Integration of Modern Molecular Tools with Geological Processes to Reveal Species Phylogeny,Biogeographical Niche Prediction,and Bio-Evolution |
| |
Authors: | Bhandari Maneesh S. Martins-Ferreira Marco Antonio Caçador Shamoon Arzoo Pandey Shailesh Meena Rajendra K. |
| |
Affiliation: | 1.Division of Genetics and Tree Improvement, Forest Research Institute (FRI), Dehradun, Uttarakhand, 248195, India ;2.Faculdade de Ciências e Tecnologia, Universidade Federal de Goiás (UFG), Rua Mucuri, Setor Conde dos Arcos, Aparecida de Goiania, GO, Brazil ;3.Forest Pathology Discipline, Division of Forest Protection, Forest Research Institute (FRI), Dehradun, Uttarakhand, 248006, India ; |
| |
Abstract: | ![]()
Nature is integrated, being simultaneously controlled by different natural aspects. Genetics, bioinformatics, biostatistics and geology are four diverse and broad scientific disciplines. But we believe that these can offer important insights into species distribution and evolution, if integrated. This perspective is grounded on a case study of the family Salvadoraceae, where species distribution and phylogeny show high correlation with the geological records. The results obtained from published and ongoing research indicate that we are pointing toward better visualizing the overlapping boundaries of these specific disciplines, which will be able to more accurately answer key evolutionary questions. We highlight: (1) the combined application of bedrock-soil geological data and bioinformatics to resolve evolutionary questions regarding species eco-distribution, niche prediction and bio-evolution; and (2) signifies the importance of relaxing boundaries between the disciplines to come to a better conclusion on species diversity and distribution-driven controls. Overall, we express and briefly explain our hypothesis to integrate modern analytical tools, viz., statistical correlation of geological data via. geo-statistics (Geo), and spatiotemporal biostatistics via. geo-informatics (Geo), with gene-based paleontological shreds of evidence, and sequence-based bioinformatics, to devise a practical analysis tool, namely “Geo2 gene-bioinformatics”. We invoke the development of algorithms through computational-based programs that can provide useful correlations to understand evolutionary systematics and phylogeny, species distribution, and niche prediction. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|