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Yang X, Zhao H, Wu H, Guo X, Jia H, Liu W, Wei Y, Can C, Ma D. Analysis of gene mutation characteristics and its correlation with prognosis in patients with myelodysplastic syndromes. Clin Chim Acta 2024; 554:117789. [PMID: 38246208 DOI: 10.1016/j.cca.2024.117789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 12/26/2023] [Accepted: 01/15/2024] [Indexed: 01/23/2024]
Abstract
Gene mutations are a pivotal component of the pathogenesis of MDS, and they hold profound prognostic significance for predicting treatment responses and survival outcomes. However, reports about mutation patterns in Chinese MDS patients are limited. In this study, we analyzed the genetic mutation of 23 genes in 231 patients with MDS using next-generation sequencing (NGS) technology, and explored the characteristics of gene mutations in MDS patients and their associations with clinical outcomes, survival, and transformation outcomes. Our results showed that 68.83% patients had at least one gene mutation, and the most common mutations were ASXL1 (21.65%), SF3B1 (17.32%), U2AF1 (16.02%), TET2 (14.72%) and TP53 (8.66%). We also showed that the genetic mutations of TP53, U2AF1 and DNMT3A are independent risk factors for death in patients with MDS, and the ETV6 gene mutation was an independent risk factor for the transformation of MDS patients to AML through the univariate and multivariate Cox regression analysis model. Additionally, the study developed a risk score based on gene mutation data that demonstrated robust predictive capability and stability for the overall survival of MDS patients. Our research provided a strong theoretical basis for the establishment of personalized treatment and prognostic risk assessment models for Chinese MDS patients.
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Affiliation(s)
- Xinyu Yang
- Department of Hematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China; Shandong Key Laboratory of Immunohematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China
| | - Hongyu Zhao
- Department of Hematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China; Shandong Key Laboratory of Immunohematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China
| | - Hanyang Wu
- Department of Hematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China; Shandong Key Laboratory of Immunohematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China
| | - Xiaodong Guo
- Department of Hematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China; Shandong Key Laboratory of Immunohematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China
| | - Hexiao Jia
- Department of Hematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China; Shandong Key Laboratory of Immunohematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China
| | - Wancheng Liu
- Department of Hematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China; Shandong Key Laboratory of Immunohematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China
| | - Yihong Wei
- Department of Hematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China; Shandong Key Laboratory of Immunohematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China
| | - Can Can
- Department of Hematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China; Shandong Key Laboratory of Immunohematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China
| | - Daoxin Ma
- Department of Hematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China; Shandong Key Laboratory of Immunohematology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, People's Republic of China.
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Sheng L, Liu Y, Zhu Y, Zhou J, Hua H. Analysis of the clinical characteristics and prognosis of adult de novo acute myeloid leukemia (none APL) with PTPN11 mutations. Open Med (Wars) 2023; 18:20230830. [PMID: 38025540 PMCID: PMC10655689 DOI: 10.1515/med-2023-0830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 09/13/2023] [Accepted: 09/29/2023] [Indexed: 12/01/2023] Open
Abstract
We discuss the clinical characteristics and prognostic significance of adult individuals with PTPN11 mutations who have developed acute myeloid leukemia (AML) (none acute promyelocytic leukemia). Next generation sequencing and Sanger sequencing were used to detect 51 gene mutations, and multiplex-PCR was used to detect 41 fusion genes from 232 de novo adult AML patients retrospectively. About 7.76% patients harbored PTPN11 mutations, 20 PTPN11 alterations were identified, all of which were missense mutations in the N-SH2 (n = 16) and PTP (n = 4) domains located in exon 3. Patients with PTPN11 mut had significantly higher platelet counts and hemoglobin levels (p < 0.001), which were mainly detected in M5 (n = 12, 66.67%, p < 0.001) subtype. Patients with MLL-AF6 positive showed a higher frequency of PTPN11 mut (p = 0.018) in the 118 AML cases. PTPN11 mut were accompanied by other mutations, which were NPM1 (44.44%), DNMT3A (38.89%), FLT3 (38.89%), and NRAS (17.2%). PTPN11 mut had a negative impact on the complete remission rate in M5 subtype patients (p < 0.001). However, no statistically significant effect on overall survival (OS) with PTPN11 mut patients in the whole cohort and age group (p > 0.05) was observed. Further analysis revealed no significant difference in OS among NPM1 mut/PTPN11 mut, NPM1 mut/PTPN11 wt, DNMT3A mut/PTPN11 mut, and DNMT3A mut/PTPN11 wt patients (p > 0.05). Multivariate analysis showed the proportion of bone marrow blasts ≥65.4% was a factor significantly affecting OS in PTPN11 mut patients (p = 0.043).
