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Asset Tag: Review

April 21, 2020  |  

Whole-Genome Alignment and Comparative Annotation.

Rapidly improving sequencing technology coupled with computational developments in sequence assembly are making reference-quality genome assembly economical. Hundreds of vertebrate genome assemblies are now publicly available, and projects are being proposed to sequence thousands of additional species in the next few years. Such dense sampling of the tree of life should give an unprecedented new understanding of evolution and allow a detailed determination of the events that led to the wealth of biodiversity around us. To gain this knowledge, these new genomes must be compared through genome alignment (at the sequence level) and comparative annotation (at the gene level). However, different alignment and annotation methods have different characteristics; before starting a comparative genomics analysis, it is important to understand the nature of, and biases and limitations inherent in, the chosen methods. This review is intended to act as a technical but high-level overview of the field that should provide this understanding. We briefly survey the state of the genome alignment and comparative annotation fields and potential future directions for these fields in a new, large-scale era of comparative genomics.

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April 21, 2020  |  

Current advances in HIV vaccine preclinical studies using Macaque models.

The macaque simian or simian/human immunodeficiency virus (SIV/SHIV) challenge model has been widely used to inform and guide human vaccine trials. Substantial advances have been made recently in the application of repeated-low-dose challenge (RLD) approach to assess SIV/SHIV vaccine efficacies (VE). Some candidate HIV vaccines have shown protective effects in preclinical studies using the macaque SIV/SHIV model but the model’s true predictive value for screening potential HIV vaccine candidates needs to be evaluated further. Here, we review key parameters used in the RLD approach and discuss their relevance for evaluating VE to improve preclinical studies of candidate HIV vaccines.Crown Copyright © 2019. Published by Elsevier Ltd. All rights reserved.

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April 21, 2020  |  

Effective approaches to study the plant-root knot nematode interaction.

Plant-parasitic nematodes cause major agricultural losses worldwide. Examining the molecular mechanisms underlying plant-nematode interactions and how plants respond to different invading pathogens is attracting major attention to reduce the expanding gap between agricultural production and the needs of the growing world population. This review summarizes the most recent developments in plant-nematode interactions and the diverse approaches used to improve plant resistance against root knot nematode (RKN). We will emphasize the recent rapid advances in genome sequencing technologies, small interfering RNA techniques (RNAi) and targeted genome editing which are contributing to the significant progress in understanding the plant-nematode interaction mechanisms. Also, molecular approaches to improve plant resistance against nematodes are considered.Copyright © 2019 Elsevier Masson SAS. All rights reserved.

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April 21, 2020  |  

A Rigorous Interlaboratory Examination of the Need to Confirm Next-Generation Sequencing-Detected Variants with an Orthogonal Method in Clinical Genetic Testing.

Orthogonal confirmation of next-generation sequencing (NGS)-detected germline variants is standard practice, although published studies have suggested that confirmation of the highest-quality calls may not always be necessary. The key question is how laboratories can establish criteria that consistently identify those NGS calls that require confirmation. Most prior studies addressing this question have had limitations: they have been generally of small scale, omitted statistical justification, and explored limited aspects of underlying data. The rigorous definition of criteria that separate high-accuracy NGS calls from those that may or may not be true remains a crucial issue. We analyzed five reference samples and over 80,000 patient specimens from two laboratories. Quality metrics were examined for approximately 200,000 NGS calls with orthogonal data, including 1662 false positives. A classification algorithm used these data to identify a battery of criteria that flag 100% of false positives as requiring confirmation (CI lower bound, 98.5% to 99.8%, depending on variant type) while minimizing the number of flagged true positives. These criteria identify false positives that the previously published criteria miss. Sampling analysis showed that smaller data sets resulted in less effective criteria. Our methodology for determining test- and laboratory-specific criteria can be generalized into a practical approach that can be used by laboratories to reduce the cost and time burdens of confirmation without affecting clinical accuracy. Copyright © 2019 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

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April 21, 2020  |  

Natural product drug discovery in the genomic era: realities, conjectures, misconceptions, and opportunities.

