Age and diet shape the genetic architecture of body weight in diversity outbred mice

  1. Kevin M Wright
  2. Andrew G Deighan
  3. Andrea Di Francesco
  4. Adam Freund
  5. Vladimir Jojic
  6. Gary A Churchill  Is a corresponding author
  7. Anil Raj  Is a corresponding author
  1. Calico Life Sciences LLC, United States
  2. The Jackson Laboratory, United States
7 figures, 1 table and 1 additional file

Figures

Figure 1 with 1 supplement
Study design and body weight data summaries.

(A) Outline of study design. (B) Median (interquartile range) body weight in grams and (C) median (interquartile range) growth rate in grams per day for five dietary treatments from 60 to 660 days …

Figure 1—figure supplement 1
Raw phenotype measurements.

Body weight and growth rate trends as a function of age. Mice in this study also underwent an array of phenotyping procedures; the age range for metabolic cage phenotyping is highlighted in pink, …

Illustrating diet-dependent association between genetic and phenotypic similarities.

Phenotypic divergence between animal pairs is quantified by the covariance in body weight at 500 days of age. We plot the cumulative density of body weight covariance for all pairs of animals in the …

Evaluating gene–environment mixed mode (G×EMM) and EMMA using simulated datasets.

(A). Comparison of true PVEtot to that estimated from EMMA (left panel) and G×EMM (right panel). Simulations were run with an equal number of samples in each environment (Ne1=Ne2) and with the same value for …

Figure 4 with 6 supplements
Proportion of phenotypic variance explained by genetics.

(A) Body weight proportion of phenotypic variance explained by genetics (PVE) (± SE) for 30–660 days of age. Total PVE estimates are derived from the EMMA (light gray) and gene–environment mixed …

Figure 4—figure supplement 1
Proportion of phenotypic variance explained by genetics (PVE) using raw measurements.

PVE (±SE) of (A) Body weight and (B) growth rate, estimated using raw body weight measurements.

Figure 4—figure supplement 2
Proportion of phenotypic variance explained by genetics (PVE) overlayed with phenotyping.

PVE (± SE) of (A) Body weight and (B) growth rate, overlayed with the timing of bouts of phenotyping.

Figure 4—figure supplement 3
Sensitivity of proportion of phenotypic variance explained by genetics (PVE).

(A) PVE (± SE) (left column) and expected phenotypic variance (±SE) (right column) estimated using kinship calculated from founder-of-origin allele probabilities (top row) and biallelic genotypes …

Figure 4—figure supplement 4
Proportion of phenotypic variance explained by genetics (PVE) with no constraints on variance components.

PVE (±SE) of body weight was estimated without imposing any non-negativity constraints on the variance components in the gene–environment mixed mode (G×EMM) model.

Figure 4—figure supplement 5
Proportion of phenotypic variance explained by genetics (PVE) comparing full and diagonal Ω.

PVE (± SE) of body weight was estimated with and without a diagonal constraint on Ω.

Figure 4—figure supplement 6
Proportion of phenotypic variance explained by genetics (PVE) decomposition.

Decomposing the total and diet-dependent PVE into contributions from diet terms (diamonds) and contributions from generation terms (x-markers).

Figure 5 with 4 supplements
Distinct founder allele patterns (FAPs) contribute to diet-independent and diet-dependent effects on body weight within a region on chromosome 6.

(A) Manhattan plots of additive genetic associations and genotype–diet associations on chromosome 6 at multiple ages. (B, D) Fine-mapping loci associated with body weight: diet-independent …

Figure 5—figure supplement 1
Age- and diet-dependent Manhattan plots for body weight, with gene–environment mixed mode (G×EMM).

Genetic loci associated with body weight, using G×EMM, at different ages identified under the additive genetic model (subpanels on the left) and genotype–diet interaction model (subpanels on the …

Figure 5—figure supplement 2
Age- and diet-dependent Manhattan plots for body weight, with EMMA.

Genetic loci associated with body weight, using EMMA, at different ages identified under the additive genetic model (subpanels on the left) and genotype–diet interaction model (subpanels on the …

Figure 5—figure supplement 3
Loci with significant diet-independent and diet-dependent associations with body weight.

(A) Fine-mapping a locus on chromosome 1 associated with body weight under the additive model (left column) and genotype–diet interaction model (right column). Each circle is a biallelic variant, …

Figure 5—figure supplement 4
Distinct founder allele patterns (FAPs) drive diet-independent and diet-dependent associations with body weight at various loci.

(A) Fine-mapping a locus on chromosome 3 associated with body weight under the additive model (left column) and genotype–diet interaction model (right column). Each circle is a biallelic variant, …

Multiple founder allele patterns (FAPs) at a body weight QTL on chromosome 12 show distinct diet-dependent effects.

(A) Fine-mapping loci, under the interaction model, at 420 days of age. Significant variants are marked as solid circles. Colors denote variants with shared FAPs; ranks 1, 2, and 3 by logarithm of …

Figure 7 with 2 supplements
Body weight loci on chromosome 6 exhibit age- and diet-specific effects.

