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ACKNOWLEDGMENTS
We thank P. Hegemann (Humboldt University of Berlin) for the
C. reinhardtiistrains, H. D. Madhani (University of California, San
Francisco) for theS. cerevisiaestrain, F. Wang and B. Yao (Emory
University) for theD. melanogasterembryos and adults, J. Dong
(Rutgers University) for theA. thalianastrains, J. Mo (Chinese
Academy of Sciences) for help with UHPLC-MS/MS analysis,
members of the Fang lab for helpful discussions, and the
Department of Scientific Computing at the Icahn School of
Medicine at Mount Sinai for computational resources and staff
expertise.Funding:Supported by the Icahn Institute for Genomics
and Multiscale Biology, NIH grants R35 GM139655, R01 HG011095,
and R56 AG071291, the Irma T. Hirschl/Monique Weill-Caulier
Trust, and the Nash Family Foundation (G.F.). UHPLC-MS/MS
analyses of 6mA were supported by Strategic Priority Research
Program of the Chinese Academy of Sciences grant XDPB2004
and National Natural Science Foundation of China grant 22021003
(H.W.).Author contributions:G.F. conceived the study and
supervised the research; Y.K. and G.F. developed the 6mASCOPE
method; Y.K. performed all the computational analyses; Y.K., L.C.,
E.A.M., X.-S.Z., and G.F. designed the experiments; L.C., E.A.M., and
X.-S.Z. performed most of the experiments; G.D. and R.S. optimized
short-insert PacBio library preparation and performed all PacBio
sequencing; Y.F. performed raw PacBio sequencing data processing
and quality control; W.L. and H.W. performed the UHPLC-MS/MS
analysis; Y.Z. and R.Y. performed glioblastoma sample preparation;
X.-S.Z. assisted the characterization of bacterial strains and collected
A. thalianasamples; Y.K., L.C., Y.F., E.A.M., X.-S.Z., and G.F. analyzed thedata; and Y.K. and G.F. wrote the manuscript with additional
information inputs from other co-authors.Competing interests:Y.K.
and G.F. are the co-inventors of a pending patent application based
on the method described in this work.Data and materials availability:
All sequencing data generated in this study have been submitted to
NCBI with accession number PRJNA667898. The software supporting
all proposed methods is available along with a tutorial at Zenodo
( 40 ) and at GitHub, http://www.github.com/fanglab/6mASCOPE.SUPPLEMENTARY MATERIALS
science.org/doi/10.1126/science.abe7489
Materials and Methods
Supplementary Text
Figs. S1 to S17
Tables S1 and S2
References ( 43 – 56 )
MDAR Reproducibility Checklist
29 September 2020; resubmitted 8 September 2021
Accepted 7 December 2021
10.1126/science.abe7489NEUROGENOMICS
Discovery of genomic loci of the human cerebral
cortex using genetically informed brain atlases
Carolina Makowski^1 , Dennis van der Meer2,3, Weixiu Dong^4 , Hao Wang^1 , Yan Wu^4 , Jingjing Zou^5 ,
Cin Liu^1 , Sara B. Rosenthal^6 , Donald J. Hagler Jr.^1 , Chun Chieh Fan^1 , William S. Kremen^7 ,
Ole A. Andreassen^2 , Terry L. Jernigan^8 , Anders M. Dale1,2, Kun Zhang^4 , Peter M. Visscher^9 ,
Jian Yang9,10, Chi-Hua Chen^1 *
To determine the impact of genetic variants on the brain, we used genetically informed brain atlases in
genome-wide association studies of regional cortical surface area and thickness in 39,898 adults and 9136
children. We uncovered 440 genome-wide significant loci in the discovery cohort and 800 from a post hoc
combined meta-analysis. Loci in adulthood were largely captured in childhood, showing signatures of negative
selection, and were linked to early neurodevelopment and pathways associated with neuropsychiatric risk.
Opposing gradations of decreased surface area and increased thickness were associated with common
inversion polymorphisms. Inferior frontal regions, encompassing BrocaÕs area, which is important for speech,
were enriched for human-specific genomic elements. Thus, a mixed genetic landscape of conserved and
human-specific features is concordant with brain hierarchy and morphogenetic gradients.