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Affiliation(s)
- Li Sheng
- Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, China
| | - Yajiao Liu
- Nursing Department, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310000, China
| | - Yingying Zhu
- Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, China
| | - Jingfen Zhou
- Department of Hematology, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214122, China
| | - Haiying Hua
- Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, China
- Department of Hematology, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu, 214122, China
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Karnatam KS, Mythri B, Un Nisa W, Sharma H, Meena TK, Rana P, Vikal Y, Gowda M, Dhillon BS, Sandhu S. Silage maize as a potent candidate for sustainable animal husbandry development-perspectives and strategies for genetic enhancement. Front Genet 2023; 14:1150132. [PMID: 37303948 PMCID: PMC10250641 DOI: 10.3389/fgene.2023.1150132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 05/09/2023] [Indexed: 06/13/2023] Open
Abstract
Maize is recognized as the queen of cereals, with an ability to adapt to diverse agroecologies (from 58oN to 55oS latitude) and the highest genetic yield potential among cereals. Under contemporary conditions of global climate change, C4 maize crops offer resilience and sustainability to ensure food, nutritional security, and farmer livelihood. In the northwestern plains of India, maize is an important alternative to paddy for crop diversification in the wake of depleting water resources, reduced farm diversity, nutrient mining, and environmental pollution due to paddy straw burning. Owing to its quick growth, high biomass, good palatability, and absence of anti-nutritional components, maize is also one of the most nutritious non-legume green fodders. It is a high-energy, low-protein forage commonly used for dairy animals like cows and buffalos, often in combination with a complementary high-protein forage such as alfalfa. Maize is also preferred for silage over other fodders due to its softness, high starch content, and sufficient soluble sugars required for proper ensiling. With a rapid population increase in developing countries like China and India, there is an upsurge in meat consumption and, hence, the requirement for animal feed, which entails high usage of maize. The global maize silage market is projected to grow at a compound annual growth rate of 7.84% from 2021 to 2030. Factors such as increasing demand for sustainable and environment-friendly food sources coupled with rising health awareness are fueling this growth. With the dairy sector growing at about 4%-5% and the increasing shortage faced for fodder, demand for silage maize is expected to increase worldwide. The progress in improved mechanization for the provision of silage maize, reduced labor demand, lack of moisture-related marketing issues as associated with grain maize, early vacancy of farms for next crops, and easy and economical form of feed to sustain household dairy sector make maize silage a profitable venture. However, sustaining the profitability of this enterprise requires the development of hybrids specific for silage production. Little attention has yet been paid to breeding for a plant ideotype for silage with specific consideration of traits such as dry matter yield, nutrient yield, energy in organic matter, genetic architecture of cell wall components determining their digestibility, stalk standability, maturity span, and losses during ensiling. This review explores the available information on the underlying genetic mechanisms and gene/gene families impacting silage yield and quality. The trade-offs between yield and nutritive value in relation to crop duration are also discussed. Based on available genetic information on inheritance and molecular aspects, breeding strategies are proposed to develop maize ideotypes for silage for the development of sustainable animal husbandry.
