by social learning imposing an altered natural selection regime. The study constitutes an important step towards an understanding of the complex interaction between demographic history, culture, ecological adaptation and evolution at the genomic level. Killer whales have evolved into specialized ecotypes based on hunting strategies and ecological niches. Here, Andrew Foote and colleagues sequenced the whole genome of individual killer whales representing 5 different ecotypes from North Pacific and Antarctic, and show expansion of small founder groups to adapt to specific ecological niches. The interplay between ecology, culture and evolution at the level of the genome remains poorly understood12Orcinus orca) are the largest species in the dolphin family (Delphinidae) and, together with humans, are one of the most cosmopolitan mammals, being found in all ocean basins and distributed from the Antarctic to the Arctic6789transient') ecotype and fish-eating  ecotype7transient and resident ecotypes across the North Pacific that diverged from common ancestral matrilines ∼68 and 35 KYA, respectivelyinformation that is capable of affecting individuals' behaviour, which they acquire from other individuals through teaching, imitation and other forms of social learning'13Killer whales , 11 individuals of a partially sympatric, smaller form which feeds on penguins (type B2), and 10 individuals of the smallest form of killer whale, which feeds on fish (type C) (FST indicated that estimates from our low-coverage data were highly consistent with published high-coverage restriction site associated DNA sequencing (RAD-seq)We generated whole-genome re-sequencing data of 48 individuals at low coverage and accessed high-coverage sequencing data from two more individuals16(type C) . A total(type C)  for whic(type C) . SubsequWe estimated a time to most recent common ancestor (TMRCA) of ∼126–227 KYA from the accumulation of derived mutations at third-codon positions for the most divergent killer whale lineages compared here  and baseK=5 populations, a maximum-likelihood-based clustering algorithmresident and transient ecotypes (FST=0.09) between even the most recently diverged and partially sympatric ecotypes (Antarctic types B1 and B2) indicates that reproductive isolation quickly becomes established after the formation of new ecotypes. Thus, whole-genome resolution confirms that, even in sympatry, contemporary gene flow occurs almost exclusively among individuals of the same ecotype, allowing genomic differentiation to build up between ecotypes so that within an ocean basin ecological variation better predicted genetic structuring than geography.Despite this recent shared ancestry, substantial genome-wide differentiation and divergence had accrued between all pairs of ecotypes included in this study . At K=5 ecotypes . The greecotypes  as visuaecotypes  and PCA ecotypes  was betwf3) and D-statistic (ABBA-BABA)To better understand and visualize the complexity of the ancestry of killer whale ecotypes, we reconstructed the genetic relationships among ecotypes in the form of a maximum likelihood graph , represeresident and North Atlantic ecotype into the transient ecotype . The asymmetrical two-dimensional (2D)-site frequency spectrum (SFS) also implies directional gene flow from a population ancestrally related to the residents into the transient ecotypetransient ecotype, otherwise it would be expected to be less correlated with the resident SFS. The sequencing of more populations is expected to shed further light on this episode of ancient admixture.The three approaches were consistent in inferring migration from source populations that share ancestry with the North Pacific  ecotype . The gentype B1 is admixed and derives from at least two populations related to both types B2 and C  and the rate of evolutionresident male, refining the methodological approach of a previous analysis of these genomes (μ); however, across a range of sensible estimates of μ, the declines broadly fall within the Late Pleistoceney axis of the PSMC plot is an estimation of Ne derived from the rate of coalescence between the two chromosomes of a diploid genome. However, in the presence of population structuring, regions of the two chromosomes will coalesce less frequently as their ancestry may derive from different demes or subpopulations; the rate of coalescence can thus be similar to a single population with large Ne. PSMC estimates of Ne during population splits can therefore be greater than the sum of the effective sizes of the subpopulations, dependent on the number of subpopulations and the degree of connectivity  between them211719Ne  of the Atlantic female and directly compared with the autosomal fraction (NeA) of the genome presented in NeX ranged from 0.58 to 0.79 of the NeA  for different SNP frequency spectra associated with different epochs, which are then scaled by the mutation rate to estimate Ne for each epochresident ecotype that was comparable to the PSMC plot from a single resident high-coverage genome, both methods identifying a decline in Ne starting at ∼60 KYA  between killer whale ecotypes across all genomic regions >1/2Ne) would have an increased fixation probability because of selection within these founder populations.Demographic bottlenecks during population splits and founding events, followed by subsequent demographic and geographic expansion, can produce rapid shifts in allele frequencies between populations regions  are consic drift , that isic drift . We therπ) was not associated with mutation rate μ, as inferred from neutral substitution rate dS, (r=−0.1 to −0.24), the observed covariation in differentiation (FST), diversity (π) and absolute divergence (Dxy) between population pairs (36Much of the heterogeneity in the differentiation landscape was shared among pairwise comparisons . Since don pairs  is best P=0.0015). Genes associated with adipose tissue development have previously been found to be evolving under positive selection in the polar bearHowever, against this background of shared differentiation, there was evidence for genic divergence of putative functional relevance. The first targets of selection following ecotype diversification and the exploitation of new ecological niches are expected to be those that facilitate ecological specializationFAM83H gene showed a signature of selection  and was found to contain four fixed non-synonymous substitutions derived in the Antarctic lineages based on the inferred ancestral state, which resulted in physicochemical changes including a hydrophobic side chain being replaced by a positively charged side chain. The keratin-associated protein encoded by the FAM83H gene is thought to be important for skin development and regulation through regulation of the filamentous state of keratin within cytoskeletal networks in epithelial cells, determining processes such as cell migration and polarizationUsing the population branch statistic (PBS), which has strong power to detect recent natural selectioncarboxylesterase 2 (CES2) gene encodes the major intestinal enzyme and has a role in fatty acyl and cholesterol ester metabolism in humans and other mammalsCES2 gene had among the top 99.9 percentile PBS values because of changes in allele frequencies (including two fixed non-synonymous amino-acid changes) along the branch to the Antarctic types (P<0.0001) in the fish-eating resident ecotype. Biological processes enriched in the resident killer whale included digestive tract morphogenesis , and gastrulation with mouth forming second : associated with the formation of the three primary germ layers of the digestive system during embryonic development. These results overlapped with enriched GO terms identified by a previously published RAD-seq study, despite the relatively sparse sampling of 3,281 SNPs in that studyGATA4 gene, which included a fixed non-synonymous substitution, sequenced in both studies.Genes encoding proteins associated with dietary variation also showed a signature of selection . For example, the ic types . Similartransient and Antarctic type B1, were found in genes that play a key role in the methionine cycle . Reproductive proteins such as PKDREJ, in which we found two fixed non-synonymous substitutions derived in the ‘resident' ecotype, are known to diverge rapidly across taxa, and because of their functional role in fertilization are emerging as candidates for the post-zygotic component of the speciation processHigh (top 99.9 percentile) PBS values, largely driven by fixed non-synonymous amino-acid substitutions, were further estimated for several genes that encode proteins associated with reproductive function, including testis development, regulation of spermatogenesis, spermatocyte development and survival, and initiating the acrosome reaction of the sperm  to minimize chances of collecting close relatives or replicate individuals. The sample set included 10 ‘resident', 10 ‘transient', 7 type B1, 11 type B2 and 10 type C killer whales.Skin biopsies from free-ranging killer whales were collected using projected biopsy darts, concurrent with the collection of photographic, photogrammetry and behavioural data, allowing sampled individuals to be binned to ecotype/morphotype DNA was extracted using a variety of common extraction methods as per ref. A high-quality, 2,249-Mb reference killer whale genome assembly Illumina HiSeq 2000 reads from each individual were processed with AdapterRemovalTursiops truncatus, Short Read Archive accession code SRX200685)The ancestral state for each site was inferred by mapping whole-genomic Illumina sequencing reads of the bottlenose dolphin , 7,547 were inferred to be transversions and 12,784 were inferred to be transitions  cutoff of 0.1 so as to exclude potential sequencing errors) from the ancestral state (inferred from comparison with the dolphin genome). Of these, 7,120 transversions and 11,176 transitions were fixed in the killer whale, and therefore were inferred to have occurred along the branch from the killer whale/bottlenose dolphin ancestor and the MRCA of the killer whales ; moreover, 421 transversions and 1,608 transitions occurred within one or more of the killer whale lineages. A further six sites were inferred to have undergone a transversion from the ancestral state in at least one of the killer whale lineages, but had derived transitions in at least one other killer whale lineage. The Ts/Tv ratio of derived mutations at third-codon positions was therefore estimated to be 3.8 within the killer whale clade.type B1 individual that were shared with each of the other eight individuals was measured. The two resident individuals shared the least number of derived transversions with the type B1 individual type B1 since splitting from a shared ancestor with the resident ecotype.The proportion of derived mutations at third-codon positions found in one individual and shared in another individual is expected to decrease in comparisons between individuals from populations that diverged longer ago, as the probability that the mutation occurred within just one population following the split increases. The proportion of derived transversions and transitions at third-codon positions inferred within the dividual . The resdividual . The meaa priori, based on observed behaviour and/or morphological characteristics at the time of sampling, represented discrete gene pools in Hardy–Weinberg equilibrium. Since the 48 genomes generated for this study had an average sequencing depth of 2 × , genotypes can only be called with very high uncertainty. Therefore, NGSadmixK set to 3–5. For each of these K values, NGSadmix was re-run multiple times with different seeds in order to