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The objective of this study was to investigate the prevalence of health related symptoms and to analyze the work activities of workers in contracted non-mechanized broiler farms in two regions of the state of Paraná in order to determine possible factors associated to those symptoms. The methods consisted in selecting the houses and the workers, and to apply a questionnaire that included demographic data, questions related to work, the Nordic Questionnaire for Musculoskeletal Symptoms, other symptoms (runny nose, skin itching, throat and eye irritation). In addition, workers were asked if they enjoyed their job, if the supervisor motivated them to work, and if they were afraid to lose their job. Activities were submitted to systematic observations, adapted from Ergonomics, and the loads carried were analyzed and some instruments weighted. The study included 80 workers of both genders between 16 and 59 years, being 40 from each region. There were evidences of low back pain risk in the activities of filling drinkers and washing bell drinkers, with a higher prevalence in region A, where automated systems were less frequently used. The study suggests that mechanized filling of feeders, and the use of nipple drinkers may prevent health problems. It was also found that psychosocial aspects were associated to musculoskeletal symptoms. Promoting better working conditions is essential, as these aspects can affect human behavior at work.

Broiler production is a significant economic activity in Brazil, and employs a large number of stockpeople in the integration process. Considering that the stockperson's perception may lead to better performance of his/her tasks and flock handling, this study aimed at verifying possible interactions between poultry productivity and stockperson's perception, emotions, and motivation. The study methodology considered two aspects: qualitative analysis, using Ergonomic Work Analysis, with observational method, and by applying a questionnaire and interview, and classification of the answers into positive relationship and "affection" to the job or negative relationship and "disaffection" to the job; and quantitative analysis, applying the Test of Hypothesis for Comparison of Means both for total flock mortality and Weight Equivalent Index data. Qualitative results showed that the stockpeople were aware that the housing environment causes specific health symptoms, as well as they presented different responses as to flock handling. Quantitative data showed a correlation between reduction of total flock mortality and positive relationship towards the broilers and "affection" to the job, whereas no statistical evidence that the same individuals influenced broiler Weight Equivalent Index was detected.

There are many situations that involve health risks to the Brazilian rural worker, and animal production is just one of them. Inhalation of organic dust, which has many microorganisms, leads in general to respiratory allergic reactions in some individuals, "asthma-like syndrome", and mucous membrane inflammation syndrome, that is a complex of nasal, eye, and throat complaints. Furthermore, workers might have farmer's hypersensitivity pneumonia, that is a respiratory health risk along the years. The objective of this study was to evaluate the potential pulmonary health risks in poultry production workers in the region of Curitiba, PR, Brazil. Interviews using a pre-elaborated questionnaire with 40 questions were made with 37 broiler production workers, which were submitted to a pulmonary function test. Results of restrictive function with lower FEV1 (the maximum respiratory potential, the forced expiratory volume in the first second of exhalation) and FVC (forced vital capacity) represented 24.32% of the total of workers, and severe obstruction represented 2.70%. Other symptoms were found in 67.57% of the workers as well. The results showed that those who work more than 4 years and within more than one poultry house, exceeding 5 hours per day of work, presented higher pulmonary health risks. It is concluded that the activities within broiler houses may induce allergic respiratory reaction in workers. The use of IPE (individual protection equipment) besides special attention to the air quality inside the housing may be advised in a preventive way.

Among the various methods, Non Thermal Plasma (NTP) has been recently introduced and is being studied to recover the damaged nerve. In the recent years, several studies have suggested that NTP accelerates nerve cell regeneration, but the mechanism remains unknown. This study evaluated the effect of NTP on neuronal proliferation in SH-SY5Y (Human neuroblastoma cells) cells differentiated by retinoic acid (RA) and investigated the mechanism by which NTP promotes cell proliferation. We analyzed the morphology of differentiated SH-SY5Y cells, and performed western blot analysis and reverse transcription polymerase chain reaction (RT-PCR). Immunofluorescence analysis was performed in an in vivo study by categorizing Wistar A rats into three groups: non-nerve damage (Non-ND), nerve damage (ND), and nerve damage + NTP treatment (ND + NTP). The cell morphology analysis revealed that the number of cells increased and axonal elongation progressed after NTP treatment. In addition, western blots indicated that tau expression increased significantly after NTP treatment. The RT-PCR results revealed that the expression of tau, wnt3a, and β-catenin increased after NTP treatment. The in vivo immunofluorescence assay showed that NTP increased the markers for tau and S100B while regulating the over-expression of MAP2 and GAP43. NTP treatment accelerated cell proliferation and regeneration of damaged neurons in differentiated SH-SY5Y cells. These results establish the fact of NTP as a noninvasive and effective treatment for nerve injury., (© 2022. The Author(s).)

