Journal of Genetics and Genomics最新文献

The thalamus regulates sensory processing, cognition, and sleep, yet the molecular mechanisms underlying its development remain incompletely understood. Long noncoding RNAs (lncRNAs), particularly evolutionarily conserved ones, are highly enriched in the brain. Using public mRNA databases, we screen for lncRNAs with embryonic brain expression and harboring ultraconserved non-coding elements (UCNEs) in humans and mice, identifying colorectal neoplasia differentially expressed (Crnde). It exhibits stage-specific upregulation in the embryonic thalamus. The Database of Genomic Variation and Phenotype in Humans using Ensembl Resources (DECIPHER) database suggests a potential association between Crnde and intellectual disability. Crnde-deficient mice display anxiety-like behaviors and spatial memory deficits. Furthermore, Crnde ablation increases progenitor cell numbers and impairs neuronal differentiation during embryonic thalamic development. Mechanistically, Crnde modulates the mRNA expression of gastrulation brain homeobox 2 (Gbx2), a gene critical for thalamic development. Collectively, our results implicate lncRNA Crnde in the proper progression of embryonic thalamic development in mice.

Amyotrophic lateral sclerosis (ALS) is a relentless and fatal neurodegenerative disorder characterized by the progressive loss of motor neurons, leading to muscle weakness, paralysis, and ultimately, respiratory failure. Despite a growing understanding of its complex pathophysiology, therapeutic options remain limited. This review critically analyzes recent clinical advances by comparing two divergent strategies, including precision gene-targeted therapies for monogenic ALS subtypes and broad-spectrum agents for the wider sporadic population. While gene therapies like tofersen demonstrate clear molecular target engagement, their translation to robust clinical benefit remains a challenge. In contrast, broad-spectrum agents have faced consistent late-stage failures, often due to the disease's underlying diversity, which undermines a one-size-fits-all approach. We argue that this heterogeneity, coupled with a lack of predictive biomarkers and the difficulty of late-stage intervention, represents the core barrier to progress. The future of ALS therapeutics therefore depends on a strategic pivot toward personalized medicine. This requires prospectively stratifying patients, developing rational combination therapies, and intervening earlier in the disease course, ultimately treating ALS as a syndrome of distinct molecular diseases rather than a single entity.

Hereditary cardiomyopathies and arrhythmias are major contributors to cardiovascular morbidity and mortality. The advent of next-generation sequencing (NGS) has made genetic testing more accessible, which is crucial for precise diagnosis and targeted therapeutic strategies. The aim of this study is to explore the landscape of genetic variants, the relationship between specific variants and clinical phenotypes, and the impact on clinical decision-making in China. A total of 1536 probands (median age, 37 years; 1025 males [66.7%]) with suspected hereditary cardiomyopathy or arrhythmia (covering 15 clinical phenotypes) are recruited from 146 hospitals across 30 provinces and cities in China. Positive results are confirmed in 390 of 1536 probands, leading to a diagnostic yield of 25.4%. Forty-two and three-tenths percent (n = 169) of family members carry the same variants as positive probands. Hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM) are the predominant phenotypes, with MYBPC3 variants having the highest frequency in HCM and TTN variants in DCM. In 76.9% of the positive probands, the identified variants are helpful in clinical management, family screening, and fertility. This large-scale study provides significant insights into the genetic landscape of hereditary cardiomyopathies and arrhythmias in China.

Existing quantitative trait locus (QTL) mapping had low efficiency in identifying small-effect and closely linked QTL-by-environment interactions (QEIs) in recombinant inbred lines (RILs), especially in the era of global climate change. To address this challenge, here we integrate the compressed variance component mixed model with our GCIM to propose 3vGCIM for identifying QEIs in RILs, and extend 3vGCIM-random to 3vGCIM-fixed. 3vGCIM integrates genome-wide scanning with machine learning, significantly improving power. In the mixed full model, we consider all possible effects and control for all possible polygenic backgrounds. In simulation studies, 3vGCIM exhibits higher power (∼92.00%), higher accuracy of the estimates for QTL position (∼1.900 cM²) and effect (∼0.050), and lower false positive rate (∼0.48‰) and false negative rate (<8.10%) in three environments of 300 RILs each than ICIM (47.57%; 3.607 cM², 0.583; 2.81‰; 52.43%) and MCIM (60.30%; 5.279 cM², 0.274; 2.17‰; 39.70%). In the real data analysis of rice yield-related traits in 240 RILs, 3vGCIM mines more known genes (57-60) and known gene-by-environment interactions (GEIs) (14-19) and candidate GEIs (21-23) than ICIM (27, 2, and 7), and MCIM (21, 1, and 3), especially in small-effect and linked QTLs and QEIs. This makes 3vGCIM a powerful and sensitive tool for QTL mapping and molecular QTL mapping.

