Allelic series of Huntington's disease knock-in mice reveals expression discorrelates

Abstract

Identifying molecular drivers of pathology provides potential therapeutic targets. Differentiating between drivers and coincidental molecular alterations presents a major challenge. Variation unrelated to pathology further complicates transcriptomic, proteomic and metabolomic studies which measure large numbers of individual molecules. To overcome these challenges towards the goal of determining drivers of Huntington's disease (HD), we generated an allelic series of HD knock-in mice with graded levels of phenotypic severity for comparison with molecular alterations. RNA-sequencing analysis of this series reveals high numbers of transcripts with level alterations that do not correlate with phenotypic severity. These discorrelated molecular changes are unlikely to be drivers of pathology allowing an exclusion-based strategy to provide a short list of driver candidates. Further analysis of the data shows that a majority of transcript level changes in HD knock-in mice involve alteration of the rate of mRNA processing and/or degradation rather than solely being due to alteration of transcription rate. The overall strategy described can be applied to assess the influence of any molecular change on pathology for diseases where different mutations cause graded phenotypic severity.

Figure 1.

Molecular aspects of the HD knock-in allelic series. (A) PCR across the repeats of genomic DNA from tail biopsies. Lanes 1–8 represent MW ladder, WT and heterozygotes for 50, 100, 150, 200, 250 and 315 CAGs in the mouse HD gene, respectively. (B) Striatal HD mRNA levels of long repeat mRNAs relative to wild type as determined by allele-specific HD QRTPCR. Levels in homozygotes was halved to provide mRNA level per allele. Each assay performed in triplicate and results normalized to β-actin mRNA levels of same sample. White, gray and black shading indicates WT, heterozygous and homozygous for expanded allele, respectively. Error bars indicate standard error of the mean and asterisks show level of statistical certainty versus line ∼100 CAGs shorter as determined by ANOVA with Tukey–Kramer multiple comparisons test (*P < 0.05, **P < 0.01, ***P < 0.001). Number of mice is shown at the base of each bar. (C) Western blot analyses of striatal protein from allelic series. Lanes 1–7 represent WT, 50, 100, 150, 200 homozygotes, 250 and 315 heterozygotes, respectively. Top panel shows detection with the anti-polyglutamine antibody 1C2, middle shows the same blot after stripping and detection with the anti-HD antibody 2166 and lower with anti-α-tubulin antibody. Filled arrowheads indicate the expected migration of wild-type Huntingtin protein (345 kDa) and open arrowhead indicates expected migration of α-tubulin (50 kDa).

Figure 2.

Transgene mRNA levels from the R6 HD allelic series. (A) R6 transgene mRNA copies per nanogram of whole brain RNA at 6 weeks of age using a transgene-specific QRTPCR assay. All R6 mice were hemizygous for transgene which is inserted in the same unknown location of the genome for all lines in the series. (B) HD mRNA copies per nanogram of whole brain RNA at 6 weeks of age weeks for HDQ50 and HDQ100 knock-in homozygotes by QRTPCR across exon2,3 junction. Absolute numbers of cDNAs present in each sample were calculated by interpolation to a standard curve of known amounts of DNA template for R6 or endogenous mouse HD. Number of mice is shown at the base of each bar. Error bars indicate standard error of the mean. Unless annotated asterisks reflect comparison with measures two bars to left (typically 100 CAGs shorter) as determined by ANOVA with Tukey–Kramer multiple comparisons test (*P < 0.05, **P < 0.01, ***P < 0.001). ^acompared with all other transgenic R6 lines shown including 50s. ^bcompared with HDQ50s.

Figure 3.

Longitudinal evaluation of behavioral abnormalities of the HDQ315 line at different ages. (A) Accelerating rotarod. (B) Time to traverse horizontal ladder in automated foot misplacement apparatus. (C) In cage activity (lower beam breaks per 24 h period). (D) Open field distance traveled per 4-min trial. (E) Voluntary wheel cage distance traveled per 24 h period. (F) Four paw grip strength. Open and gray bars represent mean of WT and HDQ315/+ mice, respectively. Error bars indicate standard error of the mean and number of mice in each group shown at base of bar. Groups contain approximately equal numbers of males and females. Statistical differences between WT and HDQ315/+ groups at same age as determined by t-test shown above bar (*P < 0.05, **P < 0.01 and ***P < 0.001). Statistically significant differences within the HDQ315/+ group between 30-week-old and both 50 and 65 weeks old were found for all six tests shown (P < 0.05 by Kruskal–Wallis non-parametric ANOVA with Dunn's multiple comparison test) showing progression of abnormality with age.

