Stiff extracellular matrix drives the differentiation of mesenchymal stem cells toward osteogenesis by the multiscale 3D genome reorganization.

Extracellular matrix (ECM) stiffness is a major driver of stem cell fate. However, the involvement of the three-dimensional (3D) genomic reorganization in response to ECM stiffness remains unclear. Here, we generated comprehensive 3D chromatin landscapes of mesenchymal stem cells (MSCs) exposed to various ECM stiffness. We found that there were more long-range chromatin interactions, but less compartment A in MSCs cultured on stiff ECM than those cultured on soft ECM. However, the switch from compartment B in MSCs cultured on soft ECM to compartment A in MSCs cultured on stiff ECM included genes encoding proteins primarily enriched in cytoskeleton organization. At the topologically associating domains (TADs) level, stiff ECM tends to have merged TADs on soft ECM. These merged TADs on stiff ECM include upregulated genes encoding proteins enriched in osteogenesis, such as SP1, ETS1, and DCHS1, which were validated by quantitative real-time polymerase chain reaction and found to be consistent with the increase of alkaline phosphatase staining. Knockdown of SP1 or ETS1 led to the downregulation of osteogenic marker genes, including COL1A1, RUNX2, ALP, and OCN in MSCs cultured on stiff ECM. Our study provides an important insight into the stiff ECM-mediated promotion of MSC differentiation towards osteogenesis, emphasizing the influence of mechanical cues on the reorganization of 3D genome architecture and stem cell fate.

Structural Maintenance of Chromosomes Complexes.

The Structural Maintenance of Chromosomes (SMC) protein complexes are DNA-binding molecular machines required to shape chromosomes into functional units and to safeguard the genome through cell division. These ring-shaped multi-subunit protein complexes, which are present in all kingdoms of life, achieve this by organizing chromosomes in three-dimensional space. Mechanistically, the SMC complexes hydrolyze ATP to either stably entrap DNA molecules within their lumen, or rapidly reel DNA into large loops, which allow them to link two stretches of DNA in cis or trans. In this chapter, the canonical structure of the SMC complexes is first introduced, followed by a description of the composition and general functions of the main types of eukaryotic and prokaryotic SMC complexes. Thereafter, the current model for how SMC complexes perform in vitro DNA loop extrusion is presented. Lastly, chromosome loop formation by SMC complexes is introduced, and how the DNA loop extrusion mechanism contributes to chromosome looping by SMC complexes in cells is discussed.

Three-Dimensional Simulation of Whole-Genome Structuring Through the Transition from Anaphase to Interphase.

In order to analyze the three-dimensional genome architecture, it is important to simulate how the genome is structured through the cell cycle progression. In this chapter, we present the usage of our computation codes for simulating how the human genome is formed as the cell transforms from anaphase to interphase. We do not use the global Hi-C data as an input into the genome simulation but represent all chromosomes as linear polymers annotated by the neighboring region contact index (NCI), which classifies the A/B type of each local chromatin region. The simulated mitotic chromosomes heterogeneously expand upon entry to the G1 phase, which induces phase separation of A and B chromatin regions, establishing chromosome territories, compartments, and lamina and nucleolus associations in the interphase nucleus. When the appropriate one-dimensional chromosomal annotation is possible, using the protocol of this chapter, one can quantitatively simulate the three-dimensional genome structure and dynamics of human cells of interest.

From MGUS to multiple myeloma: Unraveling the unknown of precursor states.