We conducted a genome-wide association study (GWAS) to identify novel predisposition alleles associated with Philadelphia chromosome-negative myeloproliferative neoplasms (MPNs) and JAK2 V617F clonal hematopoiesis in the general population. We recruited a web-based cohort of 726 individuals with polycythemia vera, essential thrombocythemia, and myelofibrosis and 252 637 population controls unselected for hematologic phenotypes. Using a single-nucleotide polymorphism (SNP) array platform with custom probes for the JAK2 V617F mutation (V617F), we identified 497 individuals (0.2%) among the population controls who were V617F carriers. We performed a combined GWAS of the MPN cases plus V617F carriers in the control population (n = 1223) vs the remaining controls who were noncarriers for V617F (n = 252 140). For these MPN cases plus V617F carriers, we replicated the germ line JAK2 46/1 haplotype (rs59384377: odds ratio [OR] = 2.4, P = 6.6 × 10(-89)), previously associated with V617F-positive MPN. We also identified genome-wide significant associations in the TERT gene (rs7705526: OR = 1.8, P = 1.1 × 10(-32)), in SH2B3 (rs7310615: OR = 1.4, P = 3.1 × 10(-14)), and upstream of TET2 (rs1548483: OR = 2.0, P = 2.0 × 10(-9)). These associations were confirmed in a separate replication cohort of 446 V617F carriers vs 169 021 noncarriers. In a joint analysis of the combined GWAS and replication results, we identified additional genome-wide significant predisposition alleles associated with CHEK2, ATM, PINT, and GFI1B All SNP ORs were similar for MPN patients and controls who were V617F carriers. These data indicate that the same germ line variants endow individuals with a predisposition not only to MPN, but also to JAK2 V617F clonal hematopoiesis, a more common phenomenon that may foreshadow the development of an overt neoplasm., (© 2016 by The American Society of Hematology.)

Roughly one in three individuals is highly susceptible to motion sickness and yet the underlying causes of this condition are not well understood. Despite high heritability, no associated genetic factors have been discovered. Here, we conducted the first genome-wide association study on motion sickness in 80 494 individuals from the 23andMe database who were surveyed about car sickness. Thirty-five single-nucleotide polymorphisms (SNPs) were associated with motion sickness at a genome-wide-significant level (P < 5 × 10(-8)). Many of these SNPs are near genes involved in balance, and eye, ear and cranial development (e.g. PVRL3, TSHZ1, MUTED, HOXB3, HOXD3). Other SNPs may affect motion sickness through nearby genes with roles in the nervous system, glucose homeostasis or hypoxia. We show that several of these SNPs display sex-specific effects, with up to three times stronger effects in women. We searched for comorbid phenotypes with motion sickness, confirming associations with known comorbidities including migraines, postoperative nausea and vomiting (PONV), vertigo and morning sickness and observing new associations with altitude sickness and many gastrointestinal conditions. We also show that two of these related phenotypes (PONV and migraines) share underlying genetic factors with motion sickness. These results point to the importance of the nervous system in motion sickness and suggest a role for glucose levels in motion-induced nausea and vomiting, a finding that may provide insight into other nausea-related phenotypes like PONV. They also highlight personal characteristics (e.g. being a poor sleeper) that correlate with motion sickness, findings that could help identify risk factors or treatments., (© The Author 2015. Published by Oxford University Press.)

