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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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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...
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Survival Tree01:19

Survival Tree

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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
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Phylogenetic Trees03:21

Phylogenetic Trees

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Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.
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Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
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Chi-square Analysis02:46

Chi-square Analysis

44.4K
The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
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Gene Duplication and Divergence02:37

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...
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Related Experiment Video

Updated: Feb 21, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

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Species Tree Estimation Using ASTRAL: How Many Genes Are Enough?

Shubhanshu Shekhar, Sebastien Roch, Siavash Mirarab

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |October 5, 2017
    PubMed
    Summary

    This study determines the number of genes needed for ASTRAL to accurately reconstruct species trees, providing theoretical bounds and simulation validation for phylogenetic analysis.

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    Area of Science:

    • Phylogenomics
    • Computational Biology
    • Evolutionary Biology

    Background:

    • Species tree reconstruction from genomic data is crucial for understanding evolutionary relationships.
    • Incomplete lineage sorting (ILS) is a major challenge in accurate species tree inference.
    • ASTRAL is a popular method for inferring species trees from gene tree topologies.

    Purpose of the Study:

    • To derive theoretical sample complexity for ASTRAL, quantifying the number of genes required for high-probability species tree reconstruction.
    • To validate these theoretical bounds using simulation studies.
    • To provide practical insights into ASTRAL's performance under various evolutionary scenarios, including the anomaly zone.

    Main Methods:

    • Derivation of theoretical sample complexity bounds for the ASTRAL algorithm.
    • Conducting simulation studies to empirically test the theoretical predictions.
    • Analyzing simulation results under different evolutionary conditions, including the anomaly zone.

    Main Results:

    • ASTRAL requires a specific number of gene trees to reconstruct the species tree with high probability, dependent on the number of species (n) and the shortest branch length (ρ).
    • Theoretical bounds were validated by simulation studies, showing consistent trends.
    • Simulations provided practical insights into the conditions favoring ASTRAL's accuracy.

    Conclusions:

    • The study provides a theoretical framework and empirical validation for the sample complexity of ASTRAL.
    • The findings offer guidance on the amount of genomic data needed for reliable species tree reconstruction using ASTRAL.
    • Results enhance our understanding of ASTRAL's performance and limitations in phylogenomic analyses.