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Abstract Many wild‐relative species are being used in prebreeding programs to increase the genetic diversity of wheat (Triticum aestivum L.). Genotyping tools such as single nucleotide polymorphism (SNP)‐based arrays and molecular markers have been widely used to characterize wheat–wild relative introgression lines. However, due to the polyploid nature of the recipient wheat genome, it is difficult to develop SNP‐based Kompetitive allele‐specific polymerase chain reaction (KASP) markers that are codominant to track the introgressions from the wild species. Previous attempts to develop KASP markers have involved both exome‐ and polymerase chain reaction (PCR)‐amplicon‐based sequencing of the wild species. But chromosome‐specific KASP assays have been hindered by homoeologous SNPs within the wheat genome. This study involved whole genome sequencing of the diploid wheat wild relative Amblyopyrum muticum (Boiss.) Eig and development of a de novo SNP discovery pipeline that generated ∼38,000 SNPs in unique wheat genome sequences. New assays were designed to increase the density of Am. muticum polymorphic KASP markers. With a goal of one marker per 60 Mbp, 335 new KASP assays were validated as diagnostic for Am. muticum in a wheat background. Together with assays validated in previous studies, 498 well distributed chromosome‐specific markers were used to recharacterize previously genotyped wheat–Am. muticum doubled haploid (DH) introgression lines. The chromosome‐specific nature of the KASP markers allowed clarification of which wheat chromosomes were involved with recombination events or substituted with Am. muticum chromosomes and the higher density of markers allowed detection of new small introgressions in these DH lines.

Abstract Purpose To identify how Epstein‐Barr virus (EBV) status combined with molecular profiling predicts the prognosis of gastric cancer patients and their associated clinical actionable biomarkers. Experimental Design A next‐generation sequencing assay targeting 295 cancer‐related genes was performed in 73 EBV‐associated gastric cancer (EBVaGC) and 75 EBV‐negative gastric cancer (EBVnGC) specimens and these results were compared with overall survival (OS). Results PIK3CA, ARID1A, SMAD4, and PIK3R1 mutated significantly more frequently in EBVaGC compared with their corresponding mutation rate in EBVnGC. As the most frequently mutated gene in EBVnGC (62.7%), TP53 also displayed a mutation rate of 15.1% in EBVaGC. PIK3R1 was revealed as a novel mutated gene (11.0%) associated almost exclusively with EBVaGC. PIK3CA, SMAD4, PIK3R1, and BCOR were revealed to be unique driver genes in EBVaGC. ARID1A displayed a significantly large proportion of inactivated variants in EBVaGC. A notable finding was that integrating the EBV status with tumor mutation burden (TMB) and large genomic instability (LGI) categorized the tumors into four distinct molecular subtypes and optimally predicted patient prognosis. The corresponding median OSs for the EBV+/TMB‐high, EBV+/TMB‐low, EBV‐/LGI‐, and EBV‐/LGI+ subtypes were 96.2, 75.3, 44.4, and 20.2 months, respectively. The different subtypes were significantly segregated according to distinct mutational profiles and pathways. Conclusions Novel mutations in PIK3R1 and TP53 genes, driver genes such as PIK3CA, SMAD4, PIK3R1, BCOR, and ARID1A, and distinguished genomic profiles from EBVnGC were identified in EBVaGC tumors. The classification of gastric cancer by EBV, TMB, and LGI could be a good prognostic indicator, and provides distinguishing, targetable markers for treatment.

Abstract Background Gene mutations may play an important role in the development, response to treatment and prognosis of colorectal cancer (CRC). This retrospective study aimed to investigate the mutation profiling of Chinese patients with CRC, and its correlation with clinicopathological features and prognosis. Methods This study included 1190 Chinese CRC patients who were diagnosed between May 1998 and December 2018 and received clinical genetic testing. The OncoCarta Panel was used to test a total of 238 possible mutations in 19 common oncogenes. Results Five hundred and eighty‐two (48.9%) cases were detected with gene mutations. Of the 582 cases, there were 111 cases (19.7%) with two concurrent mutations, and six cases (1.0%) with three concurrent mutations. KRAS was the most common gene mutation that occurred in all cases (429, 36.1%), followed by PIK3CA (121, 10.2%), NRAS (47, 3.9%), BRAF (35, 2.9%), HRAS (11, 0.9%) and epidermal growth factor receptor (EGFR) (11, 0.9%). AKT1, KIT, FGFR1, FGFR3, FLT3, CDK, ERBB2, ABL1, MET, RET and PDGFRA mutations were also detected in several cases. When it came to prognosis, we found that KRAS/NRAS/PIK3CA/BRAF mutation was not associated with prognosis. But BRAF mutation was associated with poor prognosis in patients who accepted anti‐EGFR therapy. Conclusions The molecular testing offered the clinical data and mutation profile of Chinese CRC patients. The information of these mutated genes may help to find out the correlation between mutated genes and the development or prognosis of CRC.