In the 1960s, through laboratory-based investigations of peripheral blood partnered with detailed clinical annotations, Dr. Waldenström described a condition he called "benign monoclonal gammopathy". These patients were asymptomatic with a detectable monoclonal protein, and did not meet imaging and laboratory criteria for multiple myeloma. In 1978, through observational retrospective review of medical records, Dr. Kyle observed that not all cases of monoclonal gammopathy were benign. He introduced the term monoclonal gammopathy of undetermined significance (MGUS) to describe a condition that may potentially progress to multiple myeloma (MM), highlighting clinical inability in predicting which patients might progress. In 1980, Drs. Kyle and Greipp described 6 cases which did not fit the definitions of MGUS or MM, and they remained asymptomatic after at least 5 years of follow-up; they were proposed to have smoldering multiple myeloma (SMM). Over time, SMM was defined by arbitrary numerical values (≥10 % plasma cells in the bone marrow and serum M-protein concentration ≥ 3 g/dL). Numerous clinical scores have been developed to define high-risk groups for progression to MM. Current statistical models for progression provide only average risk scores, offering limited clinical utility since the risk of progression at an individual level remains unknown. Physician-scientists are focusing on emerging technologies, such as whole genome sequencing, tumor microenvironment analysis, and single-cell RNA sequencing, to understand precursor states at a molecular level. The overarching goal of these technologies is to better characterize monoclonal gammopathy and other myeloma precursor states. This will enable clinicians to provide more precise, individualized risk assessments and ultimately improve patient outcomes. This review outlines the history of MM precursor states, current definitions, challenges in risk stratification models, and the role of emerging technologies in enhancing predictions and outcomes.

Clinical and genomic characterization of carbapenem-resistant Enterobacterales bloodstream infections in patients with hematologic malignancies.

Background: Carbapenem-resistant Enterobacterales (CRE) bloodstream infections (BSIs) pose a significant risk to patients with hematologic malignancies, yet the distinct features and outcomes of these infections are not thoroughly understood. Methods: This retrospective study examined the characteristics and clinical outcomes of patients with Enterobacterales BSIs at the Hematology Department of Fujian Medical University Union Hospital from 2018 to 2022. Whole-genome sequencing was conducted on 45 consecutive CRE BSI isolates during this period. Results: A total of 301 patients with Enterobacterales BSIs were included, with 65 (21.6%) cases of CRE and 236 (78.4%) cases of carbapenem-susceptible Enterobacterales (CSE). CRE infections accounted for 16.9% to 26.9% of all Enterobacterales BSIs, and carbapenem-resistant Klebsiella pneumoniae (CRKP) was the predominant strain. The most frequent sequence type (ST) and carbapenemase among CRKP were ST11 (68.6%) and blaKPC-2 (80.0%), respectively. Perianal infections, multiple infection foci, and a history of multiple hospitalizations, ICU stays, and prior CRE infections were identified as risk factors for CRE BSIs. Patients in the CRE group experienced significantly higher proportions of infection-related septic shock (43.1% vs. 19.9%, P < 0.0003) and 30-day all-cause mortality (56.9% vs. 24.6%, P < 0.0001) compared to those in the CSE group. Patient's age and disease subtypes, strain subtypes, and antimicrobial treatment regimens significantly influenced survival in patients with CRE BSIs. Conclusions: CRE BSIs are a frequent complication in patients with hematological malignancies undergoing treatment and are associated with poor survival rates. A comprehensive understanding of risk factors and ongoing surveillance of prevalent strains are essential for the effective management of these infections.

Prognostic value of PEA3 subfamily gene expression in cholangiocarcinoma.

BACKGROUND: Cholangiocarcinoma (CCA) is a lethal malignancy with limited treatment options and poor prognosis. The PEA3 subfamily of E26 transformation specific genes: ETV1, ETV4, and ETV5 are known to play significant roles in various cancers by influencing cell proliferation, invasion, and metastasis. AIM: To analyze PEA3 subfamily gene expression levels in CCA and their correlation with clinical parameters to determine their prognostic value for CCA. METHODS: The expression levels of PEA3 subfamily genes in pan-cancer and CCA data in the cancer genome atlas and genotype-tissue expression project databases were analyzed with R language software. Survival curve and receiver operating characteristic analyses were performed using the SurvMiner, Survival, and Procr language packages. The gene expression profiling interactive analysis 2.0 database was used to analyze the expression levels of PEA3 subfamily genes in different subtypes and stages of CCA. Web Gestalt was used to perform the gene ontology/ Kyoto encyclopedia of genes and genomes (GO/KEGG) analysis, and STRING database analysis was used to determine the genes and proteins related to PEA3 subfamily genes. RESULTS: ETV1, ETV4, and ETV5 expression levels were significantly increased in CCA. There were significant differences in ETV1, ETV4, and ETV5 expression levels among the different subtypes of CCA, and predictive analysis revealed that only high ETV1 and ETV4 expression levels were significantly associated with shorter overall survival in patients with CCA. GO/KEGG analysis revealed that PEA3 subfamily genes were closely related to transcriptional misregulation in cancer. In vitro and in vivo experiments revealed that PEA3 silencing inhibited the invasion and metastasis of CCA cells. CONCLUSION: The expression level of ETV4 may be a predictive biomarker of survival in patients with CCA.

