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The development of a tuberculosis (TB) vaccine that induces sterilizing immunity to Mycobacterium tuberculosis infection has been elusive. Absence of sterilizing immunity induced by TB vaccines may be due to delayed activation of mucosal dendritic cells (DCs), and subsequent delay in antigen presentation and activation of vaccine-induced CD4[superscript +] T-cell responses. Here we show that pulmonary delivery of activated M. tuberculosis antigen-primed DCs into vaccinated mice, at the time of M. tuberculosis exposure, can overcome the delay in accumulation of vaccine-induced CD4[superscript +] T-cell responses. In addition, activating endogenous host CD103[superscript +] DCs and the CD40–CD40L pathway can similarly induce rapid accumulation of vaccine-induced lung CD4[superscript +] T-cell responses and limit early M. tuberculosis growth. Thus, our study provides proof of concept that targeting mucosal DCs can accelerate vaccine-induced T-cell responses on M. tuberculosis infection, and provide insights to overcome bottlenecks in TB vaccine efficacy., National Institutes of Health (U.S.) (grant HL105427), National Institutes of Health (U.S.) (grant AI127172), United States. Army Research Office. Institute for Soldier Nanotechnologies (contract W911NF-13-D-0001), Howard Hughes Medical Institute (Investigator)

Population bottlenecks may result in the loss of genetic diversity, with potentially negative consequences for species of interest in conservation biology, including rare species, invasive species and biological control agents. We examined mtDNA sequence data and four variable microsatellite loci (SSRs) in the melaleuca psyllid Boreioglycaspis melaleucae, which was introduced from Australia to Florida as a biological control agent of the invasive plant Melaleuca quinquenervia. We sampled psyllids in the native and introduced ranges as well as individuals stored from the original founding population. There was a clear loss of mtDNA haplotype diversity, as well as a loss of rare microsatellite alleles, in the introduced range. However, there was little genetic differentiation between the home and introduced ranges, and no evidence for a genetic bottleneck based on an analysis of heterozygosity with the microsatellite markers. Overall, the data showed that the demographic bottleneck had a limited effect on the genetics of populations in the new range.

Background Demographic bottlenecks can severely reduce the genetic variation of a population or a species. Establishing whether low genetic variation is caused by a bottleneck or a constantly low effective number of individuals is important to understand a species’ ecology and evolution, and it has implications for conservation management. Recent studies have evaluated the power of several statistical methods developed to identify bottlenecks. However, the false positive rate, i.e. the rate with which a bottleneck signal is misidentified in demographically stable populations, has received little attention. We analyse this type of error (type I) in forward computer simulations of stable populations having greater than Poisson variance in reproductive success (i.e., variance in family sizes). The assumption of Poisson variance underlies bottleneck tests, yet it is commonly violated in species with high fecundity. Results With large variance in reproductive success (V k ≥ 40, corresponding to a ratio between effective and census size smaller than 0.1), tests based on allele frequencies, allelic sizes, and DNA sequence polymorphisms (heterozygosity excess, M-ratio, and Tajima’s D test) tend to show erroneous signals of a bottleneck. Similarly, strong evidence of population decline is erroneously detected when ancestral and current population sizes are estimated with the model based method MSVAR. Conclusions Our results suggest caution when interpreting the results of bottleneck tests in species showing high variance in reproductive success. Particularly in species with high fecundity, computer simulations are recommended to confirm the occurrence of a population bottleneck.

Cave-dwelling taxa often share the same phenotypic modifications like absence of eyes and pigmentation. These “troglomorphic characters” are expressed in the populations of Garra barreimiae from the Al Hoota Cave and nearby Hoti Pit in Northern Oman. Surface morphotypes of this cyprinid species are common throughout the distribution area. Very rarely individuals with intermediate phenotypes can be found. In the present study, potential gene flow between cave and surface populations was tested and population structure within five sampling sites was assessed. Overall, 213 individuals were genotyped at 18 microsatellite loci. We found that the cave populations have lower genetic diversity and are clearly isolated from the surface populations, which seem to be sporadically in contact with each other. The results indicate a recent genetic bottleneck in the cave populations. Thus, it can be assumed that during climatic changes the connection between cave and surface water bodies was disjoined, leaving a subpopulation trapped inside. Nevertheless, occasional gene flow between the morphotypes is detectable, but hybridisation seems only possible in cave habitat with permanent connection to surface water. Individuals from surface sites bearing intermediate phenotypes but cave genotypes imply that phenotypic plasticity might play a role in the development of the phenotype.

We aimed to analyse the genetic diversity of Romanian wild boars and to compare it with that from other wild boar and pig populations from Europe and Asia. Partial sequencing of the mitochondrial encoded cytochrome b (MT-CYB) gene from 36 Romanian wild boars and 36 domestic pigs (Mangalitza, Bazna and Vietnamese breeds) showed that the diversity of Romanian wild boars and Mangalitza pigs is fairly reduced and that most of the members of these two populations share a common MT-CYB haplotype. Besides, in strong contrast with the Bazna animals, Romanian wild boars and Mangalitza swine did not carry Asian variants at the MT-CYB locus. The autosomal genotyping of 18 Romanian wild boars with the Illumina Porcine SNP60 BeadChip revealed that their genetic background is fundamentally European, even though signs of a potential Near Eastern ancestry (~25%) were detectable at K = 4 (the most significant number of clusters), but not at higher K-values. Admixture analysis also showed that two wild boars are of a hybrid origin, which could be explained by the mating of feral animals with domestic pigs. Finally, a number of Romanian wild boars displayed long runs of homozygosity, an observation that is consistent with the occurrence of past population bottlenecks and the raise of inbreeding possibly due to overhunting or to the outbreak of infectious diseases., This article was published under the frame of the European Social Fund, Human Resources Development Operational Program 2007–2013, project no. POSDRU/159/1.5/S/132765 awarded to VB. Part of the research presented in this publication was funded by grant AGL2013-48742-C2-1-R awarded by the Spanish Ministry of Economy and Competitivity to MA. We also acknowledge the support of the Spanish Ministry of Economy and Competitivity for the Center of Excellence Severo Ochoa 2016-2019 (SEV-2015-0533) grant awarded to the Center for Research in Agricultural Genomics.

