RNA polymerase mapping in plants identifies intergenic regulatory elements enriched in causal variants.
RNA polymerase mapping in plants identifies intergenic regulatory elements enriched in causal variants.
复制标题
植物中的RNA聚合酶图谱鉴定了富含因果变异的基因间调节元件。
DOI:
10.1093/g3journal/jkab273
复制
发表时间:
2021-10-19
期刊:
影响因子:
--
通讯作者:
Jannink JL
中科院分区:
文献类型:
--
作者:
Lozano R;Booth GT;Omar BY;Li B;Buckler ES;Lis JT;Del Carpio DP;Jannink JL
Control of gene expression is fundamental at every level of cell function. Promoter-proximal pausing and divergent transcription at promoters and enhancers, which are prominent features in animals, have only been studied in a handful of research experiments in plants. PRO-Seq analysis in cassava (Manihot esculenta) identified peaks of transcriptionally engaged RNA polymerase at both the 5′ and 3′ end of genes, consistent with paused or slowly moving Polymerase. In addition, we identified divergent transcription at intergenic sites. A full genome search for bi-directional transcription using an algorithm for enhancer detection developed in mammals (dREG) identified many intergenic regulatory element (IRE) candidates. These sites showed distinct patterns of methylation and nucleotide conservation based on genomic evolutionary rate profiling (GERP). SNPs within these IRE candidates explained significantly more variation in fitness and root composition than SNPs in chromosomal segments randomly ascertained from the same intergenic distribution, strongly suggesting a functional importance of these sites. Maize GRO-Seq data showed RNA polymerase occupancy at IREs consistent with patterns in cassava. Furthermore, these IREs in maize significantly overlapped with sites previously identified on the basis of open chromatin, histone marks, and methylation, and were enriched for reported eQTL. Our results suggest that bidirectional transcription can identify intergenic genomic regions in plants that play an important role in transcription regulation and whose identification has the potential to aid crop improvement.
登录
查看更多内容
影响因子:
48
作者:
Langmead, Ben;Salzberg, Steven L.
通讯作者:
Salzberg, Steven L.
影响因子:
9.8
作者:
Gusev, Alexander;Lee, S. Hong;Price, Alkes L.
通讯作者:
Price, Alkes L.
影响因子:
64.5
作者:
Kim TK;Shiekhattar R
通讯作者:
Shiekhattar R
影响因子:
9.2
作者:
Chang CC;Chow CC;Tellier LC;Vattikuti S;Purcell SM;Lee JJ
通讯作者:
Lee JJ
影响因子:
64.5
作者:
Chen FX;Woodfin AR;Gardini A;Rickels RA;Marshall SA;Smith ER;Shiekhattar R;Shilatifard A
通讯作者:
Shilatifard A