Genes. Eukaryotic Protein-Coding Gene Structure codingnon-coding.

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Presentation transcript:

Genes

Eukaryotic Protein-Coding Gene Structure codingnon-coding

Regulatory Region  Size: 50 > 10,000 bp  Contains multiple small DNA sequence elements (5 – 20 bp) > bind regulatory proteins  Regulatory elements can be negative or positive acting  Regulatory regions found in 5’ flanking region, introns, and 3’ flanking regions – most common in 5’ flanking regions and large introns

5’-Untranslated Region  Contained in mRNA  Spans from start of transcription to start of translation  Multiple functions – translational efficiency  Size varies greatly - average > 300 nt (human) coding non-coding

Coding Sequence  Begins with initiator methionine (AUG codon)  Sometimes multiple initiator methionines are used  Stops with termination codon (UAA, UAG, and UGA)  Sizes varies: average = 1340 nt (human); encodes ~450 aa protein coding non-coding

3’ Untranslated Region  Spans translational termination codon > end of mRNA  Multiple functions: mRNA stability and localization  AAUAAA sequence signals where poly(A) is to be added (10-35 nt upstream from cleavage/poly(A) site)  Size varies: average nt (human) coding non-coding

Poly(A)  Added posttranscriptionally (not encoded in gene)  Size varies ( nt) depending on organism  Functions: mRNA stability and translational efficiency  Size of tract shortens with time  All mammalian mRNAs have poly(A) except histone mRNAs Poly(A)

Exons  Genes have a modular design  Evolutionarily assembled in pieces  Functional unit > exons  # exons can vary from 1 > 178  Average # exons/gene – different organisms  Yeast ~1  Drosophila 4  Human 9  Human genes (mean sizes)  Exon size 145 bp codingnon-coding

Introns  Introns vary greatly in size  Most ~ 50 bp but can be > 15 kb  Large genes – large introns  Small genes – small introns  Size differs between species  C. elegans 267 bp  Drosophila 487 bp  Human 3,365 bp  Human introns > exons in size Intron 2Intron 1

Genetics  Mutants  Wild-type – “normal” fully-active gene  Null – absence of any activity (e.g. deletion)  Hypomorph – reduced function  Hypermorph – enhanced activity  Neomorph – expressed in cells normally not expressed (transgenic approach)  Phenotypic analysis – development, morphology, behavior, fertility, etc.  Gene regulation  Examine how mutation in Gene A influences expression of other genes

Genetic and Molecular Genic Relationships  Organism Genes Lethal loci (%total genes)  Yeast 5,800 1,800 (30%)  Nematode 18,400 3,500 (20%)  Drosophila 13,600 3,600 (25%)  Mouse – similar % based on gene knockout studies  Lethal loci – loss of function mutant that results in death  Result: Only ~20-30% genes can be mutated to lethality

Genetic and Molecular Genic Relationships  Why are there genes with no apparent function?  Gene may not be doing anything  Other genes may compensate for defect (redundancy)  Double mutant analysis often provides evidence for this explanation  Common for highly-related genes to be (at least partially) redundant  Defect may be too subtle to detect  Proper assay not used  Need proper ecological setting and evolutionarily- relevant time span to detect  May be conditional

CNS Midline Cell Development and Transcription Requires Single-minded Function Cell division Wild-type Cell morphology Gene expression sim

Ubiquitously-Expressed Sim Transforms Entire CNS into CNS Midline Cells Heat shock-simRhomboid-lacZ Uninduced Induced  -LacZ

Gene Regulation  Regulatory proteins > DNA cis-control elements  Positive and negative regulation  Combinatorial regulation > highly specific patterns of spatial, temporal and quantitative expression Murine transthyretin gene

0.95 kb Toll-lacZ  -LacZ Sim:Tgo Binding Sites (CNS Midline Elements - CMEs) are Required for Midline Transcription 2431 XXXX CME > ACGTG

Array Analysis of Gene Expression: Drosophila  Understand complete array of gene regulatory events that underlie:  Development  Tissue and cell identity  Aging  Behavior  Circadian rhythms  Learning and memory

Example: Single-minded (Sim): Master Regulator of CNS Midline Cell Development and Transcription Sim protein (green) > CNS midline cells Vnd protein (red) > lateral CNS

Array Analysis of Gene Expression  Midline gene expression program > identify all genes expressed in midline cells  Study: function and regulation  Approaches:  Purify midline cells (GFP) > compare to other cell types and developmental time intervals  Mutant (sim) vs. wild-type  Misexpression of sim vs. wild-type  Transgenes – express in entire CNS  Genetics – snail mutant > express in entire mesoderm

Midline and Lateral CNS GFP Lines sim-GFPvnd-GFP Dissociate embryonic cells > FACS Compare expression at different stages and to other cell types Results: midline-specific transcripts high in midline cells when compared to levels in other tissues

Fluorescence Activated Cell Sorter (FACS) Allows isolation of fluorescently-labeled (GFP+) cells

Array Analysis of Gene Expression  Midline gene expression program > identify all genes expressed in midline cells  Study: function and regulation  Approaches:  Purify midline cells (GFP) > compare to other cell types and developmental time intervals  Mutant (sim) vs. wild-type  Misexpression of sim vs. wild-type  Transgenes – express in entire CNS  Genetics – snail mutant > express in entire mesoderm

Comparison of Wild-type to sim Mutant Embryos Wild-type sim Results: Expect to see midline gene expression reduced in sim mutant

Array Analysis of Gene Expression  Midline gene expression program > identify all genes expressed in midline cells  Study: function and regulation  Approaches:  Purify midline cells (GFP) > compare to other cell types and developmental time intervals  Mutant (sim) vs. wild-type  Misexpression of sim vs. wild-type  Transgenes – express in entire CNS  Genetics – snail mutant > express in entire mesoderm

Analysis of Midline Transcription by Ectopic Sim Expression: Transgenic Approaches sca-Gal4 X UAS-sim-GFP GFP  -Wrapper Wild-type  -Wrapper Result: Expect to see midline gene expression increased in sca-Gal4 X UAS-sim-GFP

Analysis of Midline Transcription by Ectopic Sim Expression: Genetic Approaches Wild-type snail sim RNA localization Result: Expect to see midline gene expression increased in snail mutant

Cluster Analysis of Combined Data Sets  Compare different data sets  Midline genes  Test by in situ hybridization for midline expression

Array Analysis of Mesoderm Gene Expression  Mesoderm  Somatic muscles  Visceral muscles  Fat body, hemocytes  twist gene  Encodes transcription factor required for mesodermal gene expression  twist mutant – no mesoderm or mesodermal gene expression  twist overexpression (Toll 10B mutation) – excess mesoderm and mesodermal gene expression

Twist Mutant and Overexpression Phenotypes

Mutant Embryo Purification  twist is embryonic lethal mutation  twi / + X twi / + only 25% embryos are mutant (twi / twi)  Use GFP-CyO chromosome and sort mutant embryos GFP-CyO / twi twi / twi GFP-CyO / GFP-Cyo

Mutant Sorting  GFP-labeled organisms  Hand sort with fluorescence microscope  Machine sort

Array Analysis: Clustering Confirm expected expression pattern by in situ hybridization