European wolf (Canis lupus) populations have suffered extensive decline and range contraction due to anthropogenic culling. In Bulgaria, although wolves are still recovering from a severe demographic bottleneck in the 1970s, hunting is allowed with few constraints. A recent increase in hunting pressure has raised concerns regarding long-term viability. We thus carried out a com- prehensive conservation genetic analysis using microsat- ellite and mtDNA markers. Our results showed high heterozygosity levels (0.654, SE 0.031) and weak genetic bottleneck signals, suggesting good recovery since the 1970s decline. However, we found high levels of inbreeding (FIS = 0.113, SE 0.019) and a Ne/N ratio lower than expected for an undisturbed wolf population (0.11, 95 % CI 0.08-0.29). We also found evidence for hybrid- isation and introgression from feral dogs (C. familiaris )i n 10 out of 92 wolves (9.8 %). Our results also suggest admixture between wolves and local populations of golden jackals (C. aureus), but less extensive as compared with the admixture with dogs. We detected local population struc- ture that may be explained by fragmentation patterns dur- ing the 1970s decline and differences in local ecological characteristics, with more extensive sampling needed to assess further population substructure. We conclude that high levels of inbreeding and hybridisation with other canid species, which likely result from unregulated hunt- ing, may compromise long-term viability of this population despite its current high genetic diversity. The existence of population subdivision warrants an assessment of whether separate management units are needed for different sub- populations. Our study highlights conservation threats for populations with growing numbers but subject to unregu- lated hunting.

More accurate and precise phenotyping strategies are necessary to empower high-resolution linkage mapping and genome-wide association studies and for training genomic selection models in plant improvement. Within this framework, the objective of modern phenotyping is to increase the accuracy, precision and throughput of phenotypic estimation at all levels of biological organization while reducing costs and minimizing labor through automation, remote sensing, improved data integration and experimental design. Much like the efforts to optimize genotyping during the 1980s and 1990s, designing effective phenotyping initiatives today requires multi-faceted collaborations between biologists, computer scientists, statisticians and engineers. Robust phenotyping systems are needed to characterize the full suite of genetic factors that contribute to quantitative phenotypic variation across cells, organs and tissues, developmental stages, years, environments, species and research programs. Next-generation phenotyping generates significantly more data than previously and requires novel data management, access and storage systems, increased use of ontologies to facilitate data integration, and new statistical tools for enhancing experimental design and extracting biologically meaningful signal from environmental and experimental noise. To ensure relevance, the implementation of efficient and informative phenotyping experiments also requires familiarity with diverse germplasm resources, population structures, and target populations of environments. Today, phenotyping is quickly emerging as the major operational bottleneck limiting the power of genetic analysis and genomic prediction. The challenge for the next generation of quantitative geneticists and plant breeders is not only to understand the genetic basis of complex trait variation, but also to use that knowledge to efficiently synthesize twenty-first century crop varieties.

Conservation of locally adapted indigenous livestock breeds has become an important objective in sustainable animal breeding, as these breeds represent a unique genetic resource. Therefore, the Agricultural Research Council of South Africa initiated a conservation programme for four South African indigenous chicken breeds. The evaluation and monitoring of the genetic constitution of these conservation flocks is important for proper management of the conservation programme. Using molecular genetic analyses, the effective population sizes and relatedness of these conservation flocks were compared to village (field) chicken populations from which they were derived. Genetic diversity within and between these populations are further discussed within the context of population size. The conservation flocks for the respective breeds had relatively small effective population sizes (point estimate range 38.6–78.6) in comparison to the field populations (point estimate range 118.9–580.0). Furthermore, evidence supports a transient heterozygous excess, generally associated with the occurrence of a recent population bottleneck. Genetic diversity, as measured by the number of alleles, heterozygosity and information index, was also significantly reduced in the conservation flocks. The average relatedness amongst the conservation flocks was high, whilst it remained low for the field populations. There was also significant evidence for population differentiation between field and conservation populations. Fst estimates for conservation flocks were moderate to high with a maximum reached between VD_C and VD_F (0.285). However, Fst estimates for field population were excessively low between the NN_C and EC_F (0.007) and between EC_F and OV_F (0.009). The significant population differentiation of the conservation flocks from their geographically correlated field populations of origin is further supported by the analysis of molecular variance (AMOVA), with 10.51 % of genetic diversity ascribed to population differences within groups (FSC = 0.106). The results suggest that significant genetic erosion has occurred within the conservation flocks due to inbreeding, pronounced effects of random drift and selection. It might be necessary to introduce new breeding individuals from the respective field populations in order to increase the effective population sizes of the conservation flocks and counter the effects of genetic erosion. Electronic supplementary material The online version of this article (doi:10.1007/s11250-016-1030-9) contains supplementary material, which is available to authorized users.

