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Background
Inbreeding reduces the fitness of individuals by increasing the frequency of homozygous deleterious recessive alleles. Some insight into the genetic architecture of fitness, and other complex traits, can be gained by using single nucleotide polymorphism (SNP) data to identify regions of the genome which lead to reduction in performance when identical by descent (IBD). Here, we compared the effect of genome-wide and location-specific homozygosity on fertility and milk production traits in dairy cattle.Methods
Genotype data from more than 43 000 SNPs were available for 8853 Holstein and 4138 Jersey dairy cows that were part of a much larger dataset that had pedigree records (338 696 Holstein and 64 049 Jersey animals). Measures of inbreeding were based on: (1) pedigree data; (2) genotypes to determine the realised proportion of the genome that is IBD; (3) the proportion of the total genome that is homozygous and (4) runs of homozygosity (ROH) which are stretches of the genome that are homozygous.Results
A 1% increase in inbreeding based either on pedigree or genomic data was associated with a decrease in milk, fat and protein yields of around 0.4 to 0.6% of the phenotypic mean, and an increase in calving interval (i.e. a deterioration in fertility) of 0.02 to 0.05% of the phenotypic mean. A genome-wide association study using ROH of more than 50 SNPs revealed genomic regions that resulted in depression of up to 12.5 d and 260 L for calving interval and milk yield, respectively, when completely homozygous.Conclusions
Genomic measures can be used instead of pedigree-based inbreeding to estimate inbreeding depression. Both the diagonal elements of the genomic relationship matrix and the proportion of homozygous SNPs can be used to measure inbreeding. Longer ROH (>3 Mb) were found to be associated with a reduction in milk yield and captured recent inbreeding independently and in addition to overall homozygosity. Inbreeding depression can be reduced by minimizing overall inbreeding but maybe also by avoiding the production of offspring that are homozygous for deleterious alleles at specific genomic regions that are associated with inbreeding depression.Electronic supplementary material
The online version of this article (doi:10.1186/s12711-014-0071-7) contains supplementary material, which is available to authorized users. 相似文献3.
Background
Drug discovery and development are predicated on elucidation of the potential mechanisms of action and cellular targets of candidate chemical compounds. Recent advances in high-content imaging techniques allow simultaneous analysis of a range of cellular events. In this study, we propose a novel strategy to identify drug targets by combining genetic screening and high-content imaging in yeast.Methodology
In this approach, we infer the cellular functions affected by candidate drugs by comparing morphologic changes induced by the compounds with the phenotypes of yeast mutants.Conclusions
Using this method and four well-characterized reagents, we successfully identified previously known target genes of the compounds as well as other genes involved with functionally related cellular pathways. This is the first demonstration of a genetic high-content assay that can be used to identify drug targets based on morphologic phenotypes of a reference mutant panel. 相似文献4.
Annie Yang Zhou Zhu Arminja Kettenbach Philipp Kapranov Frank McKeon Thomas R. Gingeras Kevin Struhl 《PloS one》2010,5(7)
Background
The p53 homologs, p63 and p73, share ∼85% amino acid identity in their DNA-binding domains, but they have distinct biological functions.Principal Findings
Using chromatin immunoprecipitation and high-resolution tiling arrays covering the human genome, we identify p73 DNA binding sites on a genome-wide level in ME180 human cervical carcinoma cells. Strikingly, the p73 binding profile is indistinguishable from the previously described binding profile for p63 in the same cells. Moreover, the p73∶p63 binding ratio is similar at all genomic loci tested, suggesting that there are few, if any, targets that are specific for one of these factors. As assayed by sequential chromatin immunoprecipitation, p63 and p73 co-occupy DNA target sites in vivo, suggesting that p63 and p73 bind primarily as heterotetrameric complexes in ME180 cells.Conclusions
The observation that p63 and p73 associate with the same genomic targets suggest that their distinct biological functions are due to cell-type specific expression and/or protein domains that involve functions other than DNA binding. 相似文献5.
