RNAseqCNV: analysis of large-scale copy number variations from RNA-seq data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11130%2F22%3A10442548" target="_blank" >RIV/00216208:11130/22:10442548 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=rGHY8fPkp4" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=rGHY8fPkp4</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41375-022-01547-8" target="_blank" >10.1038/s41375-022-01547-8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

RNAseqCNV: analysis of large-scale copy number variations from RNA-seq data

Popis výsledku v původním jazyce

Transcriptome sequencing (RNA-seq) is widely used to detect gene rearrangements and quantitate gene expression in acute lymphoblastic leukemia (ALL), but its utility and accuracy in identifying copy number variations (CNVs) has not been well described. CNV information inferred from RNA-seq can be highly informative to guide disease classification and risk stratification in ALL due to the high incidence of aneuploid subtypes within this disease. Here we describe RNAseqCNV, a method to detect large scale CNVs from RNA-seq data. We used models based on normalized gene expression and minor allele frequency to classify arm level CNVs with high accuracy in ALL (99.1% overall and 98.3% for non-diploid chromosome arms, respectively), and the models were further validated with excellent performance in acute myeloid leukemia (accuracy 99.8% overall and 99.4% for non-diploid chromosome arms). RNAseqCNV outperforms alternative RNA-seq based algorithms in calling CNVs in the ALL dataset, especially in samples with a high proportion of CNVs. The CNV calls were highly concordant with DNA-based CNV results and more reliable than conventional cytogenetic-based karyotypes. RNAseqCNV provides a method to robustly identify copy number alterations in the absence of DNA-based analyses, further enhancing the utility of RNA-seq to classify ALL subtype.

Název v anglickém jazyce

RNAseqCNV: analysis of large-scale copy number variations from RNA-seq data

Popis výsledku anglicky

Transcriptome sequencing (RNA-seq) is widely used to detect gene rearrangements and quantitate gene expression in acute lymphoblastic leukemia (ALL), but its utility and accuracy in identifying copy number variations (CNVs) has not been well described. CNV information inferred from RNA-seq can be highly informative to guide disease classification and risk stratification in ALL due to the high incidence of aneuploid subtypes within this disease. Here we describe RNAseqCNV, a method to detect large scale CNVs from RNA-seq data. We used models based on normalized gene expression and minor allele frequency to classify arm level CNVs with high accuracy in ALL (99.1% overall and 98.3% for non-diploid chromosome arms, respectively), and the models were further validated with excellent performance in acute myeloid leukemia (accuracy 99.8% overall and 99.4% for non-diploid chromosome arms). RNAseqCNV outperforms alternative RNA-seq based algorithms in calling CNVs in the ALL dataset, especially in samples with a high proportion of CNVs. The CNV calls were highly concordant with DNA-based CNV results and more reliable than conventional cytogenetic-based karyotypes. RNAseqCNV provides a method to robustly identify copy number alterations in the absence of DNA-based analyses, further enhancing the utility of RNA-seq to classify ALL subtype.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30205 - Hematology

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Leukemia

ISSN

0887-6924

e-ISSN

1476-5551

Svazek periodika

36

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

7

Strana od-do

1492-1498

Kód UT WoS článku

000774743200002

EID výsledku v databázi Scopus

2-s2.0-85127341741