Regarding the Influence of Additives and Additional Plasma-Induced Chemical Ionization on Adduct Formation in ESI/IMS/MS

Ion mobility spectrometers (IMS) separate ions based on their ion mobility, which depends mainly on collision cross-section, mass, and charge of the ions. However, the performance is often hampered in electrospray ionization (ESI) by the appearance of multiple ion mobility peaks in the spectrum for the same analyte due to clustering and additional sodium adducts. In this work, we investigate the influence of solvents and buffer additives on the detected ion mobility peaks using ESI. Additionally, we investigate the effects of an additional chemical ionization (CI) induced by plasma ionization on the ions formed by electrospray. For this purpose, we coupled our high-resolution IMS with a resolving power of Rp = 100 to a time-of-flight mass spectrometer. Depending on the analyte and the chosen additives, the ionization process can be influenced during the electrospray process. For the herbicide isoproturon, the addition of 5 mM sodium acetate results in the formation of the sodium adduct [M + Na]+, which is reflected in the ion mobility K0 of 1.22 cm2/(V·s). In contrast, the addition of 5 mM ammonium acetate yields the protonated species [M + H]+ and a correspondingly higher K0 of 1.29 cm2/(V·s). In some cases, as with the herbicide pyrimethanil, the addition of sodium acetate can completely suppress ionizations. By carefully choosing the solvent additive for ESI-IMS or additional CI, the formation of different ion mobility peaks can be observed. This can facilitate the assignment of ions to ion mobility peaks using IMS as a compact, stand-alone instrument, e.g., for on-site analysis

High throughput sequencing in mice: a platform comparison identifies a preponderance of cryptic SNPs

<p>Abstract</p> <p>Background</p> <p>Allelic variation is the cornerstone of genetically determined differences in gene expression, gene product structure, physiology, and behavior. However, allelic variation, particularly cryptic (unknown or not annotated) variation, is problematic for follow up analyses. Polymorphisms result in a high incidence of false positive and false negative results in hybridization based analyses and hinder the identification of the true variation underlying genetically determined differences in physiology and behavior. Given the proliferation of mouse genetic models (e.g., knockout models, selectively bred lines, heterogeneous stocks derived from standard inbred strains and wild mice) and the wealth of gene expression microarray and phenotypic studies using genetic models, the impact of naturally-occurring polymorphisms on these data is critical. With the advent of next-generation, high-throughput sequencing, we are now in a position to determine to what extent polymorphisms are currently cryptic in such models and their impact on downstream analyses.</p> <p>Results</p> <p>We sequenced the two most commonly used inbred mouse strains, DBA/2J and C57BL/6J, across a region of chromosome 1 (171.6 – 174.6 megabases) using two next generation high-throughput sequencing platforms: Applied Biosystems (SOLiD) and Illumina (Genome Analyzer). Using the same templates on both platforms, we compared realignments and single nucleotide polymorphism (SNP) detection with an 80 fold average read depth across platforms and samples. While public datasets currently annotate 4,527 SNPs between the two strains in this interval, thorough high-throughput sequencing identified a total of 11,824 SNPs in the interval, including 7,663 new SNPs. Furthermore, we confirmed 40 missense SNPs and discovered 36 new missense SNPs.</p> <p>Conclusion</p> <p>Comparisons utilizing even two of the best characterized mouse genetic models, DBA/2J and C57BL/6J, indicate that more than half of naturally-occurring SNPs remain cryptic. The magnitude of this problem is compounded when using more divergent or poorly annotated genetic models. This warrants full genomic sequencing of the mouse strains used as genetic models.</p

Diversity Outbred Mice at 21: Maintaining Allelic Variation in the Face of Selection

Multi-parent populations (MPPs) capture and maintain the genetic diversity from multiple inbred founder strains to provide a resource for high-resolution genetic mapping through the accumulation of recombination events over many generations. Breeding designs that maintain a large effective population size with randomized assignment of breeders at each generation can minimize the impact of selection, inbreeding, and genetic drift on allele frequencies. Small deviations from expected allele frequencies will have little effect on the power and precision of genetic analysis, but a major distortion could result in reduced power and loss of important functional alleles. We detected strong transmission ratio distortion in the Diversity Outbred (DO) mouse population on chromosome 2, caused by meiotic drive favoring transmission of the WSB/EiJ allele at the R2d2 locus. The distorted region harbors thousands of polymorphisms derived from the seven non-WSB founder strains and many of these would be lost if the sweep was allowed to continue. To ensure the utility of the DO population to study genetic variation on chromosome 2, we performed an artificial selection against WSB/EiJ alleles at the R2d2 locus. Here, we report that we have purged the WSB/EiJ allele from the drive locus while preserving WSB/EiJ alleles in the flanking regions. We observed minimal disruption to allele frequencies across the rest of the autosomal genome. However, there was a shift in haplotype frequencies of the mitochondrial genome and an increase in the rate of an unusual sex chromosome aneuploidy. The DO population has been restored to genome-wide utility for genetic analysis, but our experience underscores that vigilant monitoring of similar genetic resource populations is needed to ensure their long-term utility

