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Introduction to Genomics

Introduction to Genomics

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Introduction to Genomics

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  1. Welcome Introduction to Genomics BL3300/FW 3300 (Syllabus is emailed to all students but could be available from Dr. Joshi also)

  2. Who is your instructor? • Shekhar Joshi (Chandrashekhar P. Joshi) • Dr. Joshi • Professor of Plant Molecular Genetics, SFRES • Over 20 years of research experience • Molecular Genetics, Biotechnology, Bioinformatics • 50+ papers, 17 book chapters,100+ presentations • Michigan Tech Research Award winner of 2011 and NSF Career award winner in 2003 • Teaching molecular genetics at MTU since 1998 • This genomics class is offered since 2001 •

  3. Where and when can you find me? • Room # 168, Forestry Building • Office Hours: I am generally available between 9 am to 6 pm on all weekdays • MWF between 4-5 pm after this class (better to take my appointment). • Phone: 906-487-3480 • Email: • Web site: • For those who walk up from the main campus: Do call me or email me before walking up the hill to meet me!

  4. Why was this course proposed? Genomics is the study of genome structure and function. This is a new and exciting area that has recently witnessed many conceptual and technical advances. This information is vital to our day-to-day living in this century. Such a course would also make our students competitive in current job market Bioinformatics majors needed this type of class and now all biochemistry/molecular biology major students will need this class too.

  5. Course Description The main purpose of this course is to introduce concepts of human genomics that can also be applied to microbial, plant and animal genomes. The topics covered are: • Genes and genome organization • Genome mapping • DNA fingerprinting • Gene tagging • Bioinformatics • Legal and Ethical aspects of genomics • Genome evolution

  6. What will you learn in this class? Genes, expression and characters What is genomics? Central dogma: DNA to RNA to Proteins Features of human genome How is genome sequenced and studied? Applications of genomics in Agriculture, Medicine and Bioenergy

  7. Essential Details • Credits: 3 • Time: Monday, Wednesday and Friday 3 pm-4 pm • Place: Forestry G002 • Class Paper: • Genomics meets Hollywood! (more on this later) • Note: Class paper presentations will be held between December 5th and 9th, 2011.

  8. Not-Required Text Book • Genomics • Philip N. Benfey and Alexander D. Protopapas (Pearson Prentice Hall) (For 2006 updates go to • 2005 • Recent book • Up to date • Real genomics book • Ready made slides and space for notes • Updates available

  9. Additional Reading • Optional Reading material (No need to buy it) • Genomes by T.A. Brown, 1999, John Wiley & Sons, NY • Genes VIII by Benjamin Lewin, 2003, Oxford University Press • Molecular Biology by Robert F. Weaver, 1999, McGraw-Hill Press • Genome by Matt Ridley, Harper Collins, 2000 • Introduction to Genomics by Arthur M. Lesk, 2007, Oxford University Press

  10. Grades Grading Point System • 100-95 A • 94-90 AB • 89-85 B • 84-80 BC • 79-75 C • 74-70 CD • 69-65 D • < 64 F • Course point distribution • Class participation 10% (attendance, attention & participation) • Home work, quizzes etc 20% • Class paper 10% (class paper) • Mid-term exam 30% (October 12th or 14th, 2011) • Final exam 30% (around December 12) keep your cell phones on silent mode or put them off.

  11. Class paper • Each discussion group will consist of four-five students (you form your own group and let me know by email) • Each of you will see a movie that uses DNA, genes, genomics or genetic engineering as a theme (e.g. Jurassic park) and write a 3-5 page overview of that movie and submit to me electronically by November 4th, 2011. • You will discuss the movie that you selected with the group • You ALL in each group will select one movie that you want to present to the class and one of you will present it • Tell the class about your movie selection: its main theme, the plot and how it fits with the topic of the class. • Provide your interpretations about accuracies and discrepancies of science depicted in those movies. • If you were the writer/director, how would you improve it to portray the science more accurately (but not making it a complete flop) • One representative per group will present a 10 minute powerpoint talk sometime between December 5-9, 2011. • Questions?

