Biology subjects

Raina, P.

Publications and source records attributed to Raina, P..

5 recordsLinked to original sources

bioRxiv2024

BoMBR: An Annotated Bone Marrow Biopsy Dataset for Segmentation of Reticulin Fibers

Bone marrow reticulin fibrosis is associated with varied benign as well as malignant hematological conditions. The assessment of reticulin fibrosis is important in the diagnosis, prognostication and management of such disorders. The current methods for quantification of reticulin fibrosis are inefficient and prone to errors. Therefore, there is a need for automated tools for accurate and consistent quantification of reticulin. However, the lack of standardized datasets has hindered the development of such tools. In this study, we present a comprehensive dataset that comprises of 201 Bone Marrow Biopsy images for Reticulin (BoMBR) quantification. These images were meticulously annotated for semantic segmentation, with the focus on performing reticulin fiber quantification. This annotation was done by two trained hematopathologists who were aided by Deep Learning (DL) models and image processing techniques that generated a rough automated annotation for them to start with. This ensured precise delineation of the reticulin fibers alongside other cellular components such as bony trabeculae, fat, and cells. This is the first publicly available dataset in this domain with the aim to catalyze advancements the development of computational models for improved reticulin quantification. Further, we show that our annotated dataset can be used to train a DL model for a multi-class semantic segmentation task for robust reticulin fiber detection task (Mean Dice score: 0.92). We use these model outputs for the Marrow Fibrosis (MF) grade detection and obtained a Mean Weighted Average F1 score of 0.656 with our trained model. Our code for preprocessing the dataset is available at https://github.com/AI-in-Medicine-IIT-Ropar/BoMBR_dataset_preprocessing.

pathology↗

bioRxiv2024

Unveiling Ageing-Associated and Caloric Restriction-Associated Changes in miRNA Expression in Rat Skeletal Muscle and the Mechanisms Mediating their Effects on Muscle Cell Function

The mechanisms underlying skeletal muscle ageing, whilst poorly understood, are thought to involve dysregulated micro (mi)RNA expression. Using young and aged rat skeletal muscle tissue, we applied high-throughput RNA sequencing to comprehensively study alterations in miRNA expression occurring with age, as well as the impact of caloric restriction (CR) on these changes. Furthermore, the function of the proteins targeted by these age- and CR-associated miRNAs was ascertained. Numerous known and novel age-associated miRNAs were identified of which CR normalised 45.5% to youthful levels. Our results suggested miRNAs upregulated with age to downregulated proteins involved in muscle tissue development and metabolism, as well as longevity pathways, such as AMPK and autophagy. Furthermore, our results found miRNAs downregulated with age to upregulate pro-inflammatory proteins, particularly those involved in innate immunity and the complement and coagulation cascades. Interestingly, CR was particularly effective at normalising miRNAs upregulated with age, rescuing their associated protein coding genes but was less effective at rescuing anti-inflammatory miRNAs downregulated with age. Lastly, the effects of a specific miRNA, miR-96-5p, identified by our analysis to be upregulated with age, were studied in culture C2C12 myoblasts. We demonstrated miR-96-5p to decrease cell viability and markers of mitochondrial biogenesis, myogenic differentiation and autophagy. Overall, our results provide useful information regarding how miRNA expression changes in skeletal muscle, as well as the consequences of these changes and how they are ameliorated by CR.

molecular biology↗

bioRxiv2024

Unravelling the Transcriptomic Symphony of Sarcopenia: Key Pathways and Hub Genes Altered by Muscle Ageing and Caloric Restriction Revealed by RNA Sequencing

