Search Results (42)

Background: The tissues of origin and molecular mechanisms underlying human complex diseases remain incompletely understood. Previous studies have leveraged transcriptomic data to interpret genome-wide association studies (GWASs) for identifying disease-relevant tissues and fine-mapping causal genes. However, according to the central dogma, proteins more directly reflect cellular molecular activities than RNA. Therefore, in this study, we integrated proteomic data with GWAS to identify disease-associated tissues and genes. Methods: We compiled proteomic and paired transcriptomic data for 12,229 genes across 32 human tissues from the GTEx project. Using three tissue inference approaches—S-LDSC, MAGMA, and DESE—we analyzed GWAS data for six representative complex diseases (bipolar disorder, schizophrenia, coronary artery disease, Crohn’s disease, rheumatoid arthritis, and type 2 diabetes), with an average sample size of 260 K. We systematically compared disease-associated tissues and genes identified using proteomic versus transcriptomic data. Results: Tissue-specific protein abundance showed a moderate correlation with RNA expression (mean correlation coefficient = 0.46, 95% CI: 0.42–0.49). Proteomic data accurately identified disease-relevant tissues, such as the association between brain regions and schizophrenia and between coronary arteries and coronary artery disease. Compared to GWAS-based gene association estimates alone, incorporating proteomic data significantly improved gene association detection (AUC difference test, p = 0.0028). Furthermore, proteomic data revealed unique disease-associated genes that were not identified using transcriptomic data, such as the association between bipolar disorder and CREB1. Conclusions: Integrating proteomic data enables accurate identification of disease-associated tissues and provides irreplaceable advantages in fine-mapping genes for complex diseases. Full article

Background: Nasopharyngeal carcinoma (NPC) is a rare head and neck cancer arising from the mucosal lining of the nasopharynx, for which systemic therapeutic options remain scarce, reflecting the limited characterization of its genomic profile. This study utilized a large patient-level genomic repository to characterize genetic alterations, identify potential therapeutic targets, and improve disease modeling in NPC. Methods: A retrospective analysis of NPC samples was conducted using the AACR Project GENIE database. Targeted sequencing data were analyzed for recurrent somatic mutations, tumor mutational burden, and chromosomal copy number variations, with significance set at p < 0.05. Results: Frequent mutations were identified in KMT2D (20%), TP53 (16%), CYLD (9.6%), NFKBIA (6.4%), and PIK3CA (5.6%), implicating the p53, NF-κB, and PI3K pathways in NPC development. Notably, significantly distinct mutational profiles were observed based on both sex and race, with female patients exhibiting higher frequencies of PIK3C2G, ETV6, and CDKN1B mutations and non-Asian patients showing enrichment in KDM5A, CCND2, and TP53 mutations. Conclusions: This study presents a detailed genomic profile of NPC, identifying key mutations within established cancer-associated pathways. The identification of frequently mutated pathways (p53, NF-κB, and PI3K) suggests potential targets for novel therapies. Furthermore, distinct mutational landscapes in female and Asian NPC patients offer possibilities for precision therapeutic interventions. Full article

Obesity represents a complex interplay between genetics, nutrition, and lifestyle. This study aimed to elucidate the intricate relationship between genetic variants, energy intake, and bioactive compounds in influencing obesity risk, particularly in low energy intake, to reveal how dietary intake modulates molecular-level interactions. We analyzed 53,117 participants stratified by obesity status and energy intake levels. Genome-wide association studies explored the genetic variants associated with obesity risk in low-energy- and high-energy-intake subgroups. Advanced computational approaches, including molecular docking, k-means clustering, and uniform manifold approximation and projection (UMAP), were employed to analyze interactions between missense variants and natural compounds. Ten genetic variants were significantly associated with obesity, particularly in participants with low energy intake. The most prominent variants included brain-derived neurotrophic factor (BDNF) Val66Met polymorphism (rs6265). Molecular docking identified 152 bioactive compounds with strong binding affinity to BDNF Val66Met, including 107 compounds binding to both wild and mutant types. Citrus fruits and green vegetables showed selective binding to the mutant type. Antioxidant nutrient intake (anthocyanins, isoflavonoids, vitamins C and E, selenium) was higher in lean versus obese individuals in the high-energy-intake group. Alcohol consumption and selenium intake modulated polygenic risk scores’ influence on obesity risk in high-energy-intake individuals. Notably, citrus fruit intake correlated with lower BMI across all BDNF rs6265 genotypes. In conclusion, energy intake-specific genetic associations with obesity and identifies potential bioactive compounds for targeted interventions. The findings suggest that antioxidant nutrient intake, particularly from citrus fruits, may help manage obesity risk, especially in individuals with specific genetic variants. Full article