Mutational Landscape of Gastric Adenocarcinoma of the Fundic Gland Type Revealed by Whole Genome Sequencing.

BACKGROUND: Gastric adenocarcinoma of the fundic gland type (GA-FG) is a newly described variant of gastric adenocarcinoma with lack of knowledges regarding its genetic features. METHODS: We performed whole-genome sequencing (WGS) in formalin-fixed paraffin-embedded (FFPE) tumor tissues and matched adjacent noncancerous specimens from 21 patients with GA-FG, and integrated published datasets from 1105 patients with traditional gastric adenocarcinoma with the purpose of dissecting genetic determinants both common to conventional gastric adenocarcinoma and unique to GA-FG disease. RESULTS: We characterized the genomic architecture of GA-FG disease, revealing the predominant proportion of C > T substitution among the six types of SNVs. GNAS was the most significantly mutated driver gene (14.29%). 42.8% of samples harbored "Kataegis." Distinct genomic alterations between GA-FG and conventional gastric cancer were identified. Specifically, low mutational burden and relatively moderate mutational frequencies of significantly mutated driver genes, coupled with the absence of non-silent alterations of formerly well-known drivers such as TP53, PIK3CA and KRAS were identified in GA-FG patients. Oncogenic signaling pathway analysis revealed mutational processes associated with focal adhesions and proteoglycans in cancer, highlighting both common and specific procedures during the development of GA-FG and conventional gastric cancer. CONCLUSION: Our study is the first to comprehensively depict the genomic landscape highlighting the multidimensional perturbations in GA-FG patients. These discoveries offered mechanistic insights for novel diagnostic and therapeutic strategies for patients with such disease.

Causal relationship between 150 skin microbiomes and prostate cancer: insights from bidirectional mendelian randomization and meta-analysis.

Background: Despite relevant research, the relationship between skin microbiomes and prostate cancer remains controversial. This study utilizes bidirectional Mendelian randomization (MR) analysis combined with meta-analysis to explore the potential link between the two. Objective: This study aims to identify the causal relationship between 150 skin microbiomes and prostate cancer (PCa) using bidirectional Mendelian randomization (MR) and meta-analysis. Methods: This study employed a comprehensive Bidirectional Two-sample MR analysis using publicly available genetic data to ascertain the relationship between 150 skin microbiomes and PCa. We conducted extensive sensitivity analyses, tests for heterogeneity, and assessments of horizontal pleiotropy to ensure the accuracy of our results. Subsequently, we conducted a meta-analysis to strengthen our conclusions' robustness further. Finally, we performed reverse causal verification on the positive skin microbiomes and PCa. Results: After conducting a meta-analysis and multiple corrections of the MR analysis results, our findings reveal a correlation between Neisseria in dry skin and PCa risk, identifying it as a risk factor. The IVW result shows an Odds Ratio (OR) of 1.009 (95% Confidence Interval [CI]: 1.004-1.014, P = 0.027). Furthermore, the reverse MR analysis indicates the absence of an inverse causal relationship between the two. Apart from the identified skin microbiome, no significant associations were found between the other microbiomes and PCa. Conclusions: The study identified a correlation between Neisseria in dry skin, one of the 150 skin microbiomes, and the risk of developing PCa, establishing it as a risk factor for increased susceptibility to PCa.

Causal effects of lipid-lowering drugs on skin diseases: a two-sample Mendelian randomization study.

