bluuebunny/crossref_metadata_2025_split huggingface dataset:
Resolving Adaptive and Demographic Divergence among Chinook Salmon Populations in the Columbia River Basin
Authors: Matala Andrew P. , Hess Jon E. , Narum Shawn R. 
Published: June 2011

AbstractChinook salmon Oncorhynchus tshawytscha in the Columbia River basin (CRB) comprise three lineages—lower Columbia River and sympatric interior ocean and stream types—each with distinct biological attributes. To evaluate the adaptive and neutral genetic variation of this species in the CRB, we genotyped 54 Chinook salmon populations using a panel of 96 single‐nucleotide polymorphism (SNP) loci. All three lineages were represented among the collections and were widely distributed across locations, ranging from the upper Salmon River to near the Columbia River estuary. Our goal was to explore local adaptation as a process shaping the population structure and genetic variation among Chinook salmon beyond the inferences possible with neutral marker data. In our analyses with putatively neutral SNPs, the population structure of Chinook salmon throughout the CRB was generally concordant with that of previous studies using microsatellites. Regression analyses and outlier methods identified 28, 17, and 29 candidate SNP loci for positive selection among stream‐type, ocean‐type, and lower‐river Chinook salmon, respectively. The candidate SNP markers were tested for association with seven environmental variables using multiple methods. We identified unambiguous markers, including nine candidates in the stream‐type lineage and seven in the ocean‐type lineage that were significantly correlated with elevation and/or temperature. The association of six candidates markers in the lower‐river lineage could not be confirmed by population structure analyses and remained ambiguous. We observed a significant association of isolation by distance for the ocean‐ and stream‐type lineages with our SNP panel; however, there was also a significant relationship between pairwise FST and several habitat variables. In all cases, the apparent adaptive variation complemented the results of demographic genetic structure but with higher resolution of population differentiation.
A Microsatellite Genome Screen Identifies Chromosomal Regions under Differential Selection in Steelhead and Rainbow Trout
Authors: Martínez Andrés , Garza John Carlos , Pearse Devon E. 
Published: June 2011

AbstractNovel genetic resources now make it possible to directly assess the effects of natural selection on specific regions of the salmonid genome. Natural selection on specific genetic loci will also affect the variation in linked flanking regions through “hitchhiking” effects, causing greater differentiation between populations than would be expected from purely neutral processes. Here we identify candidate genomic regions for the effects of differential natural selection in two closely related populations of steelhead–rainbow trout Oncorhynchus mykiss separated for the last century following anthropogenic introduction above a barrier waterfall in a coastal California stream. A set of 110 expressed sequence tag (EST)‐linked and 188 anonymous microsatellite loci, most of which are mapped, were chosen to provide distributed coverage of all linkage groups in the O. mykiss genome. A genome screen was then performed to identify genomic regions under divergent selection. Multiple complementary statistical methods were used to detect outlier loci, and loci identified by more than one method were considered strong candidates for genomic regions affected by recent natural selection and genomic adaptation to the environment above the waterfall. We identified six strongly supported outlier loci, including one linked to an EST and two located in a genomic region that contains quantitative trait loci associated with egg development, spawning time, and other life history variation. Identification of regions in the genome that are potentially under selection provides valuable information about the genetic basis of selection in novel habitats and the genetic architecture of salmonid life history variation.
Relative Genetic Diversity Estimates among Four Pacific Salmonids
Authors: Campbell Nathan R. , Narum Shawn R. 
Published: June 2011

AbstractThe genetic diversity within a species is a reflection of its evolutionary past and ongoing mutation, drift, and adaptation. Species that occupy a diverse range of habitats and that have adapted for generations under selective pressures will carry a genetic imprint of that adaptation within specific functional genes. Alternatively, genetic diversity may be reduced owing to historical bottlenecks and genetic drift. In this study, genetic diversity was estimated in four species of Pacific salmon (rainbow trout, steelhead [anadromous rainbow trout] Oncorhynchus mykiss, Chinook salmon O. tshawytscha, coho salmon O. kisutch, and sockeye salmon, kokanee [lacustrine sockeye salmon] O. nerka) using 563–608 kilo–base pairs of DNA sequence data from 32 individuals per species. Individual samples were chosen to represent the major lineages of each species across their natural ranges. The results show the highest genetic diversity estimates for rainbow trout and the lowest for sockeye salmon. Statistically significant differences were observed between the species with the highest genetic diversity (rainbow trout) and the three remaining species. Loci with the highest genetic diversity within each species are listed as potentially being influenced by balancing selection.
Candidate Genetic Markers Associated with Anadromy in Oncorhynchus mykiss of the Klickitat River
Authors: Narum Shawn R. , Zendt Joseph S. , Frederiksen Chris , Campbell Nate , Matala Andrew , Sharp William R. 
Published: June 2011

