|
1
|
Hobbs CA, Chowdhury S, Cleves MA, Erickson
S, MacLeod SL, Shaw GM, Shete S, Witte JS and Tycko B: Genetic
epidemiology and nonsyndromic structural birth defects: From
candidate genes to epigenetics. Jama Pediatr. 168:371–377. 2014.
View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Mone F, Quinlan-Jones E, Ewer AK and Kilby
MD: Exome sequencing in the assessment of congenital malformations
in the fetus and neonate. Arch Dis Child Fetal Neonatal Ed.
104:F452–F456. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Kang L, Guo Z, Shang W, Cao GY, Zhang YP,
Wang QM, Shen HP, Liang WN and Liu M: Perinatal prevalence of birth
defects in the Mainland of China, 2000-2021: A systematic review
and meta-analysis. World J Pediatr. 20:669–681. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Basu M, Zhu J, LaHaye S, Majumdar U, Jiao
K, Han Z and Garg V: Epigenetic mechanisms underlying maternal
diabetes-associated risk of congenital heart disease. JCI Insight.
2:e950852017. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Nasreddine G, El HJ and Ghassibe-Sabbagh
M: Orofacial clefts embryology, classification, epidemiology, and
genetics. Mutat Res Rev Mutat. 787:1083732021. View Article : Google Scholar
|
|
6
|
Buijtendijk MF, Bet BB, Leeflang MM, Shah
H, Reuvekamp T, Goring T, Docter D, Timmerman MG, Dawood Y,
Lugthart MA, et al: Diagnostic accuracy of ultrasound screening for
fetal structural abnormalities during the first and second
trimester of pregnancy in low-risk and unselected populations.
Cochrane Database Syst Rev. 5:CD147152024.
|
|
7
|
van Nisselrooij AEL, Teunissen AKK, Clur
SA, Rozendaal L, Pajkrt E, Linskens IH, Rammeloo L, van Lith JMM,
Blom NA and Haak MC: Why are congenital heart defects being missed?
Ultrasound Obstet Gynecol. 55:747–757. 2020. View Article : Google Scholar :
|
|
8
|
Hematian MN, Hessami K, Torabi S and Saleh
M, Nouri B and Saleh M: A prospective cohort study on association
of first-trimester serum biomarkers and risk of isolated foetal
congenital heart defects. Biomarkers. 26:747–751. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Wang X, Yang X, Huang P, Meng X, Bian Z
and Meng L: Identification of maternal serum biomarkers for
prenatal diagnosis of nonsyndromic orofacial clefts. Ann NY Acad
Sci. 1510:167–179. 2022. View Article : Google Scholar
|
|
10
|
Lupo PJ, Archer NP, Harris RD, Marengo LK,
Schraw JM, Hoyt AT, Tanksley S, Lee R, Drummond-Borg M, Freedenberg
D, et al: Newborn screening analytes and structural birth defects
among 27,000 newborns. PLoS One. 19:e3042382024. View Article : Google Scholar
|
|
11
|
Li L, He Z, Huang X, Lin S, Wu J, Huang L,
Wan Y and Fang Q: Chromosomal abnormalities detected by karyotyping
and microarray analysis in twins with structural anomalies.
Ultrasound Obstet Gynecol. 55:502–509. 2020. View Article : Google Scholar
|
|
12
|
Jayashankar SS, Nasaruddin ML, Hassan MF,
Dasrilsyah RA, Shafiee MN, Ismail NAS and Alias E: Non-invasive
prenatal testing (NIPT): Reliability, challenges, and future
directions. Diagnostics (Basel). 13:25702023. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Feldkamp ML, Carey JC, Byrne JLB, Krikov S
and Botto LD: Etiology and clinical presentation of birth defects:
Population based study. BMJ. 357:j22492017. View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Zhang J: What has genomics taught an
evolutionary biologist? Genom Proteom Bioinf. 21:1–12. 2023.
View Article : Google Scholar
|
|
15
|
Green ED, Gunter C, Biesecker LG, Di
Francesco V, Easter CL, Feingold EA, Felsenfeld AL, Kaufman DJ,
Ostrander EA, Pavan WJ, et al: Strategic vision for improving human
health at The Forefront of Genomics. Nature. 586:683–692. 2020.
View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Kosugi S, Momozawa Y, Liu X, Terao C, Kubo
M and Kamatani Y: Comprehensive evaluation of structural variation
detection algorithms for whole genome sequencing. Genome Biol.
20:1172019. View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Audano PA, Sulovari A, Graves-Lindsay TA,
Cantsilieris S, Sorensen M, Welch AE, Dougherty ML, Nelson BJ, Shah
A, Dutcher SK, et al: Characterizing the major structural variant
alleles of the human genome. Cell. 176:663–675. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Levy B and Wapner R: Prenatal diagnosis by
chromosomal microarray analysis. Fertil Steril. 109:201–212. 2018.
View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Committee Opinion No. 682 Summary:
Microarrays and Next-Generation Sequencing Technology: The use of
advanced genetic diagnostic tools in obstetrics and gynecology.