ensure convergence. Sites were further filtered to include only autosomal regions covered in at least 40 individuals, and removing sites with a minor allele frequency below 5% estimated from the GLs, resulting in the analyses being based on 603,519 variant sites. The highest likelihood solutions can be seen in An individual-based assignment test was performed to determine whether the ecotypes to which each individual had been assigned R function ‘eigen', and significance was determined with a Tracy–Widom test to evaluate the statistical significance of each principal component identified by the PCA. The PCA was plotted using an in-house R script .Assignment of individuals to ecotype, and structuring among ecotypes, was further investigated using Principal Component Analysis (PCA), implemented in the ngsTools suitetransient ecotype as the root, with blocks of 1,000 SNPs  to account for linkage disequilibrium among sites. The graphs are presented in The genetic relationships among ecotypes were further reconstructed in the form of a maximum likelihood graph representing the degree of genetic drift generated using TreeMixMeasures of genetic differentiation, divergence and diversity were estimated using methods specifically designed for low-coverage sequencing data. Using a Maximum-Likelihood-based approach previously proposedFST was estimated with a method-of-moments estimatorr2>0.96) for all pairwise comparisons. However, from inspection of the data, the FST estimates generated from sample allele frequency posterior probabilities provided a more accurate estimation of fixed differences between populations. The likelihood-based method tends to flatten the FST peaks compared with the posterior probability method. This can result in masking of FST peaks with increasing genome-wide FST when using the likelihood-based method. Therefore, the posterior likelihood estimates are presented in the Manhattan plots of 50-kb sliding windows (π) from the two high-coverage genomes. We further checked by comparing FST estimates from a recently published whole-genome data set of carrion crows (Corvis corone) and hooded crows (C. cornix)FST estimates comparable to the values obtained from the 7–28 × sequences using GATK. Population-specific allele frequencies were estimated with the ancestral state fixed and the derived allele weighted by the probabilities of the three possible states. The allele frequencies were estimated based on GLs. To assess the robustness of our per-site FST value estimates, we evaluated how well the values correlated with those estimated from RAD-seq data generated in a previous studyFST, using sites called at >20 × coverage, between 43 individuals of the resident ecotype and 37 individuals of the transient ecotype (FST estimates from these random subsamples ranged from 0.6861 to 0.9372. We found the correlations between estimates of FST from the RAD-seq data and those from our whole genome sequencing (WGS) data ranged from 0.5475 to 0.7140  when it was randomly downsampled to 2 × coverage (π=0.0008). Nucleotide diversity was estimated for sites covered by at least five individuals in each population in windows of size 50, 100 and 200 kb  size. The PSMC model estimates the TMRCA of segmental blocks of the genome and uses information from the rates of the coalescent events to infer Ne at a given time, thereby providing a direct estimate of the past demographic changes of a population. The method has been validated by its successful reconstructions of demographic histories using simulated data and genome sequences from modern human populationsPSMC analysisresident genome (20 × ) was estimated, scaled to the autosomal mutation rate of 2.34 × 10−8 substitutions per nucleotide per generationμA) of 2.34 × 10−8 substitutions per nucleotide per generationμX=μA[2(2+α)]/[3(1+α)], assuming a ratio of male-to-female mutation rate of α=2 (ref. μX=2.08 × 10−8 substitutions per nucleotide per generation. The plot is presented in Ne in autosomes and X-chromosome. We found that μX=1.00 × 10−8 substitutions per nucleotide per generation would be needed to synchronize the inferred demographic changes in these two markers (α) to be orders of magnitude higher, making it seemingly biologically unrealistic.A more detailed account of PSMC analyses, including our reanalyses and reinterpretation of a previously published analysis of low-medium coverage genomest genome  ×  was et genome  ×  was eα=2 ref. . This ga markers . This woθ=4Neμ, where μ is the mutation rate per generation and Ne is the effective population size), assuming a flexible multi-epoch demographic model. Changes in effective population size through time are then estimated based on the estimations of θ. As input data, we transformed the probability estimates of our site frequency spectra into SNP counts. We first ran the method on the resident ecotype to compare with the demographic reconstruction suggested by the PSMC analysis on the high-coverage North Pacific individual (see above). Population structure is a notable confounding factor for inferring demographic history30Ne subsequent to the estimated bottlenecks in each ecotype, during a period overlapping with previous estimates of within-ecotype lineage splitsresident and transient , we potentially skew the SFS towards low-frequency polymorphism, thereby mimicking the pattern generated by population expansionTo reconstruct ancestral demography in the ecotypes for which we did not have a high-coverage genome, we applied a method that uses the SFS from population genomic data to infer ancestral population size changesNe, whereas a more gradual decline was inferred by PSMC, consistent with simulations showing that PSMC can infer abrupt changes in Ne as gradual changesNe because of further founder effects as the resident ecotype continues to split into multiple discrete populations. In contrast, the Stairway Plot is based on population genomic data and will track the change in Ne across all the sampled resident populations after they have split.The inference of demographic history from population genomic data by the Stairway Plot method provided a somewhat comparable result to reconstruction from a single 20 × genome by PSMC with respect to the time of onset and magnitude of a demographic decline inferred by both methods. The Stairway Plot method inferred a sudden drop in type C. The results are shown in type C is shown in The method was then applied to the site frequency spectra of the transient ecotype and FST values from each pairwise comparison between killer whale ecotypes. However, as FST is dependent on the underlying diversity of the locus, even extreme outlier loci can be due to genetic drift alone. We, therefore, additionally looked for over-representation of the top 1% outliers in different categories, for example, exons, 25-kb flanking regions , introns and intergenic regions, at different FST bins using a χ2-test. Residuals are expected to be normally distributed and indicate statistical significance of over- and under-representation of specific categories. The significance threshold was subjected to Bonferroni correction. The top 100 outliers in exons from each pairwise comparison were then used for GO over-representation analysisShifts in allele frequencies can occur because of selection, but differences in allele frequencies can also accumulate between populations because of drift34et al.T=−log(1−FST) to obtain estimates of the population divergence time T in units scaled by the population size. For each 50-kb window, we calculated this value between each pair of ecotypes. The length of the branch leading to the one ecotype since the divergence from a recent ancestor  is then obtained asTo more robustly infer whether genetic changes in exons were associated with ecotype divergence due to selection, we applied the PBS540resident, transient and ancestral Antarctic ecotypes) and the top 99.99 percentile for the shorter branches leading to each Antarctic ecotype from their most recent common shared ancestor. We further filtered outliers to just include exons that encoded non-synonymous amino-acid substitutions and searched the database GeneCardsThese window-based PBS values represent the amount of allele frequency change at a given 50-kb genomic region in the history of this ecotype (since its divergence from the other two populations)Accession codes: All sequencing data are available in European Nucleotide Archive (ENA) under accession numbers ERS554424– ERS554471 .Supplementary Figures 1-17, Supplementary Tables 1-10, Supplementary Note 1 and Supplementary ReferencesD-statistic (ABBA-BABA test) values and standard error estimates for the inference of ancient admixture.Details of fixed non-synonymous changes in the exons of protein coding genes, including the per-individual and per-population read count for each allele.Pairwise genetic distance estimates and 100 bootstrap replicates.Pairwise relatedness estimates


FXN gene that results in epigenetic silencing of the FXN promoter. This silencing mechanism is seen in patient-derived lymphoblastoid cells but it remains unknown if it is a widespread phenomenon affecting multiple cell types and tissues.Friedreich ataxia is caused by an expanded GAA triplet-repeat sequence in intron 1 of the FXN gene with an expanded GAA triplet-repeat in intron 1, is deficient for FXN transcript when compared to an isogenic transgenic mouse lacking the expanded repeat (Y47R). We found that in YG8sR the deficiency of FXN transcript extended both upstream and downstream of the expanded GAA triplet-repeat, suggestive of deficient transcriptional initiation. This pattern of deficiency was seen in all tissues tested, irrespective of whether they are known to be affected or spared in disease pathogenesis, in both neuronal and non-neuronal tissues, and in cultured primary fibroblasts. FXN promoter function was directly measured via metabolic labeling of newly synthesized transcripts in fibroblasts, which revealed that the YG8sR mouse was significantly deficient in transcriptional initiation compared to the Y47R mouse.The humanized mouse model of Friedreich ataxia (YG8sR), which carries a single transgenic insert of the human FXN transcriptional deficiency in the humanized mouse model of Friedreich ataxia, similar to patient-derived cells, and the mechanism underlying promoter silencing in Friedreich ataxia is widespread across multiple cell types and tissues.Deficient transcriptional initiation accounts for  FXN gene [FXN transcript [Friedreich ataxia (FRDA) is the most common inherited ataxia and it is characterized clinically by sensory ataxia, cardiomyopathy, and a predisposition to diabetes . The disFXN gene . Non-FRDanscript . This pranscript ,5, ultimanscript . A preciFXN transcript by more than one molecular mechanism. Abnormal secondary DNA structures and repeat-proximal heterochromatin, both mediated by the expanded GAA-TR sequence, result in impedance of transcriptional elongation through intron 1 of the FXN gene [FXN gene promoter [FXN promoter, renders it transcriptionally non-permissive, and thereby causes a severe deficiency of transcriptional initiation [FXN promoter silencing [FXN promoter and the expanded GAA-TR mutation in intron 1. This mechanism of gene silencing, while compelling, has so far only been demonstrated in patient-derived lymphoblastoid cells [FXN transcriptional deficiency in multiple cell types and tissues, and thus its pathophysiological significance in FRDA remains unclear.The expanded GAA-TR sequence is thought to lead to deficiency of FXN gene ,7–9. Howpromoter . This mepromoter ,11–13, wpromoter . This spitiation . Indeed,ilencing , furtherid cells , 15. It FXN gene with