● N'adabereghị na genome ọ bụla,
● Enwere ike iji data ahụ nyochaa nhazi na okwu nke ederede
● Chọpụta ebe a na-egbutu ndị na-agbanwe agbanwe
● Nnyefe nsonaazụ dabere na BMKCloud: A na-ewepụta nsonaazụ dị ka faịlụ data na akụkọ mmekọrịta site na BMKCloud n'elu ikpo okwu, nke na-enye ohere ịgụ ihe omume enyi na enyi nke nsonaazụ nyocha dị mgbagwoju anya na ntinye data ahaziri ahazi na ndabere nke nyocha bioinformatics ọkọlọtọ.
● Ọrụ ire ere: Ọrụ ire ere na-arụ ọrụ maka ọnwa 3 mgbe arụchara ọrụ, gụnyere nleba anya ọrụ, mgbapụ nsogbu, nsonaazụ Q&A, wdg.
Nucleotides:
Conc.(ng/μl) | Ọnụ ego (μg) | Ịdị ọcha | Iguzosi ike n'ezi ihe |
≥ 20 | ≥ 0.5 | OD260/280=1.7-2.5 OD260/230=0.5-2.5 Enwere oke ma ọ bụ enweghị protein ma ọ bụ mmetọ DNA nke egosiri na gel. | Maka osisi: RIN≥6.5; Maka anụmanụ: RIN≥7.0; 5.0≥28S/18S≥1.0; nwere oke ma ọ bụ enweghị mgbago elu |
Anụ ahụ: Ibu (akọrọ): ≥1 g
* Maka anụ ahụ dị obere karịa 5 mg, anyị na-akwado iziga ihe nlele anụ ahụ kpọnwụrụ akpọnwụ (na mmiri mmiri nitrogen).
Nkwụsị cell: Ọnụ ọgụgụ cell = 3×107
* Anyị na-akwado ibupu cell lysate oyi kpọnwụrụ.Ọ bụrụ na sel ahụ riri obere karịa 5 × 105, Flash jụrụ oyi na mmiri mmiri nitrogen ka akwadoro.
Ihe nlele ọbara:
PA × geneBloodRNATube;
6mLTRIzol na 2mL ọbara (TRIzol: Blood = 3: 1)
akpa:
2 ml nke centrifuge tube (anaghị akwado foil tin)
Ịkpọ aha nlele: Otu+ megharịa dịka A1, A2, A3;B1, B2, B3......
Mbupu:
1.Dry-ice: A ga-etinye ihe nlele n'ime akpa ma lie ya na akọrọ-ice.
2.RNAstable tubes: Enwere ike ihichapụ ihe nlele RNA na tube stabilization RNA (dịka RNAstable®) ma bufee ya na okpomọkụ.
Bioinformatics
1.mRNA(denovo) Ụkpụrụ Mgbakọ
Site n'Atọ n'Ime Otu, a na-ekewa akwụkwọ ndị ahụ n'ime obere iberibe, nke a maara dị ka K-mer.A na-eji K-mers ndị a dị ka mkpụrụ nke a ga-agbatị n'ime contigs wee na-adabere na contig overlappings.N'ikpeazụ, etinyere De Bruijn ebe a iji mata ederede na akụrụngwa.
mRNA (De novo) Nchịkọta nke Atọ n'Ime Otu
2.mRNA (De novo) Nkesa Ọkwa nkwupụta Gene
RNA-Seq nwere ike nweta nleba anya nke ukwuu nke okwu mkpụrụ ndụ ihe nketa.Dị ka ọ na-adịkarị, FPKM nwere ike ịchọpụta ụdị ederede ederede sitere na 10^-2 ruo 10^6.
mRNA (De novo) Nkesa njupụta FPKM na nlele ọ bụla
3.mRNA (De novo) GO Enrichment Analysis of DEGs
GO (Gene Ontology) nchekwa data bụ usoro nkọwa ihe ndụ ahaziri ahazi nke nwere ụkpụrụ okwu nke mkpụrụ ndụ ihe nketa na ọrụ mkpụrụ ndụ ihe nketa.Ọ nwere ọkwa dị iche iche, ebe ọkwa dị ala dị ala, ka a kapịrị ọnụ ọrụ ndị ahụ.
mRNA (De novo) GO nhazi ọkwa DEGs na ọkwa nke abụọ
Okwu BMK
Nyocha transcriptome nke Sucrose Metabolism n'oge ọzịza na mmepe na yabasị (Allium cepa L.)
Ebipụtara: ókè na sayensị osisi,2016
Usoro usoro
Illumina HiSeq2500
Nchịkọta ihe atụ
A na-eji osisi ubi Utah Yellow Sweet Spain mee ihe n'ọmụmụ ihe a.Ọnụọgụ ihe nlele anakọtara bụ
Ụbọchị 15 mgbe ọzịza (DAS) nke bọlbụ (dayameta 2-cm na ịdị arọ 3-4 g), 30th DAS (dayameta 5-cm na 100-110 g arọ), na ~ 3 na 40th DAS (7-cm dayameta na 260-300 grams.
Nsonaazụ igodo
1. na eserese Venn, a chọpụtara ngụkọta nke 146 DEGs n'ofe ụzọ atọ niile nke mmepe mmepe.
2. "Carbohydrate Transport and metabolism" bụ naanị 585 unigenes (ya bụ, 7% nke COG nkọwa).
3.Unigenes nke ọma kọwara na GO nchekwa data bụ nkewa n'ime atọ isi edemede maka atọ dị iche iche nkebi nke bọlbụ mmepe.Ọtụtụ ndị nọchitere anya na ngalaba “usoro ndu ndu” bụ “usoro metabolic” nke sochiri “usoro mkpụrụ ndụ”.N'ụdị isi nke "ọrụ molecular" ngalaba abụọ a kacha egosipụta bụ "njikọ" na "ọrụ catalytic".
Histogram nke ụyọkọ nke orthologous otu (COG) nhazi ọkwa | Histogram nke gene ontology (GO) nkewa maka unigenes ewepụtara na bulbs n'usoro mmepe atọ. |
Eserese Venn na-egosi mkpụrụ ndụ ihe nketa dị iche iche n'ụdị abụọ ọ bụla nke mmepe bọlbụ yabasị |
Ntụaka
Zhang C, Zhang H, Zhan Z, et al.Nyocha transcriptome nke Sucrose Metabolism n'oge ọzịza na mmepe na yabasị (Allium cepa L.)[J].Oke na sayensị osisi, 2016, 7:1425- .DOI: 10.3389/fpls.2016.01425