Natural product discovery from microorganisms provided important sources for antibiotics, anti-cancer agents, immune-modulators, anthelminthic agents, and insecticides during a span of 50 years starting in the 1940s, then became less productive because of rediscovery issues, low throughput, and lack of relevant new technologies to unveil less abundant or not easily detected drug-like natural products. In the early 2000s, it was observed from genome sequencing that Streptomyces species encode about ten times as many secondary metabolites as predicted from known secondary metabolomes. This gave rise to a new discovery approach-microbial genome mining. As the cost of genome sequencing dropped, the numbers of sequenced bacteria, fungi and archaea expanded dramatically, and bioinformatic methods were developed to rapidly scan whole genomes for the numbers, types, and novelty of secondary metabolite biosynthetic gene clusters. This methodology enabled the identification of microbial taxa gifted for the biosynthesis of drug-like secondary metabolites. As genome sequencing technology progressed, the realities relevant to drug discovery have emerged, the conjectures and misconceptions have been clarified, and opportunities to reinvigorate microbial drug discovery have crystallized. This perspective addresses these critical issues for drug discovery.

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April 21, 2020  |  

Smashing Barriers in Biolistic Plant Transformation.

A foundation of modern biotechnology is the ability to stably introduce foreign DNA into an organism. The two most widely used methods, Agrobacterium-mediated transformation and biolistics, are both steeped in a rich history of creative exploration into the molecular unknown. Agrobacterium research accelerated in the early 1970s, particularly with the discovery of the large Ti (tumor-inducing) plasmid of Agrobacterium that contained a region of transfer DNA (T-DNA). Culturing plant calli in autoclaved jelly jars, and long before the advent of PCR, Southern blots were first used to show that T-DNA fragments could stably integrate into the nuclear genome (Chilton et al., 1980; Chilton, 2001). On the other hand, the first manufactured biolistic “gene gun” was an actual gun; it shot a blank .22 caliber cartridge loaded with DNA-coated tungsten shards to integrate foreign DNA into the nuclear genome. While it has long been known that biolistic transformation violently integrates DNA in a largely random, unpredictable and imprecise way, the cellular mechanisms of damage repair and successful integration remain a complicated issue to disentangle.

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April 21, 2020  |  

A Look to the Future: Pharmacogenomics and Data Technologies of Today and Tomorrow

The ability to measure chemical and physiologic states in tandem with good experimental design has enabled the discovery and characterization of a plethora of gene–drug interactions. Recent advances in methods to measure organic molecules and phenotypes, describe clinical states, and reason across federated data offer an increasingly precise set of technologies for pharmacogenomics discovery and clinical translation.

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April 21, 2020  |  

Engineering and modification of microbial chassis for systems and synthetic biology.

Engineering and modifying synthetic microbial chassis is one of the best ways not only to unravel the fundamental principles of life but also to enhance applications in the health, medicine, agricultural, veterinary, and food industries. The two primary strategies for constructing a microbial chassis are the top-down approach (genome reduction) and the bottom-up approach (genome synthesis). Research programs on this topic have been funded in several countries. The ‘Minimum genome factory’ (MGF) project was launched in 2001 in Japan with the goal of constructing microorganisms with smaller genomes for industrial use. One of the best examples of the results of this project is E. coli MGF-01, which has a reduced-genome size and exhibits better growth and higher threonine production characteristics than the parental strain [1]. The ‘cell factory’ project was carried out from 1998 to 2002 in the Fifth Framework Program of the EU (European Union), which tried to comprehensively understand microorganisms used in the application field. One of the outstanding results of this project was the elucidation of proteins secreted by Bacillus subtilis, which was summarized as the ‘secretome’ [2]. The GTL (Genomes to Life) program began in 2002 in the United States. In this program, researchers aimed to create artificial cells both in silico and in vitro, such as the successful design and synthesis of a minimal bacterial genome by John Craig Venter’s group [3]. This review provides an update on recent advances in engineering, modification and application of synthetic microbial chassis, with particular emphasis on the value of learning about chassis as a way to better understand life and improve applications.

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April 21, 2020  |  

Computational aspects underlying genome to phenome analysis in plants.

Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high-throughput plant phenotyping is becoming widely adopted in the plant community, promising to alleviate the phenotypic bottleneck. While these technological breakthroughs are significantly accelerating quantitative trait locus (QTL) and causal gene identification, challenges to enable even more sophisticated analyses remain. In particular, care needs to be taken to standardize, describe and conduct experiments robustly while relying on plant physiology expertise. In this article, we review the state of the art regarding genome assembly and the future potential of pangenomics in plant research. We also describe the necessity of standardizing and describing phenotypic studies using the Minimum Information About a Plant Phenotyping Experiment (MIAPPE) standard to enable the reuse and integration of phenotypic data. In addition, we show how deep phenotypic data might yield novel trait-trait correlations and review how to link phenotypic data to genomic data. Finally, we provide perspectives on the golden future of machine learning and their potential in linking phenotypes to genomic features. © 2018 The Authors The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

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April 21, 2020  |  

DNA methylation analysis.