Background
The variance explained by genetic variants as identified in (genome-wide) genetic association studies is typically small compared to family-based heritability estimates. Explanations of this ‘missing heritability’ have been mainly genetic, such as genetic heterogeneity and complex (epi-)genetic mechanisms.Methodology
We used comprehensive simulation studies to show that three phenotypic measurement issues also provide viable explanations of the missing heritability: phenotypic complexity, measurement bias, and phenotypic resolution. We identify the circumstances in which the use of phenotypic sum-scores and the presence of measurement bias lower the power to detect genetic variants. In addition, we show how the differential resolution of psychometric instruments (i.e., whether the instrument includes items that resolve individual differences in the normal range or in the clinical range of a phenotype) affects the power to detect genetic variants.Conclusion
We conclude that careful phenotypic data modelling can improve the genetic signal, and thus the statistical power to identify genetic variants by 20–99%. 相似文献6.
Background
In classical pedigree-based analysis, additive genetic variance is estimated from between-family variation, which requires the existence of larger phenotyped and pedigreed populations involving numerous families (parents). However, estimation is often complicated by confounding of genetic and environmental family effects, with the latter typically occurring among full-sibs. For this reason, genetic variance is often inferred based on covariance among more distant relatives, which reduces the power of the analysis. This simulation study shows that genome-wide identity-by-descent sharing among close relatives can be used to quantify additive genetic variance solely from within-family variation using data on extremely small family samples.Methods
Identity-by-descent relationships among full-sibs were simulated assuming a genome size similar to that of humans (effective number of loci ~80). Genetic variance was estimated from phenotypic data assuming that genomic identity-by-descent relationships could be accurately re-created using information from genome-wide markers. The results were compared with standard pedigree-based genetic analysis.Results
For a polygenic trait and a given number of phenotypes, the most accurate estimates of genetic variance were based on data from a single large full-sib family only. Compared with classical pedigree-based analysis, the proposed method is more robust to selection among parents and for confounding of environmental and genetic effects. Furthermore, in some cases, satisfactory results can be achieved even with less ideal data structures, i.e., for selectively genotyped data and for traits for which the genetic variance is largely under the control of a few major genes.Conclusions
Estimation of genetic variance using genomic identity-by-descent relationships is especially useful for studies aiming at estimating additive genetic variance of highly fecund species, using data from small populations with limited pedigree information and/or few available parents, i.e., parents originating from non-pedigreed or even wild populations. 相似文献7.
Karen Christin Falke Gregory S Mahone Eva Bauer Grit Haseneyer Thomas Miedaner Frank Breuer Matthias Frisch 《BMC genomics》2014,15(1)
Background
Introgression populations are used to make the genetic variation of unadapted germplasm or wild relatives of crops available for plant breeding. They consist of introgression lines that carry small chromosome segments from an exotic donor in the genetic background of an elite line. The goal of our study was to investigate the detection of favorable donor chromosome segments in introgression lines with statistical methods developed for genome-wide prediction.Results
Computer simulations showed that genome-wide prediction employing heteroscedastic marker variances had a greater power and a lower false positive rate compared with homoscedastic marker variances when the phenotypic difference between the donor and recipient lines was controlled by few genes. The simulations helped to interpret the analyses of glycosinolate and linolenic acid content in a rapeseed introgression population and plant height in a rye introgression population. These analyses support the superiority of genome-wide prediction approaches that use heteroscedastic marker variances.Conclusions
We conclude that genome-wide prediction methods in combination with permutation tests can be employed for analysis of introgression populations. They are particularly useful when introgression lines carry several donor segments or when the donor segments of different introgression lines are overlapping. 相似文献8.
Andrew Schoenrock Bahram Samanfar Sylvain Pitre Mohsen Hooshyar Ke Jin Charles A Phillips Hui Wang Sadhna Phanse Katayoun Omidi Yuan Gui Md Alamgir Alex Wong Fredrik Barren?s Mohan Babu Mikael Benson Michael A Langston James R Green Frank Dehne Ashkan Golshani 《BMC bioinformatics》2014,15(1)
Background
Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods.Results
On the basis of short co-occurring polypeptide regions, we developed a tool called MP-PIPE capable of predicting a global human PPI network within 3 months. With a recall of 23% at a precision of 82.1%, we predicted 172,132 putative PPIs. We demonstrate the usefulness of these predictions through a range of experiments.Conclusions
The speed and accuracy associated with MP-PIPE can make this a potential tool to study individual human PPI networks (from genomic sequences alone) for personalized medicine.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0383-1) contains supplementary material, which is available to authorized users. 相似文献9.
