Era Of Sequencing Research Articles

CARD-FISH in the Sequencing Era: Opening a New Universe of Protistan Ecology.

Phagotrophic protists are key players in aquatic food webs. Although sequencing-based studies have revealed their enormous diversity, ecological information on in situ abundance, feeding modes, grazing preferences, and growth rates of specific lineages can be reliably obtained only using microscopy-based molecular methods, such as Catalyzed Reporter Deposition-Fluorescence in situ Hybridization (CARD-FISH). CARD-FISH is commonly applied to study prokaryotes, but less so to microbial eukaryotes. Application of this technique revealed that Paraphysomonas or Spumella-like chrysophytes, considered to be among the most prominent members of protistan communities in pelagic environments, are omnipresent but actually less abundant than expected, in contrast to little known groups such as heterotrophic cryptophyte lineages (e.g., CRY1), cercozoans, katablepharids, or the MAST lineages. Combination of CARD-FISH with tracer techniques and application of double CARD-FISH allow visualization of food vacuole contents of specific flagellate groups, thus considerably challenging our current, simplistic view that they are predominantly bacterivores. Experimental manipulations with natural communities revealed that larger flagellates are actually omnivores ingesting both prokaryotes and other protists. These new findings justify our proposition of an updated model of microbial food webs in pelagic environments, reflecting more authentically the complex trophic interactions and specific roles of flagellated protists, with inclusion of at least two additional trophic levels in the nanoplankton size fraction. Moreover, we provide a detailed CARD-FISH protocol for protists, exemplified on mixo- and heterotrophic nanoplanktonic flagellates, together with tips on probe design, a troubleshooting guide addressing most frequent obstacles, and an exhaustive list of published probes targeting protists.

Impact of Integrated Genetic Information on Diagnosis and Prognostication for Myeloproliferative Neoplasms in the Next-Generation Sequencing Era.

Since next-generation sequencing has been widely used in clinical laboratories, the diagnosis and risk stratification of hematologic malignancies are greatly dependent on genetic aberrations. In this study, we analyzed the genomic landscapes of 200 patients with myeloproliferative neoplasms (MPNs) and evaluated the impact of the genomic landscape on diagnosis and risk stratification. Mutations in JAK2, CALR and MPL were detected in 76.4% of MPNs. The proportion of patients with clonal genetic markers increased up to 86.4% when all detectable genetic aberrations were included. Significant co-occurring genetic aberrations potentially associated with phenotype and/or disease progression, including those in JAK2/SF3B1 and TP53/del(13q), del(5q), −7/del(7q) and complex karyotypes, were detected. We also identified genetic aberrations associated with patient outcomes: TP53 and −7/del(7q) were associated with an inferior chance of survival, RUNX1, TP53 and IDH1/2 were associated with leukemic transformation and SF3B1, IDH1/2, ASXL1 and del(20q) were associated with fibrotic progression. We compared risk stratification systems and found that mutation-enhanced prognostic scoring systems could identify lower risk polycythemia vera, essential thrombocythemia and higher risk primary myelofibrosis. Furthermore, the new risk stratification systems showed a better predictive capacity for patient outcome. These results collectively indicate that integrated genetic information can enhance diagnosis and prognostication in patients with myeloproliferative neoplasms.

"Zooming in" on Glioblastoma: Understanding Tumor Heterogeneity and its Clinical Implications in the Era of Single-Cell Ribonucleic Acid Sequencing.

Glioblastoma (GBM) is the most common primary brain malignancy in adults and one of the most aggressive of all human cancers. It is highly recurrent and treatment-resistant, in large part due to its infiltrative nature and inter- and intratumoral heterogeneity. This heterogeneity entails varying genomic landscapes and cell types within and between tumors and the tumor microenvironment (TME). In GBM, heterogeneity is a driver of treatment resistance, recurrence, and poor prognosis, representing a substantial impediment to personalized medicine. Over the last decade, sequencing technologies have facilitated deeper understanding of GBM heterogeneity by "zooming in" progressively further on tumor genomics and transcriptomics. Initial efforts employed bulk ribonucleic acid (RNA) sequencing, which examines composite gene expression of whole tumor specimens. While groundbreaking at the time, this bulk RNAseq masks the crucial contributions of distinct tumor subpopulations to overall gene expression. This work progressed to the use of bulk RNA sequencing in anatomically and spatially distinct tumor subsections, which demonstrated previously underappreciated genomic complexity of GBM. A revolutionary next step forward has been the advent of single-cell RNA sequencing (scRNAseq), which examines gene expression at the single-cell level. scRNAseq has enabled us to understand GBM heterogeneity in unprecedented detail. We review seminal studies in our progression of understanding GBM heterogeneity, with a focus on scRNAseq and the insights that it has provided into understanding the GBM tumor mass, peritumoral space, and TME. We highlight preclinical and clinical implications of this work and consider its potential to impact neuro-oncology and to improve patient outcomes via personalized medicine.

