SUPR
5x trios Bos taurus cattle Graph Genome Assembly, PacBio & Nanopore
Dnr:

NAISS 2025/5-57

Type:

NAISS Medium Compute

Principal Investigator:

Tomas Klingström

Affiliation:

Sveriges lantbruksuniversitet

Start Date:

2025-02-25

End Date:

2025-09-01

Primary Classification:

40402: Genetics and Breeding in Agricultural Sciences

Secondary Classification:

10610: Bioinformatics and Computational Biology (Methods development to be 10203)

Tertiary Classification:

10203: Bioinformatics (Computational Biology) (Applications at 10610)

Allocation

Abstract

The genetic diversity and structure of the Bos taurus cattle populations are of significant interest for both agricultural productivity and evolutionary studies. The aim of this study is to identify structural variants and to track their patterns of inheritance in three Swedish cattle breeds: Swedish Red and White, Holstein, and Jersey; as well as two South African breeds: Bonsmara and Afrikaner. Trios of dam, sire, and offspring are to be sequenced with both PacBio and Nanopore long-read sequencing, facilitating haplotype-resolved de novo graph assemblies of all chromosomes from telomere-to-telomere. This study consists of several key components: evaluation and selection of appropriate de novo graph aligner programs compatible with both PacBio and Nanopore data, a high-performance computing implementation on the National Academic Infrastructure for Super­computing in Sweden Dardel cluster. The assembled high-quality graph genomes will be used together with the extensive phenotypic data available through the Swedish University of Agricultural Sciences Gigacow database, which monitors and collects quantitative data points on thousands of Swedish cattle living on farms. Structural variant-based association studies of the Swedish breeds will be performed to find novel associations to both monogenic and polygenic traits that are of interest going forward. This study will make significant contributions to the understanding of the genetic landscape of Swedish and African cattle breeds while establishing valuable computational infrastructure for future livestock genomics research.