scholarly journals Pair-wise Comparison Analysis for Multiple Pool-seq: an efficient method identified anthocyanin biosynthesis genes in rice pericarp

2019 ◽  
Author(s):  
Xinghai Yang ◽  
Xiuzhong Xia ◽  
Zongqiong Zhang ◽  
Baoxuan Nong ◽  
Yu Zeng ◽  
...  
Keyword(s):  
Efficient Method ◽  
Complex Traits ◽  
High Throughput Sequencing ◽  
Anthocyanin Biosynthesis ◽  
Comparison Analysis ◽  
Sequencing Technologies ◽  
Filial Generation ◽  
Genomic Regions ◽  
Pair Wise Comparison ◽  
New Strategies

AbstractThe complex traits are derived from multiple genes and exhibit a large variety of phenotypes. High-throughput sequencing technologies have become the new strategies for mapping the important traits of crops. However, these methods have their own disadvantages and limitations. Here we introduced Pair-wise Comparison Analysis for Multiple Pool-seq (PCAMP) for mapping the candidate genomic regions involved in anthocyanin biosynthesis in rice pericarp. In this protocol, the second filial generation (F2) populations obtained by crossing two parents with different target traits were divided into n (n>=3) subpopulations according to their phenotypes. Thirty phenotypically identical individuals were selected from each subpopulation and DNA samples were extracted to form a pool for sequencing. Finally, we compared the SNP-index between every two Pool-seqs to map the candidate genomic regions. We applied PCAMP to analyse F2 populations and successfully identified five known genes and five new candidate genomic regions for anthocyanin biosynthesis in rice pericarp. These results demonstrate that PCAMP is an efficient new method for dissecting the complex traits of crops.

Genomic resources for improving food legume crops

2011 ◽  
Vol 150 (3) ◽  
pp. 289-318 ◽  
Author(s):  
J. KUMAR ◽  
A. PRATAP ◽  
R. K. SOLANKI ◽  
D. S. GUPTA ◽  
A. GOYAL ◽  
...  
Keyword(s):  
Complex Traits ◽  
Genetic Improvement ◽  
High Throughput Sequencing ◽  
Artificial Chromosome ◽  
Interactive Effects ◽  
Genetic Dissection ◽  
Genomic Resources ◽  
Sequencing Technologies ◽  
Food Legumes ◽  
Genomic Regions

SUMMARYFood legumes are the main source of dietary protein for a large part of the world's population, and also play an important role in maintaining soil fertility through nitrogen fixation. However, legume yields and production are often limited by large genotype×environment (G×E) interactions that influence the expression of agronomically important, complex quantitative traits. Consequently, genetic improvement has been slower than expected. Molecular marker technology enables genetic dissection of such complex traits, allowing breeders to identify genomic regions on the chromosome that have main effects or interactive effects. A number of genomic resources have been developed in several legume species during the last two decades, and provide a platform for exploiting marker technology. The present paper reviews the available genomic resources in food legumes: linkage maps, high-throughput sequencing technologies, expression sequence tag (EST) databases, genome sequences, DNA chips, targeting induced local lesions in genomes (TILLING), bacterial artificial chromosome (BAC) libraries and others. It also describes how these resources are being used to tag and map genes/quantitative trait loci (QTLs) for domesticated and other agronomically important traits. This information is important to genetic improvement efforts aiming at improving food and nutrition security worldwide.

scholarly journals Identification and Profiling of Conserved MicroRNAs in Different Developmental Stages of Crown Imperial (Fritillaria Imperialis L.) using High-throughput Sequencing

2021 ◽  
Author(s):  
Fereshteh Ahmadi Teshniz ◽  
Behrouz Shiran ◽  
Sadegh Mousavi-Fard ◽  
Hossein Fallahi ◽  
Bojana Banović Đeri
Keyword(s):  
Plant Species ◽  
Abiotic Stresses ◽  
Regulatory Networks ◽  
High Throughput Sequencing ◽  
Developmental Stages ◽  
Expression Patterns ◽  
Practical Application ◽  
Sequencing Technologies ◽  
New Strategies ◽  
Different Tissues

Abstract Novel strategies for improvement of plants’ ornamental and other properties relay on miRNA control of differential plant gene expression modulation. Still, in response to the same abiotic stresses, some conserved miRNA families show different expression patterns in different plant species. In parallel, the use of deep sequencing technologies reveals new levels of complexity of regulatory networks in plants through identification of new miRNAs. These are two major reasons why more studies are needed before envisioned new strategies may take their course in practical application domain. This research revealed 21 conserved miRNAs, matching 15 miRNA families, in Fritilaria imperialis. Among identified conserved miRNA families in crown imperial, miR166, miR169 and miR396 families were the most abundant ones. The expression of seven conserved miRNAs (Fim-miR156b, Fim-miR159, Fim-miR166a-5p, Fim-miR169d-5p, Fim-miR171c, Fim-miR393 and Fim-miR396e-3p) was further investigated in different tissues and three developmental stages, suggesting different roles these miRNAs have in growth and development of crown imperial. Gained knowledge from this research can open the door to find efficient ways to secure crown imperial survival, preservation and utilization and if proven useful may be applied in other plant species as well.

