Intron exon boundary junctions in human genome have in-built unique structural and energetic signals

Splice site recognition - deciphering Exon-Intron transitions for genetic insights using Enhanced integrated Block-Level gated LSTM model

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.

Molecular dynamics simulation-based trinucleotide and tetranucleotide level structural and energy characterization of the functional units of genomic DNA

Genomes of most organisms on earth are written in a universal language of life, made up of four units - adenine (A), thymine (T), guanine (G), and cytosine (C), and understanding the way they are put together has been a great challenge to date. Multiple efforts have been made to annotate this wonderfully engineered string of DNA using different methods but they lack a universal character. In this article, we have investigated the structural and energetic profiles of both prokaryotes and eukaryotes by considering two essential genomic sites, viz., the transcription start sites (TSS) and exon-intron boundaries. We have characterized these sites by mapping the structural and energy features of DNA obtained from molecular dynamics simulations, which considers all possible trinucleotide and tetranucleotide steps. For DNA, these physicochemical properties show distinct signatures at the TSS and intron-exon boundaries. Our results firmly convey the idea that DNA uses the same dialect for prokaryotes and eukaryotes and that it is worth going beyond sequence-level analyses to physicochemical space to determine the functional destiny of DNA sequences.

Cancer suppression and the evolution of multiple retrogene copies of TP53 in elephants: a re‐evaluation

Evolving to become bigger and/or longer lived should increase cancer susceptibility, but this predicted increase is not observed, a contradiction named Peto's paradox. A solution is that cancer suppression evolves to minimize cancer susceptibility, and the discovery of 19 retrogene (RTG) copies of the tumor suppressor gene TP53 in the African elephant (Loxodonta africana) is increasingly cited as a classic example of such adaptive suppression. However, classic examples need rigorous evaluation and an alternative hypothesis is that the RTGs spread by genetic drift. This study shows that before its duplication, the ancestral elephant RTG was already truncated from 390 amino acids to 157 by a frameshift mutation, and that 14 of the 19 copies are now truncated to ≤88 amino acids. There was no compelling evidence of either positive or negative selection acting on these 88 codons, and the pattern of RTG accumulation fits a neutral model with a duplication rate of ~10⁻⁶ per generation. It is concluded that there is no evidence supporting the hypothesis that the 19 elephant RTGs spread to fixation by selection; instead, the evidence indicates that these RTGs accumulated primarily by segmental duplication and drift. It is shown that the evolutionary multistage model of carcinogenesis (EMMC) predicts the recruitment of 1–2 independently acting tumor suppressor genes to suppress the increased cancer risk in elephants, so it is possible that one or a few RTGs may have been favored by selection resulting in the known enhanced sensitivity of elephant cells to DNA damage. However, the analysis does not provide any support for either a direct (via conserved TP53 activity) or indirect (via supporting canonical TP53 function) role of the RTGs sequences, so that the presence of multiple copies of TP53 retrogenes in elephants needs to be further justified before being used as a classic example of tumor suppression in large‐bodied animals.

Analysis of nucleoid-associated protein-binding regions reveals DNA structural features influencing genome organization in Mycobacterium tuberculosis

Nucleoid-Associated Proteins (NAPs) maintain bacterial nucleoid configuration through their architectural properties of DNA bending, wrapping, and bridging. However, the contribution of DNA structural alterations to DNA-NAP recognition at the genomic scale remains unresolved. Present work dissects the DNA sequence, shape and altered structural preferences at a genomic scale for six NAPs in Mycobacterium tuberculosis. Results suggest narrower minor groove width and higher DNA rigidity are marked for the binding sites of EspR and Lsr2, while mIHF, MtHU and NapM have heterogeneous DNA structural predilections. In contrast, WhiB4-DNA binding sites were characterized by wider minor groove width, highly deformable and less curved DNA. This work provides systematic insight into NAP-mediated genome organization as a function of DNA structural features.