This paper studies the morning commute problem under a flat peak-period toll (coarse toll) within the context of heterogeneous commuters. All the possible cumulative departure curves resulting from different choices of toll level and charging period are examined. The optimal toll schemes are then derived from minimizing the total travel cost of all commuters, excluding toll cost. We prove that at the optimum there will be no queue or capacity waste at the bottleneck at both the starting and ending points of the charging period for the type of Value-Of-Time (VOT) distribution considered in the paper. Moreover, the optimal coarse toll scheme is pareto-improving. Different from the homogeneous case, which can be regarded as a special case of the heterogeneous case, price discrimination occurs when commuters have different VOT. The optimal solution depends on the units in which the system cost is measured and we find that commuters in the middle pack of the VOT distribution are worse off by higher toll charges if the system cost is measured in money instead of time. A numerical example is provided at the end for demonstration.

Background Fuelled by the advent and subsequent development of next generation sequencing technologies, metagenomics became a powerful tool for the analysis of microbial communities both scientifically and diagnostically. The biggest challenge is the extraction of relevant information from the huge sequence datasets generated for metagenomics studies. Although a plethora of tools are available, data analysis is still a bottleneck. Results To overcome the bottleneck of data analysis, we developed an automated computational workflow called RIEMS – Reliable Information Extraction from Metagenomic Sequence datasets. RIEMS assigns every individual read sequence within a dataset taxonomically by cascading different sequence analyses with decreasing stringency of the assignments using various software applications. After completion of the analyses, the results are summarised in a clearly structured result protocol organised taxonomically. The high accuracy and performance of RIEMS analyses were proven in comparison with other tools for metagenomics data analysis using simulated sequencing read datasets. Conclusions RIEMS has the potential to fill the gap that still exists with regard to data analysis for metagenomics studies. The usefulness and power of RIEMS for the analysis of genuine sequencing datasets was demonstrated with an early version of RIEMS in 2011 when it was used to detect the orthobunyavirus sequences leading to the discovery of Schmallenberg virus. Electronic supplementary material The online version of this article (doi:10.1186/s12859-015-0503-6) contains supplementary material, which is available to authorized users.

Reduced genetic diversity due to founder effects often is expected for invasive populations. The present study examined two nuclear gene regions and one mitochondrial gene to evaluate the origins and genetic diversity of Gemma gemma, a ‘stow-away’ that was introduced to California more than 100 years ago with the importation of the Eastern oyster, Crassostrea virginica, from the United States’ Atlantic coast. A previous investigation involving mitochondrial DNA cytochrome-c-oxidase subunit I sequences reported no significant difference in haplotype diversity between the native and introduced populations; however, estimates of allelic (or haplotypic) variability are insensitive to losses of rare alleles that may accompany founder events and population bottlenecks. Estimates of allele richness and the distribution of rare alleles provide more sensitive indicators of such events. The present investigation of introduced and potential source populations identified lower allele richness and number of singleton alleles in California samples. Atlantic coast Gemma exhibit a sharp phylogeographic transition between northeastern (New York through New England) and mid-Atlantic (southern New Jersey through Virginia) subpopulations, which appear latitudinally inverted for the California Gemma populations. These genetic results, and information from the transportation history of the Eastern oyster, help to clarify processes involved in the introduction of this invasive species.

The bluntnose sixgill shark (Hexanchus griseus) is a widely distributed species found in tropical and temperate waters of every ocean, yet we know relatively little about their basic biology including their life history and population structure. From 2003–2007, we collected over 300 biopsy samples from sixgills during research operations in Puget Sound, WA, USA. Genotypic data using ten polymorphic microsatellites were used to describe sixgill genetic diversity, relatedness and mating pattern. Diversity within sixgills was found to be moderate with an average observed heterozygosity of 0.45, an average expected heterozygosity of 0.61, an average of 12 alleles per locus, and an average allelic richness of eight within microsatellite loci. Our data suggests all of the sampled individuals come from one intermixing population, and we found no historical evidence of significant population bottlenecks. Many of the sharks were sampled using longline techniques with several sharks captured at the same time and place. Similarly, multiple sharks were sampled on several occasions during research events at the Seattle Aquarium. The proportion of individuals that were full- or half-siblings was high among sharks sampled at the same time and place (range 0.65–0.87). Analysis of the genetic relationship between one large female washed ashore and 71 of her near-term pups suggested a polyandrous mating system with as many as nine males contributing to her offspring. This study is the first to investigate genetic diversity, relatedness and paternity within sixgill sharks and sheds light on important conservation implications for this little known shark population.

Background Secretory expression of valuable proteins by B. subtilis and its related species has attracted intensive work over the past three decades. Although very high yields can be achieved with homologous proteins, production of heterologous proteins by B. subtilis is unfortunately not the straight forward. The Sec pathway is the major route for protein secretion in B. subtilis. Therefore, the aim of this work was to identify the bottlenecks of the Sec pathway and improve the secretion of heterologous proteins by molecular genetic techniques. Results Two α-amylases (AmyL and AmyS) both under the control of the PHpaII promoter and equipped with their native signal peptides SPamyl and SPamyS were successfully secreted with significantly different expression levels. To improve the secretion efficiency, 23 main genes or gene operons involved in or closely related to the Sec pathway were overexpressed singly by increasing an additional copy on the chromosome, and the overexpression of prsA enhanced the production of α-amylases (AmyL and AmyS) by 3.2- and 5.5-fold, respectively. With the induction by xylose of different concentrations, prsA overexpression level was optimized and the secretion efficiency of α-amylase was further improved. Moreover, combinatorial overexpression of prsA and nine screened genes or gene operons, respectively, was performed, and the overexpression of prsA combined with partial dnaK operon improved the α-amylase activity of AmyL and AmyS by 160 and 173%, respectively, compared with the overexpression of prsA singly. Finally, the performance of the recombinant B. subtilis 1A237 was evaluated with the fed-batch fermentation in 7.5 L fermentor, and the level of secreted AmyL and AmyS reached 1,352 and 2,300 U/mL with the productivity of 16.1 U/mL h and 27.4 U/mL h, respectively. Conclusions Our systematic gene overexpression approach was designed to investigate the bottleneck of Sec pathway in B. subtilis. The deficiency of PrsA lipoprotein and chaperones of DnaK series was main rate-limiting factors for heterologous proteins secretion. Systematic and deep insight into how components of Sec pathway interact with each other may be the key to improving the yield of heterologous proteins thoroughly. Electronic supplementary material The online version of this article (doi:10.1186/s12934-015-0282-9) contains supplementary material, which is available to authorized users.

