ABSTRACT
Diversity of B and T cell receptors, achieved by gene recombination and somatic hypermutation, allows the immune system for recognition and targeted reaction against various threats. Next-generation sequencing for assessment of a cell's gene composition and variation makes deep analysis of one individual's immune spectrum feasible. An easy to apply but detailed analysis and visualization strategy is necessary to process all sequences generated. We performed sequencing utilizing the 454 system for CLL and control samples, utilized the IMGT database and applied the presented analysis tools. With the applied protocol, malignant clones are found and characterized, mutational status compared to germline identity is elaborated in detail showing that the CLL mutation status is not as monoclonal as generally thought. On the other hand, this strategy is not solely applicable to the 454 sequencing system but can easily be transferred to any other next-generation sequencing platform.
Subject(s)
Genome, Human , High-Throughput Nucleotide Sequencing/standards , Leukemia, Lymphocytic, Chronic, B-Cell/genetics , Receptors, Antigen, B-Cell/genetics , Receptors, Antigen, T-Cell/genetics , Base Sequence , Case-Control Studies , Clone Cells , Germ-Line Mutation , Humans , Leukemia, Lymphocytic, Chronic, B-Cell/immunology , Leukemia, Lymphocytic, Chronic, B-Cell/pathology , Molecular Sequence Data , Phylogeny , Receptors, Antigen, B-Cell/classification , Receptors, Antigen, B-Cell/immunology , Receptors, Antigen, T-Cell/classification , Receptors, Antigen, T-Cell/immunology , Sequence Alignment , Sequence Homology, Nucleic AcidABSTRACT
BACKGROUND: Next-generation sequencing allows for determining the genetic composition of a mixed sample. For instance, when performing resistance testing for BCR-ABL1 it is necessary to identify clones and define compound mutations; together with an exact quantification this may complement diagnosis and therapy decisions with additional information. Moreover, that applies not only to oncological issues but also determination of viral, bacterial or fungal infection. The efforts to retrieve multiple haplotypes (more than two) and proportion information from data with conventional software are difficult, cumbersome and demand multiple manual steps. RESULTS: Therefore, we developed a tool called cFinder that is capable of automatic detection of haplotypes and their accurate quantification within one sample. BCR-ABL1 samples containing multiple clones were used for testing and our cFinder could identify all previously found clones together with their abundance and even refine some results. Additionally, reads were simulated using GemSIM with multiple haplotypes, the detection was very close to linear (R(2) = 0.96). Our aim is not to deduce haploblocks over statistics, but to characterize one sample's composition precisely. As a result the cFinder reports the connections of variants (haplotypes) with their readcount and relative occurrence (percentage). Download is available at http://sourceforge.net/projects/cfinder/. CONCLUSIONS: Our cFinder is implemented in an efficient algorithm that can be run on a low-performance desktop computer. Furthermore, it considers paired-end information (if available) and is generally open for any current next-generation sequencing technology and alignment strategy. To our knowledge, this is the first software that enables researchers without extensive bioinformatic support to designate multiple haplotypes and how they constitute to a sample.