2
12
18
28
12
12
1a
14
e
12
16
a
a
2
2
a
20
32
1a
2a
19
Faculty
61 16
19
1
49
2
2
1a
32
34
1b
1d
18
2c
53
1d
2 29
1d
25
Yi Xing, Ph.D.
78
53
Professor of Pathology and Laboratory Medicine
7
78
Department: Pathology and Laboratory Medicine
4
1
23
1f
Graduate Group Affiliations
8
a
b
1d
46
Contact information
51
4
3
3
3
2
4
b
1f
51
Children's Hospital of Philadelphia
30 9054 Colket Translational Research Bldg.
3a 3501 Civic Center Blvd.
Philadelphia, PA 19104
26
30 9054 Colket Translational Research Bldg.
3a 3501 Civic Center Blvd.
Philadelphia, PA 19104
2e
Office: 215-590-0280
30
7f
30
Email:
xingyi@chop.edu
12
xingyi@chop.edu
13
Education:
21 a Ph.D. 2e (Molecular Biology, Bioinformatics) c
3d University of California Los Angeles, 2006.
c
3
27
5
3
3
92
Permanent link21 a Ph.D. 2e (Molecular Biology, Bioinformatics) c
3d University of California Los Angeles, 2006.
c
2 29
21
1e
1d
24
76
d1 Our lab is broadly interested in the computational biology and genomics of RNA processing and regulation, as well as their applications to human genetics, precision medicine, and cancer immunotherapy.
8
30 Description of Research
450 Mammalian cells generate astonishing regulatory diversity and complex phenotypes from a surprisingly small set of genes. We now know that considerable diversity is achieved by alternative processing and modifications of RNA. The long-term goal of our research is to elucidate alternative isoform complexity in mammalian transcriptomes and proteomes, and to understand how it is generated and its role in the regulation and function of complex genomes. We develop computational methods and genomic technologies for studying transcriptomic and proteomic complexity in bulk tissues and single cells (Science Advances, 2023; Nature Communications, 2021; AJHG 2020a; Nature Methods, 2019; AJHG, 2019; Genome Biology, 2017; Nature Communications, 2016; Nature Methods, 2016; PNAS, 2014; Genome Biology, 2013). We also integrate computational and genomic tools to elucidate RNA regulatory networks in health and disease (TIPS, 2021; Genome Biology, 2021; AJHG 2020b; PNAS 2020; AJHG, 2018; Genome Biology, 2016; Cell Reports, 2016; Elife, 2015; Cell Stem Cell, 2014; Molecular Cell, 2014; Neuron, 2014).
8
299 Active research topics include but are not limited to: computational methods for transcriptome analysis using short-read and long-read sequencing technologies; genomic technologies and computational methods for analyzing RNA processing and modifications using low-input or single-cell samples; studies of RNA regulatory networks in health and disease using large-scale RNA-seq data and protein-RNA interaction maps; genetic variation and evolution of transcriptome regulation and RNA processing; clinical RNA-seq technologies for disease diagnosis or early detection; multi-omic and clinical data integration for precision oncology and cancer immunotherapy.
8
25 PI Biography
27c Dr. Yi Xing is the Francis West Lewis Endowed Chair and Founding Director of the Center for Computational and Genomic Medicine, as well as the Executive Director of the Department of Biomedical and Health Informatics at the Children’s Hospital of Philadelphia (CHOP). Dr. Xing is also a Professor of Pathology and Laboratory Medicine at the University of Pennsylvania (Penn). Dr. Xing has an extensive publication record in bioinformatics, genomics, and RNA biology. His current research merges the fields of computational biology, biomedical data science, RNA genomics, human genetics, precision medicine, and immuno-oncology.
e 29
27
Description of Research Expertise
34 Research Interestsd1 Our lab is broadly interested in the computational biology and genomics of RNA processing and regulation, as well as their applications to human genetics, precision medicine, and cancer immunotherapy.
8
30 Description of Research
450 Mammalian cells generate astonishing regulatory diversity and complex phenotypes from a surprisingly small set of genes. We now know that considerable diversity is achieved by alternative processing and modifications of RNA. The long-term goal of our research is to elucidate alternative isoform complexity in mammalian transcriptomes and proteomes, and to understand how it is generated and its role in the regulation and function of complex genomes. We develop computational methods and genomic technologies for studying transcriptomic and proteomic complexity in bulk tissues and single cells (Science Advances, 2023; Nature Communications, 2021; AJHG 2020a; Nature Methods, 2019; AJHG, 2019; Genome Biology, 2017; Nature Communications, 2016; Nature Methods, 2016; PNAS, 2014; Genome Biology, 2013). We also integrate computational and genomic tools to elucidate RNA regulatory networks in health and disease (TIPS, 2021; Genome Biology, 2021; AJHG 2020b; PNAS 2020; AJHG, 2018; Genome Biology, 2016; Cell Reports, 2016; Elife, 2015; Cell Stem Cell, 2014; Molecular Cell, 2014; Neuron, 2014).
