A new set of BXD recombinant inbred lines from advanced intercross populations in mice

BACKGROUND: Recombinant inbred (RI) strains are an important resource for mapping complex traits in many species. While large RI panels are available for Arabidopsis, maize, C. elegans, and Drosophila, mouse RI panels typically consist of fewer than 30 lines. This is a severe constraint on the power and precision of mapping efforts and greatly hampers analysis of epistatic interactions. RESULTS: In order to address these limitations and to provide the community with a more effective collaborative RI mapping panel we generated new BXD RI strains from two independent advanced intercrosses (AI) between C57BL/6J (B6) and DBA/2J (D2) progenitor strains. Progeny were intercrossed for 9 to 14 generations before initiating inbreeding, which is still ongoing for some strains. Since this AI base population is highly recombinant, the 46 advanced recombinant inbred (ARI) strains incorporate approximately twice as many recombinations as standard RI strains, a fraction of which are inevitably shared by descent. When combined with the existing BXD RI strains, the merged BXD strain set triples the number of previously available unique recombinations and quadruples the total number of recombinations in the BXD background. CONCLUSION: The combined BXD strain set is the largest mouse RI mapping panel. It is a powerful tool for collaborative analysis of quantitative traits and gene function that will be especially useful to study variation in transcriptome and proteome data sets under multiple environments. Additional strains also extend the value of the extensive phenotypic characterization of the previously available strains. A final advantage of expanding the BXD strain set is that both progenitors have been sequenced, and approximately 1.8 million SNPs have been characterized. This provides unprecedented power in screening candidate genes and can reduce the effective length of QTL intervals. It also makes it possible to reverse standard mapping strategies and to explore downstream effects of known sequence variants

Using gene expression databases for classical trait QTL candidate gene discovery in the BXD recombinant inbred genetic reference population: Mouse forebrain weight

<p>Abstract</p> <p>Background</p> <p>Successful strategies for QTL gene identification benefit from combined experimental and bioinformatic approaches. Unique design aspects of the BXD recombinant inbred line mapping panel allow use of archived gene microarray expression data to filter likely from unlikely candidates. This prompted us to propose a simple five-filter protocol for candidate nomination. To filter more likely from less likely candidates, we required candidate genes near to the QTL to have mRNA abundance that correlated with the phenotype among the BXD lines as well as differed between the parental lines C57BL/6J and DBA/2J. We also required verification of mRNA abundance by an independent method, and finally we required either differences in protein levels or confirmed DNA sequence differences.</p> <p>Results</p> <p>QTL mapping of mouse forebrain weight in 34 BXD RI lines found significant association on chromosomes 1 and 11, with each C57BL/6J allele increasing weight by more than half a standard deviation. The intersection of gene lists that were within ± 10 Mb of the strongest associated location, that had forebrain mRNA abundance correlated with forebrain weight among the BXD, and that had forebrain mRNA abundance differing between C57BL/6J and DBA/2J, produced two candidates, <it>Tnni1 </it>(troponin 1) and <it>Asb3 </it>(ankyrin repeat and SOCS box-containing protein 3). Quantitative RT-PCR confirmed the direction of an increased expression in C57BL/6J genotype over the DBA/2J genotype for both genes, a difference that translated to a 2-fold difference in Asb3 protein. Although Tnni1 protein differences could not be confirmed, a 273 bp indel polymorphism was discovered 1 Kb upstream of the transcription start site.</p> <p>Conclusion</p> <p>Delivery of well supported candidate genes following a single quantitative trait locus mapping experiment is difficult. However, by combining available gene expression data with QTL mapping, we illustrated a five-filter protocol that nominated <it>Asb3 </it>and <it>Tnni1 </it>as candidates affecting increased mouse forebrain weight. We recommend our approach when (1) investigators are working with phenotypic differences between C57BL/6J and DBA/2J, and (2) gene expression data are available on <url>http://www.genenetwork.org</url> that relate to the phenotype of interest. Under these circumstances, measurement of the phenotype in the BXD lines will likely also deliver excellent candidate genes.</p

Grxcr1 promotes hair bundle development by destabilizing the physical interaction between Harmonin and Sans usher syndrome proteins

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Cell Reports 25 (2018): 1281–1291, doi:10.1016/j.celrep.2018.10.005.Morphogenesis and mechanoelectrical transduction of the hair cell mechanoreceptor depend on the correct assembly of Usher syndrome (USH) proteins into highly organized macromolecular complexes. Defects in these proteins lead to deafness and vestibular areflexia in USH patients. Mutations in a non-USH protein, glutaredoxin domain-containing cysteine-rich 1 (GRXCR1), cause non-syndromic sensorineural deafness. To understand the deglutathionylating enzyme function of GRXCR1 in deafness, we generated two grxcr1 zebrafish mutant alleles. We found that hair bundles are thinner in homozygous grxcr1 mutants, similar to the USH1 mutants ush1c (Harmonin) and ush1ga (Sans). In vitro assays showed that glutathionylation promotes the interaction between Ush1c and Ush1ga and that Grxcr1 regulates mechanoreceptor development by preventing physical interaction between these proteins without affecting the assembly of another USH1 protein complex, the Ush1c- Cadherin23-Myosin7aa tripartite complex. By elucidating the molecular mechanism through which Grxcr1 functions, we also identify a mechanism that dynamically regulates the formation of Usher protein complexes.This work was supported by grants from the NIH (DC004186, OD011195, and HD22486)

