Analysis Of Genomic Variation Research Articles

Exploring the genetic and epigenetic underpinnings of early-onset cancers: Variant prioritization for long read whole genome sequencing from family cancer pedigrees.

Despite significant advances in our understanding of genetic cancer susceptibility, known inherited cancer predisposition syndromes explain at most 20% of early-onset cancers. As early-onset cancer prevalence continues to increase, the need to assess previously inaccessible areas of the human genome, harnessing a trio or quad family-based architecture for variant filtration, may reveal further insights into cancer susceptibility. To assess a broader spectrum of variation than can be ascertained by multi-gene panel sequencing, or even whole genome sequencing with short reads, we employed long read whole genome sequencing using an Oxford Nanopore Technology (ONT) PromethION of 3 families containing an early-onset cancer proband using a trio or quad family architecture. Analysis included 2 early-onset colorectal cancer family trios and one quad consisting of two siblings with testicular cancer, all with unaffected parents. Structural variants (SVs), epigenetic profiles and single nucleotide variants (SNVs) were determined for each individual, and a filtering strategy was employed to refine and prioritize candidate variants based on the family architecture. The family architecture enabled us to focus on inapposite variants while filtering variants shared with the unaffected parents, significantly decreasing background variation that can hamper identification of potentially disease causing differences. Candidate d e novo and compound heterozygous variants were identified in this way. Gene expression, in matched neoplastic and pre-neoplastic lesions, was assessed for one trio. Our study demonstrates the feasibility of a streamlined analysis of genomic variants from long read ONT whole genome sequencing and a way to prioritize key variants for further evaluation of pathogenicity, while revealing what may be missing from panel based analyses.

AI-generated synthetic clinical-genomic data for precision oncology research: Validation using a case study on lung adenocarcinoma.

e13627 Background: The analysis of genomic variants is crucial in precision oncology research, offering insights into cancer risks and progression, especially in diverse types such as lung adenocarcinoma (LUAD). However, such research often grapples with balancing patient privacy with the need for comprehensive, high-quality genomic datasets. Our project addresses this by creating synthetic clinical-genomic data, which maintains patient confidentiality and provides a rich resource for genomic cancer research. Methods: Leveraging the GuardantINFORM database, which includes anonymized genomic data and structured payer claims, we focused on generating synthetic data for LUAD patient cohorts. This approach involves processing real patient data into a format compatible with Medisyn’s generative AI models, ensuring the synthetic data retains the original's statistical properties, and processing the output back into the original database structure and format. This method plays a crucial role in maintaining patient privacy and serves as a valuable tool for research by enabling the generation of realistic patients with desired properties on demand. Results: Our synthetic data closely mirrors real-world genomic and claims variable distributions, evidenced by a 0.994 R2 correlation between real and synthetic data along with comparable Oncoprints. Importantly, privacy tests show that patient confidentiality is effectively maintained despite this effective performance. The synthetic data's utility was then demonstrated in a study replicating real-world findings: LUAD patients with KRAS G12C in combination with STK11 mutations showed a significantly higher risk of early mortality. This underscores the potential of synthetic data in advancing cancer research. Conclusions: This research offers a promising avenue for the cancer research community. By providing a method to share privatized, synthetic genomic data, which can be combined and generated on demand, we enable broader, more responsible data sharing. This approach protects patient privacy and offers a rich dataset for groundbreaking research, potentially accelerating advances in cancer diagnosis and treatment. [Table: see text]

The great tit HapMap project: A continental-scale analysis of genomic variation in a songbird.

