Frontiers in Genetics最新文献

[This retracts the article DOI: 10.3389/fgene.2021.817672.].

Objective: To investigate a case of neurodevelopmental disorder caused by mutation of FBXW7. Methods: Clinical data were collected from the patient, trio-WES (whole-exome sequencing) was performed on the patient and his parents (trio), and the results were verified by Sanger sequencing. RESULTS: The patient was a 2-year and 1-month old male who presented with facial dysmorphism (prominent forehead, ocular hypertelorism, and low nasal bridge), global developmental delay, language impairment, hypertonia, labial hemangioma, hydrocele, and overgrowth. The trio-WES confirmed that the child had a pathogenic de novo FBXW7 gene variant, c.1612C>T (p.G1n538*), a heretofore unreported locus. Conclusion: This case of developmental delay, hypotonia, and impaired language (OMIM: #620012) related to a mutation in FBXW7, is a rare genetic disorder, newly identified in recent years, and seldom reported. The presence of hypertonia, labial hemangioma, and hydrocele in this child suggests significant phenotypic heterogeneity of the disease, and the discovery of new mutant loci enriches the spectrum of pathogenic variants of the disease.

Cyprinid species are the most cultured aquatic species around the world in terms of quantity and total value. They account for 25% of global aquaculture production and significantly contribute to fulfilling the demand for fish food. The aquaculture of these species is facing severe concerns in terms of seed quality, rising feed costs, disease outbreaks, introgression of exotic species, environmental impacts, and anthropogenic activities. Numerous researchers have explored biological issues and potential methods to enhance cyprinid aquaculture. Selective breeding is extensively employed in cyprinid species to enhance specific traits like growth and disease resistance. In this context, we have discussed the efforts made to improve important cyprinid aquaculture practices through genetic and genomic approaches. The recent advances in DNA sequencing technologies and genomic tools have revolutionized the understanding of biological research. The generation of a complete genome and other genomic resources in cyprinid species has significantly strengthened molecular-level investigations into disease resistance, growth, reproduction, and adaptation to changing environments. We conducted a comprehensive review of genomic research in important cyprinid species, encompassing genome, transcriptome, proteome, metagenome, epigenome, etc. This review reveals that considerable data has been generated for cyprinid species. However, the seamless integration of this valuable data into genetic selection programs has yet to be achieved. In the upcoming years, genomic techniques, gene transfer, genome editing tools are expected to bring a paradigm shift in sustainable cyprinid aquaculture production. The comprehensive information presented here will offer insights for the cyprinid aquaculture research community.

The human neural retina is a complex tissue with abundant alternative splicing and more than 10% of genetic variants linked to inherited retinal diseases (IRDs) alter splicing. Traditional short-read RNA-sequencing methods have been used for understanding retina-specific splicing but have limitations in detailing transcript isoforms. To address this, we generated a proteogenomic atlas that combines PacBio long-read RNA-sequencing data with mass spectrometry and whole genome sequencing data of three healthy human neural retina samples. We identified nearly 60,000 transcript isoforms, of which approximately one-third are novel. Additionally, ten novel peptides confirmed novel transcript isoforms. For instance, we identified a novel IMPDH1 isoform with a novel combination of known exons that is supported by peptide evidence. Our research underscores the potential of in-depth tissue-specific transcriptomic analysis to enhance our grasp of tissue-specific alternative splicing. The data underlying the proteogenomic atlas are available via EGA with identifier EGAD50000000101, via ProteomeXchange with identifier PXD045187, and accessible through the UCSC genome browser.