(A) Log odds ratio of additive body weight association as a function of age for the lead variant from each founder allele pattern (FAP) group. Red, orange, and yellow colors denote lead variant for …

Figure 7—figure supplement 1
Diet-dependent association with body weight in a locus on chromosome 5.

(A) Manhattan plots of additive genetic associations and genotype–diet associations on chromosome 5 at multiple ages. (B) Fine-mapping a locus associated with body weight in diet-dependent manner at …

Figure 7—figure supplement 2
Nonlinear trends in genetic effects with respect to age and dietary intervention.

For each fine-mapped locus (A-G), we note the location of the variant with the strongest association and the ages at which the genetic association is significant and plot the estimated effect (SE) …

Tables

Table 1
Candidate diet-independent and diet-dependent body weight loci.

For each locus, we identified the variant with the lowest p-value at any age, the founder allele pattern (FAP) of this variant, the number of significant variants that comprise this lead FAP, the …

FAP position (Mb)Significant variantsSignificant age range (days)Age-dependent nonlinearityLead candidate genes (if ≤3)
ChrmFounder Allele Pattern (FAP)FAP rankp-ValueStartEndTotalOpen chromatin
Diet-independent
1AJ/NOD13.24E-05**152.046626152.04662611601.44E-05Trmt1l, Edem3
AJ/NOD/12923.05E-05**151.473677152.280212581060
2129/CAST/PWK12.17E-05**77.15496277.357295808120–3602.83E-09Ccdc141, Sestd1
3AJ/NOD/NZO/CAST11.89E-05**50.53359950.59507355200–2605.03E-12Slc7a11
4AJ16.81E-06***58.95036460.26712852260–3603.82E-19Ugcg
PWK/WSB22.80E-05**59.46124859.981846393100–300
6AJ/NOD12.75E-07***53.6176155.55597789260–2001.55E-26Creb5
7B6/CAST14.20E-06***71.37500772.78684947180–1602.48E-11Mctp2
7AJ/129/NZO/PWK15.70E-06***134.08785134.70446520280–2009.17E-10Adam12
10129/NZO/PWK/WSB14.99E-06***9.0780549.0780541540–6609.52E-06Samd5
129/NZO/WSB22.25E-05**8.9033879.092694102540Sash1, Samd5
10CAST/PWK15.98E-06***91.16319191.9052872,77981120–6604.09E-10Anks1b, Apaf1
11AJ/NZO/PWK/CAST15.89E-05**58.15542458.1554241802.35E-05
B6/CAST24.91E-05**56.98564559.0353096037080–100
12NZO/CAST16.47E-05**99.52055999.907182433160–2603.83E-12Foxn3
15B6/129/NZO14.77E-07***99.39060399.652959220260–6001.50E-13Aqp2, Aqp5, Aqp6
17AJ/NOD/WSB18.56E-06***6.7532778.853111491160–4201.23E-10Pde10a
19AJ/129/NZO/PWK17.90E-05**23.02504323.17612581480–1204.46E-09Trpm3, Klf9
Diet-dependent
1NOD/CAST14.89E-04*151.032114153.716837283360–6603.32E-04
2AJ/CAST/PWK/WSB17.74E-04*22.19222222.786648684801.32E-04
2PWK13.34E-04*73.59014275.3715641,67244280–3004.62E-03
3NOD/CAST/PWK/WSB13.87E-05**50.18474650.4198215420–6607.90E-04Slc7a11
3B6/PWK18.29E-05**156.74554156.7455416601.60E-05Negr1
129/CAST/WSB27.33E-04*156.133466156.3878251708660
4129/NOD/PWK19.61E-04*57.69630157.846521012005.10E-07Palm2, Pakap, Akap2
NOD29.76E-04*57.66982757.6698271200
5NOD13.88E-05**19.21390421.5700715316420–6602.26E-03Magi2, Ptpn12
5PWK15.84E-04*68.98665570.490341277360–4802.28E-03Kctd8
5AJ/129/NOD/WSB14.00E-05**117.543498118.0504537480–5401.55E-03
B6/CAST/PWK21.04E-04*116.797769118.2707456910360–600
6B6/CAST/PWK11.04E-04*54.14613255.452827507101540–6607.51E-04Ghrhr
6B6/CAST11.68E-05**139.190506140.1416941115240–4209.63E-03Pik3c2g
7NZO/PWK19.60E-04*133.838117133.92402321834203.19E-07Adam12
12AJ/B616.29E-04*78.0610279.734912102420–5404.23E-04Gphn
WSB29.84E-04*78.10798878.9328421228360–420Gphn
12AJ/CAST/PWK/WSB13.53E-04*102.447268102.56532434420–4802.59E-05
13NZO/WSB11.00E-04**117.100864118.777463991200–3001.14E-03Fgf10
15AJ/129/NOD13.52E-04*10.73803412.040137534240–3001.27E-04
17B6/129/NZO17.52E-04*6.7558657.598818263300–3603.23E-03
18129/CAST13.86E-04*71.3608771.58844161480–5406.92E-03Dcc
19AJ/B6/WSB11.24E-04*21.80666522.051277321220–3003.54E-03

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