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In transcriptional regulatory networks (TRNs), a canonical 3-node feed-forward loop (FFL) is hypothesized to evolve to filter out short spurious signals. We test this adaptive hypothesis against a novel null evolutionary model. Our mutational model captures the intrinsically high prevalence of weak affinity transcription factor binding sites. We also capture stochasticity and delays in gene expression that distort external signals and intrinsically generate noise. Functional FFLs evolve readily under selection for the hypothesized function but not in negative controls. Interestingly, a 4-node “diamond” motif also emerges as a short spurious signal filter. The diamond uses expression dynamics rather than path length to provide fast and slow pathways. When there is no idealized external spurious signal to filter out, but only internally generated noise, only the diamond and not the FFL evolves. While our results support the adaptive hypothesis, we also show that non-adaptive factors, including the intrinsic expression dynamics, matter., Feed‐forward loops (FFLs) can filter out noise, but whether their overrepresentation in GRNs reflects adaptive evolution for this function is debated. Here, the authors develop a null model of regulatory evolution and find that FFLs evolve readily under selection for the noise filtering function.

The development of effective antifungal therapeutics remains a formidable challenge because of the close evolutionary relationship between humans and fungi. Mitochondrial function may present an exploitable vulnerability because of its differential utilization in fungi and its pivotal roles in fungal morphogenesis, virulence, and drug resistance already demonstrated by others. We now report mechanistic characterization of ML316, a thiohydantoin that kills drug-resistant Candida species at nanomolar concentrations through fungal-selective inhibition of the mitochondrial phosphate carrier Mir1. Using genetic, biochemical, and metabolomic approaches, we established ML316 as the first Mir1 inhibitor. Inhibition of Mir1 by ML316 in respiring yeast diminished mitochondrial oxygen consumption, resulting in an unusual metabolic catastrophe marked by citrate accumulation and death. In a mouse model of azole-resistant oropharyngeal candidiasis, ML316 reduced fungal burden and enhanced azole activity. Targeting Mir1 could provide a new, much-needed therapeutic strategy to address the rapidly rising burden of drug-resistant fungal infection.

Summary To cause disease, a microbial pathogen must adapt to the challenges of its host environment. The leading fungal pathogen Candida albicans colonizes nutrient-poor bodily niches, withstands attack from the immune system, and tolerates treatment with azole antifungals, often evolving resistance. To discover agents that block these adaptive strategies, we screened 300,000 compounds for inhibition of azole tolerance in a drug-resistant Candida isolate. We identified a novel indazole derivative that converts azoles from fungistatic to fungicidal drugs by selective inhibition of mitochondrial cytochrome bc 1 . We synthesized 103 analogs to optimize potency (half maximal inhibitory concentration 0.4 μM) and fungal selectivity (28-fold over human). In addition to reducing azole resistance, targeting cytochrome bc 1 prevents C. albicans from adapting to the nutrient-deprived macrophage phagosome and greatly curtails its virulence in mice. Inhibiting mitochondrial respiration and restricting metabolic flexibility with this synthetically tractable chemotype provides an attractive therapeutic strategy to limit both fungal virulence and drug resistance.

The institutions of science are in a state of flux. Declining public funding for basic science, the increasingly corporatized administration of universities, increasing “adjunctification” of the professoriate and poor academic career prospects for postdoctoral scientists indicate a significant mismatch between the reality of the market economy and expectations in higher education for science. Solutions to these issues typically revolve around the idea of fixing the career "pipeline", which is envisioned as being a pathway from higher-education training to a coveted permanent position, and then up a career ladder until retirement. In this paper, we propose and describe the term “ecosystem” as a more appropriate way to conceptualize today’s scientific training and the professional landscape of the scientific enterprise. First, we highlight the issues around the concept of “fixing the pipeline”. Then, we articulate our ecosystem metaphor by describing a series of concrete design patterns that draw on peer-to-peer, decentralized, cooperative, and commons-based approaches for creating a new dynamic scientific enterprise.