scholarly journals Detecting gene subnetworks under selection in biological pathways

2017 ◽  
Author(s):  
Alexandre Gouy ◽  
Joséphine T. Daub ◽  
Laurent Excoffier
Keyword(s):  
Complex Traits ◽  
Gene Networks ◽  
High Throughput Sequencing ◽  
Biological Pathways ◽  
General Idea ◽  
Human Populations ◽  
Sequencing Technologies ◽  
Genetic Components ◽  
Evolutionary Features ◽  
Gene Network Analysis

ABSTRACTAdvances in high throughput sequencing technologies have created a gap between data production and functional data analysis. Indeed, phenotypes result from interactions between numerous genes, but traditional methods treat loci independently, missing important knowledge brought by network-level emerging properties. Therefore, evidencing selection acting on multiple genes affecting the evolution of complex traits remains challenging. In this context, gene network analysis provides a powerful framework to study the evolution of adaptive traits and facilitates the interpretation of genome-wide data. To tackle this problem, we developed a method to analyse gene networks that is suitable to evidence polygenic selection. The general idea is to search biological pathways for subnetworks of genes that directly interact with each other and that present unusual evolutionary features. Subnetwork search is a typical combinatorial optimization problem that we solve using a simulated annealing approach. We have applied our methodology to find signals of adaptation to high-altitude in human populations. We show that this adaptation has a clear polygenic basis and is influenced by many genetic components. Our approach improves on classical tests for selection based on single genes by identifying both new candidate genes and new biological processes involved in adaptation to altitude.

scholarly journals Characterizing Promoter and Enhancer Sequences by a Deep Learning Method

2021 ◽  
Vol 12 ◽  
Author(s):  
Xin Zeng ◽  
Sung-Joon Park ◽  
Kenta Nakai
Keyword(s):  
Deep Learning ◽  
High Throughput Sequencing ◽  
Rna Stability ◽  
Predictive Performance ◽  
Regulatory Elements ◽  
Critical Determinant ◽  
Transcription Start Sites ◽  
Sequencing Technologies ◽  
Genomic Regions ◽  
Order Sequence

Promoters and enhancers are well-known regulatory elements modulating gene expression. As confirmed by high-throughput sequencing technologies, these regulatory elements are bidirectionally transcribed. That is, promoters produce stable mRNA in the sense direction and unstable RNA in the antisense direction, while enhancers transcribe unstable RNA in both directions. Although it is thought that enhancers and promoters share a similar architecture of transcription start sites (TSSs), how the transcriptional machinery distinctly uses these genomic regions as promoters or enhancers remains unclear. To address this issue, we developed a deep learning (DL) method by utilizing a convolutional neural network (CNN) and the saliency algorithm. In comparison with other classifiers, our CNN presented higher predictive performance, suggesting the overarching importance of the high-order sequence features, captured by the CNN. Moreover, our method revealed that there are substantial sequence differences between the enhancers and promoters. Remarkably, the 20–120 bp downstream regions from the center of bidirectional TSSs seemed to contribute to the RNA stability. These regions in promoters tend to have a larger number of guanines and cytosines compared to those in enhancers, and this feature contributed to the classification of the regulatory elements. Our CNN-based method can capture the complex TSS architectures. We found that the genomic regions around TSSs for promoters and enhancers contribute to RNA stability and show GC-biased characteristics as a critical determinant for promoter TSSs.

scholarly journals Reassortment of Genome Segments Creates Stable Lineages Among Strains of Orchid Fleck Virus Infecting Citrus in Mexico

2020 ◽  
Vol 110 (1) ◽  
pp. 106-120 ◽  
Author(s):  
Avijit Roy ◽  
Andrew L. Stone ◽  
Gabriel Otero-Colina ◽  
Gang Wei ◽  
Ronald H. Brlansky ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Sensu Stricto ◽  
Genome Segment ◽  
Rt Pcr ◽  
Sequence Comparisons ◽  
Orchid Fleck Virus ◽  
Reverse Transcription Pcr ◽  
Sequencing Technologies ◽  
Negative Sense

