Identifying Recent Adaptations in Large-Scale Genomic Data
Although several hundred regions of the human genome harbor signals of positive natural selection, few of the relevant adaptive traits and variants have been elucidated. Using full-genome sequence variation from the 1000 Genomes (1000G) Project and the composite of multiple signals (CMS) test, we in...
| Main Authors: | , , , , , , , , , , , , , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Elsevier
2014
|
| Online Access: | http://hdl.handle.net/1721.1/85567 https://orcid.org/0000-0001-5410-7274 https://orcid.org/0000-0001-5951-9358 |
| _version_ | 1826199766352003072 |
|---|---|
| author | Andersen, Kristian G. Tabrizi, Shervin Winnicki, Sarah Yen, Angela Park, Daniel J. Griesemer, Dustin Karlsson, Elinor K. Wong, Sunny H. Cabili, Moran N. Adegbola, Richard A. Bamezai, Rameshwar N.K. Hill, Adrian V. S. Vannberg, Fredrik O. Rinn, John L. Schaffner, Stephen F. Sabeti, Pardis C. Grossman, Sharon Rachel Shlyakhter, Ilya, 1975- Lander, Eric Steven |
| author2 | Whitaker College of Health Sciences and Technology |
| author_facet | Whitaker College of Health Sciences and Technology Andersen, Kristian G. Tabrizi, Shervin Winnicki, Sarah Yen, Angela Park, Daniel J. Griesemer, Dustin Karlsson, Elinor K. Wong, Sunny H. Cabili, Moran N. Adegbola, Richard A. Bamezai, Rameshwar N.K. Hill, Adrian V. S. Vannberg, Fredrik O. Rinn, John L. Schaffner, Stephen F. Sabeti, Pardis C. Grossman, Sharon Rachel Shlyakhter, Ilya, 1975- Lander, Eric Steven |
| author_sort | Andersen, Kristian G. |
| collection | MIT |
| description | Although several hundred regions of the human genome harbor signals of positive natural selection, few of the relevant adaptive traits and variants have been elucidated. Using full-genome sequence variation from the 1000 Genomes (1000G) Project and the composite of multiple signals (CMS) test, we investigated 412 candidate signals and leveraged functional annotation, protein structure modeling, epigenetics, and association studies to identify and extensively annotate candidate causal variants. The resulting catalog provides a tractable list for experimental follow-up; it includes 35 high-scoring nonsynonymous variants, 59 variants associated with expression levels of a nearby coding gene or lincRNA, and numerous variants associated with susceptibility to infectious disease and other phenotypes. We experimentally characterized one candidate nonsynonymous variant in Toll-like receptor 5 (TLR5) and show that it leads to altered NF-κB signaling in response to bacterial flagellin. |
| first_indexed | 2024-09-23T11:25:27Z |
| format | Article |
| id | mit-1721.1/85567 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:25:27Z |
| publishDate | 2014 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | mit-1721.1/855672022-10-01T03:29:48Z Identifying Recent Adaptations in Large-Scale Genomic Data Andersen, Kristian G. Tabrizi, Shervin Winnicki, Sarah Yen, Angela Park, Daniel J. Griesemer, Dustin Karlsson, Elinor K. Wong, Sunny H. Cabili, Moran N. Adegbola, Richard A. Bamezai, Rameshwar N.K. Hill, Adrian V. S. Vannberg, Fredrik O. Rinn, John L. Schaffner, Stephen F. Sabeti, Pardis C. Grossman, Sharon Rachel Shlyakhter, Ilya, 1975- Lander, Eric Steven Whitaker College of Health Sciences and Technology Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Biology Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Grossman, Sharon Rachel Yen, Angela Lander, Eric S. Although several hundred regions of the human genome harbor signals of positive natural selection, few of the relevant adaptive traits and variants have been elucidated. Using full-genome sequence variation from the 1000 Genomes (1000G) Project and the composite of multiple signals (CMS) test, we