The institutions of science are in a state of flux. Declining public funding for basic science, the increasingly corporatized administration of universities, increasing “adjunctification” of the professoriate and poor academic career prospects for postdoctoral scientists indicate a significant mismatch between the reality of the market economy and expectations in higher education for science. Solutions to these issues typically revolve around the idea of fixing the career "pipeline", envisioned being a pathway from higher-education training to a coveted permanent position, and then up a career ladder until retirement. In this paper, we propose and describe the term “ecosystem” as an appropriate way to conceptualize today’s scientific training and the professional landscape of the scientific enterprise. First, we highlight the issues around the concept of “fixing the pipeline”. Then, we articulate our ecosystem metaphor by describing a series of concrete design patterns that draw on peer-to-peer, decentralized, co-operative, and commons-based approaches to creating a new dynamic scientific enterprise.

Modern-day bioscientific research is now at an economic crossroads. Specifically, the past 30 years have brought extraordinary advancements in biomedical knowledge, initiating the era of “personalized medicine”, therapies tailored specifically to individual patients’ genomic, epigenomic, and transcriptomic profiles, discovery of drugs based on computational analyses of massive datasets, and systems pharmacology (optimizing dosing and detection of adverse drug events). These have resulted in an exponential increase in our understanding of biological processes at the molecular, cellular, and organismal levels. Overall U.S. life expectancy (at birth) has risen from 74.7 years in 1985 to 78.7 years in 2010. Concurrently, the U.S. infant mortality rate declined by 42%, while mortality from heart disease and cancer decreased by 53% and 20%, respectively. Despite these monumental advances, the traditional manner in which

From Yeast to Therapeutic? Yeast has shown some promise as a model system to generate lead compounds that could have therapeutic potential for the cellular problems associated with neurodegenerative diseases. Along these lines, Tardiff et al. (p. 979 , published online 24 October) and Chung et al. (p. 983 , published online 24 October) describe the results of multiple screens in yeast that lead to the identification of a potential therapeutic compound to combat the cytotoxic affect of α-synuclein accumulation. The compound was able to reverse the pathological hallmarks of Parkinson's disease in cultured neurons derived from patients with α-synuclein–induced Parkinson's disease dementia.

SummaryPrion proteins undergo self-sustaining conformational conversions that heritably alter their activities. Many of these proteins operate at pivotal positions in determining how genotype is translated into phenotype. But the breadth of prion influences on biology and their evolutionary significance are just beginning to be explored. We report that a prion formed by the Mot3 transcription factor, [MOT3+], governs the acquisition of facultative multicellularity in the budding yeast Saccharomyces cerevisiae. The traits governed by [MOT3+] involved both gains and losses of Mot3 regulatory activity. [MOT3+]-dependent expression of FLO11, a major determinant of cell-cell adhesion, produced diverse lineage-specific multicellular phenotypes in response to nutrient deprivation. The prions themselves were induced by ethanol and eliminated by hypoxia—conditions that occur sequentially in the natural respiro-fermentative cycles of yeast populations. These data demonstrate that prions can act as environmentally responsive molecular determinants of multicellularity and contribute to the natural morphological diversity of budding yeast.PaperFlick

To cause disease, a microbial pathogen must adapt to the challenges of its host environment. The leading fungal pathogen Candida albicans colonizes nutrient-poor bodily niches, withstands attack from the immune system, and tolerates treatment with azole antifungals, often evolving resistance. To discover agents that block these adaptive strategies, we screened 300,000 compounds for inhibition of azole tolerance in a drug-resistant Candida isolate. We identified a novel indazole derivative that converts azoles from fungistatic to fungicidal drugs by selective inhibition of mitochondrial cytochrome bc1. We synthesized 103 analogs to optimize potency (0.4 μM IC50) and fungal selectivity (28-fold over human). In addition to reducing azole resistance, targeting cytochrome bc1 prevents C. albicans from adapting to the nutrient-deprived macrophage phagosome and greatly curtails its virulence in mice. Inhibiting mitochondrial respiration and restricting metabolic flexibility with this synthetically tractable chemotype provides an attractive therapeutic strategy to limit both fungal virulence and drug resistance.

The self-templating conformations of yeast prion proteins act as epigenetic elements of inheritance. Yeast prions might provide a mechanism for generating heritable phenotypic diversity that promotes survival in fluctuating environments and the evolution of new traits. However, this hypothesis is highly controversial. Prions that create new traits have not been found in wild strains, leading to the perception that they are rare 'diseases' of laboratory cultivation. Here we biochemically test approximately 700 wild strains of Saccharomyces for [PSI(+)] or [MOT3(+)], and find these prions in many. They conferred diverse phenotypes that were frequently beneficial under selective conditions. Simple meiotic re-assortment of the variation harboured within a strain readily fixed one such trait, making it robust and prion-independent. Finally, we genetically screened for unknown prion elements. Fully one-third of wild strains harboured them. These, too, created diverse, often beneficial phenotypes. Thus, prions broadly govern heritable traits in nature, in a manner that could profoundly expand adaptive opportunities.

