YALI BIO

About the start-up

Yali Bio is a biotechnology startup that is using precision fermentation to produce dairy fats for plant-based foods. Yeast strains are engineered and fermented to produce specific lipid profiles that mimic animal fats.

Project Title

Genetic Drivers of Enhanced Lipid Production in Yeast

Project summary

Yali Bio has developed a platform for engineering yeast strains to produce valuable lipids. By introducing targeted genetic modifications to fatty acid and lipid biosynthesis pathways, we have created a library of engineered strains. This project will utilise bioinformatics to elucidate the genetic determinants of enhanced lipid production in these strains compared to their wild-type counterparts. Through comparative genomics, gene annotation, and variant analysis, we aim to uncover the molecular mechanisms underlying lipid accumulation. Specifically, we will identify SNPs and characterise enzyme homologs to understand their roles in lipid metabolism. By correlating genetic variations with phenotypic data, we seek to establish a foundation for optimising lipid production in yeast. The novel fats and lipids that Yali Bio will generate from these engineered strains will be used as ingredients in dairy and food applications. The candidate’s projects will align with the workflow of the strain engineering team, and will facilitate the team reaching the target milestones.

RESponsibility

The candidate will conduct a comprehensive bioinformatics analysis to elucidate the genetic basis of lipid production in engineered yeast strains. This role encompasses genome annotation, variant identification, comparative genomics, and enzyme characterization. The candidate will analyse genome sequences from both wild-type and genetically modified Yali yeast strains, identifying genes and their functions. They will then identify and characterise SNPs to understand genetic variation and its impact on lipid production. By comparing genome sequences, the candidate will pinpoint genomic regions associated with phenotypic differences. Finally, they will characterise enzyme homologs and domains to explore their roles in lipid metabolism. A robust bioinformatics pipeline, including data quality control, gene prediction, variant calling, and comparative genomics, will be employed. This research will significantly contribute to our understanding of lipid biosynthesis in Yali yeast strains.

About the candidate

The ideal candidate for this role:

• Keen interest in bioinformatics analysis

• Solid understanding of genomics

• Experience with genome annotation tools (BLAST, Prokka, MAKER)

• Familiarity with gene prediction software (Prodigal, Augustus)

• Ability to integrate functional annotations (UniProt, KEGG, Pfam)

• Proficient in identifying SNPs (GATK, Samtools)

• Competent in comparative genomics analysis

• Basic knowledge of InterProScan or Pfam for protein domains and motifs

• Skill in correlating genomic variations with phenotypic differences

• Detail-oriented, scientifically accurate, and dedicated