Genomics based evolutionary study comprises a wide choice of topics to investigate on the species evolution using their genomic data. These genomic evolutionary studies grant different models for understanding the evolutionary history of bacteria, plants, and humans. The evolution of plants and animals via the symbiotic association with microbes is well established in recent times by considering the genomic data. Since from the beginning of life, bacteria might have played a vital role in assisting the creations of multi-cellular living beings (~1-2 billion years ago) and animals (~700 million years ago). Acquisition of microbe, plant and animal genomic data is a powerful tool for understanding the evolutionary aspects of organisms. Genomics data has been successfully investigated to draw a link between bacteria and plants; plants and animals; animals and humans, etc. This is possible because of the uniformity in genetic codes across all categories of creatures, thus, allow the comparison of DNA sequences within and between species. Likewise, the concept of hologenome (host genome + microbiome) suggests that the host and their symbionts are selected accordingly in the process of evolution. According to the hologenome concept, microbes drive evolution of plants and animals. However, interpreting these DNA sequences comparisons is the major challenge to genome biologists. There are diverse ways to determine the genetic makeup of a cell (genotypes) viz., sequencing approaches. In specific, they are selected based on the characteristics of the markers or loci of interest.
The level to which detected deviations in DNA sequences reflects on the adaptive nature, and it acts as the central to interpret on the evolution. In this regard, many research efforts have been carried out in recent times to address the influence of natural selection based on the genomic diversity. In addition, other developments such as genetic drift, migration, gene overlap, mutation, recombination, etc., act together with natural selection to shape the patterns of diversity. These relations may lead to counter-intuitive outcomes. For instance, lactase persistence is one of the strongest models of niche construction in human beings. The maximum incidences of the allele linked with the lactase persistence are observed in the Northwestern Europe. This indicates that the allele would have originated from Northwestern Europe regions, and later diffused to other regions of the world. Nevertheless, a similar pattern can be drawn from the computational models. According to that there is a possibility of the combined influences of positive natural selection and 'allele surfing' phenomenon with the spread of farmers from the Eastern Europe ~ 8000 years back. These computer-aided simulation studies remain to be sensitive logical tools to recognize the relationship between the ecological and population adaptation processes.
Recently, cutting-edge tools such as advanced high-throughput next generation DNA sequencing (NGS) platforms have provided an improved analysis of the organism’s genome and their populations. In the 20th century, the evolutionary genetics studies were mainly model-based, however, recently, they are replaced by big data involving DNA sequence analysis, which is also being recognized as evolutionary genomics. The genome-wide survey (GWAS) is one of the genomic tools for detecting relationships between diseases and genetic variants or complex traits in samples from populations. GWAS also facilitates the investigations on the factors contributing to population adaptation. Studies have shown that the field of evolutionary genetics is very effective and give a better solution to everyday hitches than ever before. For example, insights into the evolutionary genomics assist in identifying a patient’s disease-causing genes and alleles, thus indirectly help to improve human health. Moreover, a detailed genomics data could be useful in the process of plant improvement programs. Even a single genetic variation may bring manifold consequences in the organism. Various studies that focus on identifying these DNA sequence variations in the genome, their impact on gene function or phenotype, and evolutionary modeling will certainly improve our understanding on the adaptability of any species and organisms, and thus allowing one to make their evolutionary linkage more evidently.
Evolutionary genomics could also be applied to identify potentially beneficial genetic variants from a single gene to the whole genome scale, for human needs such as for the production of commodity chemicals and pharmaceuticals. Likewise, phylooncogenomics study examines the cancer genome in the context of vertebrate evolution. As a dynamic force, evolutionary genomics can selectively induce favorable changes in organisms (genetic diversity) through inducing targeted, spontaneous or random mutations in a single or few genomic loci to obtain desired phenotypes in organisms. For example, recombineering techniques that are mostly used in Escherichia coli and Saccharomyces cerevisiae precisely investigate on phenotypic responses (e.g., production of a metabolite) by linking genetic manipulations (e.g., deletions, insertions, and point mutations of metabolic genes). Likewise, Adaptive Laboratory Evolution (ALE) tests have been employed to engineer microbial strains, also referred as evolutionary engineering to accomplish desired functions. In ALE tests, cells are challenged with environmental stresses so as to make them to adapt to regain fitness. Recently developed omics technologies have allowed high-throughput assessment of evolved isolates and populations at the molecular level. This has enabled the application of ALE experimentations as an instrument to discover novel biological mechanisms, such as previously uncharacterized enzyme activities that can further be used as part of rational strain development activities. The workflow of the ALE experiment is represented in Fig. 1.
Fig. 1. Adaptive laboratory evolution (ALE) workflow. Experiment starts by generating an initial population with or without genotypic diversification, followed by evolution for a desired time, and finally, analysis of populations and/or isolates for beneficial mutations. ALE can be performed sequentially with a starting population from a previous run or as a single run experiment. After ALE, the resulting isolates can be used directly as they are, but often mutations are re-implemented in a clean production strain. (Source: Shepelin et al. 2018; doi:10.3390/genes9050249).
Other approaches, such as multiplex automated genome engineering (MAGE) and trackable multiplex recombineering (TRMR) enable genome-wide identification of genetic determinants. Recently, highly accredited genome engineering tool i.e., CRISPR-Cas system can precisely and systematically edit/survey the whole genome for definite traits at the single nucleotide resolution.
In future, together with the traditional selective pressure approaches, evolutionary genomics may be well explored for sequence similarity searches. The wide application of high-throughput sequencing approaches, huge data has been created. Therefore, an efficient computational approaches are very necessary to evaluate and interpret the data. In this regard, a strong interdisciplinary efforts are required to overcome many challenges of evolutionary genomics in the present day.