Transcriptome analysis of Brassica napus pod using RNA-Seq and identification of lipid-related candidate genes

Abstract

BackgroundBrassica napus is an important oilseed crop. Dissection of the genetic architecture underlying oil-related biological processes will greatly facilitates the genetic improvement of rapeseed. The differential gene expression during pod development offers a snapshot on the genes responsible for oil accumulation in. To identify candidate genes in the linkage peaks reported previously, we used RNA sequencing (RNA-Seq) technology to analyze the pod transcriptomes of German cultivar Sollux and Chinese inbred line Gaoyou.MethodsThe RNA samples were collected for RNA-Seq at 5-7, 15-17 and 25-27 days after flowering (DAF). Bioinformatics analysis was performed to investigate differentially expressed genes (DEGs). Gene annotation analysis was integrated with QTL mapping and Brassica napus pod transcriptome profiling to detect potential candidate genes in oilseed.ResultsFour hundred sixty five and two thousand, one hundred fourteen candidate DEGs were identified, respectively, between two varieties at the same stages and across different periods of each variety. Then, 33 DEGs between Sollux and Gaoyou were identified as the candidate genes affecting seed oil content by combining those DEGs with the quantitative trait locus (QTL) mapping results, of which, one was found to be homologous to Arabidopsis thaliana lipid-related genes.DiscussionIntervarietal DEGs of lipid pathways in QTL regions represent important candidate genes for oil-related traits. Integrated analysis of transcriptome profiling, QTL mapping and comparative genomics with other relative species leads to efficient identification of most plausible functional genes underlying oil-content related characters, offering valuable resources for bettering breeding program of Brassica napus.ConclusionsThis study provided a comprehensive overview on the pod transcriptomes of two varieties with different oil-contents at the three developmental stages.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2062-7) contains supplementary material, which is available to authorized users.

Time-Series Analyses of Transcriptomes and Proteomes Reveal Molecular Networks Underlying Oil Accumulation in Canola

“…Xu et al (2015) compared the gene expression profiles of B. napus pods at 5-7 (1), 15-17 (2), and 25-27 (3) days after flowering (DAF). In general, we expect to see the up-regulation of genes involved in FA biosynthesis since oil is accumulated rapidly during the development of pod.…”

“…High-throughput gene expression profiling technologies, especially RNA sequencing, have been increasingly utilized to identify the key genes involved in lipid metabolism or seed development for various plants, such as soybean (Chen et al, 2012; Goettel et al, 2014), peanut (Yin et al, 2013), castor (Brown et al, 2012; Zhang et al, 2016), maize (Lu et al, 2013), Arabidopsis (Le et al, 2010; Belmonte et al, 2013), and rapeseed (Hu et al, 2009; Troncoso-Ponce et al, 2011; Chen et al, 2015; Deng et al, 2015; Xu et al, 2015). Although, considerable research has been devoted to study the molecular mechanism underlying lipid metabolism in various plants, little effort has been made to investigate, at the whole-genome level, dynamic changes of oil biosynthesis genes during seed development in B. napus , which is different from other oil plants in terms of oil content and oil composition.…”

An integrated analysis of QTL mapping and RNA sequencing provides further insights and promising candidates for pod number variation in rapeseed (Brassica napus L.)

“…In comparison with the previous methods, RNA sequencing possesses three key advantages: first, RNA sequencing is not limited to detect transcripts that correspond to existing genomic sequences; Second, RNA sequencing has very low background signal; Third, transcripts detected by RNA sequencing have a large dynamic range of expression levels [38]. The integration of the transcriptome profiling and QTL mapping is a very useful and popular strategy toward discovery of candidate genes [19]. …”

“…However, a large amount of differentially expressed genes (DEGs) were usually identified between contrast samples through RNA sequencing. Therefore, integration of DEGs and QTLs is considered to be a promising method to identify potential candidate genes [19]. …”

Comparative transcriptomic analysis reveals a series of single nucleotide polymorphism between red- and white-fleshed loquats (Eriobotrya japonica)

“…The usage of RNA-seq technology has greatly enhanced the understanding of transcriptome complexity in animal and plant systems, such as revealing novel transcripts, alternative splicing, transcript isoforms, new large intergenic noncoding RNAs and SNPs (Gulledge et al 2012;Lei et al 2014;Gupta et al 2015;Xu et al 2015). The next generation sequencing technology had been widely applied to the genome and transcriptome sequencing in the family Rosaceae.…”