Quantifying Fetal Reprogramming for Biomarker Development in the Era of High-Throughput Sequencing.

Gestational hypertensive disorders continue to threaten the well-being of pregnant women and their offspring. The only current definitive treatment for gestational hypertensive disorders is delivery of the fetus. The optimal timing of delivery remains controversial. Currently, the available clinical tools do not allow for assessment of fetal stress in its early stages. Placental insufficiency and fetal growth restriction secondary to gestational hypertensive disorders have been shown to have long-term impacts on offspring health even into their adulthood, becoming one of the major focuses of research in the field of developmental origins of health and disease. Fetal reprogramming was introduced to describe the long-lasting effects of the toxic intrauterine environment on the growing fetus. With the advent of high-throughput sequencing, there have been major advances in research attempting to quantify fetal reprogramming. Moreover, genes that are found to be differentially expressed as a result of fetal reprogramming show promise in the development of transcriptional biomarkers for clinical use in detecting fetal response to placental insufficiency. In this review, we will review key pathophysiology in the development of placental insufficiency, existing literature on high-throughput sequencing in the study of fetal reprogramming, and considerations regarding research design from our own experience.

InpactorDB: A Classified Lineage-Level Plant LTR Retrotransposon Reference Library for Free-Alignment Methods Based on Machine Learning.

Long terminal repeat (LTR) retrotransposons are mobile elements that constitute the major fraction of most plant genomes. The identification and annotation of these elements via bioinformatics approaches represent a major challenge in the era of massive plant genome sequencing. In addition to their involvement in genome size variation, LTR retrotransposons are also associated with the function and structure of different chromosomal regions and can alter the function of coding regions, among others. Several sequence databases of plant LTR retrotransposons are available for public access, such as PGSB and RepetDB, or restricted access such as Repbase. Although these databases are useful to identify LTR-RTs in new genomes by similarity, the elements of these databases are not fully classified to the lineage (also called family) level. Here, we present InpactorDB, a semi-curated dataset composed of 130,439 elements from 195 plant genomes (belonging to 108 plant species) classified to the lineage level. This dataset has been used to train two deep neural networks (i.e., one fully connected and one convolutional) for the rapid classification of these elements. In lineage-level classification approaches, we obtain up to 98% performance, indicated by the F1-score, precision and recall scores.

Plant Mitochondria are a Riddle Wrapped in a Mystery Inside an Enigma.

A fundamental paradox motivates the study of plant mitochondrial genomics: the mutation rate is very low (lower than in the nucleus) but the rearrangement rate is high. A landmark paper published in Journal of Molecular Evolution in 1988 established these facts and revealed the paradox. Jeffrey Palmer and Laura Herbon did a prodigious amount of work in the pre-genome sequencing era to identify both the high frequency of rearrangements between closely related species, and the low frequency of mutations, observations that have now been confirmed many times by sequencing. This paper was also the first to use molecular data on rearrangements as a phylogenetic trait to build a parsimonious tree. The work was a technical tour-de-force, its findings are still at the heart of plant mitochondrial genomics, and the underlying molecular mechanisms that produce this paradox are still not completely understood.

Integrative bioinformatics and omics data source interoperability in the next-generation sequencing era—Editorial

Integrative bioinformatics and omics data source interoperability in the next-generation sequencing era—Editorial

Next-Generation Sequencing-Based Biomarkers in Breast Cancer.

For the realization of precision medicine in cancer treatment, discovery, and validation of clinically useful biomarker is the most important prerequisite. Biomarkers are needed and used for evaluation of cancer susceptibility, cancer screening (early detection), cancer subtyping, prediction of prognosis, decision of appropriate adjuvant therapy and duration of therapy, and for monitoring of recurrence. Biomarkers are also needed for decision of target therapy in metastatic cancer and monitoring of their response during follow-up. Now is the era of Next-Generation Sequencing (NGS). NGS technology can detect almost all kind of genomic changes that occur in cancer that is different from normal condition. The cost also is now reasonably low to use in routine clinical practice.This chapter will review four kinds of NGS-based biomarkers that are already being used in clinical practice although the routine use is controversial, and that are promising and under active investigation focusing on studies done in Seoul National University Hospital (SNUH).

Dealing with Pseudogenes in Molecular Diagnostics in the Next Generation Sequencing Era.

