ppgardner-lecture07-genome-function.pdf
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This document outlines a lecture on measuring genome function, exploring the philosophical and biological definitions of 'function' in a genomic context. It discusses various evolutionary concepts, such as selected effects, constructive neutral evolution, and exaptation, while emphasizing the importance of biochemical, evolutionary, and genetic evidence in determining if genomic regions are functional. It also includes references to several studies and provides a framework for self-evaluation exercises in understanding functional DNA elements.
![Doolittle & Brunet quotes
▶ On accumulating transposable elements: “There is no
selective advantage to individuals within a species for doing
this, and evolution has no foresight [15]!”
▶ “A function concept embedded in one definitional framework
(SE) was (supposedly) refuted by empirical data based on
quite another (CR).”
▶ “it is the irrelevance of the majority of TEs (at least half of
our own DNA) to fitness at the organismal level that means
that “junk” is likely always to be a reasonable way to refer to
it”
▶ Final sentence: “If lungfishes have junk, or at the least
extraordinarily weakly or diffusely functional DNA in their
genomes, why is it that we think we do not?”
Doolittle & Brunet (2017) On causal roles and selected effects: our genome is mostly junk. BMC Biology.](https://image.slidesharecdn.com/ppgardner-lecture07-genome-function-230710220209-18d277c0/85/ppgardner-lecture07-genome-function-pdf-12-320.jpg)
ppgardner-lecture07-genome-function.pdf
- 1. GENE315: Measuring genome function Paul Gardner March 20, 2023
- 2. Objectives for lecture 07 ▶ An understanding of: ▶ How “function” in a genomic context can be defined. This is a surprisingly philosophical problem. ▶ Some strategies for determining if a genomic region is likely to be functional or not. OK Go (2010) This Too Shall Pass. Rube Goldberg machine
- 3. What are the “functional” bits in a genome? HG38 chr11::62,851,834-62,855,980. A famous region...
- 4. What is “functional”? ▶ ENCODE: “biochemically functional” i.e. anything with a reproducible biochemical activity is functional. ▶ Biological philosophy: ▶ “That A implies B does not entail that B must imply A.” ▶ I.e. Protein & ncRNA genes are transcribed, does not imply that all transcribed elements are genes (or functional). ▶ “Is the mere fact that X causes Y enough to say that Y is X’s proper function?” ▶ Doolittle & Brunet describe three posibilities based upon Darwinian evolution: ▶ Selected effect: a trait that was under positive selection in previous generations (now maintained by negative selection). ▶ Constructive neutral evolution: negative selection of traits that were never under positive selection. ▶ Exaptation: traits shaped by natural selection for some use other than their current one. ▶ I.e. evidence of evolutionary selection is required before claiming a function. Doolittle & Brunet (2017) On causal roles and selected effects: our genome is mostly junk. BMC Biology.
- 5. What is your theoretical model of the cell? Image sources: Wikimedia Commons & Prof. David S. Goodsell
- 6. What is “functional”? Doolittle & Brunet (2017) On causal roles and selected effects: our genome is mostly junk. BMC Biology.
- 7. What is “functional”? – the Gardner simplification EVIDENCE FOR MAINTENANCE BY NEGATIVE SELECTION, OR CURRENTLY UNDER POSITIVE SELECTION Based on Doolittle & Brunet (2017) On causal roles and selected effects: our genome is mostly junk. BMC Biology.
- 8. Some useful definitions ▶ Negative or purifying selection: the selective removal of alleles that are deleterious to fitness. ▶ Positive selection: Positive selection is the process by which alleles that increase organismal fitness also increase in frequency in a population. Booker et al. (2017) Detecting positive selection in the genome. BMC Biology.
- 9. ▶ Legend has it that the charismatic inventor of the “Kahungunu Wave” left many descendants (Ngā Tukemata o Kahungunu)
- 10. Some useful definitions ▶ Constructive neutral evolution: how complex biological systems might arrive via a series of neutral events. ▶ Almost synonymous with “Negative Selection”, as used by Doolittle. ▶ Exaptation: a trait (or gene) evolved to serve one particular function, but subsequently used to serve another. Lukes̆ et al. (2011) How a Neutral Evolutionary Ratchet Can Build Cellular Complexity. IUBMB Life.
- 11. A great example of Exaptation ▶ Xist (X-inactive specific transcript) is a long non-coding RNA required for X-inactivation in placental mammals ▶ Xist derived/exapted from a protein-coding pseudogene (Lnx3) ▶ Mutually exclusive phylogenetic pattern with Lnx3, sequence & synteny preserved and out-of-frame mutations in the mammals... Duret et al (2006) The Xist RNA gene evolved in eutherians by pseudogenization of a protein-coding gene. Science.
