Tree of Life and Phylogenetic Relationships.pptx

In this presentation i have discussed on the phylogenetic relationship and tree of life. Along with that i have also added many examples to interpret easily by undergraduate and postgraduate students of Botany, taxonomy, molecular systematics, biotechnology etc.

1. Tree of Life and Phylogenetic Relationships By Dr. Ratan Chowdhury Assistant Professor, Department of Botany Rangapara College (Autonomous)

2. Traditionally, taxonomy relied on visible characters like shape, anatomy, or physiology. But these can be misleading, since unrelated species may look alike due to convergent evolution. Molecular data, especially DNA and RNA, provides a deeper, more accurate picture. Phylogenetics studies evolutionary history, while molecular systematics uses genetic sequences to classify organisms. Together, they allow us to build trees of life.” By the end of today’s lecture, you should be able to: Understand how phylogenetic trees are built and interpreted. Appreciate the role of 16S and 18S rRNA in classification. Learn about the three domains of life proposed by Carl Woese . Recognize the evolutionary trends and relationships that link all organisms into one great web of life. INTRODUCTION

3. What is a Phylogenetic Tree? A phylogenetic tree is like a family tree, but instead of tracing your ancestors, it traces the evolutionary ancestry of species. It is a hypothesis about how organisms are related. Imagine that all organisms alive today are the tips of a great branching tree. If we follow those branches backward in time, they eventually join at points called nodes . Each node represents a common ancestor that gave rise to two or more lineages. At the base of the tree, there is usually a root , which represents the most ancient ancestor, sometimes called the Last Universal Common Ancestor (LUCA) .

4. Morphological characters were used in classical systematics (e.g., flower structure, bone morphology). Molecular data (DNA, RNA, protein sequences) is now the standard, especially for microbes. Main methods: Distance-based methods UPGMA, Neighbor -Joining → compare genetic distances between sequences Character-based methods Maximum Parsimony → fewest evolutionary steps Maximum Likelihood & Bayesian Inference → probability/statistics-based approaches Methods of Tree Construction Phylogenetic trees can be built using two main approaches. Distance-based methods use overall genetic distances, while character-based methods analyze each DNA site. Distance methods are fast but less precise, while character-based methods are more accurate but computationally heavy.”

5. 1. Distance-Based Methods These methods calculate an overall genetic distance between pairs of organisms, based on how many differences exist in their sequences. Imagine comparing two sentences: “The cat sat on the mat.” “The cat sat on the hat.” Only one word is different, so the sentences are very similar. Similarly, in DNA sequences, if there are fewer changes, the organisms are considered closer relatives. a. UPGMA (Unweighted Pair Group Method with Arithmetic Mean) Assumes a constant rate of evolution (molecular clock). Simple but not always realistic. b. Neighbor-Joining (NJ) More flexible; does not assume equal rates of evolution. Good for large datasets. These methods are fast and practical, but they sometimes oversimplify evolutio UPGMA clusters species by average similarity, assuming all lineages evolve at the same rate. It produces ultrametric trees, where all tips are equidistant from the root. This works only if the molecular clock holds true. Neighbor-Joining is more flexible. It does not assume constant rates, instead minimizing total branch length. It can handle unequal evolutionary speeds and is widely used in real-world phylogenetics.

6. Examples of Phylogenetic trees made with UPGMA and NJ methods

7. Character-Based Methods Instead of looking at the overall difference, these methods consider each site in the sequence individually and try to find the most plausible tree. a. Maximum Parsimony (MP) Principle: The simplest explanation is the best . Chooses the tree that requires the fewest evolutionary changes (mutations). Analogy: If you find footprints in the sand, you first assume they were made by one person walking , not by two people hopping in a strange pattern. “In character-based approaches, Maximum Parsimony finds the tree with the fewest evolutionary steps – the simplest explanation. Maximum Likelihood uses models of DNA evolution, asking which tree makes the observed data most probable. Bayesian Inference goes further, combining data with prior knowledge to give probability values for branches. These methods are more accurate but computationally intensive.

8. b. Maximum Likelihood (ML) Uses a statistical model of evolution . For each possible tree, it calculates the probability that the observed DNA sequences would have evolved along that tree. Chooses the tree with the highest likelihood . Analogy: It’s like asking, “Given how language usually changes over time, which family tree of languages is most probable?”

9. c. Bayesian Inference Very similar to Maximum Likelihood, but goes a step further. It combines data (sequence information) with prior knowledge (previous information, models, or assumptions). Produces a set of possible trees with probabilities (posterior probabilities). Analogy: A weather forecast doesn’t just say “it will rain” or “it will not rain.” Instead, it says “There’s a 70% chance of rain.” Similarly, Bayesian methods say “There’s an 85% probability this branch is correct.” These methods are more accurate but also computationally intensive .