The genus Dichorhavirus contains viruses with bipartite, negative-sense, single-stranded RNA genomes that are transmitted by flat mites to hosts that include orchids, coffee, the genus Clerodendrum, and citrus. A dichorhavirus infecting citrus in Mexico is classified as a citrus strain of orchid fleck virus (OFV-Cit). We previously used RNA sequencing technologies on OFV-Cit samples from Mexico to develop an OFV-Cit–specific reverse transcription PCR (RT-PCR) assay. During assay validation, OFV-Cit–specific RT-PCR failed to produce an amplicon from some samples with clear symptoms of OFV-Cit. Characterization of this virus revealed that dichorhavirus-like particles were found in the nucleus. High-throughput sequencing of small RNAs from these citrus plants revealed a novel citrus strain of OFV, OFV-Cit2. Sequence comparisons with known orchid and citrus strains of OFV showed variation in the protein products encoded by genome segment 1 (RNA1). Strains of OFV clustered together based on host of origin, whether orchid or citrus, and were clearly separated from other dichorhaviruses described from infected citrus in Brazil. The variation in RNA1 between the original (now OFV-Cit1) and the new (OFV-Cit2) strain was not observed with genome segment 2 (RNA2), but instead, a common RNA2 molecule was shared among strains of OFV-Cit1 and -Cit2, a situation strikingly similar to OFV infecting orchids. We also collected mites at the affected groves, identified them as Brevipalpus californicus sensu stricto, and confirmed that they were infected by OFV-Cit1 or with both OFV-Cit1 and -Cit2. OFV-Cit1 and -Cit2 have coexisted at the same site in Toliman, Queretaro, Mexico since 2012. OFV strain-specific diagnostic tests were developed.

scholarly journals Application of Oxford Nanopore Technology to Plant Virus Detection

Viruses ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1424
Author(s):  
Lia W. Liefting ◽  
David W. Waite ◽  
Jeremy R. Thompson
Keyword(s):  
Plant Virus ◽  
High Throughput Sequencing ◽  
Virus Detection ◽  
Diagnostic Methods ◽  
Plant Virus Detection ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Virus Diagnostics ◽  
Post Entry ◽  
Read Accuracy

The adoption of Oxford Nanopore Technologies (ONT) sequencing as a tool in plant virology has been relatively slow despite its promise in more recent years to yield large quantities of long nucleotide sequences in real time without the need for prior amplification. The portability of the MinION and Flongle platforms combined with lowering costs and continued improvements in read accuracy make ONT an attractive method for both low- and high-scale virus diagnostics. Here, we provide a detailed step-by-step protocol using the ONT Flongle platform that we have developed for the routine application on a range of symptomatic post-entry quarantine and domestic surveillance plant samples. The aim of this methods paper is to highlight ONT’s feasibility as a valuable component to the diagnostician’s toolkit and to hopefully stimulate other laboratories towards the eventual goal of integrating high-throughput sequencing technologies as validated plant virus diagnostic methods in their own right.

scholarly journals Assessing genotyping errors in mammalian museum study skins using high-throughput genotyping-by-sequencing

2021 ◽  
Author(s):  
Stella C. Yuan ◽  
Eric Malekos ◽  
Melissa T. R. Hawkins
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Massively Parallel Sequencing ◽  
Massively Parallel ◽  
Museum Specimens ◽  
Museum Specimen ◽  
Genotyping Errors ◽  
Allelic Dropout ◽  
Parallel Sequencing ◽  
Sequencing Technologies

AbstractThe use of museum specimens held in natural history repositories for population and conservation genetic research is increasing in tandem with the use of massively parallel sequencing technologies. Short Tandem Repeats (STRs), or microsatellite loci, are commonly used genetic markers in wildlife and population genetic studies. However, they traditionally suffered from a host of issues including length homoplasy, high costs, low throughput, and difficulties in reproducibility across laboratories. Massively parallel sequencing technologies can address these problems, but the incorporation of museum specimen derived DNA suffers from significant fragmentation and exogenous DNA contamination. Combatting these issues requires extra measures of stringency in the lab and during data analysis, yet there have not been any high-throughput sequencing studies evaluating microsatellite allelic dropout from museum specimen extracted DNA. In this study, we evaluate genotyping errors derived from mammalian museum skin DNA extracts for previously characterized microsatellites across PCR replicates utilizing high-throughput sequencing. We found it useful to classify samples based on DNA concentration, which determined the rate by which genotypes were accurately recovered. Longer microsatellites performed worse in all museum specimens. Allelic dropout rates across loci were dependent on sample quantity, with high concentration museum specimens performing as well and recovering quality metrics nearly as high as the frozen tissue sample. Based on our results, we provide a set of best practices for quality assurance and incorporation of reliable genotypes from museum specimens.

scholarly journals Multi-omics approach to precision medicine for immune-mediated diseases