- 12. Doolittle & Brunet quotes ▶ On accumulating transposable elements: “There is no selective advantage to individuals within a species for doing this, and evolution has no foresight [15]!” ▶ “A function concept embedded in one definitional framework (SE) was (supposedly) refuted by empirical data based on quite another (CR).” ▶ “it is the irrelevance of the majority of TEs (at least half of our own DNA) to fitness at the organismal level that means that “junk” is likely always to be a reasonable way to refer to it” ▶ Final sentence: “If lungfishes have junk, or at the least extraordinarily weakly or diffusely functional DNA in their genomes, why is it that we think we do not?” Doolittle & Brunet (2017) On causal roles and selected effects: our genome is mostly junk. BMC Biology.
- 13. What is “functional”? – a more holistic point of view. ▶ Argue for using combinations of biochemical, evolutionary, and genetic evidence to elucidate genome function in human biology and disease.1 Kellis et al. (2014) Defining functional DNA elements in the human genome. PNAS. 1. there are many different levels of evolutionary evidence!
- 14. Our attempt... ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 1kGP SNP Count 1kGP Average MAF gnomAD Average MAF gnomAD SNP Count Covariance Min E−value Secondary Structure MFE Interaction Energy Avg Interaction Energy Min gnomAD SNP Density Accessibility Repeat Distance Sum 1kGP SNP Density Neutral Predictor Repeat Distance Min Genomic copies (E−val<0.01) RNAalifold Score Fickett score GERP Score Avg GC% Primary Cell RPKM Covariance Max RNAcode Coding Potential Tissue RPKM Primary Cell MRD PhastCons Avg GERP Score Max Tissue MRD PhyloP Avg PhyloP Max PhastCons Max 0 50 100 150 Mean Decrease in Protein−coding Gini Coefficient over 100 runs ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 1kGP SNP Count 1kGP Average MAF Fickett score gnomAD Average MAF gnomAD SNP Count RNAcode Coding Potential gnomAD SNP Density Neutral Predictor RNAalifold Score Genomic copies (E−val<0.01) Covariance Max 1kGP SNP Density Covariance Min E−value GC% Repeat Distance Min Repeat Distance Sum Interaction Energy Min PhyloP Max GERP Score Max GERP Score Avg Secondary Structure MFE Accessibility Interaction Energy Avg PhastCons Max PhyloP Avg PhastCons Avg Tissue MRD Tissue RPKM Primary Cell RPKM Primary Cell MRD 0 50 100 Mean Decrease in Short ncRNA Gini Coefficient over 100 runs ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 1kGP SNP Count Genomic copies (E−val<0.01) gnomAD SNP Count PhastCons Max RNAalifold Score Secondary Structure MFE Accessibility Interaction Energy Avg 1kGP SNP Density gnomAD Average MAF PhyloP Avg 1kGP Average MAF Interaction Energy Min PhastCons Avg Covariance Min E−value Repeat Distance Min Neutral Predictor RNAcode Coding Potential Repeat Distance Sum gnomAD SNP Density Fickett score PhyloP Max GERP Score Avg GERP Score Max Covariance Max Primary Cell RPKM GC% Tissue RPKM Tissue MRD Primary Cell MRD 20 40 60 Mean Decrease in lncRNA Gini Coefficient over 100 runs Feature type ● ● ● ● ● ● Intrinsic sequence Sequence conservation Transcriptome expression Genomic repeat association Protein/RNA specific features Population variation Proteins Short ncRNAs Long ncRNAs Cooper & Gardner (2021) Features of Functional Human Genes. bioRxiv.
- 15. Random sequence experiments identify lots of transcription (& translation) Recall Sean Eddy’s “Random Chromosome Project”? ▶ Neme et al (2017) “Random sequences are an abundant source of bioactive RNAs or peptides”. Nature Ecology & Evolution. ▶ ... “by expressing clones with random sequences in E. coli” ... “Contrary to expectations, we find that random sequences with bioactivity are not rare.” ▶ de Boer et al (2019) “Deciphering eukaryotic gene-regulatory logic with 100 million random promoters”. Nature Biotechnology. ▶ ... “we measure the expression output of > 100 million synthetic yeast promoter sequences that are fully random” ... “ it is often tacitly assumed that functional TFBSs are rare” ... “TFBSs are common in random DNA” ... “Abundant weak regulatory interactions explain most of expression level” NB. expression from random sequence is also reproducible!
