Implementation of Functional Genome in the Functional Study of Non-coding Variants Associated with Non-syndromic Cleft Lip with or without Cleft Palate.

doi:10.13701/j.cnki.kqyxyj.2018.12.001

Abstract

Abstract: Orofacial clefting is the most common craniofacial birth defect and has a strong genetic underpinning.Genome-wide association studies have detected common variants associated with this disorder, most of which lie in the non-coding DNA segments.However, due to poor understanding on the connection between the sequence and function of non-coding DNA during human craniofacial development, how these associated variants increase the risk of orofacial clefting remain largely unknown, which is a major challenge to the translation of genetic results into clinical practice.This article aims to give a systematic introduction to craniofacial functional genome results and their integration with machine learning in order to propose an improved research system for orofacial-clefting-associated non-coding variants.

Key words: Non-syndromic cleft lip with or without cleft palate, Functional genome, Machine learning

LIU Huan. Implementation of Functional Genome in the Functional Study of Non-coding Variants Associated with Non-syndromic Cleft Lip with or without Cleft Palate.[J]. Journal of Oral Science Research, 2018, 34(12): 1265-1270.

References

[1] Beaty TH,Murray JC,Marazita ML,et al.A genome-wide association study of cleft lip with and without cleft palate identifies risk variants near MAFB and ABCA4 [J]. Nat Genet,2010,42(6)∶525-529
[2] Birnbaum S,Ludwig KU,Reutter H,et al. Key susceptibility locus for nonsyndromic cleft lip with or without cleft palate on chromosome 8q24 [J]. Nat Genet,2009,41(4)∶473-477
[3] Camargo M,Rivera D,Moreno L,et al. GWAS reveals new recessive loci associated with non-syndromic facial clefting [J]. Eur J Med Genet,2012,55(10)∶510-514
[4] Grant SF,Wang K,Zhang H,et al. A genome-wide association study identifies a locus for nonsyndromic cleft lip with or without cleft palate on 8q24[J].J Pediatr,2009,155(6)∶909-913
[5] Leslie EJ, Carlson JC, Shaffer JR,et al. Genome-wide meta-analyses of nonsyndromic orofacial clefts identify novel associations between FOXE1 and all orofacial clefts, and TP63 and cleft lip with or without cleft palate [J]. Hum Genet,2017,136(3)∶275-286
[6] Mangold E,Ludwig KU,Birnbaum S,et al. Genome-wide association study identifies two susceptibility loci for nonsyndromic cleft lip with or without cleft palate [J]. Nat Genet,2010,42(1)∶24-26
[7] Roadmap Epigenomics Consortium, Kundaje A, Meuleman W,et al. Integrative analysis of 111 reference human epigenomes [J]. Nature,2015,518(7539)∶317-330
[8] Wolf ZT, Brand HA, Shaffer JR, et al. Genome-wide association studies in dogs and humans identify ADAMTS20 as a risk variant for cleft lip and palate [J]. PLoS Genet, 2015, 11(3)∶e1005059
[9] Leslie EJ,Liu H,Carlson JC,et al. A genome-wide association study of nonsyndromic cleft palate identifies an etiologic missense variant in GRHL3 [J]. Am J Hum Genet,2016,98(4)∶744-754
[10] Yu Y, Zuo X, He M, et al. Genome-wide analyses of non-syndromic cleft lip with palate identify 14 novel loci and genetic heterogeneity [J]. Nat Commun,2017,8∶14364
[11] Leslie EJ, Taub MA, Liu H, et al. Identification of functional variants for cleft lip with or without cleft palate in or near PAX7, FGFR2, and NOG by targeted sequencing of GWAS loci [J]. Am J Hum Genet, 2015, 96(3)∶397-411