an expanded GAA-TR mutation in a murine Fxn-/- background, is known to mimic the transcriptional deficiency seen in FRDA patients [FXN transcript is clearly seen across multiple tissues, making it an adequate model to study the mechanism of FXN transcriptional deficiency in the context of the human FXN gene. Indeed, the mild and late-onset phenotype in the YG8sR mouse has the advantage that tissues isolated from young YG8sR mice would allow analysis prior to the onset of disease-associated pathology and thus “affected” cell types would likely be well represented in the tissue samples. The Y47R mouse [The YG8sR humanized mouse model of FRDA, which contains the entire human patients . Admitte7R mouse , which hWe provide evidence that deficient transcriptional initiation accounts for the transcriptional deficiency in the YG8sR mouse model of FRDA, similar to patient-derived cells. Thus, the mechanism underlying promoter silencing in Friedreich ataxia, originally discovered in patient-derived lymphoblastoid cells, is likely widespread across multiple cell types and tissues.YG8sR and Y47R mice were bred, sacrificed and autopsied at 1 and 12 months of age at Brunel University London (U.K.) under humane conditions in accordance with the U.K. Home Office “Animals (Scientific Procedures) Act 1986” and with approval from the Brunel University London Animals Welfare and Ethical Review Board. Frozen tissue samples were sent on dry ice by overnight courier service to the University of Oklahoma Health Sciences Center for further analysis. DNA and RNA from tissues and cell lines were extracted using the DNeasy Blood and Tissue kit (Qiagen) and the RNeasy kit (Qiagen), respectively. The length of the GAA-TR sequence was analyzed by PCR amplification using previously described primers , and by ® reverse transcription kit (Qiagen). Transcript levels were quantified by real-time PCR and normalized relative to expression of the control Tbp gene  for experiments using fibroblasts, and normalized relative to the geometric mean of the control genes Psmd4  and Eef2  [® 96 Real-Time PCR system (Roche Diagnostics Corp) with SsoAdvanced™ Universal SYBR® Green Supermix (BioRad) or Power SYBR® Green PCR Master Mix (Life Technologies).This was done by reverse transcription followed by quantitative polymerase chain reaction (quantitative RT-PCR), using protocols and primer sequences as previously described . BrieflyGTGA-3’)  for mous® DNA polymerase (Life Technologies) supplemented with 1x LightCycler® 480 ResoLight dye (Roche Diagnostics Corp). Reference templates, to simulate 100% and 0% CpG methylation at the three sites, were generated by PCR using the same primers but starting with single-stranded long synthetic oligonucleotides either containing all three CpG sites intact (100% methylated) or all three CpG sites converted to TpG (0% methylated). Differential DNA melting was monitored by generating normalized melting curves on the LightCycler® 96 Real-Time PCR system (Roche Diagnostics Corp) by measuring fluorescence 15 times per°C change between 65°C and 97°C, using algorithms supplied by the manufacturer.The MS-HRM assay  is based® Nascent RNA Capture Kit (Life Technologies) as previously described [® VILO™ cDNA synthesis kit (Life Technologies). Nascent transcript levels were quantified by real-time PCR relative to expression of the control Tbp gene from total biotinylated RNA using the ΔΔCt method on the LightCycler® 96 Real-Time PCR system (Roche Diagnostics Corp) with SsoAdvanced™ Universal SYBR® Green Supermix (BioRad) or Power SYBR® Green PCR Master Mix (Life Technologies).This was done by metabolic labeling of nascent RNA using the Click-iTescribed . BrieflyFXN transcript levels both upstream and downstream of the expanded GAA-TR mutation in order to differentiate between defects in transcriptional initiation and transcriptional elongation through the expanded repeat. Deficiency of transcript at both locations would suggest a defect in transcriptional initiation, but deficiency at only the downstream location would suggest a defect in transcriptional elongation  and fibroblast cell lines derived from YG8sR and Y47R mice were selected for analysis of ongation . The tisongation .FXN gene (“Ex1”), and the spliced product of exons 3 & 4 (“Ex3-Ex4”) was selected as the downstream location  indicates that the YG8sR mouse is deficient in transcriptional initiation. Moreover, the fold-difference in accumulation of FXN transcript at the various time points in YG8sR versus Y47R were similar at both the upstream and downstream locations  and dowFXN-TSS; ) of the ocations . The defocations , suggestFXN transcriptional deficiency in the YG8sR humanized mouse model of FRDA is caused by deficient transcriptional initiation as a result of promoter silencing. While this mechanism has previously been noted in patient-derived lymphoblastoid cell lines [FXN transcriptional deficiency in FRDA is unlikely to be tissue-specific.Our results indicate that ll lines ,15, our It is noteworthy that tissues from the YG8sR mouse have a GAA-TR length of ~200 triplets and the fibroblast cell line contains only 133 triplets . In FRDAOur data indicate that the YG8sR humanized mouse is a reasonable model for investigating the molecular mechanism(s) underlying repeat-mediated promoter silencing in FRDA. The YG8sR mouse model would also be useful for testing drugs that are designed to reverse the transcriptional initiation defect caused by promoter silencing in FRDA, such as the 2-aminobenzamide derived histone deacetylase inhibitors ,26–28.S1 Fig(PDF)Click here for additional data file.S2 Fig(PDF)Click here for additional data file.S3 Fig(PDF)Click here for additional data file.


Plant diversity drives changes in the soil microbial community which may result in alterations in ecosystem functions. However, the governing factors between the composition of soil microbial communities and plant diversity are not well understood. We investigated the impact of plant diversity  and plant functional group identity on soil microbial biomass and soil microbial community structure in experimental grassland ecosystems. Total microbial biomass and community structure were determined by phospholipid fatty acid (PLFA) analysis. The diversity gradient covered 1, 2, 4, 8, 16 and 60 plant species and 1, 2, 3 and 4 plant functional groups . In May 2007, soil samples were taken from experimental plots and from nearby fields and meadows. Beside soil texture, plant species richness was the main driver of soil microbial biomass. Structural equation modeling revealed that the positive plant diversity effect was mainly mediated by higher leaf area index resulting in higher soil moisture in the top soil layer. The fungal-to-bacterial biomass ratio was positively affected by plant functional group richness and negatively by the presence of legumes. Bacteria were more closely related to abiotic differences caused by plant diversity, while fungi were more affected by plant-derived organic matter inputs. We found diverse plant communities promoted faster transition of soil microbial communities typical for arable land towards grassland communities. Although some mechanisms underlying the plant diversity effect on soil microorganisms could be identified, future studies have to determine plant traits shaping soil microbial community structure. We suspect differences in root traits among different plant communities, such as root turnover rates and chemical composition of root exudates, to structure soil microbial communities. The soil microbial community holds a central position in ecosystem processes like carbon and nitrogen cycling e.g., . The perPlant diversity influences a wide range of ecosystem processes, but the underlying mechanisms are not well understood We assessed the effect of plant diversity and functional group composition on soil microbial communities using phospholipid fatty acids (PLFAs) The field site of the Jena Experiment is located close to the city of Jena (Germany) in the floodplain of the river Saale . No specific permission was required to work on “The Jena Experiment” and no endangered or protected species were involved in this study. The soil (Eutric Fluvisol) has developed from up to 2 m thick fluvial sediments presenting a systematic variation of soil texture. The sand content decreases with distance to the river from 40% to 7%, while the silt and clay content increase . Experimental plots were arranged in four blocks parallel to the river to account for these differences in soil characteristics. Before the establishment of the Jena Experiment in 2002, the site was used as arable land since the early 1960s and ploughed and fertilized regularly. The Jena Experiment comprises 86 plots . The experimental design manipulates a gradient in sown plant species richness from 1 to 60  near-orthogonal with a gradient in plant of functional group numbers from 1 to 4 . All 60 species are typical for Central European mesophilic grasslands In early May 2007, six soil samples per plot were taken with a core cutter  to a depth of 5 cm, pooled and placed immediately in cooling boxes. Within 48 hours after sampling the soil was kept at 4°C, sieved <2 mm, remains of roots were manually removed and finally the samples were stored at −20°C until further sample processing. Soil samples were shaken with a mixture of chloroform, methanol and 0.05 M phosphate buffer (pH 7.4) to extract soil lipids Fine root standing biomass (termed as ‘root biomass’ hereafter), leaf area index (LAI) and soil moisture were considered as potentially meaningful covariables. Unfortunately, in 2007, the year of the PLFA sampling, root biomass was not determined, thus we used an average of 2006 and 2008 root biomass measurements. In both years root biomass was sampled to a depth of 30 cm. In addition, the sampling in 2008 was stratified, so that the 0–5 cm depth increment could directly related to the sample of the soil microbes. Based on the ratio of the top increment (0–5 cm) to the total root biomass in 2008, we calculated the specific root biomass in the top soil (0–5 cm). Furthermore, nitrogen concentration of fine roots was determined using root material from ingrowth cores from, sampled between 2007 and 2008 Using analyses of variance (ANOVA) followed by Tukey's HSD test we assessed microbial biomass and F:B ratio in experimental plots of the Jena Experiment, and their relationship to those from control plots (arable fields and meadows). ANOVA with sequential sum of squares (type I SS) was applied to test for effects of plant diversity on microbial biomass . The Jena Experiment is based on a factorial design with different combinations of plant species richness and number of functional groups, where all plots are arranged in a block design accounting for differences in soil texture among the blocks 2χ tests) and root mean square error of approximation (RMSEA) To investigate which mechanisms underlie the effects of plant diversity, we used structural equation modelling  on experimental plots (vegetated plots and bare ground). This was significantly higher than measured on plots of arable land (5.3±2.5 nmol g−1) and significantly lower than on meadows  than on vegetated plots (14.7±3.4 nmol g−1). Plant species richness had a significant positive effect on the total microbial biomass on vegetated plots  explained 45% of the variance of total microbial biomass. Total microbial biomass was mainly explained by its positive relationship to soil moisture. Soil moisture increased with increasing plant richness and higher clay content. The major effect on soil moisture was attributed to increasing leaf area index (LAI), which itself was strongly