Differences in the Transcriptomes of Highly Purified Fetal Liver and Adult Bone Marrow Hematopoietic Stem Cells Revealed by Long Serial Analysis of Gene Expression (LongSAGE)
Notice bibliographique
Résumé
Abstract Recent improvements in the development of methods for isolating functionally validated populations of nearly pure (>20%) murine hematopoietic stem cells (HSCs) have made it possible to analyze the molecular basis of the properties of these cells with increased precision. One intriguing feature of HSCs is the change they undergo in many of their key properties during development - a change that affects the control of their self-renewal, cycling status, differentiated progeny output and steel factor sensitivity. To investigate how these differences are mediated, we undertook a genome-wide analysis of the transcripts present in highly purified fetal and adult HSCs using an adaptation of the LongSAGE methodology that allows its application to small numbers of cells (10 ng of RNA) by inclusion of an initial PCR amplification step that preserves the transcript repertoire while excluding less than 0.25% of the transcripts. The LongSAGE methodology was adopted because it is sequence-based and thus quantitative and independent of prior knowledge of expressed genes or variations in their hybridization to matching or related cDNAs, ESTs or derived oligos. A suspension of 10,000 lin-Sca-1+CD43+Mac1+ fetal liver (FL) cells (∼20% pure HSCs as determined by 16-week limiting dilution and single cell transplantation experiments) was obtained from embryonic day 14.5 fetuses. From these cells, we generated a 160,000-tag LongSAGE library containing 7865 tags that map uniquely to the mouse genome (using the RefSeq database through DiscoverySpace; www.bcgsc.ca/DiscoverySpace). A suspension of 3700 CD45midlin-Rho-SP cells (∼30% pure HSCs) was isolated from adult mouse bone marrow (BM) and then used to generate a 37,000-tag LongSAGE library (956 uniquely mapped tags). Both of these libraries contained tags identifying transcripts that have been previously reported to be associated with HSCs from FL and/or adult BM, including c-kit, pbx-1, tgf-β, cul-4a, PrP, c-myc, robo1, sox17, as well as a number of Smarc transcripts, ubiquitin ligase transcripts and TNF-related transcripts. As a first test of the utility of the libraries, we looked for differences in the expression of genes that have been broadly associated with differences in cellular proliferative activity. This comparison identified many such tags in the FL HSC library that were absent from the adult BM HSC library, including multiple cyclins (A2, B2, C, D1, D2, D3, E1, F, H, I, J L1, L2), cdc20, cdc5b, and plk, as well as 34 of the top 50 “proliferation” genes identified by Venezia et al (PLoS Biology, 2004) to be selectively expressed in adult BM HSCs that had been stimulated to proliferate. Other transcripts that were present at significantly higher levels in the FL HSC library (95% C.I. using Audic Claverie statistics) included msl2, rbx1, lmo2, pfn1, and 16 members of the tripartite motif protein (trim) family. Conversely, many transcripts for components of the proteosome, involved in nucleic acid binding, and transcripts coding for proteins with receptor activity were present at higher levels (or uniquely) in the adult BM HSC library. Taken together, these findings establish the validity and potential of these permanent HSC transcriptome resources for further investigation of mechanisms that determine the different biology of fetal and adult HSCs.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».