A major aim of evolutionary biology is to understand why patterns of genomic diversity vary within taxa and space. Large-scale genomic studies of widespread species are useful for studying how environment and demography shape patterns of genomic divergence. Here, we describe one of the most geographically comprehensive surveys of genomic variation in a wild vertebrate to date; the great tit (Parus major) HapMap project. We screened ca 500,000 SNP markers across 647 individuals from 29 populations, spanning ~30 degrees of latitude and 40 degrees of longitude - almost the entire geographical range of the European subspecies. Genome-wide variation was consistent with a recent colonisation across Europe from a South-East European refugium, with bottlenecks and reduced genetic diversity in island populations. Differentiation across the genome was highly heterogeneous, with clear 'islands of differentiation', even among populations with very low levels of genome-wide differentiation. Low local recombination rates were a strong predictor of high local genomic differentiation (FST), especially in island and peripheral mainland populations, suggesting that the interplay between genetic drift and recombination causes highly heterogeneous differentiation landscapes. We also detected genomic outlier regions that were confined to one or more peripheral great tit populations, probably as a result of recent directional selection at the species' range edges. Haplotype-based measures of selection were related to recombination rate, albeit less strongly, and highlighted population-specific sweeps that likely resulted from positive selection. Our study highlights how comprehensive screens of genomic variation in wild organisms can provide unique insights into spatio-temporal evolutionary dynamics.

Single-cell transcriptional profiling in osteosarcoma and the effect of neoadjuvant chemotherapy on the tumor microenvironment

Osteosarcoma (OS), a malignant tumor, originates from the bone marrow. Currently, treatment for OS remains limited, making it urgent to understand the immune response in the tumor microenvironment of patients with OS. A comprehensive bioinformatics analysis was performed, including cell clustering subgroups, differential expression genes screening, proposed temporal order, and genomic variant analysis on single-cell RNA-sequencing data, from ten pre-chemotherapy patients and eleven post-chemotherapy patients. Subsequently, we analyzed the differentiation trajectories of osteoblasts, osteoclasts, fibroblasts, myeloid cells, and tumor-infiltrating lymphocytes (TILs) in detail to compare the changes in cell proportions and differential genes pre- and post-chemotherapy. The nine cell types were identified, including fibroblasts, myeloid cells, osteoblasts, TILs, osteoclasts, proliferative osteoblasts, pericytes, endothelial cells, and B cells. Post-chemotherapy treatment, the proportions of myeloid cells and TILs in OS were declined, while the number of osteoblasts was elevated. Besides, a decrease was observed in CD74, FTL, FTH1, MT1X and MT2A, and an increase in PTN, COL3A1, COL1A1, IGFBP7 and FN1. Meanwhile, EMT, DNA repair, G2M checkpoint, and E2F targets were highly enriched post-chemotherapy. Furthermore, there was a down-regulation in the proportions of CD14 monocytes, Tregs, NK cells and CD1C-/CD141-DCs, while an up-regulation was observed in the proportions of SELENOP macrophages, IL7R macrophages, COL1A1 macrophages, CD1C DCs, CD4+ T cells and CD8+ T cells. Overall, these findings revealed changes in the tumor microenvironment of OS post-chemotherapy treatment, providing a new direction for investigating OS treatment.

Comprehensive analysis of genomic variation, pan-genome and biosynthetic potential of Corynebacterium glutamicum strains.

Corynebacterium glutamicum is a non-pathogenic species of the Corynebacteriaceae family. It has been broadly used in industrial biotechnology for the production of valuable products. Though it is widely accepted at the industrial level, knowledge about the genomic diversity of the strains is limited. Here, we investigated the comparative genomic features of the strains and pan-genomic characteristics. We also observed phylogenetic relationships among the strains based on average nucleotide identity (ANI). We found diversity between strains at the genomic and pan-genomic levels. Less than one-third of the C. glutamicum pan-genome consists of core genes and soft-core genes. Whereas, a large number of strain-specific genes covered about half of the total pan-genome. Besides, C. glutamicum pan-genome is open and expanding, which indicates the possible addition of new gene families to the pan-genome. We also investigated the distribution of biosynthetic gene clusters (BGCs) among the strains. We discovered slight variations of BGCs at the strain level. Several BGCs with the potential to express novel bioactive secondary metabolites have been identified. Therefore, by utilizing the characteristic advantages of C. glutamicum, different strains can be potential applicants for natural drug discovery.