We conducted a meta-analysis of Parkinson's disease genome-wide association studies using a common set of 7,893,274 variants across 13,708 cases and 95,282 controls. Twenty-six loci were identified as having genome-wide significant association; these and 6 additional previously reported loci were then tested in an independent set of 5,353 cases and 5,551 controls. Of the 32 tested SNPs, 24 replicated, including 6 newly identified loci. Conditional analyses within loci showed that four loci, including GBA, GAK-DGKQ, SNCA and the HLA region, contain a secondary independent risk variant. In total, we identified and replicated 28 independent risk variants for Parkinson's disease across 24 loci. Although the effect of each individual locus was small, risk profile analysis showed substantial cumulative risk in a comparison of the highest and lowest quintiles of genetic risk (odds ratio (OR) = 3.31, 95% confidence interval (CI) = 2.55-4.30; P = 2 × 10(-16)). We also show six risk loci associated with proximal gene expression or DNA methylation.

Allergic disease is very common and carries substantial public-health burdens. We conducted a meta-analysis of genome-wide associations with self-reported cat, dust-mite and pollen allergies in 53,862 individuals. We used generalized estimating equations to model shared and allergy-specific genetic effects. We identified 16 shared susceptibility loci with association P<5×10(-8), including 8 loci previously associated with asthma, as well as 4p14 near TLR1, TLR6 and TLR10 (rs2101521, P=5.3×10(-21)); 6p21.33 near HLA-C and MICA (rs9266772, P=3.2×10(-12)); 5p13.1 near PTGER4 (rs7720838, P=8.2×10(-11)); 2q33.1 in PLCL1 (rs10497813, P=6.1×10(-10)), 3q28 in LPP (rs9860547, P=1.2×10(-9)); 20q13.2 in NFATC2 (rs6021270, P=6.9×10(-9)), 4q27 in ADAD1 (rs17388568, P=3.9×10(-8)); and 14q21.1 near FOXA1 and TTC6 (rs1998359, P=4.8×10(-8)). We identified one locus with substantial evidence of differences in effects across allergies at 6p21.32 in the class II human leukocyte antigen (HLA) region (rs17533090, P=1.7×10(-12)), which was strongly associated with cat allergy. Our study sheds new light on the shared etiology of immune and autoimmune disease.

Motivation: Advances in high-resolution microscopy have recently made possible the analysis of gene expression at the level of individual cells. The fixed lineage of cells in the adult worm Caenorhabditis elegans makes this organism an ideal model for studying complex biological processes like development and aging. However, annotating individual cells in images of adult C.elegans typically requires expertise and significant manual effort. Automation of this task is therefore critical to enabling high-resolution studies of a large number of genes., Results: In this article, we describe an automated method for annotating a subset of 154 cells (including various muscle, intestinal and hypodermal cells) in high-resolution images of adult C.elegans. We formulate the task of labeling cells within an image as a combinatorial optimization problem, where the goal is to minimize a scoring function that compares cells in a test input image with cells from a training atlas of manually annotated worms according to various spatial and morphological characteristics. We propose an approach for solving this problem based on reduction to minimum-cost maximum-flow and apply a cross-entropy-based learning algorithm to tune the weights of our scoring function. We achieve 84% median accuracy across a set of 154 cell labels in this highly variable system. These results demonstrate the feasibility of the automatic annotation of microscopy-based images in adult C.elegans.

Myopia, or nearsightedness, is the most common eye disorder, resulting primarily from excess elongation of the eye. The etiology of myopia, although known to be complex, is poorly understood. Here we report the largest ever genome-wide association study (45,771 participants) on myopia in Europeans. We performed a survival analysis on age of myopia onset and identified 22 significant associations ([Formula: see text]), two of which are replications of earlier associations with refractive error. Ten of the 20 novel associations identified replicate in a separate cohort of 8,323 participants who reported if they had developed myopia before age 10. These 22 associations in total explain 2.9% of the variance in myopia age of onset and point toward a number of different mechanisms behind the development of myopia. One association is in the gene PRSS56, which has previously been linked to abnormally small eyes; one is in a gene that forms part of the extracellular matrix (LAMA2); two are in or near genes involved in the regeneration of 11-cis-retinal (RGR and RDH5); two are near genes known to be involved in the growth and guidance of retinal ganglion cells (ZIC2, SFRP1); and five are in or near genes involved in neuronal signaling or development. These novel findings point toward multiple genetic factors involved in the development of myopia and suggest that complex interactions between extracellular matrix remodeling, neuronal development, and visual signals from the retina may underlie the development of myopia in humans., Competing Interests: The authors are or have been employed by 23andMe and own stock options in the company.