Sarcopenia is a disease involving extensive loss of muscle mass and strength with age and is a major cause of disability and accidents in the elderly. Mechanisms purported to be involved in muscle ageing and sarcopenia are numerous but poorly understood, necessitating deeper study. Hence, we employed high-throughput RNA sequencing to explicate the global changes in protein-coding gene expression occurring in skeletal muscle with age. Caloric restriction (CR) is a proven prophylactic intervention against sarcopenia. Therefore, total RNA was isolated from the muscle tissue of both rats fed ad libitum and CR rats. Collected data were subjected to Gene Ontology, pathway, co-expression, and interaction network analyses. This revealed the functional pathways most activated by both ageing and CR, as well as the key "hub" proteins involved in their activation. RNA-seq revealed 442 protein-coding genes to be upregulated and 377 to be downregulated in aged muscle, compared to young muscle. Upregulated genes were commonly involved in protein folding and the immune response; meanwhile, downregulated genes were often related to developmental biology. CR was found to suppress 69.7% and rescue 57.8% of the genes found to be upregulated and downregulated in aged muscle, respectively. In addition, CR uniquely upregulated 291 and downregulated 304 protein-coding genes. Hub genes implicated in both ageing and CR included Gc, Plg, Irf7, Ifit3, Usp18, Rsad2, Blm and RT1-A2, whilst those exclusively implicated in CR responses included Alb, Apoa1, Ambp, F2, Apoh, Orm1, Mx1, Oasl2 and Rtp4. Hub genes involved in ageing but unaffected by CR included Fgg, Fga, Fgb and Serpinc1. In conclusion, this comprehensive RNA sequencing study highlighted gene expression patterns, hub genes and signalling pathways most affected by ageing in skeletal muscle. This data may provide the initial evidence for several targets for therapeutic interventions against sarcopenia.

genomics↗

bioRxiv2021

GeneFriends 2021: Updated co-expression databases and tools for human and mouse genes and transcripts

Gene co-expression analysis has emerged as a powerful method to provide insights into gene function and regulation. The rapid growth of publicly available RNA-sequencing (RNA-seq) data has created opportunities for researchers to employ this abundant data to help decipher the complexity and biology of genomes. Co-expression networks have proven effective for inferring relationship between the genes, for gene prioritization and for assigning function to poorly annotated genes based on their co-expressed partners. To facilitate such analyses we created previously an online co-expression tool for humans and mice entitled GeneFriends. To continue providing a valuable tool to the scientific community, we have updated the GeneFriends database. Here, we present the latest version of GeneFriends, which includes updated gene and transcript co-expression networks based on RNA-seq data from 46,475 human and 34,322 mouse samples. GeneFriends is freely available at http://www.genefriends.org/

genomics↗

bioRxiv2020

Gene size matters: What determines gene length in the human genome?

While it is expected for gene length to be influenced by factors such as intron number and evolutionary conservation, we have yet to fully understand the connection between gene length and function in the human genome. In this study, we show that, as expected, there is a strong positive correlation between gene length and the number of SNPs, introns and protein size. Amongst tissue specific genes, we find that the longest genes are expressed in blood vessels, nerve, thyroid, cervix uteri and brain, while the smallest genes are expressed within the pancreas, skin, stomach, vagina and testis. We report, as shown previously, that natural selection suppresses changes for genes with longer lengths and promotes changes for smaller genes. We also observed that longer genes have a significantly higher number of co-expressed genes and protein-protein interactions. In the functional analysis, we show that bigger genes are often associated with neuronal development, while smaller genes tend to play roles in skin development and in the immune system. Furthermore, pathways related to cancer, neurons and heart diseases tend to have longer genes, with smaller genes being present in pathways related to immune response and neurodegenerative diseases. We hypothesise that longer genes tend to be associated with functions that are important early in life, while smaller genes play a role in functions that are important throughout the organisms whole life, like the immune system which require fast responses. Author SummaryEven though the human genome has been fully sequenced, we still do not fully grasp all of its nuances. One such nuance is the length of the genes themselves. Why are certain genes longer than others? Is there a common function shared by longer/smaller genes? What exactly makes gene longer? We tried answering these questions using a variety of analysis. We found that, while there was not a particular strong factor in genes that influenced their size, there could be an influence of several gene characteristics in determining the length of a gene. We also found that longer genes are linked with the development of neurons, cancer, heart diseases and muscle cells, while smaller genes seem to be mostly related with the immune system and the development of the skin. This led us to believe that, whether the gene has an important function early in our life, or throughout our whole lives, or even if the function requires a rapid response, that its gene size will be influenced accordingly.

genomics↗