scholarly journals NGS comparison of Downy and Powdery mildew resistance genomic regions between 'Regent' and 'Red Globe'

2021 ◽  
Author(s):  
Carel Jacobus van Heerden ◽  
Phylli Burger ◽  
Johan Theodorus Burger ◽  
Renée Prins
Keyword(s):  
Next Generation Sequencing ◽  
Powdery Mildew ◽  
Downy Mildew ◽  
Genetic Factors ◽  
Powdery Mildew Resistance ◽  
Negative Impact ◽  
Chromosome 15 ◽  
Genomic Regions ◽  
Per Gene ◽  
Generation Sequencing

Powdery and downy mildew have a large negative impact on grape production worldwide. Quantitative trait loci (QTL) mapping projects have identified several loci for the genetic factors responsible for resistance to these pathogens. Several of these studies have focused on the cultivar Regent, which carries the resistance loci to downy mildew on chromosome 18 (Rpv3), as well powdery mildew on chromosome 15 (Ren3, Ren9). Several other minor resistance loci have also been identified on other chromosomes. Here we report on the re-sequencing of the Regent and Red Globe (susceptible) genomes using next generation sequencing. While the genome of Regent has more SNP variants than Red Globe, the distribution of these variants across the two genomes is not the same, nor is it uniform. The variation per gene shows that some genes have higher SNP density than others and that the number of SNPs for a given gene is not always the same for the two cultivars. In this study, we investigate the effectiveness of studying the variation of non-synonymous to synonymous SNP ratio's between resistant and susceptible cultivars in the target QTL regions as a strategy to narrow down the number of likely candidate genes for Rpv3, Ren3 and Ren9.

scholarly journals Standard enrichment methods for targeted next-generation sequencing in high-repeat genomic regions

2013 ◽  
Vol 15 (11) ◽  
pp. 910-911 ◽  
Author(s):  
Patricia W. Mueller ◽  
Justine Lyons ◽  
Gregory Kerr ◽  
Chad P. Haase ◽  
R. Benjamin Isett
Keyword(s):  
Next Generation Sequencing ◽  
Next Generation ◽  
Targeted Next Generation Sequencing ◽  
Genomic Regions ◽  
Generation Sequencing ◽  
Enrichment Methods

scholarly journals AQMM: Enabling Absolute Quantification of Metagenome and Metatranscriptome

2017 ◽  
Author(s):  
Xiao-Tao Jiang ◽  
Ke Yu ◽  
Li-Guan Li ◽  
Xiao-Le Yin ◽  
An-Dong Li ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Experimental Design ◽  
Environmental Samples ◽  
Absolute Quantification ◽  
Relative Quantification ◽  
Quantification Method ◽  
Bioinformatic Approach ◽  
Per Gene ◽  
Generation Sequencing ◽  
Microbial Functional Gene

AbstractMetatranscriptome has become increasingly important along with the application of next generation sequencing in the studies of microbial functional gene activity in environmental samples. However, the quantification of target active gene is hindered by the current relative quantification methods, especially when tracking the sharp environmental change. Great needs are here for an easy-to-perform method to obtain the absolute quantification. By borrowing information from the parallel metagenome, an absolute quantification method for both metagenomic and metatranscriptomic data to per gene/cell/volume/gram level was developed. The effectiveness of AQMM was validated by simulated experiments and was demonstrated with a real experimental design of comparing activated sludge with and without foaming. Our method provides a novel bioinformatic approach to fast and accurately conduct absolute quantification of metagenome and metatranscriptome in environmental samples. The AQMM can be accessed from https://github.com/biofuture/aqmm.

scholarly journals Using Deep Learning for Gene Detection and Classification in Raw Nanopore Signals

2021 ◽  
Author(s):  
Marketa Nykrynova ◽  
Vojtech Barton ◽  
Roman Jakubicek ◽  
Matej Bezdicek ◽  
Martina Lengerova ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Clinical Practice ◽  
Next Generation Sequencing ◽  
Nanopore Sequencing ◽  
Library Preparation ◽  
Gene Detection ◽  
Intergenic Regions ◽  
Genomic Regions ◽  
Generation Sequencing

Recently, nanopore sequencing has come to the fore as library preparation is rapid and simple, sequencing can be done almost anywhere, and longer reads are obtained than with next-generation sequencing. The main bottleneck still lies in data postprocessing which consists of basecalling, genome assembly, and localizing significant sequences, which is time consuming and computationally demanding, thus prolonging delivery of crucial results for clinical practice. Here, we present a neural network-based method capable of detecting and classifying specific genomic regions already in raw nanopore signals - squiggles. Therefore, the basecalling process can be omitted entirely as the raw signals of significant genes, or intergenic regions can be directly analysed, or if the nucleotide sequences are required, the identified squiggles can be basecalled, preferably to others. The proposed neural network could be included directly in the sequencing run, allowing real-time squiggle processing.