Obstet Gynecol. 128:1462–1463. 2016. View Article : Google Scholar
|
|
20
|
Hu P, Zhang Q, Cheng Q, Luo C, Zhang C,
Zhou R, Meng L, Huang M, Wang Y, Wang Y, et al: Whole genome
sequencing vs chromosomal microarray analysis in prenatal
diagnosis. Am J Obstet Gynecol. 229:301–302. 2023. View Article : Google Scholar
|
|
21
|
Lan L, Luo D, Lian J, She L, Zhang B,
Zhong H, Wang H and Wu H: Chromosomal abnormalities detected by
chromosomal microarray analysis and karyotype in fetuses with
ultrasound abnormalities. Int J Gen Med. 17:4645–4658. 2024.
View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Rodriguez-Revenga L, Madrigal I, Borrell
A, Martinez JM, Sabria J, Martin L, Jimenez W, Mira A, Badenas C
and Milà M: Chromosome microarray analysis should be offered to all
invasive prenatal diagnostic testing following a normal rapid
aneuploidy test result. Clin Genet. 98:379–383. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Xia M, Yang X, Fu J, Teng Z, Lv Y and Yu
L: Application of chromosome microarray analysis in prenatal
diagnosis. BMC Pregnancy Childbirth. 20:6962020. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Mangold E, Böhmer AC, Ishorst N, Hoebel
AK, Gültepe P, Schuenke H, Klamt J, Hofmann A, Gölz L, Raff R, et
al: Sequencing the GRHL3 coding region reveals rare truncating
mutations and a common susceptibility variant for nonsyndromic
cleft palate. AM J Hum Genet. 98:755–762. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Maya I, Salzer SL, Brabbing-Goldstein D,
Matar R, Kahana S, Agmon-Fishman I, Klein C, Gurevitch M,
Basel-Salmon L and Sagi-Dain L: Residual risk for clinically
significant copy number variants in low-risk pregnancies, following
exclusion of noninvasive prenatal screening-detectable findings. Am
J Obstet Gynecol. 226:562.e1–562.e8. 2022. View Article : Google Scholar
|
|
26
|
Liu X, Liu S, Wang H and Hu T: Potentials
and challenges of chromosomal microarray analysis in prenatal
diagnosis. Front Genet. 13:9381832022. View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Lee CL, Lee CH, Chuang CK, Chiu HC, Chen
YJ, Chou CL, Wu PS, Chen CP, Lin HY and Lin SP: Array-CGH increased
the diagnostic rate of developmental delay or intellectual
disability in Taiwan. Pediatr Neonatol. 60:453–460. 2019.
View Article : Google Scholar
|
|
28
|
Xie C and Tammi MT: CNV-seq, a new method
to detect copy number variation using high-throughput sequencing.
BMC Bioinformatics. 10:802009. View Article : Google Scholar : PubMed/NCBI
|
|
29
|
Wang J, Chen L, Zhou C, Wang L, Xie H,
Xiao Y, Zhu H, Hu T, Zhang Z, Zhu Q, et al: Prospective chromosome
analysis of 3429 amniocentesis samples in China using copy number
variation sequencing. AM J Obstet Gynecol. 219:287.e1–287.e18.
2018. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Yang L, Yang J, Bu G, Han R, Rezhake J and
La X: Efficiency of Non-invasive prenatal testing in detecting
fetal copy number variation: A retrospective cohort study. Int J
Womens Health. 16:1661–1669. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Wang X, Sha J, Han Y, Pang M, Liu M, Liu
M, Zhang B and Zhai J: Efficiency of copy number variation
sequencing combined with karyotyping in fetuses with congenital
heart disease and the following outcomes. Mol Cytogenet. 17:122024.
View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Huang Y, Fu S, Shao D, Yao Y, Wu F and Yao
M: Comprehensive chromosomal abnormality detection: Integrating
CNV-Seq with traditional karyotyping in prenatal diagnostics. BMC
Med Genomics. 18:812025. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Luo H, Wang Q, Fu D, Gao J and Lu D:
Additional diagnostic value of CNV-seq over conventional
karyotyping in prenatal diagnosis: A systematic review and
meta-analysis. J Obstet Gynaecol Res. 49:1641–1650. 2023.
View Article : Google Scholar : PubMed/NCBI
|
|
34
|
Ma N, Xi H, Chen J, Peng Y, Jia Z, Yang S,
Hu J, Pang J, Zhang Y, Hu R, et al: Integrated CNV-seq, karyotyping
and SNP-array analyses for effective prenatal diagnosis of
chromosomal mosaicism. BMC Med Genomics. 14:562021. View Article : Google Scholar : PubMed/NCBI
|
|
35
|
Zhao X and Fu L: Efficacy of copy-number
variation sequencing technology in prenatal diagnosis. J Perinat
Med. 47:651–655. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
36
|
Chen X, Jiang Y, Chen R, Qi Q, Zhang X,
Zhao S, Liu C, Wang W, Li Y, Sun G, et al: Clinical efficiency of
simultaneous CNV-seq and whole-exome sequencing for testing fetal
structural anomalies. J Transl Med. 20:102022. View Article : Google Scholar : PubMed/NCBI
|
|
37
|
Chen Y, Han X, Hua R, Li N, Zhang L, Hu W,
Wang Y, Qian Z and Li S: Copy number variation sequencing for the
products of conception: What is the optimal testing strategy. Clin
Chim Acta. 557:1178842024. View Article : Google Scholar : PubMed/NCBI
|
|
38
|
Yao R, Zhang C, Yu T, Li N, Hu X, Wang X,
Wang J and Shen Y: Evaluation of three read-depth based CNV
detection tools using whole-exome sequencing data. Mol Cytogenet.