Summary: Efficient workflows to shepherd clinically generated genomic data through the multiple stages of a next-generation sequencing pipeline are of critical importance in translational biomedical science. Here we present COSMOS, a Python library for workflow management that allows formal description of pipelines and partitioning of jobs. In addition, it includes a user interface for tracking the progress of jobs, abstraction of the queuing system and fine-grained control over the workflow. Workflows can be created on traditional computing clusters as well as cloud-based services. Availability and implementation: Source code is available for academic non-commercial research purposes. Links to code and documentation are provided at http://lpm.hms.harvard.edu and http://wall-lab.stanford.edu . Contact: dpwall@stanford.edu or peter_tonellato@hms.harvard.edu . Supplementary information : Supplementary data are available at Bioinformatics online.

Sequence-based typing was used to identify human leukocyte antigen (HLA)-A, -B, -C, and -DRB1 alleles from 558 consecutively recruited US volunteers with Eastern European ancestry for an unrelated hematopoietic stem cell registry. Four of 31 HLA-A alleles, 29 HLA-C alleles, 59 HLA-B alleles, and 42 HLA-DRB1 alleles identified (A*0325, B*440204, Cw*0332, and *0732N) are novel. The HLA-A*02010101g allele was observed at a frequency of 0.28. Two-, three-, and four-locus haplotypes were estimated using the expectation-maximization algorithm. The highest frequency extended haplotypes (A*010101g-Cw*070101g-B*0801g-DRB1*0301 and A*03010101g-Cw*0702-B*0702-DRB1*1501) were observed at frequencies of 0.04 and 0.03, respectively. Linkage disequilibrium values (Dij') of the constituent two-locus haplotypes were highly significant for both extended haplotypes (P values were less than 8 x 10(-10)) but were consistently higher for the more frequent haplotype. Balancing selection was inferred to be acting on all the four loci, with the strongest evidence of balancing selection observed for the HLA-C locus. Comparisons of the A-C-B haplotypes and DRB1 frequencies in this population with those for African, European, and western Asian populations showed high degrees of identity with Czech, Polish, and Slovenian populations and significant differences from the general European American population.

This paper presents a meta-analysis of high-resolution human leukocyte antigen (HLA) allele frequency data describing 497 population samples. Most of the datasets were compiled from studies published in eight journals from 1990 to 2007; additional datasets came from the International Histocompatibility Workshops and from the AlleleFrequencies.net database. In all, these data represent approximately 66,800 individuals from throughout the world, providing an opportunity to observe trends that may not have been evident at the time the data were originally analyzed, especially with regard to the relative importance of balancing selection among the HLA loci. Population genetic measures of allele frequency distributions were summarized across populations by locus and geographic region. A role for balancing selection maintaining much of HLA variation was confirmed. Further, the breadth of this meta-analysis allowed the ranking of the HLA loci, with DQA1 and HLA-C showing the strongest balancing selection and DPB1 being compatible with neutrality. Comparisons of the allelic spectra reported by studies since 1990 indicate that most of the HLA alleles identified since 2000 are very-low-frequency alleles. The literature-based allele-count data, as well as maps summarizing the geographic distributions for each allele, are available online.

Population genetic statistics from multilocus genotype data inform our understanding of the patterns of genetic variation and their implications for evolutionary studies, generally, and human disease studies in particular. In any given population one can estimate haplotype frequencies, identify deviation from Hardy-Weinberg equilibrium, test for balancing or directional selection, and investigate patterns of linkage disequilibrium. Existing software packages are oriented primarily toward the computation of such statistics on a population-by-population basis, not on comparisons among populations and across different statistics. We developed PyPop (Python for Population Genomics) to facilitate the analyses of population genetic statistics across populations and the relationships among different statistics within and across populations. PyPop is an an open-source framework for performing large-scale population genetic analyses on multilocus genotype data. It computes the statistics described above, among others. PyPop deploys a standard Extensible Markup Language (XML) output format and can integrate the results of multiple analyses on various populations that were performed at different times into a common output format that can be read into a spreadsheet. The XML output format allows PyPop to be embedded as part of a larger analysis pipeline. Originally developed to analyze the highly polymorphic genetic data of the human leukocyte antigen region of the human genome, PyPop has applicability to any kind of multilocus genetic data. It is the primary analysis platform for analyzing data collected for the Anthropological component of the 13th and 14th International Histocompatibility Workshops. PyPop has also been successfully used in studies by our group, with collaborators, and in publications by several independent research teams.