Background Deep-sequencing allows for an in-depth characterization of sequence variation in complex populations. However, technology associated errors may impede a powerful assessment of low-frequency mutations. Fortunately, base calls are complemented with quality scores which are derived from a quadruplet of intensities, one channel for each nucleotide type for Illumina sequencing. The highest intensity of the four channels determines the base that is called. Mismatch bases can often be corrected by the second best base, i.e. the base with the second highest intensity in the quadruplet. A virus variant model-based clustering method, ViVaMBC, is presented that explores quality scores and second best base calls for identifying and quantifying viral variants. ViVaMBC is optimized to call variants at the codon level (nucleotide triplets) which enables immediate biological interpretation of the variants with respect to their antiviral drug responses. Results Using mixtures of HCV plasmids we show that our method accurately estimates frequencies down to 0.5%. The estimates are unbiased when average coverages of 25,000 are reached. A comparison with the SNP-callers V-Phaser2, ShoRAH, and LoFreq shows that ViVaMBC has a superb sensitivity and specificity for variants with frequencies above 0.4%. Unlike the competitors, ViVaMBC reports a higher number of false-positive findings with frequencies below 0.4% which might partially originate from picking up artificial variants introduced by errors in the sample and library preparation step. Conclusions ViVaMBC is the first method to call viral variants directly at the codon level. The strength of the approach lies in modeling the error probabilities based on the quality scores. Although the use of second best base calls appeared very promising in our data exploration phase, their utility was limited. They provided a slight increase in sensitivity, which however does not warrant the additional computational cost of running the offline base caller. Apparently a lot of information is already contained in the quality scores enabling the model based clustering procedure to adjust the majority of the sequencing errors. Overall the sensitivity of ViVaMBC is such that technical constraints like PCR errors start to form the bottleneck for low frequency variant detection. Electronic supplementary material The online version of this article (doi:10.1186/s12859-015-0458-7) contains supplementary material, which is available to authorized users.

Background The population size of Atlantic walruses (Odobenus rosmarus rosmarus) is depleted relative to historical abundance levels. In Svalbard, centuries of over-exploitation brought the walrus herds to the verge of extinction, and such bottlenecks may have caused loss of genetic variation. To address this for Svalbard walruses, mitochondrial haplotypes of historical walruses from two major haul-out sites, Bjørnøya and Håøya, within the Archipelago were explored using bone samples from animals killed during the peak period of harvesting. Results Using ancient DNA methodologies, the mitochondrial NADH dehydrogenase 1 (ND1) gene, the cytochrome c oxidase 1 (COI) gene, and the control region (CR) were targeted for 15 specimens from Bjørnøya (of which five were entirely negative) and 9 specimens from Håøya (of which one was entirely negative). While ND1 and COI sequences were obtained for only a few samples, the CR delivered the most comprehensive data set, and the average genetic distance among historic Svalbard samples was 0.0028 (SD = 0.0023). Conclusions The CR sequences from the historical samples appear to be nested among contemporary Atlantic walruses, and no distinct mitochondrial haplogroups were identified in the historical samples that may have been lost during the periods of extensive hunting. However, given the low sample size and poor phylogenetic resolution it cannot be excluded that such haplogroups existed. Electronic supplementary material The online version of this article (doi:10.1186/s13104-016-1907-8) contains supplementary material, which is available to authorized users.

Background Previous studies documented the problem of inbreeding among Italian Greyhounds (IG) from the USA and its possible role in a multiple autoimmune disease syndrome. The present study is an extension of these earlier experiments and had two objectives: 1) to identify pockets of additional genetic diversity that might still exist among IG from the USA and Continental Europe, and 2) to determine how loss of genetic diversity within the genome and in the dog leukocyte antigen (DLA) complex relates to the problem of autoimmune disease in IG from the USA. Genetic testing was conducted using 33 short tandem repeat (STR) loci across 25 chromosomes and 7 STR loci that associated with specific dog leukocyte antigen (DLA) class I and II haplotypes. Standard genetic assessment tests based on allele frequencies and internal relatedness (IR) were used as measures of breed-wide and individual heterozygosity. Results The results of these tests demonstrated that IG from the USA and Continental Europe belonged to a single breed but were genetically distinguishable by genomic allele frequencies, DLA class I and II haplotypes, and principal coordinate analysis (PCoA). In the second part of the study, 85 IG from the USA that had suffered various autoimmune disorders (case) and 104 healthy dogs (control) of comparable age were studied for genetic associations with disease. Case dogs were found to be significantly more homozygous in the DLA regions than control dogs. Principal coordinate analysis did not differentiate case from control populations. No specific STR-associated DLA-class I or II haplotype was associated with increased autoimmune disease risks. Reasons for the loss of genetic diversity and increased homozygosity among IG from the USA were studied using registration data and deep pedigrees. The breed in the USA started from a small number of founders from Europe and has remained relatively isolated and small in numbers, limiting breeding choices especially in the period before modern transportation and artificial insemination. An additional cause of lost diversity and increased homozygosity has been the influence of famous sires and their show-winning progeny. The most influential of these sires was Ch. Dasa’s King of the Mountain (King) born in 1978. Virtually all contemporary IG from the USA have King at least once in 10 generation pedigrees and 18 % of the genome of contemporary IG from the USA is shared with King. Conclusions It was concluded that artificial genetic bottlenecks have concentrated numerous genetic polymorphisms responsible for autoimmune disease and that these risk factors did not originate in a specific individual or bloodline of the breed. Rather, they were of ancestral origin in both purebred and random bred dogs and inherited by descent. Italian Greyhound breeders in the USA have several options to improve breed health: 1) breed against homozygosity within the genome and in the DLA region, 2) avoid breeding dogs that have suffered an autoimmune disorder, 3) increase diversity by incorporating the genetic differences that exist in IG from Continental Europe, or 4) outcross to other small sighthound breeds. The latter two approaches must be undertaken with care to avoid introduction of new deleterious traits and to maximize retention and dissemination of new genetic diversity.

