Gallagher MD, Chen-Plotkin AS. The post-GWAS era: from association to function. Am J Hum Genet. 2018;102:717–30.
Article
CAS
PubMed
PubMed Central
Google Scholar
Spielman RS, Bastone LA, Burdick JT, Morley M, Ewens WJ, Cheung VG. Common genetic variants account for differences in gene expression among ethnic groups. Nat Genet. 2007;39:226–31.
Article
CAS
PubMed
PubMed Central
Google Scholar
Wainberg M, Sinnott-Armstrong N, Mancuso N, Barbeira AN, Knowles DA, Golan D, et al. Opportunities and challenges for transcriptome-wide association studies. Nat Genet. 2019;51:592–9.
Article
CAS
PubMed
PubMed Central
Google Scholar
Battle A, Khan Z, Wang SH, Mitrano A, Ford MJ, Pritchard JK, et al. Genomic variation. Impact of regulatory variation from RNA to protein. Science. 2015;347:664–7.
Article
CAS
PubMed
Google Scholar
Bader DM, Wilkening S, Lin G, Tekkedil MM, Dietrich K, Steinmetz LM, et al. Negative feedback buffers effects of regulatory variants. Mol Syst Biol. 2015;11:785.
Article
PubMed
PubMed Central
Google Scholar
Gobet C, Naef F. Ribosome profiling and dynamic regulation of translation in mammals. Curr Opin Genet Dev. 2017;43:120–7.
Article
CAS
PubMed
Google Scholar
Gorgoni B, Marshall E, McFarland MR, Romano MC, Stansfield I. Controlling translation elongation efficiency: tRNA regulation of ribosome flux on the mRNA. Biochem Soc Trans. 2014;42:160–5.
Article
CAS
PubMed
Google Scholar
Dephoure N, Hwang S, O’Sullivan C, Dodgson SE, Gygi SP, Amon A, et al. Quantitative proteomic analysis reveals posttranslational responses to aneuploidy in yeast. eLife. 2014;3:e03023.
Article
PubMed
PubMed Central
CAS
Google Scholar
Gandhi SJ, Zenklusen D, Lionnet T, Singer RH. Transcription of functionally related constitutive genes is not coordinated. Nat Struct Mol Biol. 2011;18:27–34.
Article
CAS
PubMed
Google Scholar
Li GW, Burkhardt D, Gross C, Weissman JS. Quantifying absolute protein synthesis rates reveals principles underlying allocation of cellular resources. Cell. 2014;157:624–35.
Article
CAS
PubMed
PubMed Central
Google Scholar
Vogel C, Marcotte EM. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat Rev Genet. 2012;13:227–32.
Article
CAS
PubMed
PubMed Central
Google Scholar
Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, et al. The structure of haplotype blocks in the human genome. Science. 2002;296:2225–9.
Article
CAS
PubMed
Google Scholar
Lappalainen T, Sammeth M, Friedländer MR, ’t Hoen PAC, Monlong J, Rivas MA, et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature. 2013;501:506–11 13 Behera V, Evans P, Face CJ, Hamagami N, Sankaranarayanan L, Keller CA, et al. Exploiting genetic variation to uncover rules of transcription factor binding and chromatin accessibility. Nat Commun. 2018;9:782.
Article
CAS
PubMed
PubMed Central
Google Scholar
Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136:215–33.
Article
CAS
PubMed
PubMed Central
Google Scholar
Grimson A, Farh KKH, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP. MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Mol Cell. 2007;27:91–105.
Article
CAS
PubMed
PubMed Central
Google Scholar
Riba A, Di Nanni N, Mittal N, Arhné E, Schmidt A, Zavolan M. Protein synthesis rates and ribosome occupancies reveal determinants of translation elongation rates. Proc Natl Acad Sci U S A. 2019;116:15023–32.
Article
CAS
PubMed
PubMed Central
Google Scholar
Ryu J, Lee C. Regulatory nucleotide sequence signals for expression of the genes encoding ribosomal proteins. Front Genet. 2020;11:501.
