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Biomedical subjects

Gurpreet Kaur

Publications and source records attributed to Gurpreet Kaur.

2 recordsLinked to original sources

Integrating genomics, multi-omics, CRISPR and speed breeding for stress-resilient vegetable legume improvement.

Vegetable legumes are nutritionally and ecologically important crops. However, their genetic improvement has not kept pace with the increasing challenges posed by climate change due to the polygenic nature of stress tolerance, narrow genetic diversity, and the persistent gap between molecular discoveries and field-level cultivar development. Although recent reviews have examined individual genomic tools or specific stress responses, a comprehensive synthesis integrating genomics-assisted breeding, multi-omics technologies, genome editing, and speed breeding within a unified crop improvement framework has been lacking. This review addresses that gap by critically evaluating how these complementary approaches can accelerate the development of stress-resilient vegetable legumes, including pea, common bean, cowpea, faba bean, cluster bean, yard-long bean, and hyacinth bean. This review synthesizes advances in QTL mapping, genome-wide association studies, transcriptomics, metabolomics, and CRISPR-based functional genomics that have identified key regulators and pathways underlying resistance to major biotic and abiotic stresses. Rather than considering these technologies independently, the review emphasizes their convergence into a systems-level breeding framework integrating genomic discovery, functional validation, predictive breeding, and accelerated generation advancement to improve breeding efficiency. Speed breeding, enabling up to seven to eight generations annually under optimized controlled-environment experimental conditions in cowpea, is discussed as a complementary strategy with genomic selection and genome editing. The review further identifies major translational bottlenecks, including transformation recalcitrance, limited genomic resources for underutilized vegetable legumes, inadequate multi-environment validation, and fragmented omics integration, and presents an integrated systems-breeding framework to bridge the gap between gene discovery and cultivar development.

Fabaceae

Uncovering the genetic architecture of ME/CFS: a precision approach reveals impact of rare monogenic variation.

BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disabling and heterogeneous disorder lacking validated biomarkers or targeted therapies. Clinical variability and elusive pathophysiology hinder progress toward effective diagnostics and treatment. Core symptoms include persistent fatigue, post-exertional malaise, unrefreshing sleep, cognitive dysfunction, and pain. We tested whether an individualized, “n-of-1” genomic and transcriptomic framework combined with comprehensive, participant-informed phenotyping could reveal molecular signatures unique to each patient. METHODS: Clinical-grade whole-genome sequencing was conducted in 31 affected individuals from 25 families, with RNA-seq performed on a subset (16 affected, 7 unaffected) using blood samples. Machine-learning assisted variant triage, transcript-aware damage prediction, and expert review identified pathogenic or likely pathogenic variants in 8 of 25 probands (32%) and 12 of 31 affected individuals (39%). RESULTS: Findings revealed marked genetic heterogeneity, including large-effect rare and more common variants. Implicated pathways included ATP generation, oxidative phosphorylation, fatty acid oxidation; regulation of glycolysis, amino acid and lipid turnover; ion and solute homeostasis; synaptic signaling, excitability, oxygen transport, and muscle integrity, resilience, and post-exertional recovery; previously implicated processes. Plausible modifiers influencing disease onset, severity, and relapsing–remitting patterns and possibly explaining intrafamilial variability and inconsistent findings across studies, were also identified. Despite gene-level diversity, downstream effects converged on impaired energy production, reduced stress resilience, and vulnerability to post-exertional metabolic failure; disruptions consistent with core ME/CFS symptoms of exertional intolerance, cognitive fog, and fatigue. CONCLUSIONS: Our findings support the hypothesis that at least a subset of ME/CFS cases represent distinct molecular disorders that converge on shared physiological pathways. Validation in larger, more diverse cohorts will be essential to test this hypothesis and establish generalizability, but increase size alone is unlikely to resolve causation in a disorder defined by rarity, heterogeneity, and molecular complexity. We suggest that progress will require experimental designs that integrate individual-level genomic data with deep, participant-informed deep phenotyping, capturing the combined effects of rare and common variants and environmental modifiers on disease expression and progression. We believe that an individualized precision medicine framework will uncover molecular drivers and modifiers of ME/CFS previously obscured by heterogeneity, enabling biologically informed stratification, improved trial design, biomarker discovery, and targeted interventions in this historically neglected condition.

Humans