correlated to plant richness. The negatively influence of root nitrogen concentration on total microbial biomass was driven by higher root biomass, which itself was increased at higher plant richness.Structural equation modeling (SEM) showed that block (represented by the continuous variable clay content of soil) and plant richness, the design variables with significant influence indirectly affected total microbial biomass . The min2 = 0.67, P<0.001) than to bacterial biomass .The F:B ratio did not differ among experimental plots, arable plots and meadow plots  and Gram- bacteria  explained to 41% and 44% of variance, respectively, and revealed high analogy between the groups . In contrast to the bacterial groups, fungal biomass was neither affected by the amount of root biomass nor by its quality . In contrast to all other models, only direct paths connected the experimental variables to F:B ratio  the composition of PLFAs was similar. However, the dissimilarity of the microbial community composition was more pronounced in plots with different diversity levels, i.e., low diverse plots differed most from high diverse plots. Higher diversity in plant communities leads to more diverse organic matter input in quantity, quality and timing et al.Although bacteria and fungi were similarly affected by plant diversity, we found bacteria more related to plant diversity-controlled abiotic soil properties, while and fungi were more affected by the input of organic materials. As shown by de Vries We identified changes in microclimatic conditions, in particular increased soil moisture, as a main mechanism how plant diversity affects soil microbial biomass in the topsoil. Furthermore, the results indicate that shifts in the microbial community composition, namely in the F:B ratio, heavily rely on differences in the quality and quantity of root exudates. Changes in soil microbial biomass with plant diversity suggest that microbial communities of the established grassland systems develop towards permanent meadows, but that reaching the state of these meadows takes decades. Notably, however, differences in microbial biomass indicate that high diverse plant communities promote faster transition towards permanent meadows indicating that plant diversity is a key factor for restoring functional grassland systems on former arable land.Figure S1Scheme of the full model used in the structural equation modelling. The full model included simultaneously all measures of plant diversity with significant impact  on microbes. Measurements of plant inputs (fine root biomass (RBM), and nitrogen content of fine roots (N%) leaf area index (LAI), soil moisture (SM) and clay content of soil (Clay) have also been included in the model to explain the underlying mechanisms of the diversity effect.(TIF)Click here for additional data file.Table S1−1 dw (dry weight).Mean concentrations of identified PLFAs in nmol g(DOCX)Click here for additional data file.Table S2−2] (RBM), nitrogen content of fine root biomass [%] (N%).Correlation matrix of the predictors. Abbreviations are: Block numeric (Bl_num), logarithmic plant species richness (log_PSR), number of plant functional groups (FG), presence/absence of grasses (gras), presence/absence of small herbs (sherb), presence/absence of tall herbs (therb), presence/absence of legumes (leg), soil content of clay [%] (clay), leaf area index (LAI), fine root standing biomass [g m(DOCX)Click here for additional data file.Table S3Estimates of the minimal adequate structural equation models (maximum likelihood) for a) Total microbial biomass (MicMB b) Gram positive bacteria (Gram+), c) Gram negative bacteria (Gram-), d) Fungal-to-bacterial ratio (F:B ratio) and e) Fungi.(DOCX)Click here for additional data file.


These genes code for proteins that are responsible for metabolizing dietary products that originate from distinctly different food types: sugar, meat, and starch, respectively. After surveying copy number variation among dogs with diverse dietary histories, we found no correlation between diet and positive selection in either GCKR or PHYH. Although it has been previously demonstrated that dogs experienced a copy number increase in AMY2B relative to wolves during or after the dog domestication process, we demonstrate that positive selection continued to act on amylase copy number in dog breeds that consumed starch-rich diets in time periods after domestication. Furthermore, we found that introgression with wolves is not responsible for deterioration of positive selection on AMY2B among diverse dog breeds. Together, this supports the hypothesis that the amylase copy number expansion is found universally in dogs.Prolonged human interactions and artificial selection have influenced the genotypic and phenotypic diversity among dog breeds. Because humans and dogs occupy diverse habitats, ecological contexts have likely contributed to breed-specific positive selection. Prior to the advent of modern dog-feeding practices, there was likely substantial variation in dietary landscapes among disparate dog breeds. As such, we investigated one type of genetic variant, copy number variation, in three metabolic genes:  The remarkable phenotypic diversity amongst dog breeds has been affected in part by intensive and prolonged human-facilitated artificial selection since the initial period of dog domestication . FollowiThough the exact timespan and location of initial dog-human cohabitation and domestication remains unclear, humans and dogs have lived amongst one another for thousands of years –6. ConseAlthough the driving forces of dog domestication by humans remains unclear, dogs have nonetheless evolved suites of dietary and metabolic adaptations that have been argued to reflect their direct interaction with humans. It has been suggested that humans provided food for local dogs both directly and indirectly throughout dog-human coevolution . For exaOver time, and via cohabitation, the canine diet has been transformed from the carnivorous diet of its ancestor, the wolf, to a diet more closely matching that of omnivorous humans . This trSelection on variability in both single-base pair and copy number variants may underlie key metabolic changes in the domesticated dog. Interestingly, in instances of prolonged dog-human cohabitation, there is evidence of parallel evolution in metabolic genes. For example, compared to native Chinese dogs, Tibetan mastiffs have 33 SNPs in 11 genes that display signatures of positive selection, the majority of which cluster in 9 genes related to high-altitude adaptations . Likewisglucokinase regulator (GCKR), which plays a key role in maintaining blood glucose homeostasis; phytanol CoA 2-hydroxylase (PHYH), which codes for the protein responsible for the first step of phytanic acid digestion [pancreatic α-amylase 2B (AMY2B), which, as discussed above, is involved in the starch digestion.The goal of this study was to investigate how potential selection pressures created by exposure to different diets affected copy number variation (CNV) in six dog breeds from diverse dietary backgrounds: Pekingese, Shar Pei, Shiba Inu, Akita, Siberian Husky, and Alaskan Malamute. The Pekingese and Shar Pei likely consumed high-starch diets ,24–26, wigestion  often foigestion ; and panAMY2B gene of dog breeds with both starch-rich and starch-poor diets, we were able to explore the relationship between diet and copy number post-domestication when diet likely depended greatly on location and human interactions. We found evidence that positive selection continued to affect AMY2B CNV in dog breeds that consumed starch-rich diets, but that genetic drift affected AMY2B CNV more in dogs that began consuming starch-poor diets. The data presented in our study support early positive selection on increased AMY2B CNV across all breeds of domesticated dogs.By further investigating copy number variation in the GCKR, PHYH, and AMY2B, we determined a crude dietary composition by probing archaeological and ethnographic records (Methods). We also determined the copy number of each individual in each gene using digital droplet PCR (Methods). We found that sugar intake did not predict GCKR copy number across breeds. Specifically, dogs with moderate sugar intake  had a mean CNV of 8.1±3.6, while dogs with low sugar intake  had a mean CNV of 7.8±2.5  (To investigate the impact of diet on copy number variation in p = .01) . AlthougGCKR copy number may play a role in diabetes incidence in some dog breeds [GCKR CNV was compared to diabetes risk for breeds for which this information was available . Two breeds, the Siberian Husky and the Pekingese, both had duplications relative to the reference sequence CanFam2. However, the diabetes risk for these two breeds was not the same, with Pekingese having lower risk and the Siberian Husky having higher risk. In addition, the Alaskan Malamute, which experienced both gains and losses relative to CanFam2, displayed no evidence of increased risk for diabetes , 16.2±7.1 was not significantly different from that of dogs that consumed low phytanic acid diets  which had a mean CNV of 15.5±5.4  (We next investigated the relationship between our proxies of dietary intake of phytanic acid and p = .48) . Though AMY2B copy number in our expanded dataset, which includes dog breeds representing localities with historically low levels of dietary starch intake (Methods). Consistent with studies with more limited datasets, we found that AMY2B CNV did vary with dietary starch intake. Dogs with high-starch diets  had a statistically significant higher mean CNV of 10.9±2.2, compared to dogs with low-starch diets  with a mean CNV of 7.4±4.2  (AMY2B copies (74%) was more than two times greater than that for the low starch consuming dogs (33%).Given the history of studies on the role of amylase CNV and starch digestion in humans  and dogs= .0004) . ImportaAMY2B CNV within breeds and found that AMY2B copy number also differed between high and low starch consuming dogs  for the Alaskan Malamute and Shar Pei in order to compare patterns in AMY2B CNV to genome-wide patterns in CNV. This comparison allowed us to investigate if positive selection acted on AMY2B copy number differently in dog breeds with disparate starch intake. Previously, aCGH data from copy number variable sites was compiled for four Alaskan Malamutes and five Shar Pei dogs [http://www.ncbi.nlm.nih.gov/geo/ accession number GSE26170). This distribution was used to compare the extent of breed-level differentiation at the AMY2B locus to other genomic loci for the Alaskan Malamute and the Shar Pei.Although our ddPCR data preliminarily suggest and build upon previous suppositions relating to positive selection acting on Pei dogs  (GEO httAMY2B CNV mean log2 ratio (Methods) deviated substantially from the null distribution of other copy number variable sites in the genome, we analyzed residuals of AMY2B to a linear regression line fit to the aCGH data. We found that AMY2B fell 5.8 standard deviations away from the mean, indicating that in one or both breeds, AMY2B has experienced unusual evolutionary pressures dissimilar to those experienced at other copy number variable sites throughout the genome . However, variation in AMY2B CNV increased with increasing absolute latitude  selection signal or random forces, we sought to determine if phylogeny played a role. Given the limited statistical power to detect phylogenetic signal using a dataset consisting of only six dog breeds, phylogeny could not be controlled for with traditional methods . Insteadadograms ,39, eachese dogs  Fig 5),,AMY2B CNAMY2B low copy number in the low-starch breeds, we determined the difference of derived allele frequency (ΔDAF) between our dog samples and our wolf samples for every locus in the genome for which we had genotype data (Methods). As a control, we confirmed that there was no difference between the genome-wide ΔDAF distribution and that on chromosome 6  at higher frequency than the high-starch breeds. We identified three aiSNPs in the AMY2B region of the genome. Of the two dog breeds with the highest frequency of the “wolf” allele at these three loci, one was a high-starch, high-CNV breed, and the other was a low-starch, low-CNV breed . This highlights a broader need for technologies with increased accuracy in copy number resolutions especially for high copy variants. Without reliable copy number reads especially for those at the extreme high end of the distribution , it is difficult to speculate what selective factors may have driven copy number changes within each dog breed. However, given that dietary phytanic acid is toxic at high concentrations [PHYH function and CNV detection, using better methods when they become available, should examine if copy number balances the relative importance of each pathway.Our copy number analysis and results obtained for trations ,44 and ttrations , furtherAMY2B copy number may have been subject to positive selection in multiple breeds that consumed starch-rich diets. Because aCGH data were only available for the Alaskan Malamute and the Shar Pei, the null hypothesis cannot be fully tested in other breeds. However, the pattern of AMY2B CNV observed in all dogs that consumed high starch is similar, as is the pattern observed in all dogs that consumed low starch. Analysis of global trends in AMY2B CNV in a variety of breeds also showed that this pattern is not isolated to the six breeds examined in-depth. Although structural instability in this genomic region could create a high degree of variability in copy number variation, there is no evidence that the AMY2B region shows an unusually high level of instability [Importantly, data obtained from ddPCR and aCGH suggested that tability  and any AMY2B copy number mirrors results obtained from ddPCR. Indeed, AMY2B variation increases with increasing latitude, and although latitude does not predict copy number, as starch consumption decreases, variation in copy number increases.These findings also extend species-wide. For example, when absolute latitude is used as a proxy for starch intake, global variation in AMY2B copy number is substantially increased in domestic dogs relative to wolves. This study presents evidence that in dog breeds that were exposed to starch-rich diets, positive selection continued to influence AMY2B copy number after this initial copy number expansion. Our findings also indicate that in dog breeds that adopted starch poor diets after copy number expansion, copy number likely evolved via genetic drift or via weak negative selection.These findings expand upon the recent study of Axelsson and colleagues , which fAMY2B locus, suggesting that “the AMY2B copy number expansion was not fixed across all dogs early in the domestication process” [AMY2B CNV ranged from three to four. On the contrary, with our expanded sampling strategy and use of ddPCR, which has slightly better ability to accurately call high CNV genotypes, we observed a copy number range from 2–15 in huskies, which, like all other breeds that have been surveyed, suggests that the copy number expansion event may likely have occurred prior to the split of modern major breeds worldwide. Of the 17 huskies we included in this study, four had a CNV of four or lower, which likely reflects genetic drift rather than possible introgression of alleles from wolves, though we cannot rule out introgression by other low CNV breeds. In summary, our observed patterns further validate that dogs experienced copy number expansion and that variation in CNV distribution likely reflects early positive selection at the AMY2B locus after initial expansion [Previously, it has been reported that the Siberian Husky has not experienced copy number expansion at the process” . This waImportantly, the Japanese dog breeds we sampled may represent breeds in transition between drift and positive selection. It is likely that both breeds lived among the ancient hunter-gatherer cultures that existed prior to the agriculturalists that began dominating Japan roughly 2000 years ago . The timAMY2B CNV expansion, and likely before global migration of the ancestors to modern dogs. Given the genetic patterns identified in this study, we propose a model in which starch-rich diets predominated among most dog breeds coinciding with or shortly after the AMY2B CNV expansion and proliferation.These findings provide support for the idea that starch-rich diets were consumed after AMY2B copy number expansion was likely influenced by positive selection pressure due to high-starch intake, we still find several individuals in low-starch breeds with high AMY2B copy numbers. For example, of Alaskan Malamutes sampled, close to 1/3 of individuals have a high CNV. We see three possible scenarios that could explain this finding. Scenario one calls for relatively recent positive selection for the high CNV, such that this pressure leads to the high CNV in already-differentiated high-starch dog breeds. In this case, the presence of some high copy numbers in the low-starch breeds is due to recent admixture between high- and low-starch dog breeds. We consider this scenario to be unlikely as there is no evidence of such introgression [AMY2B copy number, we reject this scenario.Although our findings suggest that gression . Both scAMY2B expansion and before migration and differentiation of high- and low-starch breeds, coinciding with local starch consumption by humans. In turn, high starch consumption created positive selective pressure that likely acted on standing variation in AMY2B CNV to increase copy number species-wide. As some dog breeds migrated away, the selection pressure for high AMY2B CNV was maintained if dogs continued to consume starch-rich diets, or AMY2B CNV was subject to genetic drift if starch-poor diets were adopted. In the case of persistent positive selection, variation in AMY2B was kept low as selection pushed copy numbers toward an adaptive optimum. In the case of relaxed selection and genetic drift, variation increased throughout the dog breed and in certain locations, variation increased throughout the dog breed, possibly combined with positive selection on the low copy number variant in these populations.We therefore find a third scenario to be the most likely. We propose a model in which starch-rich diets predominated among most dogs after AMY2B haplotype diversity using structural analyses in a variety of dog breeds in order to assess age and global distribution of haplotypes as has been carried out for the AMY2A locus in humans using 1000 Genomes datasets [In order to further test our hypotheses, future research should analyze datasets . Future AMY2B, GCKR, and PHYH.To investigate the relationship between diet and genetic polymorphisms located in and around key metabolic genes, DNA samples and dietary information were collected from multiple dog breeds  Tables. AMY2B, CNV calls were also aggregated from other published studies [AMY2B CNV calls from sixty-five other dog breeds were also included [For statistical analysis of  studies ,15,22. Eincluded ,15,22. FAMY2B CNV calls were made on these samples; however, this data provided a comparative framework for analyses of other AMY2B CNV calls.Finally, array-based comparative genomic hybridization (aCGH) data were obtained for four Alaskan Malamutes and five Shar Peis . No AMY2DNA samples were swabbed from the buccal side of each dog’s cheek using VWR Foam-Tipped Swab . Age and sex were not regarded, except all dogs sampled were older than six months of age. Following standard procedures, each sample was placed in an open 2.0 mL tube to dry for two hours and then closed and stored at -20°C until DNA extraction. DNA was extracted with the QIAamp mini DNA kit (Qiagen) using the Buccal Swab Protocol (Qiagen). Extracted samples were stored in 150 μL Buffer AE (Qiagen) at -20°C.All dog samples were collected with owner’s permission. We received exemption from the oversight of the Institutional Animal Care and Use Committee of Harvard University. No dogs were hurt or adversely affected by the collection process.AMY2B was performed as described in Arendt et al. [GCKR and PHYH were adapted from Nicholas et al. [AMY2B, GCKR, PHYH and reference genes are located in Three CNV assays were performed on all collected samples. All copy number variants were determined using droplet digital PCR (ddPCR). Previously, real-time PCR (qPCR) has been used to study CNV in select breeds ,15, howet et al. . ddPCR as et al. . For allStatistical analyses of copy number variants were performed using the StatPlus package for Microsoft Excel, as well as in R. Modeling and graphics were created using Excel and R. The Robust Rank Order Test was employed to test differences in medians because it does not assume that the populations have the same shape or variances . FlignerAMY2B CNV mean log2 ratio deviated substantially from the null distribution of other copy number variable sites in the genome, we analyzed residuals of AMY2B to a linear regression line fit to the aCGH data. 156 CNV sites were present in at least one Alaskan Malamute and one Shar Pei in the aCGH data. aCGH data are presented as log2 ratios that represent the amount of genetic material present relative to a common control (CanFam2) at each surveyed SNP. The mean log2 ratio was calculated for each site in both the Alaskan Malamute and the Shar Pei by averaging all log2 ratios within each copy number variable site. Next, mean log2 ratios for the Alaskan Malamute and the Shar Pei were plotted against each other to produce a null distribution for the relationship between standard genomic CNV in the Alaskan Malamute and the Shar Pei.To determine if 2 ratio for AMY2B in Alaskan Malamutes and Shar Peis were added to the null distribution. Mean log2 ratios were calculated relative to CanFam2 and by using the AMY2B CNV data produced by ddPCR.The mean log2 ratios to determine if AMY2B CNV deviated  and those above 40° latitude (n = 177). A Fligner-Killeen test was run between the two groups to test homogeneity of variances [Latitude at location of dog origin was used to determine breed-level designation of starch intake for breeds with published ariances .ΔDAF = DAFdogs—DAFwolves. Genotype information came from analyses conducted by vonHoldt and colleagues [The difference of derived allele frequency (ΔDAF) was determined according to the following formula, lleagues . The mealleagues  in whichS1 FigCladogram depicting the relationship between the dog breeds evaluated in this study and diploid AMY2B copy number.(PDF)Click here for additional data file.S2 FigGCKR deviates from the null distribution. The location of PHYH likely reflects error in ddPCR measurements due to high copy number.Relationship between Shar Pei and Alaskan malamute mean log2 ratios for 157 copy number variable sites in the dog genome. (PDF)Click here for additional data file.S1 AppendixAMY2B CNV using additional datasets.Analyses of (PDF)Click here for additional data file.S2 AppendixAnalyses of aCGH datasets across a number of dog breeds.(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 Table(PDF)Click here for additional data file.S6 Table(PDF)Click here for additional data file.S7 Table(PDF)Click here for additional data file.S8 Table(PDF)Click here for additional data file.S9 Table(PDF)Click here for additional data file.S10 Table(PDF)Click here for additional data file.