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

Dissection of a QTL Hotspot on Mouse Distal Chromosome 1 that Modulates Neurobehavioral Phenotypes and Gene Expression

A remarkably diverse set of traits maps to a region on mouse distal chromosome 1 (Chr 1) that corresponds to human Chr 1q21–q23. This region is highly enriched in quantitative trait loci (QTLs) that control neural and behavioral phenotypes, including motor behavior, escape latency, emotionality, seizure susceptibility (Szs1), and responses to ethanol, caffeine, pentobarbital, and haloperidol. This region also controls the expression of a remarkably large number of genes, including genes that are associated with some of the classical traits that map to distal Chr 1 (e.g., seizure susceptibility). Here, we ask whether this QTL-rich region on Chr 1 (Qrr1) consists of a single master locus or a mixture of linked, but functionally unrelated, QTLs. To answer this question and to evaluate candidate genes, we generated and analyzed several gene expression, haplotype, and sequence datasets. We exploited six complementary mouse crosses, and combed through 18 expression datasets to determine class membership of genes modulated by Qrr1. Qrr1 can be broadly divided into a proximal part (Qrr1p) and a distal part (Qrr1d), each associated with the expression of distinct subsets of genes. Qrr1d controls RNA metabolism and protein synthesis, including the expression of ∼20 aminoacyl-tRNA synthetases. Qrr1d contains a tRNA cluster, and this is a functionally pertinent candidate for the tRNA synthetases. Rgs7 and Fmn2 are other strong candidates in Qrr1d. FMN2 protein has pronounced expression in neurons, including in the dendrites, and deletion of Fmn2 had a strong effect on the expression of few genes modulated by Qrr1d. Our analysis revealed a highly complex gene expression regulatory interval in Qrr1, composed of multiple loci modulating the expression of functionally cognate sets of genes

Treatment- and Population-Dependent Activity Patterns of Behavioral and Expression QTLs

Genetic control of gene expression and higher-order phenotypes is almost invariably dependent on environment and experimental conditions. We use two families of recombinant inbred strains of mice (LXS and BXD) to study treatment- and genotype-dependent control of hippocampal gene expression and behavioral phenotypes. We analyzed responses to all combinations of two experimental perturbations, ethanol and restraint stress, in both families, allowing for comparisons across 8 combinations of treatment and population. We introduce the concept of QTL activity patterns to characterize how associations between genomic loci and traits vary across treatments. We identified several significant behavioral QTLs and many expression QTLs (eQTLs). The behavioral QTLs are highly dependent on treatment and population. We classified eQTLs into three groups: cis-eQTLs (expression variation that maps to within 5 Mb of the cognate gene), syntenic trans-eQTLs (the gene and the QTL are on the same chromosome but not within 5 Mb), and non-syntenic trans-eQTLs (the gene and the QTL are on different chromosomes). We found that most non-syntenic trans-eQTLs were treatment-specific whereas both classes of syntenic eQTLs were more conserved across treatments. We also found there was a correlation between regions along the genome enriched for eQTLs and SNPs that were conserved across the LXS and BXD families. Genes with eQTLs that co-localized with the behavioral QTLs and displayed similar QTL activity patterns were identified as potential candidate genes associated with the phenotypes, yielding identification of novel genes as well as genes that have been previously associated with responses to ethanol

Genetic Control of a Central Pattern Generator: Rhythmic Oromotor Movement in Mice Is Controlled by a Major Locus near Atp1a2

Fluid licking in mice is a rhythmic behavior that is controlled by a central pattern generator (CPG) located in a complex of brainstem nuclei. C57BL/6J (B6) and DBA/2J (D2) strains differ significantly in water-restricted licking, with a highly heritable difference in rates (h2≥0.62) and a corresponding 20% difference in interlick interval (mean ± SEM = 116.3±1 vs 95.4±1.1 ms). We systematically quantified motor output in these strains, their F1 hybrids, and a set of 64 BXD progeny strains. The mean primary interlick interval (MPI) varied continuously among progeny strains. We detected a significant quantitative trait locus (QTL) for a CPG controlling lick rate on Chr 1 (Lick1), and a suggestive locus on Chr 10 (Lick10). Linkage was verified by testing of B6.D2-1D congenic stock in which a segment of Chr 1 of the D2 strain was introgressed onto the B6 parent. The Lick1 interval on distal Chr 1 contains several strong candidate genes. One of these is a sodium/potassium pump subunit (Atp1a2) with widespread expression in astrocytes, as well as in a restricted population of neurons. Both this subunit and the entire Na+/K+-ATPase molecule have been implicated in rhythmogenesis for respiration and locomotion. Sequence variants in or near Apt1a2 strongly modulate expression of the cognate mRNA in multiple brain regions. This gene region has recently been sequenced exhaustively and we have cataloged over 300 non-coding and synonymous mutations segregating among BXD strains, one or more of which is likely to contribute to differences in central pattern generator tempo