- 16. Based upon the Doolittle & Brunet classification... ▶ Are the following elements likely to be a “Selected Effect”, “Constructive Neutral Evolution”, “Exapted” or no beneficial effect? Doolittle & Brunet (2017) On causal roles and selected effects: our genome is mostly junk. BMC Biology.
- 17. Complete the following table in small groups...
- 18. Ultra-conserved elements (UCRs) ▶ Highly conserved sequence (in mammals) Bejerano et al. (2004) Ultraconserved Elements in the Human Genome. Science. Snetkova et al. (2022) Perfect and imperfect views of ultraconserved sequences. Nature Reviews Genetics. UCNEbase: ultra-conserved non-coding elements database
- 19. Human accelerated regions (HARs) Positive selection since humans diverged from the human and chimp ancestor. ▶ Whalen & Pollard (2022) Enhancer Function and Evolutionary Roles of Human Accelerated Regions. Annual Review of Genetics.
- 20. Example: HAR1 ▶ Compare genome sequences, find otherwise conserved regions that are evolving rapidly in humans HAR1 in particular, appears to be involved in cortical development ▶ Pollard et al. (2006) Forces Shaping the Fastest Evolving Regions in the Human Genome. PLOS Genetics. ▶ Pollard et al. (2006) An RNA gene expressed during cortical development evolved rapidly in humans. Nature. Scale chr20: GWAS Catalog Chimp Gorilla Orangutan Gibbon Rhesus Crab-eating_macaque Baboon Green_monkey Marmoset Bushbaby Chinese_tree_shrew Squirrel Lesser_Egyptian_jerboa Prairie_vole Chinese_hamster Mouse Rat Naked_mole-rat Guinea_pig Chinchilla Brush-tailed_rat Rabbit Pika Pig Alpaca Bactrian_camel Killer_whale Tibetan_antelope Cow Sheep Domestic_goat White_rhinoceros Cat Dog Ferret_ Panda Pacific_walrus Weddell_seal Black_flying-fox Megabat David’s_myotis_(bat) Little_brown_bat Big_brown_bat Hedgehog Shrew Elephant Cape_elephant_shrew Manatee Cape_golden_mole Tenrec Armadillo Opossum Wallaby Chicken Common dbSNP(153) SINE LINE LTR DNA Simple Low Complexity Satellite RNA Other Unknown 100 bases hg38 63,102,050 63,102,100 63,102,150 63,102,200 63,102,250 63,102,300 63,102,350 63,102,400 63,102,450 Your Sequence from Blat Search GENCODE V39 (4 items filtered out) Basic Gene Annotation Set from GENCODE Version 39 (Ensembl 105) Pseudogene Annotation Set from GENCODE Version 39 (Ensembl 105) NHGRI-EBI Catalog of Published Genome-Wide Association Studies 100 vertebrates Basewise Conservation by PhyloP Multiz Alignments of 100 Vertebrates Short Genetic Variants from dbSNP release 153 Repeating Elements by RepeatMasker HAR1B HAR1B HAR1B ENSG00000274915 HAR1A HAR1B HAR1B HAR1B ENSG00000274915 HAR1A Wikipedia article: Human accelerated regions HAR1 in the UCSC genome browser.
- 21. 7SL RNA ▶ Also called SRP RNA, part of the signal recognition particle, involved in protein transport ▶ Universally conserved, orthologues are found in archaea, bacteria and eukaryotes. Scale chr14: GWAS Catalog Chimp Gorilla Orangutan Gibbon Rhesus Crab-eating_macaque Baboon Green_monkey Marmoset Bushbaby Chinese_tree_shrew Squirrel Lesser_Egyptian_jerboa Prairie_vole Chinese_hamster Mouse Rat Naked_mole-rat Guinea_pig Chinchilla Brush-tailed_rat Rabbit Pika Pig Alpaca Bactrian_camel Killer_whale Tibetan_antelope Cow Sheep Domestic_goat White_rhinoceros Cat Dog Ferret_ Panda Pacific_walrus Weddell_seal Black_flying-fox Megabat David’s_myotis_(bat) Little_brown_bat Big_brown_bat Hedgehog Shrew Elephant Cape_elephant_shrew Manatee Cape_golden_mole Tenrec Armadillo Opossum Wallaby Chicken Common dbSNP(153) SINE LINE LTR DNA Simple Low Complexity Satellite RNA Other Unknown 200 bases hg38 49,586,450 49,586,500 49,586,550 49,586,600 49,586,650 49,586,700 49,586,750 49,586,800 49,586,850 49,586,900 49,586,950 49,587,000 49,587,050 Basic Gene Annotation Set from GENCODE Version 39 (Ensembl 105) Pseudogene Annotation Set from GENCODE Version 39 (Ensembl 105) NHGRI-EBI Catalog of Published Genome-Wide Association Studies Vertebrate Multiz Alignment & Conservation (100 Species) Multiz Alignments of 100 Vertebrates Short Genetic Variants from dbSNP release 153 Repeating Elements by RepeatMasker RPS29 RPS29 RN7SL1 Cons 100 Verts Wikipedia article: Signal recognition particle 7SL in the UCSC genome browser.
