scholarly journals Collaborative Cross Mouse Populations as a Resource for the Study of Epilepsy

2019 ◽  
Author(s):  
Bin Gu ◽  
John R. Shorter ◽  
Lucy H. Williams ◽  
Timothy A. Bell ◽  
Pablo Hock ◽  
...  
Keyword(s):  
Animal Models ◽  
Critical Role ◽  
Reference Population ◽  
Collaborative Cross ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Unexpected Death ◽  
F2 Population ◽  
Complex Features ◽  
Genetic Reference Population

ABSTRACTEpilepsy is a neurological disorder with complex etiologies and genetic architecture. Animal models have a critical role in understanding the pathophysiology of epilepsy. Here we studied epilepsy utilizing a genetic reference population of Collaborative Cross (CC) mice with publicly available whole genome sequences. We measured multiple epilepsy traits in 35 CC strains, and we identified novel animal models that exhibit extreme outcomes in seizure susceptibility, seizure propagation, epileptogenesis, and sudden unexpected death in epilepsy. We performed QTL mapping in an F2 population and identified seven novel and one previously identified loci associated with seizure sensitivity. We combined whole genome sequence and hippocampal gene expression to pinpoint biologically plausible candidate genes and candidate variants associated with seizure sensitivity. These resources provide a powerful toolbox for studying complex features of seizures and for identifying genes associated with particular seizure outcomes, and hence will facilitate the development of new therapeutic targets for epilepsy.

scholarly journals Complete Genome Sequence of Streptococcus oralis SF100, Isolated from Blood Cultures from a Patient with Infective Endocarditis

2021 ◽  
Vol 10 (28) ◽  
Author(s):  
Ji Hee Lee ◽  
Hyun Jung Ji ◽  
Ho Seong Seo ◽  
Paul M. Sullam
Keyword(s):  
Infective Endocarditis ◽  
Animal Models ◽  
Oral Cavity ◽  
Genome Sequence ◽  
Complete Genome Sequence ◽  
Blood Cultures ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Content Type ◽  
Streptococcus Oralis

Streptococcus oralis is a commensal viridans group streptococcus of the human oral cavity and a frequent cause of endovascular infection. Here, we report the complete whole-genome sequence of S. oralis strain SF100, which was originally isolated from the blood of a patient with infective endocarditis. This strain contains the lysogenic bacteriophage SM1, which enhances the virulence of SF100 in animal models of endocardial infection.

A whole genome sequence association study for puberty in a large Duroc × Erhualian F2 population

2017 ◽  
Vol 49 (1) ◽  
pp. 29-35 ◽  
Author(s):  
W. S. Xin ◽  
F. Zhang ◽  
G. R. Yan ◽  
W. W. Xu ◽  
S. J. Xiao ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Sequence ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
F2 Population

scholarly journals gQTL: A Web Application for QTL Analysis Using the Collaborative Cross Mouse Genetic Reference Population

2018 ◽  
Vol 8 (8) ◽  
pp. 2559-2562 ◽  
Author(s):  
Kranti Konganti ◽  
Andre Ehrlich ◽  
Ivan Rusyn ◽  
David W. Threadgill
Keyword(s):  
Qtl Analysis ◽  
Web Application ◽  
Reference Population ◽  
Collaborative Cross ◽  
Genetic Reference Population ◽  
Mouse Genetic

scholarly journals Evaluation of the accuracy of imputed sequence variants and their utility for causal variant detection in cattle

2016 ◽  
Author(s):  
Hubert Pausch ◽  
Iona M MacLeod ◽  
Ruedi Fries ◽  
Reiner Emmerling ◽  
Phil J Bowman ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Milk Fat ◽  
Association Studies ◽  
Bovine Genome ◽  
Reference Population ◽  
Whole Genome Sequence ◽  
Sequence Variants ◽  
Whole Genome ◽  
Segmental Duplications ◽  
Fat Percentage

AbstractBackgroundThe availability of dense genotypes and whole-genome sequence variants from various sources offers the opportunity to compile large data sets consisting of tens of thousands of individuals with genotypes at millions of polymorphic sites that may enhance the power of genomic analyses. The imputation of missing genotypes ensures that all individuals have genotypes for a shared set of variants.ResultsWe evaluated the accuracy of imputation from dense genotypes to whole-genome sequence variants in 249 Fleckvieh and 450 Holstein cattle using Minimac and FImpute. The sequence variants of a subset of the animals were reduced to the variants that were included in the Illumina BovineHD genotyping array and subsequently inferred in silico using either within-or multi-breed reference populations. The accuracy of imputation varied considerably across chromosomes and dropped at regions where the bovine genome contains segmental duplications. Depending on the imputation strategy, the correlation between imputed and true genotypes ranged from 0.898 to 0.952. The accuracy of imputation was higher with Minimac than FImpute particularly for variants with low MAF. Considering a multi-breed reference population increased the accuracy of imputation, particularly when FImpute was used to infer genotypes. When the sequence variants were imputed using Minimac, the true genotypes were more correlated to predicted allele dosages than best-guess genotypes. The computing costs to impute 23,256,743 sequence variants in 6958 animals were ten-fold higher with Minimac than FImpute. Association studies with imputed sequence variants revealed seven quantitative trait loci (QTL) for milk fat percentage. Two causal mutations in the DGAT1 and GHR genes were the most significantly associated variants at two QTL on chromosomes 14 and 20 when Minimac was used to infer genotypes.ConclusionsThe population-based imputation of millions of sequence variants in large cohorts is computationally feasible and provides accurate genotypes. However, the accuracy of imputation is low at regions where the genome contains large segmental duplications or the coverage with array-derived SNPs is poor. Using a reference population that includes individuals from many breeds increases the accuracy of imputation particularly at low-frequency variants. Considering allele dosages rather than best-guess genotypes as explanatory variables is advantageous to detect causal mutations in association studies with imputed sequence variants.