Background Identification of good metaphase spreads is an important step in chromosome analysis for identifying individuals with genetic disorders. The process of finding suitable metaphase chromosomes for accurate clinical analysis is, however, very time consuming since they are selected manually. The selection of suitable metaphase chromosome spreads thus represents a major bottleneck for conventional cytogenetic analysis. Although many algorithms have been developed for karyotyping, none have adequately addressed the critical bottleneck of selecting suitable chromosome spreads. In this paper, we present a software tool that uses a simple rule-based system to efficiently identify metaphase spreads suitable for karyotyping. Results The chromosome shapes can be classified by the software into four main classes. The first and the second classes refer to individual chromosomes with straight and skewed shapes, respectively. The third class is characterized as those chromosomes with overlapping bodies and the fourth class is for the non-chromosome objects. Good metaphase spreads should largely contain chromosomes of the first and the second classes, while the third class should be kept minimal. Several image parameters were examined and used for creating rule-based classification. The threshold value for each parameter is determined using a statistical model. We observed that the Gaussian model can represent the empirical probability density function of the parameters and, hence, the threshold value can be easily determined. The proposed rules can efficiently and accurately classify the individual chromosome with > 90% accuracy. Conclusions The software tool, termed MetaSel, was developed. Using the Gaussian-based rules, the tool can be used to quickly rank hundreds of chromosome spread images so as to assist cytogeneticists to perform karyotyping effectively. Furthermore, MetaSel offers an intuitive, yet comprehensive, workflow to assist karyotyping, including tools for editing chromosome (split, merge and fix) and a karyotyping editor (moving, rotating, and pairing homologous chromosomes). The program can be freely downloaded from "http://www4a.biotec.or.th/GI/tools/metasel".

Background Foxtail millet (Setaria italica (L.) P. Beauv.), one of the most ancient domesticated crops, is becoming a model system for studying biofuel crops and comparative genomics in the grasses. However, knowledge on the level of genetic diversity and linkage disequilibrium (LD) is very limited in this crop and its wild ancestor, green foxtail (Setaria viridis (L.) P. Beauv.). Such information would help us to understand the domestication process of cultivated species and will allow further research in these species, including association mapping and identification of agricultural significant genes involved in domestication. Results In this study, we surveyed DNA sequence for nine loci across 50 accessions of cultivated foxtail millet and 34 of its wild progenitor. We found a low level of genetic diversity in wild green foxtail (θ = 0.0059), θ means Watterson's estimator of θ. Despite of a 55% loss of its wild diversity, foxtail millet still harbored a considerable level of diversity (θ = 0.0027) when compared to rice and sorghum (θ = 0.0024 and 0.0034, respectively). The level of LD in the domesticated foxtail millet extends to 1 kb, while it decayed rapidly to a negligible level within 150 bp in wild green foxtail. Using coalescent simulation, we estimated the bottleneck severity at k = 0.6095 when ρ/θ = 1. These results indicated that the domestication bottleneck of foxtail millet was more severe than that of maize but slightly less pronounced than that of rice. Conclusions The results in this study establish a general framework for the domestication history of foxtail millet. The low level of genetic diversity and the increased level of LD in foxtail millet are mainly caused by a population bottleneck, although gene flow from foxtail millet to green foxtail is another factor that may have shaped the pattern of genetic diversity of these two related gene pools. The knowledge provided in this study will benefit future population based studies in foxtail millet.

Background Overexploitation of wildlife populations results in direct consequences, such as extinction and local extirpation, as well as indirect effects including genetic diversity loss and changes in genetic structure. A clear understanding of the underlying genetic patterns of harvested species is necessary for sustainable management. The Nile monitor (Varanus niloticus) is a commercially valuable species in the international leather industry, with the highest levels of exploitation concentrated throughout Sahelian Africa. In this study, we examined the fine-scale genetic patterns of V. niloticus populations in the Sahel, with the expectation that the genetic structure would correspond to riverine drainage basins. The analyses were based on genotypes at 11 microsatellite loci for 318 individuals, spanning three separate watersheds throughout the Sahel. Results Our analyses identified four genetic clusters throughout the region, one of which (the westernmost population) exhibited very high levels of genetic differentiation (FST = 0.47). Contrary to our expectation, the largest genetic break occurred within a single watershed, the Niger basin, rather than between watersheds. However, other localities displayed evidence of reduced gene flow between watershed boundaries. Across methods, the westernmost population exhibited lower estimates of Ne as well as lower levels of genetic diversity compared to the other inferred populations. While we did not detect evidence for recent population bottlenecks, our analyses indicated historic population declines around 1,000–1,800 years ago. Conclusion We found that the underlying genetic structure of Varanus niloticus across Sahelian Africa reflects historic as well as present-day patterns of riverine drainages. The high degree of differentiation found for the westernmost population indicates the presence of a separate lineage, and should be taken into consideration when setting harvest limits. The historic population decline for two of the populations corresponds to a drastic expansion of an ancient human civilization in the region, suggesting that human exploitation of V. niloticus has a longer history than previously thought. Electronic supplementary material The online version of this article (doi:10.1186/s12863-015-0188-x) contains supplementary material, which is available to authorized users.

