Alan P. Boyle, Ph.D.

Principal Investigator since September 2014
Associate Professor, Computational Biology & Bioinformatics and Human Genetics

Research areas

  • Non-coding variation
  • Silencer Biology
  • Gene Regulation
  • High-throughput genomics

Education

  • B.S.: Biochemistry, Mississippi State University (2005)
  • B.S.: Computer Science, Mississippi State University (2005)
  • Ph.D.: Computational Biology and Bioinformatics, Duke University (2009)
  • Postdoc: Stanford University (2014)

Background

Alan Boyle (Computational Medicine and Bioinformatics, Human Genetics) completed his PhD in Computational Biology and Bioinformatics at Duke University where he developed methods to map open chromatin and his postdoctoral research at Stanford University where he developed new methods for interpreting non-coding variation and worked as part of ENCODE and modENCODE. Currently, he works to improve the interpretation of non-coding variation to extend from association to biological function and works to map and characterize regulatory elements in the non-coding genome. He is PI of a U41 to annotate regulatory variation and a PI of a NSF CAREER award to study the combinatorial effect of transcription factors on gene regulation.

Boyle lab papers

  1. Phanstiel DH, Boyle AP, Heidari N, Snyder MP. 2015. Mango: A bias correcting ChIA-PET analysis pipeline. Bioinformatics. DOI: 10.1093/bioinformatics/btv336.

  2. Diehl AG and Boyle AP. 2016. Deciphering ENCODE. Trends in Genetics. 32: 238-249. DOI: 10.1016/j.tig.2016.02.002.

  3. *Yang B, *Zhou W, *Jiao J, Nielsen JB, Mathis MR, Heydarpour M, Lettre G, Folkersen L, Prakash S, Schurmann C, Fritsche L, Farnum GA, Lin M, Othman M, Hornsby W, Driscoll A, Levasseur A, Thomas M, Farhat L, Dubé MP, Isselbacher EM, Franco-Cereceda A, Guo Dc, Bottinger EP, Deeb GM, Booher A, Kheterpal S, Chen YE, Kang HM, Kitzman J, Cordell HJ, Keavney BD, Goodship JA, Ganesh SK, Abecasis G, Eagle KA, Boyle AP, Loos RJF, †Eriksson P, †Tardif JC, †Brummett CM, †Milewicz DM, †Body SC, †Willer CJ. 2017. Protein-altering and regulatory genetic variants near GATA4 implicated in bicuspid aortic valve. Nature Communications. 8: 15481. DOI: 10.1038/ncomms15481.

  4. Spadafore M, Najarian K, Boyle AP. 2017. A proximity-based graph clustering method for the identification and application of transcription factor clusters. BMC Bioinformatics. 18: DOI: 10.1186/s12859-017-1935-y.

  5. Nishizaki SS and Boyle AP. 2017. Mining the Unknown: Assigning Function to Noncoding Single Nucleotide Polymorphisms. Trends in Genetics. 33: 34-45. DOI: 10.1016/j.tig.2016.10.008.

  6. Nielsen JB, Fritsche LG, Zhou W, Teslovich TM, Holmen OL, Gustafsson S, Gabrielsen ME, Schmidt EM, Beaumont R, Wolford BN, Lin M, Brummett CM, Preuss MH, Refsgaard L, Bottinger EP, Graham SE, Surakka I, Chu Y, Skogholt AH, Dalen H, Boyle AP, Oral H, Herron TJ, Kitzman J, Jalife J, Svendsen JH, Olesen MS, Njølstad I, Løchen ML, Baras A, Gottesman O, Marcketta A, O'Dushlaine C, Ritchie MD, Wilsgaard T, Loos RJF, Frayling TM, Boehnke M, Ingelsson E, Carey DJ, Dewey FE, Kang HM, Abecasis GR, Hveem K, Willer CJ. 2017. Genome-wide Study of Atrial Fibrillation Identifies Seven Risk Loci and Highlights Biological Pathways and Regulatory Elements Involved in Cardiac Development. Human Genetics. 102: 103-115. DOI: 10.1016/j.ajhg.2017.12.003.

  7. Varshney A, VanRenterghem H, Orchard P, †Boyle AP, †Stitzel ML, †Ucar D, Parker SC. 2018. Cell specificity of regulatory annotations and their genetic effects on gene expression. Genetics. DOI: 10.1534/genetics.118.301525.

  8. Diehl AG and Boyle AP. 2018. Conserved and species-specific transcription factor co-binding patterns drive divergent gene regulation in human and mouse. Nucleic Acids Research. 46: 1878-1894. DOI: 10.1093/nar/gky018.