scholarly journals Determinants of QTL mapping power in the realized Collaborative Cross

2018 ◽  
Author(s):  
Gregory R. Keele ◽  
Wesley L. Crouse ◽  
Samir N. P. Kelada ◽  
William Valdar
Keyword(s):  
Qtl Mapping ◽  
Power Analysis ◽  
Large Scale ◽  
Reference Population ◽  
R Package ◽  
Collaborative Cross ◽  
Mapping Study ◽  
General Power ◽  
Genetic Reference Population ◽  
Power Analyses

ABSTRACTThe Collaborative Cross (CC) is a mouse genetic reference population whose range of applications includes quantitative trait loci (QTL) mapping. The design of a CC QTL mapping study involves multiple decisions, including which and how many strains to use, and how many replicates per strain to phenotype, all viewed within the context of hypothesized QTL architecture. Until now, these decisions have been informed largely by early power analyses that were based on simulated, hypothetical CC genomes. Now that more than 50 CC strains are available and more than 70 CC genomes have been observed, it is possible to characterize power based on realized CC genomes. We report power analyses based on extensive simulations and examine several key considerations: 1) the number of strains and biological replicates, 2) the QTL effect size, 3) the presence of population structure, and 4) the distribution of functionally distinct alleles among the founder strains at the QTL. We also provide general power estimates to aide in the design of future experiments. All analyses were conducted with our R package, SPARCC (Simulated Power Analysis in the Realized Collaborative Cross), developed for performing either large scale power analyses or those tailored to particular CC experiments.

scholarly journals Two-step genomic sequence comparison strategy to design Trichoderma strain-specific primers for quantitative PCR

AMB Express ◽  
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Yang Zhang ◽  
Xiang Wang ◽  
Guan Pang ◽  
Feng Cai ◽  
Jian Zhang ◽  
...  
Keyword(s):  
Quantitative Pcr ◽  
Sequence Comparison ◽  
Functional Performance ◽  
Genomic Sequence ◽  
Critical Role ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Promoting Effect ◽  
Specific Primers ◽  
Significant Difference

Abstract Survival of inoculated fungal strains in a new environment plays a critical role in functional performance, but few studies have focused on strain-specific quantitative PCR (qPCR) methods for monitoring beneficial fungi. In this study, the Trichoderma guizhouense strain NJAU 4742 (transformed with the gfp gene and named gfp-NJAU 4742), which exhibits a growth-promoting effect by means of phytohormone production and pathogen antagonism, was selected as a model to design strain-specific primer pairs using two steps of genomic sequence comparison to detect its abundance in soil. After a second comparison with the closely related species T. harzianum CBS 226-95 to further differentiate the strain-specific fragments that had shown no homology to any sequence deposited in the databases used in the first comparison, ten primer pairs were designed from the whole genome. Meanwhile, 3 primer pairs, P11, P12 and P13, were also designed from the inserted fragment containing the gfp gene. After verification testing with three types of field soils, primer pairs P6, P7 and P8 were further selected by comparison with P11, P12 and P13. A practical test using a pot experiment showed that stable colonization of gfp-NJAU 4742 in pepper rhizosphere soil could be detected using primer pairs P6 and P7, showing no significant difference from the results of primers P11 and P12. Hence, the strategy described here for designing fungal-strain-specific primers may theoretically be used for any other fungi for which the whole genome sequence is available in a database, and the qPCR methodology developed can also be used to further monitor the population dynamics of different strains based on the designed primers.

scholarly journals Strategies for imputation to whole genome sequence using a single or multi-breed reference population in cattle

BMC Genomics ◽  
2014 ◽  
Vol 15 (1) ◽  
pp. 728 ◽  
Author(s):  
Rasmus Brøndum ◽  
Bernt Guldbrandtsen ◽  
Goutam Sahana ◽  
Mogens Lund ◽  
Guosheng Su
Keyword(s):  
Genome Sequence ◽  
Reference Population ◽  
Whole Genome Sequence ◽  
Whole Genome
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