BackgroundFragmentation of terrestrial ecosystems has had detrimental effects on metapopulations of habitat specialists. Maculinea butterflies have been particularly affected because of their specialized lifecycles, requiring both specific food-plants and host-ants. However, the interaction between dispersal, effective population size, and long-term genetic erosion of these endangered butterflies remains unknown. Using non-destructive sampling, we investigated the genetic diversity of the last extant population of M. arion in Denmark, which experienced critically low numbers in the 1980s.ResultsUsing nine microsatellite markers, we show that the population is genetically impoverished compared to nearby populations in Sweden, but less so than monitoring programs suggested. Ten additional short repeat microsatellites were used to reconstruct changes in genetic diversity and population structure over the last 77 years from museum specimens. We also tested amplification efficiency in such historical samples as a function of repeat length and sample age. Low population numbers in the 1980s did not affect genetic diversity, but considerable turnover of alleles has characterized this population throughout the time-span of our analysis.ConclusionsOur results suggest that M. arion is less sensitive to genetic erosion via population bottlenecks than previously thought, and that managing clusters of high quality habitat may be key for long-term conservation Background: Fragmentation of terrestrial ecosystems has had detrimental effects on metapopulations of habitat specialists. Maculinea butterflies have been particularly affected because of their specialized lifecycles, requiring both specific food-plants and host-ants. However, the interaction between dispersal, effective population size, and long-term genetic erosion of these endangered butterflies remains unknown. Using non-destructive sampling, we investigated the genetic diversity of the last extant population of M. arion in Denmark, which experienced critically low numbers in the 1980s.Results: Using nine microsatellite markers, we show that the population is genetically impoverished compared to nearby populations in Sweden, but less so than monitoring programs suggested. Ten additional short repeat microsatellites were used to reconstruct changes in genetic diversity and population structure over the last 77 years from museum specimens. We also tested amplification efficiency in such historical samples as a function of repeat length and sample age. Low population numbers in the 1980s did not affect genetic diversity, but considerable turnover of alleles has characterized this population throughout the time-span of our analysis.Conclusions: Our results suggest that M. arion is less sensitive to genetic erosion via population bottlenecks than previously thought, and that managing clusters of high quality habitat may be key for long-term conservation.

Background Network is a useful way for presenting many types of biological data including protein-protein interactions, gene regulations, cellular pathways, and signal transductions. We can measure nodes by their network features to infer their importance in the network, and it can help us identify central elements of biological networks. Results We introduce a novel Cytoscape plugin cytoHubba for ranking nodes in a network by their network features. CytoHubba provides 11 topological analysis methods including Degree, Edge Percolated Component, Maximum Neighborhood Component, Density of Maximum Neighborhood Component, Maximal Clique Centrality and six centralities (Bottleneck, EcCentricity, Closeness, Radiality, Betweenness, and Stress) based on shortest paths. Among the eleven methods, the new proposed method, MCC, has a better performance on the precision of predicting essential proteins from the yeast PPI network. Conclusions CytoHubba provide a user-friendly interface to explore important nodes in biological networks. It computes all eleven methods in one stop shopping way. Besides, researchers are able to combine cytoHubba with and other plugins into a novel analysis scheme. The network and sub-networks caught by this topological analysis strategy will lead to new insights on essential regulatory networks and protein drug targets for experimental biologists. According to cytoscape plugin download statistics, the accumulated number of cytoHubba is around 6,700 times since 2010.

Background Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the cloud computing and Software-as-a-Service (SaaS) technologies can help address these issues. Results We successfully enabled the Atlas2 Cloud pipeline for personal genome analysis on two different cloud service platforms: a community cloud via the Genboree Workbench, and a commercial cloud via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. Conclusions We find that providing a web interface and an optimized pipeline clearly facilitates usage of cloud computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms.

Many western European carnivore populations became almost or completely eradicated during the last ~200 years, but are now recovering. Extirpation of wolves started in Finland in the 19th century, and for more than 150 years the population size of wolves has remained small. To investigate historical patterns of genetic variation, we extracted DNA from 114 wolf samples collected in zoological museums over the last ~150 years. Fifteen microsatellite loci were used to look at genotypic variation in this historical sample. Additionally, we amplified a 430 bp sequence of mtDNA control region from the same samples. Contemporary wolf samples (N = 298) obtained after the population recovery in the mid-1990s, were used as a reference. Our analyses of mtDNA revealed reduced variation in the mtDNA control region through the loss of historical haplotypes observed prior to wolf declines. Heterozygosity at autosomal microsatellite loci did not decrease significantly. However, almost 20% of microsatellite alleles were unique to wolves collected before the 1960s. The genetic composition of the population changed gradually with the largest changes occurring prior to 1920. Half of the oldest historical samples formed a distinguishable genetic cluster not detected in the modern-day Finnish or Russian samples, and might therefore represent northern genetic variation lost from today’s gene pool. Point estimates of N e were small (13.2 and 20.5) suggesting population fragmentation. Evidence of a genetic population bottleneck was also detected. Our genetic analyses confirm changes in the genetic composition of the Finnish wolf population through time, despite the geographic interconnectivity to a much larger population in Russia. Our results emphasize the need for restoration of the historical connectivity between the present wolf populations to secure long-term viability. This might be challenging, however, because the management policies between Western and Eastern Europe often differ greatly. Additionally, wolf conservation is still a rather controversial issue, and anthropogenic pressure towards wolves remains strong.