Sequence-based typing was used to identify human leukocyte antigen (HLA)-A, -B, -C, and -DRB1 alleles from 564 consecutively recruited African American volunteers for an unrelated hematopoietic stem cell registry. The number of known alleles identified at each locus was 42 for HLA-A, HLA-B 67, HLA-C 33, and HLA-DRB1 44. Six novel alleles (A*260104, A*7411, Cw*0813, Cw*1608, Cw*1704, and DRB1*130502) not observed in the initial sequence-specific oligonucleotide probe testing were characterized. The action of balancing selection, shaping more 'even' than expected allele frequency distributions, was inferred for all four loci and significantly so for the HLA-A and DRB1 loci. Two-, three-, and four-locus haplotypes were estimated using the expectation maximization algorithm. Comparisons with other populations from Africa and Europe suggest that the degree of European admixture in the African American population described here is lower than that in other African American populations previously reported, although HLA-A:B haplotype frequencies similar to those in previous studies of African American individuals were also noted.

Polymerase chain reaction-sequence-specific oligonucleotide probes typing methods have been applied to 1000 individuals from the Northern Ireland population to give human leukocyte antigen DRB1 (HLA-DRB1) allele assignment. HLA-DRB1 allele frequencies and four-locus haplotypes (A/B/C/DR) for this Caucasian population, based on HLA class I and class II allele assignment, are now presented. No significant deviations from Hardy-Weinberg proportions were observed. The HLA-C locus exhibited marginal evidence of selection (p0.03, uncorrected one-sided test) in the direction of balancing selection; the HLA-A, -B, and -DRB1 allele frequency distributions were compatible with expectations under a neutral model (which does not mean that selection is not operating). Evidence for selection was seen on haplotypes HLA-A*010101-B*0801-DRB1*030101 and HLA-A*290201-B*440301-DRB1*070101 based on their patterns of linkage disequilibrium.

In experimental science, organisms are usually studied in isolation, but in the wild they compete and cooperate in complex communities. We report a system for cross-kingdom communication by which bacteria heritably transform yeast metabolism. An ancient biological circuit blocks yeast from using other carbon sources in the presence of glucose. [GAR[superscript +]], a protein-based epigenetic element, allows yeast to circumvent this glucose repression and use multiple carbon sources in the presence of glucose. Some bacteria secrete a chemical factor that induces [GAR[superscript +]]. [GAR[superscript +]] is advantageous to bacteria because yeast cells make less ethanol, and is advantageous to yeast because their growth and long-term viability is improved in complex carbon sources. This crosskingdom communication is broadly conserved, providing a compelling argument for its adaptive value. By heritably transforming growth and survival strategies in response to the selective pressures of life in a biological community, [GAR[superscript +]] presents a unique example of Lamarckian inheritance., G. Harold and Leila Y. Mathers Foundation, Howard Hughes Medical Institute

The Biostatistics Component of the 13th International Histocompatibility Workshop (IHWS) developed the PyPop (Python for Population Genomics) software framework for high-throughput analysis and quality control (QC) assessments of highly polymorphic genotype data. Since its initial release, the software has had several new analysis modules added to it. These additions, combined with improved data filtering and QC modules, facilitate analyses of data at different levels (allele, haplotype, amino acid sequence, and nucleotide sequence). Since the 13th IHWS, much of the human leukocyte antigen (HLA) data from the workshop, QCed via PyPop and other methods, have been made publicly available through the Major Histocompatibility Complex database web site at the National Center for Biotechnology Information (http://ncbi.nih.gov/mhc/). The Anthropology/Human Genetic Diversity component (AHGDC) data have been used in a variety of studies. Prugnolle et al. used this data to corroborate a model of pathogen-driven selection as a factor related to high levels of diversity at HLA loci. Using a comparative genomics approach contrasting results for HLA and non-HLA markers, Meyer et al. analyzed a subset of the 13th IHWS AHGDC data and showed that HLA loci show detectable signs of both natural selection and the demographic history of populations.

