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Sha M, Parveen Rahamathulla M. Splice site recognition - deciphering Exon-Intron transitions for genetic insights using Enhanced integrated Block-Level gated LSTM model. Gene 2024; 915:148429. [PMID: 38575098 DOI: 10.1016/j.gene.2024.148429] [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: 12/22/2023] [Revised: 03/26/2024] [Accepted: 04/01/2024] [Indexed: 04/06/2024]
Abstract
Bioinformatics is a contemporary interdisciplinary area focused on analyzing the growing number of genome sequences. Gene variants are differences in DNA sequences among individuals within a population. Splice site recognition is a crucial step in the process of gene expression, where the coding sequences of genes are joined together to form mature messenger RNA (mRNA). These genetic variants that disrupt genes are believed to be the primary reason for neuro-developmental disorders like ASD (Autism Spectrum Disorder) is a neuro-developmental disorder that is diagnosed in individuals, families, and society and occurs as the developmental delay in one among the hundred genes that are associated with these disorders. Missense variants, premature stop codons, or deletions alter both the quality and quantity of encoded proteins. Predicting genes within exons and introns presents main challenges, such as dealing with sequencing errors, short reads, incomplete genes, overlapping, and more. Although many traditional techniques have been utilized in creating an exon prediction system, the primary challenge lies in accurately identifying the length and spliced strand location classification of exons in conjunction with introns. From now on, the suggested approach utilizes a Deep Learning algorithm to analyze intricate and extensive genomic datasets. M-LSTM is utilized to categorize three binary combinations (EI as 1, IE as 2, and none as 3) using spliced DNA strands. The M-LSTM system is able to sequence extensive datasets, ensuring that long information can be stored without any impact on the current input or output. This enables it to recognize and address long-term connections and problems with rapidly increasing gradients. The proposed model is compared internally with Naïve Bayes and Random Forest to assess its efficacy. Additionally, the proposed model's performance is forecasted by utilizing probabilistic parameters like recall, F1-score, precision, and accuracy to assess the effectiveness of the proposed system.
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Affiliation(s)
- Mohemmed Sha
- Department of Software Engineering, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al Kharj 11942, Kingdom of Saudi Arabia.
| | - Mohamudha Parveen Rahamathulla
- Department of Basic Medical Sciences, College of Medicine, Prince Sattam bin Abdulaziz University, Al Kharj 11942, Kingdom of Saudi Arabia.
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Sarker S, Eshaque TB, Soorajkumar A, Nassir N, Zehra B, Kanta SI, Rahaman MA, Islam A, Akter S, Ali MK, Mim RA, Uddin KMF, Chowdhury MSJ, Shams N, Baqui MA, Lim ET, Akter H, Woodbury-Smith M, Uddin M. Mutational spectrum and phenotypic variability of Duchenne muscular dystrophy and related disorders in a Bangladeshi population. Sci Rep 2023; 13:21547. [PMID: 38057384 PMCID: PMC10700514 DOI: 10.1038/s41598-023-48982-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 12/02/2023] [Indexed: 12/08/2023] Open
Abstract
Duchenne muscular dystrophy (DMD) is a severe rare neuromuscular disorder caused by mutations in the X-linked dystrophin gene. Several mutations have been identified, yet the full mutational spectrum, and their phenotypic consequences, will require genotyping across different populations. To this end, we undertook the first detailed genotype and phenotype characterization of DMD in the Bangladeshi population. We investigated the rare mutational and phenotypic spectrum of the DMD gene in 36 DMD-suspected Bangladeshi participants using an economically affordable diagnostic strategy involving initial screening for exonic deletions in the DMD gene via multiplex PCR, followed by testing PCR-negative patients for mutations using whole exome sequencing. The deletion mapping identified two critical DMD gene hotspot regions (near proximal and distal ends, spanning exons 8-17 and exons 45-53, respectively) that comprised 95% (21/22) of the deletions for this population cohort. From our exome analysis, we detected two novel pathogenic hemizygous mutations in exons 21 and 42 of the DMD gene, and novel pathogenic recessive and loss of function variants in four additional genes: SGCD, DYSF, COL6A3, and DOK7. Our phenotypic analysis showed that DMD suspected participants presented diverse phenotypes according to the location of the mutation and which gene was impacted. Our study provides ethnicity specific new insights into both clinical and genetic aspects of DMD.