10:302017. View Article : Google Scholar : PubMed/NCBI
|
|
39
|
Pei XM, Yeung MHY, Wong ANN, Tsang HF, Yu
ACS, Yim AKY and Wong SCC: Targeted sequencing approach and its
clinical applications for the molecular diagnosis of human
diseases. Cells. 12:4932023. View Article : Google Scholar : PubMed/NCBI
|
|
40
|
Hu P, Qiao F, Wang Y, Meng L, Ji X, Luo C,
Xu T, Zhou R, Zhang J, Yu B, et al: Clinical application of
targeted next-generation sequencing in fetuses with congenital
heart defect. Ultrasound Obstet Gynecol. 52:205–211. 2018.
View Article : Google Scholar : PubMed/NCBI
|
|
41
|
Gong B, Li D, Łabaj PP, Pan B,
Novoradovskaya N, Thierry-Mieg D, Thierry-Mieg J, Chen G, Bergstrom
Lucas A, LoCoco JS, et al: Targeted DNA-seq and RNA-seq of
reference samples with Short-read and Long-read sequencing. Sci
Data. 11:8922024. View Article : Google Scholar : PubMed/NCBI
|
|
42
|
Vora NL and Norton ME: Prenatal exome and
genome sequencing for fetal structural abnormalities. Am J Obstet
Gynecol. 228:140–149. 2023. View Article : Google Scholar :
|
|
43
|
Allen VM, Schollenberg E, Aberg E and
Brock JK: Use of Clinically informed strategies and diagnostic
yields of genetic testing for fetal structural anomalies following
a non-diagnostic microarray result: A Population-based cohort
study. Prenatal Diag. 45:318–325. 2025. View Article : Google Scholar : PubMed/NCBI
|
|
44
|
Pangalos C, Hagnefelt B, Lilakos K and
Konialis C: First applications of a targeted exome sequencing
approach in fetuses with ultrasound abnormalities reveals an
important fraction of cases with associated gene defects. PeerJ.
4:e19552016. View Article : Google Scholar : PubMed/NCBI
|
|
45
|
Li Y, Anderson LA, Ginns EI and Devlin JJ:
Cost effectiveness of karyotyping, chromosomal microarray analysis,
and targeted Next-generation sequencing of patients with
unexplained global developmental delay or intellectual disability.
Mol Diagn Ther. 22:129–138. 2018. View Article : Google Scholar
|
|
46
|
Li AH, Hanchard NA, Furthner D, Fernbach
S, Azamian M, Nicosia A, Rosenfeld J, Muzny D, D'Alessandro LCA,
Morris S, et al: Whole exome sequencing in 342 congenital cardiac
left sided lesion cases reveals extensive genetic heterogeneity and
complex inheritance patterns. Genome Med. 9:952017. View Article : Google Scholar : PubMed/NCBI
|
|
47
|
Tarozzi M, Bartoletti-Stella A, Dall'Olio
D, Matteuzzi T, Baiardi S, Parchi P, Castellani G and Capellari S:
Identification of recurrent genetic patterns from targeted
sequencing panels with advanced data science: A case-study on
sporadic and genetic neurodegenerative diseases. BMC Med Genomics.
15:262022. View Article : Google Scholar : PubMed/NCBI
|
|
48
|
Iyer SV, Goodwin S and McCombie WR:
Leveraging the power of long reads for targeted sequencing. Genome
Res. 34:1701–1718. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
49
|
Mandlik JS, Patil AS and Singh S:
Next-generation sequencing (NGS): Platforms and applications. J
Pharm Bioallied Sci. 16(Supp 1): S41–S45. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
50
|
Flores WG and Pereira WC: A contrast
enhancement method for improving the segmentation of breast lesions
on ultrasonography. Comput Biol Med. 80:14–23. 2017. View Article : Google Scholar
|
|
51
|
Jelin AC and Vora N: Whole Exome
sequencing: Applications in prenatal genetics. Obstet Gyn Clin N
Am. 45:69–81. 2018. View Article : Google Scholar
|
|
52
|
Chen M, Chen J, Wang C, Chen F, Xie Y, Li
Y, Li N, Wang J, Zhang VW and Chen D: Clinical application of
medical exome sequencing for prenatal diagnosis of fetal structural
anomalies. Eur J Obstet Gynecol Reprod Biol. 251:119–124. 2020.
