In-depth transcriptomics analysis of lncRNA to identify potential functional candidates to improve fertility in cattle
Advisor: Dr. Angela Canovas, Animal Biosciences
The thesis proposal is framed into an ongoing project at the Canovas Lab, at the department of Animal Biosciences, University of Guelph, focused on cow fertility. Preliminary results of the project looked into potential key regulatory genes associated with the early embryonic and early pregnancy loss in cows. Although cow fertility has been studied thoroughly in the past, this project is novel as the group is specifically interested in genes and biomarkers associated with the early embryonic loss. This could provide producers with better selection criteria, facilitating the selection of cows with improved fertility and reproduction system. To achieve this goal, experimental samples were collected at two different stages to study early embryonic loss (day 8 following breeding to collect in vivo produced blastocysts before implantation) and early pregnancy loss (day 21-28 following breeding to compare the transcriptome of a developing fetus (“pregnant”) to a dead/regressing fetus (“not pregnant”). At day 8 following breeding (early embryonic loss), embryos are classified as of “good quality” or “poor quality” (e.g. total cell number, inner cell mass versus trophectoderm cell number ratio). Transcriptome analysis was carried out on uterus tissue samples using RNA-Sequencing from pregnant and non-pregnant cows in several lactations.
The objective of the BINF thesis will be to complete in deep transcriptomics analysis detecting lncRNA (using RNA-Sequencing data) to identify a list of potential candidate genes affecting the early embryonic and early pregnancy loss and its possible pleiotropic effect on other production traits. Also, identification of metabolic pathways involved in the quality of embryos (first critical step for embryos survival) and in early pregnancy loss, comparing the whole transcriptome of “good quality” vs “bad quality” embryos, and “pregnant” vs “not pregnant This research will provide a better understanding of the underlying biological processes involved in fertilization and the establishment of pregnancy in cattle. Currently, there is a unique opportunity to understand the nature of complex phenotypes such as embryo survival by integrating structural and functional genomic data from new high-throughput –OMICS technologies into a systems biology approach. Thus, this research will lead to the identification of functional genes and causal networks affecting embryonic mortality. This knowledge could be incorporated into breeding programs to increase the rate of genetic progress for embryo survival.