Background: Although previous studies have indicated an association between low-density lipoprotein (LDL) and skin diseases, their causal effects remain inconclusive. This study aimed to assess the causal relationship between genetically proxied lipid-lowering drugs and skin cancers and psoriasis. Methods: Two-sample Mendelian randomization (MR) analysis was performed using single-nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS). The inverse-variance weighted (IVW) method was used to determine causal relationships. The "leave-one-out" sensitivity test, Cochran's Q-statistic and MR-Egger intercept were used to assess heterogeneity and horizontal pleiotropy. Results: We identified 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) and proprotein convertase subtilisin-kexin type 9 (PCSK9) as genetically proxied lipid-lowering drugs. Genetically proxied inhibition of HMGCR (stains) was causally associated with reduced risk of nonmelanoma skin cancer (OR 0.982, 95% CI 0.967-0.997, p = 0.016 by weighted median; OR 0.977, 95% CI 0.966-0.989, p < 0.001 by IVW) and psoriasis (OR 0.585, 95% CI 0.378-0.905, p = 0.016 by IVW), while PCSK9 inhibition (alirocumab) was causally associated with reduced risk of psoriasis (OR 0.560, 95% CI 0.413-0.761 by weighted median; OR 0.564, 95% CI 0.447-0.712 by IVW; p < 0.001) in the ieu-b-5089 dataset. Similar results were observed in the ieu-b-110 dataset for HMGCR and PCSK9. Sensitivity analysis revealed no evidence of heterogeneity or horizontal pleiotropy. Conclusion: This study revealed the existing HMGCR inhibitors (stains) might be protective for reducing nonmelanoma skin cancer risk, and HMGCR inhibitors (stains) and PCSK9 inhibitor (alirocumab) might be promising for reducing psoriasis risk in the European population.

Topological stress triggers persistent DNA lesions in ribosomal DNA with ensuing formation of PML-nucleolar compartment.

PML, a multifunctional protein, is crucial for forming PML-nuclear bodies involved in stress responses. Under specific conditions, PML associates with nucleolar caps formed after RNA polymerase I (RNAPI) inhibition, leading to PML-nucleolar associations (PNAs). This study investigates PNAs-inducing stimuli by exposing cells to various genotoxic stresses. We found that the most potent inducers of PNAs introduced topological stress and inhibited RNAPI. Doxorubicin, the most effective compound, induced double-strand breaks (DSBs) in the rDNA locus. PNAs co-localized with damaged rDNA, segregating it from active nucleoli. Cleaving the rDNA locus with I-PpoI confirmed rDNA damage as a genuine stimulus for PNAs. Inhibition of ATM, ATR kinases, and RAD51 reduced I-PpoI-induced PNAs, highlighting the importance of ATM/ATR-dependent nucleolar cap formation and homologous recombination (HR) in their triggering. I-PpoI-induced PNAs co-localized with rDNA DSBs positive for RPA32-pS33 but deficient in RAD51, indicating resected DNA unable to complete HR repair. Our findings suggest that PNAs form in response to persistent rDNA damage within the nucleolar cap, highlighting the interplay between PML/PNAs and rDNA alterations due to topological stress, RNAPI inhibition, and rDNA DSBs destined for HR. Cells with persistent PNAs undergo senescence, suggesting PNAs help avoid rDNA instability, with implications for tumorigenesis and aging.

Efficiency of Non-Invasive Prenatal Testing in Detecting Fetal Copy Number Variation: A Retrospective Cohort Study.

Purpose: Screening of pathological copy number variations (CNVs) is important for early-diagnosis of hereditary disease. This study was designed to investigate the efficiency of non-invasive prenatal testing (NIPT) in detecting fetal CNVs. Methods: This retrospective analysis included fetuses with CNVs between January 2018 and December 2020. Karyotype analysis and CNV sequencing (CNV-seq) were performed. We then analyzed the positive predictive values of the subchromosomal microdeletions and microduplications. Results: Fifty-eight subjects with aberrant CNVs were screened after NIPT, among which 44 finally underwent amniocentesis. CNV-seq confirmed the presence of CNVs in 24 cases. This indicated that false positivity rate of NIPT was 45.5%. Among 24 cases with CNVs after CNV-seq, only 4 showed consistent findings with karyotype analysis, which showed that karyotyping analysis yielded a missed diagnosis rate of 83.3% for the genome CNV. Positive predictive value (PPV) was 50.0% for CNVs with a length of <5 Mb after NIPT screening. PPV for CNVs with a length of 5 Mb-10 Mb was 33.3%, while that for CNVs with a length of ≥10Mb was 60%. For CNVs duplication after NIPT, the PPV was 65.2%, while that for deletion was 36.4%. Conclusion: For CNVs detected after NIPT, it should be combined with ultrasonographic findings, karyotype analysis, CNV-seq or CMA to determine the pregnancy outcome. Expanding NIPT may increase the risk of unnecessary invasive surgery and unintended selective termination of pregnancy.

