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Abstract Sex estimation of skeletons is fundamental to many archaeological studies. Currently, three approaches are available to estimate sex–osteology, genomics, or proteomics, but little is known about the relative reliability of these methods in applied settings. We present matching osteological, shotgun-genomic, and proteomic data to estimate the sex of 55 individuals, each with an independent radiocarbon date between 2,440 and 100 cal BP, from two ancestral Ohlone sites in Central California. Sex estimation was possible in 100% of this burial sample using proteomics, in 91% using genomics, and in 51% using osteology. Agreement between the methods was high, however conflicts did occur. Genomic sex estimates were 100% consistent with proteomic and osteological estimates when DNA reads were above 100,000 total sequences. However, more than half the samples had DNA read numbers below this threshold, producing high rates of conflict with osteological and proteomic data where nine out of twenty conditional DNA sex estimates conflicted with proteomics. While the DNA signal decreased by an order of magnitude in the older burial samples, there was no decrease in proteomic signal. We conclude that proteomics provides an important complement to osteological and shotgun-genomic sex estimation.
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High-throughput proteomics: a methodological mini-review
Proteomics plays a vital role in biomedical research in the post-genomic era. With the technological revolution and emerging computational and statistic models, proteomic methodology has evolved rapidly in the past decade and shed light on solving complicated biomedical problems. Here, we summarize scientific research and clinical practice of existing and emerging high-throughput proteomics approaches, including mass spectrometry, protein pathway array, next-generation tissue microarrays, single-cell proteomics, single-molecule proteomics, Luminex, Simoa and Olink Proteomics. We also discuss important computational methods and statistical algorithms that can maximize the mining of proteomic data with clinical and/or other 'omics data. Various principles and precautions are provided for better utilization of these tools. In summary, the advances in high-throughput proteomics will not only help better understand the molecular mechanisms of pathogenesis, but also to identify the signature signaling networks of specific diseases. Thus, modern proteomics have a range of potential applications in basic research, prognostic oncology, precision medicine, and drug discovery.
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- Award ID(s):
- 2128307
- PAR ID:
- 10346760
- Date Published:
- Journal Name:
- Laboratory Investigation
- ISSN:
- 0023-6837
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1038/s41374-022-00830-7