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Affiliation(s)
- Krishna Sai Karnatam
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Bikkasani Mythri
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Wajhat Un Nisa
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Heena Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Tarun Kumar Meena
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Prabhat Rana
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Yogesh Vikal
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, Punjab, India
| | - M. Gowda
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
| | - Baldev Singh Dhillon
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Surinder Sandhu
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
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Sandoval C, Calle Y, Godoy K, Farías J. An Updated Overview of the Role of CYP450 during Xenobiotic Metabolization in Regulating the Acute Myeloid Leukemia Microenvironment. Int J Mol Sci 2023; 24:ijms24076031. [PMID: 37047003 PMCID: PMC10094375 DOI: 10.3390/ijms24076031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 03/08/2023] [Accepted: 03/16/2023] [Indexed: 04/14/2023] Open
Abstract
Oxidative stress is associated with several acute and chronic disorders, including hematological malignancies such as acute myeloid leukemia, the most prevalent acute leukemia in adults. Xenobiotics are usually harmless compounds that may be detrimental, such as pharmaceuticals, environmental pollutants, cosmetics, and even food additives. The storage of xenobiotics can serve as a defense mechanism or a means of bioaccumulation, leading to adverse effects. During the absorption, metabolism, and cellular excretion of xenobiotics, three steps may be distinguished: (i) inflow by transporter enzymes, (ii) phases I and II, and (iii) phase III. Phase I enzymes, such as those in the cytochrome P450 superfamily, catalyze the conversion of xenobiotics into more polar compounds, contributing to an elevated acute myeloid leukemia risk. Furthermore, genetic polymorphism influences the variability and susceptibility of related myeloid neoplasms, infant leukemias associated with mixed-lineage leukemia (MLL) gene rearrangements, and a subset of de novo acute myeloid leukemia. Recent research has shown a sustained interest in determining the regulators of cytochrome P450, family 2, subfamily E, member 1 (CYP2E1) expression and activity as an emerging field that requires further investigation in acute myeloid leukemia evolution. Therefore, this review suggests that CYP2E1 and its mutations can be a therapeutic or diagnostic target in acute myeloid leukemia.
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Affiliation(s)
- Cristian Sandoval
- Escuela de Tecnología Médica, Facultad de Salud, Universidad Santo Tomás, Los Carreras 753, Osorno 5310431, Chile
- Departamento de Ingeniería Química, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Temuco 4811230, Chile
- Departamento de Ciencias Preclínicas, Facultad de Medicina, Universidad de La Frontera, Temuco 4811230, Chile
| | - Yolanda Calle
- School of Life and Health Sciences, University of Roehampton, London SW15 4JD, UK
| | - Karina Godoy
- Núcleo Científico y Tecnológico en Biorecursos (BIOREN), Universidad de La Frontera, Temuco 4811230, Chile
| | - Jorge Farías
- Departamento de Ingeniería Química, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Temuco 4811230, Chile
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Lit BMW, Guo BB, Malherbe JAJ, Kwong YL, Erber WN. Mutation profile of acute myeloid leukaemia in a Chinese cohort by targeted next-generation sequencing. Cancer Rep (Hoboken) 2021; 5:e1573. [PMID: 34617422 PMCID: PMC9575498 DOI: 10.1002/cnr2.1573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 08/10/2021] [Accepted: 08/23/2021] [Indexed: 11/07/2022] Open
Abstract
Background Acute myeloid leukaemia (AML) results from the clonal expansion of blast cells of myeloid origin driven by genomic defects. The advances in next‐generation sequencing (NGS) have allowed the identification of many mutated genes important in the pathogenesis of AML. Aims In this study, we aimed to assess the mutation types and frequency in a Chinese cohort presenting with de novo AML cohort using a targeted NGS strategy. Methods In total, we studied samples from 87 adult patients with de novo AML who had no prior history of cytotoxic chemotherapy. Samples were evaluated using a 120‐gene targeted NGS panel to assess the mutation profile. Results Of the 87 AML patients, there were 60 (69%) with a normal karyotype. 89.7% of patients had variants, with an average of 1.9 mutations per patient (range: 0–5 mutations per patient). DNMT3A variants were the most common, being detected in 33 patients (37.9%). NPM1 (34.5%), IDH1/2 (24.1%) and FLT3‐ITD (20.7%) mutations was the next most common. Of the patients with DNMT3A mutations, 24.2% also had mutations NPM1 and FLT3‐ITD and 6.1% NPM1, FLT3‐ITD and IDH mutations. Conclusion Both DNMT3A and NPM1 mutations were more common than in other Chinese and Western AML cohorts that have been studied. DNMT3A mutations tended to co‐occur with NPM1 and FLT3‐ITD mutations and were most commonly seen with a normal karyotype.