Isolation, Identification, Genomic Diversity, and Antimicrobial Resistance Analysis of Streptococcus suis in Hubei Province of China from 2021 to 2023.

Streptococcus suis (S. suis) is a zoonotic pathogen capable of causing severe diseases in humans and pigs, including meningitis, sepsis, polyserositis, arthritis, and endocarditis. This study aimed to investigate the biological characteristics of 19 strains of S. suis isolated from diseased pigs in Hubei Province between 2021 and 2023. Through bioinformatics analysis, we investigated the serotype, MLST, pan-genome characteristics, SNP, AMR, and ICE of the 19 S. suis isolates. Among the 19 S. suis strains, ten serotypes were identified, and serotype 9 was the most prevalent (21.05%). Ten new alleles and nine new sequence types (STs) were discovered, with ST28 and ST243 emerging as the predominant STs. The results of the pan-genomic analysis of S. suis indicate that there are 943 core genes, 2259 shell genes, and 5663 cloud genes. Through SNP evolutionary analysis, we identified a strong genetic similarity between SS31 and the reference genome P1/7. The analysis of antibiotic resistance genes revealed widespread presence of erm(B) and tet(O) genes among 19 strains of S. suis. This association may be linked to the high resistance of S. suis to lincosamides, macrolides, and tetracyclines. Integrative and conjugative elements (ICEs) and integrative and mobilizable elements (IMEs) were identified in 16 strains, with a carriage rate of 84.21%, and resistance genes were identified within the ICE/IME elements of 8 strains. Antimicrobial susceptibility testing revealed that all strains showed sensitivity to vancomycin and lincomycin but resistance to tilmicosin, tiamulin, amoxicillin, and doxycycline. This study contributes to our understanding of the genomic diversity of S. suis in Hubei Province of China, providing essential data for the comprehensive prevention and control of S. suis infections in China.

Analysis and benchmarking of small and large genomic variants across tandem repeats.

Tandem repeats (TRs) are highly polymorphic in the human genome, have thousands of associated molecular traits and are linked to over 60 disease phenotypes. However, they are often excluded from at-scale studies because of challenges with variant calling and representation, as well as a lack of a genome-wide standard. Here, to promote the development of TR methods, we created a catalog of TR regions and explored TR properties across 86 haplotype-resolved long-read human assemblies. We curated variants from the Genome in a Bottle (GIAB) HG002 individual to create a TR dataset to benchmark existing and future TR analysis methods. We also present an improved variant comparison method that handles variants greater than 4 bp in length and varying allelic representation. The 8.1% of the genome covered by the TR catalog holds ~24.9% of variants per individual, including 124,728 small and 17,988 large variants for the GIAB HG002 'truth-set' TR benchmark. We demonstrate the utility of this pipeline across short-read and long-read technologies.

PPanG: a precision pangenome browser enabling nucleotide-level analysis of genomic variations in individual genomes and their graph-based pangenome

Graph-based pangenome is gaining more popularity than linear pangenome because it stores more comprehensive information of variations. However, traditional linear genome browser has its own advantages, especially the tremendous resources accumulated historically. With the fast-growing number of individual genomes and their annotations available, the demand for a genome browser to visualize genome annotation for many individuals together with a graph-based pangenome is getting higher and higher. Here we report a new pangenome browser PPanG, a precise pangenome browser enabling nucleotide-level comparison of individual genome annotations together with a graph-based pangenome. Nine rice genomes with annotations were provided by default as potential references, and any individual genome can be selected as the reference. Our pangenome browser provides unprecedented insights on genome variations at different levels from base to gene, and reveals how the structures of a gene could differ for individuals. PPanG can be applied to any species with multiple individual genomes available and it is available at https://cgm.sjtu.edu.cn/PPanG.

Genomic Diversity and Recombination Analysis of the Spike Protein Gene from Selected Human Coronaviruses.

