Application Of High-throughput Sequencing Technology Research Articles

Q-learning guided mutational Harris hawk optimizer for high-dimensional gene data feature selection

With the widespread application of high-throughput sequencing technology in recent years, the scale of high-dimensional gene sequence datasets has rapidly expanded. However, due to the high-dimensional nature of gene sequence data, researchers face the challenge of processing such complex data. One common preprocessing technique that can improve performance is feature selection, which selects the most relevant features from the original dataset, reducing its dimensionality. However, feature selection is often an NP-hard problem, and medical feature selection is mainly affected by the multiple attributes of features, which affect classification accuracy. In order to improve the generality of the algorithm, we propose RLHHO, which solves the feature selection problem of various medical gene datasets by combining Q-learning-guided mutation strategies. We also created binary RLHHO (bRLHHO) through conversion functions and evaluated its performance on 12 high-dimensional datasets. The experimental results show that bRLHHO is superior to the original HHO in improving classification accuracy and reducing the number of selected features. When processing high-dimensional medical gene datasets with over 1000 dimensions, bRLHHO can achieve good accuracy with fewer features. In summary, compared with other algorithms, including the original Harris Hawks Optimization (HHO), our proposed improved version of HHO, RLHHO, can handle various feature selection datasets and exhibits superior performance.

Computational Analysis of B-Cell Receptor (BCR) Immune Repertoires with Abalign.

The widespread application of high-throughput sequencing technology has generated massive sequences of B-cell receptor (BCR) immune repertoires. Computational analysis of these data has gained significant attention due to the increasing importance of immunotherapy and precision medicine. It not only reveals the diversity and dynamic changes in immune responses, contributing to the study of associated diseases, but also provides valuable information for immunodiagnostics and drug development. Recently, we introduced a BCR-specific multiple sequence alignment (MSA) method along with a comprehensive platform software called Abalign, which stands out as an excellent choice for analyzing BCR immune repertoires due to its unique high-throughput processing capability. It offers ultra-fast MSA functionality and a wide range of analytical features, including BCR/antibody extraction, clonal grouping, lineage tree construction, mutation profiling, diversity statistics, VJ gene assignment, antibody humanization, and more. Importantly, users can perform these analyses using the graphical user interface without any programming skills or scripts. In this article, we present a series of protocols that integrate Abalign's analysis modules into a cohesive workflow. This step-by-step workflow provides detailed instructions for software installation, data preparation, and comprehensive analysis of BCR immune repertoires. This workflow facilitates the efficient acquisition of comprehensive results in profiling BCR immune repertoires, offering insights into the impacts of infectious diseases, allergies, autoimmune disorders, tumor immunology, and antibody drugs. Abalign is freely available at http://cao.labshare.cn/abalign/. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Resource preparation Basic Protocol 2: Analyzing BCR immune repertoires Support Protocol 1: Aiding antibody humanization Support Protocol 2: Constructing B-cell lineage trees Alternate Protocol: Running with Linux command line Basic Protocol 3: Comparing BCR immune repertoires.

The role of microbiota in the development and treatment of gastric cancer.

The stomach was once considered a sterile organ until the discovery of Helicobacter pylori (HP). With the application of high-throughput sequencing technology and macrogenomics, researchers have identified fungi and fivemajor bacterial phyla within the stomachs of healthy individuals. These microbial communities exert regulatory influence over various physiological functions, including energy metabolism and immune responses. HP is a well-recognized risk factor for gastric cancer, significantly altering the stomach's native microecology. Currently, numerous studies are centered on the mechanisms by which HP contributes to gastric cancer development, primarily involving the CagA oncoprotein. However, aside from exogenous infections such as HP and EBV, certain endogenous dysbiosis can also lead to gastric cancer through multiple mechanisms. Additionally, gut microbiota and its metabolites significantly impact the development of gastric cancer. The role of microbial therapies, including diet, phages, probiotics and fecal microbiota transplantation, in treating gastric cancer should not be underestimated. This review aims to study the mechanisms involved in the roles of exogenous pathogen infection and endogenous microbiota dysbiosis in the development of gastric cancer. Also, we describe the application of microbiota therapy in the treatment and prognosis of gastric cancer.

Melatonin Protects the Apoptosis of Sheep Granulosa Cells by Suppressing Oxidative Stress via MAP3K8 and FOS Pathway.

