CD Genomics is dedicated to providing a comprehensive list of genomics and microarray solutions for agriculture, including genome, exome, transcriptome, and metagenome sequencing, genome-wide association studies (GWAS), and targeted sequencing and genotyping that focus on a subset of regions or genes such as single nucleotide polymorphisms (SNPs). https://www.cd-genomics.com/Whole-Genome-Sequencing.html
2. Agrigenomics – The Impact of NGS on Agriculture
Genomics has the capacity to help researchers trace molecular variability during development in diverse
conditions such as physiological or pathological conditions, or in the process of being influenced by
environmental alterations. Genomics also provides insight into the evolution of genes and organisms, which
may further help improve the productivity and sustainability in crop and livestock production. Agrigenomics
is the application of genomics in agriculture, with a focus on plants, animals, and ubiquitous microorganisms.
Agrigenomic technology is transforming traditional approaches to breeding of commercial species and
monitoring and protection of wild populations. The main methods for agrigenomics are next-generation
sequencing (NGS), microarrays, and polymerase chain reaction (PCR).
Leveraging Genomics for Agriculture
Genomic technologies are able to depict all the genes in a genome and their functions and manipulations
of genes linked to specific phenotypic traits. Agrigenomics aims to find innovative solutions for protection
and sustainable productivity for the food industry, and may provide insight into energy production or drug
discovery.
◆ Whole Genome Sequencing
While whole-genome de novo sequencing is
used to comprehensively understand novel
species, resequencing can be used to discover
SNPs and structural variants, enabling
comparative genomic analyses and improving
breeding and selection.
◆ Transcriptome Sequencing
RNA sequencing is revolutionizing the study of
gene expression dynamics in organisms,
providing insight into the key molecules and
mechanisms in development and during disease
and stress conditions. Transcriptome sequencing
is also used to understand gene function.
◆ Epigenomics
Epigenomics is used in agriculture to investigate
adaptive responses to changes in the environment.
Epigenomic technologies can be used to detect
changes in DNA methylation, chromatin structure,
and small RNA expression, and associate
epigenetic factors with traits of interest.
◆ Targeted Sequencing
Targeted sequencing with a focus on the
exome or specific genes can be used for the
identification of common and rare variants such
as SNPs and CNVs. These variants can help
inform breeding decisions and reveal causative
mutations for parasite susceptibility or disease.
◆ SNP Genotyping
SNP genotyping by sequencing or microarray
enables the whole-genome SNP profiling. SNP
genotyping has been shown to work for
GWAS, marker-assisted selction/ breeding,
marker-assisted backcrossing, QTL screening,
and trait mapping.
◆ Metagenomics
Metagenomics enables researchers to identify
microbial populations associated with animal
and plant development, detect known and
novel pathogens in animal populations,
enhance animal digestion, and improve plant
health via analysis of root-associated bacteria.
3. Bioinformatics for Agrigenomics
Bioinformatics analysis is required to elucidate the molecular mechanisms affecting the structure and the
function of the individuals, populations, and communities, and to identify molecules and mechanisms
associated with specific phenotypic traits and specific responses to environmental stress. The following table
is to introduce the most commonly used open-source software and reference databases in agrigenomics.
Task Name Details Usage
Reads
pre-processing
FastQC Quality check and report of NGS data
Genomics;
Metagenomics
Cutadapt Adapter trimming algorithm
Genomics;
Metagenomics
FASTX-toolkit
Toolset for manipulation of sequence data
and format conversion
Genomics;
Metagenomics
Assembly
(Meta)
Velvet/OASES
De novo genomic/transcriptomic assembly
based on the de Brujin graph
Genomics;
Metagenomics
SOAPdenovo
De novo short-read assembler based on the
de Brujin graph
Genomics
TRINITY De novo assembly of RNA-seq data Genomics
Gene
prediction/
annotation
Ensembl genome
annotation
Gene annotation pipeline Genomics
Infernal
RNA secondary structure prediction based on
reference multiple sequence alignments
Genomics
(Meta) Genemark
Gene prediction with unsupervised and semi-
supervised training
Genomics;
Metagenomics
(Meta)
Genomethreader
Gene prediction by similarity with cDNA/EST
and/or protein sequences
Genomics;
Metagenomics
NCBI genome
annotation
Genome annotation pipeline released by
NCBI
Genomics
tRNAscan-SE tRNA gene prediction Genomics
Repeat masker
Similarity-based detection of DNA
interspersed repeats and low complexity
sequences
Genomics
Table 1. Bioinformatics tools for agrigenomics (adapted from Esposito et al. 2016).