Human coronaviruses (HCoVs) are seriously associated with respiratory diseases in humans and animals. The first human pathogenic SARS-CoV emerged in 2002-2003. The second was MERS-CoV, reported from Jeddah, the Kingdom of Saudi Arabia, in 2012, and the third one was SARS-CoV-2, identified from Wuhan City, China, in late December 2019. The HCoV-Spike (S) gene has the highest mutation/insertion/deletion rate and has been the most utilized target for vaccine/antiviral development. In this manuscript, we discuss the genetic diversity, phylogenetic relationships, and recombination patterns of selected HCoVs with emphasis on the S protein gene of MERS-CoV and SARS-CoV-2 to elucidate the possible emergence of new variants/strains of coronavirus in the near future. The findings showed that MERS-CoV and SARS-CoV-2 have significant sequence identity with the selected HCoVs. The phylogenetic tree analysis formed a separate cluster for each HCoV. The recombination pattern analysis showed that the HCoV-NL63-Japan was a probable recombinant. The HCoV-NL63-USA was identified as a major parent while the HCoV-NL63-Netherland was identified as a minor parent. The recombination breakpoints start in the viral genome at the 142 nucleotide position and end at the 1082 nucleotide position with a 99% CI and Bonferroni-corrected p-value of 0.05. The findings of this study provide insightful information about HCoV-S gene diversity, recombination, and evolutionary patterns. Based on these data, it can be concluded that the possible emergence of new strains/variants of HCoV is imminent.

Identifying key inflammatory genes in psoriasis via weighted gene co-expression network analysis: Potential targets for therapy.

Psoriasis is a globally prevalent chronic inflammatory skin disease. This study aimed to scrutinize the hub genes related to inflammation and potential molecular mechanisms in psoriasis. Utilizing mRNA expression profiles from public datasets GSE13355, GSE78097, and GSE14905, we set up a comprehensive analysis. Initially, we selected differentially expressed genes (DEGs) from psoriasis and control samples in GSE13355, followed by calculating inflammatory indices using genomic set variation analysis (GSVA). Weighted gene co-expression network analysis (WGCNA) was then applied to link significant modules with the inflammatory index. This process helped us identify differentially expressed inflammation-related genes (DE-IRGs). A protein-protein interaction (PPI) network was established, with the molecular complex detection (MCODE) plug-in pinpointing six chemokine genes (CCR7, CCL2, CCL19, CXCL8, CXCL1, and CXCL2) as central hub genes. These genes demonstrated pronounced immunohistochemical staining in psoriatic tissues compared to normal skin. Notably, the CCR7 gene exhibited the highest potential for m6A modification sites. Furthermore, we constructed transcription factor-microRNA-mRNA networks, identifying 139 microRNAs and 52 transcription factors associated with the hub genes. For the LASSO logistic regression model, the area under the curve (AUC) in the training set was 1, and in the two validation cohorts GSE78097 and GSE14905 were 1 and 0.872, respectively. In conclusion, our study highlights six chemokine genes (CCR7, CCL2, CCL19, CXCL8, CXCL1, and CXCL2) as potential biomarkers in psoriasis, providing insights into the immune and inflammatory responses as pivotal instances in disease pathogenesis. These findings pave the way for exploring new therapeutic targets, particularly focusing on chemokine-associated pathways in psoriasis treatment.

Construction of RNA Methylation Modification-immune-related lncRNA Molecular Subtypes and Prognostic Scoring System in Lung Adenocarcinoma.