AbstractBoth environmental and genetic factors influence anadromy in rainbow trout Oncorhynchus mykiss, but the genetic mechanisms that contribute to migratory selection are not well understood. In this study, we used a limited genome scan approach to identify candidate genetic markers associated with anadromy in 10 populations of O. mykiss from the Klickitat River, Washington. From an initial panel of 96 single‐nucleotide polymorphism (SNP) markers, we identified 3 SNPs that were significantly associated with anadromy after accounting for underlying population structure and selective environmental conditions. Univariate logistic regression of allele frequencies and residency/anadromy were also significant, and thus three SNPs were considered candidate markers associated with anadromy (Omy_IL6–320, Omy_LDHB‐2_i6, and Omy_ndk‐152). A multivariate logistic model was developed from the allele frequencies of these three markers to predict the potential for anadromy in natural populations. This model was applied to eight additional populations of O. mykiss to evaluate its utility. The results of this study indicate that these markers are strong candidates for association with anadromy in O. mykiss in the Klickitat River, but further testing is needed to evaluate this association across more of this species’ range. Common‐garden experiments may also help clarify the association of these candidate markers with the smoltification phenotypes of individual fish.
Immune system simulation online
Authors: Rapin Nicolas , Lund Ole , Castiglione Filippo 
Published: June 2011

Abstract
Motivation: The recognition of antigenic peptides is a major event of an immune response. In current mesoscopic-scale simulators of the immune system, this crucial step has been modeled in a very approximated way.
Results: We have equipped an agent-based model of the immune system with immuno-informatics methods to allow the simulation of the cardinal events of the antigenic recognition, going from single peptides to whole proteomes.
The recognition process accounts for B cell-epitopes prediction through Parker-scale affinity estimation, class I and II HLA peptide prediction and binding through position-specific scoring matrices based on information from known HLA epitopes prediction tools, and TCR binding to HLA–peptide complex calculated as the averaged sum of a residue–residue contact potential.
These steps are executed for all lymphocytes agents encountering the antigen in a wide-reaching Monte Carlo simulation.
Availability: http://www.cbs.dtu.dk/services/C-ImmSim-10.1/
Contact: f.castiglione@iac.cnr.it
A tree-based approach for motif discovery and sequence classification
Authors: Yan Rui , Boutros Paul C. , Jurisica Igor 
Published: June 2011

AbstractMotivation: Pattern discovery algorithms are widely used for the analysis of DNA and protein sequences. Most algorithms have been designed to find overrepresented motifs in sparse datasets of long sequences, and ignore most positional information. We introduce an algorithm optimized to exploit spatial information in sparse-but-populous datasets.Results: Our algorithm Tree-based Weighted-Position Pattern Discovery and Classification (T-WPPDC) supports both unsupervised pattern discovery and supervised sequence classification. It identifies positionally enriched patterns using the Kullback–Leibler distance between foreground and background sequences at each position. This spatial information is used to discover positionally important patterns. T-WPPDC then uses a scoring function to discriminate different biological classes. We validated T-WPPDC on an important biological problem: prediction of single nucleotide polymorphisms (SNPs) from flanking sequence. We evaluated 672 separate experiments on 120 datasets derived from multiple species. T-WPPDC outperformed other pattern discovery methods and was comparable to the supervised machine learning algorithms. The algorithm is computationally efficient and largely insensitive to dataset size. It allows arbitrary parameterization and is embarrassingly parallelizable.Conclusions: T-WPPDC is a minimally parameterized algorithm for both pattern discovery and sequence classification that directly incorporates positional information. We use it to confirm the predictability of SNPs from flanking sequence, and show that positional information is a key to this biological problem.Contacts: ruiyan@cs.toronto.edu; paul.boutros@oicr.on.ca; juris@ai.toronto.eduAvailability: The algorithm, code and data are available at: http://www.cs.utoronto.ca/~juris/data/TWPPDCSupplementary information: Supplementary data are available at Bioinformatics online.
CHASM and SNVBox: toolkit for detecting biologically important single nucleotide mutations in cancer
Authors: Wong Wing Chung , Kim Dewey , Carter Hannah , Diekhans Mark , Ryan Michael C. , Karchin Rachel 
Published: June 2011