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Affiliation(s)
| | - Belinda B Guo
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, Australia
| | | | - Yok Lam Kwong
- Department of Medicine, Queen Mary Hospital, The University of Hong Kong, Hong Kong, China
| | - Wendy N Erber
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, Australia.,PathWest Laboratory Medicine, Nedlands, WA, Australia
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Comparison of gene mutation spectra in younger and older Chinese acute myeloid leukemia patients and its prognostic value. Gene 2020; 770:145344. [PMID: 33333221 DOI: 10.1016/j.gene.2020.145344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 11/01/2020] [Accepted: 12/01/2020] [Indexed: 11/21/2022]
Abstract
Differences in the gene mutation spectra of younger and older Chinese adult AML patients and the prognostic significance of these differentially presented gene mutations are rarely reported. One hundred and thirteen newly diagnosed Chinese adults with AML, divided into groups of younger and older patients, were enrolled in this study. Bone marrow samples from the patients were analyzed using targeted next-generation sequencing with a panel of 141 genes. Ninety-eight mutated genes were detected and the top 10 mutated genes were KMT2D, FLT3, FAT1, ASXL1, NRAS, DNMT3A, RELN, TET2, JAK2, and KRAS. The top five functional groups were the tyrosine kinase pathway, transcription factors, DNA methylation, chromatin modifiers, and the JAK-STAT signaling pathway. Younger patients exhibited higher incidences of KMT2D (33.8% vs 10.4%, P = 0.004) and KRAS (15.4% vs 2.1%, P = 0.042) mutations than older patients; whereas, older patients harbored more SRSF2 (20.8% vs 0%, P = 0.002), transcription factor (85.4% vs 67.7%, P = 0.031), DNA methylation (58.3% vs 36.9%, P = 0.024), and RNA splicing (31.3% vs 12.3%, P = 0.013) mutations than younger patients. Moreover, patients with SRSF2 mutations exhibited a lower rate of overall survival (P < 0.001) and relapse-free survival (P < 0.001) than patients carrying wild-type SRSF2. In conclusion, rarely reported KMT2D, FAT1, and RELN mutations were detected at high frequencies in our cohort. The gene mutation spectrum of older patients was different to that of younger patients. Moreover, older patients harbored more SRSF2 mutations, which predicted lower rates of overall and relapse-free survival.
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Yu J, Li Y, Zhang D, Wan D, Jiang Z. Clinical implications of recurrent gene mutations in acute myeloid leukemia. Exp Hematol Oncol 2020; 9:4. [PMID: 32231866 PMCID: PMC7099827 DOI: 10.1186/s40164-020-00161-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Accepted: 03/17/2020] [Indexed: 12/18/2022] Open
Abstract
Acute myeloid leukemia (AML) is a genetically heterogeneous clonal malignancy characterized by recurrent gene mutations. Genomic heterogeneity, patients’ individual variability, and recurrent gene mutations are the major obstacles among many factors that impact treatment efficacy of the AML patients. With the application of cost- and time-effective next-generation sequencing (NGS) technologies, an enormous diversity of genetic mutations has been identified. The recurrent gene mutations and their important roles in acute myeloid leukemia (AML) pathogenesis have been studied extensively. In this review, we summarize the recent development on the gene mutation in patients with AML.