4. Task Name Details Usage
Mapping
Star RNA-seq to genome aligner Genomics
Tophat/cufflinks
RNA-seq to genome aligner and
quantification tools
Genomics
Marker-based
metagenome
Mothur
16S data clustering, classification, and
ecological inference
Metagenomics
Qiime
Customizable pipeline for marker-gene-
based metagenomics
Metagenomics
RDPipeline
RDP-based web interface for bacterial and
fungal ribosomal marker gene analysis
Metagenomics
Mixed
Galaxy Web-based platform of general purposes
Genomics;
Metagenomics
transPLANT
Exploring genomic data from crop and
model plants
Genomics
Shotgun
metagenome
Megan
Phylogenetic and functional assignment
based on the lowest common ancestor
algorithm
Metagenomics
Metamos Shotgun data assembly and analysis Metagenomics
(Mg-)Rast Analyses of shotgun data Metagenomics
Population
genomics
Metabel
Software for meta-analysis of Genome-wide
SNP association
Genomics
Metal
Mining variation data and perform
association studies
Genomics
Plink Tools for managing genomic variation data
Genomics;
Metagenomics
SVS
Genomic and phenotypic data analysis and
visualization
Genomics
Tassel Genome variation studies Genomics
VcfTools
Tools for genome comparisons and mining
plant variation data
Genomics;
Metagenomics
5. Task Name Aims Usage
General
Genomes online
database
Metadata repository for sequencing projects
Genomics;
Metagenomics
JGI Phytozome
Plant Comparative Genomics at the Joint
Genome Institute
Genomics
INSDC
DDBJ, EMBL-EBI, and NCBI, common
repository
Genomics;
Metagenomics
PLANTGDB Unified plant genomic database Genomics
Taxonomic
annotation
RDP/Silva/
Greengenes
Repositories of ribosomal RNA genes
Genomics;
Metagenomics
Functional
annotation
KEGG
Integrated resources for functional
annotation of genes
Genomics;
Metagenomics
COG Clusters of ortholog groups
Genomics;
Metagenomics
SEED Functional annotated genes Metagenomics
RFAM RNA families collection Genomics
DFAM Repetitive DNA elements Genomics
UNIPROT Functional annotated protein sequences Genomics
Table 2. Reference databases in agrigenomics (adapted from Esposito et al. 2016).
Applications of Agrigenomics
It is very important to increase crop yields and livestock productivity to alleviate
hunger and poverty in the developing world. Genomics is a promising tool for solving
this urging problem. Genomic information enables researchers to identify genes
associated with valuable traits. Gene editing technologies such as CRISPR/Cas9 can
be used to introduce genes to promote disease or drought resistance, enhance the
taste, texture, and help crops adapt to high salinity soils, etc. Genome editing needs
to be validated via molecular methods such as PCR or sequencing.
Crop improvement
6. Adapting crops to future harsher conditions of a major concern for food security.
Agrigenomics is a potential method to improve the adaptability of crops through
increasing agrobiodiversity. It is expected that wild relatives represent an important
reservoir of adaptations to extreme environmental stresses. NGS can be used to
identify wild relatives carrying adaptations that can be used for improvement of
crop adaptation in breeding programs. It can also be used to identify genes and
polymorphisms associated with adaptations for targeted improvement.
Crop adaptation
Next-generation sequencing promotes the development and commercialization of
bioproducts which affect applied fields like biocontrol, stress protection, and arable
land. For example, the microorganisms that potentially play a role in crop health and
disease suppression can be identified with a culture-dependent approach using a
next-generation sequencing-based platform and powerful bioinformatics analysis.
NGS may impact (i) the detection of new bio-resources for biocontrol and plant
growth promotion; (ii) the optimization of formulation; (iii) risk assessment studies for
bio-products; and (iv) stabilization of the biocontrol effect under field conditions.
Development of bio-products
Recent advances in NGS and phenotyping platforms have accelerated the
genomics-assisted breeding. Genomics is consistently increasing the diversity of
alleles available for animal breeding. Genomic information can accelerate
breeding programs by selecting a combination of genomic markers associated
with desirable traits. And genome-wide arrays are used to predict the future health
and performance of the newborn animals. Microorganisms colonized in the gut of
livestock can be sequenced and analyzed to enable optimization of animal feed
and diagnosis of infections.
Animal breeding and management
Antimicrobial resistance (AMR) is a major cause of morbidity and mortality in humans
and animals on a global scale. NGS is a promising method to understand and
prepare for emerging AMR threats. To be specific, sequencing such as whole
genome sequencing can be used to comprehensively monitor AMR epidemiology
through exploring the rise and spread of resistant pathogenic strains and lineages. The
sequencing-based platform also allows researchers to track the evolutionary origins of
antimicrobial resistance microbes and determine the corresponding therapies.
Antimicrobial resistance
7. Our Comprehensive Agrigenomics Solutions
CD Genomics is dedicated to providing a comprehensive list of genomics and microarray solutions for
agriculture, including genome, exome, transcriptome, and metagenome sequencing, genome-wide
association studies (GWAS), and targeted sequencing and genotyping that focus on a subset of regions
or genes such as single nucleotide polymorphisms (SNPs).
Figure 1. General description of a standard workflow in agrigenomics (Esposito et al. 2016).
◆ Understand the complex genomes of crops
◆ Develop a reference genome sequence
◆ Analyze the genetic traits in plants and animals
◆ Analyze gene expression in plants or animals
under different conditions
◆ Predict gene functions and associate genes
with phenotypic traits
Our services help customers in the following aspects:
◆ Screen genomic markers associated with desirable traits
◆ Protect crops and livestock from pathogen infections or
genetic diseases
◆ Accelerate breeding programs or crop improvement
through genotyping
◆ Validate genome editing using CRISPR sequencing
◆ Address antimicrobial resistance and achieve food safety
If you are interested in our agrigenomics solutions, please feel free to contact us!
Contact CD Genomics for more inspiration and service content.