10. How to Interpret a Tree? Branch length may represent amount of genetic change. Topology shows relationships, not time. Bootstrap values (statistical support for a branch) – higher value = more reliable. Outgroup is used to root the tree.

11. What is Molecular Systematics? Using molecular sequences instead of morphology to study relationships. Provides more accuracy, especially in microbes where morphology is limited. Ribosomal RNA is the most widely used molecular marker in systematics. Because rRNA is essential for protein synthesis, it exists in all organisms. Conserved regions change slowly and help compare distantly related species. Variable regions evolve faster and separate closely related groups. 16S rRNA is used for bacteria and archaea, while 18S is used for eukaryotes. This approach revolutionized taxonomy.”

12. Why rRNA (16S/18S rRNA)? 16S rRNA : found in prokaryotes (Bacteria + Archaea) 18S rRNA : found in eukaryotes Features: Present in all organisms Highly conserved regions (for deep evolutionary comparison) Variable regions (for distinguishing close relatives) Large curated databases (SILVA, RDP, GenBank)

13. Identifying bacteria in environment (metagenomics) Resolving microbial taxonomy Discovering unculturable organisms Reconstructing evolutionary history Applications

14. Based on Carl Woese’s rRNA-based classification, life is divided into three domains. In the 1970s, Carl Woese used 16S rRNA to compare life forms. He discovered that prokaryotes actually consist of two very different groups – Bacteria and Archaea. Along with Eukarya, these form the three domains of life. Archaea, though prokaryotic, are genetically closer to eukaryotes than to bacteria. This was a revolutionary shift in biology.” Domains of Life

15. Early life was dominated by simple microbes. Eukaryotes evolved when one cell engulfed another, leading to mitochondria and chloroplasts – the endosymbiotic theory. But life is not a simple tree. Microbes frequently exchanged genes horizontally, across lineages and even across domains. Mitochondria and chloroplasts are examples of bacterial genes inside eukaryotes. This gives us a ‘Web of Life’ rather than a strict tree

16. Bacteria Prokaryotes with peptidoglycan cell walls Extremely diverse in metabolism: Photosynthetic (cyanobacteria) Nitrogen-fixing (Rhizobium) Pathogens (E. coli, Mycobacterium) Found everywhere – soil, water, human body Archaea Prokaryotes but not bacteria Unique features: Cell walls lack peptidoglycan Membrane lipids are ether-linked (not ester) Genetic machinery (transcription/translation) is closer to eukaryotes Many are extremophiles : Thermophiles (heat-loving) Halophiles (salt-loving) Methanogens (produce methane) Eukarya Organisms with nucleus and organelles Includes protists, fungi, plants, and animals Likely originated via endosymbiosis : Mitochondria from alpha-proteobacteria Chloroplasts from cyanobacteria

17. From prokaryotes to eukaryotes → endosymbiosis played a key role. Multicellularity → evolved independently in plants, fungi, and animals. Horizontal gene transfer (HGT) is common in microbes → complicates the simple “tree of life.” Modern view: “Web of Life” rather than just a tree. Evolutionary Trends and Relationships

18. Phylogenetic trees are tools for visualizing evolutionary hypotheses. Molecular systematics, especially using 16S/18S rRNA , has revolutionized taxonomy. Life is classified into Bacteria, Archaea, and Eukarya . Evolutionary relationships reveal both vertical descent and horizontal gene transfers , shaping biodiversity. Phylogenetic trees help us hypothesize evolutionary relationships. rRNA has become the gold standard of molecular classification. Life can be grouped into three domains – Bacteria, Archaea, and Eukarya – but evolution is more complex than a branching tree. Horizontal gene transfer shows that life is interconnected in a web. This gives us a deeper, more dynamic understanding of evolution Conclusion

19. References Textbooks Campbell Biology (Urry et al., 12th ed., 2020) – Chapters on evolution, phylogeny, and classification. Molecular Systematics (Hillis, Moritz & Mable, 3rd ed., 1996) – Classic introduction to phylogenetic methods. Evolutionary Analysis (Herron & Freeman, 5th ed., 2014) – Clear explanations of phylogenetic tree construction and evolutionary theory. Principles of Systematics (Simpson, 2005) – Covers classical and modern taxonomy. Microbial Diversity and Phylogeny – In Brock Biology of Microorganisms (Madigan et al., 16th ed., 2020). Online Databases & Resources NCBI Taxonomy Browser – https://www.ncbi.nlm.nih.gov/Taxonomy (Explore evolutionary placement of organisms). SILVA rRNA Database – https://www.arb-silva.de (Widely used for 16S/18S rRNA classification). Tree of Life Web Project – http://tolweb.org (Interactive and student-friendly). PhyloT – https://phylot.biobyte.de (Simple online tool to generate phylogenetic trees).

20. Thank You