From oocytes to table eggs: the help from computer scientists

Shau-Ping Lin
Institute of Biotechnology, National Taiwan University

Thursday 29 August 2019
11:00 - 12:00
EM 1.83

Abstract

Germ cells that make sperms and oocytes, are critical for passing the genetic materials to the next generation. The quality of germ cells, including special marks partly in the form of “epigenetic modifications”, is critical for the survival and health status of the offspring. Oocytes (female germ cells/ eggs) are not only critical for reproduction, but can also serve as a reprogramming agent to turn skin cells into an animal (the animal cloning technique as introduced by Dolly-the-sheep). In this interdisciplinary seminar, I will surf through the journey for my career as a reproductive biologist and epigeneticist using mouse, human, chicken and axolotl as model organisms. I will highlight the help I have been getting from computer scientists and bioinformaticians along the way. I will then introduce the unexpected twist since 2018, in extending the horizon of my lab research direction into facilitating the implementation of artificial intelligence tools into layer-egg industry. Collaborating with Dr. Jessica Chen-Burger, we tackle the quest for establishing simulation model that is needed to estimate the table egg profitability after implementing the AI related facilities. In addition, I will introduce briefly about the application of big data based tools to optimize the marketing strategy in digital commerce and evaluate their applicability in layer-egg industry.

Bio

Dr. Shau-Ping Lin is professor of National Taiwan University, Institute of Biotechnology, Taipei, Taiwan. She was previously PostDoc of the Columbia University, New York City, U.S.A. She obtained her PhD from the University of Cambridge, Cambridge, U.K.

Dr. Shau-Ping Lin has over 27 years of research experience in reproductive biology, embryo development and epigenomic modulatory mechanisms in germ cells and stem cells. She identified the genomic imprinting control center (Nature Genetics, 2003b) for a developmentally necessary (Development, 2007), functional non-coding RNA containing (Nature Genetics, 2003a), Dlk1-Dio3 imprinted locus. Her recent work further indicated that the expression of long non-coding RNA (lncRNA), Meg3, and its associated downstream lncRNAs and microRNAs are critical for maintaining full neurological lineage differentiation potential in human pluripotent stem cells, and can reduce cancer formation risk in stem cell based therapy in regenerative medicine (Stem Cell Research & Therapy, 2015). Meg3 is also critical for attracting proper epigenomic signature determining the body section identity of motor neuron lineage cells (Elife, 2018).

In order to gain further insight into how RNA and protein factors guided the epigenomic editors for spatial temporal gene modulation, her lab tackled how PIWI-interacting small RNAs and an epigenetic co-factor, DNA methyltransfearse 3-like (DNMT3L, Nature, 2007), facilitate transcriptional regulation on genes and transposable elements in developing germ cells and germline stem cells (BMC Genomics, 2018; Development, 2014; J Virology, 2014; Reproduction, 2015a). Throughout the course of these studies, her lab discovered that ectopic expression of DNMT3L in aging somatic cells could introduce epigenetic reinforcement on aging related relaxation of developmentally regulated genes and retrotransposons, and thus bypass senescence (J Virology, 2014; manuscript submitted). Prof. Shau-Ping Lin’s recent research activity also concerns comparing and contrasting germ cell characterization across mouse, human and chicken. She also recently extended her research scope into neuro-degeneration field, in the Parkinson’s disease, Parkinsonism and Alzheimer Disease model in human and mouse. In addition, she is involved in the discovery of epigenomic mechanism behind neural dependent limb regeneration in axolotl model (Dev. Biol, 2019; manuscript in preparation). Her 55 peer-reviewed publications is cited for over 3600 times.

Host: Jessica Chen-Burger