Background: While some factors of breast morphology, such as density, are directly implicated in breast cancer, the relationship between breast size and cancer is less clear. Breast size is moderately heritable, yet the genetic variants leading to differences in breast size have not been identified., Methods: To investigate the genetic factors underlying breast size, we conducted a genome-wide association study (GWAS) of self-reported bra cup size, controlling for age, genetic ancestry, breast surgeries, pregnancy history and bra band size, in a cohort of 16,175 women of European ancestry., Results: We identified seven single-nucleotide polymorphisms (SNPs) significantly associated with breast size (p<5.10(-8)): rs7816345 near ZNF703, rs4849887 and (independently) rs17625845 flanking INHBB, rs12173570 near ESR1, rs7089814 in ZNF365, rs12371778 near PTHLH, and rs62314947 near AREG. Two of these seven SNPs are in linkage disequilibrium (LD) with SNPs associated with breast cancer (those near ESR1 and PTHLH), and a third (ZNF365) is near, but not in LD with, a breast cancer SNP. The other three loci (ZNF703, INHBB, and AREG) have strong links to breast cancer, estrogen regulation, and breast development., Conclusions: These results provide insight into the genetic factors underlying normal breast development and show that some of these factors are shared with breast cancer. While these results do not directly support any possible epidemiological relationships between breast size and cancer, this study may contribute to a better understanding of the subtle interactions between breast morphology and breast cancer risk.

Hypothyroidism is the most common thyroid disorder, affecting about 5% of the general population. Here we present the current largest genome-wide association study of hypothyroidism, in 3,736 cases and 35,546 controls. Hypothyroidism was assessed via web-based questionnaires. We identify five genome-wide significant associations, three of which are well known to be involved in a large spectrum of autoimmune diseases: rs6679677 near PTPN22, rs3184504 in SH2B3, and rs2517532 in the HLA class I region (p-values 2.8·10(-13), 2.6·10(-12), and 1.3·10(-8), respectively). We also report associations with rs4915077 near VAV3 (p-value 7.5·10(-10)) and rs925489 near FOXE1 (p value 2.4·10(-19)). VAV3 is involved in immune function, and FOXE1 and PTPN22 have previously been associated with hypothyroidism. Although the HLA class I region and SH2B3 have previously been linked with a number of autoimmune diseases, this is the first report of their association with thyroid disease. The VAV3 association is also novel. We also show suggestive evidence of association for hypothyroidism with a SNP in the HLA class II region (independent of the other HLA association) as well as SNPs in CAPZB, PDE8B, and CTLA4. CAPZB and PDE8B have been linked to TSH levels and CTLA4 to a variety of autoimmune diseases. These results suggest heterogeneity in the genetic etiology of hypothyroidism, implicating genes involved in both autoimmune disorders and thyroid function. Using a genetic risk profile score based on the top association from each of the five genome-wide significant regions in our study, the relative risk between the highest and lowest deciles of genetic risk is 2.0.

The clinical utility of family history and genetic tests is generally well understood for simple Mendelian disorders and rare subforms of complex diseases that are directly attributable to highly penetrant genetic variants. However, little is presently known regarding the performance of these methods in situations where disease susceptibility depends on the cumulative contribution of multiple genetic factors of moderate or low penetrance. Using quantitative genetic theory, we develop a model for studying the predictive ability of family history and single nucleotide polymorphism (SNP)-based methods for assessing risk of polygenic disorders. We show that family history is most useful for highly common, heritable conditions (e.g., coronary artery disease), where it explains roughly 20%-30% of disease heritability, on par with the most successful SNP models based on associations discovered to date. In contrast, we find that for diseases of moderate or low frequency (e.g., Crohn disease) family history accounts for less than 4% of disease heritability, substantially lagging behind SNPs in almost all cases. These results indicate that, for a broad range of diseases, already identified SNP associations may be better predictors of risk than their family history-based counterparts, despite the large fraction of missing heritability that remains to be explained. Our model illustrates the difficulty of using either family history or SNPs for standalone disease prediction. On the other hand, we show that, unlike family history, SNP-based tests can reveal extreme likelihood ratios for a relatively large percentage of individuals, thus providing potentially valuable adjunctive evidence in a differential diagnosis., Competing Interests: CBD, DAH, UF, and NE are employed by 23andMe and own either stock or stock options in the company. PLOS co-founder Michael B. Eisen is a member of the 23andMe Scientific Advisory Board and also holds stock options in the company.