The evolution of drug resistance in microbial pathogens provides a paradigm for investigating evolutionary dynamics with important consequences for human health. Candida albicans, the leading fungal pathogen of humans, rapidly evolves resistance to two major antifungal classes, the triazoles and echinocandins. In contrast, resistance to the third major antifungal used in the clinic, amphotericin B (AmB), remains extremely rare despite 50 years of use as monotherapy. We sought to understand this long-standing evolutionary puzzle. We used whole genome sequencing of rare AmB-resistant clinical isolates as well as laboratory-evolved strains to identify and investigate mutations that confer AmB resistance in vitro. Resistance to AmB came at a great cost. Mutations that conferred resistance simultaneously created diverse stresses that required high levels of the molecular chaperone Hsp90 for survival, even in the absence of AmB. This requirement stemmed from severe internal stresses caused by the mutations, which drastically diminished tolerance to external stresses from the host. AmB-resistant mutants were hypersensitive to oxidative stress, febrile temperatures, and killing by neutrophils and also had defects in filamentation and tissue invasion. These strains were avirulent in a mouse infection model. Thus, the costs of evolving resistance to AmB limit the emergence of this phenotype in the clinic. Our work provides a vivid example of the ways in which conflicting selective pressures shape evolutionary trajectories and illustrates another mechanism by which the Hsp90 buffer potentiates the emergence of new phenotypes. Developing antibiotics that deliberately create such evolutionary constraints might offer a strategy for limiting the rapid emergence of drug resistance., National Science Foundation (U.S.). Graduate Research Fellowship Program, Howard Hughes Medical Institute, G. Harold and Leila Y. Mathers Foundation

[GAR[superscript +]] is a protein-based element of inheritance that allows yeast (Saccharomyces cerevisiae) to circumvent a normal hallmark of their biology: extreme metabolic specialization for glucose fermentation. When glucose is present, even in trace quantities, yeast will not use other carbon sources. [GAR[superscript +]] allows cells to circumvent this “glucose repression.” [GAR[superscript +]] is induced in yeast by a factor secreted by bacteria inhabiting their environment. We report that the de novo rates of [GAR[superscript +]] appearance correlate with the yeast’s ecological niche. Evolutionarily distant fungi possess similar epigenetic elements that are also induced by bacteria. As expected for a mechanism whose adaptive value originates from the selective pressures of life in biological communities, the ability of bacteria to induce [GAR[superscript +]] and the ability of yeast to respond to bacterial signals have been extinguished repeatedly during the extended monoculture of domestication. Thus, [GAR[superscript +]] is a broadly conserved adaptive strategy that links environmental and social cues to heritable changes in metabolism., G. Harold and Leila Y. Mathers Foundation, Howard Hughes Medical Institute

In fungi, the anchoring of proteins to the plasma membrane via their covalent attachment to glycosylphosphatidylinositol (GPI) is essential and thus provides a valuable point of attack for the development of antifungal therapeutics. Unfortunately, studying the underlying biology of GPI-anchor synthesis is difficult, especially in medically relevant fungal pathogens because they are not genetically tractable. Compounding difficulties, many of the genes in this pathway are essential in Saccharomyces cerevisiae. Here, we report the discovery of a new small molecule christened gepinacin (for GPI acylation inhibitor) which selectively inhibits Gwt1, a critical acyltransferase required for the biosynthesis of fungal GPI anchors. After delineating the target specificity of gepinacin using genetic and biochemical techniques, we used it to probe key, therapeutically relevant consequences of disrupting GPI anchor metabolism in fungi. We found that, unlike all three major classes of antifungals in current use, the direct antimicrobial activity of this compound results predominantly from its ability to induce overwhelming stress to the endoplasmic reticulum. Gepinacin did not affect the viability of mammalian cells nor did it inhibit their orthologous acyltransferase. This enabled its use in co-culture experiments to examine Gwt1's effects on host-pathogen interactions. In isolates of Candida albicans, the most common fungal pathogen in humans, exposure to gepinacin at sublethal concentrations impaired filamentation and unmasked cell wall β-glucan to stimulate a pro-inflammatory cytokine response in macrophages. Gwt1 is a promising antifungal drug target, and gepanacin is a useful probe for studying how disrupting GPI-anchor synthesis impairs viability and alters host-pathogen interactions in genetically intractable fungi.