8
299 Active research topics include but are not limited to: computational methods for transcriptome analysis using short-read and long-read sequencing technologies; genomic technologies and computational methods for analyzing RNA processing and modifications using low-input or single-cell samples; studies of RNA regulatory networks in health and disease using large-scale RNA-seq data and protein-RNA interaction maps; genetic variation and evolution of transcriptome regulation and RNA processing; clinical RNA-seq technologies for disease diagnosis or early detection; multi-omic and clinical data integration for precision oncology and cancer immunotherapy.
8
25 PI Biography
27c Dr. Yi Xing is the Francis West Lewis Endowed Chair and Founding Director of the Center for Computational and Genomic Medicine, as well as the Executive Director of the Department of Biomedical and Health Informatics at the Children’s Hospital of Philadelphia (CHOP). Dr. Xing is also a Professor of Pathology and Laboratory Medicine at the University of Pennsylvania (Penn). Dr. Xing has an extensive publication record in bioinformatics, genomics, and RNA biology. His current research merges the fields of computational biology, biomedical data science, RNA genomics, human genetics, precision medicine, and immuno-oncology.
e 29
23
108 Pan Y, Kadash-Edmondson KE, Wang R, Phillips J, Liu S, Ribas A, Aplenc R, Witte ON, Xing Y.: RNA Dysregulation: An Expanding Source of Cancer Immunotherapy Targets. Trends Pharmacol Sci 2021.
103 Xin R, Gao Y, Gao Y, Wang R, Kadash-Edmondson KE, Liu B, Wang Y, Lin L, Xing Y.: isoCirc catalogs full-length circular RNA isoforms in human transcriptomes. Nat Commun 12: 266, Jan 2021.
1ea Phillips John W, Pan Yang, Tsai Brandon L, Xie Zhijie, Demirdjian Levon, Xiao Wen, Yang Harry T, Zhang Yida, Lin Chia Ho, Cheng Donghui, Hu Qiang, Liu Song, Black Douglas L, Witte Owen N, Xing Yi: Pathway-guided analysis identifies Myc-dependent alternative pre-mRNA splicing in aggressive prostate cancers. Proceedings of the National Academy of Sciences of the United States of America 117(10): 5269-5279, Mar 2020.
138 Zhang Zijun, Pan Zhicheng, Ying Yi, Xie Zhijie, Adhikari Samir, Phillips John, Carstens Russ P, Black Douglas L, Wu Yingnian, Xing Yi: Deep-learning augmented RNA-seq analysis of transcript splicing. Nat Methods 16(4): 307-310, April 2019.
eb Park E, Pan Z, Zhang Z, Lin L, Xing Y: The expanding landscape of alternative splicing variation in human populations. Am J Hum Genet 102(1): 11-26, January 2018.
15c Molinie B*, Wang J*, Lim KS, Hillebrand R, Lu ZX, Wittenberghe NV, Howard BD, Daneshvar K, Mullen AC, Dedon P, Xing Y*, Giallourakis CC*: m(6)A-LAIC-seq reveals the census and complexity of the m(6)A epitranscriptome. Nat Methods 13(8): 692-698, August 2016 Notes: *Joint corresponding authors 7c Highlighted by: Shi H. & He C. (2016) A glance at N6-methyladenosine in transcript isoforms. Nature Methods. 13:624–625. 14
17c Shen S, Park JW, Lu ZX, Lin L, Henry MD, Wu YN, Zhou Q, Xing Y: rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data. Proc Natl Acad Sci USA 111(51): E5593-E5601, December 2014 Notes: Software received 135,000+ downloads since release (https://github.com/Xinglab/rmats-turbo). 14
1ab Batista PJ, Molinie B , Wang J, Qu K, Zhang J, Li L, Bouley DM, Lujan E, Haddad B, Daneshvar K, Carter AC, Flynn RA, Zhou C, Lim KS, Dedon P, Wernig M, Mullen AC, Xing Y*, Giallourakis CC*, Chang HY*: m(6)A RNA modification controls cell fate transition in mammalian embryonic stem cells. Cell Stem Cell 15(6): 707-719, December 2014 Notes: *Joint corresponding authors. 4c Editorial by: Jalkanen AL, Wilusz J. (2014) Cell Stem Cell. 15(6):669-70. 57 Editorial by: Stunnenberg HG, Vermeulen M, Atlasi Y. (2015) Science. 347(6222):614-5. 14
e2 Xing Y, Lee C: Alternative splicing and RNA selection pressure--evolutionary consequences for eukaryotic genomes. Nat Rev Genet 7(7): 499-509, July 2006.
