The epigenetic fate of introgressed DNA in the wheat genome

Bread wheat (Triticum aestivum) is the source of 20% of all calories consumed worldwide. Understanding its biology and
genetics is essential in developing a sustainable and productive agricultural landscape. Modern bread wheat derived from
the hybridisation of the two cereal species (Aegilops tauschii and Triticum turgidum) approximately 10,000 years ago. The
limited number of individuals involved in this hybridization, and subsequent inbreeding, mean that bread wheat has
reduced levels of genetic diversity. This lack of diversity diminishes the ability of breeders to create cultivars able to
respond to present and future environmental challenges. Introgression, the transfer of genetic material between related
species, has been successfully exploited in breeding programs to overcome this bottleneck and expand the diversity of the
bread wheat genome and to introduce agronomically beneficial traits. But how are introgressed genetic elements adapting
to the host genome and why are some introgressions retained and others removed from the genome? These are the
questions at the heart of this PhD project that combines functional wheat genomics with chromatin genetics and
bioinformatics to provide a cutting-edge training experience for the next generation plant scientists.
As part of the project, the student will initially characterise the transcriptional activity of introgressions in established and
newly created wheat accessions by RNA sequencing. Next, DNA methylation and histone H3K27me3 markings will be
analysed by bisulfite sequencing and chromatin immunoprecipitation. Both epigenetic modifications are important
mediators in the control of foreign genetic elements. These analyses will be accompanied by Hi-C experiments to study
the integration of the introgressed segment into the 3D genome of the host. Together, these analyses will enable the
student to define shared pattern in the genetic adaptation of introgressed segments. To analyse and evaluate the
generated large-scale datasets the student will be trained in the application of advanced bioinformatic analysis pipelines
of high-throughput data and essential coding skills.