Article
CAS
PubMed
PubMed Central
Google Scholar
Kenmochi N, Suzuki T, Uechi T, Magoori M, Kuniba M, Higa S, et al. The human mitochondrial ribosomal protein genes: mapping of 54 genes to the chromosomes and implications for human disorders. Genomics. 2001;77:65–70.
Article
CAS
PubMed
Google Scholar
Carroll CJ, Isohanni P, Pöyhönen R, Euro L, Richter U, Brilhante V, et al. Whole-exome sequencing identifies a mutation in the mitochondrial ribosome protein MRPL44 to underlie mitochondrial infantile cardiomyopathy. J Med Genet. 2013;50:151–9.
Article
CAS
PubMed
Google Scholar
Galmiche L, Serre V, Beinat M, Zahra Assouline Z, Lebre A-S, Chretien D, et al. Exome sequencing identifies MRPL3 mutation in mitochondrial cardiomyopathy. Hum Mutat. 2011;32:1225–31.
Article
CAS
PubMed
Google Scholar
Serre V, Rozanska A, Beinat M, Chretien D, Boddaert N, Munnich A, et al. Mutations in mitochondrial ribosomal protein MRPL12 leads to growth retardation, neurological deterioration and mitochondrial translation deficiency. Biochim Biophys Acta. 2013;1832:1304–12.
Article
CAS
PubMed
PubMed Central
Google Scholar
Das S, Abecasis GR, Browning BL. Genotype imputation from large reference panels. Annu Rev Genomics Hum Genet. 2018;19:73–96.
Article
CAS
PubMed
Google Scholar
Lee C. Genome-wide expression quantitative trait loci analysis using mixed models. Front Genet. 2018;9:341.
Article
PubMed
PubMed Central
CAS
Google Scholar
Lee C. Best linear unbiased prediction of individual polygenic susceptibility to sporadic vascular dementia. J Alzheimers Dis. 2016;53:1115–9.
Article
PubMed
Google Scholar
Pickrell JK, Marioni JC, Pai AA, Degner JF, Engelhardt BE, Nkadori E, et al. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature. 2010a;464:768–72.
Article
CAS
PubMed
PubMed Central
Google Scholar
Pickrell JK, Pai AA, Gilad Y, Pritchard JK. Noisy splicing drives mRNA isoform diversity in human cells. Plos Genet. 2010b;6:e1001236.
Article
PubMed
PubMed Central
CAS
Google Scholar
Degner JF, Pai AA, Pique-Regi R, Veyrieras J-B, Gaffney DJ, Pickrell JK, et al. DNase I sensitivity QTLs are a major determinant of human expression variation. Nature. 2012;482:390–4.
Article
CAS
PubMed
PubMed Central
Google Scholar
1000 Genomes Project Consortium. A global reference for human genetic variation. Nature. 2015;526:68–74.
Article
CAS
Google Scholar
Shin J, Lee C. A mixed model reduces spurious genetic associations produced by population stratification in genome-wide association studies. Genomics. 2015;105:191–6.
Article
CAS
PubMed
Google Scholar
Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. 2011;88:76–82.
Article
CAS
PubMed
PubMed Central
Google Scholar
Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21:263–5.
Article
CAS
PubMed
Google Scholar
Bell JT, Pai AA, Pickrell JK, Gaffney DJ, Pique-Regi R, Degner JF, et al. DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol. 2011;12:R10.
Article
CAS
PubMed
PubMed Central
Google Scholar
Bonder MJ, Luijk R, Zhernakova DV, Moed M, Deelen P, Vermaat M, et al. Disease variants alter transcription factor levels and methylation of their binding sites. Nat Genet. 2017;49:131–8.
Article
CAS
PubMed
Google Scholar
Grubert F, Zaugg JB, Kasowski M, Ursu O, Spacek DV, Martin AR, et al. Genetic control of chromatin states in humans involves local and distal chromosomal interactions. Cell. 2015;162:1051–65.