Melatonin is not only a highly effective active oxygen scavenger but also an important reproductive hormone. Melatonin has a regulatory effect on animal reproduction, especially on the ovaries. It can affect the proliferation and apoptosis of cells in follicles. However, the mechanisms of the dual antioxidation and anti-apoptosis effects of melatonin on granulosa cells are still not clear, especially in sheep. Therefore, we investigated the mechanisms of the protective effect of melatonin against oxidative damage in granulosa cells. At a concentration of 250 µmol/L, H2O2 promoted granulosa cell apoptosis; however, 10 ng/mL melatonin effectively alleviated the pro-apoptotic effect of H2O2. Furthermore, through the application of high-throughput sequencing technology, we identified 109 significantly differentially expressed genes (35 upregulated and 74 downregulated genes) involved in the protective effect of melatonin against apoptosis. The expression levels of nine related genes, i.e., ATF3, FIBIN, FOS, HSPA6, MAP3K8, FOSB, PET117, DLX2, and TRIB1, changed significantly. MAP3K8 and FOS gene overexpression impacted the protective effect of melatonin in granulosa cells; the two genes exhibited an upstream and downstream regulatory relationship. Our findings indicated that melatonin alleviated H2O2-induced apoptosis in sheep granulosa cells through the MAP3K8-FOS pathway.

Identification of gene mutations in six Chinese patients with maple syrup urine disease.

Background: Maple syrup urine disease (MSUD) is a rare autosomal recessive amino acid metabolic disease. This study is to identify the pathogenic genetic factors of six cases of MUSD and evaluates the application value of high-throughput sequencing technology in the early diagnosis of MUSD. Methods: Clinical examination was carried out for patients and used blood tandem mass spectrometry (MS/MS), urine gas chromatography-mass spectrometry (GC/MS), and the application of high-throughput sequencing technology for detection. Validate candidate mutations by polymerase chain reaction (PCR)-Sanger sequencing technology. Bioinformatics software analyzed the variants' pathogenicity. Using Swiss PDB Viewer software to predict the effect of mutation on the structure of BCKDHA and BCKDHB proteins. Result: A total of six MSUD patients were diagnosed, including four males and two females. Nine variants were found in three genes of six MSUD families by high-throughput sequencing, including four missense mutations: c.659C>T(p.A220V), c.818C>T(p.T273I), c.1134C>G(p.D378E), and c.1006G>A(p.G336S); two non-sense mutations: c.1291C>T(p.R431*) and c.331C>T(p.R111*); three deletion mutations: c.550delT (p.S184Pfs*46), c.718delC (p.P240Lfs*14), and c.795delG (p.N266Tfs*64). Sanger sequencing's results were consistent with the high-throughput sequencing. The bioinformatics software revealed that the mutations were harmful, and the prediction results of Swiss PDB Viewer suggest that variation affects protein conformation. Conclusion: This study identified nine pathogenic variants in the BCKDHA, BCKDHB, and DBT genes in six MSUD families, including two novel pathogenic variants in the BCKDHB gene, which enriched the genetic mutational spectrum of the disease. High-throughput sequencing is essential for the MSUD's differential diagnosis, early treatment, and prenatal diagnosis.

Application of High-Throughput Sequencing Technology in the Pathogen Identification of Diverse Infectious Diseases in Nephrology Departments.

Objective: The purpose of this study was to explore the clinical applications of high-throughput sequencing (HTS) in the identification of pathogens in patients with urinary tract infection (UTI), peritoneal dialysis-associated peritonitis (PDAP), central venous catheter related blood infections (CRBIs), and lung infections in the nephrology department. Methods: Midstream urine samples from 112 patients with UTI, peritoneal fluid samples from 67 patients with PDAP, blood samples from 15 patients with CRBI, and sputum specimens from 53 patients with lung infection were collected. The HTS and ordinary culture methods were carried out in parallel to identify the pathogens in each sample. Pathogen detection positive rate and efficacy were compared between the two methods. Results: The pathogen positive detection rates of HTS in UTI, PDAP, CRBI, and lung infection were strikingly higher than those of the culture method (84.8% vs. 35.7, 71.6% vs. 23.9%, 75% vs. 46.7%, 84.9% vs. 5.7%, p < 0.05, respectively). HTS was superior to the culture method in the sensitivity of detecting bacteria, fungi, atypical pathogens, and mixed microorganisms in those infections. In patients who had empirically used antibiotics before the test being conducted, HTS still exhibited a considerably higher positive rate than the culture method (81.6% vs. 39.0%, 68.1% vs. 14.9%, 72.7% vs. 36.4%, 83.3% vs. 4.2%, p < 0.05, respectively). Conclusions: HTS is remarkably more efficient than the culture method in detecting pathogens in diverse infectious diseases in nephrology, and is particularly potential in identifying the pathogens that are unable to be identified by the common culture method, such as in cases of complex infection with specific pathogens or subclinical infection due to preemptive use of antibiotics.

