model {
for (i in 1:5) {
y[i] ~ dnorm(mu[i], tau)
mu[i] <- alpha + beta*(x[i] - mean(x[]))
}
alpha ~ dflat()
beta ~ dflat()
tau <- 1/sigma2
log(sigma2) <- 2*log.sigma
log.sigma ~ dflat()
}

Data:
list(y = c(177,236,285,350,376), x = c(8,15,22,29,36))

Inits:
list(alpha=250,beta=0,log.sigma=0)

node mean sd MC error 2.5% median 97.5% start sample
alpha 284.8 7.89 0.078 269.9 284.8 300.1 4001 10000
beta 7.316 0.7814 0.008582 5.82 7.316 8.819 4001 10000
sigma2 316.3 743.6 26.14 37.24 145.6 1586.0 4001 10000