View Article : Google Scholar : PubMed/NCBI
|
|
53
|
Emms A, Castleman J, Allen S, Williams D,
Kinning E and Kilby M: Next generation sequencing after invasive
prenatal testing in fetuses with congenital malformations: Prenatal
or neonatal investigation. Genes (Basel). 13:15172022. View Article : Google Scholar : PubMed/NCBI
|
|
54
|
Qin Y, Yao Y, Liu N, Wang B, Liu L, Li H,
Gao T, Xu R, Wang X, Zhang F and Song J: Prenatal whole-exome
sequencing for fetal structural anomalies: A retrospective analysis
of 145 Chinese cases. BMC Med Genomics. 16:2622023. View Article : Google Scholar : PubMed/NCBI
|
|
55
|
Pauta M, Martinez-Portilla RJ and Borrell
A: Diagnostic yield of exome sequencing in fetuses with multisystem
malformations: Systematic review and meta-analysis. Ultrasound
Obstet Gynecol. 59:715–722. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
56
|
Reches A, Hiersch L, Simchoni S, Barel D,
Greenberg R, Ben Sira L, Malinger G and Yaron Y: Whole-exome
sequencing in fetuses with central nervous system abnormalities. J
Perinatol. 38:1301–1308. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
57
|
Li M, Ye B, Chen Y, Gao L, Wu Y and Cheng
W: Analysis of genetic testing in fetuses with congenital heart
disease of single atria and/or single ventricle in a Chinese
prenatal cohort. BMC Pediatr. 23:5772023. View Article : Google Scholar : PubMed/NCBI
|
|
58
|
Jaillard S, McElreavy K, Robevska G,
Akloul L, Ghieh F, Sreenivasan R, Beaumont M, Bashamboo A,
Bignon-Topalovic J, Neyroud AS, et al: STAG3 homozygous missense
variant causes primary ovarian insufficiency and male
non-obstructive azoospermia. Mol Hum Reprod. 26:665–677. 2020.
View Article : Google Scholar : PubMed/NCBI
|
|
59
|
Chong AS, Chong G, Foulkes WD and Saskin
A: Reclassification of a frequent African-origin variant from PMS2
to the pseudogene PMS2CL. Hum Mutat. 41:749–752. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
60
|
Beaman MM, Yin W, Smith AJ, Sears PR,
Leigh MW, Ferkol TW, Kearney B, Olivier KN, Kimple AJ, Clarke S, et
al: Promoter deletion leading to allele specific expression in a
genetically unsolved case of primary ciliary dyskinesia. Am J Med
Genet A. 197:e638802025. View Article : Google Scholar
|
|
61
|
Sarwal V, Niehus S, Ayyala R, Kim M,
Sarkar A, Chang S, Lu A, Rajkumar N, Darfci-Maher N, Littman R, et
al: A comprehensive benchmarking of WGS-based deletion structural
variant callers. Brief Bioinform. 23:bbac2212022. View Article : Google Scholar : PubMed/NCBI
|
|
62
|
Lindstrand A, Eisfeldt J, Pettersson M,
Carvalho CMB, Kvarnung M, Grigelioniene G, Anderlid BM, Bjerin O,
Gustavsson P, Hammarsjö A, et al: From cytogenetics to
cytogenomics: Whole-genome sequencing as a first-line test
comprehensively captures the diverse spectrum of disease-causing
genetic variation underlying intellectual disability. Genome Med.
11:682019. View Article : Google Scholar : PubMed/NCBI
|
|
63
|
Reurink J, Weisschuh N, Garanto A, Dockery
A, van den Born LI, Fajardy I, Haer-Wigman L, Kohl S, Wissinger B,
Farrar GJ, et al: Whole genome sequencing for USH2A-associated
disease reveals several pathogenic deep-intronic variants that are
amenable to splice correction. HGG Adv. 4:1001812023.PubMed/NCBI
|
|
64
|
Fadaie Z, Whelan L, Ben-Yosef T, Dockery
A, Corradi Z, Gilissen C, Haer-Wigman L, Corominas J, Astuti GDN,
de Rooij L, et al: Whole genome sequencing and in vitro splice
assays reveal genetic causes for inherited retinal diseases. NPJ
Genom Med. 6:972021. View Article : Google Scholar : PubMed/NCBI
|
|
65
|
Goncalves A, Fortuna A, Ariyurek Y,
Oliveira ME, Nadais G, Pinheiro J, den Dunnen JT, Sousa M, Oliveira
J and Santos R: Integrating Whole-genome sequencing in clinical
genetics: A novel disruptive structural rearrangement identified in
the dystrophin gene (DMD). Int J Mol Sci. 23:592021. View Article : Google Scholar
|
|
66
|
Iurillo AM, Sharifi S and Jafferany M:
Artificial intelligence in dermatology: Ethical dilemmas and
diagnostic decisions. J Am Acad Dermatol. Aug 25–2025.Epub ahead of
print. View Article : Google Scholar : PubMed/NCBI
|
|
67
|
Kishikawa T, Momozawa Y, Ozeki T,
Mushiroda T, Inohara H, Kamatani Y, Kubo M and Okada Y: Empirical
evaluation of variant calling accuracy using ultra-deep
whole-genome sequencing data. Sci Rep. 9:17842019. View Article : Google Scholar : PubMed/NCBI
|
|
68
|
Dippenaar A, Ismail N, Heupink TH,
Grobbelaar M, Loubser J, Van Rie A and Warren RM: Droplet based
whole genome amplification for sequencing minute amounts of
purified Mycobacterium tuberculosis DNA. Sci Rep. 14:99312024.
View Article : Google Scholar : PubMed/NCBI
|
|
69
|
Testard Q, Vanhoye X, Yauy K, Naud ME,
Vieville G, Rousseau F, Dauriat B, Marquet V, Bourthoumieu S,
Geneviève D, et al: Exome sequencing as a first-tier test for copy
number variant detection: Retrospective evaluation and prospective
screening in 2418 cases. J Med Genet. 59:1234–1240. 2022.
