Post Doctoral Associate | Statistical Genetics of Sugar Kelp Improvement | School of Integrative Plant Science, CALS
Post Doctoral Position in Statistical Genetics of Sugar Kelp Improvement School of Integrative Plant Science
College of Agriculture and Life Sciences Cornell University
The College of Agriculture and Life Sciences is a pioneer of purpose-driven science and home to Cornell University's second largest population of students, faculty and staff. We work across disciplines to tackle the challenges of our time through world-renowned research, education and outreach. The questions we probe and the answers we seek focus on three overlapping concerns: natural and human systems; food, energy and environmental resources; and social, physical and economic well-being.
The position is in the lab of Jean-Luc Jannink, Section of Plant Breeding and Genetics at Cornell, and is part of a large ARPA-E grant to develop open-ocean grown sugar kelp (Saccharina latissima). Saccharina latissima is a brown algae or kelp. It is phylogenetically distant from both plants and animals, having diverged from green algae early in the evolution of eukaryotes. The project will explore its genome, the population history of New England sugar kelp, and take advantage of its biphasic lifecycle to rapidly domesticate it using cutting edge genomic selection methods.
The Section of Plant Breeding & Genetics, within the School of Integrative Plant Sciences, trains interdisciplinary scientists in the elaboration of new breeding methods, the discovery of genetic mechanisms important for economically important traits, and the development of genetic stocks, germplasm, and varieties. Cornell University plant breeders are world leaders in innovative plant breeding research, teaching, and extension, and we collaborate globally.
The Jannink lab works with several crop species (wheat, oat, barley, cassava, and kelp) to develop new genomic prediction methods and integrate them optimally within breeding schemes. Many researchers are active in this area. We work together to discover, build on, and share new ideas and tools from across computational disciplines that lead to successful applied breeding outcomes.
The postdoc will collaborate with scientists at the Woods Hole Oceanographic Institute, the University of Connecticut, and the HudsonAlpha Institute for Biotechnology. We are a team discovering together how to address a range of challenges from evaluating many unique genotypes in common gardens, to isolating high molecular weight DNA in kelp, to designing breeding schemes around the kelp life cycle. Primary tasks for the postdoc include the bioinformatic analysis of a large panel of resequenced haploid kelp gametophytes to identify variants, use the panel as an imputation reference population, and estimate important population genetic parameters of New England sugar kelp. Individuals from this panel have been mated and their sporophyte progeny are being evaluated off the Massachusetts and New Hampshire coasts by collaborators. The postdoc will be the team's expert resource on bioinformatics and quantitative genetic questions. The postdoc will analyze data from experiments for genome wide association between variants and multiple phenotypes, for the training of genomic prediction models, and for estimating parameters of kelp population and quantitative genetics. Based on these analyses, the postdoc will select among newly-generated gametophytes genotyped by low-depth skim sequencing. Finally, the postdoc will design and analyze validation field experiments measuring the performance of progeny sporophytes. Further possibilities for the data include research on linear models to predict heterosis and the identification of evolutionary conservation and signatures of selection in the sugar kelp genome.
Term is one year renewable for an additional year contingent on performance.
Anticipated Division of Time
Experimental and breeding program design and data analysis-60%
Communication and coordination with collaborators-20%
Preparation of quarterly reports to ARPA-E-10%
Training of lab members and collaborators in statistical genetics and genomics-10%
Position Requirements: Ph.D. in statistical, population or quantitative genetics with experience or interest breeding applications, or Ph.D. in plant or animal breeding with emphasis on genomics, or population and quantitative genetics.
Preferred Specific SkillsSequence alignment and variant calling methods. Variant imputation methods. Genome-wide association studies and genomic prediction methods. High-dimensional data analysis. Basic notions of mating designs in breeding. Optimization and experimental design for field studies. Analysis of multi-generation breeding experiments. Quantitative genetic analysis of trials, estimation of inbreeding depression and variance components. Proven scientific writing ability and communication skills.
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