Long-read sequencing identified a novel nonsense and a de novo missense of PPA2 in trans in a Chinese patient with autosomal recessive infantile sudden cardiac failure

Zhao, Arman; Shen, Juntai; Ding, Yueyue; Sheng, Mao; Zuo, Mengying; Lv, Haitao; Wang, Jian; Shen, Yiping; Wang, Hongying

doi:10.1016/j.cca.2021.03.029

Cited by 3 publications

(3 citation statements)

References 45 publications

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“…GO [76], SLC16A9 [77], ACADSB (acyl-CoA dehydrogenase short/branched chain) [78], IMPA1 [79], CD300LG [80], CIRBP (cold inducible RNA binding protein) [81], PIK3R1 [82], YEATS4 [83], USP2 [84], NEDD9 [85], CHCHD5 [86] and ERAP1 [87] promotes hypertension. HSPB1 [88], CRYAB (crystallin alpha B) [89], ANXA5 [90], CCR2 [91], RGS4 [92], TNFRSF1A [93], XBP1 [94], NKX2-5 [95], NEU1 [96], GSTP1 [97], COMT (catechol-O-methyltransferase) [98], LIMK1 [99], CAMKK1 [100], CD276 [101], SMARCA4 [102], ADORA2B [103], ACOT1 [104], RGN (regucalcin) [105], PPA2 [106], KAT2B [107], PDK1 [108], CS (citrate synthase)…”

Section: Discussionmentioning

confidence: 99%

“…GO and REACTOME pathway enrichment analyses were used to investigate the interactions of these DEGs. SARS-CoV infections [45], asparagine N-linked glycosylation [46], neutrophil degranulation [47], immune system [48], respiratory electron transport [49], metabolism [50], complex I biogenesis [51], neddylation [52], localization [53], membrane [54], protein binding [55], small molecule metabolic process [56] RGN (regucalcin) [105], PPA2 [106], KAT2B [107], PDK1 [108], CS (citrate synthase) [109], FGF12 [110], AQP4 [111], LMOD2 [112], SELENBP1 [113], MB (myoglobin) [114], S100A1 [115], RYR2 [116], GPC5 [117], JARID2 [118], EGFR (epidermal growth factor receptor) [119], FUNDC1 [120], S1PR1 [121], EPAS1 [122] and OSBPL11 [123] genes are a potential biomarkers for the detection and prognosis of HF at an early age. A previous study reported that CALR (calreticulin) [124], BSCL2 [125], PKD1 [126], TMBIM1 [127], CHST15 [128] [190], SLC2A4 [191], HLA-DOA [192], TAP2 [193], HLA-DPA1 [194], NSMCE2 [195], NDUFA4 [196], HMG20A [197], AMY2B…”

Section: Discussionmentioning

confidence: 99%

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Identification of biomarkers, pathways and potential therapeutic targets for heart failure using bioinformatics analysis

Vastrad¹,

Vastrad²

2021

Preprint

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Heart failure (HF) is a complex cardiovascular diseases associated with high mortality. To discover key molecular changes in HF, we analyzed next-generation sequencing (NGS) data of HF. In this investigation, differentially expressed genes (DEGs) were analyzed using limma in R package from GSE161472 of the Gene Expression Omnibus (GEO). Then, gene enrichment analysis, protein-protein interaction (PPI) network, miRNA-hub gene regulatory network and TF-hub gene regulatory network construction, and topological analysis were performed on the DEGs by the Gene Ontology (GO), REACTOME pathway, STRING, HiPPIE, miRNet, NetworkAnalyst and Cytoscape. Finally, we performed receiver operating characteristic curve (ROC) analysis of hub genes. A total of 930 DEGs 9464 up regulated genes and 466 down regulated genes) were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections and the citric acid (TCA) cycle and respiratory electron transport. Subsequently, the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed, and 10 hub genes in these network were focused on by centrality analysis and module analysis. Furthermore, data showed that HSP90AA1, ARRB2, MYH9, HSP90AB1, FLNA, EGFR, PIK3R1, CUL4A, YEATS4 and KAT2B were good diagnostic values. In summary, this study suggests that HSP90AA1, ARRB2, MYH9, HSP90AB1, FLNA, EGFR, PIK3R1, CUL4A, YEATS4 and KAT2B may act as the key genes in HF.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Identification of biomarkers, pathways and potential therapeutic targets for heart failure using bioinformatics analysis

Vastrad¹,

Vastrad²

2021

Preprint

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“…Diagnostic uncertainty in autosomal recessive diseases also remains when parental samples are available, but one of the two variants occurred de novo in the proband. Again, LRS can resolve the phasing of variants and define their clinical relevance ( Zhao et al, 2021 ).…”

Section: Single Nucleotide Variantsmentioning

confidence: 99%

Long read sequencing on its way to the routine diagnostics of genetic diseases

Olivucci,

Iovino,

Innella

et al. 2024

Front. Genet.