RNA methylation modification is not only intimately interrelated with cancer development and progression but also actively influences immune cell infiltration in the tumor microenvironment (TME). RNA methylation modification genes influence the therapeutic progression of lung adenocarcinoma (LUAD), and mining RNA methylation modification prognosis-related markers in LUAD is crucial for its precise prognosis. RNA-Seq data and Gene sets were collected from online databases or published literature. Genomic variation analysis was conducted by the Maftools package. RNA methylation-immune-related lncRNAs were obtained by Pearson correlation analysis. Then, Consistent clustering analysis was performed to obtain RNA methylation modification- immune molecular subtypes (RMM-I Molecular subtypes) in LUAD based on selected lncRNAs. COX and random survival forest analysis were carried out to construct the RMM-I Score. The receiver operating characteristic (ROC) curve and Kaplan Meier survival analysis were used to assess survival differences. Tumor immune microenvironment was assessed through related gene signatures and CIBERSORT algorithm. In addition, drug sensitivity analysis was executed by the pRRophetic package. Four RNA methylation modified-immune molecular subtypes (RMM-I1, RMM- I2, RMM-I3, RMM-I4) were presented in LUAD. Patients in RMM-I4 exhibited excellent survival advantages and immune activity. HAVCR2, CD274, and CTLA-4 expression were activated in RMM-I4, which might be heat tumors and a potential beneficial group for immunotherapy. OGFRP1, LINC01116, DLGAP1-AS2, CRNDE, LINC01137, MIR210HG, and CYP1B1-AS1 comprised the RMM-I Score. The RMM-I Score exhibited excellent accuracy in the prognostic assessment of LUAD, as patients with a low RMM- I Score exhibited remarkable survival advantage. Patients with a low RMM-I score might be more sensitive to treatment with Docetaxel, Vinorelbine, Paclitaxel, Cisplatin, and immunotherapy. The RMM-I molecular subtype constituted the novel molecular characteristic subtype of LUAD, which complemented the existing pathological typing. More refined and accurate molecular subtypes provide help to reveal the mechanism of LUAD development. In addition, the RMM-I score offers a reliable tool for accurate prognosis of LUAD.

A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats

The seventh iteration of the reference genome assembly for Rattus norvegicus-mRatBN7.2-corrects numerous misplaced segments and reduces base-level errors by approximately 9-fold and increases contiguity by 290-fold compared with its predecessor. Gene annotations are now more complete, improving the mapping precision of genomic, transcriptomic, and proteomics datasets. We jointly analyzed 163 short-read whole-genome sequencing datasets representing 120 laboratory rat strains and substrains using mRatBN7.2. We defined ∼20.0 million sequence variations, of which 18,700 are predicted to potentially impact the function of 6,677 genes. We also generated a new rat genetic map from 1,893 heterogeneous stock rats and annotated transcription start sites and alternative polyadenylation sites. The mRatBN7.2 assembly, along with the extensive analysis of genomic variations among rat strains, enhances our understanding of the rat genome, providing researchers with an expanded resource for studies involving rats.

Potential locus W and candidate gene McPRR2 associated with pericarp pigment accumulation in bitter gourd (Momordica charantia L.) revealed via BSA-seq analysis

Pericarp color is a prominent agronomic trait that exerts a significant impact on consumer and breeder preferences. Genetic analysis has revealed that the pericarp color of bitter gourd is a quantitative trait. However, the underlying mechanism for this trait in bitter gourd remains largely unknown. In the present study, we employed bulked segregant analysis (BSA) to identify the candidate genes responsible for bitter gourd pericarp color (specifically, dark green versus white) within F2 segregation populations resulting from the crossing of B07 (dark green pericarp) and A06 (white pericarp). Through genomic variation, genetic mapping, and expression analysis, we identified a candidate gene named McPRR2, which was a homolog of Arabidopsis pseudo response regulator 2 (APRR2) encoded by LOC111023472. Sequence alignment of the candidate gene between the two parental lines revealed a 15-bp nucleotide insertion in the coding region of LOC111023472, leading to a premature stop codon and potentially causing a loss-of-function mutation. qRT-PCR analysis demonstrated that the expression of McPRR2 was significantly higher in B07 compared to A06, and it was primarily expressed in the immature fruit pericarp. Moreover, overexpression of McPRR2 in tomato could enhance the green color of immature fruit pericarp by increasing the chlorophyll content. Consequently, McPRR2 emerged as a strong candidate gene regulating the bitter gourd pericarp color by influencing chlorophyll accumulation. Finally, we developed a molecular marker linked to pericarp color, enabling the identification of genotypes in breeding populations. These findings provided valuable insights into the genetic improvement of bitter gourd pericarp color.