[12] Beaty TH, Taub MA, Scott AF, et al. Confirming genes influencing risk to cleft lip with/without cleft palate in a case-parent trio study [J]. Hum Genet, 2013, 132(7)∶771-781
[13] Ludwig KU, Mangold E, Herms S, et al. Genome-wide meta-analyses of nonsyndromic cleft lip with or without cleft palate identify six new risk loci [J]. Nat Genet, 2012, 44(9)∶968-971
[14] Moreno LM, Mansilla MA, Bullard SA, et al. FOXE1 association with both isolated cleft lip with or without cleft palate, and isolated cleft palate [J]. Hum Mol Genet, 2009, 18(24)∶4879-4896
[15] Eshete MA, Liu H, Li M, et al. Loss-of-function GRHL3 variants detected in African patients with isolated cleft palate [J]. J Dent Res, 2018, 97(1)∶41-48
[16] Mangold E, Bohmer AC, Ishorst N, et al. Sequencing the GRHL3 coding region reveals rare truncating mutations and a common susceptibility variant for nonsyndromic cleft palate [J]. Am J Hum Genet, 2016, 98(4)∶755-762
[17] Consortium EP. An integrated encyclopedia of DNA elements in the human genome [J]. Nature, 2012, 489(7414)∶57-74
[18] Brinkley JF, Fisher S, Harris MP, et al. The FaceBase Consortium: a comprehensive resource for craniofacial researchers [J]. Development,2016,143(14)∶2677-2688
[19] Wilderman A, VanOudenhove J, Kron J,et al. High-resolution epigenomic atlas of human embryonic craniofacial development [J]. Cell Rep, 2018, 23(5)∶1581-1597
[20] Maurano MT, Humbert R, Rynes E, et al. Systematic iocalization of common disease-associated variation in regulatory DNA [J]. Science,2012,337(6099)∶1190-1195
[21] Liu H, Leslie EJ, Carlson JC, et al. Identification of common non-coding variants at 1p22 that are functional for non-syndromic orofacial clefting [J]. Nat Commun, 2017, 8∶14759
[22] Soldner F, Stelzer Y, Shivalila CS, et al. Parkinson-associated risk variant in distal enhancer of alpha-synuclein modulates target gene expression [J]. Nature, 2016, 533(7601)∶95-99
[23] Ye J, Tucker NR, Weng LC, et al. A functional variant associated with atrial fibrillation regulates PITX2c expression through TFAP2a [J]. Am J Hum Genet, 2016, 99(6)∶1281-1291
[24] Chai Y, Jiang X, Ito Y, et al. Fate of the mammalian cranial neural crest during tooth and mandibular morphogenesis [J]. Development, 2000, 127(8)∶1671-1679
[25] Prescott SL, Srinivasan R, Marchetto MC, Grishina I, et al. Enhancer divergence and cis-regulatory evolution in the human and chimp neural crest [J]. Cell, 2015, 163(1)∶68-83
[26] Rada-Iglesias A, Bajpai R, Prescott S, et al. Epigenomic annotation of enhancers predicts transcriptional regulators of human neural crest [J]. Cell Stem Cell, 2012,11(5)∶633-648
[27] Attanasio C, Nord AS, Zhu Y, et al. Fine tuning of craniofacial morphology by distant-acting enhancers [J]. Science, 2013, 342(6157)∶1241006
[28] Ghandi M, Mohammad-Noori M, Ghareghani N, et al. gkmSVM: an R package for gapped-kmer SVM [J]. Bioinformatics, 2016, 32(14)∶2205-2207
[29] Shen Z, Bao W, Huang DS. Recurrent neural network for predicting transcription factor binding sites [J]. Sci Rep, 2018, 8(1)∶15270
[30] Beer MA. Predicting enhancer activity and variant impact using gkm-SVM [J]. Hum Mutat, 2017, 38(9)∶1251-1258
[31] Lee D, Gorkin DU, Baker M, et al. A method to predict the impact of regulatory variants from DNA sequence [J]. Nat Genet, 2015, 47(8)∶955-961
[32] Smith EM, Lajoie BR, Jain G, et al. Invariant TAD boundaries constrain cell-type-specific looping interactions between promoters and distal elements around the CFTR locus [J]. Am J Hum Genet, 2016, 98(1)∶185-201