scholarly journals miR-208b Reduces the Expression of Kcnj5 in a Cardiomyocyte Cell Line

Biomedicines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 719
Author(s):  
Julia Hupfeld ◽  
Maximilian Ernst ◽  
Maria Knyrim ◽  
Stephanie Binas ◽  
Udo Kloeckner ◽  
...  
Keyword(s):  
Untranslated Region ◽  
Electrical Remodeling ◽  
Sequencing Data ◽  
Western Blots ◽  
Cardiovascular Pathology ◽  
Hypertrophic Response ◽  
Channel Dependent ◽  
Cardiac Excitation ◽  
The Impact ◽  
Generation Sequencing

MicroRNAs (miRs) contribute to different aspects of cardiovascular pathology, among them cardiac hypertrophy and atrial fibrillation. Cardiac miR expression was analyzed in a mouse model with structural and electrical remodeling. Next-generation sequencing revealed that miR-208b-3p was ~25-fold upregulated. Therefore, the aim of our study was to evaluate the impact of miR-208b on cardiac protein expression. First, an undirected approach comparing whole RNA sequencing data to miR-walk 2.0 miR-208b 3′-UTR targets revealed 58 potential targets of miR-208b being regulated. We were able to show that miR-208b mimics bind to the 3′ untranslated region (UTR) of voltage-gated calcium channel subunit alpha1 C and Kcnj5, two predicted targets of miR-208b. Additionally, we demonstrated that miR-208b mimics reduce GIRK1/4 channel-dependent thallium ion flux in HL-1 cells. In a second undirected approach we performed mass spectrometry to identify the potential targets of miR-208b. We identified 40 potential targets by comparison to miR-walk 2.0 3′-UTR, 5′-UTR and CDS targets. Among those targets, Rock2 and Ran were upregulated in Western blots of HL-1 cells by miR-208b mimics. In summary, miR-208b targets the mRNAs of proteins involved in the generation of cardiac excitation and propagation, as well as of proteins involved in RNA translocation (Ran) and cardiac hypertrophic response (Rock2).

scholarly journals Hidden biases in germline structural variant detection

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Michael M. Khayat ◽  
Sayed Mohammad Ebrahim Sahraeian ◽  
Samantha Zarate ◽  
Andrew Carroll ◽  
Huixiao Hong ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
False Negative ◽  
False Negative Rate ◽  
Next Generation Sequencing Data ◽  
Chinese Family ◽  
Next Generation ◽  
Sequencing Data ◽  
Structural Variations ◽  
The Impact ◽  
Generation Sequencing

Abstract Background Genomic structural variations (SV) are important determinants of genotypic and phenotypic changes in many organisms. However, the detection of SV from next-generation sequencing data remains challenging. Results In this study, DNA from a Chinese family quartet is sequenced at three different sequencing centers in triplicate. A total of 288 derivative data sets are generated utilizing different analysis pipelines and compared to identify sources of analytical variability. Mapping methods provide the major contribution to variability, followed by sequencing centers and replicates. Interestingly, SV supported by only one center or replicate often represent true positives with 47.02% and 45.44% overlapping the long-read SV call set, respectively. This is consistent with an overall higher false negative rate for SV calling in centers and replicates compared to mappers (15.72%). Finally, we observe that the SV calling variability also persists in a genotyping approach, indicating the impact of the underlying sequencing and preparation approaches. Conclusions This study provides the first detailed insights into the sources of variability in SV identification from next-generation sequencing and highlights remaining challenges in SV calling for large cohorts. We further give recommendations on how to reduce SV calling variability and the choice of alignment methodology.

scholarly journals Assessing the impact of mutations found in next generation sequencing data over human signaling pathways

2015 ◽  
Vol 43 (W1) ◽  
pp. W270-W275 ◽  
Author(s):  
Rosa D. Hernansaiz-Ballesteros ◽  
Francisco Salavert ◽  
Patricia Sebastián-León ◽  
Alejandro Alemán ◽  
Ignacio Medina ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Signaling Pathways ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
The Impact ◽  
Generation Sequencing

scholarly journals Development and Characterization of Microsatellite Markers for Rhododendron Purdomii Using Next-Generation Sequencing

2021 ◽  
Author(s):  
Ningning Zhang ◽  
Mengyun Qin ◽  
Shixin Zhu ◽  
Ziyang Huang ◽  
Hao Dong ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Microsatellite Markers ◽  
Central China ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Information Index ◽  
Disturbance Management ◽  
The Impact ◽  
Generation Sequencing