Whole exome sequencing (WES) is increasingly used in research and diagnostics. WES users expect coverage of the entire coding region of known genes as well as sufficient read depth for the covered regions. It is, however, unknown which recent WES platform is most suitable to meet these expectations. We present insights into the performance of the most recent standard exome enrichment platforms from Agilent, NimbleGen and Illumina applied to six different DNA samples by two sequencing vendors per platform. Our results suggest that both Agilent and NimbleGen overall perform better than Illumina and that the high enrichment performance of Agilent is stable among samples and between vendors, whereas NimbleGen is only able to achieve vendor- and sample-specific best exome coverage. Moreover, the recent Agilent platform overall captures more coding exons with sufficient read depth than NimbleGen and Illumina. Due to considerable gaps in effective exome coverage, however, the three platforms cannot capture all known coding exons alone or in combination, requiring improvement. Our data emphasize the importance of evaluation of updated platform versions and suggest that enrichment-free whole genome sequencing can overcome the limitations of WES in sufficiently covering coding exons, especially GC-rich regions, and in characterizing structural variants. As a widely used method in genomic research and gene diagnostics, whole exome sequencing (WES) has the potential both to capture the entire coding region of all known genes including flanking intronic regions and to provide sequence data from these enriched genomic regions with sufficient read depth using a high-throughput DNA sequencing technology –6. WithoSince performance comparisons of three major commercial exome enrichment platforms from Agilent, NimbleGen and Illumina were reported –6, new vHere, from the perspective of WES users, we present a performance evaluation of exome captures from Agilent (SureSelect v5+UTR), NimbleGen (SeqCap v3+UTR) and Illumina (Nextera Expanded Exome) applied to six human DNA samples extracted from blood, saliva or cultured cells and sequenced by different providers (vendors). One vendor (V1) used all three platforms and applied the same data analysis workflow , ensuring best comparability. In order to avoid vendor bias and to assess the reproducibility of capture performance, each platform was used by an additional vendor specialized in the respective platform  as well, resulting in two sets of WES data per platform for all six samples. This study design allowed us to evaluate and compare the platforms not only within the same experimental and bioinformatics setting, similar to studies of previous platform versions , but alsExomes of eight DNA samples  was previously performed for at least a subset of genes listed in Supplementary Table S1 –20.Genomic DNA was extracted from EDTA-anticoagulated peripheral whole blood samples, saliva and cells cultured from aortic walls or skin biopsies (fibroblasts) using either QIAamp DNA Mini kit (Qiagen) or Chemagic Magnetic Separation Module I  according to the manufacturer's instructions. Subsequently, some of the Chemagic extracted DNA samples were purified using QIAamp DNA Mini kit as well Table . DNAs weExome enrichment was performed using the most recent versions (available by the end of 2013) of commercial sequence capture kits from Agilent (SureSelect Human All Exon kit v5+UTR), NimbleGen (SeqCap EZ Exome (v3) +UTR) and Illumina (Nextera Rapid Capture Expanded Exome). The captured libraries were sequenced using a HiSeq 2000/2500 sequencer (Illumina) and 2 × 100 bp paired-end sequencing according to the manufacturers’ recommendations. As the size of the designed target regions differs among platforms (Supplementary Table S2), the total expected read number was adjusted by the vendors to obtain 100× coverage in all cases (i.e. sequencing at 100× was requested for each sample). In addition to or instead of this comparable coverage for each platform, the usage of comparable number of reads was not pursued as this would favour the platform with the smallest exome design (Illumina).Library preparation, sequence capture and high-throughput sequencing was performed by four different sequencing service providers vendors V1–V4) according to their standard workflow. One vendor (V1) sequenced all six genomic DNA samples using all three exome enrichment platforms, whereas the three other vendors sequenced the six DNAs using only one platform in which they were specialized . Moreover, for two out of the six DNA samples (7344 and 7739) WGS was also performed by three vendors  using Illumina's TruSeq DNA PCR-Free Sample Preparation Kit on a HiSeq 2000/2500 sequencer  enrichment of ∼7600 clinically relevant genes was exemplified for sample 7739 and two additional DNA samples using the Accuracy and Content Enhanced (ACE) clinical exome platform of Personalis with ∼4 μg DNA sequenced at 60× on a HiSeq2500 system . To determine the number of reads and the coverage at defined minimal read depth  of platform-specific target regions, RefSeq exons and the subset of exons analysed by Sanger sequencing and the ACE platform of Personalis, we used the SeqMonk program version v0.25.0/v0.26.0/v0.27.0 (http://www.bioinformatics.babraham.ac.uk/projects/seqmonk) with deduplicated BAM files and the settings ‘single-end reads’ for data import to enable the counting of individual reads and ‘remove exact duplicates’ for the option ‘feature probe generator’ (Supplementary Tables S4–S15). Genomic positions of target regions were downloaded from the platforms’ websites, whereas genomic coordinates of RefSeq exons were obtained from the UCSC Genome Browser . The GC content of RefSeq exons was calculated using the Galaxy platform . Data from the X and Y chromosomes were included in our data analyses. For arithmetic means, upper and lower confidence limits  were calculated using critical values of paired t-test distribution (P = 0.05) and indicated where appropriate.Raw data processing, sequence read alignment from FASTQ to BAM format and variant calling to generate VCF files were performed by the four vendors (Supplementary Table S3). For our downstream analyses, aligned BAM files with removed duplicated reads were used, which were either directly provided by vendors (V3 and V4) or deduplicated by us (V1 and V2) using Picard tools version 1.108 or 1.118 (In order to ensure the comparability of the platforms’ mutant (non-reference) allele enrichment performance, we restricted our analyses of the provided VCF files  to shared sequence variants targeted by the design of each platform and located in RefSeq coding exons completely covered at 20× by all six platform-vendor combinations. The restriction to such shared sequence variants should largely exclude possible false-positive allele calls. Moreover, in order to avoid the influence of the vendors’ different data analysis workflows, we generated genome VCF (gVCF) files, which store sequencing information for both variant and non-variant positions, by applying the same in-house bioinformatics pipeline to all six FASTQ files provided by V1–V4 for each DNA sample (Supplementary Table S3). These gVCF files were filtered to include only positions with ≥20 reads and >30 quality scores in all samples and a non-reference allele  detected in at least one of the six platform-vendor combinations within the platform's target region and 50-bp flanking sequences.From our Sanger sequencing data, a total of 78 different single nucleotide variants (SNVs) and 11 different indels are known to be heterozygous in at least one of the six DNA samples, including clinically relevant, disease-causing mutations (Supplementary Tables S1 and S16). Thirty-five variants (30 SNVs and 5 indels) are located within our region of interest (ROI) for clinical sequencing, which consists of the entire protein-coding exonic region with −50 and +20-bp flanking intronic sequences  and five SNVs affect UTR (Supplementary Table S1). Using deduplicated BAM and unfiltered VCF files (Supplementary Table S3), these variant positions were analysed for read depth, calling and fraction of non-reference  allele and GC content of 30-bp flanking sequences .In addition, three samples  were run on a NimbleGen CGH/LOH 6 × 630K array (Roche) according to the manufacturer's instruction. This array contains probes for a total of 501 common SNVs within RefSeq coding exons. Array data of these SNVs located within the designed target region of each platform and exons completely covered at 20× by all six platform-vendor combinations  were compared to the corresponding WES variant calls in the provided unfiltered and recalibrated VCF files (Supplementary Table S3). In this comparison, array positions with no array results or false-negative or false-positive calls in all three platforms were excluded .The copy number variant (CNV) detection capability of the platforms was assessed by comparing the relative read depth of exons with known deletions (i.e. one copy) to the read depth of normal flanking exons (i.e. two copies) in affected samples and controls using Integrative Genomics Viewer . In addition, we also assessed the detection of these deletions by applying the WES-specific CNV calling tools cnMOPS  and XHMMIn contrast to the designs (target regions) of previous platform versions, NimbleGen now offers the largest target region including coding and untranslated regions (UTR), covering 96 Mb (64 Mb coding + 32 Mb UTR) compared to 75 Mb (50 Mb coding + 25 Mb UTR) of Agilent and 62 Mb (42 Mb coding + 20 Mb UTR) of Illumina. Moreover, NimbleGen promises to capture the largest portion of the entire RefSeq coding exome (98%) followed by Illumina with 95% and Agilent with <94% , producing an appropriate alignment (BAM) file per DNA sample. In this study, for the six platform-vendor combinations, on average 55.2–90.4% of the raw reads remained after mapping and deduplication, with duplicates accounting for 8.4–37% of the mapped reads. Applying the same platform, the number of deduplicated mapped reads was significantly different