Application of High-Throughput Sequencing Technology in Identifying the Pathogens in Endophthalmitis.

Infectious endophthalmitis is an important cause of vision loss worldwide. It is an inflammatory reaction caused by bacteria, fungi, and other micro-organisms and often occurs as a complication of intraocular surgery, especially following cataract surgery or intravitreal injection. The focus of the prevention and treatment of infectious endophthalmitis is the early detection of microbial flora, such as fungi or bacteria. Current identification methods for bacteria include Gram staining-based, culture-based, and polymerase chain reaction (PCR)-based methods. The matrix-assisted laser desorption/ionization time-of-flight mass spectrometry technology is now the standard identification method of bacteria and fungi after their isolation in culture. The remarkable sensitivity of PCR technology for the direct detection of micro-organisms in clinical samples makes it particularly useful in culture-positive and culture-negative endophthalmitis. Furthermore, PCR increases the rate of microorganism detection in intraocular samples by 20% and can provide a microbiology diagnosis in approximately 44.7–100% of the culture-negative cases. This review aims to introduce the development of different methods for the detection and identification of micro-organisms causing endophthalmitis through a literature review; introduce the research status of the first, second, and third-generation sequencing technologies in infectious endophthalmitis; and understand the research status of endophthalmitis microbial flora. For slow-growing and rare micro-organisms, high-throughput sequencing (HTS) offers advantages over conventional methods and provides a basis for the identification of pathogens in endophthalmitis cases with negative culture. It is a reliable platform for the identification of pathogenic bacteria of infectious endophthalmitis in the future and provides a reference for the clinical diagnosis and treatment of infectious endophthalmitis. The application of HTS technology may also be transformative for clinical microbiology and represents an exciting future direction for the epidemiology of ocular infections.

Application of high-throughput sequencing technology in prenatal thalassemia screening in Zhuhai region

To compare the performance of high-throughput sequencing technology in prenatal thalassemia screening in Zhuhai area through comparison with traditional methods. A total of 1463 pregnant women were randomly selected. Following DNA extraction, high-throughput sequencing and conventional three-step thalassemia screening were carried out for each sample. Inconsistent results samples were validated by quantitative fluorescence PCR (QF-PCR) or Sanger sequencing. The results by the two methods were compared. Among the 1463 cases, 318 (21.74%) were detected by conventional method, which included 210 (14.35%) with α-thalassemia, 97 (6.63%) with β-thalassemia, 11 (0.75%) with composite α- and β-thalassemia. Meanwhile, 379 cases (25.91%) of thalassemia were detected by high-throughput sequencing, which included 260 (17.77%) with α-thalassemia, 107 (7.31%) with β-thalassemia, 12 (0.82%) with composite α- and β-thalassemia. Six one cases were missed by the conventional method, which yielded a missed diagnosis rate of 16.09%, including 50 cases of α- thalassemia,10 cases of β-thalassemia, and 1 case of α-compound β-thalassemia. No cases of thalassemia were missed by high-throughput sequencing, and 10 rare thalassemia genotypes were detected. High-throughput sequencing technology can improve the detection rate of thalassemia and reduce the missed diagnosis rate. It has a high application value in prenatal thalassemia screening in Zhuhai area and can more effectively prevent the birth of patients with severe thalassemia.

Cancer Risk and Mutational Patterns Following Organ Transplantation.

The rapid development of medical technology and widespread application of immunosuppressive drugs have improved the success rate of organ transplantation significantly. However, the use of immunosuppressive agents increases the frequency of malignancy greatly. With the prospect of “precision medicine” for tumors and development of next-generation sequencing technology, more attention has been paid to the application of high-throughput sequencing technology in clinical oncology research, which is mainly applied to the early diagnosis of tumors and analysis of tumor-related genes. All generations of cancers carry somatic mutations, meanwhile, significant differences were observed in mutational signatures across tumors. Systematic sequencing of cancer genomes from patients after organ transplantation can reveal DNA damage and repair processes in exposed cancer cells and their precursors. In this review, we summarize the application of high-throughput sequencing and organoids in the field of organ transplantation, the mutational patterns of cancer genomes, and propose a new research strategy for understanding the mechanism of cancer following organ transplantation.