View Article : Google Scholar : PubMed/NCBI
|
|
70
|
International Society for Prenatal
Diagnosis; Society for Maternal Fetal Medicine; Perinatal Quality
Foundation: Joint Position Statement from the International Society
for Prenatal Diagnosis (ISPD), the Society for Maternal Fetal
Medicine (SMFM), and the Perinatal Quality Foundation (PQF) on the
use of genome-wide sequencing for fetal diagnosis. Prenatal Diag.
38:6–9. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
71
|
Haller M, Au J, O'Neill M and Lamb DJ:
16p11.2 transcription factor MAZ is a dosage-sensitive regulator of
genitourinary development. Proc Natl Acad Sci U S A.
115:E1849–E1858. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
72
|
Flottmann R, Kragesteen BK, Geuer S, Socha
M, Allou L, Sowińska-Seidler A, Bosquillon de Jarcy L, Wagner J,
Jamsheer A, Oehl-Jaschkowitz B, et al: Noncoding copy-number
variations are associated with congenital limb malformation. Genet
Med. 20:599–607. 2018. View Article : Google Scholar
|
|
73
|
Costain G, Silversides CK and Bassett AS:
The importance of copy number variation in congenital heart
disease. NPJ Genom Med. 1:160312016. View Article : Google Scholar
|
|
74
|
Chen X, Shen Y, Gao Y, Zhao H, Sheng X,
Zou J, Lip V, Xie H, Guo J, Shao H, et al: Detection of copy number
variants reveals association of cilia genes with neural tube
defects. PLoS One. 8:e544922013. View Article : Google Scholar : PubMed/NCBI
|
|
75
|
Ehrlich L and Prakash SK: Copy-number
variation in congenital heart disease. Curr Opin Genet Dev.
77:1019862022. View Article : Google Scholar : PubMed/NCBI
|
|
76
|
Fulcoli FG, Franzese M, Liu X, Zhang Z,
Angelini C and Baldini A: Rebalancing gene haploinsufficiency in
vivo by targeting chromatin. Nat Commun. 7:116882016. View Article : Google Scholar : PubMed/NCBI
|
|
77
|
Zhao Y, Wang Y, Shi L, McDonald-McGinn DM,
Crowley TB, McGinn DE, Tran OT, Miller D, Lin JR, Zackai E, et al:
Chromatin regulators in the TBX1 network confer risk for
conotruncal heart defects in 22q11.2DS. NPJ Genom Med. 8:172023.
View Article : Google Scholar : PubMed/NCBI
|
|
78
|
Mlynarski EE, Sheridan MB, Xie M, Guo T,
Racedo SE, McDonald-McGinn DM, Gai X, Chow EW, Vorstman J, Swillen
A, et al: Copy-number variation of the glucose transporter gene
SLC2A3 and congenital heart defects in the 22q11.2 deletion
syndrome. Am J Hum Genet. 96:753–764. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
79
|
Lin S, Shi S, Lu J, He Z, Li D, Huang L,
Huang X, Zhou Y and Luo Y: Contribution of genetic variants to
congenital heart defects in both singleton and twin fetuses: A
Chinese cohort study. Mol Cytogenet. 17:22024. View Article : Google Scholar : PubMed/NCBI
|
|
80
|
Molck MC, Simioni M, Paiva VT, Sgardioli
IC, Paoli Monteiro F, Souza J, Fett-Conte AC, Félix TM, Lopes
Monlléo I and Gil-da-Silva-Lopes VL: Genomic imbalances in
syndromic congenital heart disease. J Pediatr (Rio J). 93:497–507.
2017. View Article : Google Scholar : PubMed/NCBI
|
|
81
|
Mak C, Chow PC, Liu APY, Chan KYK, Chu
YWY, Mok GTK, Leung GKC, Yeung KS, Chau AKT, Lowther C, et al: De
novo large rare copy-number variations contribute to conotruncal
heart disease in Chinese patients. NPJ Genom Med. 1:160332016.
View Article : Google Scholar : PubMed/NCBI
|
|
82
|
Dasouki MJ, Wakil SM, Al-Harazi O,
Alkorashy M, Muiya NP, Andres E, Hagos S, Aldusery H, Dzimiri N,
Colak D, et al: New insights into the impact of Genome-wide copy
number variations on complex congenital heart disease in Saudi
Arabia. OMICS. 24:16–28. 2020. View Article : Google Scholar
|
|
83
|
Lansdon LA, Dickinson A, Arlis S, Liu H,
Hlas A, Hahn A, Bonde G, Long A, Standley J, Tyryshkina A, et al:
Genome-wide analysis of copy-number variation in humans with cleft
lip and/or cleft palate identifies COBLL1, RIC1, and ARHGEF38 as
clefting genes. Am J Hum Genet. 110:71–91. 2023. View Article : Google Scholar :
|
|
84
|
Cao Y, Li Z, Rosenfeld JA, Pursley AN,
Patel A, Huang J, Wang H, Chen M, Sun X, Leung TY, et al:
Contribution of genomic copy-number variations in prenatal oral
clefts: A multi-center cohort study. Genet Med. 18:1052–1055. 2016.