Figure 4.

Neuroanatomic and neurochemical features of the HDQ315 line. (A) HDQ315/+ mice have reduced brain weight at 70 weeks of age. (B–D) HDQ315/+ mice show reduction in striatal volume, increase in striatal neuronal density and no loss of NeuN+ striatal neurons at 70 weeks of age. (E and F) HDQ315/+ mice show reductions in D1 and D2 receptors binding at 35 and 70 weeks of age. Open bars indicate WT mice and gray bars HDQ315/+ mice. Number of mice in each group is shown at base of bar. Asterisks indicate significant difference from wild type (* P < 0.05, **P < 0.01 and ***P < 0.001) by t-test. (H) Aggregates immunoreactive to anti-HD antibody in 70-week-old HDQ315/+ striatum that are not present in age-matched WT controls (G). Bar indicates 20 µm.

Figure 5.

Comparison of phenotypic severity of HDQ150/150, HDQ315/+ and HDQ200/200 lines. (A) Body weight normalized to wild-type mice of same age and sex. Black triangles represent HDQ150/150 mice (each point n = 13–22 except 80 weeks n = 9). Gray circles represent HDQ315/+ mice (n = 13 to 29) and black squares represent 200/200 mice (n = 3–7). (B) Rotarod performance normalized to wild-type mice of same age. Black triangles represent HDQ150/150 mice (each point n = 10 except 26 weeks n = 31). Gray circles represent HDQ315/+ mice (n = 29–31) and black squares represent HDQ200/200 mice (n = 3). (C) In cage mouse activity normalized to wild-type mice of same age. Black triangles represent HDQ150/150 mice (each point n = 7–15 except 26 weeks n = 20). Gray circles represent HDQ315/+ mice (n = 29–31) and black squares represent HDQ200/200 mice (n = 3). Asterisks show statistical significance compared with HDQ315/+ mice of most similar age by t-test (*P < 0.05, **P < 0.01 and ***P < 0.001). Approximately equal numbers of male and female mice were used for each point. ‘a’ indicates our previously published data adapted from (13). Lines determined by method of least squares. In each panel, upper, middle and lower lines represent HDQ150/150, HDQ315/+ and HDQ200/200 mice, respectively.

Figure 6.

Expression correlates and discorrelates revealed by RNA-sequencing analysis. (A–F) Ordering of lines based on increasing phenotypic severity. Darker shading in arrows represents increased phenotypic severity. Bars represent striatal FPKM values of all isoforms of each gene from left to right of WT (open), HDQ150/150 (black), HDQ315/+ (gray) and HDQ200/200 (black). Definitions of correlate and discorrelate classes provided in Materials and Methods. (A–C) Examples of mRNAs with levels that correlate with phenotypic severity. (D–F) Examples of mRNAs with levels that discorrelate with phenotypic severity. (G–L) Ordering of lines based on increasing mutant gene dosage. Numbers in arrows indicate mutant gene dosage. Bars represent striatal FPKM values of all isoforms of each gene from left to right of WT (open), HDQ315/+ (gray), HDQ200/200 (black) and HDQ150/150 (black). Definition of correlate and discorrelate classes provided in Materials and Methods. (G–I) Examples of mRNAs with levels that correlate with mutant gene dosage. (J–L) Examples of mRNAs with levels that discorrelate with mutant gene dosage. Asterisks indicate p values calculated by Cuffdiff software based on dispersion model of variances (*P < 0.05, **P < 0.01, ***P < 0.001). Table 3 contains a complete list of all correlates and discorrelates that have statistical support.

Figure 7.

Levels of striatal mRNA from three commonly used markers of HD in mice. Bars represent mean mRNA levels relative to WT as determined by QRTPCR using is β-actin as an internal control. Darker shading in arrows represents increased phenotypic severity. Open bars indicate WT, grey heterozygous and black homozygous for expanded CAG repeat allele. The number of mice is shown at the base of each bar. RNA from each mouse analyzed individually to provide directly calculated statistics. Error bars show the standard error of the mean, asterisks above brackets indicate statistical significance by ANOVA with Tukey–Kramer multiple comparisons test. Asterisks directly above bars indicate significant difference from WT based on ANOVA with Dunnett multiple comparisons test (*P < 0.05, **P < 0.01 and ***P < 0.001).