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DNA Sequencing and Recent Innovations & Trends

Currently, the world is on the cusp of the technology-driven revolution in the genomics field. The rapid evolution of technological development in DNA sequencing offers researchers the capability to generate data that includes genetic patterns and variation of gene expression on an unprecedented scale.

According to the Eurofins Genomics blog, there is a chance that these technological developments may allow more accurate sequencing of human genomes to be a tool for clinicians and researchers.

This review basically covers all the emerging fields of the new technological developments in DNA sequencing and highlights the potential challenges and benefits of those technologies.

Technical Drivers

Some technical drivers influence how new products may develop and increase the accessibility of modern tools, leading to the increased number of actors who create biotech products.

Among the key areas include increasing rapid design-built-test-learn cycles, standardization of the biological parts, and DNA:

  • Sequencing
  • Editing
  • Synthesis

Recent Trends and Innovations

In the past ten years, techniques and technologies for rapid DNA sequencing have made some amazing strides. The inception of sequencing technologies, including tools and sensors, has opened up many research areas in treatment responses in animals, human diseases, and human biology.

Especially stakeholders in the DNA sequencing field, with the support from newly-commercialized technological developments, are able to unearth a lot of information on genomic and genetic factors underlying diseases. Especially stakeholders in the DNA sequencing field, with the support from newly-commercialized technological developments, are able to unearth a lot of information on genomic and genetic factors underlying diseases. If you’re curious about exploring your genetic makeup and understanding potential health risks, you can gain insights and learn how to get a healthy body with this DNA test.

Further, recent innovations and trends in DNA sequencing technology have paved the way for researchers to understand the pathogenic mechanism of various complex diseases, like neurodegenerative diseases. Some of these innovations and trends include:

1. Genetic Testing

Clinical genomics vastly improves the whole reproductive health diagnostic paradigm. Genetic testing can start with carrier screening of father and mother so as to assess around 260 hereditary illnesses.

It also extends to IVF (in-vitro fertilization), examining embryos for disease inheritance. In addition, genetic testing can happen in-utero in the mother, enabling researchers to analyze inherited diseases, such as microdeletions.

2. The Brain and Gene Regulation

For centuries, researchers have been exploring the complexity of the human brain. The human’s ability to act, do and think are shaped by many years of the anatomical revolution.

The brain is basically organized into four broad levels. These include the genome, TF-gene (transcription-factor gene), synaptic epigenesist level, and long-range connectivity level.

When the network of TF-gene got introduced, it came with new insights into the research of behaviors and cognitive disease through the genetic changes of genes, which are mostly involved in controlling:

  • Neurite growth
  • Brain growth
  • Neural maturation

3. NGS (next-generation sequencing)

The NGS arrival is the recent transformative development in genomics. Allowing billions or millions of DNA fragments to get sequenced in parallel makes NGS more measurable than the Sanger sequencing used during the Human Genome Project.

Unlike Sanger Sequencing, next-generation sequencing (NGS) is cheaper, needs less DNA, needs no prior knowledge of genes, and captures vast mutations. All thanks to these traits, the NGS arrival has as well ushered in the new era of personalized genomics.

Final Remarks!

The future discretions in precision medicine comprise NGS technology empowerment with a few parallel approaches, including deep learning methods, artificial intelligence, and machine learning.

New bioinformatics tools are also developed so as to address the current limitations when it comes to genomic data treatment while improving the general performance of the data analysis.

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