Background: The study of genome rearrangements has become a mainstay of phylogenetics and comparative genomics. Fundamental in such a study is the median problem: given three genomes find a fourth that minimizes the sum of the evolutionary distances between itself and the given three. Many exact algorithms and heuristics have been developed for the inversion median problem, of which the best known is MGR. Results: We present a unifying framework for median heuristics, which enables us to clarify existing strategies and to place them in a partial ordering. Analysis of this framework leads to a new insight: the best strategies continue to refer to the input data rather than reducing the problem to smaller instances. Using this insight, we develop a new heuristic for inversion medians that uses input data to the end of its computation and leverages our previous work with DCJ medians. Finally, we present the results of extensive experimentation showing that our new heuristic outperforms all others in accuracy and, especially, in running time: the heuristic typically returns solutions within 1% of optimal and runs in seconds to minutes even on genomes with 25’000 genes–in contrast, MGR can take days on instances of 200 genes and cannot be used beyond 1’000 genes. Conclusion: Finding good rearrangement medians, in particular inversion medians, had long been regarded as the computational bottleneck in whole-genome studies. Our new heuristic for inversion medians, ASM, which dominates all others in our framework, puts that issue to rest by providing near-optimal solutions within seconds to minutes on even the largest genomes.

Background EST sequencing projects are increasing in scale and scope as the genome sequencing technologies migrate from core sequencing centers to individual research laboratories. Effectively, generating EST data is no longer a bottleneck for investigators. However, processing large amounts of EST data remains a non-trivial challenge for many. Web-based EST analysis tools are proving to be the most convenient option for biologists when performing their analysis, so these tools must continuously improve on their utility to keep in step with the growing needs of research communities. We have developed a web-based EST analysis pipeline called ESTPiper, which streamlines typical large-scale EST analysis components. Results The intuitive web interface guides users through each step of base calling, data cleaning, assembly, genome alignment, annotation, analysis of gene ontology (GO), and microarray oligonucleotide probe design. Each step is modularized. Therefore, a user can execute them separately or together in batch mode. In addition, the user has control over the parameters used by the underlying programs. Extensive documentation of ESTPiper's functionality is embedded throughout the web site to facilitate understanding of the required input and interpretation of the computational results. The user can also download intermediate results and port files to separate programs for further analysis. In addition, our server provides a time-stamped description of the run history for reproducibility. The pipeline can also be installed locally, allowing researchers to modify ESTPiper to suit their own needs. Conclusion ESTPiper streamlines the typical process of EST analysis. The pipeline was initially designed in part to support the Daphnia pulex cDNA sequencing project. A web server hosting ESTPiper is provided at http://estpiper.cgb.indiana.edu/ to now support projects of all size. The software is also freely available from the authors for local installations.

Background Emerging viral diseases, most of which are caused by the transmission of viruses from animals to humans, pose a threat to public health. Discovering pathogenic viruses through surveillance is the key to preparedness for this potential threat. Next generation sequencing (NGS) helps us to identify viruses without the design of a specific PCR primer. The major task in NGS data analysis is taxonomic identification for vast numbers of sequences. However, taxonomic identification via a BLAST search against all the known sequences is a computational bottleneck. Description Here we propose an enhanced lowest-common-ancestor based method (ELM) to effectively identify viruses from massive sequence data. To reduce the computational cost, ELM uses a customized database composed only of viral sequences for the BLAST search. At the same time, ELM adopts a novel criterion to suppress the rise in false positive assignments caused by the small database. As a result, identification by ELM is more than 1,000 times faster than the conventional methods without loss of accuracy. Conclusions We anticipate that ELM will contribute to direct diagnosis of viral infections. The web server and the customized viral database are freely available at http://bioinformatics.czc.hokudai.ac.jp/ELM/.

Background When characterizing the structural topology of proteins, protein secondary structure (PSS) plays an important role in analyzing and modeling protein structures because it represents the local conformation of amino acids into regular structures. Although PSS prediction has been studied for decades, the prediction accuracy reaches a bottleneck at around 80%, and further improvement is very difficult. Results In this paper, we present an improved dictionary-based PSS prediction method called SymPred, and a meta-predictor called SymPsiPred. We adopt the concept behind natural language processing techniques and propose synonymous words to capture local sequence similarities in a group of similar proteins. A synonymous word is an n- gram pattern of amino acids that reflects the sequence variation in a protein’s evolution. We generate a protein-dependent synonymous dictionary from a set of protein sequences for PSS prediction. On a large non-redundant dataset of 8,297 protein chains (DsspNr-25), the average Q 3 of SymPred and SymPsiPred are 81.0% and 83.9% respectively. On the two latest independent test sets (EVA Set_1 and EVA_Set2), the average Q 3 of SymPred is 78.8% and 79.2% respectively. SymPred outperforms other existing methods by 1.4% to 5.4%. We study two factors that may affect the performance of SymPred and find that it is very sensitive to the number of proteins of both known and unknown structures. This finding implies that SymPred and SymPsiPred have the potential to achieve higher accuracy as the number of protein sequences in the NCBInr and PDB databases increases. Conclusions Our experiment results show that local similarities in protein sequences typically exhibit conserved structures, which can be used to improve the accuracy of secondary structure prediction. For the application of synonymous words, we demonstrate an example of a sequence alignment which is generated by the distribution of shared synonymous words of a pair of protein sequences. We can align the two sequences nearly perfectly which are very dissimilar at the sequence level but very similar at the structural level. The SymPred and SymPsiPred prediction servers are available at http://bio-cluster.iis.sinica.edu.tw/SymPred/.