  9. Shigaki D, Adato O, Adhikar AN, Dong S, Hawkins-Hooker A, Inoue F, Juven-Gershon T, Kenlay H, Martin B, Patra A, Penar DP, Schubach M, Xiong C, Yan Z, Boyle AP, Kreimer A, Kulakovskiy IV, Reid J, Unger R, Yosef N, Shendure J, Ahituv N, Kircher M, and Beer MA. 2019. Integration of Multiple Epigenomic Marks Improves Prediction of Variant Impact in Saturation Mutagenesis Reporter Assay. Human Mutation. 40: 1280-1291. DOI: 10.1002/humu.23797.

  10. Nishizaki SS, Ng N, Dong S, Porter RS, Morterud C, Williams C, Asman C, Switzenberg JA, and Boyle AP. 2019. Predicting the effects of SNPs on transcription factor binding affinity. Bioinformatics. 50: 2434. DOI: 10.1093/bioinformatics/btz612.

  11. Dong S and Boyle AP. 2019. Predicting functional variants in enhancer and promoter elements using RegulomeDB. Human Mutation. 40: 1292-1298. DOI: 10.1002/humu.23791.

  12. Diehl AD and Boyle AP. 2019. CGIMP: Real-time exploration and covariate projection for self-organizing map datasets. Journal of Open Source Science. 4: 1520. DOI: 10.21105/joss.01520.

  13. Amemiya HM, Kundaje A, and Boyle AP. 2019. The ENCODE Blacklist: Identification of Problematic Regions of the Genome. Scientific Reports. 9: 9354.

  14. Tsuzuki M, Sethuraman S, Coke AN, Rothi MH, Boyle AP and Wierzbicki AT. 2020. Broad noncoding transcription suggests genome surveillance by RNA polymerase V. Proceedings of the National Academy of Sciences. 117: 30799-30804. DOI: 10.1073/pnas.2014419117.

  15. Ouyang N and Boyle AP. 2020. TRACE: transcription factor footprinting using chromatin accessibility data and DNA sequence. Genome Research. 30: 1040-1046. DOI: 10.1101/gr.258228.119.

  16. Nishizaki SS and Boyle AP. 2020. SEMplMe: A tool for integrating DNA methylation effects in transcription factor binding affinity predictions. bioRxiv. DOI: 10.1101/2020.08.13.250118v2.

  17. Lee CT, Cavalcante RG, Lee C, Qin T, Patil S, Wang S, Tsai ZT, Boyle AP, Sartor MA. 2020. Poly-Enrich: count-based methods for gene set enrichment testing with genomic regions. NAR Genomics and Bioinformatics. 2: lqaa006. DOI: 10.1093/nargab/lqaa006.

  18. Diehl AD and Boyle AP. 2020. MapGL: Inferring evolutionary gain and loss of short genomic sequence features by phylogenetic maximum parsimony. BMC Bioinformatics. 21: 416. DOI: 10.1186/s12859-020-03742-9.

  19. Diehl AD, Ouyang N, and Boyle AP. 2020. Transposable elements contribute to cell and species-specific chromatin looping and gene regulation in mammalian genomes.. Nature Communications. 1: 1796. DOI: 10.1038/s41467-020-15520-5.

  20. Zhao N and Boyle AP. 2021. F-Seq2: improving the feature density based peak caller with dynamic statistics. NAR Genomics and Bioinformatics. 3: lqab012. DOI: 10.1093/nargab/lqab012.

  21. Rothi MH, Sethuraman S, Dolata J, Boyle AP and Wierzbicki AT. 2021. DNA methylation directs nucleosome positioning in RNA-mediated transcriptional silencing. bioRxiv. DOI: 10.1101/2020.10.29.359794.

  22. Nishizaki SS, McDonald TL, Farnum GA, Holmes MJ, Drexel ML, Switzenberg JA, Boyle AP. 2021. The inducible lac operator-repressor system is functional in zebrafish cells. Frontiers in Genetics. 12: 994. DOI: 10.3389/fgene.2021.683394.

  23. McDonald TL, Zhou W, Castro CP, Mumm C, Switzenberg JA, Mills RE and Boyle AP. 2021. Cas9 targeted enrichment of mobile elements using nanopore sequencing. Nature Communications. 12: 3586. DOI: 10.1038/s41467-021-23918-y.

  24. Dong S and Boyle AP. 2021. Preprint: Prioritization of regulatory variants with tissue-specific function in the non-coding regions of human genome. DOI: .