Leaf thickness in rice critically influences photosynthetic efficiency and yield, yet its genetic basis remains poorly understood, with few functional genes previously characterized. In this study, we employ a pangenome-wide association study (Pan-GWAS) on 302 diverse rice accessions from southern China, identifying 49 quantitative trait loci (QTLs) associated with leaf thickness. The most significant locus, qLT9, is fine-mapped to a 79-kb region on chromosome 9. Transcriptomic and genomic sequence analyses identify LOC_Os09g33480, which encodes a protein belonging to Multiple Organellar RNA Editing Factor family, as the key candidate gene. Overexpression and complementation transgenic experiments confirm LOC_Os09g33480 (OsLT9) as the functional gene underlying qLT9, demonstrating a 24-bp Indel in its promoter correlates with the expression levels and leaf thickness. Notably, OsLT9 overexpression lines show not only thicker leaf, but also significantly enhanced photosynthetic efficiency and grain yield, establishing a link between leaf thickness modulation and yield enhancement. Population genomic analyses indicate strong selection for OsLT9 during domestication and breeding, with modern cultivars favoring thick leaf haplotype of OsLT9. This study establishes OsLT9 as a key regulator controlling leaf thickness in rice, and provides a valuable genetic resource for molecular breeding of high-yielding rice through optimization of plant architecture.

Leaf angle is a pivotal agronomic trait that significantly influences crop architecture and yield. Plant hormones, such as auxin, play a critical role in regulating leaf angle; however, the underlying molecular mechanisms remain to be fully elucidated. Here, we reveal that the auxin response factor gene, OsARF12, which is highly expressed in the leaf lamina joint, negatively regulates rice (Oryza sativa L.) leaf angle via affecting shoot gravitropism. Overexpression lines of OsARF12 exhibit more erect leaf angles, while the osarf12 mutants display enlarged leaf angles compared to the wild type. Further studies demonstrate that OsARF12 directly activates the expression of Loose Plant Architecture1 (LPA1) and LAZY1 by binding to their promoters. The osarf12 mutant presents impaired shoot gravitropism, a phenotype consistent with that of the lpa1 and lazy1 mutants. Collectively, we elucidate the biological functions of OsARF12, which modulates leaf angle through its impact on shoot gravitropism by regulating the expression levels of LPA1 and LAZY1. This study provides insight into the role of auxin in determining rice leaf angle, potentially holding profound effects for the optimization of crop architecture.

Radish (Raphanus sativus L.) is an important cruciferous root vegetable, with bolting regulated by multiple genes. However, the genetic mechanisms underlying bolting regulation remain unclear. Here, the genome of the cultivar C60213 is assembled into a high-quality, gap-free telomere-to-telomere structure, spanning nine chromosomes and totaling 472.71 Mb, using a combination of Oxford Nanopore, PacBio, and Hi-C sequencing technologies. It identifies 49,768 protein-coding genes, 97.38% of which are functionally annotated. Repetitive sequences constitute 59.72% of the genome, primarily comprising long terminal repeats. A high-density genetic linkage map is constructed using an F₂ population derived from a cross between early- and late-bolting radishes, identifying seven major quantitative trait loci associated with bolting and flowering. RNA-seq and quantitative real-time PCR analysis reveal that the RsMIPS3 gene is found to be associated with bolting, with its expression decreasing during this process. Notably, RsMIPS3 overexpression in Arabidopsis delays bolting, confirming its role in regulating bolting time. These findings advance radish genome research and provide a valuable target for breeding late-bolting varieties.

While conventional FISH and IHC methods struggle to decode complex tissue heterogeneity and comprehensive molecular diagnosis due to low-throughput spatial information, spatial omics technologies enable high-throughput molecular mapping across tissue microenvironments. These technologies are emerging as transformative tools in molecular diagnostics and medical research. By integrating histopathological morphology with spatial multi-omics profiling (genome, transcriptome, epigenome, and proteome), spatial omics technologies open an avenue for understanding disease progression, therapeutic resistance mechanisms, and precise diagnosis. It particularly enhances tumor microenvironment analysis by mapping immune cell distributions and functional states, which may greatly facilitate tumor molecular subtyping, prognostic assessment, and prediction of the radiotherapy and chemotherapy efficacy. Despite the substantial advancements in spatial omics, the translation of spatial omics into clinical applications remains challenging due to robustness, efficacy, clinical validation, and cost constraints. In this review, we summarize the current progress and prospects of spatial omics technologies, particularly in medical research and diagnostic applications.