Background Repeat masking is an important step in the EST analysis pipeline. For new species, genomic knowledge is scarce and good repeat libraries are typically unavailable. In these cases it is common practice to mask against known repeats from other species (i.e., model organisms). There are few studies that investigate the effectiveness of this approach, or attempt to evaluate the different methods for identifying and masking repeats. Results Using zebrafish and medaka as example organisms, we show that accurate repeat masking is an important factor for obtaining a high quality clustering. Furthermore, we show that masking with standard repeat libraries based on curated genomic information from other species has little or no positive effect on the quality of the resulting EST clustering. Library based repeat masking which often constitutes a computational bottleneck in the EST analysis pipeline can therefore be reduced to species specific repeat libraries, or perhaps eliminated entirely. In contrast, substantially improved results can be achived by applying a repeat library derived from a partial reference clustering (e.g., from mapping sequences against a partially sequenced genome). Conclusion Of the methods explored, we find that the best EST clustering is achieved after masking with repeat libraries that are species specific. In the absence of such libraries, library-less masking gives results superior to the current practice of using cross-species, genome-based libraries.

A principal components analysis of genomic information showed that individuals with full Jewish ancestry formed a clearly distinct cluster from those individuals with no Jewish ancestry., Background It was recently shown that the genetic distinction between self-identified Ashkenazi Jewish and non-Jewish individuals is a prominent component of genome-wide patterns of genetic variation in European Americans. No study however has yet assessed how accurately self-identified (Ashkenazi) Jewish ancestry can be inferred from genomic information, nor whether the degree of Jewish ancestry can be inferred among individuals with fewer than four Jewish grandparents. Results Using a principal components analysis, we found that the individuals with full Jewish ancestry formed a clearly distinct cluster from those individuals with no Jewish ancestry. Using the position on the first principal component axis, every single individual with self-reported full Jewish ancestry had a higher score than any individual with no Jewish ancestry. Conclusions Here we show that within Americans of European ancestry there is a perfect genetic corollary of Jewish ancestry which, in principle, would permit near perfect genetic inference of Ashkenazi Jewish ancestry. In fact, even subjects with a single Jewish grandparent can be statistically distinguished from those without Jewish ancestry. We also found that subjects with Jewish ancestry were slightly more heterozygous than the subjects with no Jewish ancestry, suggesting that the genetic distinction between Jews and non-Jews may be more attributable to a Near-Eastern origin for Jewish populations than to population bottlenecks.

Background Relatively small, reproductively isolated populations with reduced genetic diversity may have advantages for genomewide association mapping in disease genetics. The Ashkenazi Jewish population represents a unique population for study based on its recent (< 1,000 year) history of a limited number of founders, population bottlenecks and tradition of marriage within the community. We genotyped more than 1,300 Ashkenazi Jewish healthy volunteers from the Hebrew University Genetic Resource with the Illumina HumanOmni1-Quad platform. Comparison of the genotyping data with that of neighboring European and Asian populations enabled the Ashkenazi Jewish-specific component of the variance to be characterized with respect to disease-relevant alleles and pathways. Results Using clustering, principal components, and pairwise genetic distance as converging approaches, we identified an Ashkenazi Jewish-specific genetic signature that differentiated these subjects from both European and Middle Eastern samples. Most notably, gene ontology analysis of the Ashkenazi Jewish genetic signature revealed an enrichment of genes functioning in transepithelial chloride transport, such as CFTR, and in equilibrioception, potentially shedding light on cystic fibrosis, Usher syndrome and other diseases over-represented in the Ashkenazi Jewish population. Results also impact risk profiles for autoimmune and metabolic disorders in this population. Finally, residual intra-Ashkenazi population structure was minimal, primarily determined by class 1 MHC alleles, and not related to host country of origin. Conclusions The Ashkenazi Jewish population is of potential utility in disease-mapping studies due to its relative homogeneity and distinct genomic signature. Results suggest that Ashkenazi-associated disease genes may be components of population-specific genomic differences in key functional pathways.

Self-incompatibility (SI) to self-compatibility (SC) transition is one of the most frequent and prevalent evolutionary shifts in flowering plants. Prunus L. (Rosaceae) is a genus of over 200 species most of which exhibit a Gametophytic SI system. Peach [Prunus persica (L.) Batsch; 2n = 16] is one of the few exceptions in the genus known to be a fully self-compatible species. However, the evolutionary process of the complete and irreversible loss of SI in peach is not well understood and, in order to fill that gap, in this study 24 peach accessions were analyzed. Pollen tube growth was controlled in self-pollinated flowers to verify their self-compatible phenotypes. The linkage disequilibrium association between alleles at the S-locus and linked markers at the end of the sixth linkage group was not significant (P > 0.05), except with the closest markers suggesting the absence of a signature of negative frequency dependent selection at the S-locus. Analysis of SFB1 and SFB2 protein sequences allowed identifying the absence of some variable and hypervariable domains and the presence of additional α-helices at the C-termini. Molecular and evolutionary analysis of SFB nucleotide sequences showed a signature of purifying selection in SFB2, while the SFB1 seemed to evolve neutrally. Thus, our results show that the SFB2 allele diversified after P. persica and P. dulcis (almond) divergence, a period which is characterized by an important bottleneck, while SFB1 diversified at a transition time between the bottleneck and population expansion., This research was supported by the Tunisian “Ministère de l’Enseignement Supérieur et de la Recherche Scientifique” and “Ministerio de Economía y Competitividad—European Regional Development Fund, European Union (AGL2016-77267-R and PID2019-109566RB-I00).