- 22. Alu elements (I) ▶ Transposable element, derived from 7SL RNA. Over one million copies in the human genome ▶ Breaks a LOT of bioinformatics tools, frequently masked from genome sequences Wikipedia article: Alu element Dfam entry for the AluY family
- 23. Alu elements (II) ▶ Is the Alu element on human chromosome 14, between 31,474,114 and 31,473,798 likely to be functional? Scale chr14: GWAS Catalog Chimp Gorilla Orangutan Gibbon Rhesus Crab-eating_macaque Baboon Green_monkey Marmoset Bushbaby Chinese_tree_shrew Squirrel Lesser_Egyptian_jerboa Prairie_vole Chinese_hamster Mouse Rat Naked_mole-rat Guinea_pig Chinchilla Brush-tailed_rat Rabbit Pika Pig Alpaca Bactrian_camel Killer_whale Tibetan_antelope Cow Sheep Domestic_goat White_rhinoceros Cat Dog Ferret_ Panda Pacific_walrus Weddell_seal Black_flying-fox Megabat David’s_myotis_(bat) Little_brown_bat Big_brown_bat Hedgehog Shrew Elephant Cape_elephant_shrew Manatee Cape_golden_mole Tenrec Armadillo Opossum Wallaby Chicken Common dbSNP(153) SINE LINE LTR DNA Simple Low Complexity Satellite RNA Other Unknown 100 bases hg38 31,473,750 31,473,800 31,473,850 31,473,900 31,473,950 31,474,000 31,474,050 31,474,100 31,474,150 Your Sequence from Blat Search GENCODE V39 Basic Gene Annotation Set from GENCODE Version 39 (Ensembl 105) Pseudogene Annotation Set from GENCODE Version 39 (Ensembl 105) NHGRI-EBI Catalog of Published Genome-Wide Association Studies 100 vertebrates Basewise Conservation by PhyloP Multiz Alignments of 100 Vertebrates Short Genetic Variants from dbSNP release 153 Repeating Elements by RepeatMasker An Alu element in the UCSC genome browser. Mills et al. (2007) Which transposable elements are active in the human genome?
- 24. The main points ▶ “Function” measured in a variety of ways: ▶ Phenotypic: “biochemical” activity ▶ Evolutionary: evidence of positive/negative selection ▶ Genetic: knockout or mutation and compensation/complement ▶ A Darwinian definition of “function”: phenotype/activity AND evolutionary evidence (SE, CNE or Exaptation) ▶ Evolutionary evidence can be varied: usually based on sequence conservation or reduced SNPs ▶ Some suggest overlapping evidence of biochemical activity & evolutionary conservation (i.e. regions under negative selection).
- 25. Self-evaluation exercises ▶ Compare and contrast the ENCODE definition of function to the Darwinian definition proposed by Doolittle & Brunet (2017). ▶ Outline a method for determining if a predicted mouse gene is functional. What are potential pitfalls for the approach? ▶ Where do human-accelarated regions, ultraconserved regions, Xist, BC1 RNA and Junk DNA lie in Doolittle & Brunet (2017) classification of functional DNA? ▶ Justify your answers!
- 26. Further reading ▶ Doolittle & Brunet (2017) On causal roles and selected effects: our genome is mostly junk. BMC Biology. ▶ Kellis et al. (2014) Defining functional DNA elements in the human genome. PNAS. ▶ Neme et al (2017) Random sequences are an abundant source of bioactive RNAs or peptides. Nature Ecology & Evolution. Post questions on the FAQ GoogleDoc: https://docs.google.com/document/d/1PQd dp7C 0cXA8SwUv- qrkTOj8c8fUAt-U Z5dg2yc8/edit?usp=sharing
- 27. Genetics Mātai Ira otago.ac.nz/genetics Genetics Mātai Ira Social Mixer WHEN Wednesday 29th March 6.00pm to 8pm WHERE BIG13, ground floor Biochemistry Genetics Mātai Ira otago.ac.nz/genetics PIZZA&SOFTDRINKS PROVIDED!
- 28. Near Rakiriri, Otago Harbour, 7 May 2020.