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Affiliation(s)
- Shaoli Sarker
- Genetics and Genomic Medicine Centre (GGMC), NeuroGen Healthcare, Dhaka, Bangladesh
- Bangladesh Shishu Hospital and Institute, Dhaka, Bangladesh
| | | | - Anjana Soorajkumar
- Center for Applied and Translational Genomics (CATG), Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
| | - Nasna Nassir
- Center for Applied and Translational Genomics (CATG), Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
| | - Binte Zehra
- Center for Applied and Translational Genomics (CATG), Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
| | | | - Md Atikur Rahaman
- Genetics and Genomic Medicine Centre (GGMC), NeuroGen Healthcare, Dhaka, Bangladesh
| | - Amirul Islam
- Genetics and Genomic Medicine Centre (GGMC), NeuroGen Healthcare, Dhaka, Bangladesh
- GenomeArc Inc., Mississauga, Ontario, Canada
| | - Shimu Akter
- Genetics and Genomic Medicine Centre (GGMC), NeuroGen Healthcare, Dhaka, Bangladesh
| | - Mohammad Kawsar Ali
- Genetics and Genomic Medicine Centre (GGMC), NeuroGen Healthcare, Dhaka, Bangladesh
| | - Rabeya Akter Mim
- Genetics and Genomic Medicine Centre (GGMC), NeuroGen Healthcare, Dhaka, Bangladesh
| | - K M Furkan Uddin
- Genetics and Genomic Medicine Centre (GGMC), NeuroGen Healthcare, Dhaka, Bangladesh
| | | | - Nusrat Shams
- Genetics and Genomic Medicine Centre (GGMC), NeuroGen Healthcare, Dhaka, Bangladesh
| | - Md Abdul Baqui
- Department of Biochemistry, Holy Family Red Crescent Medical College and Hospital, Dhaka, Bangladesh
| | - Elaine T Lim
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA, 01605, USA
- Department of Molecular, Cell and Cancer Biology, University of Massachusetts Chan Medical School, Worcester, MA, 01605, USA
| | - Hosneara Akter
- Genetics and Genomic Medicine Centre (GGMC), NeuroGen Healthcare, Dhaka, Bangladesh
| | - Marc Woodbury-Smith
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, UK.
| | - Mohammed Uddin
- Center for Applied and Translational Genomics (CATG), Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE.
- GenomeArc Inc., Mississauga, Ontario, Canada.
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Codina A, Roldán M, Natera-de Benito D, Ortez C, Planas R, Matalonga L, Cuadras D, Carrera L, Exposito J, Marquez J, Jimenez-Mallebrera C, M. Porta J, Nascimento A, Jou C. Innovative Computerized Dystrophin Quantification Method Based on Spectral Confocal Microscopy. Int J Mol Sci 2023; 24:ijms24076358. [PMID: 37047330 PMCID: PMC10094132 DOI: 10.3390/ijms24076358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 12/16/2022] [Accepted: 12/29/2022] [Indexed: 03/30/2023] Open
Abstract
Several clinical trials are working on drug development for Duchenne and Becker muscular dystrophy (DMD and BMD) treatment, and, since the expected increase in dystrophin is relatively subtle, high-sensitivity quantification methods are necessary. There is also a need to quantify dystrophin to reach a definitive diagnosis in individuals with mild BMD, and in female carriers. We developed a method for the quantification of dystrophin in DMD and BMD patients using spectral confocal microscopy. It offers the possibility to capture the whole emission spectrum for any antibody, ensuring the selection of the emission peak and allowing the detection of fluorescent emissions of very low intensities. Fluorescence was evaluated first on manually selected regions of interest (ROIs), proving the usefulness of the methodology. Later, ROI selection was automated to make it operator-independent. The proposed methodology correctly classified patients according to their diagnosis, detected even minimal traces of dystrophin, and the results obtained automatically were statistically comparable to the manual ones. Thus, spectral imaging could be implemented to measure dystrophin expression and it could pave the way for detailed analysis of how its expression relates to the clinical course. Studies could be further expanded to better understand the expression of dystrophin-associated protein complexes (DAPCs).
