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- Ke, Rongqin, et al.
(author)
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Fourth Generation of Next-Generation Sequencing Technologies : Promise and Consequences
- 2016
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In: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 37:12, s. 1363-1367
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Research review (peer-reviewed)abstract
- In this review, we discuss the emergence of the fourth-generation sequencing technologies that preserve the spatial coordinates of RNA and DNA sequences with up to subcellular resolution, thus enabling back mapping of sequencing reads to the original histological context. This information is used, for example, in two current large-scale projects that aim to unravel the function of the brain. Also in cancer research, fourth-generation sequencing has the potential to revolutionize the field. Cancer Research UK has named Mapping the molecular and cellular tumor microenvironment in order to define new targets for therapy and prognosis one of the grand challenges in tumor biology. We discuss the advantages of sequencing nucleic acids directly in fixed cells over traditional next-generation sequencing (NGS) methods, the limitations and challenges that these new methods have to face to become broadly applicable, and the impact that the information generated by the combination of in situ sequencing and NGS methods will have in research and diagnostics.
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| 2. |
- Ali, Heidi, et al.
(author)
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Performance of Protein Disorder Prediction Programs on Amino Acid Substitutions
- 2014
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In: Human Mutation. - : Hindawi Limited. - 1059-7794. ; 35:7, s. 794-804
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Research review (peer-reviewed)abstract
- Many proteins contain intrinsically disordered regions, which may be crucial for function, but on the other hand be related to the pathogenicity of variants. Prediction programs have been developed to detect disordered regions from sequences and used to predict the consequences of variants, although their performance for this task has not been assessed. We tested the performance of protein disorder prediction programs in detecting changes to disorder caused by amino acid substitutions. We assessed the performance of 29 protein disorder predictors and versions with 101 amino acid substitutions, whose effects have been experimentally validated. Disorder predictors detected the true positives at most with 6% success rate and true negatives with 34% rate for variants. The corresponding rates for the wild-type forms are 7% and 90%, respectively. The analysis revealed that disorder programs cannot reliably predict the effects of substitutions; consequently, the tested methods, and possibly similar programs, cannot be recommended for variant analysis without other information indicating to the relevance of disorder. These results inspired us to develop a new method, PON-Diso (http://structure.bmc.lu.se/PON-Diso), for disorder-related amino acid substitutions. With 50% success rate for independent test set and 70.5% rate in cross-validation, it outperforms the evaluated methods.
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