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Mineto Ota ◽  
Keishi Fujio
Keyword(s):  
Treatment Response ◽  
High Throughput Sequencing ◽  
Disease Risk ◽  
Clinical Information ◽  
Clinical Settings ◽  
Social Significance ◽  
Sequencing Technologies ◽  
Immune Mediated ◽  
Recent Innovation ◽  
Future Direction

AbstractRecent innovation in high-throughput sequencing technologies has drastically empowered the scientific research. Consequently, now, it is possible to capture comprehensive profiles of samples at multiple levels including genome, epigenome, and transcriptome at a time. Applying these kinds of rich information to clinical settings is of great social significance. For some traits such as cardiovascular diseases, attempts to apply omics datasets in clinical practice for the prediction of the disease risk have already shown promising results, although still under way for immune-mediated diseases. Multiple studies have tried to predict treatment response in immune-mediated diseases using genomic, transcriptomic, or clinical information, showing various possible indicators. For better prediction of treatment response or disease outcome in immune-mediated diseases, combining multi-layer information together may increase the power. In addition, in order to efficiently pick up meaningful information from the massive data, high-quality annotation of genomic functions is also crucial. In this review, we discuss the achievement so far and the future direction of multi-omics approach to immune-mediated diseases.

scholarly journals Profiling DNA Methylation Based on Next-Generation Sequencing Approaches: New Insights and Clinical Applications

Genes ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 429 ◽  
Author(s):  
Daniela Barros-Silva ◽  
C. Marques ◽  
Rui Henrique ◽  
Carmen Jerónimo
Keyword(s):  
Dna Methylation ◽  
Next Generation Sequencing ◽  
High Throughput Sequencing ◽  
Epigenetic Modification ◽  
Response To Therapy ◽  
Next Generation ◽  
Sequencing Technologies ◽  
Prognosis And Prediction ◽  
Novel Biomarkers ◽  
Generation Sequencing

DNA methylation is an epigenetic modification that plays a pivotal role in regulating gene expression and, consequently, influences a wide variety of biological processes and diseases. The advances in next-generation sequencing technologies allow for genome-wide profiling of methyl marks both at a single-nucleotide and at a single-cell resolution. These profiling approaches vary in many aspects, such as DNA input, resolution, coverage, and bioinformatics analysis. Thus, the selection of the most feasible method according with the project’s purpose requires in-depth knowledge of those techniques. Currently, high-throughput sequencing techniques are intensively used in epigenomics profiling, which ultimately aims to find novel biomarkers for detection, diagnosis prognosis, and prediction of response to therapy, as well as to discover new targets for personalized treatments. Here, we present, in brief, a portrayal of next-generation sequencing methodologies’ evolution for profiling DNA methylation, highlighting its potential for translational medicine and presenting significant findings in several diseases.

scholarly journals Detection of novel allelic variations in soybean mutant population using Tilling by Sequencing

2019 ◽  
Author(s):  
Reneth Millas ◽  
Mary Espina ◽  
CM Sabbir Ahmed ◽  
Angelina Bernardini ◽  
Ekundayo Adeleke ◽  
...  
Keyword(s):  
Fatty Acid ◽  
High Throughput ◽  
Reverse Genetics ◽  
High Throughput Sequencing ◽  
Fatty Acid Biosynthesis ◽  
Induced Mutations ◽  
Mutant Population ◽  
Sequencing Technologies ◽  
Allelic Variations ◽  
Tilling By Sequencing

ABSTRACTOne of the most important tools in genetic improvement is mutagenesis, which is a useful tool to induce genetic and phenotypic variation for trait improvement and discovery of novel genes. JTN-5203 (MG V) mutant population was generated using an induced ethyl methane sulfonate (EMS) mutagenesis and was used for detection of induced mutations in FAD2-1A and FAD2-1B genes using reverse genetics approach. Optimum concentration of EMS was used to treat 15,000 bulk JTN-5203 seeds producing 1,820 M2 population. DNA was extracted, normalized, and pooled from these individuals. Specific primers were designed from FAD2-1A and FAD2-1B genes that are involved in the fatty acid biosynthesis pathway for further analysis using next-generation sequencing. High throughput mutation discovery through TILLING-by-Sequencing approach was used to detect novel allelic variations in this population. Several mutations and allelic variations with high impacts were detected for FAD2-1A and FAD2-1B. This includes GC to AT transition mutations in FAD2-1A (20%) and FAD2-1B (69%). Mutation density for this population is estimated to be about 1/136kb. Through mutagenesis and high-throughput sequencing technologies, novel alleles underlying the mutations observed in mutants with reduced polyunsaturated fatty acids will be identified, and these mutants can be further used in breeding soybean lines with improved fatty acid profile, thereby developing heart-healthy-soybeans.

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