between V1 and V2 (Agilent) as well as between V1 and V4 (Illumina). This difference is at least partially due to variation in the proportion of duplicated reads, suggesting the impact of laboratory workflow on WES  revealed that Agilent reached the expected mean read depth of 100 (100×) for RefSeq coding region (105 ± 17), 94.7 ± 1.2% of which were sequenced at 20×, i.e. with a read depth of at least 20 Figure .The uniformity of the coverage of RefSeq coding exons was assessed by calculating the fraction of exons reaching an average read depth within ±70% of mean read depth over all coding exons . With thIn addition, we assessed what proportion of RefSeq coding exons are completely (i.e. 100%) covered at ≥20× and hence suitable for clinical WES . RegardlTo assess the impact of GC content on enrichment performance, we plotted mean read depth as well as mean coverage at 20× against the GC content of RefSeq exons . The assessment of the effect of bioinformatics pipelines on WES variant detection, however, is beyond the scope of this study and should be addressed by further works focusing on this topic.Moreover, our gVCF files generated by using the same bioinformatics pipeline also allowed a comparative assessment of variant detection in all six platforms-vendor combinations. We thereby focussed on positions with ≥20 reads and >30 quality scores which were called as heterozygous by only one or by all but one platform and hence indicate possibly false-positive or false-negative variant calls. Agilent resulted in the lowest proportion of such putative calling errors  followed by NimbleGen (1.52 ± 0.10%) and Illumina (1.66 ± 0.19%) . However, high quality variants  called by all platforms may not be sufficient to exclude all putative alignment errors and other variant calling pipelines may also lead to different results. Indeed, WES users should be aware that for the same raw reads (FASTQ file) different read aligner and variant caller combinations may result in considerably different number of true and false variants . The lowest variation of Agilent and thus its potential for best CNV detection was confirmed by assessing 182 exons with copy numbers known from array CGH .Users of WES expect coverage of the entire coding region of all known genes and sufficient read depth for the covered regions. This comparative study provides the most recent and comprehensive data to answer the question of which current standard WES enrichment platform is most suitable to meet these expectations. By including different sequencing providers (vendors) and samples into our performance comparison, our study design allowed us to evaluate the three most recent standard exome enrichment platforms not only within the same experimental and bioinformatics setting but also between different settings and among different DNA sources. Our study focuses on the enrichment of both reference and non-reference alleles, keeping the influence of bioinformatics workflow, which is a matter of ongoing research, as low as possible. We observed that the Agilent SureSelect Human All Exon v5+UTR enrichment platform is superior to the other two platforms with regard to overall performance and robustness. This superior performance of the most recent Agilent platform is, however, not applicable to its previous versions as shown by comparisons in 2011  responsible for a particular disease phenotype exists.Indeed, WES may fail to capture such regions and have difficulties to detect CNVs. We observed that capture-free, especially PCR-free, WGS can overcome these limitations, making WGS superior to WES, at least in those cases. Furthermore, the exome is not a fixed entity and still subject to changes. Projects such as ENCODE  will enhSupplementary Data are available at NAR Online.


Tetraspanins are transmembrane proteins that serve as scaffolds for multiprotein complexes containing, for example, integrins, growth factor receptors and matrix metalloproteases, and modify their functions in cell adhesion, migration and transmembrane signaling. CD151 is part of the tetraspanin family and it forms tight complexes with β1 and β4 integrins, both of which have been shown to be required for tumorigenesis and/or metastasis in transgenic mouse models of breast cancer. High levels of the tetraspanin CD151 have been linked to poor patient outcome in several human cancers including breast cancer. In addition, CD151 has been implicated as a promoter of tumor angiogenesis and metastasis in various model systems.Cd151 deletion on mammary tumorigenesis by crossing Cd151-deficient mice with a spontaneously metastasising transgenic model of breast cancer induced by the polyoma middle T antigen (PyMT) driven by the murine mammary tumor virus promoter (MMTV).Here we investigated the effect of Cd151 deletion did not affect the normal development and differentiation of the mammary gland. While there was a trend towards delayed tumor onset in Cd151−/− PyMT mice compared to Cd151+/+ PyMT littermate controls, this result was only approaching significance . Interestingly, Cd151 deletion resulted in significantly reduced numbers and size of primary tumors but did not appear to affect the number or size of metastases in the MMTV/PyMT mice. Intriguingly, no differences in the expression of markers of cell proliferation, apoptosis and blood vessel density was observed in the primary tumors.The findings from this study provide additional evidence that CD151 acts to enhance tumor formation initiated by a range of oncogenes and strongly support its relevance as a potential therapeutic target to delay breast cancer progression. Breast cancer is the most commonly diagnosed cancer among women and despite some major advances in diagnosis and treatment, it remains the second leading cause of cancer death in women worldwide. Similarly to other cancers, some of the major challenges in the treatment of breast cancer reside in the lack of response or development of resistance to existing therapies and the devastating consequences of metastasis. Better prognostic markers as well as new targeted treatments that could be used alone, or most likely in combination with existing therapies are needed to improve patient outcomes.The tetraspanin CD151 is part of the tetraspanin family of transmembrane proteins, which consists of 33 members in humans. These proteins serve as scaffolds for multiprotein complexes  where they associate with molecules such as integrins, growth factor receptors and matrix metalloproteases, modifying their functions in various cellular processes. CD151 forms tight complexes with the laminin binding integrins  [in vitro in human breast cancer cell lines and in several in vivo model systems including xenografts [Interestingly, β1-integrin and β4-integrin- heterodimers (reviewed in ) are botnografts ,11, matrnografts , as wellnografts ,14. In anografts .Cd151 deletion on de novo breast tumorigenesis and spontaneous metastasis in the very well characterized MMTV/PyMT transgenic breast cancer mouse model [Altogether these data strongly indicate a role for CD151 in tumor growth and metastasis, suggesting that it could be used as a target molecule for the design of new breast cancer therapies. However, when we started this work, the possible direct cause-effect relationship between CD151 expression and breast tumor onset/progression and metastasis had never been tested. In order to address this question, we studied the effect of se model . In thisse model  and theyse model .Cd151 deletion in another mouse model of breast cancer (the ErbB2 model) has recently been published by Deng and colleagues [It is interesting to note that a study addressing the impact of lleagues . The resCd151–null mice develop smaller and fewer PyMT mammary tumors than their age matched controls. Our results suggest that Cd151 deletion impairs tumor initiation and/or tumor growth in the MMTV/PyMT model, while an apparent effect on tumor metastasis could be attributable to larger tumor burden in Cd151+/+ mice.Here we show that Cd151−/− mice are grossly healthy on the C57Bl/6 (B6) background [Cd151−/− mice could not be used for the tumorigenesis experiments. Since F1 hybrid FVB x B6 Cd151−/− mice were healthy and did not present any sign of kidney disease onset , we conducted the experiments on this hybrid background. This allowed us to keep all experimental animals on a mixed but yet homogenous (50% B6 and 50% FVB) genetic background. FVB Cd151+/− mice were produced by backcross for 10 generations from the original B6 Cd151−/−[Cd151+/− females were crossed with FVB Cd151+/− males carrying the MMTV/PyMT transgene  animal breeding facility . All animal monitoring and experiments were approved by the Animal Care and Ethics Committee at the University of Newcastle. In the tumorigenesis experiments, we used the well-characterized FVB/N (FVB) MMTV/PyMT mouse line (MT#634) carrying a mouse mammary tumor virus promoter-driven polyoma middle T transgene . A pure ckground  but theyckground . Hence F Cd151−/− and main2 inhalation, and all the tumors were dissected and weighed. For each experimental mouse, half of the biggest tumor was fixed in 10% neutral buffered formalin (NBF) for paraffin embedding, one quarter was snap frozen in liquid nitrogen, and the last quarter was snap frozen in OCT compound. At the time of dissection and after excision of the tumors, the lungs were exposed and inflated via tracheal injection of 1 ml of 10% NBF in order to inflate and fix the lung lobes. Lungs were then excised and further fixed in 10% NBF for at least 24 hours before paraffin embedding.Beginning at weaning (3 weeks of age), female mice were palpated twice weekly for the onset of mammary tumors. For each mouse, tumor palpation was performed in each of the ten mammary glands, in a genotype-blinded fashion. At 15–16 weeks of age, female mice were euthanased by COWhole mount analysis was performed by spreading inguinal #4 mammary glands onto poly-lysine slides followed by overnight fixation in 10% NBF, defatting in acetone and overnight staining in carmine alum  as previously described . The staTumor histology/stage