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- Harper, Jon Alexander, et al.
(author)
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Systematic review reveals multiple sexually antagonistic polymorphisms affecting human disease and complex traits
- 2021
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In: Evolution. - : John Wiley & Sons. - 0014-3820 .- 1558-5646. ; 75:12, s. 3087-3097
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Journal article (peer-reviewed)abstract
- An evolutionary model for sex differences in disease risk posits that alleles conferring higher risk in one sex may be protective in the other. These sexually antagonistic (SA) alleles are predicted to be maintained at frequencies higher than expected under purifying selection against unconditionally deleterious alleles, but there are apparently no examples in humans. Discipline-specific terminology, rather than a genuine lack of such alleles, could explain this disparity. We undertook a two-stage review of evidence for SA polymorphisms in humans using search terms from (i) evolutionary biology and (ii) biomedicine. Although the first stage returned no eligible studies, the second revealed 51 genes with sex-opposite effects; 22 increased disease risk or severity in one sex but protected the other. Those with net positive effects occurred at higher frequencies. None were referred to as SA. Our review reveals significant communication barriers to fields as a result of discipline-specific terminology.
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3. |
- Qin, Yue, et al.
(author)
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A multi-scale map of cell structure fusing protein images and interactions
- 2021
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In: Nature. - : Springer Nature. - 0028-0836 .- 1476-4687. ; 600:7889, s. 536-
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Journal article (peer-reviewed)abstract
- The cell is a multi-scale structure with modular organization across at least four orders of magnitude(1). Two central approaches for mapping this structure-protein fluorescent imaging and protein biophysical association-each generate extensive datasets, but of distinct qualities and resolutions that are typically treated separately(2,3). Here we integrate immunofluorescence images in the Human Protein Atlas(4) with affinity purifications in BioPlex(5) to create a unified hierarchical map of human cell architecture. Integration is achieved by configuring each approach as a general measure of protein distance, then calibrating the two measures using machine learning. The map, known as the multi-scale integrated cell (MuSIC 1.0), resolves 69 subcellular systems, of which approximately half are to our knowledge undocumented. Accordingly, we perform 134 additional affinity purifications and validate subunit associations for the majority of systems. The map reveals a pre-ribosomal RNA processing assembly and accessory factors, which we show govern rRNA maturation, and functional roles for SRRM1 and FAM120C in chromatin and RPS3A in splicing. By integration across scales, MuSIC increases the resolution of imaging while giving protein interactions a spatial dimension, paving the way to incorporate diverse types of data in proteome-wide cell maps.
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