Summary: Prions are self-templating protein aggregates that stably perpetuate distinct biological states and are of keen interest to researchers in both evolutionary and biomedical science. The best understood prions are from yeast and have a prion-forming domain with strongly biased amino acid composition, most notably enriched for Q or N. PLAAC is a web application that scans protein sequences for domains with prion-like amino acid composition. Users can upload sequence files, or paste sequences directly into a textbox. PLAAC ranks the input sequences by several summary scores and allows scores along sequences to be visualized. Text output files can be downloaded for further analyses, and visualizations saved in PDF and PNG formats. Availability and implementation: http://plaac.wi.mit.edu/. The Ruby-based web framework and the command-line software (implemented in Java, with visualization routines in R) are available at http://github.com/whitehead/plaac under the MIT license. All software can be run under OS X, Windows and Unix. Contact: oliver.king@umassmed.edu or lindquist_admin@wi.mit.edu

PyPop (Python for Population Genomics) is an open-source framework for performing large-scale population genetic analyses on multilocus genotype and allele frequency data. It computes tests and measures of Hardy-Weinberg equilibrium (locus-level and individual genotype-level), linkage disequilibrum, and selection, and estimates multi-locus haplotypes. PyPop supplements and extends existing population genetic software incorporating them as modules, modified to accommodate highly polymorphic data, rather than reimplementing them from scratch. It facilitates evolutionary analyses by integrating population genetic statistics within and across populations. Originally developed to analyze the highly polymorphic genetic data of the human leukocyte antigen region of the human genome, PyPop has applicability to any kind of multilocus genetic data. It was the primary platform for evolutionary analysis of data collected for a major NIH-funded collaborative grant that included over 30 laboratories and 200 populations (Lancaster et al., 2007a,b). PyPop has also been successfully used in studies by our group, with collaborators, and in publications by many independent research teams in over 70 peer reviewed papers. PyPop deploys a standard Extensible Markup Language (XML) output format and integrates the results of multiple analyses on various populations that were performed at different times into a common output format that can be read into a spreadsheet. The XML output format allows PyPop to be embedded as part of larger analysis pipelines. It also features an Application Programming Interface (API) allowing functionality to be incorporated into other programs. This lightning talk will focus on recent features of PyPop which include the prefiltering of the input genotype data and the ability to translate arbitrary allele names into full amino acid or nucleotide sequences. All code is made available under the terms of the GNU General Public License (GNU GPL): Homepage: http://www.pypop.org/ References: Lancaster, A. K., M. P. Nelson, R. M. Single, D. Meyer, and G. Thomson, 2007a Software framework for the Biostatistics Core of the International Histocompatibility Working Group. In J. A. Hansen, editor, Immunobiology of the Human MHC: Proceedings of the 13th International Histocompatibility Workshop and Conference, volume I. Seattle, WA: IHWG Press, 510-517. Lancaster, A. K., R. M. Single, O. D. Solberg, M. P. Nelson, and G. Thomson, 2007b PyPop update–a software pipeline for large-scale multilocus population genomics. Tissue Antigens 69 Suppl 1:192-7.

Epigenetically inherited aggregates of the yeast prion [PSI+] cause genomewide readthrough translation that sometimes increases evolvability in certain harsh environments. The effects of natural selection on modifiers of [PSI+] appearance have been the subject of much debate. It seems likely that [PSI+] would be at least mildly deleterious in most environments, but this may be counteracted by its evolvability properties on rare occasions. Indirect selection on modifiers of [PSI+] is predicted to depend primarily on the spontaneous [PSI+] appearance rate, but this critical parameter has not previously been adequately measured. Here we measure this epimutation rate accurately and precisely as 5.8 × 10−7 per generation, using a fluctuation test. We also determine that genetic “mimics” of [PSI+] account for up to 80% of all phenotypes involving general nonsense suppression. Using previously developed mathematical models, we can now infer that even in the absence of opportunities for adaptation, modifiers of [PSI+] are only weakly deleterious relative to genetic drift. If we assume that the spontaneous [PSI+] appearance rate is at its evolutionary optimum, then opportunities for adaptation are inferred to be rare, such that the [PSI+] system is favored only very weakly overall. But when we account for the observed increase in the [PSI+] appearance rate in response to stress, we infer much higher overall selection in favor of [PSI+] modifiers, suggesting that [PSI+]-forming ability may be a consequence of selection for evolvability.

