Paternally biased X inactivation in mouse neonatal brain View Full Text


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Article Info

DATE

2010-07-27

AUTHORS

Xu Wang, Paul D Soloway, Andrew G Clark

ABSTRACT

BackgroundX inactivation in female eutherian mammals has long been considered to occur at random in embryonic and postnatal tissues. Methods for scoring allele-specific differential expression with a high degree of accuracy have recently motivated a quantitative reassessment of the randomness of X inactivation.ResultsAfter RNA-seq data revealed what appeared to be a chromosome-wide bias toward under-expression of paternal alleles in mouse tissue, we applied pyrosequencing to mouse brain cDNA samples from reciprocal cross F1 progeny of divergent strains and found a small but consistent and highly statistically significant excess tendency to under-express the paternal X chromosome.ConclusionsThe bias toward paternal X inactivation is reminiscent of marsupials (and extraembryonic tissues in eutherians), suggesting that there may be retained an evolutionarily conserved epigenetic mark driving the bias. Allelic bias in expression is also influenced by the sampling effect of X inactivation and by cis-acting regulatory variation (eQTL), and for each gene we quantify the contributions of these effects in two different mouse strain combinations while controlling for variability in Xce alleles. In addition, we propose an efficient method to identify and confirm genes that escape X inactivation in normal mice by directly comparing the allele-specific expression ratio profile of multiple X-linked genes in multiple individuals. More... »

PAGES

r79

References to SciGraph publications

  • 1998-03. X chromosome-inactivation patterns in patients with Rett syndrome in HUMAN GENETICS
  • 2005-05-22. Xlr3b is a new imprinted candidate for X-linked parent-of-origin effects on cognitive function in mice in NATURE GENETICS
  • 2007-07-29. A sequence-based variation map of 8.27 million SNPs in inbred mouse strains in NATURE
  • 2006-08. Evolution on the X chromosome: unusual patterns and processes in NATURE REVIEWS GENETICS
  • 2005-09. Skewed X Inactivation of the Normal Allele in Fully Mutated Female Carriers Determines the Levels of FMRP in Blood and the Fragile X Phenotype in MOLECULAR DIAGNOSIS
  • 2000-12-01. The Jackson Laboratory in BREAST CANCER RESEARCH
  • 1961-04. Gene Action in the X-chromosome of the Mouse (Mus musculus L.) in NATURE
  • 2005-09. Genetic and parent-of-origin influences on X chromosome choice in Xce heterozygous mice in MAMMALIAN GENOME
  • 2000-05. Expression-based assay of an X-linked gene to examine effects of the X-controlling element (Xce) locus in MAMMALIAN GENOME
  • 1993-09. Mapping the murine Xce locus with (CA)n repeats in MAMMALIAN GENOME
  • 2005-09-16. Brief Report: Non-Random X Chromosome Inactivation in Females with Autism in JOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERS
  • 2005-03. X-inactivation profile reveals extensive variability in X-linked gene expression in females in NATURE
  • 2008-05. Genome analysis of the platypus reveals unique signatures of evolution in NATURE
  • 2005-04-08. X-chromosome inactivation: a hypothesis linking ontogeny and phylogeny in NATURE REVIEWS GENETICS
  • 2007-01. Dosage compensation: the beginning and end of generalization in NATURE REVIEWS GENETICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/gb-2010-11-7-r79

    DOI

    http://dx.doi.org/10.1186/gb-2010-11-7-r79

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1042208401

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/20663224


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