Transcriptome analysis is the study of the transcriptome using high-throughput methods. Transcriptome analysis can be applied to loss- and gain-of-function mutants to identify changes associated with the mutant phenotype. Transcriptomic techniques are particularly useful in characterizing gene function. Transcriptomics can also identify pathways that respond to or ameliorate environmental stresses. RNA sequencing (RNA-Seq) can also identify disease-associated gene fusions, single-nucleotide polymorphisms (SNP), and even allele-specific expression. RNA-Seq experiments generate a large number of raw sequence reads, which must be processed to produce useful information. Data analysis often requires a combination of bioinformatics software tools that vary depending on the experimental design and objectives.

Fig. 1. Weighted gene co-expression network analysis of RNA-seq based expression profiles of two-year-old Jatropha curcas inflorescences. (Govender et al., 2018)

Our agricultural transcriptomic data analysis service

CD Genomics is a leading company in the field of agricultural genomics research, providing comprehensive agricultural transcriptomic data analysis services. Our transcriptomic data analysis covers the four phases of quality control, comparison, quantification, and differential expression to review and interpret complex gene expression within plant and animal genomes. Our bioinformatics team has extensive experience in analyzing agricultural transcriptomic data to drive crop improvement and increase agricultural productivity. Our analysis of agricultural transcriptomic data encompasses all aspects of transcriptomic research, including large-scale identification of transcriptional start sites, discovery of alternative promoter uses and novel splicing alterations, identification of SNPs, allele-specific expression and gene fusions, etc.

We offer the following agricultural transcriptomic data analysis services:

• RNA-seq data analysis. We offer RNA-Seq data analysis services to examine the entire transcriptome of a crop. By sequencing and analyzing the entire set of RNA transcripts, we help you identify expressed genes and splice variants, determine gene structure, quantify absolute and relative gene expression levels, detect post-transcriptional edits, discover SNPs, perform gene ontology (GO) enrichment analysis, etc. This information can provide a holistic view of gene expression patterns and regulatory networks within a crop and help identify key genes associated with specific agricultural traits.
• Small RNA sequencing data analysis. We provide small RNA sequencing data analysis services to identify and quantify known and novel miRNAs, analyze their differential expression, predict target genes, and comprehensive network and pathway analysis. We aim to provide useful information on post-transcriptional regulatory mechanisms that regulate crop development and respond to various stresses.

Our services can be applied to the following research areas

• Crop improvement and breeding. Transcriptomic data analysis enables the identification and characterization of genes and pathways associated with desired crop traits. By generating gene expression profiles for traits such as yield, disease resistance, and abiotic stress tolerance (e.g., drought, heat, salinity), it can help develop targeted breeding strategies and accelerate crop improvement programs.
• Plant-microbe interactions. Transcriptomic analysis can comprehensively characterize changes in gene expression during plant-microbe interactions.
• Gene function annotation. Transcriptomic analysis can characterize gene function and identify those genes responsible for specific phenotypes. Integration of RNA-Seq datasets across different organizations has been widely used to improve gene function annotation in commercially important organisms or threatened species.

Our advantages and features

• Cutting-edge technology and expertise. Our laboratory has state-of-the-art sequencing platforms with bioinformatics processes. Our team of highly skilled bioinformaticians and molecular biologists have extensive experience in processing and analyzing large-scale transcriptomic datasets.
• Customized analysis solutions. Whether it's a targeted analysis of a specific gene or a comprehensive examination of an entire transcriptome, our team works closely with researchers to design an analytical process that meets their research goals.
• Comprehensive data interpretation. We don't just provide raw data analysis. Our team of experts provides comprehensive interpretations of the results, offering insights into the biological significance of gene expression patterns, pathway analysis, and functional annotation.

CD Genomics provides comprehensive agricultural transcriptomic data analysis services to accelerate crop improvement and promote sustainable agricultural practices. If you are interested, please feel free to contact us.

Reference

1. Govender, Nisha, et al. An integration of phenotypic and transcriptomic data analysis reveals yield-related hub genes in Jatropha curcas inflorescence. Plos one. 13.9 (2018): e0203441.