46, XX disorder of sexual development associated with mixed germ cell tumor of the prostate: a rare case report

BackgroundExtragonadal germ cell tumors originating from the prostate are exceptionally rare. To the best of our knowledge, there have been no reported cases of mixed germ cell tumors in individuals with 46 XX disorder of sex development. In this study, we conducted a comprehensive analysis using whole genome sequencing to investigate the clinicopathological and molecular genetic characteristics of a submitted case, with the objective of elucidating its underlying pathogenesis.Case presentationA 40-year-old male patient was diagnosed with a combination of 46, XX disorder of sex development and a primary prostate mixed germ cell tumor with yolk sac tumor and teratoma components. Whole-genome sequencing revealed that the tumor cells had a high somatic mutational load. Analysis of genomic structural variations and copy number variants confirmed the patient's karyotype as 46, XX (SRY +). Additionally, the patient exhibited short stature, small bilateral testes, slightly enlarged breasts, elevated serum alpha-fetoprotein concentrations, elevated follicle-stimulating hormone and luteinizing hormone levels, and low testosterone levels.DiscussionA case of 46, XX disorder of sex development, along with a primary prostatic mixed germ cell tumor, was diagnosed. This diagnosis has contributed to advancing our understanding of the genetic and phenotypic profile of the disease and may provide some insights for its treatment.

Evidence of Zika Virus Reinfection by Genome Diversity and Antibody Response Analysis, Brazil.

We generated 238 Zika virus (ZIKV) genomes from 135 persons in Brazil who had samples collected over 1 year to evaluate virus persistence. Phylogenetic inference clustered the genomes together with previously reported ZIKV strains from northern Brazil, showing that ZIKV has been remained relatively stable over time. Temporal phylogenetic analysis revealed limited within-host diversity among most ZIKV-persistent infected associated samples. However, we detected unusual virus temporal diversity from >5 persons, uncovering the existence of divergent genomes within the same patient. All those patients showed an increase in neutralizing antibody levels, followed by a decline at the convalescent phase of ZIKV infection. Of interest, in 3 of those patients, titers of neutralizing antibodies increased again after 6 months of ZIKV infection, concomitantly with real-time reverse transcription PCR re-positivity, supporting ZIKV reinfection events. Altogether, our findings provide evidence for the existence of ZIKV reinfection events.

Key genes involved in nonalcoholic steatohepatitis improvement after bariatric surgery.

Nonalcoholic steatohepatitis (NASH) is the advanced stage of nonalcoholic fatty liver disease (NAFLD), one of the most prevalent chronic liver diseases. The effectiveness of bariatric surgery in treating NASH and preventing or even reversing liver fibrosis has been demonstrated in numerous clinical studies, but the underlying mechanisms and crucial variables remain unknown. Using the GSE135251 dataset, we examined the gene expression levels of NASH and healthy livers. Then, the differentially expressed genes (DEGs) of patients with NASH, at baseline and one year after bariatric surgery, were identified in GSE83452. We overlapped the hub genes performed by protein-protein interaction (PPI) networks and DEGs with different expression trends in both datasets to obtain key genes. Genomic enrichment analysis (GSEA) and genomic variation analysis (GSVA) were performed to search for signaling pathways of key genes. Meanwhile, key molecules that regulate the key genes are found through the construction of the ceRNA network. NASH mice were induced by a high-fat diet (HFD) and underwent sleeve gastrectomy (SG). We then cross-linked the DEGs in clinical and animal samples using quantitative polymerase chain reaction (qPCR) and validated the key genes. Seven key genes (FASN, SCD, CD68, HMGCS1, SQLE, CXCL10, IGF1) with different expression trends in GSE135251 and GSE83452 were obtained with the top 30 hub genes selected by PPI. The expression of seven key genes in mice after SG was validated by qPCR. Combined with the qPCR results from NASH mice, the four genes FASN, SCD, HMGCS1, and CXCL10 are consistent with the biological analysis. The GSEA results showed that the 'cholesterol homeostasis' pathway was enriched in the FASN, SCD, HMGCS1, and SQLE high-expression groups. The high-expression groups of CD68 and CXCL10 were extremely enriched in inflammation-related pathways. The construction of the ceRNA network obtained microRNAs and ceRNAs that can regulate seven key genes expression. In summary, this study contributes to our understanding of the mechanisms by which bariatric surgery improves NASH, and to the development of potential biomarkers for the treatment of NASH.

