TAR1  is a young gene, located antisense to the 25S rRNA gene in Saccharomyces cerevisiaeTAR1 the most abundant protein-coding gene in yeast. Oddly, TAR1 is normally silenced by Sir2p, a repressor of RNA polymerase II (pol-II)-transcribed genes TAR1 function is lacking however, as available observations derive from monitoring a single, modified TAR1 copy TAR1.TAR1 ameliorates the behaviour of selfish yeast mitochondrial mutants first identified over fifty years ago. The location of TAR1 in the ribosomal DNA (rDNA) repeat array is crucial to our model, as this means it is also present on extra-chromosomal ribosomal circles (ERCs). ERCs are rDNA repeats that have ‘popped out’ of the chromosome by intra-chromatid recombination, and exist in the cell as plasmid-like circular DNA  activate the retrograde response. Therefore, increases in TAR1 expression and copy number occur at precisely the times when a suppressor of mitochondrial conflict would be expected to act.Our proposal derives from findings that TAR1 suppresses the transmission advantage of hypersuppressive mitochondria.The retrograde response may thus have two regulatory roles: coordinating gene expression following mitochondrial damage, and suppression of the transmission advantage enjoyed by hypersuppressive mitochondria. This annuls the paradox of why the retrograde response produces both life-extending and life-shortening effects: these are separate genetic outcomes of different arms of the retrograde response. We now consider how these observations fit a model wherein TAR1 modifies drive, what is its mode of action? The propensity for hypersuppressives to drive may stem from a mtDNA replicative advantage. Hypersuppressive mtDNA carries many origins of replication (ori), which may lead to monopoly of the replication apparatus when hypersuppressives are crossed with strains harbouring wild-type mitochondria oris‘Drive’ in the yeast mitochondrial system means the ability of one mitochondrial type to be preferentially transmitted or to subsequently overrun daughter cells if two mitochondrial types are present. If ori sequences. Consequently, any nuclear-encoded modifier ought to operate in a dose-dependent manner to counteract mtDNA overreplication. TAR1 is a strong candidate for such a modifier for three reasons. First, rDNA copy number varies within yeast populations TAR1 copy number increase. Third, pol-II dependent TAR1 transcription is normally silenced by Sir2p; this silencing is reduced in petites TAR1 upregulation via the retrograde response: TAR1 copy number increases through ERC formation, and pol-II-dependent transcription increases, perhaps specifically on ERCs Hypersuppressive mtDNA genomes are shorter than wild-type and carry higher numbers of TAR1 copy number/expression and ori sequence copy number in hypersuppressive mitochondria. Whether hypersuppressive petite mtDNA transmission is suppressed depends upon the relative dosage of Tar1p and ori sequences. Similar phenomena have been seen in other cases of drive Our model predicts a dynamic competition between nuclear TAR1 does suppress drive, it presumably acts to reduce the replicative advantage of hypersuppressive mitochondria or prevent transmission to buds . ERC production would already have been a byproduct of rDNA array copy number maintenance, and the rDNA locus would have already been subject to Sir2p-dependent pol-II transcription silencing. We envisage that the TAR1 open reading frame emerged by chance (other overprinted genes are known at the rDNA locus TAR1 is present in Kluyveromyces lactisTAR1 evolved in an ancestral petite-forming lineage.Multicopy rDNA arrays provide a broad target for the emergence of mutants TAR1 reduces the transmission advantage of hypersuppressive mtDNA, potentially explains the connection between the retrograde response and ERC production/rDNA pol-II transcription. If true, we predict that a TAR1 knockout will not exhibit a detrimental phenotype, other than any that may arise as a side effect of deleting an overprinted gene.Our model, in which we propose that TAR1 is a drive suppressor, its effects should be observed postzygotically. We predict that increases in TAR1 copy number and/or expression level would suppress the transmission advantage observed for hypersuppressives crossed with wild-type, provided Tar1p levels are sufficient to counteract the increased ori sequence copy number in hypersuppressive mitochondria. Consequently, petite hypersuppressivity should drop in crosses where TAR1 is overexpressed. In a tar1Δ knockout, we predict that suppressive petite strains will become hypersuppressive. Furthermore, sir2Δ mutants should resemble a TAR1 overexpression strain, exhibiting greater resistance to drive by hypersuppressives. This should also be observed in an rtg2Δ knockout, which eliminates transduction of mitochondrial dysfunction but also removes suppression of ERC function If ori sequences and rDNA operons. Spontaneous emergence of hypersuppressive petites may be more frequent in younger yeast, since ERC accumulation is a facet of ageing, and ERCs are not passed to daughters TAR1 expression is, and whether older and younger cells differ in their resistance to hypersuppressivity.Natural variations in rDNA copy number should also affect strain susceptibility to drive; whether drive occurs will be dependent on the relative copy numbers of mtDNA TAR1 dampens intragenomic conflict resulting from biparental transmission of mitochondria. TAR1 may also serve to reduce proliferation of petite mitochondria during vegetative growth, where a single mutant mtDNA spreads to fixation within a cell or cell lineage.Our model resolves the paradoxical role of the retrograde response in lifespan. If correct, derepressing ERC formation is integral to the retrograde response as it enables Tar1p production. We propose that Tar1p eliminates the transmission advantage of hypersuppressive petite mitochondria, and reduces fixation of petite genotypes within cell lineages. According to this model, T. H. Huxley proclaimed the great tragedy of science to be ‘the slaying of a beautiful hypothesis by an ugly fact’


The prevalence of perceptions of odors and sensations of air humidity and sick building syndrome symptoms in domestic environments were studied using responses to a questionnaire on the home environment. Parents of 4530 1–8 year old children from randomly selected kindergartens in Chongqing, China participated. Stuffy odor, unpleasant odor, pungent odor, mold odor, tobacco smoke odor, humid air and dry air in the last three month (weekly or sometimes) was reported by 31.4%, 26.5%, 16.1%, 10.6%, 33.0%, 32.1% and 37.2% of the parents, respectively. The prevalence of parents’ SBS symptoms (weekly or sometimes) were: 78.7% for general symptoms, 74.3% for mucosal symptoms and 47.5% for skin symptoms. Multi-nominal regression analyses for associations between odors/sensations of air humidity and SBS symptoms showed that the odds ratio for “weekly” SBS symptoms were consistently higher than for “sometimes” SBS symptoms. Living near a main road or highway, redecoration, and new furniture were risk factors for perceptions of odors and sensations of humid air and dry air. Dampness related problems  were all risk factors for perceptions of odors and sensations of humid air and dry air, as was the presence of cockroaches, rats, and mosquitoes/flies, use of mosquito-repellent incense and incense. Protective factors included cleaning the child’s bedroom every day and frequently exposing bedding to sunshine. In conclusion, adults’ perceptions of odors and sensations of humid air and dry air are related to factors of the home environment and SBS symptoms are related to odor perceptions. Humans spend 90% of their time in indoor environment and home is the indoor environment where we stay most of our time Sick building syndrome (SBS) symptoms usually reported by occupants in certain buildings or specific rooms, has been defined by WHO in 1983 Perceptions of the indoor air quality include odor perceptions and sensory irritation. An odor (commonly referred to as a smell) is caused by one or more volatile organic compounds (VOCs), usually at very low concentrations, that humans or other animals perceived by the olfactory sense as either pleasant or unpleasant. Odor adaptation is always occurring and can explain individual differences on perceived intensity or quality of special odors Most indoor chemicals are nonreactive substances It is commonly believed that indoor air humidity is of importance for health but the association between humidity perceptions and relative humidity (RH) is not clear. Studies have concluded that increased air pollution levels is a more important factor for the sensation of “dryness” than low relative air humidity Sources of odors in daily life in indoor environments include: human body odors; environmental tobacco smoke (ETS); perfume and cosmetics products; commercial products such as deodorizers and air fresheners and building materials. Moreover, fungal growth can release bio-odorants Ventilation flow in building plays an important role in reducing human exposure to indoor pollutants Odors and air quality perception are early predictors of SBS, and can be a signal for other health effects. It was found that mold odor at the skirting board level was strongly associated with allergic symptoms among children in Sweden Reports of odors, as well as stuffy air or dry air are common both in homes and other environments We have found no previous study from China on odor or humidity perception in relation to the home environment factors or SBS symptoms. The aims of this study include four parts. Firstly to describe the prevalence of perceptions of different odors and air humidity in adults in Chongqing and to study gender differences in these perceptions. Secondly to study associations between these perceptions and SBS in adults in Chongqing. Thirdly to study associations between these perceptions and characteristics of the home environment, in order to identify possible sources of odors or irritative emissions. Lastly to study if associations between home environmental factors and SBS symptoms is different in those perceiving or not perceiving odors or humidity sensations, in order to better understand the role of sensory perception for the effect of different home environment factors for SBS symptoms.Both the study and the consent procedure were approved by the Medical Research Ethics Committee of School of Public Health, Fudan University. The participants gave informed consent.The present study is part of an epidemiological multi-center study of asthma and allergies among children and their relation to the home environment in China . The study is using the same study protocol and questionnaire as earlier studies The questionnaires were distributed to children’s parents through teachers in kindergartens in three districts  that were randomly selected from 9 districts of Chongqing city. From the 54 randomly selected kindergartens , 7117 subjects (one parent per child aged from 1–8 years old) were selected and invited for the questionnaire survey. Completed questionnaires were collected one week later by teachers.A modified version of a self-administered questionnaire previously used in Sweden, and among Chinese university students Questions about odor and air humidity perceptions were: During the last 3 months, have you