Loading…
Age and diet shape the genetic architecture of body weight in diversity outbred mice
Understanding how genetic variation shapes a complex trait relies on accurately quantifying both the additive genetic and genotype–environment interaction effects in an age-dependent manner. We used a linear mixed model to quantify diet-dependent genetic contributions to body weight measured through...
Saved in:
Published in: | eLife 2022-07, Vol.11 |
---|---|
Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c452t-1fcb0af4f15900908bf3eba6566a16cc5ecca4bd74b28f843c72420a08b1ef903 |
---|---|
cites | cdi_FETCH-LOGICAL-c452t-1fcb0af4f15900908bf3eba6566a16cc5ecca4bd74b28f843c72420a08b1ef903 |
container_end_page | |
container_issue | |
container_start_page | |
container_title | eLife |
container_volume | 11 |
creator | Wright, Kevin M Deighan, Andrew G Di Francesco, Andrea Freund, Adam Jojic, Vladimir Churchill, Gary A Raj, Anil |
description | Understanding how genetic variation shapes a complex trait relies on accurately quantifying both the additive genetic and genotype–environment interaction effects in an age-dependent manner. We used a linear mixed model to quantify diet-dependent genetic contributions to body weight measured through adulthood in diversity outbred female mice under five diets. We observed that heritability of body weight declined with age under all diets, except the 40% calorie restriction diet. We identified 14 loci with age-dependent associations and 19 loci with age- and diet-dependent associations, with many diet-dependent loci previously linked to neurological function and behavior in mice or humans. We found their allelic effects to be dynamic with respect to genomic background, age, and diet, identifying several loci where distinct alleles affect body weight at different ages. These results enable us to more fully understand and predict the effectiveness of dietary intervention on overall health throughout age in distinct genetic backgrounds.
Body weight is one trait influenced by genes, age and environmental factors. Both internal and external environmental pressures are known to affect genetic variation over time. However, it is largely unknown how all factors – including age – interact to shape metabolism and bodyweight.
Wright et al. set out to quantify the interactions between genes and diet in ageing mice and found that the effect of genetics on mouse body weight changes with age. In the experiments, Wright et al. weighed 960 female mice with diverse genetic backgrounds, starting at two months of age into adulthood. The animals were randomized to different diets at six months of age. Some mice had unlimited food access, others received 20% or 40% less calories than a typical mouse diet, and some fasted one or two days per week.
Variations in their genetic background explained about 80% of differences in mice’s weight, but the influence of genetics relative to non-genetic factors decreased as they aged. Mice on the 40% calorie restriction diet were an exception to this rule and genetics accounted for 80% of their weight throughout adulthood, likely due to reduced influence from diet and reduced interactions between diet and genes. Several genes involved in metabolism, neurological function, or behavior, were associated with mouse weight.