DNA methylation is a process by which methyl groups are added to cytosine or adenine. DNA methylation can change the activity of the DNA molecule without changing the sequence. Methylation of 5-methylcytosine (5mC) is widespread in both eukaryotes and prokaryotes, and it is a very important epigenetic modification event, which can regulate gene activity and influence a number of key processes such as genomic imprinting, cell differentiation, transcriptional regulation, and chromatin remodeling. Profiling DNA methylation across the genome is critical to understanding the influence of methylation in normal biology and diseases including cancer. Recent discoveries of 5-methylcytosine (5mC) oxidation derivatives including 5-hydroxymethylcytosine (5hmC), 5-formylcytsine (5fC), and 5-carboxycytosine (5caC) in mammalian genome further expand our understanding of the methylation regulation. Genome-wide analyses such as microarrays and next-generation sequencing technologies have been used to assess large fractions of the methylome. A number of different quantitative approaches have also been established to map the DNA epigenomes with single-base resolution, as represented by the bisulfite-based methods, such as classical bisulfite sequencing, pyrosequencing etc. These methods have been used to generate base-resolution maps of 5mC and its oxidation derivatives in genomic samples. The focus of this chapter is to provide the methodologies that have been developed to detect the cytosine derivatives in the genomic DNA.

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April 21, 2020  |  

Deciphering bacterial epigenomes using modern sequencing technologies.

Prokaryotic DNA contains three types of methylation: N6-methyladenine, N4-methylcytosine and 5-methylcytosine. The lack of tools to analyse the frequency and distribution of methylated residues in bacterial genomes has prevented a full understanding of their functions. Now, advances in DNA sequencing technology, including single-molecule, real-time sequencing and nanopore-based sequencing, have provided new opportunities for systematic detection of all three forms of methylated DNA at a genome-wide scale and offer unprecedented opportunities for achieving a more complete understanding of bacterial epigenomes. Indeed, as the number of mapped bacterial methylomes approaches 2,000, increasing evidence supports roles for methylation in regulation of gene expression, virulence and pathogen-host interactions.

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April 21, 2020  |  

Harnessing genomic information for livestock improvement.

The world demand for animal-based food products is anticipated to increase by 70% by 2050. Meeting this demand in a way that has a minimal impact on the environment will require the implementation of advanced technologies, and methods to improve the genetic quality of livestock are expected to play a large part. Over the past 10 years, genomic selection has been introduced in several major livestock species and has more than doubled genetic progress in some. However, additional improvements are required. Genomic information of increasing complexity (including genomic, epigenomic, transcriptomic and microbiome data), combined with technological advances for its cost-effective collection and use, will make a major contribution.

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April 21, 2020  |  

The role of genomic structural variation in the genetic improvement of polyploid crops

Many of our major crop species are polyploids, containing more than one genome or set of chromosomes. Polyploid crops present unique challenges, including difficulties in genome assembly, in discriminating between multiple gene and sequence copies, and in genetic mapping, hindering use of genomic data for genetics and breeding. Polyploid genomes may also be more prone to containing structural variation, such as loss of gene copies or sequences (presence–absence variation) and the presence of genes or sequences in multiple copies (copy-number variation). Although the two main types of genomic structural variation commonly identified are presence–absence variation and copy-number variation, we propose that homeologous exchanges constitute a third major form of genomic structural variation in polyploids. Homeologous exchanges involve the replacement of one genomic segment by a similar copy from another genome or ancestrally duplicated region, and are known to be extremely common in polyploids. Detecting all kinds of genomic structural variation is challenging, but recent advances such as optical mapping and long-read sequencing offer potential strategies to help identify structural variants even in complex polyploid genomes. All three major types of genomic structural variation (presence–absence, copy-number, and homeologous exchange) are now known to influence phenotypes in crop plants, with examples of flowering time, frost tolerance, and adaptive and agronomic traits. In this review, we summarize the challenges of genome analysis in polyploid crops, describe the various types of genomic structural variation and the genomics technologies and data that can be used to detect them, and collate information produced to date related to the impact of genomic structural variation on crop phenotypes. We highlight the importance of genomic structural variation for the future genetic improvement of polyploid crops.

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April 21, 2020  |  

Informatics for PacBio Long Reads.

In this article, we review the development of a wide variety of bioinformatics software implementing state-of-the-art algorithms since the introduction of SMRT sequencing technology into the field. We focus on the three major categories of development: read mapping (aligning to reference genomes), de novo assembly, and detection of structural variants. The long SMRT reads benefit all the applications, but they are achievable only through considering the nature of the long reads technology properly.

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