Pathways between Genes and Behaviour

Functional Genomics Understanding the pathways between genes and behaviours (i.e., mechanisms of genes affecting behaviour) Levels of analysis DNA Genome RNA Transcriptome Protein Proteome Brain Neurome Mind Behaviour Phenome

Levels of Analysis Functional genomics –Bottom up –Start at level of cells, molecular biology –Work up to more complex systems Behavioural genomics –Top down –Identify relevant/interesting behaviour –Reductionism towards genes Between level relationships correlational until proven causal –E.g., behaviour can change brain structure, just as structural changes can alter behaviour

Transcriptome Gene expression throughout the genome Gene expression beginning point for gene to behaviour pathway Housekeeping genes –Expressed at steady rate; most cells, most times “Special purpose” genes –Only expressed when needed, at particular developmental points, when activated by other genes or environmental stimulus…

Factors on Expression Altering rate of transcription initiation Alteration of RNA transcript –Passage of mRNA out of nucleus –Protection/degradation of RNA transcript in cytoplasm Rate of translation Posttranslational modification of protein

Gene Expression Profiling DNA permanent RNA ephemeral and specific RNA microarrays –1000s of genes simultaneously monitored –Study effects of treatments, diseases, developmental stages on gene expression –“Snapshots” of gene expression throughout genome

Brain Mapping Can create an atlas of localized patterns of gene expression Need brain tissue, so limited in humans and issues of pathology Mouse brain atlas Such maps are functional, because genes only detected if expressed

Genetical Genomics Emphasizes links between genome and transcriptome Treats gene expression as phenotypic trait Aim is to find expression QTLs (eQTLs) associated with gene expression Primarily with rodent models

Gene Expression & Environment Individual differences in gene expression Not necessarily highly heritable Gene expression responds to intra- and extra- cellular environmental variation Environmental influence at transcript level quite significant Consider gene expression as a phenotype Epigenesis: gene-gene effects and environment- gene effects

The Proteome Refers to entire compliment of proteins Complexity increase from transcriptome –Many more proteins than genes –Post-translation from mRNA, amino acid sequences can be modified, changing their function –Protein function is affected by other proteins; they work in complexes

Analysis Like transcriptome, consider proteome as a phenotype Hence, gene and environmental interaction Useful, given high individual differences in protein function in different tissues –Protein trait: differences in quantity of protein in different tissues Protein microarrays –Antibodies detect specific proteins –Limited capacity (100s of proteins on array)

Early Protein Microarray Findings Most proteins show linkage to several regions Chromosomal positions often differed from those of the genes that code for the proteins Suggests multiple genes affect individual protein traits

The Neurome Another step up in complexity Trillions of synapses vs. only billions of DNA base pairs 100s of neurotransmitters Brain phenotypes called endophenotypes

Circadian Rhythm Approximately daily periodicity Endogenously generated, although modifiable by external cues From prokaryotic cyanobacteria to humans

Period Konopka & Benzer (1971) Fruit fly Three mutant lines of flies showed shorter, longer, and no circadian rhythm All mutations mapped to same gene, named period Conservative gene –Responsible for Familial Advanced Sleep Phase Syndrome in humans Not the only gene involved; interactions between many genes

PER Genes Per1, Per2, Per3 Members of period family of genes Expressed in suprachiasmatic nucleus –Bilateral brain region, located in anterior hypothalamus; controls circadian rhythms –E.g., rats with SCN damage have no circadian rhythm; they sleep the same amount, but polyphasically for random lengths

Mice Per2 and Bmal1 work in opposition Per2 peaking for sleep Bmal1 peaking for wakefulness

Humans Per2 and Bmal1 work together Both peak around the same time

Lark vs. Owl Genes influencing morning or night person Per2 produces high RNA levels around 4AM; associated with sleeping Food influences gene expression; Per2 has small peak after food intake (post-lunch “slump”) REV-ERB works in opposition to Per2, peaking its expression around 4PM; associated with wakefulness Recent research looking to see if environmental factors (e.g., shift work) can permanently alter gene expression

Pleiotropy Clock genes have many functions Period found to have role in long term memory Per genes may be involved in influencing effect and abuse of drugs like cocaine Disruption of genes linked to bipolar disorder, cardiovascular disease, effects of drug toxicity

Learning and Memory Short-term memory Long-term memory Long-term potentiation –Long-term synaptic changes

Drosophila Dunce and rutabaga: first learning and memory mutants Disrupts STM, but LTM works fine Encode components of an intracellular signaling pathway involving cAMP, protein kinase A, and a transcription factor (CREB) < en.wikipedia.org/wiki/Image:Drosophila_ melanogaster_-_side_%28aka%29.jpg>

Mouse Targeted mutations Hippocampus Knocked out  -CaMKII –Increased difficulty learning spatial tasks Well over 20 genes known to affect learning and memory in mice –Change strength of synaptic connections

Long-Term Potentiation Genes drive long-term potentiation But not an easy mechanism to understand 1000s of protein components involved Numerous systems –Glutamate receptor, NMDA receptor, CREB, etc., etc., etc. None of the fly or mouse genes and signaling molecules involved are exclusive to learning processes Many necessary for basic cell functions –Is memory being regulated by modulating background function of cells involved in memory encoding?