had any of the following perceptions: (1) Stuffy odor; (2) Unpleasant odor; (3) Pungent odor; (4) Mold odor; (5) Tobacco smoke odor; (6) Humid air; (7) Dry air. There were 3 options: (A) weekly; (B) sometimes; (C) never.Questions about SBS symptoms were obtained from the Northern Swedish Office Illness study SBS symptoms were grouped into the following three groups: general symptoms, which include fatigue, feeling heavy headed, headache/nausea/dizziness and difficulties concentrating; mucosal symptoms, which include itching, burning or irritation of the eyes, irritating, stuffy or runny nose, hoarse, dry throat and cough; skin symptoms, which include dry or flushed facial skin, scaling/itching scalp or ears and hands dry, itching, red skin. Results for SBS symptoms were analyzed for general symptoms (at least one), mucosal symptoms (at least one), skin symptoms (at least one).Questions about demographic information, exposure indicators and building characteristics used into the present study included:(1) Gender;(2) A history of asthma, allergic rhinitis or eczema (yes/no);(3) Current smoker (yes/no);(4) House site ;(5) Whether current residence is near a main road or highway within a distance of 200 m (yes/no);(6) Building construction time (before 1980/1980–1990/1991–2000/2001–2005/after 2005);2/41–60 m2/61–75 m2/76–100 m2/101–150 m2/>150 m2);(7) Residence area (≤40 m(8) Wall materials on children’s bedroom ;(9) Floor materials (wood/cement/ceramic tile or stone/laminated floor/other);(10) Whether any redecoration has been done since one year before pregnancy (yes/no);(11) Whether any new furniture has been bought since 1 year before pregnancy (yes/no);(12) Whether subject has reported any mold spots in child’s bedroom (yes/no);(13) Whether subject has reported any damp stains in child’s bedroom (yes/no);(14) Whether subject has reported any water damage in child’s bedroom (yes/no);(15) Whether subject has reported condensation on window panels during winter in child bedroom (yes/no);(16) Whether subject has seen cockroaches in home before (yes/no);(17) Whether subject has seen rats in home before (yes/no);(18) Whether subject has seen mosquitoes/flies in home before (yes/no);(19) Whether subject has used mosquito-repellent incense in home before (yes/no);(20) Whether subject has used incense (not including mosquito-repellent incense) in home before (yes/no);(21) Whether subject has pets in home currently (yes/no); if yes, please indicate it is (cat/dog/rodent (rabbit/rat)/bird/aquarium fishes or reptiles/other);(22) The frequency of cleaning child’s bedroom ;(23) The frequency of putting child’s bedding to sunshine (frequently/never or rarely);(24) The frequency of opening window in child’s bedroom in winter (frequently/never or rarely).An odor and humidity perceptions score was constructed , by adding the number of yes response (weekly or sometimes) to the following odor and humidity perceptions: (1) Stuffy odor; (2) Unpleasant odor; (3) Pungent odor; (4) Mold odor; (5) Tobacco smoke odor; (6) Humid air; (7) Dry air.The Continuous OH-score was then classified in three categories to make another Categorized OH-score: score category 0 (without any odor or humidity perception), score category 1 (1 out of 7 yes answers), score category 2 (2 or 3 out of 7 yes answers), score category 3 (4 or more out of 7 yes answers).All statistical analyses were conducted with SPSS 17.0. Initially, factor analysis was applied to all odor and humidity perceptions questions, using principal component analysis and rotated component matrix . Associations between odor and humidity perceptions and SBS symptoms were calculated by multi-nominal regression models with adjustment for parents’ gender, parents’ history of asthma, rhinitis or eczema and current smoker. Then, the same model was applied for stratified analyses (stratified for gender). As a next step, associations between SBS symptoms and the Continuous OH-score were calculated by logistic regression models (enter method). Odds Ratios were calculated for one unit increase on the 7 steps. Stratified analysis was applied (stratified for gender), using the same model. Then, the OH-score was categorized  and applied in logistic regression models analyzing associations between the Categorized OH-score and SBS symptoms. Stratified analysis was applied (stratified for gender), using the same model. Then, stepwise logistic regression models  were used to find the most significant variables associated with odors . When studying associations between SBS symptoms, home environment and lifestyle characteristics, and odor and humidity perceptions, those reporting any odor (weekly or sometimes) were compared with those not reporting any odor. Results on associations between odor and humidity perceptions and SBS symptoms were given for general symptoms (at least one), mucosal symptoms (at least one), skin symptoms (at least one).Associations were expressed as odds ratios (OR) with a 95% confidence interval (CI) for logistic regression but relative risk ratios (RRR) with a 95% confidence interval (CI) for multi-nominal regression. Analyses are considered to be statistically significant if the p-value was less than 0.05. In all statistical analysis, two-tailed tests and a 5% level of significance were applied.Totally, 5299 of 7117 questionnaires were returned. The total response rate was 74.5%, with small fluctuations across different kindergartens. 4530 complete questionnaires answered by children’ parents (one parent per child) were included in this analysis, excluding questionnaires answered by children’s grandparents or others. Totally, 1340 (29.6%) were males and 3190 (70.4%) were females. Demographic information is shown in Result from factor analysis of odor and humidity perceptions showed that there were 7 factors, none of the perceptions were grouped together (data not shown).The prevalence of parents’ SBS symptoms are shown in Associations between SBS symptoms and the Continuous OH-score were calculated by multiple logistic regression models in Associations between SBS symptoms and the Categorized OH-score were calculated by multiple logistic regression . ResultsAs a next step, associations between building characteristics and odor and humidity perceptions were analyzed. 64.6% of the homes in our study were constructed after 2000. Crude analysis showed that older buildings (constructed before 2001) had more stuffy odor [OR (95% CI): 1.16], unpleasant odor [OR (95% CI): 1.20], mold odor [OR (95% CI): 1.50], tobacco smoke odor [OR (95% CI): 1.21] and the sensation of humid air [OR (95% CI): 1.18]. Stepwise logistic regression (forward elimination) was applied to reduce the models, including the 24 factors see  in TableIn total, 74.5% subjects reported at least one odor or humidity perception in the last three months (shorted as “odor group” in the following text) and 25.5% did not report any odor or humidity perception (shorted as “non-odor group” in the following text). Stratified analyses (stratified for odor and humidity perceptions) using stepwise logistic regression models  were applied to find factors that remained in the models in each stratified group (data not shown). Logistic models were then applied for all factors significant in at least one model in either odor group or non-odor group for particular SBS symptoms . A compaSeveral indoor environmental risk factors were associated with adults’ odor or humidity perceptions. The most significant risk factors were living near a main road or highway, dampness, redecoration, new furniture, the presence of cockroaches, rats, mosquitoes/flies, using mosquito-repellent incense and incense. Protective factors were a higher frequency of cleaning and putting bedding to sunshine. Odors and humidity perceptions were associated with all types of SBS symptoms, both “weekly” and less common symptoms, but associations for weekly symptoms were stronger. A higher number of reported odor or humidity perceptions were associated with a higher odds ratio for SBS symptoms. The associations between new furniture, signs of dampness, cleaning frequency and SBS symptoms were stronger among the odor group, while the association between SBS symptoms and the presence of cockroaches and mosquitoes/flies were stronger among the non-odor group.Epidemiological studies can be affected by selection bias. In this study, we included all parents from the cross-sectional study, with no prior information on parents’ health status. The sample size of this study was reasonably large, and the response rate was good (74.5%). Thus, selection bias is fairly unlikely. However, since the study population consists of young parents, results may not be representative for the entire adult population in Chongqing.Recall bias is another potential problem; subjects may overestimate or underestimate their personal symptoms and/or signs of indoor environment risk factors. Recall bias for odors and humidity perceptions, and SBS symptoms should not be a big issue in this study, since the recall period was short (last three months). Information bias, in which subjects are aware that certain factors have previously been identified as risks, is another potential problem. However, the indoor factors studied in this paper , are not well known as creating indoor health problems among the Chinese population. Moreover, SBS symptoms is not a concept known in China.The prevalence of weekly perceptions of odors and humidity perceptions was not high in our study, except the perception of weekly tobacco smoke odor, but less frequent perceptions were common (range from 16.1% to 37.2%).One main finding was that odor and humidity perceptions were associated with SBS symptoms. Associations between odor and humidity perceptions and SBS symptoms has also been demonstrated in previous studies. One Japanese study found an association between mold odor, stuffiness of air and sick house syndrome (defined similar to SBS) Parents with a history of asthma, allergic rhinitis or eczema had more reports of tobacco smoke odor, but not for other odors or humidity perceptions. This indicates that asthmatic or atopic subjects are more sensitive to some but not all types of odors. Patient studies have demonstrated that nasal allergic symptoms could reduce patients’ sensitivity or olfactory function 2 and PM10 exceed the air quality standards A noteworthy finding in our study is that people living near a main road or highway report more unpleasant odor and pungent odor. Complaints of odors could be signal of polluted air. In an Austrian study, 39.7% adult respondents were annoyed by odorous traffic fumes although pollutant levels complied with current World Health Organization (WHO) guidelines The present study shows that dampness  was significantly related to perceptions of many types of odor and humidity perceptions. This is in agreement with previous studies. Mold, yeasts, wood-rooting fungi, and bacteria can grow in damp buildings New furniture, which often is of “Pleather”  in the dwelling was associated with stuffy odor, unpleasant odor, tobacco smoke odor and the perception of dry air in our study and redecoration was associated with the perception of humid air. Formaldehyde concentrations have been shown to be higher in the presence of furniture bought new or restored less than one year before 2.5 mass as burning 75–137 cigarettes Our study also found that using mosquito-repellent