Chromosome-level genome assembly of the sacoglossan sea slug Elysia timida (Risso, 1818).

BACKGROUND: Sequencing and annotating genomes of non-model organisms helps to understand genome architecture, the genetic processes underlying species traits, and how these genes have evolved in closely-related taxa, among many other biological processes. However, many metazoan groups, such as the extremely diverse molluscs, are still underrepresented in the number of sequenced and annotated genomes. Although sequencing techniques have recently improved in quality and quantity, molluscs are still neglected due to difficulties in applying standardized protocols for obtaining genomic data. RESULTS: In this study, we present the chromosome-level genome assembly and annotation of the sacoglossan sea slug species Elysia timida, known for its ability to store the chloroplasts of its food algae. In particular, by optimizing the long-read and chromosome conformation capture library preparations, the genome assembly was performed using PacBio HiFi and Arima HiC data. The scaffold and contig N50s, at 41.8 Mb and 1.92 Mb, respectively, are approximately 30-fold and fourfold higher compared to other published sacoglossan genome assemblies. Structural annotation resulted in 19,904 protein-coding genes, which are more contiguous and complete compared to publicly available annotations of Sacoglossa with respect to metazoan BUSCOs. We found no evidence for horizontal gene transfer (HGT), i.e. no photosynthetic genes encoded in the sacoglossan nucleus genome. However, we detected genes encoding polyketide synthases in E. timida, indicating that polypropionates are produced. HPLC-MS/MS analysis confirmed the presence of a large number of polypropionates, including known and yet uncharacterised compounds. CONCLUSIONS: We can show that our methodological approach helps to obtain a high-quality genome assembly even for a "difficult-to-sequence" organism, which may facilitate genome sequencing in molluscs. This will enable a better understanding of complex biological processes in molluscs, such as functional kleptoplasty in Sacoglossa, by significantly improving the quality of genome assemblies and annotations.

Assessing the causal relationship between non-small cell lung cancer and sepsis: a Mendelian randomization study.

BACKGROUND: A Two-sample Mendelian randomization (MR) Analysis was used to assess the causal relationship between non-small cell lung cancer (NSCLC) and sepsis. METHOD: Single nucleotide polymorphisms (SNPs) closely associated with NSCLC were utilized as instrumental variables (IVs) in this study. The Inverse Variance Weighted (IVW) method was used as the primary method for MR analysis, supplemented by the Weighted median, Weighted model, and MR-Egger regression method. Sensitivity analysis was conducted to improve result robustness, and data from various sources were validated and integrated. Bonferroni tests were applied to adjust for multiple comparisons. RESULTS: After Bonferroni tests correcting the combined results, MR analysis revealed a significant association between genetically predicted NSCLC and an increased susceptibility to sepsis (odds ratios [OR]: 1.140, 95% confidence interval [CI]: 1.085-1.199, P = 2.61 × 10- 7). The combined results demonstrated that NSCLC is associated with a heightened risk of sepsis in patients under 75 years of age (OR: 1.085, 95%CI: 1.037-1.353, P = 3.84 × 10- 4). Furthermore, lung adenocarcinoma (LUAD) was found to be potentially associated with an increased susceptibility to sepsis (OR: 1.040, 95% CI: 1.009-1.073, P = 1.16 × 10- 2). These results withstood multiple sensitivity analyses, demonstrating their robustness. CONCLUSION: This study confirms that NSCLC can significantly increase susceptibility to sepsis at the genetic level, providing valuable insights for the early identification of individuals at risk for sepsis.

A clinically feasible algorithm for the parallel detection of glioma-associated copy number variation markers based on shallow whole genome sequencing.