Rice provides poor yields in acidic soils due to several nutrient deficiencies and metal toxicities. The low availability of phosphorus (P) in acidic soils offers a natural condition for screening genotypes for grain yield and phosphorus utilization efficiency (PUE). The objective of this study was to phenotype a subset of indica rice accessions from 3000 Rice Genome Project (3K-RGP) under acidic soils and find associated genes and alleles. A panel of 234 genotypes, along with checks, were grown under low-input acidic soils for two consecutive seasons, followed by a low-P-based hydroponic screening experiment. The heritability of the agro-morphological traits was high across seasons, and Ward’s clustering method identified 46 genotypes that can be used as low-P-tolerant donors in acidic soil conditions. Genotypes ARC10145, RPA5929, and K1559-4, with a higher grain yield than checks, were identified. Over 29 million SNPs were retrieved from the Rice SNP-Seek database, and after quality control, they were utilized for a genome-wide association study (GWAS) with seventeen traits. Ten quantitative trait nucleotides (QTNs) for three yield traits and five QTNs for PUE were identified. A set of 34 candidate genes for yield-related traits was also identified. An association study using this indica panel for an already reported 1.84 Mbp region on chromosome 2 identified genes Os02g09840 and Os02g08420 for yield and PUE, respectively. A haplotype analysis for the candidate genes identified favorable allelic combinations. Donors carrying the superior haplotypic combinations for the identified genes could be exploited in future breeding programs. Full article

The Tibetan Plateau’s distinctive high-altitude environment, marked by extreme cold and reduced oxygen levels, presents considerable survival challenges for both humans and mammals. Natural selection has led to the accumulation of adaptive mutations in Tibetan pigs, enabling them to develop distinctive adaptive phenotypes. Here, we aim to uncover the genetic mechanisms underlying the adaptation of Tibetan pigs to high-altitude hypoxia. Therefore, we conducted a systematic analysis of 140 whole-genome sequencing (WGS) data points from different representing pig populations. Our analysis identified a total of 27,614,561 mutations, including 22,386,319 single-nucleotide variants (SNVs) and 5,228,242 insertions/deletions (INDELs, size < 50 bp). A total of 11% (2,678,569) of the SNVs were newly identified in our project, significantly expanding the dataset of genetic variants in Tibetan pigs. Compared to other pig breeds, Tibetan pigs are uniquely adapted to high-altitude environments, exhibiting the highest genetic diversity and the lowest inbreeding coefficient. Employing the composite of multiple signals (CMS) method, we scanned the genome-wide Darwinian positive selection signals and identified 32,499 Tibetan pig positively selected SNVs (TBPSSs) and 129 selected genes (TBPSGs), including 213 newly discovered genes. Notably, we identified eight genes (PHACTR1, SFI1, EPM2A, SLC30A7, NKAIN2, TNNI3K, and PLIN2) with strong nature selection signals. They are likely to improve cardiorespiratory function and fat metabolism to help Tibetan pigs become adapted to the high-altitude environment. These findings provide new insights into the genetic mechanisms of high-altitude adaptation and the adaptive phenotypes of Tibetan pigs. Full article

The worldwide emergence and dissemination of carbapenem-resistant Gram-negative bacteria (CRGNB) is a challenging problem of antimicrobial resistance today. Outbreaks with CRGNB have severe consequences for both the affected healthcare settings as well as the patients with infection. Thus, bloodstream infections caused by metallo-ß-lactamase-producing Enterobacterales can often have clinical implications, resulting in high mortality rates due to delays in administering effective treatment and the limited availability of treatment options. The overall threat of CRGNB is substantial because carbapenems are used to treat infections caused by ESBL-producing Enterobacterales which also exist with high frequency within the same geographical regions. A genome-based surveillance of 589 CRGNB from 61 hospitals across the federal state Hesse in Germany was implemented using next-generation sequencing (NGS) technology to obtain a high-resolution landscape of carbapenem-resistant isolates over a three-year period (2017–2019). The study examined all reportable CRGNB isolates submitted by participating hospitals. This included isolates carrying known carbapenemases (435) together with carbapenem-resistant non-carbapenemase producers (154). Predominant carbapenemase producers included Klebsiella pneumoniae, Escherichia coli, Citrobacter freundii and Acinetobacter baumannii. Over 80% of 375 carbapenem-resistant determinants including KPC-, NDM-, VIM- and OXA-48-like ones detected in 520 Enterobacterales were plasmid-encoded, and half of these were dominated by a few incompatibility (Inc) types, viz., IncN, IncL/M, IncFII and IncF(K). Our results revealed that plasmids play an extraordinary role in the dissemination of carbapenem resistance in the heterogeneous CRGNB population. The plasmids were also associated with several multispecies dissemination events and local outbreaks throughout the study period, indicating the substantial role of horizontal gene transfer in carbapenemase spread. Furthermore, due to vertical and horizontal plasmid transfer, this can have an impact on implant-associated infections and is therefore important for antibiotic-loaded bone cement and drug-containing devices in orthopedic surgery. Future genomic surveillance projects should increase their focus on plasmid characterization. Full article

