CGT-seq: epigenome-guided de novo assembly of the core genome for divergent populations with large genome.
CGT-seq: epigenome-guided de novo assembly of the core genome for divergent populations with large genome.
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CGT-seq:表观基因组引导的核心基因组从头组装,适用于具有大基因组的不同群体
DOI:
10.1093/nar/gky522
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发表时间:
2018-10-12
影响因子:
14.9
通讯作者:
Zhang Y
中科院分区:
文献类型:
--
作者:
Qi M;Li Z;Liu C;Hu W;Ye L;Xie Y;Zhuang Y;Zhao F;Teng W;Zheng Q;Fan Z;Xu L;Lang Z;Tong Y;Zhang Y
Abstract Genetic diversity in plants is remarkably high. Recent whole genome sequencing (WGS) of 67 rice accessions recovered 10,872 novel genes. Comparison of the genetic architecture among divergent populations or between crops and wild relatives is essential for obtaining functional components determining crucial traits. However, many major crops have gigabase-scale genomes, which are not well-suited to WGS. Existing cost-effective sequencing approaches including re-sequencing, exome-sequencing and restriction enzyme-based methods all have difficulty in obtaining long novel genomic sequences from highly divergent population with large genome size. The present study presented a reference-independent core genome targeted sequencing approach, CGT-seq, which employed epigenomic information from both active and repressive epigenetic marks to guide the assembly of the core genome mainly composed of promoter and intragenic regions. This method was relatively easily implemented, and displayed high sensitivity and specificity for capturing the core genome of bread wheat. 95% intragenic and 89% promoter region from wheat were covered by CGT-seq read. We further demonstrated in rice that CGT-seq captured hundreds of novel genes and regulatory sequences from a previously unsequenced ecotype. Together, with specific enrichment and sequencing of regions within and nearby genes, CGT-seq is a time- and resource-effective approach to profiling functionally relevant regions in sequenced and non-sequenced populations with large genomes.
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影响因子:
46.9
作者:
通讯作者:
--
影响因子:
64.8
作者:
Luo MC;Gu YQ;Puiu D;Wang H;Twardziok SO;Deal KR;Huo N;Zhu T;Wang L;Wang Y;McGuire PE;Liu S;Long H;Ramasamy RK;Rodriguez JC;Van SL;Yuan L;Wang Z;Xia Z;Xiao L;Anderson OD;Ouyang S;Liang Y;Zimin AV;Pertea G;Qi P;Bennetzen JL;Dai X;Dawson MW;Müller HG;Kugler K;Rivarola-Duarte L;Spannagl M;Mayer KFX;Lu FH;Bevan MW;Leroy P;Li P;You FM;Sun Q;Liu Z;Lyons E;Wicker T;Salzberg SL;Devos KM;Dvořák J
通讯作者:
Dvořák J
影响因子:
7
作者:
Jackman, Shaun D.;Vandervalk, Benjamin P.;Birol, Inanc
通讯作者:
Birol, Inanc
影响因子:
5.8
作者:
Li, Heng
通讯作者:
Li, Heng
影响因子:
30.8
作者:
Chia, Jer-Ming;Song, Chi;Ware, Doreen
通讯作者:
Ware, Doreen