We're looking to hire at least one more postdoctoral researcher in population genetics! Come join us!
Our paper on the comparison of the distribution of fitness effects (DFE) between species is now out! We found that humans have more strongly deleterious nonsynonymous mutations than do flies. Extending to yeast and mice, we found that the average selection coefficient tends to become more deleterious with increasing species complexity. Additionally, genes we believe to be less pleiotropic tend to have a more skewed DFE. These patterns are consistent with Fisher’s geometric model, where species complexity and long-term population size are key drivers in determining the DFE. Congratulations Christian!
Our paper describing our inferences of the distribution of fitness effects (DFE) in humans using large samples of individuals is now out! Here we extend the Dadi software package (Gutenkunst et al. 2009) to efficiently estimate a DFE. We apply the method to estimate the DFE for nonsynonymous mutations in humans using samples of hundreds to thousands of individuals. We find fewer strongly deleterious mutations than inferred in previous studies. The FitDadi software and parameter files implementing our new DFEs for several population forward simulations programs can be found here. Congratulations Bernard!
We have developed a forward simulation program under the PRF model. This program can quickly generate frequency spectra and frequency trajectories of neutral and selected alleles in complex demographic scenarios. The program can be downloaded from here.
Our paper examining patterns of neutral sequence divergence between species is out! We find that linked neutral divergence, even between distantly related species (e.g. human-mouse) is reduced near genes and is correlated with the strength of background selection in humans. Further, we show using coalescent models that linked selection can affect the variance in the distribution of divergence across the genome, even when the average amount of ancestral polymorphism is low. Congratulations Tanya!
Congratulations to Dr. Diego Ortega Del Vecchyo
Congratulations to Dr. Diego Ortega Del Vecchyo on successful his dissertation defense in July! Diego is the first student to graduate from the Lohmueller lab! He has set the bar quite high! We wish Diego the best of luck as he goes on for a postdoc at UC Berkeley!
Our paper in collaboration with Bob Wayne's group examining patterns of neutral and deleterious genetic variation in genome sequencing data from California channel island foxes has been published in Current Biology. In particular, we find that population bottlenecks have led to extremely low genetic diversity in the island populations relative to the gray fox. In particular, the San Nicolas island fox has the lowest genetic diversity seen in any of 159 eukaryotic species surveyed to date. Further, we find an increase in the proportion of deleterious variants per individual on the island populations relative to the mainland. We also found a higher number of deleterious alleles per individual in the island populations and a greater number of homozygous loss of function mutations in the island populations. These findings suggest an accumulation of deleterious variation in the small island populations.
Special congratulations to Jaqueline Robinson (UCLA EEB graduate student with Bob Wayne), and Diego, Bernard, and Clare in my group for their hard work on this project! Jacqueline's paper has been covered in the UCLA Newsroom, The New York Times, Why Evolution is True (Posted May 2016).
New paper in PNAS by Marsden et al. on deleterious mutations in dogs
Our paper examining patterns of deleterious genetic variation in genome sequencing data from dogs and wolves has been published in PNAS. In particular, we find that population bottlenecks have led to an accumulation of deleterious variants in dogs compared to wolves. Additionally, regions of the genome surrounding selective sweeps carry more amino acid changing variants than regions away from sweeps, suggesting that natural selection for one trait can increase nearby deleterious variation.
Special congratulations to Clare and Diego in my group for their hard work on this project! Clare and Diego's paper has been covered in The New York Times, The Scientist, The Daily Mail, and the LA Times (Posted January 2016).
New paper in BMC Bioinformatics describing Lab Retriever
Our paper with Keith Inman and Norah Rudin describing the Lab Retreiver soffware has been published in BMC Bioinformatics. This method allows one to assess the evidentiary weight of challanging forensic DNA proifles. Software is available here.
New paper in AJHG by Kim & Lohmueller!
Our paper suggesting that simple demogrpahy & natural selection cannot explain higher Nenaderthal ancestry in East Asian than European popualtions has been published in AJHG. Congratulations to 2nd year Lohmueller Lab graduate student Bernard Kim on his first publication!
Welcome to Ying Zhen!
Ying Zhen will be joining our group (along with Tom Smith's group) as a postdoc this fall to study population genetics of non-model systems. Previously, Ying was a postdoc with Peter Andolfatto at Princeton. Welcome Ying! (Posted August 2014).
Welcome to Christian Huber!
Christian Huber will be joining our group as a postdoc this fall. Previously, Christian was a graduate student at the Vienna Graduate School of Population Genetics where he was supervised by Ines Hellmann, Magnus Nordborg, and Joachim Hermisson. Welcome Christian! (Posted August 2014).
Kirk's paper on the impact of recent population history on patterns of deleterious variation and the architecture of complex traits has now been published in PLoS Genetics!
Many human populations have dramatically expanded over the last several thousand years. I use population genetic models to investigate how recent population expansions affect patterns of mutations that reduce reproductive fitness and contribute to the genetic basis of complex traits (including common disease). I show that recent population growth increases the proportion of mutations found in the population that reduce fitness. When mutations that have the greatest effect on reproductive fitness also have the greatest effect on a complex trait, more of the heritability of the trait is due to mutations at very low-frequency in populations that have recently expanded, as compared to populations that have not. Also, under this model, for a given sample size and false-positive rate, fewer variants show statistically significant associations with the trait in the population that has expanded than in one that has not. Both of these findings suggest that recent population growth may make it more difficult to fully elucidate the genetic basis of complex traits that are directly or indirectly correlated with reproductive fitness Read more about this work. (Posted June 2014).
Postdoctoral position is available!
We are looking to hire a postdoc to work on evolutionary genomics of non-model taxa. This position will be jointly advised by Tom B. Smith in the Center for Tropical Research and by Kirk. Please see the following ad for a more detailed description of the position! Review of applciations will begin on June 1, 2014. (Posted April 2014).
Welcome to Megan Roytman!
Megan Roytman, a first year PhD student in the Bioinformatics program, is rotating with us this quarter. Megan will be working on population genetic models for complex disesae risk. Welcome Megan! (Posted March 2014).
Welcome to the new Lohmueller Lab website!
Though Kirk has been at UCLA for several months, the group finally has a proper website! Please check back frequently for updates on what we’re up to in the lab and beyond! (March 2014)
Our analysis of exome sequencing data for type 2 diabetes has now been published in AJHG!
By analyzing exome sequencing data from 1,000 Danish individuals with type 2 diabetes and 1,000 without, we did not detect any significant association between low-frequency coding variants and type 2 diabetes. Nevertheless, this result is informative regarding the genetic architecture of type 2 diabetes. Using quantitative genetic models, we found that if low-frequency coding genetic variants account for much of the heritability of type 2 diabetes, they must be scattered in more than 20 distinct genes. Read more about this work here.