Genome-wide analysis of copy number variants and normal facial variation in a large cohort of Bantu Africans.
Genome-wide analysis of copy number variants and normal facial variation in a large cohort of Bantu Africans.
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DOI:
10.1016/j.xhgg.2021.100082
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发表时间:
2022-01-13
期刊:
影响因子:
--
通讯作者:
Hendricks AE
中科院分区:
文献类型:
--
作者:
Null M;Yilmaz F;Astling D;Yu HC;Cole JB;Hallgrímsson B;Santorico SA;Spritz RA;Shaikh TH;Hendricks AE
Similarity in facial characteristics between relatives suggests a strong genetic component underlies facial variation. While there have been numerous studies of the genetics of facial abnormalities and, more recently, single nucleotide polymorphism (SNP) genome-wide association studies (GWASs) of normal facial variation, little is known about the role of genetic structural variation in determining facial shape. In a sample of Bantu African children, we found that only 9% of common copy number variants (CNVs) and 10-kb CNV analysis windows are well tagged by SNPs (r2 ≥ 0.8), indicating that associations with our internally called CNVs were not captured by previous SNP-based GWASs. Here, we present a GWAS and gene set analysis of the relationship between normal facial variation and CNVs in a sample of Bantu African children. We report the top five regions, which had p values ≤ 9.35 × 10−6 and find nominal evidence of independent CNV association (p < 0.05) in three regions previously identified in SNP-based GWASs. The CNV region with strongest association (p = 1.16 × 10−6, 55 losses and seven gains) contains NFATC1, which has been linked to facial morphogenesis and Cherubism, a syndrome involving abnormal lower facial development. Genomic loss in the region is associated with smaller average lower facial depth. Importantly, new loci identified here were not identified in a SNP-based GWAS, suggesting that CNVs are likely involved in determining facial shape variation. Given the plethora of SNP-based GWASs, calling CNVs from existing data may be a relatively inexpensive way to aid in the study of complex traits.
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DOI:
10.1093/bioinformatics/btq033
发表时间:
2010-03-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Quinlan AR;Hall IM
通讯作者:
Hall IM
影响因子:
14.9
作者:
Frankish A;Diekhans M;Ferreira AM;Johnson R;Jungreis I;Loveland J;Mudge JM;Sisu C;Wright J;Armstrong J;Barnes I;Berry A;Bignell A;Carbonell Sala S;Chrast J;Cunningham F;Di Domenico T;Donaldson S;Fiddes IT;García Girón C;Gonzalez JM;Grego T;Hardy M;Hourlier T;Hunt T;Izuogu OG;Lagarde J;Martin FJ;Martínez L;Mohanan S;Muir P;Navarro FCP;Parker A;Pei B;Pozo F;Ruffier M;Schmitt BM;Stapleton E;Suner MM;Sycheva I;Uszczynska-Ratajczak B;Xu J;Yates A;Zerbino D;Zhang Y;Aken B;Choudhary JS;Gerstein M;Guigó R;Hubbard TJP;Kellis M;Paten B;Reymond A;Tress ML;Flicek P
通讯作者:
Flicek P
影响因子:
64.8
作者:
Sudmant PH;Rausch T;Gardner EJ;Handsaker RE;Abyzov A;Huddleston J;Zhang Y;Ye K;Jun G;Fritz MH;Konkel MK;Malhotra A;Stütz AM;Shi X;Casale FP;Chen J;Hormozdiari F;Dayama G;Chen K;Malig M;Chaisson MJP;Walter K;Meiers S;Kashin S;Garrison E;Auton A;Lam HYK;Mu XJ;Alkan C;Antaki D;Bae T;Cerveira E;Chines P;Chong Z;Clarke L;Dal E;Ding L;Emery S;Fan X;Gujral M;Kahveci F;Kidd JM;Kong Y;Lameijer EW;McCarthy S;Flicek P;Gibbs RA;Marth G;Mason CE;Menelaou A;Muzny DM;Nelson BJ;Noor A;Parrish NF;Pendleton M;Quitadamo A;Raeder B;Schadt EE;Romanovitch M;Schlattl A;Sebra R;Shabalin AA;Untergasser A;Walker JA;Wang M;Yu F;Zhang C;Zhang J;Zheng-Bradley X;Zhou W;Zichner T;Sebat J;Batzer MA;McCarroll SA;1000 Genomes Project Consortium;Mills RE;Gerstein MB;Bashir A;Stegle O;Devine SE;Lee C;Eichler EE;Korbel JO
通讯作者:
Korbel JO
影响因子:
4.5
作者:
Cole JB;Manyama M;Kimwaga E;Mathayo J;Larson JR;Liberton DK;Lukowiak K;Ferrara TM;Riccardi SL;Li M;Mio W;Prochazkova M;Williams T;Li H;Jones KL;Klein OD;Santorico SA;Hallgrimsson B;Spritz RA
通讯作者:
Spritz RA
影响因子:
4.4
作者:
Nyangiri, Oscar A.;Noyes, Harry;Matovu, Enock
通讯作者:
Matovu, Enock