Significance of RNA Processing Factors in Prognosis and Treatment of Hepatocellular Carcinoma: Implications for Precision Medicine

Hepatocellular carcinoma (HCC) is a malignant tumor with heterogenous nature and high mortality worldwide. RNA processing has been implicated in tumorigenesis, progression, and prognosis to develop early diagnosis and targeted therapy for cancer, including HCC. This study aimed to identify and validate a novel RNA processing gene signature for predicting HCC prognosis. Transcriptome and clinical data of HCC samples were obtained from Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), Gene Expression Omnibus databases, and RNA processing factors from the AmiGO database. The least absolute shrinkage and selection operator and multivariate Cox regression analysis were performed to examine prognostic gene signatures. Correlation analysis of prognostic models with clinical features and HallMark pathway-based Genomic Variation Analysis enrichment analysis were performed. We identified seven distinguished RNA processing factors to build the prognostic model for HCC patients. ROC curve analysis of the TCGA-HCC, ICGC-HCC, and GSE76427 cohorts determined the ability to predict prognosis through a sevengene-based model (AUC > 0.7). A nomogram to forecast the overall survival among HCC patients was established. In addition, 7 cell types (CD3+ cells, CD8+ T cells, macrophage/monocyte, monocyte, myeloid dendritic cells, neutrophils and cancer-associated fibroblast) significantly differed between the two risk groups. Furthermore, enrichment analysis showed significant enrichment in fatty acid metabolism, lipogenesis, pancreatic beta cells, and bile acid metabolism in the low-risk group, while in the high-risk group, DNA repair, protein secretion, and mitotic pathways were significantly enriched. Analyzing the Tumor Immune Dysfunction and Exclusion results demonstrated that immune checkpoint blockade therapy was poorly efficacious in the high-risk group. This study constructed and validated a novel prognostic signature related to RNA processing factors in HCC, improving therapeutic strategies for HCC. Building such prognostic signatures could pave the way for developing targeted therapy and precision medicine in HCC.

Complete mitochondrial genome of the endangered Prunus pedunculata (Prunoideae, Rosaceae) in China: characterization and phylogenetic analysis.