Abstract Rhododendron purdomii, an endangered ornamental species endemic to the Qinling Mountains, is an important component of montane ecosystem in central China. Due to the impact of climate change and human disturbance, management and conservation of this species are in urgent needs. In this study, we developed 13 novel microsatellite markers for R. purdomii based on next-generation sequencing data, and tested these markers’ utility in congeneric species R. concinnum. For the 13 microsatellite markers in three R. purdomii populations, number of alleles ranged from two to 12, number of effective alleles was from 1.000 to 8.892, Shannon’s information index was from 0.000 to 2.320, and the observed and expected heterozygosity were from 0.000 to 1.000 and from 0.000 to 0.888, respectively. Cross-species amplification for R. concinnum indicated eight microsatellite loci were successfully amplified and polymorphic. The microsatellite markers developed in this study will provide opportunities for examining the genetic diversity and population structure of R. purdomii and contribute to the effective conservation of this species.

IsoDetect: Detection of splice isoforms from third generation long reads based on short feature sequences

2020 ◽  
Vol 15 ◽  
Author(s):  
Hongdong Li ◽  
Wenjing Zhang ◽  
Yuwen Luo ◽  
Jianxin Wang
Keyword(s):  
Sequence Similarity ◽  
Detection Methods ◽  
Sequence Information ◽  
Third Generation ◽  
Sequencing Data ◽  
Splice Isoforms ◽  
Third Generation Sequencing ◽  
Long Reads ◽  
Feature Sequence ◽  
Generation Sequencing

Aims: Accurately detect isoforms from third generation sequencing data. Background: Transcriptome annotation is the basis for the analysis of gene expression and regulation. The transcriptome annotation of many organisms such as humans is far from incomplete, due partly to the challenge in the identification of isoforms that are produced from the same gene through alternative splicing. Third generation sequencing (TGS) reads provide unprecedented opportunity for detecting isoforms due to their long length that exceeds the length of most isoforms. One limitation of current TGS reads-based isoform detection methods is that they are exclusively based on sequence reads, without incorporating the sequence information of known isoforms. Objective: Develop an efficient method for isoform detection. Method: Based on annotated isoforms, we propose a splice isoform detection method called IsoDetect. First, the sequence at exon-exon junction is extracted from annotated isoforms as the “short feature sequence”, which is used to distinguish different splice isoforms. Second, we aligned these feature sequences to long reads and divided long reads into groups that contain the same set of feature sequences, thereby avoiding the pair-wise comparison among the large number of long reads. Third, clustering and consensus generation are carried out based on sequence similarity. For the long reads that do not contain any short feature sequence, clustering analysis based on sequence similarity is performed to identify isoforms. Result: Tested on two datasets from Calypte Anna and Zebra Finch, IsoDetect showed higher speed and compelling accuracy compared with four existing methods. Conclusion: IsoDetect is a promising method for isoform detection. Other: This paper was accepted by the CBC2019 conference.

scholarly journals NGSremix: A software tool for estimating pairwise relatedness between admixed individuals from next-generation sequencing data

2021 ◽  
Author(s):  
Anne Krogh Nøhr ◽  
Kristian Hanghøj ◽  
Genis Garcia Erill ◽  
Zilong Li ◽  
Ida Moltke ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Genetic Research ◽  
Likelihood Estimation ◽  
Software Tool ◽  
Estimation Methods ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Ngs Data ◽  
Generation Sequencing

Abstract Estimation of relatedness between pairs of individuals is important in many genetic research areas. When estimating relatedness, it is important to account for admixture if this is present. However, the methods that can account for admixture are all based on genotype data as input, which is a problem for low-depth next-generation sequencing (NGS) data from which genotypes are called with high uncertainty. Here we present a software tool, NGSremix, for maximum likelihood estimation of relatedness between pairs of admixed individuals from low-depth NGS data, which takes the uncertainty of the genotypes into account via genotype likelihoods. Using both simulated and real NGS data for admixed individuals with an average depth of 4x or below we show that our method works well and clearly outperforms all the commonly used state-of-the-art relatedness estimation methods PLINK, KING, relateAdmix, and ngsRelate that all perform quite poorly. Hence, NGSremix is a useful new tool for estimating relatedness in admixed populations from low-depth NGS data. NGSremix is implemented in C/C ++ in a multi-threaded software and is freely available on Github https://github.com/KHanghoj/NGSremix.

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