was assessed on the largest tumor for each mouse using 5 μm paraffin sections stained with hematoxylin and eosin. Immunohistochemistry (IHC) was performed on 5 μm paraffin sections using a peroxidase VECTASTAIN ABC elite kit and DAB peroxidase substrate kit as per the manufacturer’s recommendations . The antibodies and dilutions used for IHC were rabbit monoclonal anti-Ki67 at 1:200  and polyclonal rabbit anti-cleaved caspase 3 at 1:800 .Immunofluorescence labelings were performed on 5 μm frozen sections as previously described . PrimaryThe largest tumor for each mouse was used to quantitate proliferation, apoptosis and vascularization in a genotype-blinded manner. Tumor cell proliferation was assessed by immunohistochemistry (as described above) for the commonly used Ki67 nuclear marker. Ki67 stained slides were scanned in a digital format using the Aperio™ digital pathology system (Aperio) and 200× magnification snapshots of digital images were generated using Imagescope. Quantitation of proliferation  was then performed on the 200× digital images using ImmunoRatio, a publicly available web-based application . The extTo estimate blood vessel density, CD31 immunofluorescence labeling was performed and Image J was used to quantitate the proportion of CD31 positive area inside the tumors. At least five fluorescent microscope pictures (100× magnification) per tumor were used in the CD31 analysis.2 of metatastases/cm2 lung) was calculated for each animal, using the data from 3 sections at least 100 μm apart, as previously described [All the lung lobes were dissected and processed for paraffin embedding. Five microns paraffin sections were stained with hematoxylin and eosin and slides were scanned in a digital format using the Aperio™ digital pathology system (Aperio). The lung area per section was measured using Scanscope and the metastatic burden . Kaplan-Meier survival curves were analysed with the log-rank test. Metastasis distribution was assessed with a contingency table and Chi-square test. All the other data sets were submitted to the Shapiro-Wilk normality test and depending on the result of this test, parametric or non-parametric comparison tests were performed. Specific tests used for each data set are mentioned in the figure legends. In all tests, Cd151 deletion on mammary tumorigenesis it was necessary to determine whether mammary gland development and differentiation was normal in Cd151 knock-out mice. For this purpose, we performed whole mount analysis of #4 inguinal mammary glands in virgin, pregnant and lactating FVB Cd151+/+ and Cd151−/− mice  background (see explanations in Methods). Consistent with previous reports showing increased PyMT tumor latency on the B6 background [To avoid the kidney phenotype that has been described in FVB −/− mice , we chosckground ,25, the Cd151+/+ and Cd151−/− PyMT mice  as compared to Cd151+/+  that was approaching significance . Interestingly, the median age to tumor onset in the heterozygous Cd151+/− mice was in between the values reported for Cd151+/+ and Cd151−/− PyMT mice . However, the difference between the median tumor latency of Cd151+/− versus Cd151+/+ mice was not significant (Log-rank test P = 0.7533).Investigation of mammary tumor onset by palpation showed no statistically significant difference in tumor latency between e Figure A. There P = 0.0003) and tumor multiplicity (P = 0.0008) per mouse were significantly decreased in the Cd151−/− group as compared to Cd151+/+ group , suggesting an effect of Cd151 gene deletion on both mammary tumor induction and growth/proliferation in vivo. Regardless of the Cd151 genotype, at least part of the largest tumor of each mouse had progressed to the carcinoma stage as determined by H&E staining , the mice were euthanased and all the tumors were collected and weighed for each mouse. Interestingly both the total tumor weight  and 20 out of 24 Cd151−/− (83%) mice developing lung metastases  and the average size of individual metastasis per mouse  were similar between the two groups  and whether the extent of hyperplasia is different between genotypes before a palpable tumor can be detected. The decreased number of detectable tumors could also reflect a pronounced defect in tumor growth. Indeed, the size of the mammary tumors was also reduced in Cd151−/− mice, as shown by the total tumor burden per mouse , as well as the individual tumor weight (represented as the weight of the largest tumor for each mouse). Intriguingly however we did not find a difference in tumor vascularisation or tumor cell proliferation and apoptosis that could explain the decreased tumor size in Cd151−/− mice. In conclusion, the absence of effect on tumor proliferation and apoptosis reinforces the hypothesis stated above that Cd151 deletion may act predominantly by delaying PyMT tumor initiation, as suggested by the trend towards delayed tumor onset and the decreased number of tumors per mouse.In this study, we found that deletion of de novo MMTV/PyMT tumors and because rich vascular networks do not develop at the periphery of tumors in this model.In recent years, Sadej and colleagues have reported a decrease in tumor growth associated with CD151 knock-down in a subcutaneous xenograft model [Cd151 deletion could affect tumor development indirectly through the microenvironment, by modifying the phenotype of the myoepithelial cells. However CD151 is also expressed, to a lesser extent, at the basolateral membrane of the luminal epithelium. It would be interesting to evaluate separately the specific effect of Cd151 deletion in the stroma  and the luminal epithelium/tumor cells respectively, using a conditional knock-out model. In addition, one could study the tumor cell autonomous versus microenvironment effect by performing orthotopic tumor grafts.Tumor progression in the MMTV/PyMT model has been very well characterized; it follows several well-defined stages from hyperplasia to non-invasive adenoma and finally invasive carcinoma . Loss ofCd151 deletion on tumor onset, growth and metastasis of another well characterized mouse mammary tumor model, the MMTV/Neu model . In their study, Deng and colleagues observed a significant delay in tumor onset as well as a decreased number of metastases per animal in the Cd151−/− and Cd151+/− groups compared with Cd151+/+ and they also suggest that the effects of CD151 in the MMTV/Neu model are largely mediated through α6β4 integrin. Together our data shows that Cd151 deletion significantly impairs tumor occurrence and growth. On assessment of lung metastasis, we obtained different results from Deng and colleagues. The median incidence, number and size of lung metastases did not vary with the Cd151 genotype in our study, and the higher metastatic burden in a proportion of wild-type mice was associated with increased primary tumors. These results suggest that ablation of Cd151 does not directly affect metastasis in the PyMT model. Future studies using experimental metastasis models will be required to elucidate the contradictory effects on metastasis in the MMTV/Neu and MMTV/PyMT models.A recent study  investigde novo tumorigenesis in mouse cancer models other than breast. Firstly, similarly to our results in the PyMT breast cancer model, Takeda and colleagues have demonstrated that CD151 promotes tumor incidence and multiplicity in a skin carcinogenesis model [Cd151 reduces spontaneous metastasis of prostate tumors in the TRAMP model [de novo tumorigenesis and/or spontaneous metastasis across a broad range of cancer types.In addition, two other studies have assessed the role of CD151 on is model . SecondlMP model . AltogetInterestingly, the functional role of CD151 in tumorigenesis and metastasis has been mainly linked to its association with the laminin receptors in the literature. These adhesion receptors include mostly α3β1, α6β1 and α6β4 integrins in the mammary epithelium. Laminin binding integrins have a well-documented role in malignant cell processes regulating crucial functions such as cell proliferation and invasion. β1-integrins represent the most predominantly expressed integrins in the mammary epithelium and their direct involvement in mammary tumorigenesis has been extensively demonstrated using mouse models of breast cancer. For example, it has been shown that β1-integrin is absolutely required for PyMT mammary tumor initiation and progression . SimilarCd151 deletion in the MMTV/PyMT model are likely to be mediated by a combination of both β1- and β4-integrins but this remains to be tested. In conclusion, our findings strongly support the relevance of CD151 as a potential therapeutic target to delay breast cancer progression.In summary, the results of this study show that CD151 enhances mammary tumor initiation and progression in the MMTV/PyMT mouse model but no direct effect on metastasis was demonstrated. The effects of IHC: Immunohistochemistry; NBF: Neutral buffered formalin; PyMT: Polyoma middle T antigen; MMTV: Mouse mammary tumor virus.The authors declare that they have no competing interests.SR and LKA conceived and designed the project. MJN participated in the analysis of mammary gland development and differentiation. J.W. participated in the tumor and metastasis data analysis. WJM provided the MMTV/PyMT mouse model and participated in the study design. BTC performed some of the immunohistochemical data analysis. SR and RGK carried out the monitoring of the mice and the tissue collections. SR analysed the data and drafted the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/14/509/prepubCd151+/+ and Cd151−/− experimental animals.Diagram representing the breeding protocol used to generate the F1 (FVBxB6) PyMT Click here for file50 indicates the median time to development of a palpable mammary tumor for each group of mice. The difference in T50 between FVB (42 d) and F1 FVB:B6 (62.5 d) was statistically significant (P=0.0001).Effect of the genetic background on MMTV/PyMT tumor onset. The appearance of mammary tumors in wild-type pure FVB or F1 FVB:B6 mice was monitored by bi-weekly palpation and is represented on a Kaplan-Meier survival curve. TClick here for file