Polygonati Rhizoma and Polygonati odorati Rhizoma, known as "Huangjing" and "Yuzhu" in China, are medicinal Polygonatum species resources with top-grade medical and edible properties. The chloroplast (cp) genome has been used to study species diversity, evolution, and breeding of species for applications in genetic engineering. Codon usage bias (CUB), a common and complex natural phenomenon, is essential for studies of codon optimization of exogenous genes, genetic engineering, and molecular evolution. However, the CUB of medicinal Polygonatum species chloroplast genomes has not been systematically studied. In our study, a detailed analysis of CUB was performed in the medicinal Polygonatum species chloroplast genomes. We investigated the codon bias of 204 plastid protein-coding genes (PCGs) in 4 medicinal Polygonatum species using CodonW and CUSP online software. Through the analysis of the codon bias index, we found that the medicinal Polygonatum species chloroplast genomes had weak codon usage bias. In addition, our results also showed a high preference for AT bases in medicinal Polygonatum species chloroplast genomes, and the preference to use AT-ending codons was observed in these species chloroplast genomes. The neutrality plot, ENC plot, PR2-Bias plot, and correspondence analysis showed that compared with mutation pressure, natural selection was the most important factor of CUB. Based on the comparative analysis of high-frequency codons and high expression codons, we also determined the 10-11 optimal codons of investigative medicinal Polygonatum species. Furthermore, the result of RSCU-based cluster analysis showed that the genetic relationship between different medicinal Polygonatum species could be well reflected. This study provided an essential understanding of CUB and evolution in the medicinal Polygonatum species chloroplast genomes.

Multi-omics data integration is a term that refers to the process of combining and analyzing data from different omic experimental sources, such as genomics, transcriptomics, methylation assays, and microRNA sequencing, among others. Such data integration approaches have the potential to provide a more comprehensive functional understanding of biological systems and has numerous applications in areas such as disease diagnosis, prognosis and therapy. However, quantitative integration of multi-omic data is a complex task that requires the use of highly specialized methods and approaches. Here, we discuss a number of data integration methods that have been developed with multi-omics data in view, including statistical methods, machine learning approaches, and network-based approaches. We also discuss the challenges and limitations of such methods and provide examples of their applications in the literature. Overall, this review aims to provide an overview of the current state of the field and highlight potential directions for future research.

Accurate species identification of the mosquitoes in the genus Anopheles is of crucial importance to implement malaria control measures and monitor their effectiveness. We use a previously developed amplicon panel (ANOSPP) that retrieves sequence data from multiple short nuclear loci for any species in the genus. Species assignment is based on comparison of samples to a reference index using k-mer distance. Here, we provide a protocol to generate version controlled updates of the reference index and present its latest release, NNv2, which contains 91 species, compared to 56 species represented in its predecessor NNv1. With the updated reference index, we are able to assign samples to species level that previously could not be assigned. We discuss what happens if a species is not represented in the reference index and how this can be addressed in a future update. To demonstrate the increased power of NNv2, we showcase the assignments of 1789 wild-caught mosquitoes from Madagascar and demonstrate that we can detect within species population structure from the amplicon sequencing data.

Introduction: In this study, we aimed to explore the relationship between clinicopathological features and driver gene changes in Chinese NSCLC patients.

Methods: Amplification refractory mutation system PCR was used to detect the aberrations of 10 driver oncogenes in 851 Chinese NSCLC patients, and their correlation with clinicopathological characteristics was also analyzed. Moreover, three models of logistic regression were used to analyze the association between histopathology and EGFR or KRAS mutations.

Results: The top two most frequently aberrant target oncogenes were EGFR (48.06%) and KRAS (9.51%). These were followed by ALK (5.41%), HER2 (2.35%), MET (2.23%), RET (2.11%), ROS1 (1.88%), BRAF (0.47%), NRAS (0.24%), and PIK3CA (0.12%). Additionally, 11 (1.29%) patients had synchronous gene alterations in two genes. The main EGFR mutations were exon 21 L858R and exon 19-Del, which accounted for 45.97% and 42.79% of all EGFR mutations, respectively. Logistic regression analysis showed that the frequency of EGFR mutations was positively correlated with women, non-smokers, lung adenocarcinoma, and invasive non-mucinous adenocarcinoma (IA), and negatively correlated with solid nodule, micro-invasive adenocarcinoma, and solid-predominant adenocarcinoma. KRAS mutations were positively associated with men and longer tumor long diameters and negatively correlated with lung adenocarcinoma (P < 0.05 for all).

Conclusion: Our findings suggest that the EGFR mutation frequency was higher in women, non-smokers, lung adenocarcinoma, and the IA subtype in lung adenocarcinoma patients, while the KRAS mutation rate was higher in men and patients with longer tumor long diameter and lower in lung adenocarcinoma patients.