Reversible phenotypic switching can be caused by a number of different mechanisms including epigenetic inheritance systems and DNA-based contingency loci. Previous work has shown that reversible switching systems may be favored by natural selection. Many switches can be characterized as "on/off" where the "off" state constitutes a temporary and reversible loss of function. Loss-of-function phenotypes corresponding to the "off" state can be produced in many different ways, all yielding identical fitness in the short term. In the long term, however, a switch-induced loss of function can be reversed, whereas many loss-of-function mutations, especially deletions, cannot. We refer to these loss-of-function mutations as "irreversible mimics" of the reversible switch. Here, we develop a model in which a reversible switch evolves in the presence of both irreversible mimics and metapopulation structure. We calculate that when the rate of appearance of irreversible mimics exceeds the migration rate, the evolved reversible switching rate will exceed the bet-hedging rate predicted by panmictic models.

During 2005, a total of 174 cord blood units with their paired maternal samples from the Singapore Cord Blood Bank were typed for HLA-A, -B, -C at intermediate resolution and DRB1 at allelic resolution. Analysis of allele segregation in mother and child assigned 185 different four locus (HLA-A, -B, -C, -DRB1) haplotypes in Chinese, 66 in Malays, and 34 in Asian Indians. Very few four locus haplotypes were shared among population groups. To evaluate the frequencies of four locus haplotypes, the Expectation Maximization algorithm was used with HLA assignments from 536 unrelated Chinese volunteers from the Singapore Bone Marrow Donor Program registry. The paired maternal and cord blood study identified 75 different B-C associations in Chinese, 52 in Malays, and 24 in Asian Indians. Common B-C associations may be shared among population groups; for example, B*4001g-Cw*0702g was common in Chinese and Malays, whereas B*1502g-Cw*0801g and B*3501g-Cw*0401g were found in all three groups. The high diversity of four locus haplotypes originates from multiple combinations of both HLA-A and -DRB1 alleles with each B-C haplotype.

The allelic and haplotypic diversity of the HLA-A, HLA-B, and HLA-C loci was investigated in 852 subjects from five sub-Saharan populations from Kenya (Nandi and Luo), Mali (Dogon), Uganda, and Zambia. Distributions of genotypes at all loci and in all populations fit Hardy-Weinberg equilibrium expectations. There was not a single allele predominant at any of the loci in these populations, with the exception of A*3002 [allele frequency (AF) = 0.233] in Zambians and Cw*1601 (AF = 0.283) in Malians. This distribution was consistent with balancing selection for all class I loci in all populations, which was evidenced by the homozygosity F statistic that was less than that expected under neutrality. Only in the A locus in Zambians and the C locus in Malians, the AF distribution was very close to neutrality expectations. There were six instances in which there were significant deviations of allele distributions from neutrality in the direction of balancing selection. All allelic lineages from each of the class I loci were found in all the African populations. Several alleles of these loci have intermediate frequencies (AF = 0.020-0.150) and seem to appear only in the African populations. Most of these alleles are widely distributed in the African continent and their origin may predate the separation of linguistic groups. In contrast to native American and other populations, the African populations do not seem to show extensive allelic diversification within lineages, with the exception of the groups of alleles A*02, A*30, B*57, and B*58. The alleles of human leukocyte antigen (HLA)-B are in strong linkage disequilibrium (LD) with alleles of the C locus, and the sets of B/C haplotypes are found in several populations. The associations between A alleles with C-blocks are weaker, and only a few A/B/C haplotypes (A*0201-B*4501-Cw*1601; A*2301-B*1503-Cw*0202; A*7401-B* 1503-Cw*0202; A*2902-B*4201-Cw*1701; A*3001-B*4201-Cw*1701; and A*3601-B*5301-Cw*0401) are found in multiple populations with intermediate frequencies [haplotype frequency (HF) = 0.010-0.100]. The strength of the LD associations between alleles of HLA-A and HLA-B loci and those of HLA-B and HLA-C loci was on average of the same or higher magnitude as those observed in other non-African populations for the same pairs of loci. Comparison of the genetic distances measured by the distribution of alleles at the HLA class I loci in the sub-Saharan populations included in this and other studies indicate that the Luo population from western Kenya has the closest distance with virtually all sub-Saharan population so far studied for HLA-A, a finding consistent with the putative origin of modern humans in East Africa. In all African populations, the genetic distances between each other are greater than those observed between European populations. The remarkable current allelic and haplotypic diversity in the HLA system as well as their variable distribution in different sub-Saharan populations is probably the result of evolutionary forces and environments that have acted on each individual population or in their ancestors. In this regard, the genetic diversity of the HLA system in African populations poses practical challenges for the design of T-cell vaccines and for the transplantation medical community to find HLA-matched unrelated donors for patients in need of an allogeneic transplant.