View Article : Google Scholar : PubMed/NCBI
|
|
85
|
Younkin SG, Scharpf RB, Schwender H,
Parker MM, Scott AF, Marazita ML, Beaty TH and Ruczinski I: A
genome-wide study of de novo deletions identifies a candidate locus
for non-syndromic isolated cleft lip/palate risk. BMC Genet.
15:242014. View Article : Google Scholar : PubMed/NCBI
|
|
86
|
Younkin SG, Scharpf RB, Schwender H,
Parker MM, Scott AF, Marazita ML, Beaty TH and Ruczinski I: A
genome-wide study of inherited deletions identified two regions
associated with nonsyndromic isolated oral clefts. Birth Defects
Res A Clin Mol Teratol. 103:276–283. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
87
|
Vong KI, Lee S, Au KS, Crowley TB, Capra
V, Martino J, Haller M, Araújo C, Machado HR, George R, et al: Risk
of meningomyelocele mediated by the common 22q11.2 deletion.
Science. 384:584–590. 2024. View Article : Google Scholar : PubMed/NCBI
|
|
88
|
Wolujewicz P, Aguiar-Pulido V, AbdelAleem
A, Nair V, Thareja G, Suhre K, Shaw GM, Finnell RH, Elemento O and
Ross ME: Genome-wide investigation identifies a rare copy-number
variant burden associated with human spina bifida. Genet Med.
23:1211–1218. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
89
|
Tian T, Lei Y, Chen Y, Guo Y, Jin L,
Finnell RH, Wang L and Ren A: Rare copy number variations of planar
cell polarity genes are associated with human neural tube defects.
Neurogenetics. 21:217–225. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
90
|
Zhai Y, Zhang Z, Shi P, Martin DM and Kong
X: Incorporation of exome-based CNV analysis makes trio-WES a more
powerful tool for clinical diagnosis in neurodevelopmental
disorders: A retrospective study. Hum Mutat. 42:990–1004. 2021.
View Article : Google Scholar : PubMed/NCBI
|
|
91
|
Yang L, Wei Z, Chen X, Hu L, Peng X, Wang
J, Lu C, Kong Y, Dong X, Ni Q, et al: Use of medical exome
sequencing for identification of underlying genetic defects in
NICU: Experience in a cohort of 2303 neonates in China. Clin Genet.
101:101–109. 2022. View Article : Google Scholar
|
|
92
|
Sevim BC, Zhang P, Tristani-Firouzi M,
Gelb BD and Itan Y: De novo variants in exomes of congenital heart
disease patients identify risk genes and pathways. Genome Med.
12:92020. View Article : Google Scholar
|
|
93
|
Okashah S, Vasudeva D, El Jerbi A,
Khodjet-El-Khil H, Al-Shafai M, Syed N, Kambouris M, Udassi S,
Saraiva LR, Al-Saloos H, et al: Investigation of genetic causes in
patients with congenital heart disease in Qatar: Findings from the
Sidra cardiac Registry. Genes (Basel). 13:13692022. View Article : Google Scholar : PubMed/NCBI
|
|
94
|
Shi X, Zhang L, Bai K, Xie H, Shi T, Zhang
R, Fu Q, Chen S, Lu Y, Yu Y and Sun K: Identification of rare
variants in novel candidate genes in pulmonary atresia patients by
next generation sequencing. Comput Struct Biotechnol J. 18:381–392.
2020. View Article : Google Scholar : PubMed/NCBI
|
|
95
|
Shi X, Huang T, Wang J, Liang Y, Gu C, Xu
Y, Sun J, Lu Y, Sun K, Chen S and Yu Y: Next-generation sequencing
identifies novel genes with rare variants in total anomalous
pulmonary venous connection. EBioMedicine. 38:217–227. 2018.
View Article : Google Scholar : PubMed/NCBI
|
|
96
|
Basha M, Demeer B, Revencu N, Helaers R,
Theys S, Bou Saba S, Boute O, Devauchelle B, Francois G, Bayet B
and Vikkula M: Whole exome sequencing identifies mutations in 10%
of patients with familial non-syndromic cleft lip and/or palate in
genes mutated in well-known syndromes. J Med Genet. 55:449–458.
2018. View Article : Google Scholar : PubMed/NCBI
|
|
97
|
Hoebel AK, Drichel D, van de Vorst M,
Böhmer AC, Sivalingam S, Ishorst N, Klamt J, Gölz L, Alblas M,
Maaser A, et al: Candidate genes for nonsyndromic cleft palate
detected by exome sequencing. J Dent Res. 96:1314–1321. 2017.
View Article : Google Scholar : PubMed/NCBI
|
|
98
|
Awotoye W, Mossey PA, Hetmanski JB, Gowans
LJJ, Eshete MA, Adeyemo WL, Alade A, Zeng E, Adamson O, James O, et
al: Damaging mutations in AFDN contribute to risk of nonsyndromic
cleft lip with or without cleft palate. Cleft Palate Craniofac J.
61:697–705. 2024. View Article : Google Scholar
|
|
99
|
Fu Z, Yue J, Xue L, Xu Y, Ding Q and Xiao
W: Using whole exome sequencing to identify susceptibility genes
associated with nonsyndromic cleft lip with or without cleft
palate. Mol Genet Genomics. 298:107–118. 2023. View Article : Google Scholar
|
|
100
|
Kumari P, Singh SK and Raman R: TGFβ3,
MSX1, and MMP3 as Candidates for NSCL+/-P in an Indian population.