The experiments highlight the importance of considering interactions between genetics, environment, and age in determining com |
doi_str_mv | 10.7554/eLife.64329 |
format | article |
fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_f881879d4a56447d87f8bfb12b7cda95</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_f881879d4a56447d87f8bfb12b7cda95</doaj_id><sourcerecordid>2691057938</sourcerecordid><originalsourceid>FETCH-LOGICAL-c452t-1fcb0af4f15900908bf3eba6566a16cc5ecca4bd74b28f843c72420a08b1ef903</originalsourceid><addsrcrecordid>eNpdkV1rHCEUhofS0oQ0V_0DQm8KZVN1dNSbQgj9CCz0JoXeiR_HGZfdcatOyv77uruhNPVG0cfneHy77i3BN4Jz9hHWMcDNwHqqXnSXFHO8wpL9fPnP-qK7LmWD2xBMSqJedxc9l70kPb_sHm5HQGb2yEeoqExmD6hOgEaYoUaHTHZTrODqkgGlgGzyB_Qb4jhVFOd26xFyifWA0lJtBo920cGb7lUw2wLXT_NV9-PL54e7b6v196_3d7frlWOc1hUJzmITWCBcYaywtKEHawY-DIYMznFwzjDrBbNUBsl6Jyij2DSQQFC4v-ruz16fzEbvc9yZfNDJRH3aSHnUJrcutqBD61wK5ZnhA2PCSxFaOUuoFc4bxZvr09m1X-wOvIO5ZrN9Jn1-MsdJj-lRKyoHwUgTvH8S5PRrgVL1LhYH262ZIS1F00ERzIXqZUPf_Ydu0pLn9lVHapAUY3KkPpwpl1MpGcLfxxCsj-HrU_j6FH7_B9inoW4</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2696820018</pqid></control><display><type>article</type><title>Age and diet shape the genetic architecture of body weight in diversity outbred mice</title><source>Open Access: PubMed Central</source><source>Publicly Available Content Database</source><creator>Wright, Kevin M ; Deighan, Andrew G ; Di Francesco, Andrea ; Freund, Adam ; Jojic, Vladimir ; Churchill, Gary A ; Raj, Anil</creator><creatorcontrib>Wright, Kevin M ; Deighan, Andrew G ; Di Francesco, Andrea ; Freund, Adam ; Jojic, Vladimir ; Churchill, Gary A ; Raj, Anil</creatorcontrib><description>Understanding how genetic variation shapes a complex trait relies on accurately quantifying both the additive genetic and genotype–environment interaction effects in an age-dependent manner. We used a linear mixed model to quantify diet-dependent genetic contributions to body weight measured through adulthood in diversity outbred female mice under five diets. We observed that heritability of body weight declined with age under all diets, except the 40% calorie restriction diet. We identified 14 loci with age-dependent associations and 19 loci with age- and diet-dependent associations, with many diet-dependent loci previously linked to neurological function and behavior in mice or humans. We found their allelic effects to be dynamic with respect to genomic background, age, and diet, identifying several loci where distinct alleles affect body weight at different ages. These results enable us to more fully understand and predict the effectiveness of dietary intervention on overall health throughout age in distinct genetic backgrounds.
Body weight is one trait influenced by genes, age and environmental factors. Both internal and external environmental pressures are known to affect genetic variation over time. However, it is largely unknown how all factors – including age – interact to shape metabolism and bodyweight.
Wright et al. set out to quantify the interactions between genes and diet in ageing mice and found that the effect of genetics on mouse body weight changes with age. In the experiments, Wright et al. weighed 960 female mice with diverse genetic backgrounds, starting at two months of age into adulthood. The animals were randomized to different diets at six months of age. Some mice had unlimited food access, others received 20% or 40% less calories than a typical mouse diet, and some fasted one or two days per week.
Variations in their genetic background explained about 80% of differences in mice’s weight, but the influence of genetics relative to non-genetic factors decreased as they aged. Mice on the 40% calorie restriction diet were an exception to this rule and genetics accounted for 80% of their weight throughout adulthood, likely due to reduced influence from diet and reduced interactions between diet and genes. Several genes involved in metabolism, neurological function, or behavior, were associated with mouse weight.