incense in the home was associated with mold odor and tobacco smoke odor and using incense in the home was associated with stuffy odor, unpleasant odor and mold odor. It has been demonstrated that burning one mosquito coil releases the same PMCurrent smoker was associated with tobacco smoke odor in our study. Smoking is the main source of tobacco smoke odor, but the tobacco smoke odor can contaminate the interior and give tobacco odor. New furniture, the presence of cockroaches, rats, mosquitoes/flies and using mosquito-repellent incense and incense were also found to be associated with tobacco smoke odor in this study. It is unclear why new furniture was associated with tobacco smoke odor, possibly there could be an interaction between the VOCs, or SVOCs (semi-volatile organic compounds) emission and the tobacco smoke.The presence of cockroaches, rats, mosquitoes/flies were associated with reported odor and humidity perceptions in present study. Such factors could be a reflection of poor hygiene. Stratified analysis on the construction time of building showed that subjects living in older buildings (constructed before 2001) reported significantly more cockroaches, rats, and mosquitoes/flies in homes as well as more stuffy odor, unpleasant odor, mold odor, tobacco smoke odor and the sensation of humid air. However, the associations between construction time of building and odors disappeared when controlling for other building factors.In this study we found some similar risk factors for the perception of humid air and dry air. They were both associated with current smoker, condensation and the presence of cockroaches, which could be indicators of poor indoor hygiene. Sensation of humid as well as dry air can be indicator of presence of air pollutants rather than a measure of air humidity. Humid air can be an indicator of poor ventilation. It has been discussed that air pollution is a more important factor for the sensation of dryness than low relative humidity Protective factors were also found in this study, including cleaning every day and frequently putting bedding to sunshine. We found no other study about the association between cleaning frequency and perceptions of odor and humidity in the home environment. However, there is no doubt that cleaning and putting bedding to sunshine could improve indoor hygiene conditions.Analysis stratified by odor or humidity perception show that there was no great difference between the odor and non-odor group. However, some associations were stronger among the odor group while other factors were more significant in the non-odor group. For the odor group, it seems that new furniture, dampness related factors and cleaning frequency play a more important role of causing SBS symptoms, while, for the non-odor group, cockroaches and mosquitoes/flies could be more important for causing SBS symptoms. SBS symptoms can be caused by different mechanisms, including airway infections, inflammations, allergic reactions or sensory irritations. It has been shown that subjects who were prone to have infections reported more SBS symptoms Adults’ odor perceptions are associated with both home environmental factors and SBS symptoms. Factors in the home environment, especially living near a main road or highway, dampness and new furniture may increase the risk of odor perception in Chinese residents. The results of this study indicate a need to control material emissions from indoor surfaces, reduce household dampness and encourage frequent cleaning and putting bedding to sunshine to improve occupants’ complaints in indoor environment. Since SBS was associated with odor and humidity perceptions, perceived poor air quality could have medical implications.


ACTN3 resulting in α-actinin-3 deficiency (the ACTN3 577XX genotype) is common in humans and reduces strength, muscle mass, and fast-twitch fiber diameter, but increases the metabolic efficiency of skeletal muscle. Linkage disequilibrium data suggest that the ACTN3 R577X allele has undergone positive selection during human evolution. The allele has been hypothesized to be adaptive in environments with scarce resources where efficient muscle metabolism would be selected. Here we test this hypothesis by using recently developed comparative methods that account for evolutionary relatedness and gene flow among populations. We find evidence that the ACTN3 577XX genotype evolved in association with the global latitudinal gradient. Our results suggest that environmental variables related to latitudinal variation, such as species richness and mean annual temperature, may have influenced the adaptive evolution of ACTN3 577XX during recent human history.A premature stop codon in  ACTN2 is expressed in all skeletal muscle fibers, while ACTN3 is expressed in fast-twitch muscle fibers. Mammalian ACTN2 and ACTN3 genes appear to have arisen from a gene duplication that occurred over 310 million years ago, before the divergence of birds and mammals ACTN 2/3 gene, ACTN3 evolved specific expression patterns in fast twitch muscle fibers, which are responsible for generating force at high velocity. Yet, approximately 18% of the human population is homozygous for an allele (R577X) that contains a premature stop codon in ACTN3ACTN3 577XX genotype has been hypothesized to be adaptive where efficient muscle metabolism is concerned, such as in environments with scarce resources or where endurance running has an impact on survival ACTN3 577XX genotype frequency and global latitudinal patterns of biodiversity. This relationship is predicted because factors related to food acquisition and hunting, such as species richness or mean annual temperature, show well-established global latitudinal patterns Genes important for metabolism include the α-actinin family that code for contractile proteins in muscle ACTN3 577X substitution likely preceded the arrival of anatomically modern humans in Europe and Asia 40,000–60,000 years ago ACTN3 577XX may have arisen during the recent past, specifically in relation to the global latitudinal gradient. Here we test the ACTN3 577XX adaptation hypothesis using global genotype and biodiversity data, with Bayesian comparative methods that account for phylogeny and migration.The ACTN3 XX frequency data were obtained from the literature . ACTN3 XX frequency data were Arcsin transformed before statistical analysis, a transform suitable for nominal and percentage data terature . These do), net primary productivity (grams of carbon), and total species richness (tetrapods) data for each country/region. Although some of these metrics have changed over the time period in which ACTN3 polymorphisms arose in human populations, they nonetheless show a consistent relationship with the global latitudinal gradient ACTN3 allele frequencies arose among human populations. Even so, we expect differences in our gene frequency data to have arisen relatively recently in line with modern climatic variation .Using the World Wildlife Fund Ecoregion database We curated our data by compiling a list of every ecoregion within each country. The list was constructed first using maps to form overestimated rectangles of minimum and maximum latitude and longitude around each country to account for irregular borders. Every ecoregion within these rectangles was gathered and narrowed down further using Google Earth (we limited Russia to west of Mongolia). By using the average latitudinal and longitudinal coordinates of each ecoregion, we were able to see if the ecoregion fell within the borders of the country in question. Ecoregions within the country were retained, while ecoregions outside of the country were removed from the list. One exception was Israel, which had no ecoregions within its borders, so the two closest ecoregions were used.Homo Neanderthalensis (NCBI 196123578) was included as an outgroup.We produced a Bayesian posterior distribution of phylogenetic trees from whole mitochondrial sequences for the following human lineages: Aboriginal Australian (NCBI 134303155), Bantu (NCBI 160426755), Israeli (NCBI 145968101), Japanese (NCBI 61287226), Chinese (NCBI 292597164), Kenyan (NCBI 13272962), Papua New Guinean (NCBI 256946671), Lithuanian (NCBI 301017707) Russian (NCBI 290555741), Swedish (NCBI 215789486), Nigerian (EMBL AF346985), Italian (EMBL AF346988), Greek (EMBL GQ129165), Spanish (NCBI 74475826), and Ethiopian (NCBI 156459510). The whole mitochondrial genome of The program MUSCLE http://www.evolution.rdg.ac.uk). BayesTraits accounts for confounding phylogenetic relatedness in continuous data using a generalized least square (PGLS) approach. It can also account for phylogenetic uncertainty by integrating analyses over more than one tree (or a distribution of trees). Before we ran the regression analysis, we tested whether a random walk model of character evolution or a directional model of evolution best fit our data. We found no evidence for directional evolution . Our analysis also estimated phylogenetic signal (λ), a parameter that assesses the degree to which covariation among trait values follows the phylogeny during the random walk and regression analysis Statistical tests that accounted for phylogeny  were performed in the program BayesTraits Significance was determined for the random walk test using Bayes Factors, calculated as two times the difference between the harmonic means of log-likelihoods for the two models. Bayes factors of three or more indicate positive evidence, five of more strong evidence, and 10 or more very strong evidence Statistical tests that account for both phylogeny and migration were performed in the statistical programming language R ACTN3 577XX genotype may have evolved in association with global latitudinal patterns of biodiversity.Recent work ACTN3 577XX population frequency onto latitude, while estimating phylogenetic signal over the distribution of trees (and thereby accounting for phylogenetic uncertainty). We found strong phylogenetic signal in the regression model relating ACTN3 577XX frequency and latitude (maximum likelihood estimate of λ = 1). The model relating ACTN3 577XX frequency and latitude  was supported, with a slope parameter for the generalized linear mixed model of 0.003 . It should be noted here the importance of properly controlling for relatedness among the data – a standard linear regression model returns the same slope, but with an associated p-value of 0.006 and an R2 of 0.45. Note that goodness of fit is not reported in MCMCglmm, but an R2 of 0.32 is reported in BayesTraits, which controls for phylogeny, but not migration.We began by inferring a Bayesian posterior distribution of phylogenetic trees , which mACTN3 577XX frequency variation. We tested only the most plausible factors to avoid overt testing of multiple hypotheses: species richness, mean annual temperature, and net primary productivity . We found no evidence for phylogenetic signal in the regression model relating ACTN3 577XX frequency and total vertebrate species richness (maximum likelihood estimate of λ = 0), but high levels of phylogenetic signal (maximum likelihood estimate of λ = 1) for both mean annual temperature and primary productivity. Accounting for phylogeny and migration, the model relating ACTN3 577XX frequency and total vertebrate species richness was supported, with a slope parameter of −0.23 , as was the relationship between ACTN3 577XX frequency and mean annual temperature . However, we found no support for a model relating ACTN3 577XX frequency and net primary productivity .As discussed earlier, many factors covary with latitude that could explain ACTN3 variation in the 577XX genotype, long-range linkage disequilibrium associated with ACTN3 577X (signature of positive selection) ACTN3 577XX frequency were driven by changing environmental conditions and resources associated with latitudinal migration.For present day latitude and associated data (such as species richness) to be meaningful in an evolutionary analysis, it must fairly represent latitudinal data of the past where genetic associations may have evolved. The relationship between latitudinal gradients and species richness, for example, is consistent through the recent past, with taxa preferentially originating in the tropics and spreading toward the poles


