scholarly journals A 3’-end capture sequencing method for high-throughput targeted gene expression profiling

2021 ◽  
Author(s):  
Eric de Bony ◽  
Fien Gysens ◽  
Nurten Yigit ◽  
Jasper Anckaert ◽  
Celine Everaert ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Rna Sequencing ◽  
Expression Profiling ◽  
Large Scale ◽  
Target Genes ◽  
Cost Effective ◽  
Targeted Gene Expression ◽  
Gene Panels ◽  
Capture Sequencing

AbstractMolecular phenotyping through shallow 3’-end RNA-sequencing workflows is increasingly applied in the context of large-scale chemical or genetic perturbation screens to study disease biology or support drug discovery. While these workflows enable accurate quantification of the most abundant genes, they are less effective for applications that require expression profiling of low abundant transcripts, like long non-coding RNAs (lncRNAs), or selected gene panels. To tackle these issues, we describe a workflow combining 3’-end library preparation with 3’-end hybrid capture probes and shallow RNA-sequencing for cost-effective, targeted quantification of subsets of (low abundant) genes across hundreds to thousands of samples. To assess the performance of the method, we designed a capture probe set for more than 100 mRNA and lncRNA target genes and applied the workflow to a cohort of 360 samples. When compared to standard 3’-end RNA-sequencing, 3’-end capture sequencing resulted in a more than 100-fold enrichment of target gene abundance while conserving relative inter-gene and inter-sample abundances. 3’-end RNA capture sequencing enables accurate targeted gene expression profiling at extremely shallow sequencing depth.

scholarly journals Multiplexed, Targeted Gene Expression Profiling and Genetic Analysis on Electronic Microarrays

2002 ◽  
Vol 48 (11) ◽  
pp. 1873-1882 ◽  
Author(s):  
Elaine M Weidenhammer ◽  
Brenda F Kahl ◽  
Ling Wang ◽  
Larry Wang ◽  
Melanie Duhon ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Target Genes ◽  
Mrna Targets ◽  
Amplification Method ◽  
Polymorphism Detection ◽  
Targeted Gene Expression ◽  
Electronic Microarray ◽  
Electronic Field

Abstract Background: Electronic microarrays comprise independent microelectrode test sites that can be electronically biased positive or negative, or left neutral, to move and concentrate charged molecules such as DNA and RNA to one or more test sites. We developed a protocol for multiplexed gene expression profiling of mRNA targets that uses electronic field-facilitated hybridization on electronic microarrays. Methods: A multiplexed, T7 RNA polymerase-mediated amplification method was used for expression profiling of target mRNAs from total cellular RNA; targets were detected by hybridization to sequence-specific capture oligonucleotides on electronic microarrays. Activation of individual test sites on the electronic microarray was used to target hybridization to designated subsets of sites and allow comparisons of target concentrations in different samples. We used multiplexed amplification and electronic field-facilitated hybridization to analyze expression of a model set of 10 target genes in the U937 cell line during lipopolysaccharide-mediated differentiation. Performance of multiple genetic analyses (single-nucleotide polymorphism detection, gene expression profiling, and splicing isoform detection) on a single electronic microarray was demonstrated using the ApoE and ApoER2 genes as a model system. Results: Targets were detected after a 2-min hybridization reaction. With noncomplementary capture probes, no signal was detectable. Twofold changes in target concentration were detectable throughout the (∼64-fold) range of concentrations tested. Levels of 10 targets were analyzed side by side across seven time points. By confining electronic activation to subsets of test sites, polymorphism detection, expression profiling, and splicing isoform analysis were performed on a single electronic microarray. Conclusions: Microelectronic array technology provides specific target detection and quantification with advantages over currently available methodologies for targeted gene expression profiling and combinatorial genomics testing.

