Showing posts with label genetic background effects. Show all posts
Showing posts with label genetic background effects. Show all posts

Friday, September 13, 2013

Our new pre-print: An integrative genomic approach illuminates the causes and consequences of genetic background effects

This is a guest post by Dr. Chris Chandler. Cross posted from Haldane's Sieve.

Biologists have long recognized that a mutation can have variable effects on an organism's phenotype; even introductory genetics classes often make this observation by introducing the concepts of penetrance and expressivity. More mysterious, however, are the factors that influence the phenotypic expression of a mutation or allele. We know, for instance, that introducing the same mutation into two different but otherwise wild-type genetic backgrounds can result in vastly different phenotypes. But what specific differences between these two genetic backgrounds interact with the mutation, and how? And how does gene expression fit into this puzzle? Answering these questions has not been an easy task, which is not too surprising when you realize that penetrance and expressivity are, in reality, complex quantitative traits. We therefore adopted a multi-pronged genetic and genomic approach to tease apart the mechanisms mediating background dependence in a mutation affecting wing development in the fly Drosophila melanogaster.

The phenotypic patterns seen in our model trait have already been characterized: the scalloped[E3] (sd[E3]) mutation has strong effects in the Oregon-R (ORE) background, resulting in a tiny, underdeveloped wing, while its effects in the Samarkand (SAM) background are still obvious but much less extreme, resulting in a blade-like wing.

To try to find out what causes these differences, we generated and combined a variety of datasets: whole-genome re-sequencing of the parental strains and a panel of introgression lines to map the background modifiers of the sd[E3] phenotype; transcription profiling (using two microarray datasets and one RNA-seq-like dataset), including analyses of allele-specific expression in flies carrying a "hybrid" genetic background; predictions of binding sites for the SD protein, which is a transcription factor; and a screen for deletion alleles that enhance or suppress the sd[E3] phenotype in a background-dependent fashion.

Our results point to a complex genetic basis for this background dependence. We found evidence for a number of loci that are likely to modulate the effects of the sd[E3] allele. However, some unexpected inconsistencies provide a cautionary tale for those intending to take a similar mapping-by-introgression approach for their trait of interest: do multiple replicates, and introgress in both directions, or you may inadvertently end up mapping some other trait! Although the number of candidate genes we identified were generally large, by combining those results with data from our other datasets, we were able to narrow our focus to those showing a consistent signal, yielding a robust set of candidate genes for further study. Without getting into too much detail, we also used a novel approach to show that background-dependent modifier deletions of the sd[E3] phenotype (of which there are many) involve higher-order epistatic interactions between the sd[E3] mutation, the deletion, and the genetic background, rather than quantitative non-complementation (so more than two genes were involved).

Overall, we think that an integrative approach like this could be useful for others trying to understand complex traits, including genetic background-dependence of mutations. In addition, if you're a Drosophila researcher working with the commonly used Samarkand or Oregon-R strains, our genome re-sequencing data (raw and assembled), including SNPs, will soon be available in public repositories for genetic data.


Wednesday, July 24, 2013

Genetics really is hard (to interpret)

I am sure this will not surprise most of you, but genetics research can be really hard. I don't simply mean that doing genetics experiments is hard (which it can be), but interpreting the results from genetic analysis can be difficult.  This post is about an interesting story involving the analysis of a a gene called I'm not dead yet (Indy) in the fruitfly Drosophila (one of the geneticists favorite organisms) and its role in extending lifespan. This story, that has taken place over the past decade has taken a number of interesting twist and turns involving many of the subjects that I like to discuss in this blog and my own work, including trying to make sense of the results from genetic studies, the influence of factors like genetic background and environment on mutational effects, and of course Drosophila itself. While I do not study lifespan (longevity), I have been interested, and following the story for this research over the past 5-6 years because of the implications of the influence of genetic background effects (which I do work on).  I should also mention that other than being a geneticist I do not claim to have any great knowledge of the study of aging, but I will do my best on that.