Background
Cellular activities are governed by the physical and the functional interactions among several proteins involved in various biological pathways. With the availability of sequenced genomes and high-throughput experimental data one can identify genome-wide protein-protein interactions using various computational techniques. Comparative assessments of these techniques in predicting protein interactions have been frequently reported in the literature but not their ability to elucidate a particular biological pathway.Methods
Towards the goal of understanding the prediction capabilities of interactions among the specific biological pathway proteins, we report the analyses of 14 biological pathways of Escherichia coli catalogued in KEGG database using five protein-protein functional linkage prediction methods. These methods are phylogenetic profiling, gene neighborhood, co-presence of orthologous genes in the same gene clusters, a mirrortree variant, and expression similarity.Conclusions
Our results reveal that the prediction of metabolic pathway protein interactions continues to be a challenging task for all methods which possibly reflect flexible/independent evolutionary histories of these proteins. These methods have predicted functional associations of proteins involved in amino acids, nucleotide, glycans and vitamins & co-factors pathways slightly better than the random performance on carbohydrate, lipid and energy metabolism. We also make similar observations for interactions involved among the environmental information processing proteins. On the contrary, genetic information processing or specialized processes such as motility related protein-protein linkages that occur in the subset of organisms are predicted with comparable accuracy. Metabolic pathways are best predicted by using neighborhood of orthologous genes whereas phyletic pattern is good enough to reconstruct central dogma pathway protein interactions. We have also shown that the effective use of a particular prediction method depends on the pathway under investigation. In case one is not focused on specific pathway, gene expression similarity method is the best option. 相似文献10.
Ja-Rang Lee Chang Pyo Hong Jae-Woo Moon Yi-Deun Jung Dae-Soo Kim Tae-Hyung Kim Jeong-An Gim Jin-Han Bae Yuri Choi Jungwoo Eo Yun-Jeong Kwon Sanghoon Song Junsu Ko Young Mok Yang Hak-Kyo Lee Kyung-Do Park Kung Ahn Kyoung-Tag Do Hong-Seok Ha Kyudong Han Joo Mi Yi Hee-Jae Cha Byung-Wook Cho Jong Bhak Heui-Soo Kim 《BMC genomics》2014,15(1)
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Li Jiang Stefan M Edwards Bo Thomsen Christopher T Workman Bernt Guldbrandtsen Peter S?rensen 《BMC bioinformatics》2014,15(1)
Background
Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile of genes with respect to their connection to disease phenotypes. The importance of protein-protein interaction networks in the genetic heterogeneity of common diseases or complex traits is becoming increasingly recognized. Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization.Results
We developed a random-set scoring model and implemented it to quantify phenotype relevance in a network-based disease gene-prioritization approach. We validated our approach based on different gene phenotypic profiles, which were generated from PubMed abstracts, OMIM, and GeneRIF records. We also investigated the validity of several vocabulary filters and different likelihood thresholds for predicted protein-protein interactions in terms of their effect on the network-based gene-prioritization approach, which relies on text-mining of the phenotype data. Our method demonstrated good precision and sensitivity compared with those of two alternative complex-based prioritization approaches. We then conducted a global ranking of all human genes according to their relevance to a range of human diseases. The resulting accurate ranking of known causal genes supported the reliability of our approach. Moreover, these data suggest many promising novel candidate genes for human disorders that have a complex mode of inheritance.Conclusion
We have implemented and validated a network-based approach to prioritize genes for human diseases based on their phenotypic profile. We have devised a powerful and transparent tool to identify and rank candidate genes. Our global gene prioritization provides a unique resource for the biological interpretation of data from genome-wide association studies, and will help in the understanding of how the associated genetic variants influence disease or quantitative phenotypes.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-315) contains supplementary material, which is available to authorized users. 相似文献12.
