News

Congratulations to postdoc Justin Conover, who has accepted a position as Assistant Member and Principal Investigator position at the Donald Danforth Plant Science Center in St. Louis, MO. The Conover Lab will open June 1, 2025, and will be broadly interested in polyploid evolutionary genomics. Projects in the lab will range from population genetics to better understand the auto-allopolyploid continuum, to comparative genomics of diploids that have experienced ancient polyploidy events.

Low-pass genome sequencing is cost-effective and enables analysis of large cohorts. However, it introduces biases by reducing heterozygous genotypes and low-frequency alleles, impacting subsequent analyses such as demographic history inference. We developed a probabilistic model of low-pass biases from the Genome Analysis Toolkit (GATK) multi-sample calling pipeline, and we implemented it in the population genomic inference software dadi. Our model is widely applicable and substantially improves model-based inferences from low-pass population genomic data.

The Genomic History Inference Strategies Tournament (GHIST) is an annual competition to showcase methods for inference from population genomic data. This year the focus is demographic history. Join the competition!

Congratulations to Linh Tran, who successfully defended her PhD in Genetics. After graduation, she will be doing a postdoc with Alison Feder at the University of Washington.

Together with Lindi Wahl's group, we have posted a preprint in which we use cancer genomic data to reveal the differing strategies hypermutator and nonhypermutator tumors use to access adaptive mutations.

Former postdoc Xin Huang and research professional Travis Struck have spearheaded the development of a command-line interface for dadi. This interface not only makes dadi much easier to use, it also supports parallel and distributed computing. Read about it in our preprint, and find the code on GitHub.

Our paper modeling homeologous exchange between chromosomes within polyploids is now published in Genetics.

PhD student Linh Tran has developed a remarkably efficient approach to infer demographic history models from allele frequency spectra using feedforward neural networks. The preprint shows that this approach is just as accurate as likelihood optimization using dadi, while being instantaneous with a pre-trained model. To enable usage, we have pre-trained a wide selection of models, which our software donni will automatically download from the CyVerse DataCommons.

Justin Conover has been awarded and NSF Postdoctoral Research Fellowship in Biology to work together with our group and Mike Barker's group. Justin's research will focus on the effects of polyploidy on distributions of fitness effects. He will testing whether DFEs differ between an allotetraploid and its diploid progenitors, and he will also extend our joint DFE approach to test the correlation of fitness effects between subgenomes.

Undergraduate student Olivia Fernflores has been named a 2023 Beckman Scholar. This prestigious award will fund Olivia's research for two summers plus an academic year and enable her to travel to several conferences.