Dataset Information

Detection of Structural Variations and Fusion Genes in Breast Cancer Samples Using Third-Generation Sequencing.

ABSTRACT: Background: Structural variations (SVs) are common genetic alterations in the human genome that could cause different phenotypes and diseases, including cancer. However, the detection of structural variations using the second-generation sequencing was limited by its short read length, which restrained our understanding of structural variations. Methods: In this study, we developed a 28-gene panel for long-read sequencing and employed it to Oxford Nanopore Technologies and Pacific Biosciences platforms. We analyzed structural variations in the 28 breast cancer-related genes through long-read genomic and transcriptomic sequencing of tumor, para-tumor, and blood samples in 19 breast cancer patients. Results: Our results showed that some somatic SVs were recurring among the selected genes, though the majority of them occurred in the non-exonic region. We found evidence supporting the existence of hotspot regions for SVs, which extended our previous understanding that they exist only for single nucleotide variations. Conclusion: In conclusion, we employed long-read genomic and transcriptomic sequencing to identify SVs from breast cancer patients and proved that this approach holds great potential in clinical application.

SUBMITTER: Hu T

PROVIDER: S-EPMC9043247 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Detection of Structural Variations and Fusion Genes in Breast Cancer Samples Using Third-Generation Sequencing.

Hu Taobo T Li Jingjing J Long Mengping M Wu Jinbo J Zhang Zhen Z Xie Fei F Zhao Jin J Yang Houpu H Song Qianqian Q Lian Sheng S Shi Jiandong J Guo Xueyu X Yuan Daoli D Lang Dandan D Yu Guoliang G Liang Baosheng B Zhou Xiaohua X Ishibashi Toyotaka T Fan Xiaodan X Yu Weichuan W Wang Depeng D Wang Yang Y Peng I-Feng IF Wang Shu S

Frontiers in cell and developmental biology 20220413

<b>Background:</b> Structural variations (SVs) are common genetic alterations in the human genome that could cause different phenotypes and diseases, including cancer. However, the detection of structural variations using the second-generation sequencing was limited by its short read length, which restrained our understanding of structural variations. <b>Methods:</b> In this study, we developed a 28-gene panel for long-read sequencing and employed it to Oxford Nanopore Technologies and Pacific B ...[more]

PMID: 35493102

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Project description:ObjectiveThe Shanghai Holstein cattle breed is susceptible to severe mastitis and other diseases due to the hot weather and long-term humidity in Shanghai, which is the main distribution centre for providing Holstein semen to various farms throughout China. Our objective was to determine the genetic mechanisms influencing economically important traits, especially diseases that have huge impact on the yield and quality of milk as well as reproduction.MethodsIn our study, we detected the structural variations of 1,092 Shanghai Holstein cows by using next-generation sequencing. We used the DELLY software to identify deletions and insertions, cn.MOPS to identify copy-number variants (CNVs). Furthermore, we annotated these structural variations using different bioinformatics tools, such as gene ontology, cattle quantitative trait locus (QTL) database and ingenuity pathway analysis (IPA).ResultsThe average number of high-quality reads was 3,046,279. After filtering, a total of 16,831 deletions, 12,735 insertions and 490 CNVs were identified. The annotation results showed that these mapped genes were significantly enriched for specific biological functions, such as disease and reproduction. In addition, the enrichment results based on the cattle QTL database showed that the number of variants related to milk and reproduction was higher than the number of variants related to other traits. IPA core analysis found that the structural variations were related to reproduction, lipid metabolism, and inflammation. According to the functional analysis, structural variations were important factors affecting the variation of different traits in Shanghai Holstein cattle. Our results provide meaningful information about structural variations, which may be useful in future assessments of the associations between variations and important phenotypes in Shanghai Holstein cattle.ConclusionStructural variations identified in this study were extremely different from those of previous studies. Many structural variations were found to be associated with mastitis and reproductive system diseases; these results are in accordance with the characteristics of the environment that Shanghai Holstein cattle experience.

Project description:BackgroundSchizophrenia (SCZ) is a heterogeneous psychiatric disorder, with significant contribution from genetic factors particularly for chronic cases with negative symptoms and cognitive deficits. To date, Genome Wide Association Studies (GWAS) and exome sequencing have associated SCZ with a number of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs), but there is still missing heritability. Medium-sized structural variants (SVs) are difficult to detect using SNP arrays or second generation sequencing, and may account for part of the missing heritability of SCZ.Aims and objectivesTo identify SVs associated with severe chronic SCZ across the whole genome.Study design10 multiplex families with probands suffering from chronic SCZ with negative symptoms and cognitive deficits were recruited, with all their affected members demonstrating uni-lineal inheritance. Control subjects comprised one affected member from the affected lineage, and unaffected members from each paternal and maternal lineage.MethodsThird generation sequencing was applied to peripheral blood samples from 10 probands and 5 unaffected controls. Bioinformatic tools were used to identify SVs from the long sequencing reads, with confirmation of findings in probands by short-read Illumina sequencing, Sanger sequencing and visual manual validation with Integrated Genome Browser.ResultsIn the 10 probands, we identified and validated 88 SVs (mostly in introns and medium-sized), within 79 genes, which were absent in the 5 unaffected control subjects. These 79 genes were enriched in 20 biological pathways which were related to brain development, neuronal migration, neurogenesis, neuronal/synaptic function, learning/memory, and hearing. These identified SVs also showed evidence for enrichment of genes that are highly expressed in the adolescent striatum.ConclusionA substantial part of the missing heritability in SCZ may be explained by medium-sized SVs detectable only by third generation sequencing. We have identified a number of such SVs potentially conferring risk for SCZ, which implicate multiple brain-related genes and pathways. In addition to previously-identified pathways involved in SCZ such as neurodevelopment and neuronal/synaptic functioning, we also found novel evidence for enrichment in hearing-related pathways and genes expressed in the adolescent striatum.

Dataset Information

Detection of Structural Variations and Fusion Genes in Breast Cancer Samples Using Third-Generation Sequencing.

Publications

Detection of Structural Variations and Fusion Genes in Breast Cancer Samples Using Third-Generation Sequencing.

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