● Independent of any reference genome,
● The data could be used to analyze the structure and expression of transcripts
● Identify variable clipping sites
● BMKCloud-based result delivery: Results are delivered as data file and interactive report via BMKCloud platform, which allows user-friendly reading of complex analysis outputs and customized data mining on base of standard bioinformatics analysis.
● After-sale services: After-sale services valid for 3 months upon project completion, including projects follow-up, trouble-shooting, results Q&A, etc.
Nucleotides:
Conc.(ng/μl) |
Amount (μg) |
Purity |
Integrity |
≥ 20 |
≥ 0.5 |
OD260/280=1.7-2.5 OD260/230=0.5-2.5 Limited or no protein or DNA contamination shown on gel. |
For plants: RIN≥6.5; For animals: RIN≥7.0; 5.0≥28S/18S≥1.0; limited or no baseline elevation |
Tissue: Weight(dry): ≥1 g
*For tissue smaller than 5 mg, we recommend to send flash frozen(in liquid nitrogen) tissue sample.
Cell suspension: Cell count = 3×107
*We recommend to ship frozen cell lysate. In case that cell counts smaller than 5×105, flash frozen in liquid nitrogen is recommended.
Blood samples:
PA×geneBloodRNATube;
6mLTRIzol and 2mL blood(TRIzol:Blood=3:1)
Container:
2 ml centrifuge tube (Tin foil is not recommended)
Sample labeling: Group+replicate e.g. A1, A2, A3; B1, B2, B3... ...
Shipment:
1.Dry-ice: Samples need to be packed in bags and buried in dry-ice.
2.RNAstable tubes: RNA samples can be dried in RNA stabilization tube(e.g. RNAstable®) and shipped in room temperature.
Bioinformatics
1.mRNA(denovo) Principle of Assembly
By Trinity, reads are fragmented into smaller pieces, known as K-mer. These K-mers are then used as seeds to be extended into contigs and then component basing on contig overlappings. Finally, De Bruijn was applied here to recognize transcripts in the components.
mRNA (De novo) Overview of Trinity
2.mRNA (De novo) Distribution of Gene Expression Level
RNA-Seq is able to achieve a highly sensitive estimation of gene expression. Normally, the detectable range of transcripts expression FPKM is ranging from 10^-2 to 10^6
mRNA (De novo) Distribution of FPKM density in each sample
3.mRNA (De novo) GO Enrichment Analysis of DEGs
GO (Gene Ontology) database is a structured biological annotation system containing a standard vocabulary of gene and gene products functions. It contains multiple levels, where the lower the level is, the more specific the functions are.
mRNA (De novo) GO classification of DEGs at second level
BMK Case
Transcriptome Analysis of Sucrose Metabolism during Bulb Swelling and Development in Onion (Allium cepa L.)
Published: frontiers in plant science,2016
Sequencing strategy
Illumina HiSeq2500
Sample collection
The Utah Yellow Sweet Spain cultivar “Y1351” was used in this study. The number of samples collected was
15th day after swelling (DAS) of bulb (2-cm diameter and 3–4 g weight), 30th DAS (5-cm diameter and 100–110 g weight), and ∼3 on the 40th DAS (7-cm diameter and 260–300 gram).
Key results
1. in the Venn diagram, a total of 146 DEGs were detected across all three pairs of developmental stages
2.“Carbohydrate transport and metabolism” was represented by only 585 unigenes (i.e., 7% of the annotated COG).
3.Unigenes successfully annotated to the GO database were classified into three principal categories for the three different stages of bulb development. Most represented in the “biological process” principal category were “metabolic process”, followed by “cellular process”. In the principal category of “molecular function” the two categories most represented were “binding” and “catalytic activity”.
![]() Histogram of clusters of orthologous groups (COG) classification |
![]() Histogram of gene ontology (GO) classification for unigenes derived from bulbs in three developmental stages |
![]() Venn diagram showing genes differentially expressed in any two stages of onion bulb development |
Reference
Zhang C, Zhang H , Zhan Z , et al. Transcriptome Analysis of Sucrose Metabolism during Bulb Swelling and Development in Onion (Allium cepa L.)[J]. Frontiers in Plant Science, 2016, 7:1425-. DOI: 10.3389/fpls.2016.01425