Dr William Schierding
William came to New Zealand in 2012 after beginning his career in the United States, where he earned his Masters Degree in Genetic Epidemiology and then worked as a Programmer Analyst at the McDonnell Genome Institute at Washington University in St. Louis. In New Zealand, William completed his PhD at the University of Auckland (Liggins Institute, under the leadership of Wayne Cutfield and Justin O’Sullivan), where he was focused on the functional consequences of the three-dimensional structure of genome organization.
Research | Current
My areas of expertise involve the analysis of deep sequence data: genome mapping, variant detection, RNA-sequencing, methylome epigenetics, and metagenomics data.
In addition to my research, I also have joined a bioinformatics group with the goals of developing of a universal nationwide New Zealand bioinformatics teaching toolset. My current teaching role has centered around developing, delivering, and promoting a consistent bioinformatics infrastructure for the New Zealand research community.
My research focus is on the intersection of genetic and epigenetic research with modern “big data” approaches to answers. In this quest, William is actively seeking out answers in the analysis of high-throughput genetics (next generation sequencing) and the impact that common variations in genetic sequence have on the three-dimensional structure of the genome within the nucleus.
Hypothesis: Amongst 3 billion bases of DNA lurks some 10 million points of genetic variation, making us who we are as individuals. In some cases, those variants contribute to diseases. Around two-thirds of those disease-associated variants are in non-coding regions of the DNA, a major challenge to those hoping to attribute these variants to altered function. Ultimately, this makes it difficult for scientists to understand why this variation is hazardous to our health, leaving diagnosis tricky and remediation nearly impossible. Some of these non-coding genetic changes can alter structural relationships within the nucleus, altering regulatory patterns, resulting in disease risk in humans. Thus, the failure of GWAS to turn SNP associations into clinically-relevant (actionable) causes for disease has resulted from a genetic approach that tries to link the complex phenotype to only the local genetic landscape. My approach aims to describe how non-coding regions of the DNA alter 3D organization of DNA in the nucleus, resulting in altered function.
For example, applying structural genomics to the problem of post-term birth. Somewhere between 5-20% of all births are post-term (born after 293 days – 41 weeks – of gestation), an affliction that carries both short- and long-term health consequences for the child. We identified genetic influences on birth timing and related these changes to alterations in enhancer regions, altering the three-dimensional structure of the genome within the nucleus. From this, we identified several major pathways for possible pathogenesis, most notably haematopoiesis. The next steps here are to understand how genetic variation in this pathway can directly influence gestational timing, hopefully in a way to improve obstectric management of birth as well as to identify ways to mitigate the later-in-life health effects related to prolonged gestation.
Work at the institute has led to several successful collaborations within the UK, USA, and Finland.
Teaching | Current
I have joined a bioinformatics group with the goals of developing of a universal nationwide New Zealand bioinformatics teaching toolset. My current teaching role has centered around developing, delivering, and promoting a consistent bioinformatics infrastructure for the New Zealand research community.
Areas of expertise
William’s areas of expertise involve genome mapping, variant detection, RNA-sequencing, epigenetics, and analysing of environmental metagenomics data. Outside of his research, William’s teaching role at the University has centered around developing, delivering, and promoting a consistent bioinformatics infrastructure for the New Zealand research community.
Institute of Engineering and Technology (IET) (2016-2017)
University of Auckland Postgraduate Student Association (2012-2016) - Vice President 2015-16
Selected publications and creative works (Research Outputs)
- Schierding, W. S., Fan, V., & Poonawala, N. (2017). Bioinformatics Workshops A-C on R and R Shiny, RNAswq and Metagenomics. Paper presented at Annual Conference of the Genetics Society of Australasia with the NZ Society for Biochemistry& Molecular Biology, Dunedin, NZ. 2 July - 6 July 2017. Related URL.
Other University of Auckland co-authors: Nooriyan Poonawala-Lohani
- Schierding, W., Antony, J., Cutfield, W. S., Horsfield, J. A., & O'Sullivan JM (2016). Intergenic GWAS SNPs are key components of the spatial and regulatory network for human growth. Human molecular genetics, 25 (15), 3372-3382. 10.1093/hmg/ddw165
Other University of Auckland co-authors: Justin O'Sullivan, Wayne Cutfield
- Polin, R. A., Abman, S. H., Rowitch, D., & Benitz, W. E. (2016). Fetal and Neonatal Physiology. Elsevier Health Sciences. Pages: 2050.
- Pichugina, T., Sugawara, T., Kaykov, A., Schierding, W., Masuda, K., Uewaki, J., ... Nurse, P. (2016). A diffusion model for the coordination of DNA replication in Schizosaccharomyces pombe. Scientific reports, 610.1038/srep18757
Other University of Auckland co-authors: Justin O'Sullivan
- Schierding, W. S. (2016). The Third Dimension of Genetics: The Role of Spatial Genetics as Revealed by Common Human Variation The University of Auckland. ResearchSpace@Auckland.
- Griffith, M., Griffith, O. L., Smith, S. M., Ramu, A., Callaway, M. B., Brummett, A. M., ... Oberkfell, B. J. (2015). Genome Modeling System: A Knowledge Management Platform for Genomics. PLOS Computational Biology, 11 (7), e1004274-e1004274. 10.1371/journal.pcbi.1004274
- Schierding, W., & O'Sullivan JM (2015). Connecting SNPs in Diabetes: A Spatial Analysis of Meta-GWAS Loci. Frontiers in endocrinology, 610.3389/fendo.2015.00102
Other University of Auckland co-authors: Justin O'Sullivan
- Airhart, N., Brownstein, B. H., Cobb, J. P., Schierding, W., Arif, B., Ennis, T. L., ... Curci, J. A. (2014). Smooth muscle cells from abdominal aortic aneurysms are unique and can independently and synergistically degrade insoluble elastin. Journal of Vascular Surgery, 60 (4), 1033-1042.e5. 10.1016/j.jvs.2013.07.097