The experiments highlight the importance of considering interactions between genetics, environment, and age in determining complex traits like body weight. The results and the approaches used by Wright et al. may help other scientists learn more about how the genetic predisposition to disease changes with environmental stimuli and age.</description><identifier>ISSN: 2050-084X</identifier><identifier>EISSN: 2050-084X</identifier><identifier>DOI: 10.7554/eLife.64329</identifier><identifier>PMID: 35838135</identifier><language>eng</language><publisher>Cambridge: eLife Sciences Publications Ltd</publisher><subject>Age ; Animals ; Body weight ; Diet ; diversity outbred ; Gene loci ; gene-environment interaction ; Genetic diversity ; Genetics and Genomics ; Genotype & phenotype ; Genotype-environment interactions ; Genotypes ; Heritability ; Hypotheses ; Intervention ; Laboratories ; longitudinal ; mixed models ; Nutrient deficiency ; Population ; quantitative trait locus</subject><ispartof>eLife, 2022-07, Vol.11</ispartof><rights>2022, Wright et al. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022, Wright et al 2022 Wright et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c452t-1fcb0af4f15900908bf3eba6566a16cc5ecca4bd74b28f843c72420a08b1ef903</citedby><cites>FETCH-LOGICAL-c452t-1fcb0af4f15900908bf3eba6566a16cc5ecca4bd74b28f843c72420a08b1ef903</cites><orcidid>0000-0001-8772-2687 ; 0000-0001-9190-9284 ; 0000-0002-7956-5332 ; 0000-0001-6867-8203 ; 0000-0003-4412-0883</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2696820018/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2696820018?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,74998</link.rule.ids></links><search><creatorcontrib>Wright, Kevin M</creatorcontrib><creatorcontrib>Deighan, Andrew G</creatorcontrib><creatorcontrib>Di Francesco, Andrea</creatorcontrib><creatorcontrib>Freund, Adam</creatorcontrib><creatorcontrib>Jojic, Vladimir</creatorcontrib><creatorcontrib>Churchill, Gary A</creatorcontrib><creatorcontrib>Raj, Anil</creatorcontrib><title>Age and diet shape the genetic architecture of body weight in diversity outbred mice</title><title>eLife</title><description>Understanding how genetic variation shapes a complex trait relies on accurately quantifying both the additive genetic and genotype–environment interaction effects in an age-dependent manner. We used a linear mixed model to quantify diet-dependent genetic contributions to body weight measured through adulthood in diversity outbred female mice under five diets. We observed that heritability of body weight declined with age under all diets, except the 40% calorie restriction diet. We identified 14 loci with age-dependent associations and 19 loci with age- and diet-dependent associations, with many diet-dependent loci previously linked to neurological function and behavior in mice or humans. We found their allelic effects to be dynamic with respect to genomic background, age, and diet, identifying several loci where distinct alleles affect body weight at different ages. These results enable us to more fully understand and predict the effectiveness of dietary intervention on overall health throughout age in distinct genetic backgrounds.
Body weight is one trait influenced by genes, age and environmental factors. Both internal and external environmental pressures are known to affect genetic variation over time. However, it is largely unknown how all factors – including age – interact to shape metabolism and bodyweight.
Wright et al. set out to quantify the interactions between genes and diet in ageing mice and found that the effect of genetics on mouse body weight changes with age. In the experiments, Wright et al. weighed 960 female mice with diverse genetic backgrounds, starting at two months of age into adulthood. The animals were randomized to different diets at six months of age. Some mice had unlimited food access, others received 20% or 40% less calories than a typical mouse diet, and some fasted one or two days per week.
Variations in their genetic background explained about 80% of differences in mice’s weight, but the influence of genetics relative to non-genetic factors decreased as they aged. Mice on the 40% calorie restriction diet were an exception to this rule and genetics accounted for 80% of their weight throughout adulthood, likely due to reduced influence from diet and reduced interactions between diet and genes. Several genes involved in metabolism, neurological function, or behavior, were associated with mouse weight.
