Rossi, Rachele;
Fang, Mingyan;
Zhu, Lin;
Jiang, Chongyi;
Yu, Cong;
Flesia, Cristina;
Nie, Chao;
... Ferlini, Alessandra; + view all
(2022)
Calculating and comparing codon usage values in rare disease genes highlights codon clustering with disease-and tissue- specific hierarchy.
PLoS One
, 17
(3)
, Article e0265469. 10.1371/journal.pone.0265469.
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Abstract
We designed a novel strategy to define codon usage bias (CUB) in 6 specific small cohorts of human genes. We calculated codon usage (CU) values in 29 non-disease-causing (NDC) and 31 disease-causing (DC) human genes which are highly expressed in 3 distinct tissues, kidney, muscle, and skin. We applied our strategy to the same selected genes annotated in 15 mammalian species. We obtained CUB hierarchical clusters for each gene cohort which showed tissue-specific and disease-specific CUB fingerprints. We showed that DC genes (especially those expressed in muscle) display a low CUB, well recognizable in codon hierarchical clustering. We defined the extremely biased codons as “zero codons” and found that their number is significantly higher in all DC genes, all tissues, and that this trend is conserved across mammals. Based on this calculation in different gene cohorts, we identified 5 codons which are more differentially used across genes and mammals, underlining that some genes have favorite synonymous codons in use. Since of the muscle genes clear clusters, and, among these, dystrophin gene surprisingly does not show any “zero codon” we adopted a novel approach to study CUB, we called “mapping-on-codons”. We positioned 2828 dystrophin missense and nonsense pathogenic variations on their respective codon, highlighting that its frequency and occurrence is not dependent on the CU values. We conclude our strategy consents to identify a hierarchical clustering of CU values in a gene cohort-specific fingerprints, with recognizable trend across mammals. In DC muscle genes also a disease-related fingerprint can be observed, allowing discrimination between DC and NDC genes. We propose that using our strategy which studies CU in specific gene cohorts, as rare disease genes, and tissue specific genes, may provide novel information about the CUB role in human and medical genetics, with implications on synonymous variations interpretation and codon optimization algorithms.
Type: | Article |
---|---|
Title: | Calculating and comparing codon usage values in rare disease genes highlights codon clustering with disease-and tissue- specific hierarchy |
Location: | United States |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1371/journal.pone.0265469 |
Publisher version: | https://doi.org/10.1371/journal.pone.0265469 |
Language: | English |
Additional information: | © 2022 Rossi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Keywords: | Science & Technology, Multidisciplinary Sciences, Science & Technology - Other Topics, BIAS, SELECTION, MECHANISMS, MUTATIONS, EVOLUTION, VARIANTS, PATTERNS, ORIGINS, INDEX |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Developmental Neurosciences Dept UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences |
URI: | https://discovery.ucl.ac.uk/id/eprint/10158071 |
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