Abstract
Summary: Thousands of cancer exomes are currently being sequenced, yielding millions of non-synonymous single nucleotide variants (SNVs) of possible relevance to disease etiology. Here, we provide a software toolkit to prioritize SNVs based on their predicted contribution to tumorigenesis. It includes a database of precomputed, predictive features covering all positions in the annotated human exome and can be used either stand-alone or as part of a larger variant discovery pipeline.
Availability and Implementation: MySQL database, source code and binaries freely available for academic/government use at http://wiki.chasmsoftware.org, Source in Python and C++. Requires 32 or 64-bit Linux system (tested on Fedora Core 8,10,11 and Ubuntu 10), 2.5*≤ Python &lt;3.0*, MySQL server &gt;5.0, 60 GB available hard disk space (50 MB for software and data files, 40 GB for MySQL database dump when uncompressed), 2 GB of RAM.
Contact: karchin@jhu.edu
Supplementary Information: Supplementary data are available at Bioinformatics online.
Noise reduction in genome-wide perturbation screens using linear mixed-effect models
Authors: Yu Danni , Danku John , Baxter Ivan , Kim Sungjin , Vatamaniuk Olena K. , Salt David E. , Vitek Olga 
Published: June 2011

Abstract
Motivation: High-throughput perturbation screens measure the phenotypes of thousands of biological samples under various conditions. The phenotypes measured in the screens are subject to substantial biological and technical variation. At the same time, in order to enable high throughput, it is often impossible to include a large number of replicates, and to randomize their order throughout the screens. Distinguishing true changes in the phenotype from stochastic variation in such experimental designs is extremely challenging, and requires adequate statistical methodology.
Results: We propose a statistical modeling framework that is based on experimental designs with at least two controls profiled throughout the experiment, and a normalization and variance estimation procedure with linear mixed-effects models. We evaluate the framework using three comprehensive screens of Saccharomyces cerevisiae, which involve 4940 single-gene knock-out haploid mutants, 1127 single-gene knock-out diploid mutants and 5798 single-gene overexpression haploid strains. We show that the proposed approach (i) can be used in conjunction with practical experimental designs; (ii) allows extensions to alternative experimental workflows; (iii) enables a sensitive discovery of biologically meaningful changes; and (iv) strongly outperforms the existing noise reduction procedures.
Availability: All experimental datasets are publicly available at www.ionomicshub.org. The R package HTSmix is available at http://www.stat.purdue.edu/~ovitek/HTSmix.html.
Contact: ovitek@stat.purdue.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
KvSNP: accurately predicting the effect of genetic variants in voltage-gated potassium channels
Authors: Stead L. F. , Wood I. C. , Westhead D. R. 
Published: June 2011

Abstract
Motivation: Non-synonymous single nucleotide polymorphisms (nsSNPs) in voltage-gated potassium (Kv) channels cause diseases with potentially fatal consequences in seemingly healthy individuals. Identifying disease-causing genetic variation will aid presymptomatic diagnosis and treatment of such disorders. NsSNP-effect predictors are hypothesized to perform best when developed for specific gene families. We, thus, created KvSNP: a method that assigns a disease-causing probability to Kv-channel nsSNPs.
Results: KvSNP outperforms popular non gene-family-specific methods (SNPs&GO, SIFT and Polyphen) in predicting the disease potential of Kv-channel variants, according to all tested metrics (accuracy, Matthews correlation coefficient and area under receiver operator characteristic curve). Most significantly, it increases the separation of the median predicted disease probabilities between benign and disease-causing SNPs by 26% on the next-best competitor. KvSNP has ranked 172 uncharacterized Kv-channel nsSNPs by disease-causing probability.
Availability and Implementation:KvSNP, a WEKA implementation is available at www.bioinformatics.leeds.ac.uk/KvDB/KvSNP.html.
Contact: d.r.westhead@leeds.ac.uk
Supplementary Information: Supplementary data are available at Bioinformatics online.
Decomposing flux distributions into elementary flux modes in genome-scale metabolic networks
Authors: Chan Siu Hung Joshua , Ji Ping 
Published: June 2011