The experiments highlight the importance of considering interactions between genetics, environment, and age in determining complex traits like body weight. The results and the approaches used by Wright et al. may help other scientists learn more about how the genetic predisposition to disease changes with environmental stimuli and age.</description><subject>Age</subject><subject>Animals</subject><subject>Body weight</subject><subject>Diet</subject><subject>diversity outbred</subject><subject>Gene loci</subject><subject>gene-environment interaction</subject><subject>Genetic diversity</subject><subject>Genetics and Genomics</subject><subject>Genotype & phenotype</subject><subject>Genotype-environment interactions</subject><subject>Genotypes</subject><subject>Heritability</subject><subject>Hypotheses</subject><subject>Intervention</subject><subject>Laboratories</subject><subject>longitudinal</subject><subject>mixed models</subject><subject>Nutrient deficiency</subject><subject>Population</subject><subject>quantitative trait locus</subject><issn>2050-084X</issn><issn>2050-084X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkV1rHCEUhofS0oQ0V_0DQm8KZVN1dNSbQgj9CCz0JoXeiR_HGZfdcatOyv77uruhNPVG0cfneHy77i3BN4Jz9hHWMcDNwHqqXnSXFHO8wpL9fPnP-qK7LmWD2xBMSqJedxc9l70kPb_sHm5HQGb2yEeoqExmD6hOgEaYoUaHTHZTrODqkgGlgGzyB_Qb4jhVFOd26xFyifWA0lJtBo920cGb7lUw2wLXT_NV9-PL54e7b6v196_3d7frlWOc1hUJzmITWCBcYaywtKEHawY-DIYMznFwzjDrBbNUBsl6Jyij2DSQQFC4v-ruz16fzEbvc9yZfNDJRH3aSHnUJrcutqBD61wK5ZnhA2PCSxFaOUuoFc4bxZvr09m1X-wOvIO5ZrN9Jn1-MsdJj-lRKyoHwUgTvH8S5PRrgVL1LhYH262ZIS1F00ERzIXqZUPf_Ydu0pLn9lVHapAUY3KkPpwpl1MpGcLfxxCsj-HrU_j6FH7_B9inoW4</recordid><startdate>20220715</startdate><enddate>20220715</enddate><creator>Wright, Kevin M</creator><creator>Deighan, Andrew G</creator><creator>Di Francesco, Andrea</creator><creator>Freund, Adam</creator><creator>Jojic, Vladimir</creator><creator>Churchill, Gary A</creator><creator>Raj, Anil</creator><general>eLife Sciences Publications Ltd</general><general>eLife Sciences Publications, Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-8772-2687</orcidid><orcidid>https://orcid.org/0000-0001-9190-9284</orcidid><orcidid>https://orcid.org/0000-0002-7956-5332</orcidid><orcidid>https://orcid.org/0000-0001-6867-8203</orcidid><orcidid>https://orcid.org/0000-0003-4412-0883</orcidid></search><sort><creationdate>20220715</creationdate><title>Age and diet shape the genetic architecture of body weight in diversity outbred mice</title><author>Wright, Kevin M ; Deighan, Andrew G ; Di Francesco, Andrea ; Freund, Adam ; Jojic, Vladimir ; Churchill, Gary A ; Raj, Anil</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c452t-1fcb0af4f15900908bf3eba6566a16cc5ecca4bd74b28f843c72420a08b1ef903</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Age</topic><topic>Animals</topic><topic>Body weight</topic><topic>Diet</topic><topic>diversity outbred</topic><topic>Gene loci</topic><topic>gene-environment interaction</topic><topic>Genetic diversity</topic><topic>Genetics and Genomics</topic><topic>Genotype & phenotype</topic><topic>Genotype-environment interactions</topic><topic>Genotypes</topic><topic>Heritability</topic><topic>Hypotheses</topic><topic>Intervention</topic><topic>Laboratories</topic><topic>longitudinal</topic><topic>mixed models</topic><topic>Nutrient deficiency</topic><topic>Population</topic><topic>quantitative trait locus</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wright, Kevin M</creatorcontrib><creatorcontrib>Deighan, Andrew G</creatorcontrib><creatorcontrib>Di Francesco, Andrea</creatorcontrib><creatorcontrib>Freund, Adam</creatorcontrib><creatorcontrib>Jojic, Vladimir</creatorcontrib><creatorcontrib>Churchill, Gary A</creatorcontrib><creatorcontrib>Raj, Anil</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>ProQuest Science Journals</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>eLife</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wright, Kevin M</au><au>Deighan, Andrew G</au><au>Di Francesco, Andrea</au><au>Freund, Adam</au><au>Jojic, Vladimir</au><au>Churchill, Gary A</au><au>Raj, Anil</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Age and diet shape the genetic architecture of body weight in diversity outbred mice</atitle><jtitle>eLife</jtitle><date>2022-07-15</date><risdate>2022</risdate><volume>11</volume><issn>2050-084X</issn><eissn>2050-084X</eissn><abstract>Understanding how genetic variation shapes a complex trait relies on accurately quantifying both the additive genetic and genotype–environment interaction effects in an age-dependent manner. We used a linear mixed model to quantify diet-dependent genetic contributions to body weight measured through adulthood in diversity outbred female mice under five diets. We observed that heritability of body weight declined with age under all diets, except the 40% calorie restriction diet. We identified 14 loci with age-dependent associations and 19 loci with age- and diet-dependent associations, with many diet-dependent loci previously linked to neurological function and behavior in mice or humans. We found their allelic effects to be dynamic with respect to genomic background, age, and diet, identifying several loci where distinct alleles affect body weight at different ages. These results enable us to more fully understand and predict the effectiveness of dietary intervention on overall health throughout age in distinct genetic backgrounds.