Enrique Sánchez-Molano John A Woolliams Ricardo Pong-Wong Dylan N Clements Sarah C Blott Pamela Wiener 《BMC genomics》2014,15(1)
Background
Canine hip dysplasia (CHD) is characterised by a malformation of the hip joint, leading to osteoarthritis and lameness. Current breeding schemes against CHD have resulted in measurable but moderate responses. The application of marker-assisted selection, incorporating specific markers associated with the disease, or genomic selection, incorporating genome-wide markers, has the potential to dramatically improve results of breeding schemes. Our aims were to identify regions associated with hip dysplasia or its related traits using genome and chromosome-wide analysis, study the linkage disequilibrium (LD) in these regions and provide plausible gene candidates. This study is focused on the UK Labrador Retriever population, which has a high prevalence of the disease and participates in a recording program led by the British Veterinary Association (BVA) and The Kennel Club (KC).Results
Two genome-wide and several chromosome-wide QTLs affecting CHD and its related traits were identified, indicating regions related to hip dysplasia.Conclusion
Consistent with previous studies, the genetic architecture of CHD appears to be based on many genes with small or moderate effect, suggesting that genomic selection rather than marker-assisted selection may be an appropriate strategy for reducing this disease.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-833) contains supplementary material, which is available to authorized users. 相似文献13.
Background
Hsp90 is an essential molecular chaperone that is also a novel anti-cancer drug target. There is growing interest in developing new drugs that modulate Hsp90 activity.Methodology/Principal Findings
Using a virtual screening approach, 4-hydroxytamoxifen, the active metabolite of the anti-estrogen drug tamoxifen, was identified as a putative Hsp90 ligand. Surprisingly, while all drugs targeting Hsp90 inhibit the chaperone ATPase activity, it was found experimentally that 4-hydroxytamoxifen and tamoxifen enhance rather than inhibit Hsp90 ATPase.Conclusions/Significance
Hence, tamoxifen and its metabolite are the first members of a new pharmacological class of Hsp90 activators. 相似文献14.
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Bas E Dutilh Cristiane C Thompson Ana CP Vicente Michel A Marin Clarence Lee Genivaldo GZ Silva Robert Schmieder Bruno GN Andrade Luciane Chimetto Daniel Cuevas Daniel R Garza Iruka N Okeke Aaron Oladipo Aboderin Jessica Spangler Tristen Ross Elizabeth A Dinsdale Fabiano L Thompson Timothy T Harkins Robert A Edwards 《BMC genomics》2014,15(1)
Background
Vibrio cholerae is a globally dispersed pathogen that has evolved with humans for centuries, but also includes non-pathogenic environmental strains. Here, we identify the genomic variability underlying this remarkable persistence across the three major niche dimensions space, time, and habitat.Results
Taking an innovative approach of genome-wide association applicable to microbial genomes (GWAS-M), we classify 274 complete V. cholerae genomes by niche, including 39 newly sequenced for this study with the Ion Torrent DNA-sequencing platform. Niche metadata were collected for each strain and analyzed together with comprehensive annotations of genetic and genomic attributes, including point mutations (single-nucleotide polymorphisms, SNPs), protein families, functions and prophages.Conclusions
Our analysis revealed that genomic variations, in particular mobile functions including phages, prophages, transposable elements, and plasmids underlie the metadata structuring in each of the three niche dimensions. This underscores the role of phages and mobile elements as the most rapidly evolving elements in bacterial genomes, creating local endemicity (space), leading to temporal divergence (time), and allowing the invasion of new habitats. Together, we take a data-driven approach for comparative functional genomics that exploits high-volume genome sequencing and annotation, in conjunction with novel statistical and machine learning analyses to identify connections between genotype and phenotype on a genome-wide scale.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-654) contains supplementary material, which is available to authorized users. 相似文献16.
Stefan Walter M. Maria Glymour Karestan Koenen Liming Liang Eric J. Tchetgen Tchetgen Marilyn Cornelis Shun-Chiao Chang Eric Rimm Ichiro Kawachi Laura D. Kubzansky 《PloS one》2013,8(11)
Context
Anxiety disorders are common, with a lifetime prevalence of 20% in the U.S., and are responsible for substantial burdens of disability, missed work days and health care utilization. To date, no causal genetic variants have been identified for anxiety, anxiety disorders, or related traits.Objective
To investigate whether a phobic anxiety symptom score was associated with 3 alternative polygenic risk scores, derived from external genome-wide association studies of anxiety, an internally estimated agnostic polygenic score, or previously identified candidate genes.Design
Longitudinal follow-up study. Using linear and logistic regression we investigated whether phobic anxiety was associated with polygenic risk scores derived from internal, leave-one out genome-wide association studies, from 31 candidate genes, and from out-of-sample genome-wide association weights previously shown to predict depression and anxiety in another cohort.Setting and Participants
Study participants (n = 11,127) were individuals from the Nurses'' Health Study and Health Professionals Follow-up Study.Main Outcome Measure
Anxiety symptoms were assessed via the 8-item phobic anxiety scale of the Crown Crisp Index at two time points, from which a continuous phenotype score was derived.Results
We found no genome-wide significant associations with phobic anxiety. Phobic anxiety was also not associated with a polygenic risk score derived from the genome-wide association study beta weights using liberal p-value thresholds; with a previously published genome-wide polygenic score; or with a candidate gene risk score based on 31 genes previously hypothesized to predict anxiety.Conclusion
There is a substantial gap between twin-study heritability estimates of anxiety disorders ranging between 20–40% and heritability explained by genome-wide association results. New approaches such as improved genome imputations, application of gene expression and biological pathways information, and incorporating social or environmental modifiers of genetic risks may be necessary to identify significant genetic predictors of anxiety. 相似文献17.