Cleft Palate-Cran J. 56:363–372. 2019. View Article : Google Scholar
|
|
101
|
Renard E, Chery C, Oussalah A, Josse T,
Perrin P, Tramoy D, Voirin J, Klein O, Leheup B, Feillet F, et al:
Exome sequencing of cases with neural tube defects identifies
candidate genes involved in one-carbon/vitamin B12 metabolisms and
Sonic Hedgehog pathway. Hum Genet. 138:703–713. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
102
|
Han X, Cao X, Aguiar-Pulido V, Yang W,
Karki M, Ramirez PAP, Cabrera RM, Lin YL, Wlodarczyk BJ, Shaw GM,
et al: CIC missense variants contribute to susceptibility for spina
bifida. Hum Mutat. 43:2021–2032. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
103
|
Lemay P, Guyot MC, Tremblay E,
Dionne-Laporte A, Spiegelman D, Henrion É, Diallo O, De Marco P,
Merello E, Massicotte C, et al: Loss-of-function de novo mutations
play an important role in severe human neural tube defects. J Med
Genet. 52:493–497. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
104
|
Chen Z, Kuang L, Finnell RH and Wang H:
Genetic and functional analysis of SHROOM1-4 in a Chinese neural
tube defect cohort. Hum Genet. 137:195–202. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
105
|
Lupo PJ, Mitchell LE and Jenkins MM:
Genome-wide association studies of structural birth defects: A
review and commentary. Birth Defects Res. 111:1329–1342. 2019.
View Article : Google Scholar : PubMed/NCBI
|
|
106
|
Abdellaoui A, Yengo L, Verweij KJH and
Visscher PM: 15 years of GWAS discovery: Realizing the promise. Am
J Hum Genet. 110:179–194. 2023. View Article : Google Scholar : PubMed/NCBI
|
|
107
|
Tam V, Patel N, Turcotte M, Bosse Y, Pare
G and Meyre D: Benefits and limitations of genome-wide association
studies. Nat Rev Genet. 20:467–484. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
108
|
Pirruccello JP, Di Achille P, Nauffal V,
Nekoui M, Friedman SF, Klarqvist MDR, Chaffin MD, Weng LC,
Cunningham JW, Khurshid S, et al: Genetic analysis of right heart
structure and function in 40,000 people. Nat Genet. 54:792–803.
2022. View Article : Google Scholar : PubMed/NCBI
|
|
109
|
Aung N, Vargas JD, Yang C, Fung K, Sanghvi
MM, Piechnik SK, Neubauer S, Manichaikul A, Rotter JI, Taylor KD,
et al: Genome-wide association analysis reveals insights into the
genetic architecture of right ventricular structure and function.
Nat Genet. 54:783–791. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
110
|
Lahm H, Jia M, Dreßen M, Wirth F, Puluca
N, Gilsbach R, Keavney BD, Cleuziou J, Beck N, Bondareva O, et al:
Congenital heart disease risk loci identified by genome-wide
association study in European patients. J Clin Invest.
131:e1418372021. View Article : Google Scholar :
|
|
111
|
Jin SC, Homsy J, Zaidi S, Lu Q, Morton S,
DePalma SR, Zeng X, Qi H, Chang W, Sierant MC, et al: Contribution
of rare inherited and de novo variants in 2,871 congenital heart
disease probands. Nat Genet. 49:1593–1601. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
112
|
Rojas-Martinez A, Reutter H,
Chacon-Camacho O, Leon-Cachon RB, Munoz-Jimenez SG, Nowak S, Becker
J, Herberz R, Ludwig KU, Paredes-Zenteno M, et al: Genetic risk
factors for nonsyndromic cleft lip with or without cleft palate in
a Mesoamerican population: Evidence for IRF6 and variants at 8q24
and 10q25. Birth Defects Res A Clin Mol Teratol. 88:535–537. 2010.
View Article : Google Scholar : PubMed/NCBI
|
|
113
|
Alade A, Peter T, Busch T, Awotoye W,
Anand D, Abimbola O, Aladenika E, Olujitan M, Rysavy O, Nguyen PF,
et al: Shared genetic risk between major orofacial cleft phenotypes
in an African population. Genet Epidemiol. 48:258–269. 2024.
View Article : Google Scholar : PubMed/NCBI
|
|
114
|
Gaczkowska A, Biedziak B, Budner M,
Zadurska M, Lasota A, Hozyasz KK, Dąbrowska J, Wójcicki P,
Szponar-Żurowska A, Żukowski K, et al: PAX7 nucleotide variants and
the risk of non-syndromic orofacial clefts in the Polish
population. Oral Dis. 25:1608–1618. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
115
|
Tindula G, Issac B, Mukherjee SK,
Ekramullah SM, Arman DM, Islam J, Suchanda HS, Sun L, Rockowitz S,
Christiani DC, et al: Genome-wide analysis of spina bifida risk
variants in a case-control study from Bangladesh. Birth Defects
Res. 116:e23312024. View Article : Google Scholar : PubMed/NCBI
|
|
116
|
King DA, Sifrim A, Fitzgerald TW, Rahbari
R, Hobson E, Homfray T, Mansour S, Mehta SG, Shehla M, Tomkins SE,
et al: Detection of structural mosaicism from targeted and
whole-genome sequencing data. Genome Res. 27:1704–1714. 2017.
