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Increasing demands for food and energy require a step change in the effectiveness, speed and flexibility of crop breeding. Therefore, the aim of this study was to assess the potential of genome-wide association studies (GWASs) and genomic selection (i.e. phenotype prediction from a genome-wide set of markers) to guide fundamental plant science and to accelerate breeding in the energy grass Miscanthus. We generated over 100 000 single-nucleotide variants (SNVs) by sequencing restriction site-associated DNA (RAD) tags in 138 Micanthus sinensis genotypes, and related SNVs to phenotypic data for 17 traits measured in a field trial. Confounding by population structure and relatedness was severe in naïve GWAS analyses, but mixed-linear models robustly controlled for these effects and allowed us to detect multiple associations that reached genome-wide significance. Genome-wide prediction accuracies tended to be moderate to high (average of 0.57), but varied dramatically across traits. As expected, predictive abilities increased linearly with the size of the mapping population, but reached a plateau when the number of markers used for prediction exceeded 10 000–20 000, and tended to decline, but remain significant, when cross-validations were performed across subpopulations. Our results suggest that the immediate implementation of genomic selection in Miscanthus breeding programs may be feasible.

Glioblastoma, isocitrate dehydrogenase wildtype (GBM, IDH‐wt), is a highly aggressive brain tumor with a poor prognosis. Alterations in the fibroblast growth factor receptor (FGFR) gene family—such as FGFR::TACC fusions and FGFR1 mutations—have emerged as potential therapeutic targets; however, their clinical and genetic features in GBM, IDH‐wt remain unclear. We analyzed 1076 GBM, IDH‐wt cases using comprehensive genomic profiling data from the Center for Cancer Genomics and Advanced Therapeutics (C‐CAT) database in Japan. FGFR alterations were detected in 8.0% of patients, including FGFR::TACC fusions (3.3%) and FGFR1 mutations (2.9%). The FGFR::TACC fusion‐positive group was older at diagnosis and showed higher frequencies of TERT promoter mutation and MDM2 amplification, and lower frequencies of EGFR amplification and TP53 mutation, compared with the fusion‐negative group. The FGFR1 mutation‐positive group was enriched for ATRX, NF1, and PIK3CA mutations and had significantly fewer TERT promoter and PTEN mutations, compared with the mutation‐negative group. No significant differences in overall survival were observed, although both groups tended to have longer median overall survival compared with their respective negative groups. This study represents the largest genomic cohort to date of FGFR alterations in GBM, IDH‐wt. FGFR::TACC fusion‐positive and FGFR1 mutation‐positive GBMs exhibited distinct genetic profiles, highlighting the clinical relevance of molecular subclassification and providing insight for future therapeutic strategies. We analyzed 1076 cases of glioblastoma, IDH‐wildtype (GBM, IDH‐wt) using the C‐CAT genomic database to clarify the clinical and genetic features of FGFR alterations. FGFR::TACC fusions and FGFR1 mutations were identified in distinct subsets and were associated with unique co‐mutation patterns. These findings highlight the relevance of FGFR‐driven molecular subclassification in GBM and may inform future therapeutic strategies.

Circulating tumor DNA (ctDNA) is a biomarker that could potentially improve the survival rate of ovarian cancer (OC), e.g., by monitoring treatment response and early relapse detection. However, an optimal method for ctDNA analysis in OC remains to be established. We developed a method for tumor-informed single-nucleotide variant detection of ctDNA in OC using whole-genome sequencing. Tumor and plasma samples obtained at the time of diagnosis from 10 patients with OC were included. The tested method involved applying basic filters with different cut-offs of read depth, allelic depth, and variant allele frequency of tumor and normal DNA. In addition, we applied a new filtering approach using plasma samples from the other included OC patients (the plasma pool) for specific removal of artefacts. The basic filters with varying cut-offs showed minor improvement in signal-to-noise ratio (S2N). However, the addition of the plasma pool filter resulted in a considerable ctDNA signal improvement, indicated by both S2N and z-score. This study demonstrates a promising method for ctDNA detection in OC patients using a tumor-informed approach for whole-genome sequencing. Despite the limited number of patients involved, the results suggest a significant potential of the method for ctDNA signal detection in patients with OC.

Single nucleotide variant (SNV) has become an emerging biomarker for various diseases such as cancers and infectious diseases. Toehold‐mediated strand displacement (TMSD), the core reaction of DNA nanotechnology, has been widely leveraged to identify SNVs. However, inappropriate choice of mismatch location results in poor discrimination ability. Here, we comprehensively investigate the effect of mismatch location on TMSD kinetics by molecular dynamic simulation tool oxDNA through umbrella sampling and forward flux sampling disclosing that mismatches at the border of the toehold and branch migration domain yield the lowest TMSD reaction rate. Nine disease‐related SNVs (SARS‐CoV‐2‐D614G, EGFR‐L858R, EGFR‐T790M, KRAS‐G12R, etc.) were tested experimentally showing a good agreement with simulation. The best choice of mismatch location enables high discrimination factor with a median of 124 for SNV and wild type. Coupling with a probe‐sink system, a low variant allele frequency of 0.1% was detected with 3 S/N. We successfully used the probes to detect SNVs with high confidence in the PCR clones of constructed plasmids. This work provides mechanistic insights into TMSD process at the single‐nucleotide level and can be a guidance for the design of TMSD system with fine‐tuning kinetics for various applications in biosensors and nanotechnology. This work provides mechanistic insights into toehold‐mediated strand displacement process at the single‐nucleotide level through molecular dynamics simulation. Mismatches at the border of the toehold and branch migration domain yield the lowest reaction rate. Based on the simulation results, single nucleotide variants of disease‐related genes were detected with high specificity.