More than 800 published genetic association studies have implicated dozens of potential risk loci in Parkinson's disease (PD). To facilitate the interpretation of these findings, we have created a dedicated online resource, PDGene, that comprehensively collects and meta-analyzes all published studies in the field. A systematic literature screen of -27,000 articles yielded 828 eligible articles from which relevant data were extracted. In addition, individual-level data from three publicly available genome-wide association studies (GWAS) were obtained and subjected to genotype imputation and analysis. Overall, we performed meta-analyses on more than seven million polymorphisms originating either from GWAS datasets and/or from smaller scale PD association studies. Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls. Eleven loci showed genome-wide significant (P < 5 × 10(-8)) association with disease risk: BST1, CCDC62/HIP1R, DGKQ/GAK, GBA, LRRK2, MAPT, MCCC1/LAMP3, PARK16, SNCA, STK39, and SYT11/RAB25. In addition, we identified novel evidence for genome-wide significant association with a polymorphism in ITGA8 (rs7077361, OR 0.88, P  =  1.3 × 10(-8)). All meta-analysis results are freely available on a dedicated online database (www.pdgene.org), which is cross-linked with a customized track on the UCSC Genome Browser. Our study provides an exhaustive and up-to-date summary of the status of PD genetics research that can be readily scaled to include the results of future large-scale genetics projects, including next-generation sequencing studies., Competing Interests: CB Do, N Eriksson, and JY Tung are employed by 23andMe and own stock options in the company. MJ Farrer and Mayo Foundation received royalties from H.Lundbeck A/S and Isis Pharmaceuticals. In addition, MJ Farrer has received an honorarium for a seminar at Genzyme. T Gasser has received consultancy fees from Cephalon and Merck-Serono, grants from Novartis, payments for lectures including service on speakers' bureaus from Boehringer Ingelheim, Merck-Serono, UCB, and Valean, and holds patents NGFN2 and KASPP. JA Hardy has received consulting fees or honoraria from Eisai and his institute has received consulting fees or honoraria from Merck-Serono. DM Maraganore has received extramural research funding support from the National Institutes of Health (2R01 ES10751), the Michael J. Fox Foundation (Linked Efforts to Accelerate Parkinson Solutions Award, Edmond J. Safra Global Genetics Consortia Award), and from Alnylam Pharmaceuticals and Medtronic (observational studies of Parkinson's disease). DM Maraganore has also received intramural research funding support from the Mayo Clinic and from NorthShore University Health System. DM Maraganore filed a provisional patent for a method to predict Parkinson's disease. This provisional patent is unlicensed. He also filed a provisional patent for a method to treat neurodegenerative disorders. That provisional patent has been licensed to Alnylam Pharmaceuticals and DM Maraganore has received royalty payments in total of less than $20,000. K Stefansson has received grants from deCODE.