Molecular features are incorporated into the integrated diagnostic system for adult diffuse gliomas. Of these, copy number variation (CNV) markers, including both arm-level (1p/19q codeletion, +7/-10 signature) and gene-level (EGFR gene amplification, CDKN2A/B homozygous deletion) changes, have revolutionized the diagnostic paradigm by updating the subtyping and grading schemes. Shallow whole genome sequencing (sWGS) has been widely used for CNV detection due to its cost-effectiveness and versatility. However, the parallel detection of glioma-associated CNV markers using sWGS has not been optimized in a clinical setting. Herein, we established a model-based approach to classify the CNV status of glioma-associated diagnostic markers with a single test. To enhance its clinical utility, we carried out hypothesis testing model-based analysis through the estimation of copy ratio fluctuation level, which was implemented individually and independently and, thus, avoided the necessity for normal controls. Besides, the customization of required minimal tumor fraction (TF) was evaluated and recommended for each glioma-associated marker to ensure robust classification. As a result, with 1× sequencing depth and 0.05 TF, arm-level CNVs could be reliably detected with at least 99.5% sensitivity and specificity. For EGFR gene amplification and CDKN2A/B homozygous deletion, the corresponding TF limits were 0.15 and 0.45 to ensure the evaluation metrics were both higher than 97%. Furthermore, we applied the algorithm to an independent glioma cohort and observed the expected sample distribution and prognostic stratification patterns. In conclusion, we provide a clinically applicable algorithm to classify the CNV status of glioma-associated markers in parallel.

The Prospective role of lapatinib as an adjuvant therapy in prevalent cancers: Insights from in silico analysis targeting EGFR and HER2.

INTRODUCTION: Various pieces of evidence suggest an elevation in the levels of EGFR and HER2 in different cancers leading to the proliferation, invasion, and metastasis of cancer cells. In this study, we conducted a comprehensive investigation into the expression alterations of these two receptors in various cancers using in silico data. In addition, we investigated the therapeutic potential of lapatinib as an inhibitor of these receptors in various cancer types. METHODS: RNAseq data for prevalent cancers were downloaded from The Cancer Genome Atlas (TCGA). After initial preprocessing, expression changes of HER2, EGFR, and candidate genes-identified based on their association with EGFR and HER2 signaling pathways-were examined. Human protein atlas data were utilized to assess the protein expression of HER2 and EGFR. GSE129254 was employed to identify molecular pathways and candidate genes associated with lapatinib. The protein-protein interaction network was used to identify lapatinib-influenced hub genes. Clinical data for common cancers were used to investigate the correlation between the expression of candidate genes and patients' mortality rates by Cox regression test. RESULTS: The findings clearly indicated a significant increase in the expression levels of HER2 and EGFR in cancers such as kidney, lung, breast, bladder, pancreas, head and neck, stomach, and endometrial, both at the mRNA and protein levels (p-value <0.01). Additionally, more than 30 % of samples in some cancers showed a twofold increase in HER2 or EGFR expression. The analysis of GSE129254 data revealed that lapatinib reduces the expression of numerous genes associated with cell proliferation. METTL1, LYAR, LTV1, CCND1, NOP2, and DDX21 were identified as hub genes related to the effect of lapatinib. Our results demonstrated that many hub genes exhibited elevated expression in candidate cancers, and the upregulation of some of them was correlated with poor prognosis. CONCLUSION: Our results indicate an upregulation in the expression levels of HER2 and EGFR in certain common cancers, suggesting that lapatinib, in addition to breast cancer, could be considered for the treatment of these cancers. Furthermore, we demonstrated that some genes with increased expression in prevalent cancers and associated with poor prognosis have the potential to be modulated by lapatinib.

Enhancing Variant Calling in Whole-Exome Sequencing Data Using Population-Matched Reference Genomes.