In the Asian general population, at least six single‐nucleotide variants (SNVs) in the UDP‐glucuronosyltransferase (UGT) 1A1 gene have been identified: −3279T>G, −53A(TA)6TAA>A(TA)7TAA, 211G>A, 686C>A, 1091C>T, and 1456T>G. Each of these six SNVs was observed in at least four ethnic groups of the 12 Asian populations studied. In East Asian populations, the descending frequency of these six SNVs was as follows: −3279G>[−53A(TA)7TAA, 211A]>(686A, 1091T)>1456G. Because of the presence of linkage disequilibrium and the expulsion phenomenon, when the SNVs −3279G, −53A(TA)7TAA, 211A, and 686A were simultaneously involved, 15 instead of the estimated 81 genotypes were observed. Those carrying 686AA or 1456GG developed Gilbert's syndrome or Crigler–Najjar syndrome type 2. Both −53A(TA)7TAA/A(TA)7TAA and 211AA are the main causes of Gilbert's syndrome in East Asian populations. In East Asian populations, the 211AA genotype is the main cause of neonatal hyperbilirubinemia, whereas −53A(TA)7TAA/A(TA)7TAA exerts a protective effect on hyperbilirubinemia development in neonates fed with breast milk. Both 211A and −53A(TA)7TAA are significantly associated with adverse drug reactions induced by irinotecan (one of the most widely used anticancer agents) in Asians. However, at least three common SNVs (−3279G, −53A(TA)7TAA, and 211A) should be comprehensively analyzed. This study investigated the clinical significance of these six SNVs and demonstrated that examining UGT1A1 variants in Asian populations is considerably challenging.

Accurate identification of single‐nucleotide variants (SNVs) is paramount for disease diagnosis. Despite the facile design of DNA hybridization probes, their limited specificity poses challenges in clinical applications. Here, a differential reaction pathway probe (DRPP) based on a dynamic DNA reaction network is presented. DRPP leverages differences in reaction intermediate concentrations between SNV and WT groups, directing them into distinct reaction pathways. This generates a strong pulse‐like signal for SNV and a weak unidirectional increase signal for wild‐type (WT). Through the application of machine learning to fluorescence kinetic data analysis, the classification of SNV and WT signals is automated with an accuracy of 99.6%, significantly exceeding the 80.7% accuracy of conventional methods. Additionally, sensitivity for variant allele frequency (VAF) is enhanced down to 0.1%, representing a ten‐fold improvement over conventional approaches. DRPP accurately identified D614G and N501Y SNVs in the S gene of SARS‐CoV‐2 variants in patient swab samples with accuracy over 99% (n = 82). It determined the VAF of ovarian cancer‐related mutations KRAS‐G12R, NRAS‐G12C, and BRAF‐V600E in both tissue and blood samples (n = 77), discriminating cancer patients and healthy individuals with significant difference (p < 0.001). The potential integration of DRPP into clinical diagnostics, along with rapid amplification techniques, holds promise for early disease diagnostics and personalized diagnostics. The differential reaction pathway probe is presented, which utilizes a dynamic DNA reaction network to separate single‐nucleotide variants (SNVs) and wild‐type (WT) into distinct reaction pathways, generating unique fingerprinting kinetics pulse‐like for SNVs and weak unidirectional signals for WT. High accuracy is achieved for SNV detection in clinical samples including SARS‐CoV‐2 patient swab samples and ovarian cancer patient tissue/blood samples.

The aim of this study was to use whole‐exome sequencing to derive a molecular classifier for nasopharyngeal carcinoma (NPC) and evaluate its clinical performance. We performed whole‐exome sequencing on 82 primary NPC tumors from Sun Yat‐sen University Cancer Center (Guangzhou cohort) to obtain somatic single‐nucleotide variants, indels, and copy number variants. A novel molecular classifier was then developed and validated in another NPC cohort (Hong Kong cohort, n = 99). Survival analysis was estimated by the Kaplan‐Meier method and compared using the log‐rank test. Cox proportional hazards model was adopted for univariate and multivariate analyses. We identified three prominent NPC genetic subtypes: RAS/PI3K/AKT (based on RAS, AKT1, and PIK3CA mutations), cell‐cycle (based on CDKN2A/CDKN2B deletions, and CDKN1B and CCND1 amplifications), and unclassified (based on dominant mutations in epigenetic regulators, such as KMT2C/2D, or the Notch signaling pathway, such as NOTCH1/2). These subtypes differed in survival analysis, with good, intermediate, and poor progression‐free survival in the unclassified, cell‐cycle, and RAS/PI3K/AKT subgroups, respectively, among the Guangzhou, Hong Kong, and combined cohorts (n = 82, P = 0.0342; n = 99, P = 0.0372; and n = 181, P = 0.0023; log‐rank test). We have uncovered genetic subtypes of NPC with distinct mutations and/or copy number changes, reflecting discrete paths of NPC tumorigenesis and providing a roadmap for developing new prognostic biomarkers and targeted therapies. We proposed three prominent NPC genetic subtypes: RAS/PI3K/AKT, cell‐cycle, and unclassified using the whole‐exome sequencing. Survival analysis indicated that there were statistically significant among patients with three subgroups. This result reflects the genetic alterations of NPC with distinct mutations and/or copy number changes and provides a roadmap for developing new prognostic biomarkers and targeted therapies.