Resolving driver events in MLL-r negative high-risk infant ALL.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 10030-10030
Author(s):  
Jennifer Seelisch ◽  
Matthew Zatzman ◽  
Federico Comitani ◽  
Fabio Fuligni ◽  
Ledia Brunga ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
High Risk ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Rna Sequencing ◽  
Clinical Features ◽  
Expression Profiling ◽  
High Risk Infant ◽  
Childhood All

10030 Background: Infant acute lymphoblastic leukemia (ALL) is the only subtype of childhood ALL whose outcome has not improved over the past two decades. The most important prognosticator is the presence of rearrangements in the Mixed Lineage Leukemia gene (MLL-r), however, many patients present with high-risk clinical features but without MLL-r. We recently identified two cases of infant ALL with high-risk clinical features resembling MLL-r, but were negative for MLL-r by conventional diagnostics. RNA sequencing revealed a partial tandem duplication in MLL (MLL-PTD). We thus aimed to determine if MLL-PTD, other MLL abnormalities, or other genetic or transcriptomic features were driving this subset of high-risk infant ALL without MLL-r. Methods: We obtained 19 banked patient samples from the Children’s Oncology Group (COG) infant ALL trial (AALL0631) from MLL wildtype patients as determined by FISH and cytogenetics. Utilizing deep RNA-sequencing, we manually inspected the MLL gene for MLL-PTD, while also performing automated fusion detection and gene expression profiling in search of defining features of these tumors. Results: 3 additional MLL-PTDs were identified, all in patients with infant T-cell ALL, whereas both index cases were in patients with infant B-cell ALL. Gene expression profiling analysis revealed that all five MLL-PTD infants clustered together. Eight infants (7 with B-cell ALL) were found to have Ph-like expression. Five of these 8 infants were also found to have an IKZF1/JAK2 expression profile; one of these five had a PAX5-JAK2 fusion detected. Two infants (including the one noted above) had novel PAX5 fusions, known drivers of B-cell leukemia. Additional detected fusions included TCF3-PBX1 and TCF4-ZNF384. Conclusions: MLL-PTDs were found in both B- and T-cell infant ALL. Though Ph-like ALL has been described in adolescents and young adults, we found a substantial frequency of Ph-like expression among MLL-WT infants. Further characterization of these infants is ongoing. If replicated in other infant cohorts, these two findings may help explain the poor prognosis of MLL-WT ALL when compared to children with standard risk ALL, and offer the possibility of targeted therapy for select infants.

scholarly journals Gene expression profiling by targeted RNA sequencing in pathological stage I lung adenocarcinoma with a solid component

Lung Cancer ◽  
2020 ◽  
Vol 147 ◽  
pp. 56-63
Author(s):  
Yoshiteru Kidokoro ◽  
Tomohiko Sakabe ◽  
Tomohiro Haruki ◽  
Taichi Kadonaga ◽  
Kanae Nosaka ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Gene Expression Profiling ◽  
Rna Sequencing ◽  
Expression Profiling ◽  
Stage I ◽  
Solid Component ◽  
Pathological Stage

scholarly journals Targetable subsets of non-Hodgkin lymphoma in Malawi define therapeutic opportunities

2016 ◽  
Vol 1 (1) ◽  
pp. 84-92 ◽  
Author(s):  
Elizabeth A. Morgan ◽  
M. Patrick Sweeney ◽  
Tamiwe Tomoka ◽  
Nadja Kopp ◽  
Daniel Gusenleitner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Hodgkin Lymphoma ◽  
Expression Profiling ◽  
Resource Constraints ◽  
Objective Assessment ◽  
Non Hodgkin Lymphoma ◽  
Key Points ◽  
Targeted Gene Expression

Key Points NHL subclassification is lacking in Malawi due to resource constraints yet is critical for directing therapy. Targeted gene expression profiling facilitates objective assessment and segregation of biologically defined subsets of NHL from Malawi.

Large-scale gene expression profiling reveals major pathogenetic pathways of cartilage degeneration in osteoarthritis

2006 ◽  
Vol 54 (11) ◽  
pp. 3533-3544 ◽  
Author(s):  
Thomas Aigner ◽  
Katrin Fundel ◽  
Joachim Saas ◽  
Pia M. Gebhard ◽  
Jochen Haag ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Large Scale ◽  
Cartilage Degeneration
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