Although the causes of Parkinson's disease (PD) are thought to be primarily environmental, recent studies suggest that a number of genes influence susceptibility. Using targeted case recruitment and online survey instruments, we conducted the largest case-control genome-wide association study (GWAS) of PD based on a single collection of individuals to date (3,426 cases and 29,624 controls). We discovered two novel, genome-wide significant associations with PD-rs6812193 near SCARB2 (p = 7.6 × 10(-10), OR = 0.84) and rs11868035 near SREBF1/RAI1 (p = 5.6 × 10(-8), OR = 0.85)-both replicated in an independent cohort. We also replicated 20 previously discovered genetic associations (including LRRK2, GBA, SNCA, MAPT, GAK, and the HLA region), providing support for our novel study design. Relying on a recently proposed method based on genome-wide sharing estimates between distantly related individuals, we estimated the heritability of PD to be at least 0.27. Finally, using sparse regression techniques, we constructed predictive models that account for 6%-7% of the total variance in liability and that suggest the presence of true associations just beyond genome-wide significance, as confirmed through both internal and external cross-validation. These results indicate a substantial, but by no means total, contribution of genetics underlying susceptibility to both early-onset and late-onset PD, suggesting that, despite the novel associations discovered here and elsewhere, the majority of the genetic component for Parkinson's disease remains to be discovered., Competing Interests: CBD, JYT, ED, AKK, EMD, UF, JLM, AW, and NE are or have been employed by 23andMe and own stock options in the company. 23andMe CEO AW has provided general guidance, including guidance related to the company's research undertakings and direction. PLoS co-founder Michael B. Eisen is a member of the 23andMe Scientific Advisory Board.

While the cost and speed of generating genomic data have come down dramatically in recent years, the slow pace of collecting medical data for large cohorts continues to hamper genetic research. Here we evaluate a novel online framework for obtaining large amounts of medical information from a recontactable cohort by assessing our ability to replicate genetic associations using these data. Using web-based questionnaires, we gathered self-reported data on 50 medical phenotypes from a generally unselected cohort of over 20,000 genotyped individuals. Of a list of genetic associations curated by NHGRI, we successfully replicated about 75% of the associations that we expected to (based on the number of cases in our cohort and reported odds ratios, and excluding a set of associations with contradictory published evidence). Altogether we replicated over 180 previously reported associations, including many for type 2 diabetes, prostate cancer, cholesterol levels, and multiple sclerosis. We found significant variation across categories of conditions in the percentage of expected associations that we were able to replicate, which may reflect systematic inflation of the effects in some initial reports, or differences across diseases in the likelihood of misdiagnosis or misreport. We also demonstrated that we could improve replication success by taking advantage of our recontactable cohort, offering more in-depth questions to refine self-reported diagnoses. Our data suggest that online collection of self-reported data from a recontactable cohort may be a viable method for both broad and deep phenotyping in large populations.

We developed Graemlin 2.0, a new multiple network aligner with (1) a new multi-stage approach to local network alignment; (2) a novel scoring function that can use arbitrary features of a multiple network alignment, such as protein deletions, protein duplications, protein mutations, and interaction losses; (3) a parameter learning algorithm that uses a training set of known network alignments to learn parameters for our scoring function and thereby adapt it to any set of networks; and (4) an algorithm that uses our scoring function to find approximate multiple network alignments in linear time. We tested Graemlin 2.0's accuracy on protein interaction networks from IntAct, DIP, and the Stanford Network Database. We show that, on each of these datasets, Graemlin 2.0 has higher sensitivity and specificity than existing network aligners. Graemlin 2.0 is available under the GNU public license at http://graemlin.stanford.edu .

Motivation: Genome-wide association studies are commonly used to identify possible associations between genetic variations and diseases. These studies mainly focus on identifying individual single nucleotide polymorphisms (SNPs) potentially linked with one disease of interest. In this work, we introduce a novel methodology that identifies similarities between diseases using information from a large number of SNPs. We separate the diseases for which we have individual genotype data into one reference disease and several query diseases. We train a classifier that distinguishes between individuals that have the reference disease and a set of control individuals. This classifier is then used to classify the individuals that have the query diseases. We can then rank query diseases according to the average classification of the individuals in each disease set, and identify which of the query diseases are more similar to the reference disease. We repeat these classification and comparison steps so that each disease is used once as reference disease., Results: We apply this approach using a decision tree classifier to the genotype data of seven common diseases and two shared control sets provided by the Wellcome Trust Case Control Consortium. We show that this approach identifies the known genetic similarity between type 1 diabetes and rheumatoid arthritis, and identifies a new putative similarity between bipolar disease and hypertension.

