Using next-generation RNA sequencing to identify imprinted genes

被引:67
|
作者
Wang, X. [1 ,2 ]
Clark, A. G. [1 ,2 ]
机构
[1] Cornell Univ, Dept Mol Biol & Genet, Ithaca, NY 14853 USA
[2] Cornell Univ, Cornell Ctr Comparat & Populat Genom, Ithaca, NY 14853 USA
关键词
X-CHROMOSOME INACTIVATION; RANDOM MONOALLELIC EXPRESSION; ORIGIN ALLELIC EXPRESSION; WIDE IDENTIFICATION; MOUSE-BRAIN; GENOME; MECHANISMS; PLACENTA; HETEROZYGOSITY; MICROARRAY;
D O I
10.1038/hdy.2014.18
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Genomic imprinting is manifested as differential allelic expression (DAE) depending on the parent-of-origin. The most direct way to identify imprinted genes is to directly score the DAE in a context where one can identify which parent transmitted each allele. Because many genes display DAE, simply scoring DAE in an individual is not sufficient to identify imprinted genes. In this paper, we outline many technical aspects of a scheme for identification of imprinted genes that makes use of RNA sequencing (RNA-seq) from tissues isolated from F1 offspring derived from the pair of reciprocal crosses. Ideally, the parental lines are from two inbred strains that are not closely related to each other. Aspects of tissue purity, RNA extraction, library preparation and bioinformatic inference of imprinting are all covered. These methods have already been applied in a number of organisms, and one of the most striking results is the evolutionary fluidity with which novel imprinted genes are gained and lost within genomes. The general methodology is also applicable to a wide range of other biological problems that require quantification of allele-specific expression using RNA-seq, such as cis-regulation of gene expression, X chromosome inactivation and random monoallelic expression.
引用
收藏
页码:156 / 166
页数:11
相关论文
共 50 条
  • [1] Using next-generation RNA sequencing to identify imprinted genes
    X Wang
    A G Clark
    [J]. Heredity, 2014, 113 : 156 - 166
  • [2] Using next-generation sequencing to identify novel disease genes
    Blaydon, D. C.
    Walne, A. J.
    Plagnol, V.
    van Heel, D. A.
    Vulliamy, T.
    Kelsell, D. P.
    [J]. BRITISH JOURNAL OF DERMATOLOGY, 2011, 164 (04) : 930 - 931
  • [3] Genes, behavior and next-generation RNA sequencing
    Hitzemann, R.
    Bottomly, D.
    Darakjian, P.
    Walter, N.
    Iancu, O.
    Searles, R.
    Wilmot, B.
    McWeeney, S.
    [J]. GENES BRAIN AND BEHAVIOR, 2013, 12 (01) : 1 - 12
  • [4] USE OF NEXT-GENERATION SEQUENCING PLATFORMS TO IDENTIFY SCHIZOPHRENIA GENES
    Hodgkinson, Colin
    [J]. SCHIZOPHRENIA BULLETIN, 2011, 37 : 71 - 71
  • [5] FRO 2014: using targeted next-generation sequencing to identify genes underlying keratoconus
    Valgaeren, H.
    [J]. ACTA OPHTHALMOLOGICA, 2014, 92
  • [6] A bioinformatics workflow to identify neoantigens using next-generation sequencing
    Zhang, Shile
    So, Alex
    Kaplan, Shannon
    Kruglyak, Kristina
    [J]. CANCER IMMUNOLOGY RESEARCH, 2017, 5 (03)
  • [7] Using Next-Generation Sequencing Technology To Identify Candidate Genes for Familial Mesial Temporal Lobe Epilepsy
    Santos, Renato
    Borges, Murillo
    Ide, Wesley
    Rocha, Cristiane
    Secolin, Rodrigo
    Artiguenave, Francois
    Yasuda, Clarissa
    Coan, Ana
    Morita, Marcia
    Cendes, Fernando
    Maurer-Morelli, Claudia
    Lopes-Cendes, Iscia
    [J]. NEUROLOGY, 2013, 80
  • [8] Application of next-generation sequencing to identify different pathogens
    Nafea, Aljuboori M.
    Wang, Yuer
    Wang, Duanyang
    Salama, Ahmed M.
    Aziz, Manal A.
    Xu, Shan
    Tong, Yigang
    [J]. FRONTIERS IN MICROBIOLOGY, 2024, 14
  • [9] Next-generation sequencing to identify genetic causes of cardiomyopathies
    Norton, Nadine
    Li, Duanxiang
    Hershberger, Ray E.
    [J]. CURRENT OPINION IN CARDIOLOGY, 2012, 27 (03) : 214 - 220
  • [10] Investigation of chicken housekeeping genes using next-generation sequencing data
    Hasanpur, Karim
    Hosseinzadeh, Sevda
    Mirzaaghayi, Atiye
    Alijani, Sadegh
    [J]. FRONTIERS IN GENETICS, 2022, 13