  12. University Policies • or student handbook • Academic Integrity: plagiarism • Attendance Policy: email me if absent • Code of Conduct: follow the laws of the land • Computer Use Policy: use responsibly Please visit this site and make sure that all your actions in the class are within the bounds of these policies.

  13. Class coverage • Chapter 1: Introduction • Revision: Cells, Genes and Genomes • Chapter 2: Technical Foundations of Genomics • Chapter 3: Fundamentals of Genome Mapping and Sequencing • Chapter 4: Genome sequencing • Chapter 5: RNA expression analysis • Chapter 6: The Computational Foundations of Genomics • Chapter 7: High-Throughput Genetics • Chapter 8: Proteomics • Chapter 13: The Structure of Genomes • Chapter 15: Genomics and Medicine • Chapter 19: Genomics and Agriculture • Chapter 20: Ethical issues of genomics

  14. What is the definition of genomics? Study of genomes

  15. What is the genome? Entire genetic compliment of an organism

  16. How many types of genomes are there in this world? Prokaryotic genomes Eukaryotic Genomes Nuclear Genomes Mitochondrial genomes Choloroplast genomes

  17. Why should we study genomes? • Each and everyone is a unique creation! • Life’s little book of instructions • DNA blue print of life! • Human body has 1013 cells and each cell has 6 billion base pairs (A, C, G, T) • A hidden language/code determines which proteins should be made and when • This language is common to all organisms

  18. What can genome sequence tell us? • Everything about the organism's life • Its developmental program • Disease resistance or susceptibility • History • Where you are going?

  19. How is human genome organized? • 3% coding and rest of it junk (repetitive DNA). • Nuclear and mitochondrial • You are 99.99% similar to your neighbor

  20. Why human genome? • We want to know about ourselves • How do we develop? • How do we struggle, survive and die? • Where are we going and where we came from? • How similar are we to apes, trees, and yeast?

  21. How will we change in this century because of the Genomics? • You will control the destiny of this planet • Big changes in our own life • Biotechnology: more products • GMOs: More food-More problems? • Our society will not be the same! • Individualized medicine • Gene therapy • Immortality? Disease free life?

  22. Are we playing GOD? Central dogma in Molecular Biology

  23. DNA sequence DNA to RNA to Proteins • 1 gtcgacccac gcgtccgtct tgaaagaata tgaagttgta aagagctggt aaagtggtaa • 61 taagcaagat gatggaatct ggggctccta tatgccatac ctgtggtgaa caggtggggc • 121 atgatgcaaa tggggagcta tttgtggctt gccatgagtg tagctatccc atgtgcaagt • 181 cttgtttcga gtttgaaatc aatgagggcc ggaaagtttg cttgcggtgt ggctcgccat • 241 atgatgagaa cttgctggat gatgtagaaa agaaggggtc tggcaatcaa tccacaatgg • 301 catctcacct caacgattct caggatgtcg gaatccatgc tagacatatc agtagtgtgt • 361 ccactgtgga tagtgaaatg aatgatgaat atgggaatcc aatttggaag aatcgggtga • 421 agagctgtaa ggataaagag aacaagaaga aaaagagaag tcctaaggct gaaactgaac • Protein coding regions of Genes begin with ATG and end with either TAG, TGA or TAA • atg atg gaa tct ggg gct cct… use genetic code.. • M M E S G A P ..* • Study function of proteins and expression of genes in different organs and tissues transcription translation

  24. Wild type What genomics has to do with me?

  25. Why horse is a horse and duck is a duck? It is in their genes! DNA structure was discovered in 1953 DNA replicates by making a copy of itself and passes to next generation of cells or organisms Purity of lineages maintained Biotechnology: fish genes in plants

  26. Now look at your neighbor and say Hi! What do you see? Someone is different than you! Could be that your friend differs in his/her sex, looks, nature, smartness, or simply the way he/she dresses and talks How much similarity you think you share with your friend at the gene level? 99.9% so we could fix genes if we want

  27. Now look at your own hands and legs Do they look similar? No! But they contain the same DNA in each of their cells DNA makes RNA makes proteins Different genes are expressed differently in different cells, tissues and organs of an organism Having a gene does not mean it will be expressed.