Sub‐heading Compound hemizygous variants in SERPINA7 gene. Background Thyroxine‐binding globulin (TBG) is encoded by SERPINA7 (OMIM. 314200) which is located on Xq22.3. SERPINA7 variants caused TBG deficiency which does not require treatment, but the decreased thyroxine may be misdiagnosed as hypothyroidism. We discovered some variants of TBG caused by alterations that differ from previously reported. Materials and Methods In this study, we enrolled 32 subjects from 10 families and sequenced the SERPINA7 genes of TBG‐deficient subjects. Then, variants were analyzed to assess their effect on TBG expression and secretion. Bioinformatics database, protein structure, and dynamics simulation were used to evaluate the deleterious effects. Finally, we identified 2 novel and 4 known variants, and found 26 of 30 subjects carried the p.L303F. The DynaMut predictions indicated the variants (p.E91K, p.I92T, p.R294C, and p.L303F) exhibited decreased stability. Conclusion Analyses revealed the p.L303F change the protein stability and flexibility, and it had an impact on the function of TBG, but when coexisted with other variants it might change the conformational structure of the protein and aggravate the damage to the protein. We speculated that the existence of a higher number of variants resulted in lower TBG secretion. The p.L303F that previouly identified as a variant had an impact on the function and stability of TBG, and when coexisted with other variants it might change the conformational structure of the protein and aggravate the damage to the protein. The existence of a higher number of variants resulted in lower TBG secretion.

Single-nucleotide variants (SNVs) in segmental duplications (SDs) have not been systematically assessed because of the limitations of mapping short-read sequencing data 1 , 2 . Here we constructed 1:1 unambiguous alignments spanning high-identity SDs across 102 human haplotypes and compared the pattern of SNVs between unique and duplicated regions 3 , 4 . We find that human SNVs are elevated 60% in SDs compared to unique regions and estimate that at least 23% of this increase is due to interlocus gene conversion (IGC) with up to 4.3 megabase pairs of SD sequence converted on average per human haplotype. We develop a genome-wide map of IGC donors and acceptors, including 498 acceptor and 454 donor hotspots affecting the exons of about 800 protein-coding genes. These include 171 genes that have ‘relocated’ on average 1.61 megabase pairs in a subset of human haplotypes. Using a coalescent framework, we show that SD regions are slightly evolutionarily older when compared to unique sequences, probably owing to IGC. SNVs in SDs, however, show a distinct mutational spectrum: a 27.1% increase in transversions that convert cytosine to guanine or the reverse across all triplet contexts and a 7.6% reduction in the frequency of CpG-associated mutations when compared to unique DNA. We reason that these distinct mutational properties help to maintain an overall higher GC content of SD DNA compared to that of unique DNA, probably driven by GC-biased conversion between paralogous sequences 5 , 6 . A study comparing the pattern of single-nucleotide variation between unique and duplicated regions of the human genome shows that mutation rate and interlocus gene conversion are elevated in duplicated regions.

Early detection of rare mutations through liquid biopsy can provide real-time information related to cancer diagnosis, prognosis, and treatment outcomes. Cell-free DNA samples used in liquid biopsies contain single-nucleotide variants (SNVs) with a variant allele frequency (VAF) of approximately ≤1%. Droplet digital polymerase chain reaction (ddPCR) is considered the gold standard of sequencing using liquid samples, generating amplicons from samples containing mutations with 0.001–0.005% VAF; however, it requires expensive equipment and time-consuming protocols. Therefore, various PCR methods for discriminating SNVs have been developed; nonetheless, non-specific amplification cannot be avoided even in the absence of mutations, which hampers the accurate diagnosis of SNVs. In this study, we introduce single-nucleotide variant on–off discrimination–PCR (Soo-PCR), a highly accurate and practical method that uses a 3′-end tailing primer for the on–off discrimination of low-abundance mutant-type targets, including SNVs. Soo-PCR minimizes the chance of incorrect judgments owing to its high discriminating power. Cancer markers, such as KRAS G12D, EGFR L858R, and EGFR T790M mutations, containing 0.1% VAF, were clearly detected in under 2 h with a high reliability comparable with that of ddPCR. This new method serves as a practical approach to accurately detect and evaluate low-abundance mutations in a user-friendly manner.