  We introduce a new oriented evolving graph model inspired by biological
networks. A node is added at each time step and is connected to the rest of the
graph by random oriented edges emerging from older nodes. This leads to a
statistical asymmetry between incoming and outgoing edges. We show that the
model exhibits a percolation transition and discuss its universality. Below the
threshold, the distribution of component sizes decreases algebraically with a
continuously varying exponent depending on the average connectivity. We prove
that the transition is of infinite order by deriving the exact asymptotic
formula for the size of the giant component close to the threshold. We also
present a thorough analysis of aging properties. We compute local-in-time
profiles for the components of finite size and for the giant component, showing
in particular that the giant component is always dense among the oldest nodes
but invades only an exponentially small fraction of the young nodes close to
the threshold.