Article
CAS
PubMed
PubMed Central
Google Scholar
Roadmap Epigenomics Consortium, Kundaje A, Meuleman W, Ernst J, Bilenky M, Yen A, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518:317–30.
Article
PubMed Central
CAS
Google Scholar
ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489:57–74.
Article
CAS
Google Scholar
Ward LD, Kellis M. HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease. Nucleic Acids Res. 2016;44:D877–81.
Article
CAS
PubMed
Google Scholar
Matys V, Fricke E, Geffers R, Gössling E, Haubrock M, Hehl R, et al. TRANSFAC®: transcriptional regulation, from patterns to profiles. Nucleic Acids Res. 2003;31:374–8.
Article
CAS
PubMed
PubMed Central
Google Scholar
Portales-Casamar E, Thongjuea S, Kwon AT, Arenillas D, Zhao X, Valen E, et al. JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles. Nucleic Acids Res. 2010;38:D105–10.
Article
CAS
PubMed
Google Scholar
Badis G, Berger MF, Philippakis AA, Talukder S, Gehrke AR, Jaeger SA, et al. Diversity and complexity in DNA recognition by transcription factors. Science. 2009;324:1720–3.
Article
CAS
PubMed
PubMed Central
Google Scholar
Berger MF, Badis G, Gehrke AR, Talukder S, Philippakis AA, Peña-Castillo L, et al. Variation in homeodomain DNA binding revealed by high-resolution analysis of sequence preferences. Cell. 2008;133:1266–76.
Article
CAS
PubMed
PubMed Central
Google Scholar
Berger MF, Philippakis AA, Qureshi AM, He FS, Estep PW 3rd, Bulyk ML. Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities. Nat Biotechnol. 2006;24:1429–35.
Article
CAS
PubMed
PubMed Central
Google Scholar
Chen J, Rozowsky J, Galeev TR, Harmanci A, Kitchen R, Bedford J, et al. A uniform survey of allele-specific binding and expression over 1000-genomes-project individuals. Nat Commun. 2016;7:11101.
Article
CAS
PubMed
PubMed Central
Google Scholar
Fishilevich S, Nudel R, Rappaport N, Hadar R, Plaschkes I, Iny Stein T, et al. GeneHancer: genome-wide integration of enhancers and target genes in GeneCards. Database. 2017;2017:bax028.
Zhernakova DV, Deelen P, Vermaat M, van Iterson M, van Galen M, Arindrarto W, et al. Identification of context-dependent expression quantitative trait loci in whole blood. Nat Genet. 2017;49:139–45.
Article
CAS
PubMed
Google Scholar
Pai AA, Cain CE, Mizrahi-Man O, De Leon S, Lewellen N, Veyrieras J-B, et al. The contribution of RNA decay quantitative trait loci to inter-individual variation in steady-state gene expression levels. Plos Genet. 2012;8:e1003000.
Article
CAS
PubMed
PubMed Central
Google Scholar
Piva F, Giulietti M, Burini AB, Principato G. SpliceAid 2: a database of human splicing factors expression data and RNA target motifs. Hum Mutat. 2012;33:81–5.
Article
CAS
PubMed
Google Scholar
Wang X. Improving microRNA target prediction by modeling with unambiguously identified microRNA-target pairs from CLIP-ligation studies. Bioinformatics. 2016;32:1316–22.
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhou J, Theesfeld CL, Yao K, Chen KM, Wong AK, Troyanskaya OG. Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk. Nat Genet. 2018;50:1171–9.
Article
CAS
PubMed
PubMed Central
Google Scholar
Jaganathan K, Kyriazopoulou PSK, McRae JF, Darbandi SF, Knowles D, Li YI, et al. Predicting splicing from primary sequence with deep learning. Cell. 2019;176:535–48.e24.
Article
CAS
PubMed
Google Scholar
Gu T, Zhao X, Barbazuk WB, Lee JH. miTAR: a hybrid deep learning-based approach for predicting miRNA targets. BMC Bioinformatics. 2021;22:96.
Article
CAS
PubMed
PubMed Central
Google Scholar