Wheat (Triticum aestivum L.) production is adversely impacted by Septoria nodorum blotch (SNB), a fungal disease caused by Parastagonospora nodorum. Wheat breeders are constantly up against this biotic challenge as they try to create resistant cultivars. The genome-wide association study (GWAS) has become an efficient tool for identifying molecular markers linked with SNB resistance. This technique is used to acquire an understanding of the genetic basis of resistance and to facilitate marker-assisted selection. In the current study, a total of 174 bread wheat accessions from South Asia and CIMMYT were assessed for SNB reactions at the seedling stage in three greenhouse experiments at CIMMYT, Mexico. The results indicated that 129 genotypes were resistant to SNB, 39 were moderately resistant, and only 6 were moderately susceptible. The Genotyping Illumina Infinium 15K Bead Chip was used, and 11,184 SNP markers were utilized to identify marker–trait associations (MTAs) after filtering. Multiple tests confirmed the existence of significant MTAs on chromosomes 5B, 5A, and 3D, and the ones at Tsn1 on 5B were the most stable and conferred the highest phenotypic variation. The resistant genotypes identified in this study could be cultivated in South Asian countries as a preventative measure against the spread of SNB. This work also identified molecular markers of SNB resistance that could be used in future wheat breeding projects. Full article

Protein ubiquitination is common and crucial in cellular functions, however, little is known about how deubiquitinating enzymes (DUBs) reverse regulate the ubiquitination signaling process. PPPDE family proteins are a novel class of deubiquitinating peptidases with demonstrated deubiquitination/deSUMOylating activities. In this study, we identified 10 PPPDE genes from the rice (Oryza sativa L.) genome unevenly distributed on five chromosomes, where most of these members have not been reported to date. Based on the gene structure, the OsPPPDE family consists of three distinct subgroups within the phylogenetic tree. Cis-element analysis identified light/phytohormone-responsive, development, and abiotic stress-related elements in the promoters of OsPPPDE. Furthermore, we conducted and analyzed the transcript abundance of OsPPPDE under various tissues and stresses using the transcriptome data of 352 samples from the Rice Expression Database and GEO datasets. Moreover, OsPPPDE5 showed differential regulation of its transcript abundance during Cd and drought stress. Collinearity and syntenic analysis of 101 PPPDEs and PPPDE-like proteins in 10 plant genomes indicated that this family is evolutionarily conserved. Domestication analysis suggests that OsPPPDEs may contribute to indica–japonica divergence using the data from the 3K Rice Genome Project. Our study provides a foundation for further study on the function and molecular mechanism of the OsPPPDE gene family. Full article

Since the implementation of the Materials Genome Project by the Obama administration in the United States, the development of various computational materials’ databases has fundamentally expanded the choice of industries such as materials and energy. In the field of thermoelectric materials, the thermoelectric figure of merit (ZT) quantifies the performance of the material. From the viewpoint of calculations for vast materials, the ZT values are not easily obtained due to their computational complexity. Here, we show how to build a database of thermoelectric materials based on first-principle calculations for the electronic and heat transport of materials. Firstly, the initial structures are classified according to the values of bandgap and other basic properties using the clustering algorithm K-means in machine learning, and high-throughput first principle calculations are carried out for narrow-bandgap semiconductors which exhibit a potential thermoelectric application. The present framework of calculations mainly includes a deformation potential module, an electrical transport performance module, a mechanical and a thermodynamic properties module. We have also set up a search webpage for the calculated database of thermoelectric materials, providing search facilities and the ability to view the related physical properties of materials. Our work may inspire the construction of more computational databases of first-principle thermoelectric materials and accelerate research progress in the field of thermoelectrics. Full article

