Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling of mouse lymphoid neoplasia shows changes in processing of 3 prime-UTR characterize clinically distinct tumor types

ABSTRACT: We used a novel probe-level microarray analysis, revealing connections between mRNA processing and lymphoid neoplasia, in a mouse leukemia model. Characteristic differences in mRNA processing, primarily in the 3’-untranslated region, distinguished histologically similar tumor subtypes with different survival characteristics. Gene sets with specific processing in each tumor subtype defined signatures useful for tumor subclassification, as demonstrated by internal cross-validation with up to 80% discrimination accuracy. A combination of mRNA expression and sequence analysis suggested that differences in isoform abundance likely arose from both alternative polyadenylation and differential degradation. Experiment Overall Design: 5 types of samples were analyzed with multiple biological replicates. Progenitor B-cells, mature B-cells were the control. LPC, APC, APN were the tumor cells. LPC (Lig4/P53 deficient cells developed pro-B lymphoma with c-myc amplification), APC (Artemis/P53 deficient cells developed pro-B lymphoma with c-myc amplification), APN (Artemis/P53 deficient cells developed pro-B lymphoma with N-myc amplification)

ORGANISM(S): Mus musculus

SUBMITTER: priyam singh

PROVIDER: E-GEOD-15808 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Developing B lymphocytes undergo V(D)J recombination to assemble germline V, D, and J gene segments into exons that encode the antigen-binding variable region of immunoglobulin (Ig) heavy (H) and light (L) chains. IgH and IgL chains associate to form the B cell receptor (BCR), which upon antigen binding activates B cells to secrete BCR as an antibody. Each of the huge number of clonally independent B cells expresses a unique set of IgH and IgL variable regions. Ability of V(D)J recombination to generate vast primary B cell repertoires results from combinatorial assortment of large numbers of different V, D, and J segments, coupled with diversification of the junctions between them to generate the complementary determining region 3 (CDR3) for antigen contact. Approaches to evaluate in depth the content of primary antibody repertoires and, ultimately, to study how they are further molded by secondary mutation and affinity maturation processes are of great importance to the B cell development, vaccine, and antibody fields. We now describe an unbiased, sensitive, and readily accessible assay, referred to as HTGTS repertoire sequencing (HTGTS-Rep-seq), to quantify antibody repertoires. HTGTS-Rep-seq quantitatively identifies the vast majority of IgH and IgL V(D)J exons, including their unique CDR3 sequences, from progenitor and mature mouse B lineage cells via the use of specific J primers. HTGTS-Rep-seq also accurately quantifies DJH intermediates and V(D)J exons in either productive or non-productive configurations. HTGTS-Rep-seq should be useful for studies of human samples, including clonal B-cell expansions and also for following antibody affinity maturation processes. We employed high-throughput genome-wide translocation sequencing adapted repertoire sequencing (HTGTS-Rep-seq) to study antibody repertoires. For HTGTS-Rep-seq libraries, we utilize bait coding ends of J segments to identify, in unbiased fashion, mouse IgH DJH repertoires [processed tlx files] along with both productive and non-productive IgH V(D)J repertoires from both pro-B and peripheral B cells [processed xls files of samples 1-18, 21-51]. Similarly, we also identify mouse productive and non-productive Igk repertoires from peripheral B cells [processed xls files of samples 19,20,52-57].

Project description:In order to investigate how transcription factor dose impacts B-lymphocyte development, we generated mice carrying transheterozygous mutations in the Pax5 and Ebf1 genes. While combined reduction of Pax5 and Ebf1 dose had minimal impact on the development of the earliest CD19+ progenitors, these cells displayed an increased T-cell potential in vivo and in vitro. Alteration in lineage fate depended on a Notch1 mediated conversion process while no signs of de-differentiation could be detected. The differences in functional response to Notch signaling in Wt and Pax5+/-Ebf1+/- pro-B cells was reflected in the transcriptional response because even though cells of both genotypes responded by the generation of intracellular Notch1 and activation of a set of target genes, only the Pax5+/-Ebf1+/- pro-B cells down-regulated genes central for the preservation of stable B-cell identity. This report stresses the importance of transcription factor dose in lymphocyte development and suggests that Pax5 and Ebf1 collaborate to modulate the transcriptional response to Notch signaling after the generation of activated intracellular Notch1. This provides an insight to how transcription factors like Ebf1 and Pax5 preserve cellular identity during differentiation. EBF-1 ChIP-seq: Cultivated CD43+IgM- cells (ProB) cells from Wt, EBF-1 +/-, PAX-5 +/- and EBF-1 +/- PAX-5 +/- (TH) were assessed for EBF-1 binding by ChIP-seq. Replicate Ebf1 ChIP-seq runs on each genotype (Wt, TH, Ebf1+/- and Pax5+/-) and corresponding inputs were pooled into one dataset and analyzed as one combined sample per genotype. RNA-seq no treatment: Briefly, ProB-cells from C57BL/6J Ebf1+/-Pax5+/- (n=4), WT (n=4), Ebf1+/- (n=2) and Pax5+/- (n=2) were sorted and RNA extracted with Qiagen RNeasy Micro Kit. RNA was sent to UCLA Microarray Core for library preparation and were subsequently for 50 cycles of HiSeq 2000 SBS sequencing generating 20-30 million reads/sample. Data analysis was performed with Arraystar® (DNASTAR)). RNA-seq 1 day on OP9DL1 and OP9: In short, in vitro expanded ProB-cells from C57BL/6J Ebf1+/-Pax5+/- (n=4) and WT (n=4) were exposed either on OP9 or OP9-DL1 stromal cells for 24 hours and RNA extracted with Qiagen RNeasy Micro Kit. Due to low reads, two Wt and Ebf1+/-Pax5+/- were sequenced twice. Libraries were constructed using Nugen's Ovation Ultralow Library systems and were subsequently for 50 cycles of NextSeq500 sequencing generating 20-30 million reads/sample. Data analysis was performed with Arraystar® (DNASTAR)).

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Transcription profiling of mouse lymphoid neoplasia shows changes in processing of 3 prime-UTR characterize clinically distinct tumor types

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