Prunus pedunculata (Prunoideae: Rosaceae), a relic shrub with strong resistance and multiple application values, is endangered in China. Extensive research had been devoted to gene expression, molecular markers, plastid genome analysis, and genetic background investigations of P. pedunculata. However, the mitochondrial genome of this species has not been systematically described, owing to the complexity of the plant mitogenome. In the present research, the complete mitochondrial genome of P. pedunculata was assembled, annotated, and characterized. The genomic features, gene content and repetitive sequences were analyzed. The genomic variation and phylogenetic analysis have been extensively enumerated. The P. pedunculata mitogenome is a circular molecule with a total length of 405,855 bp and a GC content of 45.63%, which are the smallest size and highest GC content among the known Prunus mitochondrial genomes. The mitogenome of P. pedunculata encodes 62 genes, including 34 unique protein-coding genes (PCGs, excluding three possible pseudogenes), three ribosomal RNA genes, and 19 transfer RNA genes. The mitogenome is rich in repetitive sequences, counting 112 simple sequence repeats, 15 tandem repeats, and 50 interspersed repetitive sequences, with a total repeat length of 11,793 bp, accounting for 2.91% of the complete genome. Leucine (Leu) was a predominant amino acid in PCGs, with a frequency of 10.67%, whereas cysteine (Cys) and tryptophan (Trp) were the least adopted. The most frequently used codon was UUU (Phe), with a relative synonymous codon usage (RSCU) value of 1.12. Selective pressure was calculated based on 20 shared PCGs in the mitogenomes of the 32 species, most of which were subjected to purifying selection (Ka/Ks < 1), whereas ccmC and ccmFn underwent positive selection. A total of 262 potential RNA editing sites in 26 PCGs were identified. Furthermore, 56 chloroplast-derived fragments were ascertained in the mitogenome, ranging from 30 to 858 bp, and were mainly located across IGS (intergenic spacer) regions or rRNA genes. These findings verify the occurrence of intracellular gene transfer events from the chloroplast to the mitochondria. Furthermore, the phylogenetic relationship of P. pedunculata was supported by the mitogenome data of 30 other taxa of the Rosaceae family. Understanding the mitochondrial genome characteristics of P. pedunculata is of great importance to promote comprehension of its genetic background and this study provides a basis for the genetic breeding of Prunus.

Integrative multiomics profiling of passion fruit reveals the genetic basis for fruit color and aroma.

Passion fruit (Passiflora edulis) possesses a complex aroma and is widely grown in tropical and subtropical areas. Here, we conducted the de novo assembly, annotation, and comparison of PPF (P. edulis Sims) and YPF (P. edulis f. flavicarpa) reference genomes using PacBio, Illumina, and Hi-C technologies. Notably, we discovered evidence of recent whole-genome duplication events in P. edulis genomes. Comparative analysis revealed 7.6∼8.1 million single nucleotide polymorphisms, 1 million insertions/deletions, and over 142 Mb presence/absence variations among different P. edulis genomes. During the ripening of yellow passion fruit, metabolites related to flavor, aroma, and color were substantially accumulated or changed. Through joint analysis of genomic variations, differentially expressed genes, and accumulated metabolites, we explored candidate genes associated with flavor, aroma, and color distinctions. Flavonoid biosynthesis pathways, anthocyanin biosynthesis pathways, and related metabolites are pivotal factors affecting the coloration of passion fruit, and terpenoid metabolites accumulated more in PPF. Finally, by heterologous expression in yeast (Saccharomyces cerevisiae), we functionally characterized 12 terpene synthases. Our findings revealed that certain TPS homologs in both YPF and PPF varieties produce identical terpene products, while others yield distinct compounds or even lose their functionality. These discoveries revealed the genetic and metabolic basis of unique characteristics in aroma and flavor between the 2 passion fruit varieties. This study provides resources for better understanding the genome architecture and accelerating genetic improvement of passion fruits.

Comparative genomic analysis reveals niche adaption of Lactobacillus acidophilus.

Lactobacillus acidophilus has been extensively applied in plentiful probiotic products. Although several studies have been performed to investigate the beneficial characteristics and genome function of L. acidophilus, comparative genomic analysis remains scarce. In this study, we collected 74L. acidophilus genomes from our gut bacterial genome collection and the public database and conducted a comprehensive comparative genomic analysis. This study revealed the potential correlation of the genomic diversity and niche adaptation of L. acidophilus from different perspectives. The pan-genome of L. acidophilus was found to be open, with metabolism, information storage and processing genes mainly distributed in the core genome. Phage- and peptidase-associated genes were found in the genome of the specificity of animal-derived strains, which were related to adaptation of animal gut. SNP analysis showed the differences of the utilization of vitamin B12 in cellular of L. acidophilus strains from animal gut and others. This work provides new insights for the genomic diversity analysis of Lactobacillus acidophilus and uncovers the ecological adaptation of the specific strains.