Presence of pseudogenes is a dreadful issue in next generation sequencing (NGS), because their contamination can interfere with the detection of variants in the genuine gene and generate false positive and false negative variants.In this chapter we focus on issues related to the application of NGS strategies for analysis of genes with pseudogenes in a clinical setting. The degree to which a pseudogene impacts the ability to accurately detect and map variants in its parent gene depends on the degree of similarity (homology) with the parent gene itself. Hereby, target enrichment and mapping strategies are crucial factors to avoid "contaminating" pseudogene sequences. For target enrichment, we describe advantages and disadvantages of PCR- and capture-based strategies. For mapping strategies, we discuss crucial parameters that need to be considered to accurately distinguish sequences of functional genes from pseudogenic sequences. Finally, we discuss some examples of genes associated with Mendelian disorders, for which interesting NGS approaches are described to avoid interference with pseudogene sequences.

Molecular epidemiology of Mycobacterium tuberculosis in Brazil before the whole genome sequencing era: a literature review.

Molecular-typing can help in unraveling epidemiological scenarios and improvement for disease control strategies. A literature review of Mycobacterium tuberculosis transmission in Brazil through genotyping on 56 studies published from 1996-2019 was performed. The clustering rate for mycobacterial interspersed repetitive units - variable tandem repeats (MIRU-VNTR) of 1,613 isolates were: 73%, 33% and 28% based on 12, 15 and 24-loci, respectively; while for RFLP-IS6110 were: 84% among prison population in Rio de Janeiro, 69% among multidrug-resistant isolates in Rio Grande do Sul, and 56.2% in general population in São Paulo. These findings could improve tuberculosis (TB) surveillance and set up a solid basis to build a database of Mycobacterium genomes.

Synthetic genomics for curing genetic diseases.

From the beginning of the genome sequencing era, it has become increasingly evident that genetics plays a role in all diseases, of which only a minority are single-gene disorders, the most common target of current gene therapies. However, the majority of people have some kind of health problems resulting from congenital genetic mutations (over 6000 diseases have been associated to genes, https://www.omim.org/statistics/geneMap) and most genetic disorders are rare and only incompletely understood. The vision and techniques applied to the synthesis of genomes may help to address unmet medical needs from a chromosome and genome-scale perspective. In this chapter, we address the potential therapy of genetic diseases from a different outlook, in which we no longer focus on small gene corrections but on higher-order tools for genome manipulation. These will play a crucial role in the next years, as they prelude to a much deeper understanding of the architecture of the human genome and a more accurate modeling of human diseases, offering new therapeutic opportunities.

Content and Performance of the MiniMUGA Genotyping Array: A New Tool To Improve Rigor and Reproducibility in Mouse Research.

The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research.

Risk stratification in primary sclerosing cholangitis.

Primary Sclerosing Cholangitis (PSC) is a chronic liver disorder commonly affecting young patients and associated with uncertain prognosis and elevated risk of end-stage liver disease and hepatobiliary cancer. Rate of progression in PSC is heterogeneous and accurately predicting the disease course is of paramount importance to clinical practice and interventional trial design. So far, efforts have brought to the development of models looking at short-to-middle-term outcome using composite models including clinical, laboratory, radiological and histological parameters with limited performance. In the era of whole genome sequencing and digital innovation, the time is ripe for the development of stratified medicine in PSC. Efforts should be directed toward developing wellphenotyped cohorts of patients with longitudinal follow-up across sustained periods of time, application of novel image-processing technology, and biomarker discovery using multi-omics platforms.

Ovarian cancer risk assessment in the era of next-generation sequencing.

Ovarian cancer is one of the cancers most influenced by hereditary factors. Testing for hereditary susceptibility genes is recommended for every woman with epithelial ovarian cancer (EOC). Pathogenic germline variants in BRCA1 and BRCA2 genes are responsible for a substantial fraction of hereditary ovarian cancer. However, alterations in other genes, such as BRIP1, RAD51C, RAD51D, and mismatch repair genes, also enhance ovarian cancer risk. Other genes may also participate in ovarian carcinogenesis, but their role as ovarian cancer susceptibility genes still needs to be clarified. With several genes involved, the complexity of genetic testing increases. In this context, next-generation sequencing (NGS) allows testing for multiple genes simultaneously, with rapid turn-around time. However, the incorporation of this technology into clinical practice faces some challenges. In this review, we will discuss the ovarian cancer risk assessment in the era of NGS.

Exploring systematic biases, rooting methods and morphological evidence to unravel the evolutionary history of the genus Ficus (Moraceae).