The proportion of conserved DNA sequences with no clear function is steadily growing in bioinformatics databases. Studies of sequence and structural homology have indicated that many uncharacterized protein domain sequences are variants of functionally described domains. If these variants promote an organism's ecological fitness, they are likely to be conserved in the genome of its progeny and the population at large. The genetic composition of microbial communities in their native ecosystems is accessible through metagenomics. We hypothesize the co-variation of protein domain sequences across metagenomes from similar ecosystems will provide insights into their potential roles and aid further investigation.Cyanobacteria. Other clusters included DUFs associated with DNA maintenance and repair, inorganic nutrient metabolism, and sodium-translocating transport domains. We also observed a number of clusters reflecting known metabolic associations and cases that predicted functional reclassification of DUFs.We calculated the correlation of Pfam protein domain sequences across the Global Ocean Sampling metagenome collection, employing conservative detection and correlation thresholds to limit results to well-supported hits and associations. We then examined intercorrelations between domains of unknown function (DUFs) and domains involved in known metabolic pathways using network visualization and cluster-detection tools. We used a cautious “guilty-by-association” approach, referencing knowledge-level resources to identify and discuss associations that offer insight into DUF function. We observed numerous DUFs associated to photobiologically active domains and prevalent in the in silico may draw from these insights and opportunities to discover new associations and corroborate existing ones will arise as more large-scale metagenomic datasets emerge.Critically examining domain covariation across metagenomic datasets can grant new perspectives on the roles and associations of DUFs in an ecological setting. Targeted attempts at DUF characterization in the laboratory or  In recent years, genomic sequencing projects have revealed a large number of novel genes across a wide range of organisms and environments. Many of these have poor sequence-level similarity to genes that have been characterized in a laboratory setting and, consequently, have not been annotated with functional roles. These ‘hypothetical’ genes are becoming increasingly prevalent in bioinformatics databases. For example, the Pfam 24 database 2 sulfonates Several groups have employed biochemical and molecular techniques in DUF characterization. Among these, Deng et al. in situ sequence data from a range of ecosystems. These metagenomic resources are ripe for mining, with intra-ecosystem variation in microbial function cited as a high-value target for exploration Metagenomics allows insight into an entire ecological community's genetic content Here, we propose that correlations of protein domain sequences found in intra-ecosystem metagenomic data may provide insight into the functional roles of DUFs. We critically examined the correlation of protein domains of known and unknown function across the Global Ocean Sampling (GOS) collection Here, we queried raw sequences of selected GOS metagenomes against version 24 of the Pfam database −6. These included 225 (UM) and 75 (SM) DUFs. Correlation of domains in the UM resulted in largely Gaussian distribution of rho coefficients ; however, a slight second peak around a rho of 0.80 was observed . Correlation of domains in the SM displayed a more Gaussian distribution of rho values ; however, with a positive skew . Based on these distributions, we chose a correlation threshold and conservative significance values to focus on robust associations.Removal of rows (sites) and columns (Pfams) dominated by zero abundances was performed to decrease the sparseness of the dataset and focus on observed variation. The dataset was thus reduced from a matrix of 80 GOS metagenomes and 3,587 Pfam domains to 69 sites and 1,863 Pfam domains. A total of 670 of the domains retained were DUFs. We standardized abundances by their site maxima to mitigate the effect of differing sample size across metagenomes; however, the co-variation of domain abundances due to sample size may still provide insights into their potential associations, assuming proportionality. Thus, we used the unstandardized matrix (UM) and its standardized counterpart (SM) in further analysis. Totals of 975 (UM) and 167 (SM) Pfams were retained following removal of those with no correlations stronger than a rho of 0.80 and Bonferroni-corrected P-values below 1×10S2), many of which were also associated with a septum formation inhibitor domain (MinC_C) involved in the control of cell division. In the analysis of the SM, 48 DUFs showed biased correlations, with 45 in favor of photobiological processes (Table S3). Of these 45, 15 showed some bias (≥40% of the maximum correlated category) towards domains in carbohydrate and/or coenzyme metabolism. The three remaining DUFs were associated to domains in inorganic ion transport and metabolism (DUF1008); carbohydrate transport and metabolism (DUF111); and transcription (DUF37). Such biased connectivity of DUFs to domains in a particular functional category is not a guarantee of related function; however, it provides associative context for hypothesis generation.In the UM, a total of 94 DUFs showed biased correlations to Pfam domains assigned to a single metabolic category . Of thesFigure S3 for node labels). The larger of these regions (Box 1) contained a core of highly interconnected nodes with domains from a wide variety of metabolic categories, as well as ‘spokes’ of less interconnected nodes. The highly-enmeshed topology of this large connected complex (LCC) prevents speculation on DUF function by visual inspection alone. However, a spoke of the UM LCC . These included a central photosystem II domain, a subunit of the photosystem I reaction center, a domain that targets precursors of light-harvesting prosthetic groups, and a proton-pumping domain essential for photoheterotrophic cell growth. The taxonomic distribution of the DUFs in this region (after Pfam v26) was heavily weighted toward the Cyanobacteria and other photobiologically active taxa, such as the Viridiplantae. It is premature to connect the DUFs in this region directly to phototrophic mechanisms; however, a photoresponsive mode of life may have some bearing on their function and association in marine metagenomes.The smaller region of this network (Table S5). For example, eight domains were involved in cobalamin metabolism and the large and small subunits of RuBisCO were also present. Cobalamin (vitamin B12) is characterized by a corrin ring, which is chemically similar to the porphyrin ring found in heme, chlorophyll, and cytochrome. Further, cobalamin-dependent methyltransferases are involved in C1 metabolism and CO2 fixation Additionally, we noted the domains bridging this putative module to the bulk of the LCC were also photobiologically relevant  with similar membership to the bridge and photobiological regions discussed above (Table S6). This network featured 112 Pfams, which included DUFs (n = 72), photoreactive domains (n = 10), and coenzyme transport and metabolism domains (n = 8). We also observed a network , coenzyme F420 hydrogenase , and domains involved in eukaryotic DNA polymerase processivity .Cyanobacteria; however, their specific correlation with the photoreaction center domain is likely caused by the co-occurrence of these domains in marine cyanophages, which infect the genera Synechococcus and Prochlorococcus. Previous work has identified a number of cyanophage-borne photosynthetic genes which are transferred to their hosts, including psbA and psbDAlphaproteobacteria and Pfam architectures note them in proximity to the inner membrane component of a binding-protein-dependent transport system (BPD_transp_1). DUF137 was associated with two ATP synthase subunits. We observed these three domains to be prevalent in the Archaea, thus, attributing DUF137 with ATP synthase activity is premature, as taxonomic restriction may also explain their correlation. A similar explanation can be applied to the association of DUF655 and DUF54, the former domain reportedly resembling a ribosomal protein Archaea. Similarly, a pair comprising DUF126 and DUF521 shared similar taxonomic distributions, occurring primarily in the Bacteria and Archaea. The remaining networks, often featuring few domains with broad taxonomic distribution and poor characterization, were not amenable to our ‘guilty-by-association’ interpretative approach.We also observed several small networks with DUFs associated to domains that may shed light on their roles. Notably, a haemin-degrading domain was associated with DUF1008 in analysis of both the SM  and 13 such clusters from the SM .Associations between DUFs in highly-enmeshed regions are difficult to evaluate by visual inspection. Transitivity clustering Much of the highly-enmeshed core of the UM-derived LCC remained in a single cluster (Table S7) contained most domains from the photobiological region of the original network (Table S8) was similar and included 28 DUFs, five photobiological domains, two cobalamin metabolism domains, and a fructosamine kinase domain.We observed prominent transitivity clusters with photobiologically relevant domain membership. A UM-derived cluster . For example, DUF484 and DUF2066 were clustered with domains involved in sodium translocation linked to amino acid transport and redox as well as a ligase that initiates the glutathione biosynthesis pathway  with very low representation in the Proteobacteria, a restriction that may account for their clustering. However, domains in several smaller clusters showed dissimilar taxonomic distributions. These included a cluster  and are not intended as a basis for phylogenomic profiling.The taxonomic distribution of Pfam domains, particularly those present in the highly abundant marine Proteobacteria, Firmicutes, Actinobacteria, and Cyanobacteria. The DUFs of the largest UM-derived transitivity cluster (TC1) had similar distributions to the whole collection, while DUFs whose instances were concentrated in cyanobacterial genomes dominated the second cluster (∼55%). The proteobacterial proportion of this latter cluster was dominated by the Gammaproteobacteria (∼56%) and a proportion of Alphaproteobacteria (∼23%). The genera Rhodobacterales and Rhodospirillales, known to possess proteorhodopsin