Lecture 11+12.docx

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Ecology & Evolutionary Biology
Stephen Wright

Lecture 11+12:  Humans and chimps protein sequences are very similar: only 1% difference  Regulatory mutations account for differences  Measuring expression: 1. Microarrarys: Measures the amount of RNAs that bind to probes, tag sample with fluorescent dye and the array have probes with specific sequences, look at fluoresce of the probe to determine expression level. Problem: genetic divergence can cause variance in binding 2. RNA-sequencing: short-read sequencing of RNA, thus number of reads is equal to expression level. RNA sample, change it to cDNA and then sequence it and thus short reads are aligned to reference sequence  Gene expression is controlled in cis and trans:  Cis: regulates directly regulate the gene that is located on that same molecule of DNA  Trans: regulates the expression of distant genes  Cis variation can cause allele-specific expression (differences in expression of alleles): more reads in one of the copies than the other-homeospecific regulation  Cis is 1) specific to a specific location at a specific time, and thus cis regulation contributes to adaptation: if individual misses cis regulatory then reduce pelvis and thus might deleterious  Cis-regulation also avoids deleterious pleiotropy  Lactose intolerance: in Europeans cis regulates lactase expression. Lactase persistence is associated with multiple noncoding variants, which evolved independently in European and African populations  Local elements could act in trans and not cis.  How has selection affected expression divergence between humans and other primates?  What happens to gene expression in absence of selection  How does selection shape expression variation within humans?  Approaches: 1. Focus on expression level variation (phenotype)  Small population: mutations will accumulate although they may be deleterious  What happens to gene expression in mutation accumulation lines (MAL): compare expression in MAL to natural lines  X-axis is gene expression, y-axis is the log p value, gene expression are more likely to be differentially expressed  MAL for selection are weak, increase amount of genes have higher p value and thus are under stabilizing selection  Comparing expression levels between humans and other relatives: if no selection then there is a lot of variation between and within species,  Purifying selection will have little variation between and within species  Positive selection will have more variation between species and little variation within specieis  Some genes show evidence of positive selection in some lineages: expression study, where DUSP6 is more highly expressed in humans, perhaps is positive selection? However it might be because we drink more alcohol and thus we need to increase human longevity  Difficult to disentangle genetic variation from environmental variation 2. Find regulatory regions and study evolution in them (genotype)  Association mapping to find eQTLs (expression QTL)  eQTLs are single nucleotide polymorphisms associated with or causes variation in gene expression  If T causes lower expression and G has higher expression, then they are eQTL  Pickrell et al. found eQTLs for 900 genes only looking at variants located near genes  X is position, Y is expression levels. Thus different expression levels in gene QTL in indivbiduals with GG, GA and AA. Since GA has an intermediate value then G and A are codominant to each other  Local eQTLs show allele specific expression (they mostly act in cis)  However Pickrell only looked for associations between expression level and a limited set of common genetic variants, these variants may affect expression directly or they may just be linked to the casual variants. A more powerful approach would be to use whole-genome data to find the causal genetic variants  Finding eQTLs for divergence between humans and other primates:  Mapping QTLs in the offspring of
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