Whole-exome sequencing (WES) data are frequently used for cancer diagnosis and genome-wide association studies (GWAS), based on high-coverage read mapping, informative variant calling, and high-quality reference genomes. The center position of the currently used genome assembly, GRCh38, is now challenged by two newly published telomere-to-telomere (T2T) genomes, T2T-CHM13 and T2T-YAO, and it becomes urgent to have a comparative study to test population specificity using the three reference genomes based on real case WES data. Here we report our analysis along this line for 19 tumor samples collected from Chinese patients. The primary comparison of the exon regions among the three references reveals that the sequences in up to ∼ 1% target regions in T2T-YAO are widely diversified from GRCh38 and may lead to off-target in sequence capture. However, T2T-YAO still outperforms GRCh38 genomes by obtaining 7.41% more mapped reads. Due to more reliable read-mapping and closer phylogenetic relationship with the samples than GRCh38, T2T-YAO reduces half of variant calls of clinical significance which are mostly benign, while maintaining sensitivity in identifying pathogenic variants. T2T-YAO also outperforms T2T-CHM13 in reducing calls of Chinese-specific variants. Our findings highlight the critical need for employing population-specific reference genomes in genomic analysis to ensure accurate variant analysis and the significant benefits of tailoring these approaches to the unique genetic backgrounds of each ethnic group.

Identification of 10 differentially expressed genes involved in the tumorigenesis of cervical cancer via next-generation sequencing.

Background: The incidence and mortality of cervical cancer remain high in female malignant tumors worldwide. There is still a lack of diagnostic and prognostic markers for cervical carcinoma. This study aimed to screen differentially expressed genes (DEGs) between normal and cervical cancer tissues to identify candidate genes for further research. Methods: Uterine cervical specimens were resected from our clinical patients after radical hysterectomy. Three patients' transcriptomic datasets were built by the next generation sequencing (NGS) results. DEGs were selected through the edgeR and DESeq2 packages in the R environment. Functional enrichment analysis, including GO/DisGeNET/KEGG/Reactome enrichment analysis, was performed. Normal and cervical cancer tissue data from the public databases TCGA and GTEx were collected to compare the expression levels of 10 selected DEGs in tumor and normal tissues. ROC curve and survival analysis were performed to compare the diagnostic and prognostic values of each gene. The expression levels of candidate genes were verified in 15 paired clinical specimens via quantitative real-time polymerase chain reaction. Results: There were 875 up-regulated and 1,482 down-regulated genes in cervical cancer samples compared with the paired adjacent normal cervical tissues according to the NGS analysis. The top 10 DEGs included APOD, MASP1, ACKR1, C1QTNF7, SFRP4, HSPB6, GSTM5, IGFBP6, F10 and DCN. GO, DisGeNET and Reactome analyses revealed that the DEGs were related to extracellular matrix and angiogenesis which might influence tumorigenesis. KEGG enrichment showed that PI3K-Akt signaling pathway might be involved in cervical cancer tumorigenesis and progression. The expression levels of selected genes were decreased in tumors in both the public database and our experimental clinical specimens. All the candidate genes showed excellent diagnostic value, and the AUC values exceeded 0.90. Additionally, APOD, ACKR1 and SFRP4 expression levels could help predict the prognosis of patients with cervical cancer. Conclusions: In this study, we selected the top 10 DEGs which were down-regulated in cervical cancer tissues. All of them had dramatically diagnostic value. APOD, ACKR1 and SFRP4 were associated with the survivals of cervical cancer. C1QTNF7, HSPB6, GSTM5, IGFBP6 and F10 were first reported to be candidate genes of cervical carcinoma.

Extensive transcriptome data providing great efficacy in genetic research and adaptive gene discovery: a case study of Elymus sibiricus L. (Poaceae, Triticeae).

Genetic markers play a central role in understanding genetic diversity, speciation, evolutionary processes, and how species respond to environmental stresses. However, conventional molecular markers are less effective when studying polyploid species with large genomes. In this study, we compared gene expression levels in 101 accessions of Elymus sibiricus, a widely distributed allotetraploid forage species across the Eurasian continent. A total of 20,273 high quality transcriptomic SNPs were identified. In addition, 72,344 evolutionary information loci of these accessions of E. sibiricus were identified using genome skimming data in conjunction with the assembled composite genome. The population structure results suggest that transcriptome SNPs were more effective than SNPs derived from genome skimming data in revealing the population structure of E. sibiricus from different locations, and also outperformed gene expression levels. Compared with transcriptome SNPs, the investigation of population-specifically-expressed genes (PSEGs) using expression levels revealed a larger number of locally adapted genes mainly involved in the ion response process in the Sichuan, Inner Mongolia, and Xizang geographical groups. Furthermore, we performed the weighted gene co-expression network analysis (WGCNA) and successfully identified potential regulators of PSEGs. Therefore, for species lacking genomic information, the use of transcriptome SNPs is an efficient approach to perform population structure analysis. In addition, analyzing genes under selection through nucleotide diversity and genetic differentiation index analysis based on transcriptome SNPs, and exploring PSEG through expression levels is an effective method for analyzing locally adaptive genes.