Integrated Multi-Omics Analysis Model to Identify Biomarkers Associated With Prognosis of Breast Cancer.

BackgroundWith the rapid development and wide application of high-throughput sequencing technology, biomedical research has entered the era of large-scale omics data. We aim to identify genes associated with breast cancer prognosis by integrating multi-omics data.MethodGene-gene interactions were taken into account, and we applied two differential network methods JDINAC and LGCDG to identify differential genes. The patients were divided into case and control groups according to their survival time. The TCGA and METABRIC database were used as the training and validation set respectively.ResultIn the TCGA dataset, C11orf1, OLA1, RPL31, SPDL1 and IL33 were identified to be associated with prognosis of breast cancer. In the METABRIC database, ZNF273, ZBTB37, TRIM52, TSGA10, ZNF727, TRAF2, TSPAN17, USP28 and ZNF519 were identified as hub genes. In addition, RPL31, TMEM163 and ZNF273 were screened out in both datasets. GO enrichment analysis shows that most of these hub genes were involved in zinc ion binding.ConclusionIn this study, a total of 15 hub genes associated with long-term survival of breast cancer were identified, which can promote understanding of the molecular mechanism of breast cancer and provide new insight into clinical research and treatment.

Research progress on biological functions of lncRNAs in major vegetable crops

With the advances in genomics and bioinformatics, particularly the extensive application of high-throughput sequencing technology, a large number of non-coding RNAs (ncRNAs) have been discovered, of which long ncRNAs (lncRNAs) refer to a class of transcripts that are more than 200 nucleotides in length. Accumulating evidence demonstrates that lncRNAs play significant roles in a wide range of biological processes, including regulating plant growth and development as well as modulating biotic and abiotic stress responses. Although the study of lncRNAs has been a hotspot of biological research in recent years, the functional characteristics of plant lncRNAs are still in their initial phase and face great challenges. Here, we summarize the characteristics and screening methods of lncRNAs and highlight their biological functions in major vegetable crops, including tomato, <italic>Brassica</italic> genus crops, cucumber, pepper, carrot, radish, potato, and spinach, which are implicated in the interaction of lncRNAs and miRNAs. This review enhances the understanding of lncRNAs' roles and can guide crop improvement programs in the future.

Diagnostic Classification of Lung Cancer Using Deep Transfer Learning Technology and Multi‐Omics Data

In recent years, with the increasing application of highthroughput sequencing technology, researchers have obtained and accumulated a large amount of multi-omics data, making it possible to diagnose cancer at the gene expression level. The proliferation of various omics data can provide a large amount of biological information, which brings new opportunities and great challenges as well to cancer classification and diagnosis. Machine learning algorithms for early diagnosis of lung cancer have emerged that distinguish cancers of the early and late stages by using genomic features. Omics data are generally characterized with low sample size, high dimensionality and high noise. Therefore, simple direct application of common classification methods cannot achieve better performance and must be improved in a targeted manner. This paper puts forward a combined convolutional neural network and convolutional auto-encoders approach to construct a deep migratory learning classification model for early lung cancer diagnosis. First, the convolutional auto-encoders algorithm is used to reduce the dimensionality of the dataset in order to make it better meet the requirements of migration learning. Second, a neural network model is constructed with the original dataset and the existing labeled dataset, and the model migration rules are set as well. Finally, a small number of labeled target datasets are used in the training to complete the construction of the classification model. The proposed convolutional neural network method based on model migration and five other popular machine learning models are used to classify and predict the three lung cancer gene datasets and the integrated dataset. The experimental results show that such four evaluation metrics as accuracy, precision, recall, and f1-score with our proposed method have obtained better prediction performance, and the average area under curve result also shows our proposed method is optimal.

The prognostic factors and nomogram for patients with high-grade gliomas

The evaluation on prognosis of glioma patients is critical for the individualized treatment. Despite of the widely used mRNA expression level and methylation status of prognostic genes in predicting the patients’ prognosis, the clinical application of high-throughput sequencing technology is still limited. Thus, this study aimed to construct a visual and reliable nomogram based on the common clinicopathological parameters for predicting the prognosis of patients diagnosed with high grade glioma (HGG). Notably, age, histopathology, IDH status, 1p/19q status, radiotherapy status, chemotherapy status, and tumor recurrence were identified as seven independent prognostic factors for HGG patients. A comprehensive nomogram based on the seven identified factors was subsequently constructed with the remarkable C-index of 0.732. Calibrations for nomogram showed great consistency between the predictive values and the actual values in 1-, 3-, and 5-year survival rates. Besides, the areas under the ROC curve (AUC) for predicting 1-, 3-, and 5-year survival rates of patients had the values of 0.796 (95% CI: 0.759-0.833), 0.809 (95% CI: 0.770-0.848), and 0.820 (95% CI: 0.771-0.869), respectively. Furthermore, an external cohort (n=89) was used to validate the nomogram. In conclusion, age, histopathology, IDH status, 1p/19q status, radiotherapy status, chemotherapy status, and tumor progression were identified as independent prognostic factors, on which a visual predictive model was constructed with powerful predictive value.