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Affiliation(s)
- Jifeng Yu
- 1Department of Hematology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052 Henan China.,2Academy of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450052 Henan China
| | - Yingmei Li
- 1Department of Hematology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052 Henan China
| | - Danfeng Zhang
- 1Department of Hematology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052 Henan China
| | - Dingming Wan
- 1Department of Hematology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052 Henan China
| | - Zhongxing Jiang
- 1Department of Hematology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052 Henan China
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Levy MA, Santos S, Kerkhof J, Stuart A, Aref‐Eshghi E, Guo F, Hedley B, Wong H, Rauh M, Feilotter H, Berardi P, Semenuk L, Yang P, Knoll J, Ainsworth P, McLachlin CM, Chin‐Yee I, Kovacs M, Deotare U, Lazo‐Langner A, Hsia C, Keeney M, Xenocostas A, Howlett C, Lin H, Sadikovic B. Implementation of an NGS‐based sequencing and gene fusion panel for clinical screening of patients with suspected hematologic malignancies. Eur J Haematol 2019; 103:178-189. [DOI: 10.1111/ejh.13272] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 05/27/2019] [Accepted: 06/03/2019] [Indexed: 12/28/2022]
Affiliation(s)
- Michael A. Levy
- Department of Pathology and Laboratory Medicine Western University London Ontario Canada
- Molecular Genetics Laboratory, Molecular Diagnostics Division London Health Sciences Centre London Ontario Canada
| | - Stephanie Santos
- Molecular Genetics Laboratory, Molecular Diagnostics Division London Health Sciences Centre London Ontario Canada
| | - Jennifer Kerkhof
- Molecular Genetics Laboratory, Molecular Diagnostics Division London Health Sciences Centre London Ontario Canada
| | - Alan Stuart
- Molecular Genetics Laboratory, Molecular Diagnostics Division London Health Sciences Centre London Ontario Canada
| | - Erfan Aref‐Eshghi
- Department of Pathology and Laboratory Medicine Western University London Ontario Canada
- Molecular Genetics Laboratory, Molecular Diagnostics Division London Health Sciences Centre London Ontario Canada
| | - Fen Guo
- Molecular Genetics Laboratory, Molecular Diagnostics Division London Health Sciences Centre London Ontario Canada
| | - Ben Hedley
- Pathology and Laboratory Medicine London Health Sciences Centre London Ontario Canada
| | - Henry Wong
- Clinical Laboratories Kingston Health Sciences Centre Kingston Ontario Canada
| | - Michael Rauh
- Department of Pathology and Molecular Medicine Queen's University Kingston Ontario Canada
| | - Harriet Feilotter
- Department of Pathology and Molecular Medicine Queen's University Kingston Ontario Canada
- Molecular Diagnostics Kingston Health Sciences Centre Kingston Ontario Canada
| | - Philip Berardi
- University of Ottawa Ottawa Ontario Canada
- Eastern Ontario Regional Laboratory Association (EORLA) The Ottawa Hospital Ottawa Ontario Canada
| | - Laura Semenuk
- DNA Diagnostics & Cytogenetics Laboratory Kingston Health Sciences Centre Kingston Ontario Canada
| | - Ping Yang
- Department of Pathology and Laboratory Medicine Western University London Ontario Canada
- Cytogenetics Laboratory, Molecular Diagnostics Division London Health Sciences Centre London Ontario Canada
| | - Joan Knoll
- Department of Pathology and Laboratory Medicine Western University London Ontario Canada
- Molecular Diagnostics Division London Health Sciences Centre London Ontario Canada
| | - Peter Ainsworth
- Department of Pathology and Laboratory Medicine Western University London Ontario Canada
- Molecular Genetics Laboratory, Molecular Diagnostics Division London Health Sciences Centre London Ontario Canada
- Department of Biochemistry Western University London Ontario Canada
| | | | - Ian Chin‐Yee
- Hematology Division London Health Sciences Centre London Ontario Canada
| | - Michael Kovacs