genes encoding light-powered proton pumps, were present in the alphaproteobacterial division. As reviewed by DeLong and Béjà Proteobacteria and those from TC15 were almost exclusively Cyanobacteria (∼95%). Other clusters with conspicuous taxonomic restrictions included TC31, with domains prevalent in actinobacterial genomes, and TC43, with domains prevalent in bacterial, fungal, and plant genomes.In the UM-derived clusters Table 6,Fungi, Firmicutes, and Cyanobacteria.The DUFs in SM-derived clusters Table 7 Assigning the associations discussed above with meaningful measures of confidence is an immediate concern. False positives may lead experimentalists in fruitless directions, while false negatives may limit functional discovery. Similar difficulties are encountered when attempting to benchmark protein interaction networks and attempts to minimize them rely on the reproducibility of interactions across datasets or the use of well-characterized model systems or gold standards Bacteria and Archaeain silico predictions in vitro may, en masse, provide a degree of confidence estimation for studies similar to ours. DUFs which have been described as at least partially characterized in subsequent releases of Pfam may anticipate such estimation. Relative to Pfam v24, we noted 28 DUF families present in our UM and SM datasets which have been renamed or merged into existing families in Pfam v26 (Table S10). In the UM-derived data, eight of these DUFs were not clustered while a further eight occurred in the highly-enmeshed TC1  and 48 (SM) DUFs with connectivity biased towards a single metabolic category. Further, the results above list 73 DUFs from the UM-derived and 41 DUFs from SM-derived networks and transitivity clusters whose associations may reflect ecological features of the marine epipelagic zone. While these results represent only a fraction of the DUFs detected in the GOS metagenomes, this analysis is an initial step in using ecogenomic variation to assist functional discovery. The opportunity to routinely perform such exploratory analyses and establish quantitative benchmarks is emerging as data from large-scale metagenomic, metatranscriptomic, and metaproteomic sampling campaigns becomes publically available. The perspectives that can be derived from this data will almost certainly forward efforts to characterize DUFs where homology-based approaches cannot.Table S1), were used in further analyses.A collection of 10,133,846 unassembled reads from the Global Ocean Sampling expedition metagenomes GS000a-GS023, GS025-GS051, GS108a-GS117b, GS119-GS123, GS148-GS149, and MOVE858 http://cran.r-project.org/). Pfam categories listed in more than one metabolic category were removed. Distributions of total, non-zero abundances across Pfam categories and sites were used to advise data preparation. Categories with less than 20 non-zero abundances across the 80 sites analyzed and sites with less than 1,000 non-zero abundances across the 3,587 Pfam categories analyzed were removed. A copy of the resulting matrix was subject to row standardization, whereby the Pfam abundances across a given site (row) were divided by the maximum Pfam abundance of that site. The Spearman's rank correlation of Pfam categories in both matrices was determined using the rcorr function from the R package Hmisc. Pfam categories with no correlations greater than a rho of 0.80 and with a P-value less than a Bonferroni corrected cut-off of ∼1×10−6 were removed. DUFs that showed correlations biased towards Pfams in a single metabolic category were noted. Bias was declared when the number of correlations of a DUF to Pfams in a given category was at least double that of correlations to any other category.The site×Pfam matrix described above was imported into the R statistical computing environment (The igraph R package www.pfam.sanger.ac.uk) and further literature where appropriate.Networks were manually inspected for distinct topological features, particularly those where DUFs were associated with characterized Pfams from a narrow range of COG categories. The domains comprising these features were investigated further by retrieving descriptions from Pfam 26 via its webportal  and the results stored in a relational database. Only clusters with ≥4 members and ≥2 DUFs were examined and those with notable distributions were discussed.The DUFs in several transitivity clusters were annotated with their collective taxonomic distribution. Distributions were retrieved from the Pfam website Click here for additional data file.Table S1Pfam 24 domains categorized as photobiologically relevant in this analysis.(DOC)Click here for additional data file.Table S2DUFs with correlative bias towards photobiologically relevant domains (unstandardized data).(DOC)Click here for additional data file.Table S3DUFs with correlative bias towards metabolic categories (standardized data). Refer to (DOC)Click here for additional data file.Table S4Domains present in a network region characterized by photobiologically relevant domains . Refer to (DOC)Click here for additional data file.Table S5Domains present in a network region bridging two enmeshed regions . Refer to (DOC)Click here for additional data file.Table S6Domains present in the primary network generated from standardized Pfam abundances across GOS sites . Refer to (DOC)Click here for additional data file.Table S7Pfam domains contained in the second largest transitivity cluster derived from unstandardized domain abundances (: TC2). Refer to (DOC)Click here for additional data file.Table S8Pfam domains contained in the largest transitivity cluster derived from standardized domain abundances (: TC1). Refer to (DOC)Click here for additional data file.Table S9Pfam domains contained in the selected transitivity clusters derived from unstandardized domain abundances . Refer to (DOC)Click here for additional data file.Table S10DUFs with updated statuses in Pfam v26 and their location in transitivity clusters (TCs) from both the unstandardized  and standardized  datasets.(DOC)Click here for additional data file.Figure S1Histogram of correlation strength between unstandardized abundances of Pfam domains across GOS metagenomes. The distribution's mean and standard deviation were ∼0.41 and ∼0.26 respectively. A normal distribution with equal mean and standard deviation is indicated by a blue contour.(TIF)Click here for additional data file.Figure S2Histogram of correlation strength between abundances of Pfam domains across GOS metagenomes, standardized by site maxima. The distribution's mean and standard deviation were ∼0.03 and ∼0.19 respectively. A normal distribution with equal mean and standard deviation is indicated by a blue contour.(TIF)Click here for additional data file.Figure S3High resolution, unannotated version of  with individual node labels.(TIF)Click here for additional data file.Figure S4High resolution, unannotated version of  with individual node labels.(TIF)Click here for additional data file.Figure S5High resolution, unannotated version of  with individual node labels.(TIF)Click here for additional data file.Figure S6High resolution, unannotated version of  with individual node labels.(TIF)Click here for additional data file.Figure S7Color key for network nodes.(TIF)Click here for additional data file.


BRCA1 and BRCA2, was the beginning of a sustained effort to uncover new genes explaining the missing heritability in this disease. Today, additional high, moderate and low penetrance genes have been identified in breast cancer, such as P53, PTEN, STK11, PALB2 or ATM, globally accounting for around 35 percent of the familial cases. In the present study we used massively parallel sequencing to analyze 7 BRCA1/BRCA2 negative families, each having at least 6 affected women with breast cancer (between 6 and 10) diagnosed under the age of 60 across generations. After extensive filtering, Sanger sequencing validation and co-segregation studies, variants were prioritized through either control-population studies, including up to 750 healthy individuals, or case-control assays comprising approximately 5300 samples. As a result, a known moderate susceptibility indel variant (CHEK2 1100delC) and a catalogue of 11 rare variants presenting signs of association with breast cancer were identified. All the affected genes are involved in important cellular mechanisms like DNA repair, cell proliferation and survival or cell cycle regulation. This study highlights the need to investigate the role of rare variants in familial cancer development by means of novel high throughput analysis strategies optimized for genetically heterogeneous scenarios. Even considering the intrinsic limitations of exome resequencing studies, our findings support the hypothesis that the majority of non-BRCA1/BRCA2 breast cancer families might be explained by the action of moderate and/or low penetrance susceptibility alleles.The identification of the two most prevalent susceptibility genes in breast cancer,  BRCA1 and BRCA2P53, PTEN or STK11PALB2, BRIP1, RAD51C and XRCC2ATM, CHEK2, RAD51D and RAD51BFrom the original publication of the two most widely known breast cancer (BC) susceptibility genes, namely In this regard, linkage analysis has been one of the most widespread techniques for the identification of susceptibility genes. Our group presented one such study in 41 BC families, which revealed three genomic regions of interest Massively parallel sequencing was demonstrated to be a good strategy for the identification of genes responsible for monogenic diseases BRCA1/BRCA2 mutations and younger than 60 y/o. Here, we found several rare variants that could putatively act as BC susceptibility genes but we also highlight the lack of evidence of novel high penetrance genes in this disease.In the present study we employed massively parallel sequencing technology to investigate 7 families with at least 6 women (between 6 and 10) bearing unilateral and/or bilateral BC, previously tested negative for Written informed consent was obtained from all patients included in this study. The research project was approved by the following ethics committees: Instituto de Salud Carlos III Ethics Committee (Spain), Fondazione IRCCS Istituto Nazionale Tumori Ethical Committee , Human Research Ethics Committee of the University of Melbourne , Comité Ético de Investigación Clínica del Hospital Clínico San Carlos de Madrid (Spain), Human Research Ethics Committee of Bellvitge University Hospital (Spain), Creighton University Ethics Committee (US), Medical Ethics Committee of the Leiden University Medical Center (The Netherlands).BRCA1 and BRCA2 genes and having no women affected with ovarian cancer in the family. When possible, genomic DNA samples from two individuals per family were selected for whole exome sequencing, while samples from additional individuals in the family were obtained for further validation , including several BC-affected individuals, were evaluated for the present study. Seven families were finally selected based on having at least 6 BC cases (between 6 and 10) diagnosed before the age of 60, being negative for mutations in lidation  and S2.BRCA1 or BRCA2 (named BRCAx families). Briefly, families contained at least three females affected with breast cancer or at least two first-degree females affected with breast cancer (at least one of them diagnosed before 50) or at least one case of female breast cancer and at least one