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Clinical, muscle imaging, and genetic characteristics of dystrophinopathies with deep-intronic DMD variants. J Neurol 2023; 270:925-937. [PMID: 36319768 DOI: 10.1007/s00415-022-11432-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 10/15/2022] [Accepted: 10/17/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND Phenotypic heterogeneity within or between families with a same deep-intronic splice-altering variant in the DMD gene has never been systematically analyzed. This study aimed to determine the phenotypic and genetic characteristics of patients with deep-intronic DMD variants. METHODS Of 1338 male patients with a suspected dystrophinopathy, 38 were confirmed to have atypical pathogenic DMD variants via our comprehensive genetic testing approach. Of the 38 patients, 30 patients from 22 unrelated families with deep-intronic DMD variants underwent a detailed clinical and imaging assessment. RESULTS Nineteen different deep-intronic DMD variants were identified in the 30 patients, including 15 with Duchenne muscular dystrophy (DMD), 14 with Becker muscular dystrophy (BMD), and one with X-linked dilated cardiomyopathy. Of the 19 variants, 15 were single-nucleotide variants, 2 were structural variants (SVs), and 2 were pure-intronic large-scale SVs causing aberrant inclusion of other protein-coding genes sequences into the mature DMD transcripts. The trefoil with single fruit sign was observed in 18 patients and the concentric fatty infiltration pattern was observed in 2 patients. Remarkable phenotypic heterogeneity was observed not only in skeletal but also cardiac muscle involvement in 2 families harboring a same deep-intronic variant. Different skeletal muscle involvement between families with a same variant was observed in 4 families. High inter-individual phenotypic heterogeneity was observed within two BMD families and one DMD family. CONCLUSIONS Our study first highlights the variable phenotypic expressivity of deep-intronic DMD variants and demonstrates a new class of deep-intronic DMD variants, i.e., pure-intronic SVs involving other protein-coding genes.
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Keegan NP, Wilton SD, Fletcher S. Analysis of Pathogenic Pseudoexons Reveals Novel Mechanisms Driving Cryptic Splicing. Front Genet 2022; 12:806946. [PMID: 35140743 PMCID: PMC8819188 DOI: 10.3389/fgene.2021.806946] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 12/09/2021] [Indexed: 12/16/2022] Open
Abstract
Understanding pre-mRNA splicing is crucial to accurately diagnosing and treating genetic diseases. However, mutations that alter splicing can exert highly diverse effects. Of all the known types of splicing mutations, perhaps the rarest and most difficult to predict are those that activate pseudoexons, sometimes also called cryptic exons. Unlike other splicing mutations that either destroy or redirect existing splice events, pseudoexon mutations appear to create entirely new exons within introns. Since exon definition in vertebrates requires coordinated arrangements of numerous RNA motifs, one might expect that pseudoexons would only arise when rearrangements of intronic DNA create novel exons by chance. Surprisingly, although such mutations do occur, a far more common cause of pseudoexons is deep-intronic single nucleotide variants, raising the question of why these latent exon-like tracts near the mutation sites have not already been purged from the genome by the evolutionary advantage of more efficient splicing. Possible answers may lie in deep intronic splicing processes such as recursive splicing or poison exon splicing. Because these processes utilize intronic motifs that benignly engage with the spliceosome, the regions involved may be more susceptible to exonization than other intronic regions would be. We speculated that a comprehensive study of reported pseudoexons might detect alignments with known deep intronic splice sites and could also permit the characterisation of novel pseudoexon categories. In this report, we present and analyse a catalogue of over 400 published pseudoexon splice events. In addition to confirming prior observations of the most common pseudoexon mutation types, the size of this catalogue also enabled us to suggest new categories for some of the rarer types of pseudoexon mutation. By comparing our catalogue against published datasets of non-canonical splice events, we also found that 15.7% of pseudoexons exhibit some splicing activity at one or both of their splice sites in non-mutant cells. Importantly, this included seven examples of experimentally confirmed recursive splice sites, confirming for the first time a long-suspected link between these two splicing phenomena. These findings have the potential to improve the fidelity of genetic diagnostics and reveal new targets for splice-modulating therapies.
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Affiliation(s)
- Niall P. Keegan
- Centre for Molecular Medicine and Innovative Therapeutics, Health Futures Institute, Murdoch University, Perth, WA, Australia
- Centre for Neuromuscular and Neurological Disorders, Perron Institute for Neurological and Translational Science, The University of Western Australia, Perth, WA, Australia
- *Correspondence: Niall P. Keegan,
| | - Steve D. Wilton
- Centre for Molecular Medicine and Innovative Therapeutics, Health Futures Institute, Murdoch University, Perth, WA, Australia
- Centre for Neuromuscular and Neurological Disorders, Perron Institute for Neurological and Translational Science, The University of Western Australia, Perth, WA, Australia
| | - Sue Fletcher
- Centre for Molecular Medicine and Innovative Therapeutics, Health Futures Institute, Murdoch University, Perth, WA, Australia
- Centre for Neuromuscular and Neurological Disorders, Perron Institute for Neurological and Translational Science, The University of Western Australia, Perth, WA, Australia
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