scholarly journals A mild form of Mucopolysaccharidosis IIIB diagnosed with targeted next-generation sequencing of linked genomic regions

2011 ◽  
Vol 20 (1) ◽  
pp. 58-63 ◽  
Author(s):  
Kaja K Selmer ◽  
Gregor D Gilfillan ◽  
Petter Strømme ◽  
Robert Lyle ◽  
Timothy Hughes ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Next Generation ◽  
Mild Form ◽  
Targeted Next Generation Sequencing ◽  
Genomic Regions ◽  
Generation Sequencing

Comprehensive next-generation sequencing to portray distinctive molecular characteristics of hypermutant lung cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15255-e15255
Author(s):  
Hongbin Zhang ◽  
Yuan Wang ◽  
Qiaoxia Ji ◽  
Hongmei Cai ◽  
Xiangcun Liang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Next Generation Sequencing ◽  
Genetic Factors ◽  
Brca1 Gene ◽  
Driver Mutations ◽  
Molecular Characteristics ◽  
Next Generation ◽  
Molecular Features ◽  
Genetic Profiles ◽  
Generation Sequencing

e15255 Background: Tumor mutation burden (TMB) has been confirmed to predict the sensitivity to immunotherapy across multiple tumor types. Multiple genetic factors have been confirmed to increase the level of TMB, such as mutations in DNA damage repair (DDR) genes, POLE/POLD1, and high microsatellite instability (MSI). However, the extent that these factors contribute to hypermutation in lung cancer has not been fully investigated. Methods: We retrospectively reviewed the genetic profiles of 1000 lung cancer patients (pts) who underwent 1021-panel matched tumor-normal next-generation sequencing using tumor tissue samples and peripheral blood. Their TMB status were analyzed to determine the threshold of hypermutation. The clinicopathological characteristics, genetic profiles and genetic factors related to hypermutation were investigated for the pts in hypermutant cohort. Results: The threshold of hypermutation was determined as 19 muts/MB (top 5% in 1000 pts). As a result, 53 pts were included in the hypermutant cohort. A total of 1725 nonsynonymous somatic variants in 506 genes were identified. The most frequently mutated genes included TP53 (88.7%), LRP1B (71.7%), MLL2 (35.8%), EPHA5 (34.0%), and FAT1 (34.0%). KRAS was mutated in 17% pts, whereas mutations in EGFR, BRAF, ERBB2, MET were identified less commonly. MSI-high was observed in 5 cases. A germline mutation in BRCA1 gene was identified in an adenocarcinoma patient. Compared to genetic profiles of non-small cell lung cancer from TCGA database, mutations in multiple DDR genes were enriched in the hypermutant cohort (Table). No known driver mutation in POLE/POLD1 was identified. Conclusions: MSI-high and mutations in DDR genes may be associated with high level of TMB, whereas POLE/POLD1 driver mutations may not be related to hypermutant lung cancer. Hypermutant lung cancer displays distinctive molecular features that may be used as complementary indicators to screening pts sensitive to immunotherapy. [Table: see text]

scholarly journals Association Study of Puberty-Related Candidate Genes in Chinese Female Population

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Gideon Omariba ◽  
Junhua Xiao
Keyword(s):  
Next Generation Sequencing ◽  
Association Study ◽  
Candidate Genes ◽  
Genetic Factors ◽  
Transition Period ◽  
Female Population ◽  
Number Of Genes ◽  
Puberty Onset ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Puberty is a transition period where a child transforms to an adult. Puberty can be affected by various genetic factors and environmental influences. In mammals, the regulation of puberty is enhanced by the hypothalamic-pituitary-gonadal axis (HPG axis). A number of genes such as GnRH, Kiss1, and GPR54 have been reported as key regulators of puberty onset. In this study, we have conducted an association study of puberty-related candidate genes in Chinese female population. Gene variations reported to be related with some traits in a population may not exist in others due to different genetic and ethnic backgrounds, hence the need for this kind of study. The genotyping of SNPs was based on multiplex PCR and the next-generation sequencing (NGS) platform of Illumina. We finally performed association study using PLINK software. Our results confirmed that SNPs rs34787247 in LIN28, rs74795793 and rs9347389 in OCT-1, and rs379202 and rs10491080 in ZEB1 genes showed a significant association with puberty. With the result, it is reasonable to conclude that these genes affect the process of puberty in Shanghai Chinese female population, yet the mechanism remains to be investigated by further study.

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