I hope in this (and future) posts to accomplish a few things, so I thought I would lay them all out first (in case I start to ramble off in strange directions).

  1. Describe a cool story about something important to just about everyone (who does not want to find out how to live longer).
  2. Discuss the means and logic of how genetic analysis. That is how we (geneticists) go about figuring out whether a particular gene (or variant of a gene) influences something we care about (like how long we live).
  3. Context matters a lot for genetic analysis. Factors like the food used to feed your critters (among many others factors), and the genetic background (of the critters) that the mutation is studied in can profoundly change what you see (the results).
  4. Scientists, even when making honest efforts to perform good, reproducible research can get different results because of seemingly subtle differences in 2&3. 


Not surprisingly, many scientists are interested in the biology of aging, and in particular in what factors influence longevity. In addition to it being very cool, and of obvious importance to many people on the planet, it is also important for aspects of evolutionary theory. The point being that many scientists are interested, and approach questions of aging from many different perspectives, which is great. It is also not surprising that geneticists (and again the general public) are interested in finding genes that influence the aging process (why do some people live longer than others). So in the year 2000 (you know, when all of our computers did not shut down) when a paper entitled "Extended life-span conferred by cotransporter gene mutations in Drosophila" came out, there was a lot of buzz. The basic results suggested that reducing the function or expression of a particular gene, Indy increased how long fruit flies lived. While we (the people) are not fruit flies, by the year 2000 research had already clearly demonstrated that there were many shared genes in all animals (including people and flies), and many seemed to have pretty similar functions. Thus explaining the excitement and buzz. By the way, Indy is short for "I'm not dead yet", and if you do not get the reference check this out (start at 0:58 if the two minutes is too long), or here if you prefer it in musical form, or here as a cartoon.

So what did they do in this study? The punchline is that using multiple, independently generated mutations they demonstrated that as you reduced Indy expression and function, the fruit flies lived for a longer time (increased longevity) when compared to the fruit flies with normal (wild-type) copies of the Indy gene. Seems straightforward enough, and by using multiple independent mutations they demonstrate (at one level) the repeatability of the results. That is, there results are not some strange one-off random results, but can be reproduced, which provides some degree of generality to these results.

Of course, results are rarely so simple and clear, and with additional investigations layers of complexities are often demonstrated.  Studying longevity can be particularly difficult, and not only because you will have to wait a long time to see when something dies of natural causes.

So does Indy actually influence lifespan? The short answer is that the results from follow up studies have been pretty mixed, so it is perhaps not as clear as hoped from the original study. More on that soon in subsequent posts!

References and links if you want more information from the original studies
Rogina B, et al. (2000) Extended life-span conferred by cotransporter gene mutations in Drosophila. Science 290:2137–2140.

Toivonen, et al. 2007. No influence of Indy on lifespan in Drosophila after correction for genetic and cytoplasmic background effects. PLoS Genetics. 3(6):e95

Wang, et al. 2009. Long-lived Indy and calorie restriction interact to extend life span. PNAS USA. 106(23):9262-7. doi: 10.1073/pnas.0904115106

Toivonen JM, Gems D, Partridge L. Longevity of Indy mutant Drosophila not attributable to Indy mutation. Proc Natl Acad Sci USA. doi: 10.1073/pnas.0902462106.

Helfand, SL. et al., 2009. Reply to Partridge et al.: Longevity of Drosophila Indy mutant is influenced by caloric intake and genetic background. 106(21): E54. doi:  10.1073/pnas.0902947106.

Frankel. S. & B. Rogina. 2012. Indy mutants: live long and prosper. Frontiers in Genetics. 3(13). doi: 10.3389/fgene.2012.00013

Rogina B, Helfand SL. 2013. Indy mutations and Drosophila longevity. Front Genet. 4:47. 
  doi: 10.3389/fgene.2013.00047