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Raja, N. S.

Publications and source records attributed to Raja, N. S..

3 recordsLinked to original sources

Spatial Single-Cell Proteomics Reveals Molecular Trajectories Of Tangle-Bearing Neurons In Alzheimer's Disease

Neurofibrillary tangles composed of hyperphosphorylated tau are a defining pathological hallmark of Alzheimers disease (AD); however, the pathways and mechanisms associated with the transition from physiological tau to tangle pathology remain unclear. Here, we integrate laser microdissection of post-mortem, fixed human AD brain tissue labelled with an antibody recognizing tangle-associated phospho-tau (AT8) with mass spectrometry-based proteomics, applied to individual neurons and to small neuronal pools. This approach identified [~]2,000 and [~]5,000 proteins, respectively, and enabled direct detection of disease-associated tau phosphorylation sites without prior enrichment. A layered analysis of the proteome of tangle-positive and tangle-negative neurons revealed heterogeneous disease-associated states. Pseudotime analysis, combined with an AI-driven analytical framework, indicates that neurons do not segregate into discrete classes but instead organize along a continuum of proteomic changes that correlate with tau abundance. This organization enabled the construction of a trajectory of pathological neuronal responses that can be resolved within an individual brain. Early stages of this trajectory are characterized by coordinated remodeling of proteostasis networks, including reduced proteasome component abundance and increased lysosomal acidification machinery, followed by disruption of synaptic pathways. Notably, despite extensive proteomic remodeling, neurons bearing tangles show little evidence of activated cell-death programs, suggesting prolonged molecular adaptation rather than acute degeneration. Together, these findings establish a framework for single-cell-resolved proteome analysis of human brain disease in situ and define a continuum of neuronal states underlying tau pathogenesis, revealing early vulnerabilities and adaptive responses during AD progression.

neuroscience↗

LncRAnalyzer: Uncovering Long Non-Coding RNAs and Exploring Gene Co-expression Patterns in Sorghum Genomics

Sorghum (Sorghum bicolor L. Moench) is a versatile crop with significant phenotypic and genetic diversity. Despite the availability of multiple resequenced sorghum genomes, noncoding genomic regions remain underexplored. Long noncoding RNA (lncRNA) is a major transcript category with relatively low expression and complex expression patterns that can be identified via RNA-seq. However, it is challenging to distinguish them from protein-coding genes because of their low abundance and tissue-specific expression. In the present study, we employed a dual sorghum reference genome scheme to identify 9467 (31.49% cultivar-specific) and 9551 (28.93% cultivar-specific) lncRNAs in sorghum cultivars BTX642 and RTX430, respectively. Our results showed that a few lncRNAs were linked to pre- and post-flowering drought tolerance in these two genotypes. The NPCTs encoded elements such as transposon-derived Pol polyproteins (RE-1, RE-2, TNT-1), pentatricopeptide repeat proteins, receptor-like protein kinases, zinc finger BED proteins, and putative disease resistance proteins, etc., suggesting their involvement in drought-specific phenotype development. Cis and trans acting targets for identified lncRNAs were predicted. The results showed that upregulated lncRNAs targeted C2H2, B3, putative zinc finger domain, Ras-related protein, L-ascorbate peroxidase-S, lanosterol synthase, and DUF domain genes during drought, which highlights their role in drought tolerance. The downstream gene coexpression analysis revealed time point-specific lncRNA interactions with TFs, resulting in substantial alterations in major TF numbers, including AP2/ERF-ERF, bHLH, bZIP, C2H2, MYB, and NAC. This study provided a more comprehensive understanding of drought tolerance in sorghum by identifying lncRNAs and examining their gene coexpression patterns.

bioinformatics↗

Unlocking the Genetic Landscape: Enhanced Insights into Sweet Sorghum Genomes through Comprehensive superTranscriptomic Analysis

Sweet sorghum has gained global significance as a versatile crop for food, fodder, and biofuel. Department of Agriculture, USA declared sorghum a sweet alternative for corn and sugarcane for biofuel production. Its cultivated varieties, along with their wild counterparts, contribute to the core genetic pool. We harnessed 223 publicly available RNA-seq datasets from sweet sorghum to construct the superTranscriptome and analyze gene structure. This approach yielded 45,864 Representative Transcript Assemblies (RTA) that showcased intriguing Presence-Absence Variation (PAV) across 15 existing sorghum genomes, even incorporating one wild progenitor. We identified 301 superTranscripts exclusive to sweet sorghum, encompassing elements such as hexokinases, cytochromes, select lncRNAs, and histones. Moreover, this study enriched sweet sorghum annotations with 2,802 newly identified protein-coding genes, including 559 encoding diverse transcription factors (TFs). This study unveiled 10,059 superTranscripts associated with various non-coding RNAs. The Rio variety displayed elevated expression of light-harvesting complexes (LHCs) and reduced expression of Metallothioneins during internode growth, suggesting the influence of photosynthesis and metal ion transport on sugar accumulation. Intriguingly, specific lncRNAs exhibited significant expression shifts in Rio during internode development, possibly implying their role in sugar accumulation. We validated the superTranscriptome against the Sweet Sorghum Reference Genome (SSRG) using Differential Exon Usage (DEU) and Differential Gene Expression (DGE), which yielded superior estimations. This study underscores the superTranscriptomes utility in unraveling fundamental sorghum mechanisms, enhancing genome annotations, and offering a potential alternative to the reference genome. Significance StatementThe comprehensive superTranscriptome of seven sweet sorghum genotypes revealed 45,864 genes, including 28.27% novel ones, predominantly comprising non-coding RNAs. Distributing core, dispensable, and cloud genes across 15 sorghum genomes differentiated common genes from cultivar-specific ones. superTranscriptome enhanced the annotation of 14 sorghum genomes with new genes/exons and effectively utilized RNA-seq data to annotate reference genomes. It identified presence/absence variations and non-coding genes and could be a potential alternative to the reference genome.

genomics↗