Objective: To explore genes potentially co-expressed with cyclin E in gastric cancer and discover possible targets for gastric cancer treatment. Methods: The Cancer Genome Atlas (TCGA) stomach adenocarcinoma sequencing data were used to predict genes co-expressed with cyclin E. Co-expression genes predicted by cBioPortal online analysis with Pearson correlation coefficient ≥0.4 were analyzed by gene ontology (GO) enrichment annotation using the PANTHER online platform (Ver. 7). Interactions between proteins encoded by these genes were analyzed using the STRING online platform (Ver. 10.5) and Cytoscape software (Ver. 3.5.1). Genes displaying a high degree of connection were analyzed by transcription factor enrichment prediction using FunRich software (Ver. 3). The significant transcription factor and cyclin E expression levels and their impact on gastric cancer progression were analyzed by Western blotting and Kaplan–Meier survival curve analysis. Results: After filtering the co-expression gene prediction results, 78 predicted genes that included 73 protein coding genes and 5 non-coding genes with Pearson correlation coefficient ≥0.4 were selected. The expressions of the genes were considered to be correlated with cyclin E expression. Among the 78 genes co-expressed with cyclin E, 19 genes at the central of the regulatory network associated with cyclin E were discovered. Nuclear transcription factor Y subunit alpha (NF-YA) was identified as a significant transcription factor associated with cyclin E co-expressing genes. Analysis of specimen donors’ clinical records revealed that high expression of NF-YA tended to be associated with increased cyclin E expression. The expression of both was associated with progression of gastric cancer. Western blotting results showed that compared with normal tissues, NF-YA and cyclin E were highly expressed in tumor tissues (P

Krüppel‐like factor 4 (KLF4) functions as either a tumor suppressor or an oncogene in different tissues by regulating the expression of various genes. The aim of this study was to reveal the functions of KLF4 in regulating breast cancer apoptosis, proliferation, and tumorigenic progression. KLF4 expression levels in breast cancer tissues and breast cancer cell lines were found to be much lower than those in nontumorous tissues and a nontransformed mammary epithelial cell line. KLF4 was upregulated in the tumor necrosis factor‐α–induced SK‐BR‐3 breast cancer cell apoptotic process. Overexpression of KLF4 promoted SK‐BR‐3 breast cancer cell apoptosis and suppressed SK‐BR‐3 cell tumorigenicityin vivo.

Adaptation is a characteristic that enhances the survival or reproduction of organisms; selection is the critical process leading to adaptive evolution. Therefore, detecting selection is important in studying evolutionary biology. Changes in allele frequency are fundamental to adaptive evolution. The allele frequency of entire genes at the genomic scale is more intensive and precise for analyzing selection effects, compared with simple sequence repeat and single nucleotide polymorphism (SNP) alleles from nuclear gene fragments. Here, we analyzed 29,094 SNPs derived from 80 individuals of 14 L. Liou ex S.L. Chen & Renvoize populations planted near their native habitat (Jiangxia, Hubei Province, JH) and a stressful environment (Qingyang, Gansu Province, QG) to detect selection during initial adaptation. The nucleotide diversity of over 60% of genes was decreased in QG compared with JH, suggesting that most genes were undergoing selection in the stressful environment. We explored a new approach based on haplotype data inferred from RNA-seq data to analyze the change in frequency between two sites and to detect selection signals. In total, 402 and 51 genes were found to be targets of positive and negative selection, respectively. Among these candidate genes, the enrichment of abiotic stress-response genes and photosynthesis-related genes might have been responsible for establishment in the stressful environment. This is the first study assessing the change in allele frequency at the genomic level during adaptation. The method in which allele frequency detects selection during initial adaptation using population RNA-seq data would be useful for developing evolutionary biology.

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is potentially lethal, but it is also a treatable autoimmune disorder characterized by prominent psychiatric and neurologic symptoms. It is often accompanied with teratoma or other neoplasm, especially in female patients. Anti-NMDAR antibodies in cerebrospinal fluid (CSF) and serum are characteristic features of the disease, thereby suggesting a pathogenic role in the disease. Here, we summarize recent studies that have clearly documented that both clinical manifestations and the antibodies may contribute to early diagnosis and multidisciplinary care. The clinical course of the disorder is reversible and the relapse could occur in some patients. Anti-NMDAR encephalitis coexisting with demyelinating disorders makes the diagnosis more complex; thus, clinicians should be aware of the overlapping diseases.

GC-MS method combined with FTIR techniques by the analysis of polysaccharide was applied to evaluate the similarity between wild (W) and tissue-cultured (TC) Dendrobium huoshanense (DHS), Dendrobium officinale (DO), and Dendrobium moniliforme (DM) as well as 3 wild Dendrobium spp.: Dendrobium henanense (DHN), Dendrobium loddigesii (DL), and Dendrobium crepidatum (DC). Eight monosaccharides involving xylose, arabinose, rhamnose, glucose, mannose, fructose, galactose, and galacturonic acid were identified in the polysaccharide from each Dendrobium sample while the contents of the monosugars varied remarkably across origins and species. Further similarity evaluation based on GC-MS data showed that the rcor values of different origins of DHS, DO, and DM were 0.831, 0.865, and 0.884, respectively, while the rcor values ranged from 0.475 to 0.837 across species. FTIR files of the polysaccharides revealed that the similarity coefficients between W and TC-DHS, DO, and DM were 88.7%, 86.8%, and 88.5%, respectively, in contrast to the similarity coefficients varying from 57.4% to 82.6% across species. These results suggested that the structures of polysaccharides between different origins of the investigated Dendrobiums might be higher than what we had supposed.