Serial genomic inversions induce tissue-specific architectural stripes, gene misexpression and congenital malformations.
Katerina KraftAndreas MaggVerena HeinrichChristina RiemenschneiderRobert SchöpflinJulia MarkowskiDaniel M IbrahimRocío Acuna-HidalgoAlexandra DespangGuillaume AndreyLars WittlerBernd TimmermannMartin VingronStefan MundlosPublished in: Nature cell biology (2019)
Balanced chromosomal rearrangements such as inversions and translocations can cause congenital disease or cancer by inappropriately rewiring promoter-enhancer contacts1,2. To study the potentially pathogenic consequences of balanced chromosomal rearrangements, we generated a series of genomic inversions by placing an active limb enhancer cluster from the Epha4 regulatory domain at different positions within a neighbouring gene-dense region and investigated their effects on gene regulation in vivo in mice. Expression studies and high-throughput chromosome conformation capture from embryonic limb buds showed that the enhancer cluster activated several genes downstream that are located within asymmetric regions of contact, the so-called architectural stripes3. The ectopic activation of genes led to a limb phenotype that could be rescued by deleting the CCCTC-binding factor (CTCF) anchor of the stripe. Architectural stripes appear to be driven by enhancer activity, because they do not form in mouse embryonic stem cells. Furthermore, we show that architectural stripes are a frequent feature of developmental three-dimensional genome architecture often associated with active enhancers. Therefore, balanced chromosomal rearrangements can induce ectopic gene expression and the formation of asymmetric chromatin contact patterns that are dependent on CTCF anchors and enhancer activity.
Keyphrases
- copy number
- transcription factor
- genome wide
- binding protein
- genome wide identification
- dna methylation
- gene expression
- high throughput
- dna binding
- embryonic stem cells
- poor prognosis
- machine learning
- type diabetes
- young adults
- metabolic syndrome
- squamous cell
- squamous cell carcinoma
- atomic force microscopy
- papillary thyroid
- skeletal muscle
- bioinformatics analysis
- neural network
- dna damage