Body weight is one trait influenced by genes, age and environmental factors. Both internal and external environmental pressures are known to affect genetic variation over time. However, it is largely unknown how all factors – including age – interact to shape metabolism and bodyweight.
Wright et al. set out to quantify the interactions between genes and diet in ageing mice and found that the effect of genetics on mouse body weight changes with age. In the experiments, Wright et al. weighed 960 female mice with diverse genetic backgrounds, starting at two months of age into adulthood. The animals were randomized to different diets at six months of age. Some mice had unlimited food access, others received 20% or 40% less calories than a typical mouse diet, and some fasted one or two days per week.
Variations in their genetic background explained about 80% of differences in mice’s weight, but the influence of genetics relative to non-genetic factors decreased as they aged. Mice on the 40% calorie restriction diet were an exception to this rule and genetics accounted for 80% of their weight throughout adulthood, likely due to reduced influence from diet and reduced interactions between diet and genes. Several genes involved in metabolism, neurological function, or behavior, were associated with mouse weight.
The experiments highlight the importance of considering interactions between genetics, environment, and age in determining complex traits like body weight. The results and the approaches used by Wright et al. may help other scientists learn more about how the genetic predisposition to disease changes with environmental stimuli and age.</abstract><cop>Cambridge</cop><pub>eLife Sciences Publications Ltd</pub><pmid>35838135</pmid><doi>10.7554/eLife.64329</doi><orcidid>https://orcid.org/0000-0001-8772-2687</orcidid><orcidid>https://orcid.org/0000-0001-9190-9284</orcidid><orcidid>https://orcid.org/0000-0002-7956-5332</orcidid><orcidid>https://orcid.org/0000-0001-6867-8203</orcidid><orcidid>https://orcid.org/0000-0003-4412-0883</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2050-084X |
ispartof | eLife, 2022-07, Vol.11 |
issn | 2050-084X 2050-084X |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_f881879d4a56447d87f8bfb12b7cda95 |
source | Open Access: PubMed Central; Publicly Available Content Database |
subjects | Age Animals Body weight Diet diversity outbred Gene loci gene-environment interaction Genetic diversity Genetics and Genomics Genotype & phenotype Genotype-environment interactions Genotypes Heritability Hypotheses Intervention Laboratories longitudinal mixed models Nutrient deficiency Population quantitative trait locus |
title | Age and diet shape the genetic architecture of body weight in diversity outbred mice |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T22%3A03%3A17IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Age%20and%20diet%20shape%20the%20genetic%20architecture%20of%20body%20weight%20in%20diversity%20outbred%20mice&rft.jtitle=eLife&rft.au=Wright,%20Kevin%20M&rft.date=2022-07-15&rft.volume=11&rft.issn=2050-084X&rft.eissn=2050-084X&rft_id=info:doi/10.7554/eLife.64329&rft_dat=%3Cproquest_doaj_%3E2691057938%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c452t-1fcb0af4f15900908bf3eba6566a16cc5ecca4bd74b28f843c72420a08b1ef903%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2696820018&rft_id=info:pmid/35838135&rfr_iscdi=true |