Bioinformatics, Volume I Data, Sequence Analysis and Evolution

3.1. Splice Graph
Representation of
Gene Structure Structure and
Alternative Alternative Splicing
Fig. 10.1. Splice graph representation
of gene structure
and alternative splicing. (A)
The exon-intron structure
of a three-exon gene. The
middle exon is alternatively
spliced. (B) The splice graph
representation of the gene
structure. Alternative splicing
of the second exon is
represented by a directed
edge from node 1 to node 3.
Reconstruction of Full-Length Isoforms from Splice Graphs 201
Conventionally, a gene structure is represented as a linear string
of exons (Fig. 10.1A), ordered according to the positions of
exons from 5′ to 3′. This simple representation, however, is insufficient
for the analyses of alternative splicing and the inference of
full-length isoforms. By definition, alternative splicing introduces
branches to the gene structure, disrupting the validity of a single
linear order of all exons.
In a pioneering study, Heber and colleagues introduced the
concept of “splice graph” (3), which is a directed acyclic graph
representation of gene structure. In the splice graph, each exon
is represented as a node, and each splice junction is represented
as a directed edge between two nodes (i.e., exons) (Fig. 10.1B).
Different types of alternative splicing events, such as exon skipping,
alternative 5′/3′ splicing, and intron retention, can be easily
represented using splice graphs. Fig. 10.2 shows the splice
graph of a multi-exon human gene TCN1. The observed exon
skipping event of exon 2 is represented as a directed edge from
node 1 to node 3. Similarly, the observed exon skipping event of
exon 5/6 is represented as a directed edge from node 4 to node
7. One EST from unspliced genomic DNA is represented as a
single isolated node of the splice graph (node 8). Under such a
representation, the isoform problem becomes a graph traversal
problem. Multiple traversals of the splice graph correspond to
multiple isoforms of a gene. Furthermore, the splice graph can
be weighted. The edge weight reflects the strength of experimental
evidence for a particular splice junction.
For EST data, this can be the number of ESTs on
which two exons are connected by a splice junction.
For microarray data, this can be the signal
intensity of a particular exon junction probe.
To construct a splice graph, we start from
sequence-based detection of exon-intron structure
and alternative splicing (which is described in
detail in the previous chapter). We treat each exon
as a node in the splice graph. Alternative donor/
acceptor splicing can produce two exon forms
with a common splice site at one end, and different
splice sites at the other end. We treat these two exon forms
as different nodes in the splice graph. Next, we go through each
expressed sequence to obtain edge information of the splice
graph. We connect two nodes with a directed edge if the two
exons are linked by a splice junction in the expressed sequences.
The edge weight is set as N if the connection between two
nodes is observed in N expressed sequences. In the end, we
obtain a directed acyclic graph (DAG). This graph represents all
splicing events of a gene and their numbers of occurrences in
the sequence data.