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Animal and Plant Whole Genome Sequencing

What is Animal and Plant Whole Genome Sequencing?

Animal and Plant Whole Genome Sequencing is an instrumental technique that is commonly being employed to sequence the entire genomes of animals and plants, respectively, and aims at identifying genomic variations such as SNP, InDel, CNV, and SV. Whole Genome Sequencing is an ideal approach to determine the entirety of genetic information at a single nucleotide level.

Novogene offers Animal and Plant Whole Genome Sequencing services with ultra-fast turnaround time, high-quality sequencing data, and reliable results. Animal and Plant Whole-genome sequencing has found its applications in several fields including population genetics research, genome-wide association studies (GWAS), and agricultural breeding programs.

Applications of Animal and Plant Whole Genome Sequencing

  • Reveals the molecular mechanism
  • Provide resources for accelerating genetic development
  • Investigates the origin and evolution of species
  • Identifies common genetic variations among populations

Animal and Plant WGS Specifications:
DNA Sample Requirements

Platform Type Sample Type Amount (Qubit®) Purity
Illumina

NovaSeq 6000

Genomic DNA ≥ 200 ng OD260/280=1.8-2.0;

no degradation, no contamination

Genomic DNA

(PCR free non-350bp)

≥ 5 μg
Genomic DNA

(PCR free -350bp)

≥ 1 μg
PacBio Sequel II
DNA CLR library
HMW Genomic DNA ≥ 8 μg A260/280=1.8~2.0;
A260/230=1.5~2.6;
Nc/Qc***=0.95~3.00
Fragments should be  ≥ 40k
PacBio sequel II
DNA HiFi library
HMW Genomic DNA ≥15 μg A260/280=1.8~2.0;
A260/230=1.5~2.6;
Nc/Qc=0.95~3.00
Fragments should be  ≥ 30k
Nanopore PromethION HMW Genomic DNA ≥ 8 μg OD260/280=1.8-2.0;
OD260/230=1.5-2.6;
Fragments should be ≥ 30K

Animal and Plant WGS Specifications: Sequencing & Analysis

Platform Type Illumina NovaSeq 6000 PacBio Sequel II/IIe Nanopore PromethION
Read Length Paired-end 150 bp Average > 15 Kb Average > 17 Kb
Recommended

Sequencing Depth

For SNP/InDel detection: ≥ 10× For SV detection: ≥ 20×
For SV/CNV detection: ≥ 20×
Content of

Analysis

Standard Analysis

  • Data quality control
  • Sequencing error rate
  • Filtering reads containing adapter or with low quality
  • Alignment with reference genome
  • Statistics of mapping, sequencing depth and coverage
  • SNP calling, annotation and statistics

Advanced Analysis

  • SV calling, annotation and statistics
  • CNV calling, annotation and statistics
Standard Analysis

  • Data quality control
  • Sequencing alignment
  • Structural Variant (SV) detection

Novogene Workflow of Animal and Plant Genome Sequencing Service

 

From sample and library preparation, short and long-read sequencing, and data quality control, to bioinformatics analysis, Novogene provides high-quality products and professional services. Each step is performed in agreement with a high scientific standard and meticulous design to ensure high-quality research results.

[1]https://www.nature.com/articles/jhg2013114

Featured Publications of Animal and Plant Whole Genome Sequencing

Demo Result

  • Sequencing Quality Distribution

Sequencing quality distribution is examined over the entire length of all sequences, to detect regions where incorrect bases are incorporated at abnormally high levels. The detailed sequencing quality distribution is as follows.

 

Novogene hWGS GC Content Distribution
Distribution of sequencing quality

Note: The x-axis shows the base position within a sequencing read, and the y-axis shows the average phred score of all reads at each position.
(Pair-end sequencing data are plotted together, with the first PE150 bp representing read 1 and the following PE150 bp for read 2.)

