Evidence map›Paper›PMID 38157018›Full record

ArticleHuman genetics2024

Recombination map tailored to Native Hawaiians may improve robustness of genomic scans for positive selection.

Bryan L Dinh, Echo Tang, Kekoa Taparra, Nathan Nakatsuka, Fei Chen, Charleston W K Chiang

Open access · hybridAbstract read
In one paragraph

Article in Human genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 3 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Bryan L DinhDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
Echo TangDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
Kekoa TaparraDepartment of Radiation Oncology, Stanford University, Palo Alto, CA, USA.
Nathan NakatsukaNew York Genome Center, New York, NY, USA.
Fei ChenCenter for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Charleston W K ChiangDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA. charleston.chiang@med.usc.edu.
University of Southern California · USNew York Genome Center · USStanford University · US

Funding

Understanding Population Differences in Cancer: The MEC StudyU01CA164973 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI HAIMAN, CHRISTOPHER ALAN, LE MARCHAND, LOIC · 2015 to 2025
$37.4M
Recruitment and Data CollectionP01CA168530 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI WILKENS, LYNNE R · 2012 to 2016
$19.9M
Leveraging the Evolutionary History to Improve Identification of Trait-Associated Alleles and Risk Stratification Models in Native HawaiiansR01HG011646 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Charleston Chiang · 2022 to 2026
$4.0M
Epidemiologic Studies of Putative Functional Variation in Multiethnic CohortU01HG007397 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI HAIMAN, CHRISTOPHER ALAN, LE MARCHAND, LOIC · 2013 to 2017
$3.7M
An evolutionary framework to elucidate and interpret the genetic architecture of complex traits in diverse populations - diversity supplementR35GM142783 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHIANG, CHARLESTON · 2021 to 2025
$2.2M
Genomic resources and references for genetic investigation of an understudied populationF31HG012159 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI DINH, BRYAN LY · 2021 to 2024
$143k
NCI NIH HHS P01 CA168530NCI NIH HHS U01 CA164973NHGRI NIH HHS F31 HG012159NHGRI NIH HHS F31HG012159NHGRI NIH HHS R01 HG011646NHGRI NIH HHS U01 HG007397NIGMS NIH HHS R35 GM142783NIGMS NIH HHS R35GM142783
6 · The paper itself

Abstract

Recombination events establish the patterns of haplotypic structure in a population and estimates of recombination rates are used in several downstream population and statistical genetic analyses. Using suboptimal maps from distantly related populations may reduce the efficacy of genomic analyses, particularly for underrepresented populations such as the Native Hawaiians. To overcome this challenge, we constructed recombination maps using genome-wide array data from two study samples of Native Hawaiians: one reflecting the current admixed state of Native Hawaiians (NH map) and one based on individuals of enriched Polynesian ancestries (PNS map) with the potential to be used for less admixed Polynesian populations such as the Samoans. We found the recombination landscape to be less correlated with those from other continental populations (e.g. Spearman's rho = 0.79 between PNS and CEU (Utah residents with Northern and Western European ancestry) compared to 0.92 between YRI (Yoruba in Ibadan, Nigeria) and CEU at 50 kb resolution), likely driven by the unique demographic history of the Native Hawaiians. PNS also shared the fewest recombination hotspots with other populations (e.g. 8% of hotspots shared between PNS and CEU compared to 27% of hotspots shared between YRI and CEU). We found that downstream analyses in the Native Hawaiian population, such as local ancestry inference, imputation, and IBD segment and relatedness detections, would achieve similar efficacy when using the NH map compared to an omnibus map. However, for genome scans of adaptive loci using integrated haplotype scores, we found several loci with apparent genome-wide significant signals (|Z-score|> 4) in Native Hawaiians that would not have been significant when analyzed using NH-specific maps. Population-specific recombination maps may therefore improve the robustness of haplotype-based statistics and help us better characterize the evolutionary history that may underlie Native Hawaiian-specific health conditions that persist today.

Indexed as

GenomicsNative Hawaiian or Pacific IslanderRecombination, GeneticHawaiiHumans

Identifiers

PMID38157018
PMCPMC10794367
OpenAlexW4390398058

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.