case of either ovarian, female bilateral breast or male breast cancer. Control population consisted of DNA samples from 3960 women aged between 25 and 65 years and without personal or familial antecedents of any cancer cases. Controls proceeded from the different countries and their distribution is shown in For case control association studies we selected index cases from 3694 high risk breast/ovarian cancer families without deleterious mutations in DNA samples from eleven cases  and S2 awww.novocraft.com) applying standard parameters except for the option of reporting three alignments where multiple alignment sites were found. Those reads not meeting Novoalign’s quality criteria or not matching the reference genome were removed. Samtools version 0.1.8 Raw sequencing data for cases and controls was first filtered to remove those reads with (1) no base called in more than 5 positions and (2) having called the same base in more than 70% of the total read length. After filtering, reads were aligned against the human reference genome (hg18) using Novoalign version 2.06.09 .Not being present in any of the 7 HapMap controls.Not being present in dbSNP130.Remaining variants were annotated using Annovar SNPs were filtered by DS and QS, selecting those with a DS and QS between 20 and 210.INDELs were filtered by DS <140, Phred Scaled Quality >10, SNP Quality >10 and having at least 3 reads supporting each reference and variant alleles.In order to set up our score filtering criteria, SNPs and INDELs from the seven HapMap controls already present in dbSNP130 were selected. Several combinations of scores were tested for selecting the highest possible number of variants present in dbSNP130, while targeting the lowest number of total variants detected. For SNPs, the selected combination of scores targeted over 95% of the total number of SNPs detected, while for indels the percentage was reduced to 22% due to the high number of false positive calls in our unfiltered indel data set.Candidate variants obtained after all the filtering steps were prioritized by Fisher’s Exact Test p value, OR value, segregation and control population studies as described in the text.Sensitivity confirmation analysis for our pipeline, in the form of several modifications to the standard variant filtering strategy, were performed in order to validate the best possible sensitivity for candidate variant detection. These modifications included:Manual re-analysis of all variants in every family after removing variant type and gene filters.Contrasting our set of unfiltered SNP variants against those in 1000 Genomes Project. Common variants presenting minor allele frequencies (MAF) below or equal to 1% were reviewed to guarantee no potential causal variants were missed in the original dbSNP130 filtering step.All stop, frameshift and splicing variants regardless of gene and score filters were re-analysed.XRCC2, RAD51C, RAD51D, PALB2, BRIP and other DNA repair genes were investigated in greater detail.Our unfiltered set of variants was matched against some of the latest identified risk modifier variants in BC, while all variants in moderate penetrance genes Interesting variants not shared by both individuals in those families with two individuals available for massively parallel sequencing were evaluated. This was conceived as a confirmation test to rule out the possibility of having selected a phenocopy for our initial sequencing analysis in one of the families.www.ensembl.org) for further information and validated by Sanger sequencing.All candidate variants were manually matched against the latest available version of Ensembl .Genotyping in the control collection was done by dHPLC screening or TaqMan (Applied Biosciences). Briefly, appropriate amplification primers were designed for a genomic region containing the variant of interest. Then, genomic control DNA from individuals without familial BC antecedents was PCR amplified and analysed by dHPLC as previously described Case control studies were performed either using TaqMan genotyping assays or TaqMan OpenArray technology (Applied Biosciences). Genotyping using TaqMan assays was performed as previously described, this time including both familial BC affected (cases) and non-affected (control) individuals. TaqMan OpenArray technology was used for large scale genotyping. Briefly, 64 SNP array format was selected to genotype 56 variants of unknown significance in 2693 cases and 2544 controls from different ethnic origin coming from various centers from the BC consortium. Issues with custom probe design and cluster discrimination in specific probes reduced the final number of informative variants to 39. A total of 130 arrays were performed and analyzed uniformly according to the manufacturer’s standard protocol. HapMap and sample duplicates were included in each array to serve as internal controls and to ensure reproducibility of the results. Genotype calling and sample clustering for OpenArray assays was performed in TaqMan Genotyper Software v1.0 (Applied Biosciences). Statistical analysis of the data was done using PLINK software The potential functional impact of the non-synonymous variants detected in this study was inferred based on predictions made by SIFT Eleven individuals from 7 families and 7 HapMap cell lines, serving as internal and filtering controls, were analyzed by massively parallel sequencing in this study. Results including number of reads, sample coverage and sequencing depth have been summarized in The bioinformatics analysis and variant filtering pipeline was developed by our group and recently used in the identification of a novel familial pheocromocytoma gene FANCM, CNTROB) or affected a P53-related gene, TP53I13 , a gene already described as a moderated susceptibility gene One of the variants identified in Family RUL153 was a deletion in FANCM was mutated in families 694 and 531  ; CNTROB   and HSP90B1  , were discarded for being present in control population with a MAF >1% (SLBP (c.697G>A) (a stem-loop binding protein) and CNTROB (c.1819G>A), both in family RUL036, were not found in the same set of controls. A splice site variant in the oncogenesis-involved WNT8A (c.103G>T) gene was found in family 694. We were unable to confirm experimentally whether the variant altered the splicing, due to a very low expression level of the gene in fibroblasts (data not shown). However, after performing a case-control study by TaqMan in 2043 BRCAx cases and 2186 controls, none of the 4229 samples were found to carry the same variant. Ultimately, four rare variants were selected from the group of 25 high interest variants: FANCM , SLBP , CNTROB  and WNT8A .Other candidate variants segregating in more that 50% of the individuals in our families such as  MAF >1% . On the We then focused on the analysis of the remaining 56 missense variants of unknown significance, not previously described in ensemble database and predicted to be deleterious or probably damaging in at least one of the two predictive programs, SIFT From the previous group of 39 variants, we selected for further validation those variants with an estimated OR higher than two or not present in controls. Thirteen variants fulfilling these criteria were Sanger-validated and analyzed for segregation in their original families (except for variants in family 694) . Five vaThe present study was designed to identify new high susceptibility genes in familial BC. Family selection was based in the highest possible number BC cases per family under the age of 60 (6 to 10 cases through generations), while having no other tumor types segregating in the family. As proposing candidates relying on next generation sequencing results alone is not sufficient evidence, segregation, control population and case-control studies were performed to gain further insight on the relevance of the proposed candidates in BC.A total number of 81 variants, 67 snps and 14 indels, were identified as potential candidates after applying our filtering protocols. These were subdivided into two groups to facilitate the analysis, a first group containing mainly putative protein truncating variants or variants shared between several families and a second group of rare missense mutations. Among those in the first group, we detected a previously identified moderate susceptibility indel variant in CHEK2 (c.1100delC) in family RUL153 , which sFANCM variant c.5791C>T generates a premature stop codon, originating the loss of 118 aminoacids from the c-terminal end of the main transcript and putatively influencing FANCD2 monoubiquitination. A case control study in a cohort of over 7300 samples revealed an OR = 2.29 and a non-significant Fisher’s Exact Test p value (p = 0.13). However, given the low frequency of this variant (0.0011 in cases and 0.00077 in controls), its variable prevalence in the available populations  in the Australian controls, data not shown) and FANCM’s important role in DNA repair, it would be interesting to analyze this gene in a higher number of samples to fully understand its contribution to BC. Also, hints of a possible link with BC were found for BRCA2 interacting CNTROB (c.1819G>A), SLBP (c.697G>A) and WNT8A (c.103G>T). Those presented a high level of familiar segregation in the available individuals (greater than 50%) and absence of the variant in over 700 controls (CNTROB and SLBP) or in over 4000 samples (WNT8A), similarly to what could be expected for rare susceptibility variants , a large enough cohort to obtain a preliminary idea of association with BC. Since we discarded variants with a MAF higher than 1% and only rare variants were considered after this point in the analysis, we did not have enough statistical power or we could not calculate it in those variants present in neither cases nor controls. Therefore, we selected variants with a high probability of being linked with cancer by prioritizing variants with OR higher than 2 or absent in controls, a damaging predicted functional impact and segregating in over 50% of the available individuals in each family. Our final candidates include 7 variants in genes related with cell survival, proliferation, angiogenesis, cell cycle progression, cell adhesion and other roles plausibly related to cancer development and progression . These gFANCC and BLM, which would be mutated in approximately 0.5% of BRCAx families. Both studies also suggested a number of rare variants to be analyzed further in future studies.As our families were selected for the high number of affected women across generations and their seemingly dominant model of inheritance, our results were unexpected. However, two recent whole exome studies were also unsuccessful in finding novel high penetrance genes in BC, pointing our result towards a more common scenario in this disease. While selecting their families with less strict criteria, Snape et al A number of limitations in the present study need to be taken into consideration. The number of individuals/families selected for this re-sequencing study is smaller than that of similar studies. While this approach might limit the number of potential candidate variants detected as compared to other less stringent family selection strategies Finally we cannot rule out that some of these families shift a putative explanation towards a polygenic model where moderate and low penetrance alleles would play a predominant role. This hypothesis has been suggested by different authors According to the presented data, families fulfilling the criteria of high risk for BC and including several affected women across generations show evidence of a high genetic heterogeneity and complexity. In this context, some families would be explained based in a polygenic model where rare variants would play an interesting role in BC susceptibility.Further studies in a larger number of families, using a combined strategy of whole exome/whole genome sequencing, case-control association studies including thousands of samples and targeted resequencing of genomic regions containing rare variants is needed to confirm these preliminary results and to define the genetic architecture of non-BRCA1/2 BC families.Figure S1Pedigrees of families included in this study I. Pedigrees 694, RUL153 and 531 are represented in this figure. Arrows indicate individuals selected for massively parallel sequencing. Cancer affected individuals are partly or totally highlighted in black. Br sign followed by a number under affected individuals marks the age of diagnostics of each breast cancer event. Deceased individuals are marked by a slash. Arabic numbers refer to those members used for segregation. UL = Unilateral breast cancer. BL = Bilateral breast cancer.