AbstractMotivation: Elementary flux mode (EFM) is a fundamental concept as well as a useful tool in metabolic pathway analysis. One important role of EFMs is that every flux distribution can be decomposed into a set of EFMs and a number of methods to study flux distributions originated from it. Yet finding such decompositions requires the complete set of EFMs, which is intractable in genome-scale metabolic networks due to combinatorial explosion.Results: In this article, we proposed an algorithm to decompose flux distributions into EFMs in genome-scale networks. It is an iterative scheme of a mixed integer linear program. Unlike previous optimization models to find pathways, any feasible solutions can become EFMs in our algorithm. This advantage enables the algorithm to approximate the EFM of largest contribution to an objective reaction in a flux distribution. Our algorithm is able to find EFMs of flux distributions with complex structures, closer to the realistic case in which a cell is subject to various constraints. A case of Escherichia coli growth in the Lysogeny broth (LB) medium containing various carbon sources was studied. Essential metabolites and their syntheses were located. Information on the contribution of each carbon source not obvious from the apparent flux distribution was also revealed. Our work further confirms the utility of finding EFMs by optimization models in genome-scale metabolic networks.Contact: joshua.chan@connect.polyu.hkSupplementary information: Supplementary data are available at Bioinformatics online.
AMIGO, a toolbox for advanced model identification in systems biology using global optimization
Authors: Balsa-Canto Eva , Banga Julio R. 
Published: June 2011

Abstract
Motivation: Mathematical models of complex biological systems usually consist of sets of differential equations which depend on several parameters which are not accessible to experimentation. These parameters must be estimated by fitting the model to experimental data. This estimation problem is very challenging due to the non-linear character of the dynamics, the large number of parameters and the frequently poor information content of the experimental data (poor practical identifiability). The design of optimal (more informative) experiments is an associated problem of the highest interest.
Results: This work presents AMIGO, a toolbox which facilitates parametric identification by means of advanced numerical techniques which cover the full iterative identification procedure putting especial emphasis on robust methods for parameter estimation and practical identifiability analyses, plus flexible capabilities for optimal experimental design.
Availability: The toolbox and the corresponding documentation may be downloaded from: http://www.iim.csic.es/~amigo
Contact: ebalsa@iim.csic.es
Diagnostic Performance and Therapeutic Consequence of Thromboelastometry Activated by Kaolin versus a Panel of Specific Reagents
Authors: Larsen Ole Halfdan , Fenger-Eriksen Christian , Christiansen Kirsten , Ingerslev Jørgen , Sørensen Benny 
Published: June 2011

Background
Thromboelastography/metry (TEG®; Haemoscope, Niles, IL/ROTEM®; Tem International GmbH, Munich, Germany) is increasingly used to guide transfusion therapy. This study investigated the diagnostic performance and therapeutic consequence of using kaolin-activated whole blood compared with a panel of specific TEM®-reagents to distinguish: dilutional coagulopathy, thrombocytopenia, hyperfibrinolysis, and heparinization.

Methods
Blood was drawn from 11 healthy volunteers. Dilutional coagulopathy was generated by 50% dilution with hydroxyethyl starch 130/0.4 whereas thrombocytopenia (mean platelet count 20 ×10⁹/l) was induced using a validated model. Hyperfibrinolysis and heparin contamination were generated by tissue plasminogen activator 2 nM and unfractionated heparin 0.1U/ml, respectively. Coagulation tests were run on ROTEM® delta.

Results
Kaolin-activated whole blood showed no differences between dilutional coagulopathy and thrombocytopenia (mean clotting time 450 s vs. 516 s, α-angle 47.1° vs. 41.5°, maximum clot firmness 35.0 mm vs. 34.2 mm, all P values ≥0.14). Hyperfibrinolysis specifically disclosed an increased maximum lysis (median: 100%, all P values less than 0.001), and heparin induced a distinctly prolonged clotting time (2283 s, all P values less than 0.02). The coagulopathies were readily distinguishable using a panel of TEM-reagents. In particular, dilutional coagulopathy was separated from thrombocytopenia using FIBTEM (maximum clot firmness 1.9 mm vs. 11.2 mm, P < 0.001). The run time of analysis to achieve diagnostic data was shorter applying a panel of TEM-reagents. A transfusion algorithm based on kaolin suggested platelets in case of dilutional coagulopathy, whereas an algorithm applying TEM-reagents suggested fibrinogen.

