Bioinformatics Analysis for Agricultural Technology

Bioinformatics Analysis for Agricultural Technology

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Bioinformatics-Analysis, a division of CD Genomics, as one of bioinformatics data analysis providers, we provide customers with professional bioinformatics analysis services, aiming to help you solve various problems encountered in agricultural genome research. We can help at different stages and for different purposes, including collection of germplasm resources, genome sequencing and analysis, functional gene mining, molecular design and breeding and other different stages of biological information analysis needs. You only need to provide the original data and analysis needs, we will provide you with a one-stop biological information data analysis service.

Introduction of Agricultural Technology

In the late 1980s, the launch of the Human Genome Project promoted the emergence and vigorous development of bioinformatics. With the completion of the sequencing of the genomes of various crops such as rice, sorghum, and wheat, it has announced the arrival of a prosperous information age for crop genetic engineering. The development and technological innovation of a series of disciplines such as genome, proteomics, metabonomics, gene editing, and synthetic biology, etc. have promoted the development of agricultural biotechnology at an unprecedented speed. In particular, it plays an important leading role in the innovation of the seed industry, and related scientific research results are affecting the development of global agriculture.

Bioinformatics, as a powerful auxiliary tool for biological experiments, provides valuable data-based information for basic research and applied research on food crops, and plays an extremely prominent role in agricultural scientific research. For example, the identification of important genes through comparative genomics, expression analysis and functional genomics analysis will lay the foundation for the cultivation of genetically modified crops and the improvement of crop quality and quantitative traits. Based on the analysis of signal receptors and transcription pathway components, the design of agricultural compounds, combined with chemoinformatics methods, identifies potential chemical components that can be used in pesticides and herbicides. And use plant genetic resources to protect the genetic diversity of crops.

Fig 2. Identification of the hst1 mutation by MutMap. Fig 1. Identification of the hst1 mutation by MutMap. (Takagi H, et al. 2015)

Bioinformatics in Agricultural Technology

In the research process of crops, bioinformatics takes nucleic acids and proteins in biological macromolecule databases as the main research objects, and comprehensively uses mathematics, computer science and biological tools to store, manage, annotate, and process them to make them have Information that clarifies biological significance. At the same time, through the query, search, comparison, and analysis of biological information, information about gene coding, gene regulation, nucleic acid and protein structure, function, and their relationships can be obtained.

Fig 3. CD Genomics bioinformatics data analysis process. - CD Genomics. Fig 2. CD Genomics bioinformatics data analysis process.

What can CD Genomics Do?

CD Genomics provides a variety of agricultural bioinformatics solutions to help customers conduct agricultural scientific research and exploration at different research stages. We provide various bioinformatics services tailored specifically for agricultural genome data, including:

Whole Genome De Novo Sequencing Data Analysis, Genome Survey Sequencing Data Analysis, Pan-genomics, providing a valuable reference sequence for phylogenetic studies, analysis of species diversity, mapping of specific traits and genetic markers, and other genomics research.

Variant Detection and Analysis- through variation analysis, a large amount of genetic variation information can be obtained, such as single nucleotide polymorphism (SNP), insertion and deletion (InDel), structural variation (SV), copy number variation CNV. Mutation detection can be used to develop molecular markers and establish genetic polymorphism databases, laying a data foundation for revealing evolutionary relationships, mining functional genes and breeding.

QTL-seq Analysis - Through the analysis of quantitative trait genes, the main loci of certain quantitative traits in isolated populations can be detected.

Genetic Map Analysis - Obtain markers closely related to traits, design primers according to marker sequences, and assist molecular marker breeding.

CD Genomics provides you with one-stop biological information data analysis services. In addition to the above analysis, we also provide microbiological analysis services, which can help you analyze the microbial communities in different environments to better predict the health and yield of crops. For agricultural science-related data analysis, if you have any questions, please feel free to contact us.


  1. Takagi H, et al. MutMap accelerates breeding of a salt-tolerant rice cultivar[J]. Nature Biotechnology, 2015.(33).5 445-449.
* For Research Use Only. Not for use in diagnostic procedures.
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