- Hematology Division London Health Sciences Centre London Ontario Canada
| | - Uday Deotare
- Hematology Division London Health Sciences Centre London Ontario Canada
- Schulich School of Medicine and Dentistry Western University London Ontario Canada
- Departments of Medicine and Oncology London Health Sciences Centre London Ontario Canada
| | - Alejandro Lazo‐Langner
- Hematology Division London Health Sciences Centre London Ontario Canada
- Department of Epidemiology and Biostatistics Western University London Ontario Canada
| | - Cyrus Hsia
- Hematology Division London Health Sciences Centre London Ontario Canada
| | - Mike Keeney
- Hematology Division London Health Sciences Centre London Ontario Canada
| | - Anargyros Xenocostas
- Hematology Division London Health Sciences Centre London Ontario Canada
- Schulich School of Medicine and Dentistry Western University London Ontario Canada
| | - Christopher Howlett
- Department of Pathology and Laboratory Medicine Western University London Ontario Canada
- Molecular Genetics Laboratory, Molecular Diagnostics Division London Health Sciences Centre London Ontario Canada
| | - Hanxin Lin
- Department of Pathology and Laboratory Medicine Western University London Ontario Canada
- Molecular Genetics Laboratory, Molecular Diagnostics Division London Health Sciences Centre London Ontario Canada
| | - Bekim Sadikovic
- Department of Pathology and Laboratory Medicine Western University London Ontario Canada
- Molecular Genetics Laboratory, Molecular Diagnostics Division London Health Sciences Centre London Ontario Canada
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Boutigny AL, Barranger A, De Boisséson C, Blanchard Y, Rolland M. Targeted Next Generation Sequencing to study insert stability in genetically modified plants. Sci Rep 2019; 9:2308. [PMID: 30783176 PMCID: PMC6381221 DOI: 10.1038/s41598-019-38701-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Accepted: 01/08/2019] [Indexed: 01/12/2023] Open
Abstract
The EU directive 2001/18/EC requires any genetically modified (GM) event to be stable. In the present work, a targeted Next-Generation Sequencing (NGS) approach using barcodes to specifically tag each individual DNA molecules during library preparation was implemented to detect mutations taking into account the background noise due to amplification and sequencing errors. The method was first showed to be efficient in detecting the mutations in synthetic samples prepared with custom-synthesized mutated or non-mutated P35S sequences mixed in different proportions. The genetic stability of a portion of the P35S promoter targeted for GM detection was then analyzed in GM flour samples. Several low frequency mutations were detected in the P35S sequences. Some mutated nucleotides were located within the primers and probes used in the P35S diagnostic test. If present not as somatic mutations but as the consensus sequence of some individuals, these mutations could influence the efficiency of the P35S real time PCR diagnostic test. This methodology could be implemented in genetic stability studies of GM inserts but also to detect single nucleotide mutant GM plants produced using "new breeding techniques".
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Affiliation(s)
- Anne-Laure Boutigny
- Anses, Plant Health Laboratory, Bacteriology Virology GMO Unit, 7 rue Jean Dixméras, 49044, Angers cedex 01, France.
| | - Audrey Barranger
- Anses, Plant Health Laboratory, Bacteriology Virology GMO Unit, 7 rue Jean Dixméras, 49044, Angers cedex 01, France
| | - Claire De Boisséson
- Anses, Ploufragan Laboratory, Viral Genetics and Biosafety Unit, BP 53, 22440, Ploufragan, France
| | - Yannick Blanchard
- Anses, Ploufragan Laboratory, Viral Genetics and Biosafety Unit, BP 53, 22440, Ploufragan, France
| | - Mathieu Rolland
- Anses, Plant Health Laboratory, Bacteriology Virology GMO Unit, 7 rue Jean Dixméras, 49044, Angers cedex 01, France
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