Genetic biomarkers have played a pivotal role in the classification, prognostication, and guidance of clinical cancer therapies. Large-scale and multi-dimensional analyses of entire cancer genomes, as exemplified by projects like The Cancer Genome Atlas (TCGA), have yielded an extensive repository of data that holds the potential to unveil the underlying biology of these malignancies. Mutations stand out as the principal catalysts of cellular transformation. Nonetheless, other global genomic processes, such as alterations in gene expression and chromosomal re-arrangements, also play crucial roles in conferring cellular immortality. The incorporation of multi-omics data specific to cancer has demonstrated the capacity to enhance our comprehension of the molecular mechanisms underpinning carcinogenesis. This report elucidates how the integration of comprehensive data on methylation, gene expression, and copy number variations can effectively facilitate the unsupervised clustering of cancer samples. We have identified regressors that can effectively classify tumor and normal samples with an optimal integration of RNA sequencing, DNA methylation, and copy number variation while also achieving significant $p$-values. Further, these regressors were trained using linear and logistic regression with $k$-means clustering. For comparison, we employed autoencoder- and stacking-based omics integration and computed silhouette scores to evaluate the clusters. The proof of concept is illustrated using liver cancer data. Our analysis serves to underscore the feasibility of unsupervised cancer classification by considering genetic markers beyond mutations, thereby emphasizing the clinical relevance of additional global cellular parameters that contribute to the transformative process in cells. This work is clinically relevant because changes in gene expression and genomic re-arrangements have been shown to be signatures of cellular transformation across cancers, as well as in liver cancers. Full article

Genetic enhancement of grain production and quality is a priority in wheat breeding projects. In this study, we assessed two key agronomic traits—grain protein content (GPC) and thousand kernel weight (TKW)—across 179 Bulgarian contemporary and historic varieties and landraces across three growing seasons. Significant phenotypic variation existed for both traits among genotypes and seasons, and no discernible difference was evident between the old and modern accessions. To understand the genetic basis of the traits, we conducted a genome-wide association study with MLM using phenotypic data from the crop seasons, best linear unbiased estimators, and genotypic data from the 25K Infinium iSelect array. As a result, we detected 16 quantitative trait nucleotides (QTNs) associated with GPC and 15 associated with TKW, all of which passed the false discovery rate threshold. Seven loci favorably influenced GPC, resulting in an increase of 1.4% to 8.1%, while four loci had a positive impact on TKW with increases ranging from 1.9% to 8.4%. While some loci confirmed previously published associations, four QTNs linked to GPC on chromosomes 2A, 7A, and 7B, as well as two QTNs related to TKW on chromosomes 1B and 6A, may represent novel associations. Annotations for proteins involved in the senescence-associated nutrient remobilization and in the following buildup of resources required for seed germination have been found for selected putative candidate genes. These include genes coding for storage proteins, cysteine proteases, cellulose-synthase, alpha-amylase, transcriptional regulators, and F-box and RWP-RK family proteins. Our findings highlight promising genomic regions for targeted breeding programs aimed at improving grain yield and protein content. Full article

Background: The advancement of next-generation sequencing (NGS) technologies provides opportunities for large-scale Pharmacogenetic (PGx) studies and pre-emptive PGx testing to cover a wide range of genotypes present in diverse populations. However, NGS-based PGx testing is limited by the lack of comprehensive computational tools to support genetic data analysis and clinical decisions. Methods: Bioinformatics utilities specialized for human genomics and the latest cloud-based technologies were used to develop a bioinformatics pipeline for analyzing the genomic sequence data and reporting PGx genotypes. A database was created and integrated in the pipeline for filtering the actionable PGx variants and clinical interpretations. Strict quality verification procedures were conducted on variant calls with the whole genome sequencing (WGS) dataset of the 1000 Genomes Project (G1K). The accuracy of PGx allele identification was validated using the WGS dataset of the Pharmacogenetics Reference Materials from the Centers for Disease Control and Prevention (CDC). Results: The newly created bioinformatics pipeline, Pgxtools, can analyze genomic sequence data, identify actionable variants in 13 PGx relevant genes, and generate reports annotated with specific interpretations and recommendations based on clinical practice guidelines. Verified with two independent methods, we have found that Pgxtools consistently identifies variants more accurately than the results in the G1K dataset on GRCh37 and GRCh38. Conclusions: Pgxtools provides an integrated workflow for large-scale genomic data analysis and PGx clinical decision support. Implemented with cloud-native technologies, it is highly portable in a wide variety of environments from a single laptop to High-Performance Computing (HPC) clusters and cloud platforms for different production scales and requirements. Full article

