Johanna Osterman

Genomic selection tools such as linear mixed models for trait prediction rely heavily on genetic information, i.e. whether an individual is homozygote or heterozygote for a given marker. However, for outcrossing crops, data is collected on a population or family level; hence, the genetic data summarises the allele frequency for each marker. Thus, any information about the distribution of heterozygotes versus homozygotes is lost. During my visit I will aim to investigate possible estimates of this genotype distribution from allele frequency information and see whether these estimates can be implemented in a genomic section pipeline leveraging both additive and dominance genetic variation.

Goals:

• Evaluate modes of estimating allele frequencies 
• Find appropriate models for estimating genotype distribution in populations

• Assess the inclusion of estimated genotype distribution to estimate additive and dominance genetic variation with LMM models and evaluate how much data is required for best accuracy of genomic prediction.

I have graduated from Umeå University with a Master of Science in Engineering with a specialisation in biotechnology. For my PhD, which I’m currently obtaining from the Swedish University of Agriculture (SLU), I pivoted to plant breeding as I have a great interest in statistical modelling and R coding.

I am specifically interested in:

Programming language and software:

Knitting, crochet and sewing:

I enjoy creating my own items of clothing, from pattern drafting to final product. It gives me a nice perspective of the hard work that goes in to an item of clothing. I love working with my hands and there are more arts and crafts I’d like to try.

Hiking and fitness:

I love spending time in the great outdoors no matter the weather. And even though fitness doesn’t always give me instant joy it’s something I value a lot. However sometimes I get stuck in researching it instead of just going for a workout.