Sheep-TreeSeq: Analisi scalabile della diversità genetica ovina usando alberi (grafi) di sequenze genomiche

Sheep-TreeSeq will perform scalable analysis of genomic diversity of sheep global populations using the novel tree sequence data format and methodology.

Technological advances in agritech have increased the availability of genomic data, leading to massive datasets (“big data”) which pose challenges for storage, processing and analysis, e.g. the sheer volume of the data, the rapid generation of new data (updating results, expanding training populations, streaming applications), and the heterogeneity of data sources (integration of data from multiple sequencing and genotyping platforms). The tree sequence algorithm offers an excellent way to address such challenges, by providing lossless compression and novel representation of the data. As an example, using tree sequences on the 1000 Bull Genome Project data a 90% lossless compression was obtained, reducing the data size from ~800 GB to 45 GB. For the Sheep TreeSeq project we will use around 3,500 sheep whole genome sequences and over 50,000 genotypes (~10 TB of data).

Our plan is to apply the tree sequence approach to compress the data and obtain a data representation highly suited for population genetics and demographic analysis: (i) principal component and genealogical nearest neighbour clustering; (ii) fixation index measuring genetic differentiation; (iii) deep neural network based clustering methods; iv) detection of runs of homozygosity (ROH) and heterozygosity-rich regions (HRR).

This is the first time that this approach is applied to sheep genomics.