View Article : Google Scholar : PubMed/NCBI
|
|
117
|
VanOudenhove J, Yankee TN, Wilderman A and
Cotney J: Epigenomic and transcriptomic dynamics during human heart
organogenesis. Circ Res. 127:e184–e209. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
118
|
Suhaimi SA, Zulkipli IN, Ghani H and
Abdul-Hamid M: Applications of next generation sequencing in the
screening and diagnosis of thalassemia: A mini-review. Front
Pediatr. 10:10157692022. View Article : Google Scholar : PubMed/NCBI
|
|
119
|
Bajaj LM, Agarwal S, Paliwal P, Saviour P,
Joshi A, Joshi A, Mahajan S, Bijarnia-Mahay S, Dua Puri R and Verma
IC: Prenatal diagnosis by chromosome microarray analysis, an Indian
experience. J Obstet Gynaecol India. 71:156–167. 2021. View Article : Google Scholar
|
|
120
|
Yin Y, Butler C and Zhang Q: Challenges in
the application of NGS in the clinical laboratory. Hum Immunol.
82:812–819. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
121
|
Povysil G, Petrovski S, Hostyk J, Aggarwal
V, Allen AS and Goldstein DB: Rare-variant collapsing analyses for
complex traits: guidelines and applications. Nat Rev Genet.
20:747–759. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
122
|
Giacopuzzi E, Popitsch N and Taylor JC:
GREEN-DB: A framework for the annotation and prioritization of
non-coding regulatory variants from whole-genome sequencing data.
Nucleic Acids Res. 50:2522–2535. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
123
|
Pei Y, Tanguy M, Giess A, Dixit A, Wilson
LC, Gibbons RJ, Twigg SRF, Elgar G and Wilkie AOM: A comparison of
structural variant calling from Short-read and Nanopore-based
Whole-genome sequencing using optical genome mapping as a
benchmark. Genes (Basel). 15:9252024. View Article : Google Scholar : PubMed/NCBI
|
|
124
|
Lu H, Giordano F and Ning Z: Oxford
nanopore MinION sequencing and genome assembly. Genomics Proteomics
Bioinformatics. 14:265–279. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
125
|
van Dijk EL, Jaszczyszyn Y, Naquin D and
Thermes C: The third revolution in sequencing technology. Trends
Genet. 34:666–681. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
126
|
Hassan S, Bahar R, Johan MF, Mohamed
Hashim EK, Abdullah WZ, Esa E, Abdul Hamid FS and Zulkafli Z:
Next-generation sequencing (NGS) and Third-Generation Sequencing
(TGS) for the diagnosis of thalassemia. Diagnostics (Basel).
13:3732023. View Article : Google Scholar : PubMed/NCBI
|
|
127
|
Jeffet J, Kobo A, Su T, Grunwald A, Green
O, Nilsson AN, Eisenberg E, Ambjörnsson T, Westerlund F, Weinhold
E, et al: Super-resolution genome mapping in silicon nanochannels.
ACS Nano. 10:9823–9830. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
128
|
Sahajpal NS, Dean J, Hilton B, Fee T,
Skinner C, Hastie A, DuPont BR, Chaubey A, Friez MJ and Stevenson
RE: Optical genome mapping identifies rare structural variants in
neural tube defects. Genome Res. 35:798–809. 2025. View Article : Google Scholar : PubMed/NCBI
|
|
129
|
Tang D, Freudenberg J and Dahl A:
Factorizing polygenic epistasis improves prediction and uncovers
biological pathways in complex traits. Am J Hum Genet.
110:1875–1887. 2023. View Article : Google Scholar : PubMed/NCBI
|
|
130
|
Zhang W, Dai X, Wang Q, Xu S and Zhao PX:
PEPIS: A pipeline for estimating epistatic effects in quantitative
trait locus mapping and genome-wide association studies. PLoS
Comput Biol. 12:e10049252016. View Article : Google Scholar : PubMed/NCBI
|
|
131
|
Wang S, Ge S, Sobkowiak B, Wang L,
Grandjean L, Colijn C and Elliott LT: Genome-Wide association with
uncertainty in the genetic similarity matrix. J Comput Biol.
30:189–203. 2023. View Article : Google Scholar
|
|
132
|
Bose A, Burch M, Chowdhury A, Paschou P
and Drineas P: Structure-informed clustering for population
stratification in association studies. BMC Bioinformatics.
24:4112023. View Article : Google Scholar : PubMed/NCBI
|
|
133
|
Zhang D, Zhou S, Zhou Z, Jiang X, Chen D,
Sun HX, Huang J, Qu S, Yang S, Gu Y, et al: BDdb: A comprehensive
platform for exploration and utilization of birth defect
multi-omics data. BMC Med Genomics. 14:2602021. View Article : Google Scholar : PubMed/NCBI
|
|
134
|
Kernohan KD and Boycott KM: The expanding
diagnostic toolbox for rare genetic diseases. Nat Rev Genet.
25:401–415. 2024. View Article : Google Scholar : PubMed/NCBI
|