Toolkit/Illumina NovaSeq X Plus sequencing
Illumina NovaSeq X Plus sequencing
Also known as: Illumina NovaSeq X Plus platform
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
Sequencing of the samples was performed using Illumina NovaSeq X Plus platform.
Usefulness & Problems
Why this is useful
This platform was used to sequence oil palm leaf samples for RNA-seq analysis under cold treatment.; RNA-seq sample sequencing in cold-stress transcriptomics
Source:
This platform was used to sequence oil palm leaf samples for RNA-seq analysis under cold treatment.
Source:
RNA-seq sample sequencing in cold-stress transcriptomics
Problem solved
It provides the raw sequencing data needed to quantify transcriptomic responses to cold stress.; Generates sequencing reads for gene-expression analysis
Source:
It provides the raw sequencing data needed to quantify transcriptomic responses to cold stress.
Source:
Generates sequencing reads for gene-expression analysis
Problem links
Generates sequencing reads for gene-expression analysis
LiteratureIt provides the raw sequencing data needed to quantify transcriptomic responses to cold stress.
Source:
It provides the raw sequencing data needed to quantify transcriptomic responses to cold stress.
Published Workflows
Objective: To investigate physiological and genetic adaptations of oil palm seedlings to cold stress using fresh leaf samples collected across exposure durations.
Why it works: The study combines time-resolved physiological measurements with transcriptome profiling so that observable stress phenotypes and pathway-level gene-expression changes can be interpreted together under the same cold-treatment regime.
Stages
- 1.Cold treatment and time-course sampling(functional_characterization)
This stage establishes the perturbation and sampling framework needed to measure how cold stress responses change over time.
Selection: Expose oil palm seedlings to cold and collect fresh leaf samples across exposure durations for downstream physiological and genetic analysis.
- 2.Physiological parameter measurement(secondary_characterization)
This stage captures phenotypic consequences of cold stress that can be compared with gene-expression changes.
Selection: Measure antioxidant enzyme activity, ROS levels, photosynthetic pigment ratios, and photosynthetic efficiency under cold exposure.
- 3.RNA sequencing(functional_characterization)
This stage generates transcriptomic data for differential expression and pathway analysis.
Selection: Sequence leaf-sample transcriptomes using the Illumina NovaSeq X Plus platform.
- 4.Read quality filtering(decision_gate)
This stage filters raw reads before downstream analysis to improve data quality.
Selection: Remove adapter-containing reads, reads with >10% unidentified nucleotides, and reads where >50% of bases had Phred scores ≤20.
- 5.Reference-guided transcriptomic interpretation(secondary_characterization)
This stage converts filtered sequencing data into interpretable gene and pathway changes associated with cold stress.
Selection: Analyze expression against reference genome GCF_000442705.2 and identify DEGs and enriched pathways.
Steps
- 1.Subject oil palm seedlings to cold treatment
Induce cold stress for downstream physiological and transcriptomic analysis.
The perturbation must occur before any response measurements can be collected.
- 2.Collect fresh leaf samples across exposure durations
Capture time-resolved material for physiological and gene-expression analysis.
Sampling follows treatment so that duration-dependent responses can be measured.
- 3.Measure physiological stress-response parameters
Quantify antioxidant, ROS-related, and photosynthetic responses to cold stress.
These measurements characterize phenotypic stress responses from the collected samples before integrating them with transcriptomic results.
- 4.Sequence samples on Illumina NovaSeq X Plussequencing platform
Generate RNA-seq reads for transcriptomic analysis.
Sequencing is required before computational read filtering and expression analysis.
- 5.Filter raw reads with fastpread preprocessing software
Remove adapter-containing and low-quality reads before downstream transcriptomic analysis.
Quality filtering follows sequencing because raw reads must be cleaned before reliable DEG and pathway analysis.
- 6.Analyze filtered reads against reference genome and identify DEGs and enriched pathways
Convert filtered sequencing data into differential-expression and pathway-level interpretations of cold response.
This analysis depends on having filtered reads and a specified reference genome.
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete measurement method used to characterize an engineered system.
Mechanisms
No mechanism tags yet.
Target processes
recombinationImplementation Constraints
It requires prepared biological samples and downstream read-processing and reference-mapping workflows.; Requires fresh leaf samples prepared for sequencing
Independent follow-up evidence is still limited. Validation breadth across biological contexts is still narrow. Independent reuse still looks limited, so the evidence base may be fragile. No canonical validation observations are stored yet, so context-specific performance remains under-specified.
Validation
Supporting Sources
Ranked Claims
RNA-seq identified increasing numbers of differentially expressed genes in oil palm under cold exposure at 1, 4, and 8 hours.
RNA-seq analysis identified 144, 392, and 6,585 differentially expressed genes (DEGs) after 1, 4, and 8 h of cold exposure, respectively.
Approval Evidence
Sequencing of the samples was performed using Illumina NovaSeq X Plus platform.
Source:
RNA-seq identified increasing numbers of differentially expressed genes in oil palm under cold exposure at 1, 4, and 8 hours.
RNA-seq analysis identified 144, 392, and 6,585 differentially expressed genes (DEGs) after 1, 4, and 8 h of cold exposure, respectively.
Source:
Comparisons
Source-backed strengths
Sequencing of the samples was performed using Illumina NovaSeq X Plus platform.
Compared with barcoded Cre recombinase mRNA barcode platform
Illumina NovaSeq X Plus sequencing and barcoded Cre recombinase mRNA barcode platform address a similar problem space because they share recombination.
Shared frame: same top-level item type; shared target processes: recombination
Compared with calcium imaging
Illumina NovaSeq X Plus sequencing and calcium imaging address a similar problem space because they share recombination.
Shared frame: same top-level item type; shared target processes: recombination
Relative tradeoffs: appears more independently replicated.
Compared with two-photon excitation microscopy
Illumina NovaSeq X Plus sequencing and two-photon excitation microscopy address a similar problem space because they share recombination.
Shared frame: same top-level item type; shared target processes: recombination
Strengths here: looks easier to implement in practice.
Ranked Citations
- 1.