Human genes are units of inheritance composed of DNA sequences that code for proteins or regulatory molecules that are necessary for the body to function. Humans have a genome with around 3 billion base pairs of DNA and around 20,000 or 25,000 genes. These genes perform all kinds of biochemical activities, from protein production to the control of the cellular machinery. Genomics - the science of genes, how they work and how they interact - quickly became an interlocking domain of molecular biology, bioinformatics, and computational biology. In this article, I cover some fundamentals about human genes, genomics and how many human beings actually have.
Coding and non-coding DNA make up the human genome. Proteins are directly encoded by coding regions called exons, while non-coding regions consist of regulatory sequences and all sorts of RNA, some of which could regulate gene expression. As a field, geneomics attempts to decipher the full internals and functions of genes. Through high-throughput sequencing, researchers can now systematically sequence whole genomes to discover genetic variation, gene activity, and disease risk.
Traditionally, we knew that the human genome had from 100,000 to several million genes. But the Human Genome Project concluded in 2003, and the estimated number has since been lowered to about 20,000 or 25,000 protein-coding genes. That was an evolutionary paradigm shift, as it transpired that gene complexity in human biology had less to do with genes themselves than with gene regulation, alternative splicing and post-translational editing.
Even though there are fewer genes, a growing body of evidence now tells us that human genomes include an even more complex web of genetic materials, including an enormous number of non-coding RNAs involved in gene regulation. These long non-coding RNAs (lncRNAs) which were once thought of as "junk" DNA have now been identified as crucial to numerous biological activities such as cell differentiation, development and disease.
Figure 1. The general structure of a typical human gene[1].
Structured genomics refers to mapping all the genes in an organism's genome. High-throughput sequencing, especially next-generation sequencing (NGS), now enabled the analysis of human genomes. Structural changes - insertions, deletions and copies of genes - gave us some fundamental information about genetic disease, cancer and human evolution.
Functional genomics isn't just about finding genes, but also about what these genes do in cells. This genomics subfield uses techniques such as RNA sequencing (RNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq) and gene knockdowns to study the expression, regulation and interaction of genes. Functional genomics has been the key to figuring out how complex diseases like cancer, cardiovascular disease and neurological diseases function on the molecular level.
Comparative genomics looks at the genomes of multiple species in search of shared and differing genetic elements. When we compare the human genome with that of model animals such as mice, fruit flies and even bacteria, we can identify genes important for human development and disease. Comparative genomics also shed light on how different species relate to each other, and how some genes are preserved over time.
This is because genetic variation creates all the difference in individuals and populations. SNPs and structural variants can alter gene expression and even make people vulnerable to disease. Genomics helped pinpoint genetic variants that cause cancer, Alzheimer's and diabetes. These markers have been uncovered at an even faster pace thanks to whole-genome sequencing (WGS) and genome-wide association studies (GWAS).
After the Human Genome Project, the human genome had once been deemed 'fully catalogued'. But studies are still improving our gene annotation - especially non-coding regions and regulatory features. Plans to identify all human genes - including those formerly unnamed lncRNA genes - now encompass more accurate gene databases. This refined naming has enormous consequences both for basic science and for clinical practice, in the areas of oncology and rare genetic disorders.
Figure 2. Decision tree and clusters for the human genome[2].
Non-coding RNAs such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are another new genomics field of focus. Although most early genomic work was on protein-coding genes, we now know that non-coding regions are also essential for gene regulation. Particularly LncRNAs regulate gene expression from chromatin to transcriptional and post-transcriptional levels. Their prevalence in cancer, cardiovascular diseases, and neurological disorders makes them attractive targets for therapy.
Figure 3. Manual annotation of lncRNAs in the human genome. (A) How lncRNAs are subdivided based on their intersection with protein-coding genes. (B) The number of lncRNA transcripts in each subcategory[3].
Genomics is developing quickly as a technology. The technology of next-generation sequencing (NGS) has democratised the time and cost of genome sequencing and has helped scientists to build large datasets from single patients. It has been the source of personalized medicine - treatments tailored to a patient's genetic code. It's not only CRISPR-Cas9 gene-editing technology, but the potential of the technology to transform gene therapy and genetics research.
Future use of artificial intelligence (AI) and machine learning (ML) on genomic data analysis is set to spur discoveries in gene function, disease mechanisms and therapeutics. They can also promise better forecasts of disease risk, better diagnosis of complex genetic disorders, and the discovery of new therapies.
There is a lot to be learned from the field of genomics, in clinical practice as well as in public health. Personalised medicine, in which care plans are personalised according to the patient's genes, could drastically transform outcomes for patients with all types of illnesses, including cancer and rare genetic conditions. What's more, finding genetic risk factors for common diseases like heart disease and diabetes can help to identify ways to prevent and catch problems in time.
Also, genomic data integration into EHRs will become one of the main players in precision medicine, giving clinicians the data they need to diagnose and treat patients more accurately. But en masse the utilisation of genomic data is incompatible with legitimate ethical and privacy concerns that will need to be resolved as the discipline develops.
We are changing how human biology, genetics and medicine work thanks to genomics. And with an increased interest in nucleic acid structure, gene regulation and genetic variation, research on human genes is evolving too. The more we learn about how genes really work, and how they contribute to health and disease, the more we know about what goes on under the hood. The genomics will transform the way we approach disease prevention and cure, which can improve personalized therapy approaches.
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