  The Minimum Path Cover problem on directed acyclic graphs (DAGs) is a
classical problem that provides a clear and simple mathematical formulation for
several applications in different areas and that has an efficient algorithmic
solution. In this paper, we study the computational complexity of two
constrained variants of Minimum Path Cover motivated by the recent introduction
of next-generation sequencing technologies in bioinformatics. The first problem
(MinPCRP), given a DAG and a set of pairs of vertices, asks for a minimum
cardinality set of paths "covering" all the vertices such that both vertices of
each pair belong to the same path. For this problem, we show that, while it is
NP-hard to compute if there exists a solution consisting of at most three
paths, it is possible to decide in polynomial time whether a solution
consisting of at most two paths exists. The second problem (MaxRPSP), given a
DAG and a set of pairs of vertices, asks for a path containing the maximum
number of the given pairs of vertices. We show its NP-hardness and also its
W[1]-hardness when parametrized by the number of covered pairs. On the positive
side, we give a fixed-parameter algorithm when the parameter is the maximum
overlapping degree, a natural parameter in the bioinformatics applications of
the problem.
