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Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

Microbial Phylogeny

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Understanding the evolutionary relationships among microorganisms is fundamental to microbial ecology and taxonomy. Phylogenetic trees are essential tools for inferring these relationships, relying primarily on comparative analyses of molecular sequences such as DNA, RNA, or proteins. In microbial studies, these trees typically depict the evolutionary paths of diverse bacterial and archaeal species by mapping genetic differences accumulated over time.Phylogenetic trees are composed of tips,...

Gene Duplication and Divergence

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The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are characterized.

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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Reconstruction of ancestral genomic sequences using likelihood.

Isaac Elias¹, Tamir Tuller

¹Department of Numerical Analysis and Computer Science, KTH, Stockholm, Sweden. isaac@nada.kth.se

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology

|April 26, 2007

Summary

Reconstructing ancestral genomes is crucial in computational biology. This study introduces novel algorithms offering guaranteed approximations and optimal solutions for ancestral sequence reconstruction, even when phylogenetic trees are unknown.

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Primer Extension Capture: Targeted Sequence Retrieval from Heavily Degraded DNA Sources

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Published on: September 3, 2009

Area of Science:

Computational Biology
Bioinformatics
Genomics

Background:

Reconstructing ancestral genomic sequences is vital for understanding evolutionary history.
Current heuristic methods lack performance guarantees, necessitating improved algorithms.

Purpose of the Study:

To develop algorithms for ancestral genome reconstruction with performance guarantees.
To address both scenarios: known and unknown phylogenetic trees.

Main Methods:

Developed approximation algorithms with a log-likelihood ratio guarantee.
Implemented a fixed-parameter tractable (FPT) algorithm for optimal solutions on small trees.
Created a Polynomial Time Approximation Scheme (PTAS) by combining approximation and FPT algorithms.

Main Results:

The approximation algorithm provides a solution with a log-likelihood ratio of 2.
The FPT algorithm is efficient for small numbers of taxa.
The PTAS offers arbitrarily good approximation guarantees.
Algorithms were validated on synthetic and biological data, including hominid mitochondrial genomes and lentiviruses.

Conclusions:

The developed algorithms significantly advance ancestral genome reconstruction capabilities.
These methods provide reliable solutions for both theoretical and practical biological questions.
The study offers a valuable toolkit for evolutionary and genomic research.