Allelic Expression of Deleterious Protein-Coding Variants across Human Tissues

被引:45
|
作者
Kukurba, Kimberly R. [1 ,2 ]
Zhang, Rui [2 ]
Li, Xin [1 ,2 ]
Smith, Kevin S. [1 ,2 ]
Knowles, David A. [3 ]
Tan, Meng How [2 ]
Piskol, Robert [2 ]
Lek, Monkol [4 ,5 ]
Snyder, Michael [2 ]
MacArthur, Daniel G. [4 ,5 ]
Li, Jin Billy [2 ]
Montgomery, Stephen B. [1 ,2 ,3 ]
机构
[1] Stanford Univ, Dept Pathol, Sch Med, Stanford, CA 94305 USA
[2] Stanford Univ, Dept Genet, Sch Med, Stanford, CA 94305 USA
[3] Stanford Univ, Dept Comp Sci, Sch Med, Stanford, CA 94305 USA
[4] Massachusetts Gen Hosp, Analyt & Translat Genet Unit, Boston, MA 02114 USA
[5] Broad Inst Harvard & MIT, Program Med & Populat Genet, Cambridge, MA USA
来源
PLOS GENETICS | 2014年 / 10卷 / 05期
关键词
OF-FUNCTION VARIANTS; REGULATORY VARIATION; GENE-EXPRESSION; PATTERNS; MUTATION; RARE;
D O I
10.1371/journal.pgen.1004304
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Personal exome and genome sequencing provides access to loss-of-function and rare deleterious alleles whose interpretation is expected to provide insight into individual disease burden. However, for each allele, accurate interpretation of its effect will depend on both its penetrance and the trait's expressivity. In this regard, an important factor that can modify the effect of a pathogenic coding allele is its level of expression; a factor which itself characteristically changes across tissues. To better inform the degree to which pathogenic alleles can be modified by expression level across multiple tissues, we have conducted exome, RNA and deep, targeted allele-specific expression (ASE) sequencing in ten tissues obtained from a single individual. By combining such data, we report the impact of rare and common loss-of-function variants on allelic expression exposing stronger allelic bias for rare stop-gain variants and informing the extent to which rare deleterious coding alleles are consistently expressed across tissues. This study demonstrates the potential importance of transcriptome data to the interpretation of pathogenic protein-coding variants.
引用
收藏
页数:9
相关论文
共 50 条
  • [31] Elucidating the role of protein-coding variants in type 2 diabetes susceptibility
    Mahajan, A.
    DIABETOLOGIA, 2015, 58 : S89 - S89
  • [32] Regional fat depot masses are influenced by protein-coding gene variants
    Neville, Matt J.
    Wittemans, Laura B. L.
    Pinnick, Katherine E.
    Todorcevic, Marijana
    Kaksonen, Risto
    Pietilainen, Kirsi H.
    Luan, Jian'an
    Scott, Robert A.
    Wareham, Nicholas J.
    Langenberg, Claudia
    Karpe, Fredrik
    PLOS ONE, 2019, 14 (05):
  • [33] Identification of Novel Protein-Coding Genetic Variants Associated with Takayasu Arteritis
    Renauer, Paul
    Coit, Patrick
    Merkel, Peter A.
    Sawalha, Amr H.
    ARTHRITIS & RHEUMATOLOGY, 2015, 67
  • [34] Identification of protein-coding variants associated with risk of type 2 diabetes
    Mahajan, A.
    Fuchsberger, C.
    Flannick, J.
    Rivas, M.
    Fontanillas, P.
    Morris, A.
    Teslovich, T.
    McCarthy, M.
    DIABETOLOGIA, 2014, 57 : S51 - S51
  • [35] WHOLE EXOME SEQUENCING IDENTIFIES RARE PROTEIN-CODING VARIANTS IN DERMATOMYOSITIS
    Li, Liubing
    Liu, Chenxi
    Yan, Songxin
    Li, Yongzhe
    CLINICAL AND EXPERIMENTAL RHEUMATOLOGY, 2023, 41 (02) : 439 - 439
  • [36] Genetic Screening for Low-Penetrance Variants in Protein-Coding Genes
    Waalen, Jill
    Beutler, Ernest
    ANNUAL REVIEW OF GENOMICS AND HUMAN GENETICS, 2009, 10 : 431 - 450
  • [37] Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants
    Fu, Wenqing
    O'Connor, Timothy D.
    Jun, Goo
    Kang, Hyun Min
    Abecasis, Goncalo
    Leal, Suzanne M.
    Gabriel, Stacey
    Altshuler, David
    Shendure, Jay
    Nickerson, Deborah A.
    Bamshad, Michael J.
    Akey, Joshua M.
    NATURE, 2013, 493 (7431) : 216 - 220
  • [38] Dominant transcript expression profiles of human protein-coding genes interrogated with GTEx dataset
    Kuo-Feng Tung
    Chao-Yu Pan
    Wen-chang Lin
    Scientific Reports, 12
  • [39] Dominant transcript expression profiles of human protein-coding genes interrogated with GTEx dataset
    Tung, Kuo-Feng
    Pan, Chao-Yu
    Lin, Wen-chang
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [40] Prediction and interpretation of deleterious coding variants in terms of protein structural stability
    François Ancien
    Fabrizio Pucci
    Maxime Godfroid
    Marianne Rooman
    Scientific Reports, 8