Table 2.
Model | ||||
---|---|---|---|---|
(1) E[log2(WBSCR17i + 1)] = 0.432 + 1.101 * Cfa6.7i + 0.6 * Ri + 0.374 * PC1i – 0.099 * PC2ia | ||||
Estimate | Std. Error | t Value | P-value | |
(Intercept) | 0.432 | 0.163 | 2.655 | 0.0161 |
Locus | 1.101 | 0.264 | 4.176 | 0.000568 |
RNAseq2 | 0.600 | 0.230 | 2.609 | 0.0178 |
PC1 | 0.374 | 0.500 | 0.751 | 0.4626 |
PC2 | −0.099 | 0.468 | −0.211 | 0.8354 |
(2) E[log2 (WBSCR27i + 1)] = 0.854 − 0.637 * Cfa6.66i + 0.552 * Ri – 1.074 * PC1i – 0.406 * PC2ia | ||||
Estimate | Std. Error | t Value | P-value | |
(Intercept) | 0.854 | 0.217 | 3.929 | 0.0010 |
Locus | −0.637 | 0.199 | −3.200 | 0.00499 |
RNAseq2 | 0.552 | 0.243 | 2.268 | 0.0359 |
PC1 | −1.074 | 0.555 | −1.933 | 0.0691 |
PC2 | −0.406 | 0.552 | −0.736 | 0.4713 |
(3) E[log2(RPL37i + 1)] = 3.029 + 1.944 * Cfa6.24i + 3.355 * Ri – 2.168 * PC1i – 0.921 * PC2ia | ||||
Estimate | Std. Error | t Value | P-value | |
(Intercept) | 3.029 | 0.624 | 4.851 | 0.0001 |
Locus | 1.944 | 0.456 | 4.262 | 0.000469 |
RNAseq2 | 3.355 | 0.488 | 6.880 | 0.000002 |
PC1 | −2.168 | 1.240 | −1.748 | 0.0975 |
PC2 | −0.921 | 1.113 | −0.827 | 0.4189 |
(4) E[log2(LIMK1i + 1)] = 0.123 + 0.420 * Cfa6.7i + 0.153 * Ri – 0.326 * PC1i – 0.352 * PC2ia | ||||
Estimate | Std. Error | t Value | P-value | |
(Intercept) | 0.123 | 0.084 | 1.469 | 0.1592 |
Locus | 0.420 | 0.136 | 3.085 | 0.00638 |
RNAseq2 | 0.153 | 0.119 | 1.288 | 0.2141 |
PC1 | −0.326 | 0.257 | −1.266 | 0.2217 |
PC2 | 0.352 | 0.241 | 1.459 | 0.1617 |
(5) E[log2 (BCL7Bi + 1)] = 2.218 − 0.582 * Cfa6.9i + 0.497 * Ri + 1.077 * PC1i – 0.916 * PC2ia | ||||
Estimate | Std. Error | t Value | P-value | |
(Intercept) | 2.218 | 0.350 | 6.345 | 0.00001 |
Locus | −0.582 | 0.193 | −3.011 | 0.00751 |
RNAseq2 | 0.497 | 0.197 | 2.529 | 0.0210 |
PC1 | 1.077 | 0.399 | 2.697 | 0.0147 |
PC2 | 0.916 | 0.383 | 2.389 | 0.0280 |
(6) E[log2(BAZ1B2i + 1)]% = -0.215 + 1.44Cfa6.41i + 0.227Ri + 1.936PC1i – 0.996PC2ia | ||||
Estimate | Std. Error | t Value | P-value | |
(Intercept) | −0.215 | 0.392 | −0.548 | 0.5902 |
Locus | 1.440 | 0.492 | 2.926 | 0.00901 |
RNAseq2 | 0.227 | 0.507 | 0.447 | 0.6599 |
PC1 | 1.936 | 1.292 | 1.498 | 0.1515 |
PC2 | −0.996 | 1.099 | −0.906 | 0.3768 |
NOTE.—Additional covariates were included adjust for potential confounding: two principle components (PC1 and PC2) to account for genetic structure and RNA-seq method (R) to account for batch effects. All models except model 3 (log2(RPL37i + 1)) demonstrate a good fit with the underlying modeling assumptions.
Equations represent the expected log2 (TPM + 1) value for wolf i as predicted by the locus and additional coefficients.
BAZ1Bi = ENSCAFT00000046458.2.