Page 121 - Read Online

Page 255 Ratnapriya. J Transl Genet Genom 2022;6:240-256 https://dx.doi.org/10.20517/jtgg.2021.54

70. Jaitin DA, Kenigsberg E, Keren-Shaul H, et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into
cell types. Science 2014;343:776-9. DOI PubMed PMC
71. Regev A, Teichmann SA, Lander ES, et al; Human Cell Atlas Meeting Participants. The human cell atlas. Elife 2017;6:e27041. DOI
PubMed PMC
72. Mathys H, Davila-Velderrain J, Peng Z, et al. Single-cell transcriptomic analysis of Alzheimer’s disease. Nature 2019;570:332-7.
DOI PubMed PMC
73. Agarwal D, Sandor C, Volpato V, et al. A single-cell atlas of the human substantia nigra reveals cell-specific pathways associated
with neurological disorders. Nat Commun 2020;11:4183. DOI PubMed PMC
74. Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat
Methods 2008;5:621-8. DOI PubMed
75. Stark R, Grzelak M, Hadfield J. RNA sequencing: the teenage years. Nat Rev Genet 2019;20:631-56. DOI PubMed
76. Wang Y, Navin NE. Advances and applications of single-cell sequencing technologies. Mol Cell 2015;58:598-609. DOI PubMed
PMC
77. Schaid DJ, Chen W, Larson NB. From genome-wide associations to candidate causal variants by statistical fine-mapping. Nat Rev
Genet 2018;19:491-504. DOI PubMed PMC
78. Nicolae DL, Gamazon E, Zhang W, Duan S, Dolan ME, Cox NJ. Trait-associated SNPs are more likely to be eQTLs: annotation to
enhance discovery from GWAS. PLoS Genet 2010;6:e1000888. DOI PubMed PMC
79. Nica AC, Montgomery SB, Dimas AS, et al. Candidate causal regulatory effects by integration of expression QTLs with complex
trait genetic associations. PLoS Genet 2010;6:e1000895. DOI PubMed PMC
80. Ratnapriya R, Sosina OA, Starostik MR, et al. Retinal transcriptome and eQTL analyses identify genes associated with age-related
macular degeneration. Nat Genet 2019;51:606-10. DOI PubMed PMC
81. Albert FW, Kruglyak L. The role of regulatory variation in complex traits and disease. Nat Rev Genet 2015;16:197-212. DOI
PubMed
82. Cookson W, Liang L, Abecasis G, Moffatt M, Lathrop M. Mapping complex disease traits with global gene expression. Nat Rev
Genet 2009;10:184-94. DOI PubMed PMC
83. Gilad Y, Rifkin SA, Pritchard JK. Revealing the architecture of gene regulation: the promise of eQTL studies. Trends Genet
2008;24:408-15. DOI PubMed PMC
84. Hukku A, Pividori M, Luca F, Pique-Regi R, Im HK, Wen X. Probabilistic colocalization of genetic variants from complex and
molecular traits: promise and limitations. Am J Hum Genet 2021;108:25-35. DOI PubMed PMC
85. Strunz T, Kiel C, Grassmann F, et al. A mega-analysis of expression quantitative trait loci in retinal tissue. PLoS Genet
2020;16:e1008934. DOI PubMed PMC
86. Orozco LD, Chen HH, Cox C, et al. Integration of eQTL and a single-cell atlas in the human eye identifies causal genes for age-
related macular degeneration. Cell Rep 2020;30:1246-59.e6. DOI PubMed
87. Liu B, Calton MA, Abell NS, et al. Genetic analyses of human fetal retinal pigment epithelium gene expression suggest ocular
disease mechanisms. Commun Biol 2019;2:186. DOI PubMed PMC
88. White MJ, Yaspan BL, Veatch OJ, Goddard P, Risse-Adams OS, Contreras MG. Strategies for pathway analysis using GWAS and
WGS data. Curr Protoc Hum Genet 2019;100:e79. DOI PubMed PMC
89. Waksmunski AR, Grunin M, Kinzy TG, Igo RP Jr, Haines JL, Cooke Bailey JN; International Age-Related Macular Degeneration
Genomics Consortium. Pathway analysis integrating genome-wide and functional data identifies PLCG2 as a candidate gene for age-
related macular degeneration. Invest Ophthalmol Vis Sci 2019;60:4041-51. DOI PubMed PMC
90. Sekar S, McDonald J, Cuyugan L, et al. Alzheimer’s disease is associated with altered expression of genes involved in immune
response and mitochondrial processes in astrocytes. Neurobiol Aging 2015;36:583-91. DOI PubMed PMC
91. Fromer M, Roussos P, Sieberts SK, et al. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat
Neurosci 2016;19:1442-53. DOI PubMed PMC
92. Tian L, Kazmierkiewicz KL, Bowman AS, Li M, Curcio CA, Stambolian DE. Transcriptome of the human retina, retinal pigmented
epithelium and choroid. Genomics 2015;105:253-64. DOI PubMed PMC
93. Newman AM, Gallo NB, Hancox LS, et al. Systems-level analysis of age-related macular degeneration reveals global biomarkers and
phenotype-specific functional networks. Genome Med 2012;4:16. DOI PubMed PMC
94. Pauly D, Agarwal D, Dana N, et al. Cell-type-specific complement expression in the healthy and diseased retina. Cell Rep
2019;29:2835-48.e4. DOI PubMed PMC
95. Zhang B, Horvath S. A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol
2005;4:Article17. DOI PubMed
96. Calabrese GM, Mesner LD, Stains JP, et al. Integrating GWAS and co-expression network data identifies bone mineral density genes
SPTBN1 and MARK3 and an osteoblast functional module. Cell Syst 2017;4:46-59.e4. DOI PubMed PMC
97. Gustafsson M, Gawel DR, Alfredsson L, et al. A validated gene regulatory network and GWAS identifies early regulators of T cell-
associated diseases. Sci Transl Med 2015;7:313ra178. DOI PubMed
98. Mäkinen VP, Civelek M, Meng Q, et al; Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM)
Consortium. Integrative genomics reveals novel molecular pathways and gene networks for coronary artery disease. PLoS Genet
2014;10:e1004502. DOI PubMed PMC