Genomic characterization and clinical evaluation of prosthetic joint infections caused by Cutibacterium acnes.

Cutibacterium acnes is a major skin commensal that may act as an opportunistic pathogen. It is difficult to interpret findings of C. acnes in tissue cultures obtained during arthroplasty revision surgery, since they may represent true infection or contamination. This study investigated whether C. acnes obtained from prosthetic joint infections (PJIs) were related and shared common genomic traits that might correlate with clinical courses and patient outcomes. C. acnes isolates from revision surgery of patients with PJIs of the hip, shoulder, and knee were characterized using molecular methods to determine the sequence type (ST) and the presence of possible virulence determinants (Christie-Atkins-Munch-Peterson factors, dermatan sulfate-binding adhesion 1, hyaluronidase lyase, and linear plasmid). A standardized review of the patients' medical charts was performed. The study included 37 patients with C. acnes culture-positive tissue samples where multiple isolates of C. acnes belonged to the same ST. Most of the isolates belonged to phylotype IA1. Phylogenetic analysis of virulence determinants revealed no shared pattern among PJI isolates. Seven patients had a polymicrobial infection. Exchange revision was performed in 70% of the patients, and >50% of all patients received antibiotic treatment for ≥3 months. Failure was noted in seven patients. No specific ST or any identifiable unique feature among virulence determinants were found among C. acnes isolated from PJIs of hips and shoulders. The majority of patients had low inflammatory markers and were treated successfully, even polymicrobial infections. However, failure was more common among shoulder infections compared with hip infections. IMPORTANCE: Prosthetic joint infection (PJI) is a rare complication after arthroplasty surgery. The infection seldom resolves without a combination of both surgical and antibiotic treatment and can cause significant suffering among affected patients. Cutibacterium acnes is a common skin bacterium that is most often found in shoulder PJIs but can also infect other prostheses. In this study, we conducted a review of patients with previously verified PJIs involving C. acnes in hip or shoulder prostheses, along with a genomic analysis of the bacteria causing the infections. The majority of patients had successful outcomes. We did not identify any specific phylogenetic lineage or specific molecular signature of virulence factors among these PJI-associated C. acnes isolates that seemed to be associated with increased potential to cause infection among this species. This indicates that C. acnes isolated from PJIs originates from the patients' own skin microbiome and is inoculated during the arthroplasty surgery.

FANCD2 genome binding is nonrandom and is enriched at large transcriptionally active neural genes prone to copy number variation.

Fanconi anemia (FA) is a rare genetic disease characterized by congenital abnormalities and increased risk for bone marrow failure and cancer. Central nervous system defects, including acute and irreversible loss of neurological function and white matter lesions with calcifications, have become increasingly recognized among FA patients, and are collectively referred to as Fanconi Anemia Neurological Syndrome or FANS. The molecular etiology of FANS is poorly understood. In this study, we have used a functional integrative genomics approach to further define the function of the FANCD2 protein and FA pathway. Combined analysis of new and existing FANCD2 ChIP-seq datasets demonstrates that FANCD2 binds nonrandomly throughout the genome with binding enriched at transcription start sites and in broad regions spanning protein-coding gene bodies. FANCD2 demonstrates a strong preference for large neural genes involved in neuronal differentiation, synapse function, and cell adhesion, with many of these genes implicated in neurodevelopmental and neuropsychiatric disorders. Furthermore, FANCD2 binds to regions of the genome that replicate late, undergo mitotic DNA synthesis (MiDAS) under conditions of replication stress, and are hotspots for copy number variation. Our analysis describes an important targeted role for FANCD2 and the FA pathway in the maintenance of large neural gene stability.