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10/20/19: Ronan is here!

Siobhan gave birth today to her baby boy Ronan! Congrats Siobhan and Geoff!

9/27/19: Christina defeneded her PhD

Christina today defended her PhD thesis titled Interpretable machine laerning in plant genomes: studies in the complex relationship between genotype and phenotype. The seminar was held in Plant Biology Lab 247 and was full! Christina’s parents also attended her seminar. In the talk, Christina laid out the overarching Christina is now moving to Australia working in algorithm development in single cell genomics studies. All the best Christina!

9/24/19: Sahra and Christina’s work on the regulatory mechanisms of cell-type stress response is published

Our story titled Cis-regulatory code for predicting plant cell-type transcriptional response to high salinity is now published in Plant Physiology with Sahra and Christina as joint first authors. Using the root cell-type transcriptome data, Sahra and Christina identified cis-regulatory sequences likely specify cell-type response to high salinity stress. More importantly, machine learning models were built to ask how well the identified regulatory sequences can predict cell-type response. The findings not only advance our understanding of the regulatory mechanisms of the plant spatial transcriptional response, but also suggest broad applicability of the approach to any species, particularly those with little or no trans regulatory data.

9/18/19: Christina’s work on benchmarking genomic prediction algorithms is published

Chrisitina’s paper on Benchmarking Parametric and Machine Learning Models for Genomic Prediction of Complex Traits is published today in G3. This is a collaborative between our colleague Gustavo de los Compos, Chrisitna’s internship mentors Andrew McCarren and Mark Roantree, and Emily Bolger a highly productive summer research student. Using data of 18 traits across six plant species with different marker densities and training population sizes, Christina spearheaded a comparison of the performance of six linear and six non-linear algorithms. The findings highlight that simpler, linear algorithm can beat out more sophiscated machine learning approaches, and the importance of algorithm selection for the prediction of trait values.

8/20/19: John’s work on poaceae intergenic transcription is published

John’s paper on Evolutionary characteristics of intergenic transcribed regions indicate rare novel genes and widespread noisy transcription in the Poaceae is published in Scientific Report. Christina as well as Rosalie Sowers, a highly talented undergrad from Penn State also contribute to this work. Extensive transcriptional activity occurring in intergenic regions of genomes has raised the question whether intergenic transcription represents the activity of novel genes or noisy expression. To assess this, John et al. evaluated cross-species and post-duplication sequence and expression conservation of intergenic transcribed regions. This study provides a framework to identify novel genes using comparative transcriptomic data to improve genome annotation that is fundamental for connecting genotype to phenotype in crop and model systems.

8/19/19: Our newest addition to the lab, Thilanka Ranaweera

Thilanka is a new graduate student in the lab. Thilnaka graduated from the University of Peradeniya in Sri Lanka in 2016 and worked as a teaching assistant in the past two years in Peradeniya. He is energetic, communicative, and excited about learning new topics. Welcome to the lab!

7/24/19: Siobhan got the Dissertation Completion Fellowship

Siobhan has been selected to receive a $7,500 College of Natural Science Dissertation Completion Fellowship during fall semester 2019. Congrats Siobhan!

7/13/19: Nick’s work on regulatory assymmetry of plant duplicate genes is published

Nick’s paper on Expression and regulatory asymmetry of retained Arabidopsis thaliana transcription factor genes derived from whole genome duplication is published in BMC Evoltionary Biology. Christina and Eamon Winship, an undergraduate reseracher at the time also contributed. Transcription factors (TFs) play a key role in gene regulation and tend to be retained after duplication. Nick et al.’s work provide answers about about how TF duplicates have diverged in their expression and regulation that contribute to a better understanding of the elevated retention rate among TFs.

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