investigated 412 candidate signals and leveraged functional annotation, protein structure modeling, epigenetics, and association studies to identify and extensively annotate candidate causal variants. The resulting catalog provides a tractable list for experimental follow-up; it includes 35 high-scoring nonsynonymous variants, 59 variants associated with expression levels of a nearby coding gene or lincRNA, and numerous variants associated with susceptibility to infectious disease and other phenotypes. We experimentally characterized one candidate nonsynonymous variant in Toll-like receptor 5 (TLR5) and show that it leads to altered NF-κB signaling in response to bacterial flagellin. National Institute of General Medical Sciences (U.S.) (T32GM007753) 2014-03-10T15:06:08Z 2014-03-10T15:06:08Z 2013-02 2013-01 Article http://purl.org/eprint/type/JournalArticle 00928674 1097-4172 http://hdl.handle.net/1721.1/85567 Grossman, Sharon R., Kristian G. Andersen, Ilya Shlyakhter, Shervin Tabrizi, Sarah Winnicki, Angela Yen, Daniel J. Park, et al. “Identifying Recent Adaptations in Large-Scale Genomic Data.” Cell 152, no. 4 (February 2013): 703–713. Copyright © 2013 Elsevier Inc. https://orcid.org/0000-0001-5410-7274 https://orcid.org/0000-0001-5951-9358 en_US http://dx.doi.org/10.1016/j.cell.2013.01.035 Cell Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Elsevier Elsevier Open Archive |
| spellingShingle | Andersen, Kristian G. Tabrizi, Shervin Winnicki, Sarah Yen, Angela Park, Daniel J. Griesemer, Dustin Karlsson, Elinor K. Wong, Sunny H. Cabili, Moran N. Adegbola, Richard A. Bamezai, Rameshwar N.K. Hill, Adrian V. S. Vannberg, Fredrik O. Rinn, John L. Schaffner, Stephen F. Sabeti, Pardis C. Grossman, Sharon Rachel Shlyakhter, Ilya, 1975- Lander, Eric Steven Identifying Recent Adaptations in Large-Scale Genomic Data |
| title | Identifying Recent Adaptations in Large-Scale Genomic Data |
| title_full | Identifying Recent Adaptations in Large-Scale Genomic Data |
| title_fullStr | Identifying Recent Adaptations in Large-Scale Genomic Data |
| title_full_unstemmed | Identifying Recent Adaptations in Large-Scale Genomic Data |
| title_short | Identifying Recent Adaptations in Large-Scale Genomic Data |
| title_sort | identifying recent adaptations in large scale genomic data |
| url | http://hdl.handle.net/1721.1/85567 https://orcid.org/0000-0001-5410-7274 https://orcid.org/0000-0001-5951-9358 |
| work_keys_str_mv | AT andersenkristiang identifyingrecentadaptationsinlargescalegenomicdata AT tabrizishervin identifyingrecentadaptationsinlargescalegenomicdata AT winnickisarah identifyingrecentadaptationsinlargescalegenomicdata AT yenangela identifyingrecentadaptationsinlargescalegenomicdata AT parkdanielj identifyingrecentadaptationsinlargescalegenomicdata AT griesemerdustin identifyingrecentadaptationsinlargescalegenomicdata AT karlssonelinork identifyingrecentadaptationsinlargescalegenomicdata AT wongsunnyh identifyingrecentadaptationsinlargescalegenomicdata AT cabilimorann identifyingrecentadaptationsinlargescalegenomicdata AT adegbolaricharda identifyingrecentadaptationsinlargescalegenomicdata AT bamezairameshwarnk identifyingrecentadaptationsinlargescalegenomicdata AT hilladrianvs identifyingrecentadaptationsinlargescalegenomicdata AT vannbergfredriko identifyingrecentadaptationsinlargescalegenomicdata AT rinnjohnl identifyingrecentadaptationsinlargescalegenomicdata AT schaffnerstephenf identifyingrecentadaptationsinlargescalegenomicdata AT sabetipardisc identifyingrecentadaptationsinlargescalegenomicdata AT grossmansharonrachel identifyingrecentadaptationsinlargescalegenomicdata AT shlyakhterilya1975 identifyingrecentadaptationsinlargescalegenomicdata AT landerericsteven identifyingrecentadaptationsinlargescalegenomicdata |