Bioinformatics of High-Throughput Insertional Mutagenesis

ABSTRACTAvian leukosis virus subgroup J (ALV-J) is a simple retrovirus that can cause hemangiomas and myeloid tumors in chickens and is currently a major economic problem in Asia. Here we characterize ALV-J strain PDRC-59831, a newly studied U.S. isolate of ALV-J. Five-day-old chicken embryos were infected with this virus, and the chickens developed myeloid leukosis and hemangiomas within 2 months after hatching. To investigate the mechanism of pathogenesis, we employed high-throughput sequencing to analyze proviral integration sites in these tumors. We found expanded clones with integrations in theMETgene in two of the five hemangiomas studied. This integration locus was not seen in previous work characterizing ALV-J-induced myeloid leukosis.METis a known proto-oncogene that acts through a diverse set of signaling pathways and is involved in many neoplasms. We show that tumors harboringMETintegrations exhibit strong overexpression ofMETmRNA.IMPORTANCEThese data suggest that ALV-J induces oncogenesis by insertional mutagenesis, and integrations in theMEToncogene can drive the overexpression ofMETand contribute to the development of hemangiomas.

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Cancer LncRNA Census 2 (CLC2): an enhanced resource reveals clinical features of cancer lncRNAs

NAR Cancer ◽

10.1093/narcan/zcab013 ◽

2021 ◽

Vol 3 (2) ◽

Author(s):

Adrienne Vancura ◽

Andrés Lanzós ◽

Núria Bosch-Guiteras ◽

Mònica Torres Esteban ◽

Alejandro H Gutierrez ◽

...

Keyword(s):

High Throughput ◽

Insertional Mutagenesis ◽

Somatic Mutations ◽

Annotation Scheme ◽

Genomic Features ◽

Gene Sets ◽

Therapeutic Development ◽

Non Coding Rnas ◽

Clinical Genomic ◽

Suppressor Analysis

Abstract Long non-coding RNAs (lncRNAs) play key roles in cancer and are at the vanguard of precision therapeutic development. These efforts depend on large and high-confidence collections of cancer lncRNAs. Here, we present the Cancer LncRNA Census 2 (CLC2). With 492 cancer lncRNAs, CLC2 is 4-fold greater in size than its predecessor, without compromising on strict criteria of confident functional/genetic roles and inclusion in the GENCODE annotation scheme. This increase was enabled by leveraging high-throughput transposon insertional mutagenesis screening data, yielding 92 novel cancer lncRNAs. CLC2 makes a valuable addition to existing collections: it is amongst the largest, contains numerous unique genes (not found in other databases) and carries functional labels (oncogene/tumour suppressor). Analysis of this dataset reveals that cancer lncRNAs are impacted by germline variants, somatic mutations and changes in expression consistent with inferred disease functions. Furthermore, we show how clinical/genomic features can be used to vet prospective gene sets from high-throughput sources. The combination of size and quality makes CLC2 a foundation for precision medicine, demonstrating cancer lncRNAs’ evolutionary and clinical significance.

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Comparison and Validation of Putative Pathogenicity-Related Genes Identified by T-DNA Insertional Mutagenesis and Microarray Expression Profiling inMagnaporthe oryzae

BioMed Research International ◽

10.1155/2017/7198614 ◽

2017 ◽

Vol 2017 ◽

pp. 1-7

Author(s):

Ying Wang ◽

Ying Wáng ◽

Qi Tan ◽

Ying Nv Gao ◽

Yan Li ◽

...

Keyword(s):

High Throughput ◽

Expression Profiling ◽

Insertional Mutagenesis ◽

Target Gene ◽

Gene Replacement ◽

Knockout Mutants ◽

Target Gene Replacement ◽

Microarray Expression Profiling ◽

Microarray Expression ◽

Dna Insertional Mutagenesis

High-throughput technologies of functional genomics such as T-DNA insertional mutagenesis and microarray expression profiling have been employed to identify genes related to pathogenicity inMagnaporthe oryzae. However, validation of the functions of individual genes identified by these high-throughput approaches is laborious. In this study, we compared two published lists of genes putatively related to pathogenicity inM. oryzaeidentified by T-DNA insertional mutagenesis (comprising 1024 genes) and microarray expression profiling (comprising 236 genes), respectively, and then validated the functions of some overlapped genes between the two lists by knocking them out using the method of target gene replacement. Surprisingly, only 13 genes were overlapped between the two lists, and none of the four genes selected from the overlapped genes exhibited visible phenotypic changes on vegetative growth, asexual reproduction, and infection ability in their knockout mutants. Our results suggest that both of the lists might contain large proportions of unrelated genes to pathogenicity and therefore comparing the two gene lists is hardly helpful for the identification of genes that are more likely to be involved in pathogenicity as we initially expected.

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Cancer LncRNA Census 2 (CLC2): an enhanced resource reveals clinical features of cancer lncRNAs

10.1101/2020.04.28.066225 ◽

2020 ◽

Author(s):

Adrienne Vancura ◽

Andrés Lanzós ◽

Núria Bosch ◽

Mònica Torres ◽

Alejandro Hionides Gutierrez ◽

...

Keyword(s):

High Throughput ◽

Insertional Mutagenesis ◽

Somatic Mutations ◽

High Confidence ◽

Annotation Scheme ◽

Genomic Features ◽

Gene Sets ◽

Therapeutic Development ◽

Clinical Genomic ◽

Suppressor Analysis

AbstractLong noncoding RNAs play key roles in cancer and are at the vanguard of precision therapeutic development. These efforts depend on large and high-confidence collections of cancer lncRNAs. Here we present the Cancer LncRNA Census 2 (CLC2): at 492 cancer lncRNAs, it is 4-fold greater than its predecessor, without compromising on strict criteria of confident functional / genetic roles and inclusion in the GENCODE annotation scheme. This increase was enabled by leveraging high-throughput transposon insertional mutagenesis (TIM) screening data, yielding 95 novel cancer lncRNAs. CLC2 makes a valuable addition to existing collections: it is amongst the largest, holds the greatest number of unique genes, and carries functional labels (oncogene / tumour suppressor). Analysis of this dataset reveals that cancer lncRNAs are impacted by germline variants, somatic mutations, and changes in expression consistent with inferred disease functions. Furthermore, we show how clinical / genomic features can be used to vet prospective gene sets from high-throughput sources. The combination of size and quality makes CLC2 a foundation for precision medicine, demonstrating cancer lncRNAs’ evolutionary and clinical significance.

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