(TIF)Click here for additional data file.Figure S2Pedigrees of families included in this study II. Pedigrees 3311, RUL036, 49 and 2887 are represented in this figure. Arrows indicate individuals selected for next generation sequencing. Cancer affected individuals are partly or totally highlighted in black. Br sign followed by a number under affected individuals marks the age of diagnostics of each breast cancer event. Deceased individuals are marked by a slash. Arabic numbers refer to those members used for segregation. UL = Unilateral breast cancer. BL = Bilateral breast cancer.(TIF)Click here for additional data file.Table S1Clustering of Validation Samples by Country of Origin. Distribution of samples and controls used for the different case-control studies and validation analysis by TaqMan and OpenArray. FANCM was studied with samples from 1–6. WNT8A was studied with samples 1, 2, 4 and 5. OpenArray: samples from 1–5. CNIO control samples were used for validation of variants in aSpanish National Cancer Research Centre (Spain). bHospital Clinico San Carlos (Spain). cHospital Universitario Valladolid (Spain). dLeiden University Medical Center (Netherlands). eIstituto Nazionale dei Tumori . dThe University of Melbourne .(DOC)Click here for additional data file.Table S2Next Generation Sequencing Metrics and Coverage. Next generation sequencing results per sample. aSequence stands for the number of bases sequenced per individual. bNumber of genomic matches refers to the number of genomic locations aligning to the total number of reads in a given sample. The option of reporting up to 3 alignment positions on conflicting matches increases this number with regard to the total number of reads. cOn-target refers to the total number of reads on target. dPaired end column represents the number of on-target positions successfully aligned as paired-end reads.(DOC)Click here for additional data file.Table S3Candidate Variants I: Potential Protein Truncating, Splicing Variants and Indels. List of 25 potential protein truncating or splicing variants, indels and variants of unknown significance in genes shared by different families. In bold, selected variants. aPosition according to the coordinate system (HG18). bSanger sequencing validation. cResults of segregation studies marking positive individuals out of the total number available for validation. dControl population studies were performed in variants segregating in over 50% of the available individuals for validation. Figures represent the number of positive cases out of the total number tested, as well as the percentage of positive cases in the population. eMinor Allele Frequency reported in 1000 Genomes Project (May 2011 release). N/A = not available. NV = non validated.(DOC)Click here for additional data file.Table S4List of Variants Analyzed by Open Array Case-control Design and Results. List of variants analyzed by Open Array case-control design. In bold, selected candidates. aChromosome where the variant was mapped. bPosition according to the coordinate system (HG18). cVariant consequence: NS = non-synonymous variant UTR3 = 3′ untranslated region variant. dFisher’s Exact Test P value. eOdds Ratio. f95% confidence interval for the Odds Ratio. gMinor Allele Frequency reported in 1000 Genomes Project (May 2011 release). N/A = not available.(DOC)Click here for additional data file.Table S5Candidate Variants II. Open Array Variants with an OR higher than 2 or absent in control population. In bold, selected candidates. aPosition according to the coordinate system (HG18). bVariant consequence. UTR3 = variant is located at the 3′ untranslated region. NS = non-synonymous variant. cSanger sequencing validation. dResults of segregation studies stating the number of positive individuals out of the total number available for validation in the family. eSHIFT/Polyphen predictions: D = Damaging PD = Probably damaging T = Tolerated.(DOC)Click here for additional data file.


Drosophila melanogaster. The SAA is nearly twice as costly to females as it is beneficial to males, but the harmful effects to females are recessive and X-linked, and thus are rarely expressed when SAA occurs at low frequency. We experimentally show how the evolutionary dynamics of the novel SAA are qualitatively consistent with the predictions of population genetic models: SAA frequency decreases when common, but increases when rare, converging toward an equilibrium frequency of ∼8%. Furthermore, we show that persistence of the SAA requires the mating advantage it provides to males: the SAA frequency declines towards extinction when the male advantage is experimentally abolished. Our results empirically demonstrate the dynamics underlying the evolutionary fate of a sexually antagonistic allele, validating a central assumption of intralocus sexual conflict theory: that variation in fitness-related traits within populations can be maintained via sex-linked sexually antagonistic loci.Evolutionary conflict permeates biological systems. In sexually reproducing organisms, sex-specific optima mean that the same allele can have sexually antagonistic expression, i.e. beneficial in one sex and detrimental in the other, a phenomenon known as intralocus sexual conflict. Intralocus sexual conflict is emerging as a potentially fundamental factor for the genetic architecture of fitness, with important consequences for evolutionary processes. However, no study to date has directly experimentally tested the evolutionary fate of a sexually antagonistic allele. Using genetic constructs to manipulate female fecundity and male mating success, we engineered a novel sexually antagonistic allele (SAA) in  Drosophila melanogaster, allowing us to study whether such an allele can persist in populations. We show that the sexually antagonistic allele causes more harm to females than it provides benefits to males but—as predicted by theory—it is able to persist in the population. This is because the harmful effects to females are both recessive  and linked to the X-chromosome, so females are rarely harmed when the allele is at low frequency. These results show how a sexually antagonistic allele can be maintained in populations and contribute to maintain variation in male and female reproductive success.Males and females are markedly different in many features, meaning that a trait that is beneficial for one sex may be detrimental for the other. Recent studies show that this type of sexual antagonism is abundant in natural populations; however, no study has tested the evolutionary fate of a sexually antagonistic allele. Using genetic manipulations to alter female fecundity and male mating success, we generated a novel sexually antagonistic allele in  Understanding the mechanisms that promote variation in fitness-related traits within populations presents an enduring challenge in evolutionary biology We aimed to validate predictions made by intra-locus sexually antagonistic theory by experimentally engineering a novel sexually antagonistic X-linked allele. We empirically explored a fundamental principle of intralocus sexual conflict theory: that a recessive allele that benefits the heterogametic sex but harms the homogametic sex can invade a population, even when the cost exceeds the benefit, if the locus is located on the homogametic sex-chromosome Drosophila melanogaster. We then tested: a) the magnitude of the cost to females (in terms of offspring production) and benefits to males (in terms of mating success), b) whether the allele could invade and persist in a population and how the invasion dynamics compared to predictions derived from theoretical models, and c) whether the evolutionary persistence of the allele was dependent upon the benefit provided to males.We first used genetic manipulations to generate a putative sexually antagonistic allele on the X-chromosome of D. melanogaster X chromosome, we used two genetic constructs: 1) Df(1)Exel6234, a genetic deficiency which covers the sex-peptide receptor gene and 4 other genes of unknown function 1118w, a loss of function allele for the white gene which determines eye color Df(1)Exel6234 and 1118w are located on the X-chromosome. Homozygous Df(1)Exel6234 females fail to react to the male seminal protein, sex peptide Df(1)Exel6234 females lay significantly fewer eggs after mating than wild-type females white have white eyes, and white-eyed males suffer from impaired vision and reduced mating success compared to wild-type males (which have red eyes) in photophase  white suffer no obvious reduction in adult fitness  under standard laboratory conditions Df(1)Exel6234 deficiency carries a white+ transgene white mutations . Tight linkage between the Df(1)Exel6234 deficiency and the white+ transgene ensures that recombination between them is negligible. Thus, in a 1118w background, male hemizygote and female homozygote carriers of Df(1)Exel6234 possess red eyes, whilst heterozygote females possess orange eyes Exel6234 bearing males have increased competitive mating success relative to 1118w white-eyed males in photophase, presumably due to improved vision. In direct, one-on-one, male-male competition, Df(1)Exel6234 bearing males were significantly more likely to achieve the first mating with a single virgin female in photophase  but not in scotophase . We also tested whether the SAA has an effect on male post-copulatory competitive ability. Female D. melanogaster mate multiply 1) or sperm offense (P2) abilities of SAA and control males Exel6234 females suffer significant reproductive costs compared to heterozygote and control females Exel6234 fits the conditions required for an X-linked sexually antagonistic allele: it benefits one sex but harms the other. Moreover, the costs of Df(1)Exel6234 to females are recessive: we detected no significant fecundity cost to heterozygote females (Df(1)Exel6234 as the SAA  flies and non-carriers as controls  containing a mixture of SAA and control individuals. We initiated the populations with a SAA frequency of 3% and tracked the frequency of SAA for 16 generations in P1–P4, and a further 7 generations in two of these populations that we randomly selected (P1 and