It is remarkable that sequencing the first human enome in 2003 required 13 years of work and cost nearly $US3 billion. In contrast, the HiSeqX Ten,released in 2013, can sequence over 45 human genomes in a single day for approximately $US1000 each.The critical evolution in terms of technology/chemistry is that, instead of sequencing a single DNA fragment as in the past, next-generation sequencing (NGS) today extends this process across millions of fragments in a massively parallel fashion, and enables researchers to study biological systems at a level never before possible.
The transcriptomics approach
Transcriptomics refer to the study of the transcriptome—the sum total of all messenger RNA molecules (mRNAs) being actively expressed from an organism’s genes. The use of NGS technology to study the transcriptome at the nucleotide level is known as RNA sequencing (Figure 1). RNA sequencing is a major advance in the study of gene expression because it allows a snapshot of the whole transcriptome rather than a predetermined subset of genes. This provides a comprehensive view of a cellular transcriptional profile at a given biological moment—which entails the quantification of each product of gene expression from between20,000 and 25,000 genes. Recent advances in RNA sequencing technology have made this high-throughput sequencing platform more accessible to researchers,and it is expected to become the predominant tool for transcriptome analysis. As exhibited in Figure 2, the use of RNA sequencing in scientific studies has grown exponentially—largely due to the advantages it offers over using microarrays.
Figure 1. The RNA sequencing process.
Figure 2. Scientific studies using ‘RNA sequencing’.
Application in animal nutrition
Rapidly developing NGS technology will play an important role in increasing our understanding of how nutrition influences metabolic and immunity pathways and enhances animal health and well-being—a field of animal science called nutrigenomics. Its principal line of enquiry examines the direct effects of feed constituents on gene expression. As such, nutrigenomics could lead the way to develop rational means to optimize animal nutrition and achieve more sustainable, profitable agriculture. Figure 3 presents an overview of how RNA sequencing can determine the mode of action of feed constituents and/or find potential biomarker(s).
Figure 3. Feed additives and the analysis of differences in gene expression.
Nutrigenomics and phytogenics in poultry
To the best of our knowledge, there are few nutrigenomics studies on the effects of phytogenics on the whole transcriptome. In 2016, a broiler experiment was conducted at the BIOMIN Research Center in which RNA sequencing analysis was done on tissue samples from the intestinal tract of birds fed with or without phytogenics.
The expression of more than 20,000 genes was determined.Preliminary results showed that 73 genes were differentially expressed between birds fed basal feed and birds fed the same feed supplemented with phytogenics. Table 1 gives an overview of some signaling pathways associated with these DEGs (Differentially Expressed Genes), namely the acute phase response and cytokine signaling pathways related to inflammatory response.These results were obtained based on an updated version of the chicken genome (Galgal5) released in December 2016. This makes them more accurate than results using older versions (e.g. Galgal4) or technologies, such as microarray, that rely on a pre-designed sequence detection probe for hybridization that would need to be redesigned for every new update of the genome.
Table 1. Effect of phytogenics on the intestine of 35-day-old broiler chickens.
|Total number of genes analyzed with Galgal5||24838|
|Number of differentially expressed genes compared to control birds –mapping Galgal5||73|
|Signaling pathways associated with these differentially expressed genes:||- Acute phase response signaling|
- Cytokine signaling (IL-22 and STAT3 pathway)
Limitations of NGS and transcriptomics
As with any technology, next-generation sequencing is not without its limitations and challenges. For instance, despite the superior benefits of RNA sequencing, microarrays are still the more common choice of researchers when conducting transcriptional profiling experiments.
This is likely because the newer RNA sequencing technology is more expensive than microarray, data storage is more challenging and analysis is more complex. NGS platforms provide vast quantities of data (e.g. 200 GB generated from RNA sequencing for 30 biological samples), and therefore requires servers with high computational resources. There is no reference methodology for processing and analyzing NGS data: this is a growing field with continuous development of bioinformatics tools. All have advantages but also limitations, and it is necessary to evaluate them and take a consensus for data analysis.The complexity of NGS analysis and data interpretation requires both expertise and knowledge in informatics and biology (Figure 4).
Figure 4. Requirements for RNA sequencing analysis.
Additionally, a transcriptomics approach alone is not sufficient to fully conclude on mode of action of feed constituents. For instance, the intestinal tract environment is quite complex: the host tissue, cells and nutrients all interact with the intestinal microflora. Combining so-called ‘–omics’ approaches, such as genomics, transcriptomics, proteomics and metabolomics, would provide an even better understanding on the mode of action and gut performance.