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| Status |
Public on Feb 23, 2022 |
| Title |
Whole body except venom gland, rep2 |
| Sample type |
SRA |
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| Source name |
whole body without venom gland
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| Organism |
Agelena koreana |
| Characteristics |
tissue: whole body without venom gland
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| Growth protocol |
The spider Agelena koreana was collected from Chungbuk, Korea. The venom glands of the spider were separated from the chelicerae and stored after washing in phosphate buffered saline.
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| Extracted molecule |
total RNA |
| Extraction protocol |
TRIzol reagent (Life Technologies, Grand Island, NY, USA) was used for extracting total RNA and subsequent RNA sequencing using NGS method was followed (Macrogen, Seoul, Korea). The sequencing was performed in triplicates for both venom gland and body, producing 6 data pools.
The sequencing library is prepared by random fragmentation of the DNA or cDNA sample, followed by 5' and 3' adapter ligation. Alternatively, "tagmentation" combines the fragmentation and ligation reactions into a single step that greatly increases the efficiency of the library preparation process. Adapter-ligated fragments are then PCR amplified and gel purified.
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
HiSeq X Ten |
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| Data processing |
Analyze the quality control of the sequenced raw reads. Overall reads’ quality, total bases, total reads, GC (%) and basic statistics are calculated. In order to reduce biases in analysis, artifacts such as low quality reads, adaptor sequence, contaminant DNA, or PCR duplicates are removed.
The trimmed reads for all samples that should be compared each other are merged into one file to do transcriptome assembly. Merged data is assembled using Trinity program, a generally utilized for de novo reconstruction of transcriptomes, combining read sequences of a certain length of overlap to form longer fragments without N gaps, called contigs.
For assembled genes, the longest contig of the assembled contigs are filtered and clustered into the non-redundant transcripts using CD-HIT-EST program. We defined these transcripts as unigenes. Obtained unigenes are used for the subsequent annotation and ORF prediction. The abundance of unigenes across samples is estimated by RSEM algorithm. The expression level is calculated as read count.
Genome_build: In order to build a reference for Agelena koreana RNA-seq analysis, sequencing reads from this study were merged and assembled by Trinity.
Supplementary_files_format_and_content: Fasta files include assembled gene, unigenes, and predicted open read frame by trinity and transdecoder software.
Supplementary_files_format_and_content: tsv file include raw gene counts and FPKM values for every gene and every sample.
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| Submission date |
Feb 21, 2022 |
| Last update date |
Feb 23, 2022 |
| Contact name |
Jungsuk Sung |
| E-mail(s) |
sungjs@dongguk.edu
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| Organization name |
Life science
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| Street address |
32, Dongguk-ro, Ilsandong-gu
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| City |
Goyang-si |
| State/province |
Gyeonggi-do |
| ZIP/Postal code |
10326 |
| Country |
South Korea |
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| Platform ID |
GPL31963 |
| Series (1) |
| GSE197102 |
Agelena koreana whole body and venom gland transcriptome |
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| Relations |
| BioSample |
SAMN26135905 |
| SRA |
SRX14239593 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM5908719_AK_body-2_readcount.tsv.gz |
519.4 Kb |
(ftp)(http) |
TSV |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
| Processed data are available on Series record |
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