  • Sequencing Error Rate

The sequencing error rate is the major confounding factor of precise detection of low-frequency variations by deep sequencing. It determines the quality of the sequencing data. The sequencing error rate is highly associated with the sequencing cycle, escalating towards the end of each read because of the consumption of chemical reagents, which is a common feature of the Illumina high throughput sequencing platform.

Novogene hWGS GC Content Distribution

Distribution of sequencing error rate

Note: The x-axis shows the base position along each sequencing read and the y-axis shows the base error rate.
(Pair-end sequencing data are plotted together, with the first PE150 bp representing read 1 and the following PE150 bp describes read 2.)

  • Filtering reads containing adapter or with low quality

The sequencingraw reads often contain low-quality reads or reads with adaptors, which influences the quality of the downstream analysis. To avoid this, it is necessary to filter out the raw reads and obtain clean reads. Raw reads filtering should be done under the following conditions:

(1) Remove the paired reads when either read contains adapter contamination;
(2) Remove the paired reads when uncertain nucleotides (N) constitute more than 10 percent of either read;
(3) Remove the paired reads when low quality nucleotides (base quality less than 5, Q ≤ 5) constitute more than 50 percent of either read.

Novogene hWGS GC Content Distribution

Note:
Classification of the sequenced reads

(1) Adapter related: (reads containing adapter) / (total raw reads).
(2) Containing N: (reads with more than 10% N) / (total raw reads).
(3) Low quality: (reads of low quality) / (total raw reads).
(4) Clean reads: (clean reads) / (total raw reads).


Alignment with reference genome

  • Mapping Statistics with Reference Genome

Novogene hWGS GC Content Distribution

The mean depth of each chromosome.

Note: The x-axis shows the chromosome and the y-axis shows the mean depth


Standard Analysis

  • SNP Detection & Annotation

ANNOVAR is a software that efficiently annotates genetic variants spotted from the genome utilizing contemporary information. Provided an index of variants with reference nucleotide, start position, end position, observed nucleotides, and chromosome, ANNOVAR can perform gene-based annotation, region-based annotation, filter-based annotation as well as other functionalities.

Novogene hWGS Sequencing Depth & Coverage Distribution

Note: The figure demonstrates the distribution of (A) The number of SNPs in different regions of the genome (left) and (B) the number of SNPs of different types in the coding region (right)

  •  SNP Quality Distribution

To assess the credibility of detected SNPs, we checked the distribution of support reads number, SNP quality, as well as the distance between adjacent SNPs. The results as follows.

Novogene hWGS Sequencing Depth & Coverage Distribution

Cumulative distribution of SNP quality

Note: These figures demonstrate the quality distribution of SNPs, the distribution of SNP support reads number, the distribution of distances between adjacent SNPs, and the cumulative distribution of SNP quality.

  • SNP Mutation Frequency

Take the T:A>C:G mutations as an example, this category includes mutations from T to C and A to G. When T>C mutation appears on either of the double-strand, the A>G mutation will be found in the same position of the other chain. Therefore the T>C and A>G mutations are classified into one category. Accordingly, the whole-genome SNP mutations could be classified into six categories.

Novogene hWGS Sequencing Depth & Coverage Distribution

Novogene hWGS Sequencing Depth & Coverage Distribution

Frequency of SNP mutations

Note:The x-axis represents the number of the SNPs, and y-axis indicates the mutation types.


CNV Detection & Annotation

Copy-number variation (CNV) is a type of structural variation that happens when a DNA fragment is present in variable copy number in comparison to a reference genome. It pinpoints the deletions and duplications in the genome. Based on the reads depth of the reference genome, CNVnator can be used to detect CNVs of potential deletions and duplications with the following parameter ‘-call 100’. The detected CNVs are then further annotated by ANNOVAR.

Novogene hWGS Sequencing Depth & Coverage Distribution
CNV annotation

Novogene hWGS Sequencing Depth & Coverage Distribution

Ann Variation type statistics distribution of CNVs

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Note:The x-axis represents samples, and the y-axis indicates the proportion of each type of CNVs.