Despite many attempts in the Sanger sequencing era, the phylogeny of fig trees remains unresolved, which limits our ability to analyze the evolution of key traits that may have contributed to their evolutionary and ecological success. We used restriction-site-associated DNA sequencing (c. 420kb) and 102 morphological characters to elucidate the relationships between 70 species of Ficus. To increase phylogenetic information for higher-level relationships, we targeted conserved regions and assembled paired reads into long loci to enable the retrieval of homologous loci in outgroup genomes. We compared morphological and molecular results to highlight discrepancies and reveal possible inference bias. For the first time, we recovered a monophyletic subgenus Urostigma (stranglers) and a clade with all gynodioecious Ficus. However, we show, with a new approach based on iterative principal component analysis, that it is not (and will probably never be) possible to homogenize evolutionary rates and GC content for all taxa before phylogenetic inference. Four competing positions for the root of the molecular tree are possible. The placement of section Pharmacosycea as sister to other fig trees is not supported by morphological data and considered a result of a long-branch attraction artefact to the outgroups. Regarding morphological features and indirect evidence from the pollinator tree of life, the topology that divides Ficus into monoecious versus gynodioecious species appears most plausible. It seems most likely that the ancestor of fig trees was a freestanding tree and active pollination is inferred as the ancestral state, contrary to previous hypotheses. However, ambiguity remains on the ancestral breeding system. Despite morphological plasticity, we advocate restoring a central role to morphology in our understanding of the evolution of Ficus, as it can help detect systematic errors that appear more pronounced with larger molecular datasets.

Liquid‐based shaking of core needle biopsy samples for the molecular characterisation of tumours: A fallback in cytopathology

Cytological specimens may be the ideal source of nucleic acids for the molecular characterization of tumors in the next generation sequencing (NGS) era. Liquid‐based shaking of core needle biopsy samples could enhance the diagnostic yield, allowing additional material to be examined in parallel with histopathology.

Examination of Clinical and Molecular Characteristics and Treatment Patterns of Adolescent and Young Adult (AYA) Patients with Chronic Lymphocytic Leukemia

Examination of Clinical and Molecular Characteristics and Treatment Patterns of Adolescent and Young Adult (AYA) Patients with Chronic Lymphocytic Leukemia

Nimpress brings polygenic scores to the sequencing era

Nimpress brings polygenic scores to the sequencing era

Motley Crew: Overview of the Currently Available Phage Diversity.

The first complete genome that was sequenced at the beginning of the sequencing era was that of a phage, since then researchers throughout the world have been steadily describing and publishing genomes from a wide array of phages, uncovering the secrets of the most abundant and diverse biological entities known to man. Currently, we are experiencing an unprecedented rate of novel bacteriophage discovery, which can be seen from the fact that the amount of complete bacteriophage genome entries in public sequence repositories has more than doubled in the past 3 years and is steadily growing without showing any sign of slowing down. The amount of publicly available phage genome-related data can be overwhelming and has been summarized in literature before but quickly becomes out of date. Thus, the aim of this paper is to briefly outline currently available phage diversity data for public acknowledgment that could possibly encourage and stimulate future “depth” studies of particular groups of phages or their gene products.

Correlating Neuroimaging and CNVs Data: 7 Years of Cytogenomic Microarray Analysis on Patients Affected by Neurodevelopmental Disorders.

The aim of this study was to evaluate the relationship between neurodevelopmental disorders, brain anomalies, and copy number variations (CNVs) and to estimate the diagnostic potential of cytogenomical microarray analysis (CMA) in individuals neuroradiologically characterized with intellectual developmental disorders (IDDs) isolated or associated with autism spectrum disorders (ASDs) and epilepsy (EPI), all of which were identified as a "synaptopathies." We selected patients who received CMA and brain magnetic resonance imaging (MRI) over a 7-year period. We divided them into four subgroups: IDD, IDD + ASD, IDD + EPI, and IDD + ASD + EPI. The diagnostic threshold of CMA was 16%. The lowest detection rate for both CMA and brain anomalies was found in IDD + ASD, while MRI was significantly higher in IDD and IDD + EPI subgroups. CMA detection rate was significantly higher in patients with brain anomalies, so CMA may be even more appropriate in patients with pathological MRI, increasing the diagnostic value of the test. Conversely, positive CMA in IDD patients should require an MRI assessment, which is more often associated with brain anomalies. Posterior fossa anomalies, both isolated and associated with other brain anomalies, showed a significantly higher rate of CMA positive results and of pathogenic CNVs. In the next-generation sequencing era, our study confirms once again the relevant diagnostic output of CMA in patients with IDD, either isolated or associated with other comorbidities. Since more than half of the patients presented brain anomalies in this study, we propose that neuroimaging should be performed in such cases, particularly in the presence of genomic imbalances.