Next generation sequencing and its applications

Gupta, Anuj; Gupta, UD

doi:10.1016/b978-0-12-811710-1.00018-5

Cited by 14 publications

(17 citation statements)

References 31 publications

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“…The first-generation sequencing technology is based on the chain termination method developed by Sanger and Coulson in 1975 and was used to sequence the first deoxyribonucleic acid (DNA) genome of the bacteriophage φX174 with a total length of 5,375 bases in 1977 (Sanger et al, 1977;Heather and Chain, 2016). After years of improvements of Sanger's dideoxy sequencing method, Applied Biosystems (today a brand of Thermo Fisher Scientific) launched the first automated sequencer (AB370) in 1987, which uses capillary electrophoresis for sequencing to this day (Kulski, 2016;Gupta and Gupta, 2020). Sanger sequencing has a read length of up to 1,000 base pairs with 99.999% accuracy (Kulski, 2016).…”

Section: (A) First-generation Sequencing (Also Addressed As Sanger Sequencing)mentioning

confidence: 99%

“…It is based on 2-nucleotide sequencing-by-ligation reaction, by sequential annealing of probes to the template and their subsequent ligation. The advantage of this method is its high accuracy by interrogating each base twice (Gupta and Gupta, 2020). The major disadvantages are the short read lengths (∼50-75 base pairs of ∼99.94% accuracy) (Wong et al, 2019), the very long run times of 7-14 days and the additional need for extra computationally steps for raw data conversion (Liu et al, 2012;Kulski, 2016).…”

Section: (B) Second-generation Sequencing (Also Addressed As Nextgeneration Sequencing)mentioning

confidence: 99%

“…The clonally enriched DNA template for sequencing is generated by PCR bridge amplification that generate clusters of molecules bound on a flow cell (Goodwin et al, 2016). The output of sequencing data per run is higher, costs are lower, and run times are moderately faster than most other systems (up to 3 days), but in contrast read lengths being shorter (up to 300 base pairs) (Gupta and Gupta, 2020).…”

Section: (B) Second-generation Sequencing (Also Addressed As Nextgeneration Sequencing)mentioning

confidence: 99%

“…For sequencing, the single-stranded DNA template will be linked to the immobilized DNA polymerase, whereupon fluorescently labeled nucleotides are incorporated into the growing strand within the well (Goodwin et al, 2016;Heather and Chain, 2016). Cameras continuously monitor the wells as a series of observed pulses that are converted into single molecular tracks representing the template sequences (Gupta and Gupta, 2020). Because all four nucleotides are added simultaneously and measured in real time, the speed of sequencing is much faster compared to technologies in which individual nucleotides are flushed in sequentially one after another (Heather and Chain, 2016;Wong et al, 2019).…”

Section: (B) Second-generation Sequencing (Also Addressed As Nextgeneration Sequencing)mentioning

confidence: 99%

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A Beginner’s Guide on Integrating *Omics Approaches to Study Marine Microbial Communities: Details and Discussions From Sample Collection to Bioinformatics Analysis

Wilms

2021

Front. Mar. Sci.

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The variety of Earth’s organisms is manifold. However, it is the small-scale marine community that makes the world goes round. Microbial organisms of pro- and eukaryotic origin drive the carbon supply and nutrient cycling, thus are mediating the primary productivity within the world largest ecosystem called ocean. But due to the ocean’s great size and large number of biogeographically habitats, the total of microbial species can hardly be grabbed and therefore their functional roles not fully described. However, recent advances in high-throughput sequencing technologies are revolutionizing our understanding of the marine microbial diversity, ecology and evolution. Nowadays, research questions on species differentiation can be solved with genomic approaches such as metabarcoding, while transcriptomics offers the possibility to assign gene functions even to a single cell, e.g., single-cell transcriptomics. On the other hand, due to the diversified amount of sequencing data, the certainty of a data crisis is currently evolving. Scientists are forced to broaden their view on bioinformatics resources for analysis and data storage in from of, e.g., cloud services, to ensure the data’s exchangeability. Which is why time resources are now shifting toward solving data problems rather than answering the eco-evolutionary questions stated in the first place. This review is intended to provide exchange on *omics approaches and key points for discussions on data handling used to decipher the relevant diversity and functions of microbial organisms in the marine ecosystem.

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Section: (A) First-generation Sequencing (Also Addressed As Sanger Sequencing)mentioning

confidence: 99%

Section: (B) Second-generation Sequencing (Also Addressed As Nextgeneration Sequencing)mentioning

confidence: 99%

Section: (B) Second-generation Sequencing (Also Addressed As Nextgeneration Sequencing)mentioning

confidence: 99%

Section: (B) Second-generation Sequencing (Also Addressed As Nextgeneration Sequencing)mentioning

confidence: 99%

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A Beginner’s Guide on Integrating *Omics Approaches to Study Marine Microbial Communities: Details and Discussions From Sample Collection to Bioinformatics Analysis

Wilms

2021

Front. Mar. Sci.

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“…Transcriptome sequencing, also known as RNA sequencing (RNA-seq), is a technique used to explore and quantitatively describe the differences in gene types and expression levels at a global level [ 5 ]. It could also intuitively link changes at the gene level with phenotypic changes.…”

Section: Introductionmentioning

confidence: 99%

Transcriptome Analysis Reveals the Genes Involved in Growth and Metabolism in Muscovy Ducks

Wang

Xiao

Yang

et al. 2021

BioMed Research International

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Muscovy ducks are among the best meat ducks in the world. The objective of this study was to identify genes related to growth metabolism through transcriptome analysis of the ileal tissue of Muscovy ducks. Duck ileum samples with the highest (H group, n = 5 ) and lowest (L group, n = 5 ) body weight were selected from two hundred 70-day-old Muscovy ducks for transcriptome analysis by RNA sequencing. In the screening of differentially expressed genes (DEGs) between the H and L groups, a total of 602 DEGs with a fold change no less than 2 were identified, among which 285 were upregulated and 317 were downregulated. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that glutathione metabolism, pyrimidine metabolism, and protein digestion and absorption processes played a vital role in regulating growth and metabolism. The results showed that 7 genes related to growth and metabolism, namely, ANPEP, ENPEP, UPP1, SLC2A2, SLC6A19, NME4, and LOC106034733, were significantly expressed in group H, which was consistent with the phenotype results. The validation of these 7 genes using real-time quantitative PCR results indicated that the expression level of ENPEP was significantly different between the H and L groups ( P < 0.05 ). This study provides a theoretical basis for exploring the influence of the ileum on growth and metabolism in ducks.

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