Conclusion
Monoanalysis with kaolin was unable to distinguish coagulopathies caused by dilution from that of thrombocytopenia. Algorithms based on the use of kaolin may lead to unnecessary transfusion with platelets, whereas the application of TEM-reagents may result in goal-directed fibrinogen substitution.
Congenital Hepatic Fibrosis and Portal Hypertension in Autosomal Dominant Polycystic Kidney Disease
Authors: O'Brien Kevin , Font‐Montgomery Esperanza , Lukose Linda , Bryant Joy , Piwnica‐Worms Katie , Edwards Hailey , Riney Lauren , Garcia Angelica , Daryanani Kailash , Choyke Peter , Mohan Parvathi , Heller Theo , Gahl William A. , Gunay‐Aygun Meral 
Published: June 2011

ABSTRACTObjectives:Autosomal dominant (ADPKD) and recessive (ARPKD) polycystic kidney diseases are the most common hepatorenal fibrocystic diseases (ciliopathies). Characteristics of liver disease of these disorders are quite different. All of the patients with ARPKD have congenital hepatic fibrosis (CHF) often complicated by portal hypertension. In contrast, typical liver involvement in ADPKD is polycystic liver disease, although rare atypical cases with CHF are reported. Our goal was to describe the characteristics of CHF in ADPKD.Patients and Methods:As a part of an intramural study of the National Institutes of Health on ciliopathies (www.clinicaltrials.gov, trial NCT00068224), we evaluated 8 patients from 3 ADPKD families with CHF. We present their clinical, biochemical, imaging, and PKD1 and PKHD1 sequencing results. In addition, we tabulate the characteristics of 15 previously reported patients with ADPKD‐CHF from 11 families.Results:In all of the 19 patients with ADPKD‐CHF (9 boys, 10 girls), portal hypertension was the main manifestation of CHF; hepatocelllular function was preserved and liver enzymes were largely normal. In all of the 14 families, CHF was not inherited vertically, that is the parents of the index cases had PKD but did not have CHF‐suggesting modifier gene(s). Our 3 families had pathogenic mutations in PKD1; sequencing of the PKHD1 gene as a potential modifier did not reveal any mutations.Conclusions:Characteristics of CHF in ADPKD are similar to CHF in ARPKD. ADPKD‐CHF is caused by PKD1 mutations, with probable contribution from modifying gene(s). Given that both boys and girls are affected, these modifier(s) are likely located on autosomal chromosome(s) and less likely X‐linked.
Decrease of Total Subcutaneous Adipose Tissue From Infancy to Childhood
Authors: Kaimbacher Petra S. , Dunitz‐Scheer Marguerite , Wallner‐Liebmann Sandra J. , Scheer Peter J.Z. , Sudi Karl , Schnedl Wolfgang J. , Tafeit Erwin 
Published: June 2011

ABSTRACTObjectives:The observation and research of body composition is a topic of present interest. For the assessment of health and variables influencing growth and nutrition, it is of utmost interest to focus on the population of young children.Subjects and Methods:The measurements of subcutaneous body fat distribution in a sample of clinically healthy children ages 0 to 7 years were examined. The optical device LIPOMETER was applied to measure the thickness of subcutaneous adipose tissue layers (in millimeters) at 15 well‐defined body sites. This set of measurement points defines the subcutaneous adipose tissue topography. In the present study, subcutaneous adipose tissue topography was determined in 275 healthy children (128 girls and 147 boys) divided into 3 age groups.Results:The results of the measurements are presented in 3 levels: total subcutaneous adipose tissue, 4 body regions, and 15 body sites. Our results show a clear physiological decrease in subcutaneous body fat in boys (−43.8%) and girls (−39.8%). One interesting finding was that the decrease occurs mainly in the trunk, abdomen, and lower extremities, whereas the body fat distribution of the upper extremities did not differ. Furthermore, slight subcutaneous adipose tissue topography differences between both sexes were found.Conclusions:The present study provides basic documentation of subcutaneous adipose tissue topography in healthy children ages 0 to 7 years. An accurate description of subcutaneous adipose tissue topography in healthy subjects could help to characterize various diseases in relation to overnutrition and malnutrition throughout childhood.