Software to analyze multi-locus genotype data for entire populations is useful for estimating haplotype frequencies, deviation from Hardy-Weinberg equilibrium and patterns of linkage disequilibrium. These statistical results are important to both those interested in human genome variation and disease predisposition as well as evolutionary genetics. As part of the 13th International Histocompatibility and Immunogenetics Working Group (IHWG), we have developed a software framework (PyPop). The primary novelty of this package is that it allows integration of statistics across large numbers of data-sets by heavily utilizing the XML file format and the R statistical package to view graphical output, while retaining the ability to inter-operate with existing software. Largely developed to address human population data, it can, however, be used for population based data for any organism. We tested our software on the data from the 13th IHWG which involved data sets from at least 50 laboratories each of up to 1000 individuals with 9 MHC loci (both class I and class II) and found that it scales to large numbers of data sets well.

Background While next-generation sequencing (NGS) costs have plummeted in recent years, cost and complexity of computation remain substantial barriers to the use of NGS in routine clinical care. The clinical potential of NGS will not be realized until robust and routine whole genome sequencing data can be accurately rendered to medically actionable reports within a time window of hours and at scales of economy in the 10’s of dollars. Results We take a step towards addressing this challenge, by using COSMOS, a cloud-enabled workflow management system, to develop GenomeKey, an NGS whole genome analysis workflow. COSMOS implements complex workflows making optimal use of high-performance compute clusters. Here we show that the Amazon Web Service (AWS) implementation of GenomeKey via COSMOS provides a fast, scalable, and cost-effective analysis of both public benchmarking and large-scale heterogeneous clinical NGS datasets. Conclusions Our systematic benchmarking reveals important new insights and considerations to produce clinical turn-around of whole genome analysis optimization and workflow management including strategic batching of individual genomes and efficient cluster resource configuration. Electronic supplementary material The online version of this article (doi:10.1186/s12920-015-0134-9) contains supplementary material, which is available to authorized users.

Background The dramatic fall of next generation sequencing (NGS) cost in recent years positions the price in range of typical medical testing, and thus whole genome analysis (WGA) may be a viable clinical diagnostic tool. Modern sequencing platforms routinely generate petabyte data. The current challenge lies in calling and analyzing this large-scale data, which has become the new time and cost rate-limiting step.

Background Spiders (Order Araneae) are essential predators in every terrestrial ecosystem largely because they have evolved potent arsenals of silk and venom. Spider silks are high performance materials made almost entirely of proteins, and thus represent an ideal system for investigating genome level evolution of novel protein functions. However, genomic level resources remain limited for spiders. Results We de novo assembled a transcriptome for the Western black widow (Latrodectus hesperus) from deeply sequenced cDNAs of three tissue types. Our multi-tissue assembly contained ~100,000 unique transcripts, of which > 27,000 were annotated by homology. Comparing transcript abundance among the different tissues, we identified 647 silk gland-specific transcripts, including the few known silk fiber components (e.g. six spider fibroins, spidroins). Silk gland specific transcripts are enriched compared to the entire transcriptome in several functions, including protein degradation, inhibition of protein degradation, and oxidation-reduction. Phylogenetic analyses of 37 gene families containing silk gland specific transcripts demonstrated novel gene expansions within silk glands, and multiple co-options of silk specific expression from paralogs expressed in other tissues. Conclusions We propose a transcriptional program for the silk glands that involves regulating gland specific synthesis of silk fiber and glue components followed by protecting and processing these components into functional fibers and glues. Our black widow silk gland gene repertoire provides extensive expansion of resources for biomimetic applications of silk in industry and medicine. Furthermore, our multi-tissue transcriptome facilitates evolutionary analysis of arachnid genomes and adaptive protein systems. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-365) contains supplementary material, which is available to authorized users.