The RYK gene encodes a receptor-like tyrosine kinase crucial for several biological processes, including development, tissue homeostasis, and cancer. This study utilized data from the Cancer Genome Atlas Project (TCGA) to evaluate RYK expression at both mRNA and protein levels in various cancers, determine its prognostic significance, and explore its involvement in cancer-related signaling pathways. Elevated levels of RYK mRNA were identified in cholangiocarcinoma (CHOL), pancreatic adenocarcinoma (PAAD), glioblastoma multiforme (GBM), lung squamous cell carcinoma (LUSC), brain lower grade glioma (LGG), head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LICH), esophageal carcinoma (ESCA), and colon adenocarcinoma (COAD), while RYK protein levels were observed to be increased in colon adenocarcinoma (COAD), GBM, LICH, cervical and endocervical adenocarcinoma (CESC), and breast invasive carcinoma (BRCA). Additionally, RYK overexpression correlated with poorer prognosis in several cancers, including PAAD, LICH, BRCA, ESCA, COAD, and CESC. Furthermore, RYK showed a positive correlation with the upregulation of multiple receptors and coreceptors in the WNT signaling pathway in various types of cancer. In terms of cancer-related signaling pathways, RYK was found to potentially interact with DNA damage, TSC/mTOR, PI3K/AKT, EMT, RTK, RAS/MAPK, ER hormone, AR hormone, and the cell cycle. This study provides new and previously unreported insights into the role of RYK in cancer biology. Full article

Familial non-medullary thyroid carcinoma (FNMTC) accounts for 3% to 9% of all thyroid cancer cases, yet its genetic mechanisms remain unknown. Our study aimed to screen and identify novel susceptibility genes for FNMTC. Whole-exome sequencing (WES) was conducted on a confirmed FNMTC pedigree, comprising four affected individuals across two generations. Variants were filtered and analyzed using ExAC and 1000 Genomes Project, with candidate gene pathogenicity predicted using SIFT, PolyPhen, and MutationTaster. Validation was performed through Sanger sequencing in affected pedigree members and sporadic patients (TCGA database) as well as general population data (gnomAD database). Ultimately, we identified the mutant PPP4R3A (NC_000014.8:g.91942196C>T, or NM_001366432.2(NP_001353361.1):p.(Asp409Asn), based on GRCH37) as an FNMTC susceptibility gene. Subsequently, a series of functional experiments were conducted to investigate the impact of PPP4R3A and its Asp409Asn missense variant in thyroid cancer. Our findings demonstrated that wild-type PPP4R3A exerted tumor-suppressive effects via the Akt-mTOR-P70 S6K/4E-BP1 axis. However, overexpression of the PPP4R3A Asp409Asn mutant resulted in loss of tumor-suppressive function, ineffective inhibition of cell invasion, and even promotion of cell proliferation and migration by activating the Akt/mTOR signaling pathway. These results indicated that the missense variant PPP4R3A Asp409Asn is a candidate susceptibility gene for FNMTC, providing new insights into the diagnosis and intervention of FNMTC. Full article

Histone methylation and acetylation play a crucial role in response to developmental cues and environmental changes. Previously, we employed mass spectrometry to identify histone modifications such as H3K27ac and H3K36me3 in the model diatom Phaeodactylum tricornutum, which have been shown to be important for transcriptional activation in animal and plant species. To further investigate their evolutionary implications, we utilized chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) and explored their genome-wide distribution in P. tricornutum. Our study aimed to determine their role in transcriptional regulation of genes and transposable elements (TEs) and their co-occurrence with other histone marks. Our results revealed that H3K27ac and H3K36me3 were predominantly localized in promoters and genic regions indicating a high conservation pattern with studies of the same marks in plants and animals. Furthermore, we report the diversity of genes encoding H3 lysine 36 (H3K36) trimethylation–specific methyltransferase in microalgae leveraging diverse sequencing resources including the Marine Microbial Eukaryote Transcriptome Sequencing Project database (MMETSP). Our study expands the repertoire of epigenetic marks in a model microalga and provides valuable insights into the evolutionary context of epigenetic-mediated gene regulation. These findings shed light on the intricate interplay between histone modifications and gene expression in microalgae, contributing to our understanding of the broader epigenetic landscape in eukaryotic organisms. Full article