CircRNA_0000392 promotes colorectal cancer progression through the miR-193a-5p/PIK3R3/AKT axis

BackgroundCircular RNAs (circRNAs), important members of the noncoding RNA family, have been recently revealed to play a role in the pathogenic progression of diseases, particularly in the malignant progression of cancer. With the application of high-throughput sequencing technology, a large number of circRNAs have been identified in tumor tissues, and some circRNAs have been demonstrated to act as oncogenes. In this study, we analyzed the circRNA expression profile in colorectal cancer (CRC) tissues and normal adjacent tissues by high-throughput sequencing. We focused on circRNA_0000392, a circRNA with significantly increased expression in CRCtissues, and further investigated its function in the progression of colorectal cancer.MethodsThe expression profile of circRNAs in 6 pairs of CRC tissues and normal adjacent tissues was analyzed by RNA sequencing. We verified the identified differentially expressed circRNAs in additional samples by qRT-PCR and selected circRNA_0000392 to evaluate its associations with clinicopathological features. Then, we knocked down circRNA_0000392 in CRC cells and investigated the in vitro and in vivo effects using functional experiments. Dual luciferase and RNA pull-down assays were performed to further explore the downstream potential molecular mechanisms.ResultsCircRNA_0000392 was significantly upregulated in CRC compared with normal adjacent tissues and cell lines. The expression level of circRNA_0000392 was positively correlated with the malignant progression of CRC. Functional studies revealed that reducing the expression of circRNA_0000392 could inhibit the proliferation and invasion of CRC both in vitro and in vivo. Mechanistically, circRNA_0000392 could act as a sponge of miR-193a-5p and regulate the expression of PIK3R3, affecting the activation of the AKT-mTOR pathway in CRC cells.ConclusionsCircRNA_0000392 functions as an oncogene through the miR-193a-5p/PIK3R3/Akt axis in CRC cells, suggesting that circRNA_0000392 is a potential therapeutic target for the treatment of colorectal cancer and a predictive marker for CRC patients.

Application of high-throughput sequencing technology for the detection of fetal copy number variations

To assess the value of non-invasive prenatal testing (NIPT) for the detection of fetal copy number variations (CNVs) in addition to trisomies 21, 18, and 13. A total of 37 306 pregnant women underwent the NIPT test. For those with fetal CNVs indicated by NIPT and accepted invasive prenatal diagnosis, amniotic fluid samples were obtained for chromosomal karyotyping analysis and chromosome microarray analysis (CMA). All cases were followed up. Among the 37 306 cases, 78 (0.209%) were predicted to have fetal CNVs. Among these, 52 pregnant women accepted invasive prenatal diagnosis, and 15 of them (28.85%) obtained a consistent result. Follow up of 26 women who refused invasive prenatal diagnosis have found 2 cases with spontaneous abortion, 2 with induced labor for fetal malformation indicated by ultrasonography, and 1 had multiple malformations and a consistent result by CMA, which yielded an abnormal rate of 19.23%. NIPT can signal fetal chromosomal abnormalities through detection of gain and/or loss of fetal DNA copies. Combined chromosomal karyotyping and CMA can increase the detection rate for common chromosomal aneuploidies and CNVs, thereby provide a basis for genetic counseling for the affected families.

