A fusion gene is a hybrid gene that combines parts of two or more original genes. They can form as a result of chromosomal rearrangements (such as translocation, interstitial deletion, or chromosomal inversion) or abnormal transcription and have been shown to act as drivers of malignant transformation or/and progression in various neoplasms (1). The discovery and characterization of fusion genes hav been greatly facilitated by the use of NGS (2) and several computational algorithms have been developed to detect them.
This chapter covers will illustrate how to detect fusion genes by:
The Partek® Flow® fusion detection algorithm uses paired-end information to find pairs of genes that may express as a hybrid. A paired-end read is considered for a fusion event if:
The algorithm then reports peaks of reads that are potentially involved in a fusion event. Adjacent peaks are merged if their distance is less than 200 bp (default) and the probability that the peak is derived from the null distribution of peaks (determined by permutation) is reported. False positives hits are reduced by ignoring alignments that overlap with regions masked in the .2bit file. Finally, the peaks are annotated with a transcript model and a report is generated for pairs of peaks which map to different transcripts.
Partek algorithm can be invoked on a data node containing aligned paired-end reads (i.e. Aligned reads node), through the Detect fusion genes link in the Variant detection section of the toolbox (Figure 1).
First, the genome build that should be used for fusion gene detection needs to be specified (Figure 2).
The next dialog (Fusion options; Figure 3) allows for optimization of several parameters. Min distance between ends specifies the minimum distance (bp) between first in pair and second in pair reads to be considered for a fusion event, while Window gap (bp) defines the minimum distance that needs to be detected between two neighboring fusion candidates in order to label them as independent fusion events. The Annotation model is required to annotate the components of the fusion gene in the output table (see below).
As a result, a new data node (Fusion) will be created (Figure 4). Selecting the Fusion node opens the toolbox and the list of fusion genes can then be reached via the Task report link.
An example of the output, i.e. Fusion report, is shown in Figure 5. Each row of the table is a potential fusion event, with the columns providing the following information.
All the columns can be sorted by using the arrow buttons () in column headers.
TopHat-Fusion is a version of TopHat (see Chapter 6.1) with the ability to align reads across fusion points and detect fusion genes resulting from breakage and re-joining of two different chromosomes or from rearrangements within a chromosome (3). It is independent of gene annotation and can discover fusion products from known genes, unannotated splice variants of known genes or completely unknown genes.
The reads are first aligned to the genome and initially, unaligned reads are then split into multiple 25 bp sequences which are, in turn, aligned to the genome by Bowtie. TopHat-Fusion algorithm then identifies the cases where the first and the last 25 bp segment are aligned to either two different chromosomes or two locations on the same chromosome (spacing is defined by the user). The whole read is then used to identify a fusion point. After the initial fusion candidates are defined, all the segments from initially unaligned reads are realigned against the fusion points (as well as intron boundaries and indels) and the resulting alignments are combined to full read alignments.
The most up to date TopHat-Fusion version implemented in Partek Flow when the manual was written (2.0.8) focuses on fusions due to chromosomal rearrangements, while fusions resulting from read-through transcription or trans-splicing were not supported. TopHat-Fusion can handle both paired- and single-end reads, but the support of color-space reads is still pending. For details as well as discussion of TopHat-Fusion options, see TopHat-Fusion home page (4).
TopHat-Fusion is integrated with TopHat 2 and fusion detection is activated by using the Fusion search check box in the TopHat 2 Alignment options dialog (Figure 6).
The output is associated with the Fusion results data node (Figure 7), which is a part of TopHat 2 results (in addition to Aligned reads node and, optionally, Unaligned reads node).
Selecting the Fusion results node opens the toolbox, with Variant detection options (Figure 8).
Fusion report displays an annotated report on detected fusion genes. For that purpose an annotation file needs to be specified first (Figure 9).
The result of annotation is the Fusion report task node as seen in Figure 10.
The list of annotated fusion genes, in a form of Fusion report (Figure 11), can be obtained by first selecting the Fusion report task node and then the Task report link from the toolbox. Each row of the table in Figure 11 is a potential fusion event, with the columns providing the following information.
All the columns can be sorted by using the arrow buttons () in column headers.
Moreover, Fusion attribute report, when invoked from the Fusion results node, displays a report on attributes of detected fusion genes. Attributes to be tested for association with the fusion should be specified first (Figure 12).
A new data node, Fusion attribute report, is generated in the Analysis tab (Figure 13) and it provides access to the Task report link in the toolbox.
The output, Fusion report table (Figure 14) resembles the basic TopHat-Fusion output (Figure 11); each row of the table is a single fusion event and three right-most columns are as follows:
STAR Algorithm
STAR aligner (see Chapter 6.1) also has the ability to detect fusion genes (referred to as “chimeric alignments”) (5). During the first phase of alignment, STAR searches for maximal mappable prefixes (seeds) of sequencing reads. In the second phase, all the seeds that align within user-defined genomic windows are stitched together. If an alignment within one genomic window does not cover the entire read sequence, STAR will try to find two or more windows that cover the entire read. This essentially results in detection of fusion events, with different parts of reads aligning to distal genomic locations, or different chromosomes, or different strands.
The most up to date STAR version implemented in Partek Flow when the manual was written (2.3.0) aligns both paired- and single-end reads. Color-space reads are not supported.
STAR fusion detection algorithm is integrated with STAR aligner and fusion detection is activated by tick-marking Chimeric alignment option in the Advanced options of the aligner (the Advanced options dialog is reached via Configure link in the setup dialog). As soon as the Chimeric alignment is selected, additional options, specific to the fusion search algorithm, are shown (Figure 15). For discussion on the options details, see STAR documentation.
The output is associated with the Chimeric results data node (Figure 16), which is a part of STAR results (in addition to Aligned reads node and, optionally, Unaligned reads node).
Selecting the Chimeric results node opens the toolbox, with Variant detection options (Figure 17).
Fusion report displays an annotated report on detected fusion genes. For that purpose, an annotation file needs to be specified first (Figure 18).
The result of annotation is the Fusion report task node as seen in Figure 19.
The list of annotated fusion genes, in a form of Fusion report (Figure 20), can be obtained by first selecting the Fusion report task node and then the Task report link from the toolbox. Each row of the table in Figure 20 is a potential fusion event, with the columns providing the following information.
All the columns can be sorted by using the arrow buttons () in column headers.
Moreover, Fusion attribute report, when invoked from the Chimeric results node, displays a report on attributes of detected fusion genes. Attributes to be tested for association with the fusion should be specified (Figure 21).
A new data node, Fusion attribute report, is generated in the Analysis tab (Figure 22) and it provides access to the Task report link in the toolbox.
The output, Fusion report table (Figure 23) resembles the basic TopHat-Fusion output (Figure 11); each row of the table is a single fusion event and three right-most columns are as follows:
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