VDJSeq-Solver is a completely automated workflow for the in silico detection of the main clone V(D)J recombination sequence characterizing neoplastic tissues, using RNA-Seq paired-end reads.
B-cells and T-cells are different from other cells in the fact that their genomes bear a genomic birthmark of diversity. They can expand under specific conditions and form monoclonal populations bearing identically rearranged gene segments. These clonal populations are usually under tight control mechanisms. However, under special occasions they might expand to an extent which causes a disease, such as in autoimmune disorders, leukemias and lymphomas: It is nowadays note that knowing the precise sequence of rearranged BCR genes provides lots of useful information both from an investigative and from a clinical point of view.
Among Next Generation Sequencing (NGS) approaches, RNA sequencing (RNA-Seq) can theoretically identify sequences and quantitate every RNA fragment present in a sample. In theory, it should be an ideal method to identify clonal lymphocyte populations (also in the context of a polyclonal background), since the number of reads mapping to the genes rearranged in the neoplastic clone should be much larger than those mapping to other BCR or TCR genes. Moreover, precise information concerning the rearranged BCR or TCR genes of the dominant clone should be available at the same time, therefore promising to be the most complete clonality test.
Using a set of paired-end RNA-Seq reads, derived from the sequencing of lymphoma mRNA samples, VDJSeq-Solver firstly identifies the main clone characterizing the tissue of interest by detecting the most amplificated V(D)J rearrangement of the sample under study. Then considering how reads are mapped on the V, D and J alleles involved in the selected rearrangement, the specific sequence of the clone is reconstructed.
