Adaptive immunity is mediated by T- and B-cells, which are immune cells capable of developing pathogen-specific memory that confers immunological protection. Memory and effector functions of B- and T-cells are predicated on the recognition through specialized receptors of specific targets (antigens) in pathogens. More specifically, B- and T-cells recognize portions within their cognate antigens known as epitopes. There is great interest in identifying epitopes in antigens for a number of practical reasons, including understanding disease etiology, immune monitoring, developing diagnosis assays, and designing epitope-based vaccines. Epitope identification is costly and time-consuming as it requires experimental screening of large arrays of potential epitope candidates. Fortunately, researchers have developed in silico prediction methods that dramatically reduce the burden associated with epitope mapping by decreasing the list of potential epitope candidates for experimental testing. Here, we analyze aspects of antigen recognition by T- and B-cells that are relevant for epitope prediction. Subsequently, we provide a systematic and inclusive review of the most relevant B- and T-cell epitope prediction methods and tools, paying particular attention to their foundations.

Correction of mis-splicing events is a growing therapeutic approach for neurological diseases such as spinal muscular atrophy or neuronal ceroid lipofuscinosis 7, which are caused by splicing-affecting mutations. Non-mutation harboring mis-spliced effector genes are also good candidate therapeutic targets in diseases with more complex etiologies such as cancer, autism, muscular dystrophies or neurodegenerative diseases. Next-generation RNA sequencing (RNA-seq) has boosted investigation of global mis-splicing in diseased tissue to identify such key pathogenic mis-spliced genes. Nevertheless, while analysis of tumour or dystrophic muscle biopsies can be informative on early stage pathogenic mis-splicing, for neurodegenerative diseases, these analyses are intrinsically hampered by neuronal loss and neuroinflammation in post-mortem brains. To infer splicing alterations relevant to Huntington’s disease (HD) pathogenesis, here we performed intersect-RNA-seq analyses of human post-mortem striatal tissue and of an early symptomatic mouse model in which neuronal loss and gliosis are not yet present. Together with a human/mouse parallel motif scan analysis, this approach allowed us to identify the shared mis-splicing signature triggered by the HD-causing mutation in both species and to infer upstream deregulated splicing factors. Moreover, we identified a plethora of downstream neurodegeneration-linked mis-spliced effector genes that -together with the deregulated splicing factors- become new possible therapeutic targets. In summary, here we report pathogenic global mis-splicing in HD striatum captured by our new intersect-RNA-seq approach that can be readily applied to other neurodegenerative diseases for which bona fide animal models are available.