  28. Someone has a cancer gene! It is a normal gene that got mutated or changed and does not perform same job But having a gene does not mean you will get cancer Because environment has a big role in turning a gene on or off Different genes and their products also interact: microecosystem Genes do not work alone (G X E)

  29. Genomcis is the study of all genes present in an organism

  30. Origin of terminology The term genome was used by German botanist Hans Winker in 1920 Collection of genes in haploid set of chromosomes Now it encompasses all DNA in a cell In 1986 mouse geneticist Thomas Roderick used Genomics for “mapping, sequencing and characterizing genomes” New terms: Functional genomics, transcriptomics, proteomics, metabolomics, phenomics (Omics)

  31. What is genomics? A marriage of molecular biology, robotics, and computing Tools and techniques of recombinant DNA technology e.g., DNA sequencing, making libraries and PCRs High-throughput technology e.g., robotics for sequencing Computers are essential for processing and analyzing the large quantities of data generated

  32. Origin of Genomics Human Genome Project Goal: sequence 3 billion base pairs High-quality sequence (<1 error per 10 K bases) ACGT Immensity of task required new technologies Automated sequencing Decision to sequence other genomes: yeast and bacteria Beginnings of comparative genomics

  33. Technical foundations of genomics Molecular biology: recombinant-DNA technology DNA sequencing Library construction PCR amplification Hybridization techniques . . Log MW . . Distance

  34. Genomics relies onhigh-throughput technologies 200 Automated sequencers Fluorescent dyes Robotics Microarray spotters Colony pickers High-throughput genetics ABI3700

  35. Industrial-scale genomics laboratory

  36. Bioinformatics: computational analysis of genomics data Uses computational approaches to solve genomics problems Sequence analysis Gene prediction Modeling of biological processes/network

  37. Genome sequencing Analogy: Complete works of an author in partially understood language Two approaches Page by page All at once

  38. Page-by-page sequencing strategy Sequence = determining the letters of each word on each piece of paper Assembly = fitting the words back together in the correct order

  39. All-at-once sequencing strategy Find small pieces of paper Decipher the words on each fragment Look for overlaps to assemble

  40. Genome size and gene number Amoeba dubia: 670 billion base pairs

  41. Lessons from sequencing Variability of genome structure: junk Duplication events Transposons Microsatellites Repetitive DNAs 1 2 3 4 5

  42. Functional genomics Once we know the sequence of genes, we want to know the function The genome is the same in all cells of an individual, except for random mutations However, in each cell, only a subset of the genes is expressed The portion of the genome that is used in each cell correlates with the cell’s differentiated state

  43. Analogy for gene expression Genome is a hard drive of a computer Contains all the programs Gene expression What’s loaded into RAM (short-term memory) Subset of genome used in each cell

  44. Gene-by-gene approach to understand biological processes Analogous to understanding circuitry by following wires Choose one wire Follow circuit to transistor Follow from transistor to capacitor Follow from capacitor to power source Do again

  45. Genomics provides a parts list Provides list of all parts Parts list in itself doesn’t say how the genome works Can use to get global picture e.g., RNA expression

  46. Genomics applications to biology Cellular function Microarrays: RNA Proteomics: proteins Cellular networks: Metabolites Evolutionary mechanisms Comparative genomics

  47. Expression microarrays Global expression analysis RNA levels of every gene in the genome analyzed in parallel Compare with Northern blot Microarrays contain more information by many orders of magnitude

  48. Biological networks: Systems Biology Neuronal network Transcriptional network Food chain

  49. From parts to systems Parts list + interactions = road map Properties = traffic patterns Want to understand properties Why certain traffic patterns emerge Perturb system and see how it responds Place traffic light at intersection