Motivation: The need for accurate and efficient tools for computational RNA structure analysis has become increasingly apparent over the last several years: RNA folding algorithms underlie numerous applications in bioinformatics, ranging from microarray probe selection to de novo non-coding RNA gene prediction. In this work, we present RAF (RNA Alignment and Folding), an efficient algorithm for simultaneous alignment and consensus folding of unaligned RNA sequences. Algorithmically, RAF exploits sparsity in the set of likely pairing and alignment candidates for each nucleotide (as identified by the CONTRAfold or CONTRAlign programs) to achieve an effectively quadratic running time for simultaneous pairwise alignment and folding. RAF's fast sparse dynamic programming, in turn, serves as the inference engine within a discriminative machine learning algorithm for parameter estimation., Results: In cross-validated benchmark tests, RAF achieves accuracies equaling or surpassing the current best approaches for RNA multiple sequence secondary structure prediction. However, RAF requires nearly an order of magnitude less time than other simultaneous folding and alignment methods, thus making it especially appropriate for high-throughput studies., Availability: Source code for RAF is available at:http://contra.stanford.edu/contrafold/.

The genome of an admixed individual with ancestors from isolated populations is a mosaic of chromosomal blocks, each following the statistical properties of variation seen in those populations. By analyzing polymorphisms in the admixed individual against those seen in representatives from the populations, we can infer the ancestral source of the individual's haploblocks. In this paper we describe a novel approach for ancestry inference, HAPAA (HMM-based analysis of polymorphisms in admixed ancestries), that models the allelic and haplotypic variation in the populations and captures the signal of correlation due to linkage disequilibrium, resulting in greatly improved accuracy. We also introduce a methodology for evaluating the effect of genetic divergence between ancestral populations and time-to-admixture on inference accuracy. Using HAPAA, we explore the limits of ancestry inference in closely related populations.

Protein sequence alignment is the task of identifying evolutionarily or structurally related positions in a collection of amino acid sequences. Although the protein alignment problem has been studied for several decades, many recent studies have demonstrated considerable progress in improving the accuracy or scalability of multiple and pairwise alignment tools, or in expanding the scope of tasks handled by an alignment program. In this chapter, we review state-of-the-art protein sequence alignment and provide practical advice for users of alignment tools.

Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.

We describe CONTRAST, a gene predictor which directly incorporates information from multiple alignments rather than employing phylogenetic models. This is accomplished through the use of discriminative machine learning techniques, including a novel training algorithm. We use a two-stage approach, in which a set of binary classifiers designed to recognize coding region boundaries is combined with a global model of gene structure. CONTRAST predicts exact coding region structures for 65% more human genes than the previous state-of-the-art method, misses 46% fewer exons and displays comparable gains in specificity.

Motivation: For several decades, free energy minimization methods have been the dominant strategy for single sequence RNA secondary structure prediction. More recently, stochastic context-free grammars (SCFGs) have emerged as an alternative probabilistic methodology for modeling RNA structure. Unlike physics-based methods, which rely on thousands of experimentally-measured thermodynamic parameters, SCFGs use fully-automated statistical learning algorithms to derive model parameters. Despite this advantage, however, probabilistic methods have not replaced free energy minimization methods as the tool of choice for secondary structure prediction, as the accuracies of the best current SCFGs have yet to match those of the best physics-based models., Results: In this paper, we present CONTRAfold, a novel secondary structure prediction method based on conditional log-linear models (CLLMs), a flexible class of probabilistic models which generalize upon SCFGs by using discriminative training and feature-rich scoring. In a series of cross-validation experiments, we show that grammar-based secondary structure prediction methods formulated as CLLMs consistently outperform their SCFG analogs. Furthermore, CONTRAfold, a CLLM incorporating most of the features found in typical thermodynamic models, achieves the highest single sequence prediction accuracies to date, outperforming currently available probabilistic and physics-based techniques. Our result thus closes the gap between probabilistic and thermodynamic models, demonstrating that statistical learning procedures provide an effective alternative to empirical measurement of thermodynamic parameters for RNA secondary structure prediction., Availability: Source code for CONTRAfold is available at http://contra.stanford.edu/contrafold/.

