@article{Hiller:Huse:Szafranski:Singl_Polym_NAGNA:2006,
author = {Hiller, Michael and Huse, Klaus and Szafranski, Karol and 
          Jahn, Niels and Hampe, Jochen and Schreiber, Stefan and 
          Backofen, Rolf and Platzer, Matthias},
title = {Single-{Nucleotide} {Polymorphisms} in {NAGNAG} {Acceptors} 
         {Are} {Highly} {Predictive} for {Variations} of 
         {Alternative} {Splicing}},
journal = {Am J Hum Genet},
year = {2006},
doi = {10.1086/500151},
volume = {78},
user = {hiller},
publists = {Michael Hiller and Rolf Backofen and All},
pmid = {16400609},
pages = {291-302},
number = {2},
issn = {0002-9297},
abstract = {Aberrant or modified splicing patterns of genes are 
            causative for many human diseases. Therefore, the 
            identification of genetic variations that cause changes in 
            the splicing pattern of a gene is important. Elsewhere, we 
            described the widespread occurrence of alternative splicing 
            at NAGNAG acceptors. Here, we report a genomewide screen for 
            single-nucleotide polymorphisms (SNPs) that affect such 
            tandem acceptors. From 121 SNPs identified, we extracted 64 
            SNPs that most likely affect alternative NAGNAG splicing. We 
            demonstrate that the NAGNAG motif is necessary and 
            sufficient for this type of alternative splicing. The 
            evolutionarily young NAGNAG alleles, as determined by the 
            comparison with the chimpanzee genome, exhibit the same 
            biases toward intron phase 1 and single-amino acid 
            insertion/deletions that were already observed for all human 
            NAGNAG acceptors. Since 28% of the NAGNAG SNPs occur in 
            known disease genes, they represent preferable candidates 
            for a more-detailed functional analysis, especially since 
            the splice relevance for some of the coding SNPs is 
            overlooked. Against the background of a general lack of 
            methods for identifying splice-relevant SNPs, the presented 
            approach is highly effective in the prediction of 
            polymorphisms that are causal for variations in alternative 
            splicing.}
}