Sebastiaan van Heesch Michal Mokry Veronika Boskova Wade Junker Rajdeep Mehon Pim Toonen Ewart de Bruijn James D Shull Timothy J Aitman Edwin Cuppen Victor Guryev 《Genome biology》2013,14(4):R33
Background
The ability to accurately detect DNA copy number variation in both a sensitive and quantitative manner is important in many research areas. However, genome-wide DNA copy number analyses are complicated by variations in detection signal.Results
While GC content has been used to correct for this, here we show that coverage biases are tissue-specific and independent of the detection method as demonstrated by next-generation sequencing and array CGH. Moreover, we show that DNA isolation stringency affects the degree of equimolar coverage and that the observed biases coincide with chromatin characteristics like gene expression, genomic isochores, and replication timing.Conclusion
These results indicate that chromatin organization is a main determinant for differential DNA retrieval. These findings are highly relevant for germline and somatic DNA copy number variation analyses. 相似文献18.
Background
Genomic evaluations are rapidly replacing traditional evaluation systems used for dairy cattle selection. Higher reliabilities from larger genotype files promote cooperation across country borders. Genomic information can be exchanged across countries using simple conversion equations, by modifying multi-trait across-country evaluation (MACE) to account for correlated residuals originating from the use of foreign evaluations, or by multi-trait analysis of genotypes for countries that use the same reference animals.Methods
Traditional MACE assumes independent residuals because each daughter is measured in only one country. Genomic MACE could account for residual correlations using daughter equivalents from genomic data as a fraction of the total in each country and proportions of bulls shared. MACE methods developed to combine separate within-country genomic evaluations were compared to direct, multi-country analysis of combined genotypes using simulated genomic and phenotypic data for 8,193 bulls in nine countries.Results
Reliabilities for young bulls were much higher for across-country than within-country genomic evaluations as measured by squared correlations of estimated with true breeding values. Gains in reliability from genomic MACE were similar to those of multi-trait evaluation of genotypes but required less computation. Sharing of reference genotypes among countries created large residual correlations, especially for young bulls, that are accounted for in genomic MACE.Conclusions
International genomic evaluations can be computed either by modifying MACE to account for residual correlations across countries or by multi-trait evaluation of combined genotype files. The gains in reliability justify the increased computation but require more cooperation than in previous breeding programs. 相似文献19.
Isaak Y Tecle Jeremy D Edwards Naama Menda Chiedozie Egesi Ismail Y Rabbi Peter Kulakow Robert Kawuki Jean-Luc Jannink Lukas A Mueller 《BMC bioinformatics》2014,15(1)
Background
Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders.Results
We have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model. It has an intuitive web-interface for selecting a training population for modeling and estimating genomic estimated breeding values of selection candidates. It estimates phenotypic correlation and heritability of traits and selection indices of individuals. Raw data is stored in a generic database schema, Chado Natural Diversity, co-developed by multiple database groups. Analysis output is graphically visualized and can be interactively explored online or downloaded in text format. An instance of its implementation can be accessed at the NEXTGEN Cassava breeding database, http://cassavabase.org/solgs.Conclusions
solGS enables breeders to store raw data and estimate GEBVs of individuals online, in an intuitive and interactive workflow. It can be adapted to any breeding program.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0398-7) contains supplementary material, which is available to authorized users. 相似文献20.
Haroon Naeem Nicholas C Wong Zac Chatterton Matthew K H Hong John S Pedersen Niall M Corcoran Christopher M Hovens Geoff Macintyre 《BMC genomics》2014,15(1)