2c
7
1d
1f
Selected Publications
133 Gao Y, Wang F, Wang R, Kutschera E, Xu Y, Xie S, Wang Y, Kadash-Edmondson KE, Lin L, Xing Y.: ESPRESSO: Robust discovery and quantification of transcript isoforms from error-prone long-read RNA-seq data. Sci Adv 9: eabq5072, Jan 2023.108 Pan Y, Kadash-Edmondson KE, Wang R, Phillips J, Liu S, Ribas A, Aplenc R, Witte ON, Xing Y.: RNA Dysregulation: An Expanding Source of Cancer Immunotherapy Targets. Trends Pharmacol Sci 2021.
103 Xin R, Gao Y, Gao Y, Wang R, Kadash-Edmondson KE, Liu B, Wang Y, Lin L, Xing Y.: isoCirc catalogs full-length circular RNA isoforms in human transcriptomes. Nat Commun 12: 266, Jan 2021.
1ea Phillips John W, Pan Yang, Tsai Brandon L, Xie Zhijie, Demirdjian Levon, Xiao Wen, Yang Harry T, Zhang Yida, Lin Chia Ho, Cheng Donghui, Hu Qiang, Liu Song, Black Douglas L, Witte Owen N, Xing Yi: Pathway-guided analysis identifies Myc-dependent alternative pre-mRNA splicing in aggressive prostate cancers. Proceedings of the National Academy of Sciences of the United States of America 117(10): 5269-5279, Mar 2020.
138 Zhang Zijun, Pan Zhicheng, Ying Yi, Xie Zhijie, Adhikari Samir, Phillips John, Carstens Russ P, Black Douglas L, Wu Yingnian, Xing Yi: Deep-learning augmented RNA-seq analysis of transcript splicing. Nat Methods 16(4): 307-310, April 2019.
eb Park E, Pan Z, Zhang Z, Lin L, Xing Y: The expanding landscape of alternative splicing variation in human populations. Am J Hum Genet 102(1): 11-26, January 2018.
15c Molinie B*, Wang J*, Lim KS, Hillebrand R, Lu ZX, Wittenberghe NV, Howard BD, Daneshvar K, Mullen AC, Dedon P, Xing Y*, Giallourakis CC*: m(6)A-LAIC-seq reveals the census and complexity of the m(6)A epitranscriptome. Nat Methods 13(8): 692-698, August 2016 Notes: *Joint corresponding authors 7c Highlighted by: Shi H. & He C. (2016) A glance at N6-methyladenosine in transcript isoforms. Nature Methods. 13:624–625. 14
17c Shen S, Park JW, Lu ZX, Lin L, Henry MD, Wu YN, Zhou Q, Xing Y: rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data. Proc Natl Acad Sci USA 111(51): E5593-E5601, December 2014 Notes: Software received 135,000+ downloads since release (https://github.com/Xinglab/rmats-turbo). 14
1ab Batista PJ, Molinie B , Wang J, Qu K, Zhang J, Li L, Bouley DM, Lujan E, Haddad B, Daneshvar K, Carter AC, Flynn RA, Zhou C, Lim KS, Dedon P, Wernig M, Mullen AC, Xing Y*, Giallourakis CC*, Chang HY*: m(6)A RNA modification controls cell fate transition in mammalian embryonic stem cells. Cell Stem Cell 15(6): 707-719, December 2014 Notes: *Joint corresponding authors. 4c Editorial by: Jalkanen AL, Wilusz J. (2014) Cell Stem Cell. 15(6):669-70. 57 Editorial by: Stunnenberg HG, Vermeulen M, Atlasi Y. (2015) Science. 347(6222):614-5. 14
e2 Xing Y, Lee C: Alternative splicing and RNA selection pressure--evolutionary consequences for eukaryotic genomes. Nat Rev Genet 7(7): 499-509, July 2006.
2c
4d
22
22
7
10
a
a
2
2
19
18
10
22
10
11
c
5b © The Trustees of the University of Pennsylvania | Site best viewed a in a supported browser. | Site Design: 57 PMACS Web Team. 3 22
10
c