L
arge-scale magnetic resonance imaging
and genetics datasets have afforded the
opportunity to discover common genetic
variants contributing to the morphology
of the human cortex. Studies in model
organisms have revealed intricate genetic
mechanisms underlying cortical area and thick-
ness (i.e., laminar) patterning, although it has
been challenging to define aspects of cortical
development that are shared across mammals
as opposed to those that are human-specific ( 1 ).
Nevertheless, many studies have shown support
for the radial unit hypothesis, which posits dif-
ferential neurodevelopment programs shaping
and regulating these two cortical measures ( 2 ).
Consistent with this, the ENIGMA (Enhanc-
ing Neuroimaging Genetics through Meta-
Analysis) Consortium’s genome-wide association
study (GWAS) of the human cortex found many
variants associated with surface area and
thickness linked to neurodevelopmental pro-
cesses during fetal development ( 3 ). Such
evidence for neurodevelopmental programming
indicates the need to investigate these ques-
tions at earlier ages, as previous cortical GWASs
have almost exclusively been conducted in
older adults.
Cortical expansion and regional patterning
are largely genetically determined ( 2 ); there-
fore, we used data-driven genetically informed
atlases in this study ( 4 , 5 ), rather than atlases
primarily determined by sulcal-gyral patterns.
These genetically determined atlases capture
patterns of hierarchical genetic similarity fol-
lowing known developmental gradients that
shape the cortex along their anterior-posterior
(A-P) and dorsal-ventral (D-V) axes, includ-
ing 12 surface area and 12 thickness regions
( 2 , 4 , 5 ), and increase discoverability of genetic
variants underlying the cortex ( 6 ).Results
Genetic variants underlying cortical thickness
and area
In our discovery UK Biobank (UKB) sample
of 32,488 individuals (table S1), we found 440genome-wide significant [mixed linear model
association tests ( 7 ),P<5×10−^8 ] variants after
clumping each phenotype separately in PLINK
( 8 ) [linkage disequilibrium (LD)R^2 =0.1,250kb],
where 305 and 88 regional genetic variants
were associated with the 12 surface area
phenotypes and the 12 cortical thickness pheno-
types, respectively (Fig. 1 and tables S2 and S3).
Twenty-seven genetic variants were signifi-
cantly associated with total surface area and
20 variants with mean cortical thickness (table
S2). After correction for multiple comparisons,
234 genetic variants remained significant (P<
2.27 × 10−^9 ,5×10−^8 /te, withte= 22 being the
effective number of independent traits). We
performed subsequent functional analyses for
the 393 regional variants. Single-nucleotide
polymorphisms (SNPs) were mapped to genes
on the basis of their genomic position with
FUMA ( 9 ). Across all phenotypes, SNPs were
significantly enriched for noncoding regions
(44.0% enriched for intronic variants, 33.4%
for intergenic, and 17.7% for noncoding in-
tronic RNA; Fisher’s exact test,P< 0.05)
(Fig. 1 and table S4).522 4 FEBRUARY 2022•VOL 375 ISSUE 6580 science.orgSCIENCE
(^1) Center for Multimodal Imaging and Genetics, University of
California, San Diego, CA, USA.^2 Norwegian Centre for
Mental Disorders Research (NORMENT), Division of Mental
Health and Addiction, Oslo University Hospital and Institute
of Clinical Medicine, University of Oslo, Oslo, Norway.
(^3) School of Mental Health and Neuroscience, Faculty of
Health, Medicine and Life Sciences, Maastricht University,
Maastricht, Netherlands.^4 Department of Bioengineering,
University of California, San Diego, CA, USA.^5 Division of
Biostatistics, Herbert Wertheim School of Public Health and
Human Longevity Science, University of California, San
Diego, CA, USA.^6 Center for Computational Biology and
Bioinformatics, University of California, San Diego, CA, USA.
(^7) Department of Psychiatry and Center for Behavior Genetics
of Aging, University of California, San Diego, CA, USA.
(^8) Center for Human Development, University of California,
San Diego, CA, USA.^9 Institute for Molecular Bioscience, The
University of Queensland, Brisbane, Queensland, Australia.
(^10) School of Life Sciences, Westlake University, Hangzhou,
Zhejiang, China.
*Corresponding author. Email: [email protected] (C.-H.C.)
†Present address: Cellarity, Somerville, MA, USA.
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