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The clinical application of technological progress in the identification of DNA alterations has always led to improvements of diagnostic yields in genetic medicine. At chromosome side, from cytogenetic techniques evaluating number and gross structural defects to genomic microarrays detecting cryptic copy number variants, and at molecular level, from Sanger method studying the nucleotide sequence of single genes to the high-throughput next-generation sequencing (NGS) technologies, resolution and sensitivity progressively increased expanding considerably the range of detectable DNA anomalies and alongside of Mendelian disorders with known genetic causes. However, particular genomic regions (i.e., repetitive and GC-rich sequences) are inefficiently analyzed by standard genetic tests, still relying on laborious, time-consuming and low-sensitive approaches (i.e., southern-blot for repeat expansion or long-PCR for genes with highly homologous pseudogenes), accounting for at least part of the patients with undiagnosed genetic disorders. Third generation sequencing, generating long reads with improved mappability, is more suitable for the detection of structural alterations and defects in hardly accessible genomic regions. Although recently implemented and not yet clinically available, long read sequencing (LRS) technologies have already shown their potential in genetic medicine research that might greatly impact on diagnostic yield and reporting times, through their translation to clinical settings. The main investigated LRS application concerns the identification of structural variants and repeat expansions, probably because techniques for their detection have not evolved as rapidly as those dedicated to single nucleotide variants (SNV) identification: gold standard analyses are karyotyping and microarrays for balanced and unbalanced chromosome rearrangements, respectively, and southern blot and repeat-primed PCR for the amplification and sizing of expanded alleles, impaired by limited resolution and sensitivity that have not been significantly improved by the advent of NGS. Nevertheless, more recently, with the increased accuracy provided by the latest product releases, LRS has been tested also for SNV detection, especially in genes with highly homologous pseudogenes and for haplotype reconstruction to assess the parental origin of alleles with de novo pathogenic variants. We provide a review of relevant recent scientific papers exploring LRS potential in the diagnosis of genetic diseases and its potential future applications in routine genetic testing.

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Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis

Ganekal¹,

Vastrad²,

Vastrad³

et al. 2023

Therapeutic Advances in Cardiovascular Disease

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Background: Heart failure (HF) is the most common cardiovascular diseases and the leading cause of cardiovascular diseases related deaths. Increasing molecular targets have been discovered for HF prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might aid the diagnosis and treatment of HF. Methods: We searched next-generation sequencing (NGS) dataset (GSE161472) and identified differentially expressed genes (DEGs) by comparing 47 HF samples and 37 normal control samples using limma in R package. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g: Profiler database. The protein–protein interaction (PPI) network was plotted with Human Integrated Protein–Protein Interaction rEference (HiPPIE) and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. Then, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed by Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes. Results: A total of 930 DEGs, 464 upregulated genes and 466 downregulated genes, were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections, and the citric acid tricarboxylic acid (TCA) cycle and respiratory electron transport. After combining the results of the PPI network miRNA-hub gene regulatory network and TF-hub gene regulatory network, 10 hub genes were selected, including heat shock protein 90 alpha family class A member 1 (HSP90AA1), arrestin beta 2 (ARRB2), myosin heavy chain 9 (MYH9), heat shock protein 90 alpha family class B member 1 (HSP90AB1), filamin A (FLNA), epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), cullin 4A (CUL4A), YEATS domain containing 4 (YEATS4), and lysine acetyltransferase 2B (KAT2B). Conclusions: This discovery-driven study might be useful to provide a novel insight into the diagnosis and treatment of HF. However, more experiments are needed in the future to investigate the functional roles of these genes in HF.

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Long-read sequencing identified a novel nonsense and a de novo missense of PPA2 in trans in a Chinese patient with autosomal recessive infantile sudden cardiac failure

Cited by 3 publications

References 45 publications

Identification of biomarkers, pathways and potential therapeutic targets for heart failure using bioinformatics analysis

Identification of biomarkers, pathways and potential therapeutic targets for heart failure using bioinformatics analysis

Long read sequencing on its way to the routine diagnostics of genetic diseases

Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis

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