A Simple Method for Combining Genetic Mapping Data from Multiple Crosses and Experimental Designs

Over the past decade many linkage studies have defined chromosomal intervals containing polymorphisms that modulate a variety of traits. Many phenotypes are now associated with enough mapping data that meta-analysis could help refine locations of known QTLs and detect many novel QTLs.We describe a simple approach to combining QTL mapping results for multiple studies and demonstrate its utility using two hippocampus weight loci. Using data taken from two populations, a recombinant inbred strain set and an advanced intercross population we demonstrate considerable improvements in significance and resolution for both loci. 1-LOD support intervals were improved 51% for Hipp1a and 37% for Hipp9a. We first generate locus-wise permuted P-values for association with the phenotype from multiple maps, which can be done using a permutation method appropriate to each population. These results are then assigned to defined physical positions by interpolation between markers with known physical and genetic positions. We then use Fisher's combination test to combine position-by-position probabilities among experiments. Finally, we calculate genome-wide combined P-values by generating locus-specific P-values for each permuted map for each experiment. These permuted maps are then sampled with replacement and combined. The distribution of best locus-specific P-values for each combined map is the null distribution of genome-wide adjusted P-values.Our approach is applicable to a wide variety of segregating and non-segregating mapping populations, facilitates rapid refinement of physical QTL position, is complementary to other QTL fine mapping methods, and provides an appropriate genome-wide criterion of significance for combined mapping results

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

How replicable are mRNA expression QTL?

Applying quantitative trait analysis methods to genome-wide microarray-derived mRNA expression phenotypes in segregating populations is a valuable tool in the attempt to link high-level traits to their molecular causes. The massive multiple-testing issues involved in analyzing these data make the correct level of confidence to place in mRNA abundance quantitative trait loci (QTL) a difficult problem. We use a unique resource to directly test mRNA abundance QTL replicability in mice: paired recombinant inbred (RI) and F2 data sets derived from C57BL/6J (B6) and DBA/2J (D2) inbred strains and phenotyped using the same Affymetrix arrays. We have one forebrain and one striatum data set pair. We describe QTL replication at varying stringencies in these data. For instance, 78% of mRNA expression QTL (eQTL) with genome-wide adjusted p ≤ 0.0001 in RI data replicate at a genome-wide adjusted p \u3c 0.05 or better. Replicated QTL are disproportionately putatively cis-acting, and approximately 75% have higher apparent expression levels associated with B6 genotypes, which may be partly due to probe set generation using B6 sequence. Finally, we note that while trans-acting QTL do not replicate well between data sets in general, at least one cluster of trans-acting QTL on distal Chr 1 is notably preserved between data sets. © 2006 Springer Science+Business Media, Inc

BMC Genetics BioMed Central Methodology article

A new set of BXD recombinant inbred lines from advanced intercross populations in mic

Combined mapping for <i>Hipp1a</i> and <i>Hipp9a.</i>

<p>This figure shows mapping data for the hippocampus weight loci <i>Hipp1a</i> and <i>Hipp9a</i> using 34 BXD strains (BXD; shaded line) and 679 advanced intercross animals (AIL, thin solid line) as well as the composite map using the described method (thick solid line). The genome-wide adjusted composite P = 0.05 threshold is −log P = 3.5 (dark solid horizontal line). Since 5000 permutations were used for each data set, the maximum −log P<3.7 (graphed as −log P = 3.7 for convenience) for each individual data set, so increasing the number of permutations might increase the peak combined value and slightly improve the range of the combined interval. Bars underneath the peaks are labeled AIL, BXD, and combined to indicate the l-LOD support interval of these mapping populations.</p

The need for locus-specific P-values.

<p>The 95% LOD score (the LOD score equivalent to a locus-specific P = 0.05) was calculated using 10,000 permutations for markers on Chr. 1 for body weight in several different populations. Each marker is indicated by a dot with connecting lines interpolated between adjacent markers. TJL BXD are BXD strains available from The Jackson Laboratory (The BXD strains developed by Taylor and colleagues <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001036#pone.0001036-Taylor1" target="_blank">[26]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001036#pone.0001036-Taylor2" target="_blank">[27]</a>). New BXD are the recently developed BXD strains currently resident at UTHSC. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001036#pone.0001036-Peirce2" target="_blank">[18]</a> Note that the maximum and minimum values of the 95^th percentile LOD score vary considerably for the AIL population, somewhat for the RI (New BXD and TJL BXD) populations, (predicted by missing data pattern) and very little for the 183 member F2 population tested. (There are only three widely spaced markers genotyped for the F2 population on Chr. 1, so the interpolation between points should not be interpreted as a meaningful line. However, markers on all chromosomes were very similar, between a 95% LOD of 1.2 and 1.4.)</p