14 research outputs found
Clusters of orthologous groups (COG) function classification of differentially expressed genes (DEGs) in <i>B</i>. <i>napu</i>s.
<p>A total of 678 DEGs were distributed across 25 COG categories.</p
Gene ontology (GO) function classification of differentially expressed genes (DEGs) in <i>B</i>. <i>napu</i>s.
<p>A total of 1,763 genes were assigned to the three main GO functional categories and then divided into 57 sub-categories.</p
RNA-seq transcriptome analysis of the immature seeds of two <i>Brassica napus</i> lines with extremely different thousand-seed weight to identify the candidate genes related to seed weight
<div><p><i>Brassica napus</i> is an important oilseed crop worldwide. Although seed weight is the main determinant of seed yield, few studies have focused on the molecular mechanisms that regulate seed weight in <i>B</i>. <i>napus</i>. In this study, the immature seeds of G-42 and 7–9, two <i>B</i>. <i>napus</i> doubled haploid (DH) lines with extremely different thousand-seed weight (TSW), were selected for a transcriptome analysis to determine the regulatory mechanisms underlying seed weight at the whole gene expression level and to identify candidate genes related to seed weight. A total of 2,251 new genes and 2,205 differentially expressed genes (DEGs) were obtained via RNA-seq (RNA sequencing). Among these genes, 1,747 (77.61%) new genes and 2020 (91.61%) DEGs were successfully annotated. Of these DEGs, 1,118 were up-regulated and 1,087 were down-regulated in the large-seed line. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database analysis indicated that 15 DEGs were involved in ubiquitin-mediated proteolysis and proteasome pathways, which might participate in regulating seed weight. The Gene Ontology (GO) database indicated that 222 DEGs were associated with the biological process or molecular function categories related to seed weight, such as cell division, cell size and cell cycle regulation, seed development, nutrient reservoir activity, and proteasome-mediated ubiquitin-dependent protein catabolic processes. Moreover, 50 DEGs encoding key enzymes or proteins were identified that likely participate in regulating seed weight. A DEG (<i>GSBRNA2T00037121001</i>) identified by the transcriptome analysis was also previously identified in a quantitative trait locus (QTL) region for seed weight via SLAF-seq (Specific Locus Amplified Fragment sequencing). Finally, the expression of 10 DEGs with putative roles in seed weight and the expression of the DEG <i>GSBRNA2T00037121001</i> were confirmed by a quantitative real-time reverse transcription PCR (qRT-PCR) analysis, and the results were consistent with the RNA sequencing data. This work has provided new insights on the molecular mechanisms underlying seed weight-related biosynthesis and has laid a solid foundation for further improvements to the seed yield of oil crops.</p></div
Hierarchical clustering analysis of DEGs based on FPKM data between T3 and T4.
<p>The colour key represents the FPKM (Fragments Per Kilobase of exon per Million fragments mapped) normalized log<sub>2</sub> transformed counts. Red represents high expression, and blue represents low expression. Each row represents a gene.</p
Summary of key enzymes and proteins related to seed weight in the Swiss-Prot and NR databases.
<p>Summary of key enzymes and proteins related to seed weight in the Swiss-Prot and NR databases.</p
Statistics of the seed weight, seed size and fresh seed weight at different periods of development.
<p>Statistics of the seed weight, seed size and fresh seed weight at different periods of development.</p
Statistics of the seed weight, seed size and fresh seed weight at different periods of development.
<p>Statistics of the seed weight, seed size and fresh seed weight at different periods of development.</p
KEGG pathway analysis identified the ubiquitin-mediated proteolysis pathway (ko04120) and proteasome pathway (ko03050) for 15 DEGs between T3 and T4.
<p>(A) ko04120, and (B) ko03050.</p
Statistics of RNA-seq data aligned to the reference genome.
<p>Statistics of RNA-seq data aligned to the reference genome.</p
Functional annotation of new genes and differentially expressed genes in the COG, GO, KEGG, Swiss-Prot and NR databases.
<p>Functional annotation of new genes and differentially expressed genes in the COG, GO, KEGG, Swiss-Prot and NR databases.</p