Multiple sequence alignments are the usual starting point for analyses of protein structure and evolution. For proteins with repeated, shuffled and missing domains, however, traditional multiple sequence alignment algorithms fail to provide an accurate view of homology between related proteins, because they either assume that the input sequences are globally alignable or require locally alignable regions to appear in the same order in all sequences. In this paper, we present ProDA, a novel system for automated detection and alignment of homologous regions in collections of proteins with arbitrary domain architectures. Given an input set of unaligned sequences, ProDA identifies all homologous regions appearing in one or more sequences, and returns a collection of local multiple alignments for these regions. On a subset of the BAliBASE benchmarking suite containing curated alignments of proteins with complicated domain architectures, ProDA performs well in detecting conserved domain boundaries and clustering domain segments, achieving the highest accuracy to date for this task. We conclude that ProDA is a practical tool for automated alignment of protein sequences with repeats and rearrangements in their domain architecture.

To study gene evolution across a wide range of organisms, biologists need accurate tools for multiple sequence alignment of protein families. Obtaining accurate alignments, however, is a difficult computational problem because of not only the high computational cost but also the lack of proper objective functions for measuring alignment quality. In this paper, we introduce probabilistic consistency, a novel scoring function for multiple sequence comparisons. We present ProbCons, a practical tool for progressive protein multiple sequence alignment based on probabilistic consistency, and evaluate its performance on several standard alignment benchmark data sets. On the BAliBASE, SABmark, and PREFAB benchmark alignment databases, ProbCons achieves statistically significant improvement over other leading methods while maintaining practical speed. ProbCons is publicly available as a Web resource.

To compare entire genomes from different species, biologists increasingly need alignment methods that are efficient enough to handle long sequences, and accurate enough to correctly align the conserved biological features between distant species. We present LAGAN, a system for rapid global alignment of two homologous genomic sequences, and Multi-LAGAN, a system for multiple global alignment of genomic sequences. We tested our systems on a data set consisting of greater than 12 Mb of high-quality sequence from 12 vertebrate species. All the sequence was derived from the genomic region orthologous to an approximately 1.5-Mb region on human chromosome 7q31.3. We found that both LAGAN and Multi-LAGAN compare favorably with other leading alignment methods in correctly aligning protein-coding exons, especially between distant homologs such as human and chicken, or human and fugu. Multi-LAGAN produced the most accurate alignments, while requiring just 75 minutes on a personal computer to obtain the multiple alignment of all 12 sequences. Multi-LAGAN is a practical method for generating multiple alignments of long genomic sequences at any evolutionary distance. Our systems are publicly available at http://lagan.stanford.edu.

Motivation: To compare entire genomes from different species, biologists increasingly need alignment methods that are efficient enough to handle long sequences, and accurate enough to correctly align the conserved biological features between distant species. The two main classes of pairwise alignments are global alignment, where one string is transformed into the other, and local alignment, where all locations of similarity between the two strings are returned. Global alignments are less prone to demonstrating false homology as each letter of one sequence is constrained to being aligned to only one letter of the other. Local alignments, on the other hand, can cope with rearrangements between non-syntenic, orthologous sequences by identifying similar regions in sequences; this, however, comes at the expense of a higher false positive rate due to the inability of local aligners to take into account overall conservation maps., Results: In this paper we introduce the notion of glocal alignment, a combination of global and local methods, where one creates a map that transforms one sequence into the other while allowing for rearrangement events. We present Shuffle-LAGAN, a glocal alignment algorithm that is based on the CHAOS local alignment algorithm and the LAGAN global aligner, and is able to align long genomic sequences. To test Shuffle-LAGAN we split the mouse genome into BAC-sized pieces, and aligned these pieces to the human genome. We demonstrate that Shuffle-LAGAN compares favorably in terms of sensitivity and specificity with standard local and global aligners. From the alignments we conclude that about 9% of human/mouse homology may be attributed to small rearrangements, 63% of which are duplications.

A cell suspension of grape, Vitis vinifera L. cv Gamay Fréaux, was grown under different conditions of water stress (high external osmotic potential) induced by an increase of sucrose concentration or by the addition of mannitol to the culture medium. Best growth (cell density) was achieved in the low osmotic potential medium. Increasing the osmotic potential of the medium from -0.5 MPa to -0.9 MPa medium resulted in a significant increase in accumulation of anthocyanins in pigmented cells. Regulation of the osmotic potential of culture medium may be useful in controlling anthocyanin production.