Novel genetic loci affecting facial shape variation in humans
- Erasmus MC University Medical Center, Netherlands
- University of Bristol, United Kingdom
- University of Pittsburgh, United States
- King's College London, United Kingdom
- QIMR Berghofer Medical Research Institute, Australia
- University College London, United Kingdom
- CAS-MPG Partner Institute for Computational Biology, China
- Bejing Institute of Genomics, China
- Plastic Surgery Hospital, China
- Cardiff University, United Kingdom
- Instituto Patagonico de Ciencias Sociales y Humanas, Argentina
- Universidade Federal do Rio Grande do Sul, Brazil
- UNAM-Instituto Nacional de Medicina Genomica, Mexico
- Universidad Peruana Cayetano Heredia, Peru
- Universidad de Antioquia, Colombia
- Universidad de Tarapaca, Chile
- Leiden University Medical Center, Netherlands
- Beijing Institute of Genomics, China
Abstract
The human face represents a combined set of highly heritable phenotypes, but knowledge on its genetic architecture remains limited, despite the relevance for various fields. A series of genome-wide association studies on 78 facial shape phenotypes quantified from 3-dimensional facial images of 10,115 Europeans identified 24 genetic loci reaching study-wide suggestive association (p<5x10-8), among which 17 were previously unreported. A follow-up multi-ethnic study in additional 7,917 individuals confirmed 10 loci including 6 unreported ones (padjusted<2.1x10-3). A global map of derived polygenic face scores assembled facial features in major continental groups consistent with anthropological knowledge. Analyses of epigenomic datasets from cranial neural crest cells revealed abundant cis-regulatory activities at the face-associated genetic loci. Luciferase reporter assays in neural crest progenitor cells highlighted enhancer activities of several face-associated DNA variants. These results substantially advance our understanding of the genetic basis underlying human facial variation and provide candidates for future in-vivo functional studies.
Data availability
GWAS meta-analysis summary statistics data of the significantly associated SNPs are provided with the paper in the supplementary file 1. In addition, GWAS meta-analysis summary statistics of all SNPs and all facial phenotypes, including for each SNP the effect allele, non-effect allele and for each phenotype the effect size alligned to the effect allele with standard error and p-value, are made publically available via figshare under https://doi.org/10.6084/m9.figshare.10298396 (updated file). Moreover, after the paper is accepted for publication, we will upload to the EBI GWAS Catalogue the complete summary statistics of all SNPs (same information as on figshare now) into the GWAS Catalogue. We included this information and the website links in the Material and Method section.
Article and author information
Author details
Funding
European Union Horizon 2020 Research and Innovation Programme (740580 (VISAGE))
- Manfred Kayser
Levelhulm Trust (F/07 134/DF)
- Andrés Ruiz-Linares
National Natural Science Foundation of China (91631307)
- Sijia Wang
National Natural Science Foundation of China (91731303)
- Shu-Hua Xu
National Natural Science Foundation of China (30890034)
- Li Jin
Australian NHMRC
- Nicholas G Martin
Australian NHMRC Fellowship (APP1103623)
- Sarah E Medland
National Natural Science Foundation of China (31771388)
- Shu-Hua Xu
National Natural Science Foundation of China (315014)
- Shu-Hua Xu
National Natural Science Foundation of China (31711530331)
- Shu-Hua Xu
National Natural Science Foundation of China (31271338)
- Li Jin
National Science Foundation of China (91651507)
- Fan Liu
National Institute of Dental and Craniofacial Research (R01-DE027023)
- Seth M Weinberg
National Institute of Dental and Craniofacial Research (R01-DE016148)
- Seth M Weinberg
National Institute of Dental and Craniofacial Research (X01-HG007821)
- Seth M Weinberg
Netherlands Organization of Scientific Research (911-03-012)
- M Arfan Ikram
National Key R&D Program of China (2017YFC083501)
- Fan Liu
Strategic Priority Reserach Program Chinese Academy of Sciences (XDC010400100)
- Fan Liu
China Scholarship Council (PhD Fellowship)
- Ziyi Xiong
Netherlands Organization of Scientific Research (1750102005011)
- M Arfan Ikram
Wellcome Trust
- Timothy D Spector
Medical Research Council (102215/2/13/2)
- Evie Stergiakouli
National Institute of Dental and Craniofacial Research (U01-DE20078)
- Seth M Weinberg
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: All cohort participants gave informed consent and consent to publish. The different cohort studies involved have been approved by their local ethics committees and in part higher institutions such as ministries, as described in the Material and Method section. Protocol numbers can be found for each cohort in the Materials and Methods section.
Copyright
© 2019, Xiong et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 5,804
- views
-
- 791
- downloads
-
- 63
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Novel genetic loci affecting facial shape variation in humans
eLife 8:e49898.
https://doi.org/10.7554/eLife.49898
Further reading
-
- Evolutionary Biology
- Genetics and Genomics
Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs in Saccharomyces cerevisiae by single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses. We used scRNA-seq data to genotype each cell, measure gene expression, and classify the cells by cell-cycle stage. We mapped thousands of local and distant eQTLs and identified interactions between eQTL effects and cell-cycle stages. We took advantage of single-cell expression information to identify hundreds of genes with allele-specific effects on expression noise. We used cell-cycle stage classification to map 20 loci that influence cell-cycle progression. One of these loci influenced the expression of genes involved in the mating response. We showed that the effects of this locus arise from a common variant (W82R) in the gene GPA1, which encodes a signaling protein that negatively regulates the mating pathway. The 82R allele increases mating efficiency at the cost of slower cell-cycle progression and is associated with a higher rate of outcrossing in nature. Our results provide a more granular picture of the effects of genetic variants on gene expression and downstream traits.
-
- Genetics and Genomics
- Microbiology and Infectious Disease
Evolution of gene expression frequently drives antibiotic resistance in bacteria. We had previously (Patel and Matange, eLife, 2021) shown that, in Escherichia coli, mutations at the mgrB locus were beneficial under trimethoprim exposure and led to overexpression of dihydrofolate reductase (DHFR), encoded by the folA gene. Here, we show that DHFR levels are further enhanced by spontaneous duplication of a genomic segment encompassing folA and spanning hundreds of kilobases. This duplication was rare in wild-type E. coli. However, its frequency was elevated in a lon-knockout strain, altering the mutational landscape early during trimethoprim adaptation. We then exploit this system to investigate the relationship between trimethoprim pressure and folA copy number. During long-term evolution, folA duplications were frequently reversed. Reversal was slower under antibiotic pressure, first requiring the acquisition of point mutations in DHFR or its promoter. Unexpectedly, despite resistance-conferring point mutations, some populations under high trimethoprim pressure maintained folA duplication to compensate for low abundance DHFR mutants. We find that evolution of gene dosage depends on expression demand, which is generated by antibiotic and exacerbated by proteolysis of drug-resistant mutants of DHFR. We propose a novel role for proteostasis as a determinant of copy number evolution in antibiotic-resistant bacteria.