Clinical Application of High-throughput Sequencing Technology for the Diagnosis of Patients With Severe Infection

Clinical Application of High-throughput Sequencing Technology for the Diagnosis of Patients With Severe Infection

The application of high-throughput sequencing technology to analysis of amoA phylogeny and environmental niche specialisation of terrestrial bacterial ammonia-oxidisers

BackgroundCharacterisation of microbial communities increasingly involves use of high throughput sequencing methods (e.g. MiSeq Illumina) that amplify relatively short sequences of 16S rRNA or functional genes, the latter including ammonia monooxygenase subunit A (amoA), a key functional gene for ammonia oxidising bacteria (AOB) and archaea (AOA). The availability of these techniques, in combination with developments in phylogenetic methodology, provides the potential for better analysis of microbial niche specialisation. This study aimed to develop an approach for sequencing of bacterial and archaeal amoA genes amplified from soil using bioinformatics pipelines developed for general analysis of functional genes and employed sequence data to reassess phylogeny and niche specialisation in terrestrial bacterial ammonia oxidisers.ResultsamoA richness and community composition differed with bioinformatics approaches used but analysis of MiSeq sequences was reliable for both archaeal and bacterial amoA genes and was used for subsequent assessment of potential niche specialisation of soil bacteria ammonia oxidisers. Prior to ecological analysis, phylogenetic analysis of Nitrosospira, which dominates soil AOB, was revisited using a phylogenetic analysis of 16S rRNA and amoA genes in available AOB genomes. This analysis supported congruence between phylogenies of the two genes and increased previous phylogenetic resolution, providing support for additional gene clusters of potential ecological significance. Analysis of environmental sequences using these new sequencing, bioinformatics and phylogenetic approaches demonstrated, for the first time, similar niche specialisation in AOB to that in AOA, indicating pH as a key ecological factor controlling the composition of soil ammonia oxidiser communities.ConclusionsThis study presents the first bioinformatics pipeline for optimal analysis of Illumina MiSeq sequencing of a functional gene and is adaptable to any amplicon size (even genes larger than 500 bp). The pipeline was used to provide an up-to-date phylogenetic analysis of terrestrial betaproteobacterial amoA genes and to demonstrate the importance of soil pH for their niche specialisation and is broadly applicable to other ecosystems and diverse microbiomes.

Further delineation of spondyloepimetaphyseal dysplasia Faden-Alkuraya type: A RSPRY1-associated spondylo-epi-metaphyseal dysplasia with cono-brachydactyly and craniosynostosis.

Our understanding of the molecular basis of the genetic disorders of the skeleton has steadily increased, as the application of high-throughput sequencing technology has expanded. One of the newcomers is Spondyloepimetaphyseal dysplasia Faden-Alkuraya type. In this study, we aimed to further delineate the clinical, radiographic, and molecular findings of this entity in five affected individuals from two unrelated families. All patients have short stature, extremity deformities, facial dysmorphism and intellectual disability. The skeletal hallmarks include (a) mild spondylar dysplasia, (b) epimetaphyseal dysplasia of the long bones associated with coxa vara and genu valgum, (c) brachymesophalangy with cone-shaped epiphyses, and (d) craniosynostosis. Unlike the previously reported clinical findings, all patients except one are normocephalic, and all share the clinical findings including craniosynostosis, varying degrees of intellectual disability, facial dysmorphism, and skeletal findings including pes planus, prominent heels, and pectus deformity. Interestingly one of the patients presented with a cemento-ossifying fibrous lesion of the maxilla. Whole exome sequencing revealed a novel homozygous [c.377delT] [p.Ile126fs*] frameshift mutation at exon 2 in one family, while Sanger sequencing revealed a novel homozygous splice site mutation [c.516+2T>A] at exon 4/intron 4 border of RSPRY1 in the other family. In conclusion; we provide further evidence that Spondyloepimetaphyseal dysplasia Faden-Alkuraya type is a RSPRY1-associated skeletal dysplasia with a distinctive phenotype composed of spondyloepimetaphyseal dysplasia, cono-brachydactyly, and craniosynostosis along with recognizable facial features and intellectual disability.

A Bioinformatics Study on the Application of High-Throughput Sequencing Technology to Pathogen Detection in Patients with Sepsis

A Bioinformatics Study on the Application of High-Throughput Sequencing Technology to Pathogen Detection in Patients with Sepsis

Introduction to High-Throughput Sequencing Technologies and Review of its Application in Bioleaching

Over the past years, the traditional cultivation-independent genomic approaches which rely on the preexisting knowledge about gene sequence, have significantly promoted our understanding of the structural and functional diversity of bioleaching microorganisms in extremely acidic environments. However, high-throughput sequencing technology as a comprehensive and rapid method is now being ported to bioleaching systems for microbial community and gene expression analysis. Years of research have demonstrated that high-throughput sequencing technology has the potential to dramatically accelerate biological research, by enabling the comprehensive analysis of genomes and transcriptomes. This paper aims to introduce the high-throughput sequencing methodology, particularly focusing on the application of high-throughput sequencing technology on bioleaching microorganisms and the challenges associated with its applications.