P2). Populations were maintained on a 12∶12 light dark cycle, and thus for 50% of the time (during the photophase), SAA males were predicted to possess a mating advantage , together with the expected mating rates during light As predicted, average SAA frequency in P1–P4 significantly increased from the 3% starting frequency and appeared to reach a plateau at an equilibrium frequency. Initially, the frequency increased more rapidly than predicted by the model but thereafter stabilized around 8% , which bTo test the prediction that, due to the harmful effects on female fecundity, the SAA frequency should decline if the SAA is common, we set up a further 4 populations (P5–P8) with a range of higher initial SAA frequencies (31% to 85%) and measured SAA frequency over 3 subsequent generations. As expected, SAA frequency significantly declined in P5–P8. Moreover, the steepness of the decline was significantly greater in populations with higher initial frequencies , confirmDrosophila require scotophases to initiate courtship efficiently A central assumption of our hypothesis is that the SAA invades, and is maintained in the population, as a result of the mating advantage it provides males during photophase. Without this advantage, we expect a decline in the SAA and eventual extinction due to the costs imposed upon SAA females. To test this prediction we set up replicate populations of P1 and P2 at generation 16  and maintained adults in these populations in permanent dark  conditions, under which SAA males should posses no mating advantage. To control for the disruption to circadian rhythm we set up replicate control populations maintained in permanent light . We measured SAA frequency over 6 subsequent generations in the dark and light populations. As expected, within each replicate SAA frequency significantly decreased in the dark population relative to the light population  indicatiDf(1)Exel6234 deficiency that have not been characterized – on development time, ejaculate depletion rates or other traits that might impact male or female fitness – might contribute to differences between model predictions and our observed SAA frequencies. Nevertheless, our results provide robust qualitative support for sexually antagonistic evolution.Our experimental data indicate that 1) SAA frequency declines when it is common, because there is a large negative impact on the fecundity of homozygous females 2) SAA persists in populations because of the mating benefit it provides males in photophase, and SAA frequency declines towards extinction if the mating advantage of SAA males is abolished and 3) SAA has a single equilibrium frequency that is of broadly similar magnitude to that predicted by models based on intra-locus sexual conflict theory. Quantitative discrepancies between the model and our empirical data – for example, the surprisingly rapid increase in SAA frequency in the P1–4 lines – may derive from a range of factors. For example, any potential subtle effects of the Previous empirical evidence for intralocus sexual conflict derives from studies that demonstrate negative intersexual correlations for fitness, sexually antagonistic selection on phenotypes, or changes in sexually dimorphic traits under sex-limited evolution . Df(1)Exel6234whiteDahomey to generate SAA flies. Thus, all flies were in the same genetic background before experiments began. All stocks and experimental flies were maintained in plastic vials or bottles on sugar-yeast-molasses medium with ad libitum live yeast granules at 25°C on a 12∶12 hr light dark cycle (except where specified). We used a standard density method to rear flies. First instar larvae were picked from petri dishes containing an agar-grape-juice laying medium and placed in batches of 150 into plastic bottles containing 50 mL of food.The control, white-eyed D. melanogaster cannot see red light). We recorded which male mated first. To assay the post-copulatory competitive ability of SAA and control males, we conducted tests of sperm defense  and sperm offense . The competitor males and the females were homozygous for the poliertsparkling (polspa) mutation polspa homozygotes posses a distinct eye phenotype which allows for easy visual determination of paternity. All flies were 3–5 days post-eclosion at the time of first mating. To assay P1, single virgin polspa females were first mated to either a SAA or control male, and then mated to a single polspa male 24 hours after this initial mating. Females were then allowed to oviposit individually in vials for 24 hours. Offspring from these vials were assayed for paternity . The P2 assay was identical except that the matings were reversed: the first mating was conducted with polspa males, and the second mating with either a SAA or control male . To measure offspring production of females we placed 5 3-day old virgin SAA, heterozygote or control females in vials with 5 virgin SAA or control males of the same age . Flies were transferred to fresh vials every 2 or 3 days until day 10 when they were separated into pairs of 1 male and 1 female and transferred to fresh vials for 24 hrs. Eggs oviposited over the 24 hrs were counted. 14 days later the eclosed offspring were counted and scored for eye colour.We measured male mating success by introducing a single virgin wild-type female (N = 28) into a vial containing a virgin control male and a virgin SAA male of matched age. Experiments were conducted in light or in dark under red-light . Initial numbers of SAA and control males, and SAA, heterozygote and control females were, respectively, P5) 44, 56, 4, 42, 54 ; P6) 65, 35, 12, 56, 31 ; P7) 81, 19, 29, 57, 14 ; P8) 94, 6, 64, 33, 2 . These proportions were calculated based on selection at Hardy-Weinberg equilibrium using rudimentary fitness estimates  for each genotype .Flies for the 1Adult flies were placed in a 4.5 L plastic cage containing a food bottle, which was replaced every 2 or 3 days. After 8 days eggs were collected for propagation of the subsequent generation. 13 days later , offspring were counted and eye colour recorded to determine genotypes. The proportions of genotypes were calculated and the next generation of 100 males and 100 females was established for each population based on these proportions, rounded to the nearest integer. During photophase we made a total of 62 spot-check mating observations on P1–P4 – over generations 1, 3–7, 9, 11, 12 and 15 – to estimate the relative mating success of SAA and control males in the population cage environment.vs dark  varied with each generation and with the parameter values used, and was typically 2500–5400. Each run of this simulation model generated new frequencies of the SAA at each generation. We performed 100 runs of the model with each set of parameter values and then calculated at each generation the mean, standard deviation, and 95% confidence interval for SAA frequency.Data were analysed using R and JMP v9. SAA male mating advantage was calculated using chi square tests on the total number of observed SAA-male and control-male mating opportunities taken as a proportion of the total number of potential mating opportunities . P1 and P2 data for the sperm competitive ability assays could not be satisfactorily normalized and so were analyzed using Wilcoxon signed ranks tests. Analyses using parametric methods  produced qualitatively similar  results. Female fitness costs of bearing the SAA were analyzed using a generalized linear model (GLM) with Poisson error distribution on the total number of offspring resulting from each of the six combinations of parental crosses. Father (2 level factor), mother (3 level factor) and their interaction were specified as fixed effects. SAA frequency data in P1–P8 and in the light/dark lines were analyzed with generalized linear mixed-effects (GLMM) models. To account for replicate lines and for repeated measures across generations, line within generation was specified as a random effect in all GLMM models. Generation and, where appropriate, ln generation, light manipulation or initial SAA frequency were specified as fixed effects. To analyze the change in SAA frequency in P1–4 in more detail we conducted a segmented regression. We partitioned the data based on the observation that the change in SAA frequency appeared to follows 3 distinct phases of increase, decrease, and plateau. Thus, we tested for changes in SAA frequency between generations 1–6, 6–10, and 10–16.Figure S1Proportion of offspring sired by SAA and control males following post-copulatory competition (a) Paternity share of the first male to mate with a female (b) Paternity share of the second male to mate with a female.(TIF)Click here for additional data file.Table S1Number of offspring of each genotype produced when a single female , mated to either control or SAA males, was allowed to lay eggs over a 24 hr period.(DOCX)Click here for additional data file.Table S2Results from a generalized linear model with Poisson error distribution of the number of offspring produced when a single female , mated to either control or SAA males, was allowed to lay eggs over a 24 hr period.(DOCX)Click here for additional data file.


The aim of this study was to evaluate left atrial (LA) volume measurements using cardiac magnetic resonance (CMR) based angiography before and after LA radio frequency (RF) ablation therapy as a treatment strategy for atrial fibrillation (AFIB).Recent studies have demonstrated the usefulness of CMR imaging in the management of patients with cardiac arrhythmia. CMR imaging allows for more accurate measurement of various cardiac dimensions. Significant changes in LA volumes have previously been documented in patients who have undergone ablation therapy. However, these studies have relied on simple two dimensional measurement techniques and did not specify how much time post ablation the volumes were measured. More accurate three-dimensional measurement techniques and the serial follow up of LA volume have been lacking and need further investigation.53 patients (45 of whom underwent a single ablation procedure and stayed in sinus rhythm and 8 of whom went back into AFIB and had to undergo repeat ablation procedures) underwent CMR evaluation before and after ablation procedure. Contrast enhanced MR angiography (MRA) with 0.1mmol/kg of Multihance contrast agent (Bracco Diagnostics) was performed in each of these patients on a 3T MR scanner . Typical scan parameters were - axial image volume, TR/TE: 2.8/1.0ms, FOV: 400x400x110, voxel size: 1.25x1.25x2.5mm. Left atrial volumes were accurately calculated using a novel software program (Corview), which allows for segmentation and single slice analysis of individual MRA images as seen in Figure Accurate LA volumes were estimated using the Corview software program over multiple time points post ablation. It was observed that the LA volume reduced in the patients that were in sinus rhythm after the procedure and stayed the same even 6 months post ablation. However, for the patients that went back into AFIB, the LA volume increased to higher than the pre-ablation value by the time 6 months had passed since the ablation procedure, as seen in Figure CMR imaging in conjunction with newer software capabilities can more accurately measure cardiac chamber volumes. It is interesting to note that the LA volume as a function of time post ablation procedure may be used as a predictor for procedure outcome.None.