A cattle graph genome incorporating global breed diversity

Abstract

Despite only 8% of cattle being found in Europe, European breeds dominate current genetic resources. This adversely impacts cattle research in other important global cattle breeds, especially those from Africa for which genomic resources are particularly limited, despite their disproportionate importance to the continent’s economies. To mitigate this issue, we have generated assemblies of African breeds, which have been integrated with genomic data for 294 diverse cattle into a graph genome that incorporates global cattle diversity. We illustrate how this more representative reference assembly contains an extra 116.1 Mb (4.2%) of sequence absent from the current Hereford sequence and consequently inaccessible to current studies. We further demonstrate how using this graph genome increases read mapping rates, reduces allelic biases and improves the agreement of structural variant calling with independent optical mapping data. Consequently, we present an improved, more representative, reference assembly that will improve global cattle research.

Optical mapping compendium of structural variants across global cattle breeds

“…No duplications, inverted duplications and translocations passed the quality filtering. Consistent with results from previous studies 28 , most of the post-filtering insertions and deletions identified fell into the smaller classes, though 1,796 SVs (403 deletions, 1,389 insertions and 4 inversions) of over 50kb in length were identified (Figure 1).…”

“…This number is comparable to what has been seen for novel sequences (i.e. insertions) using graph genome approaches, where an extra 70Mb and 116Mb of novel sequence were reported on 5 and 4 cattle reference genomes, respectively 28,29 . After merging the filtered variants from all the samples, most of the SVs were found to be private to an individual (Figure 2), consistent with what has been observed in previous studies 1 .…”

“…This compendium of SVs across global cattle breeds provides a validation set called using an independent technology that can be used to assess the quality of cattle SV calls. In fact, optical mapping data has previously been used to validate sequencing based SV calls 28 , and we believe this dataset provides the largest set of optical maps to date for a livestock species.…”

“…We aligned the Saphyr optical mapping reads to the ARS-UCD1.2 genome 27 , expanded with the BTau5 Y chromosome generated by the 1000 bulls genome project, using Bionano Solve (v3.3 and 3.5) to assemble the genome maps and call SVs. The two NDama samples had previously been used to validate SV using graph genome approaches 28 . The Bionano Solve workflow identified a number of SV in each sample, ranging from 4,944 to 11,184 for a Hereford and Nelore, respectively (Table 2).…”

ODGI: understanding pangenome graphs

“…This progression is already afoot, particularly for targets that involve complex variation, such as cancer (The Computational Pan-Genomics Consortium, 2016), plant pangenomics (Bayer et al, 2020;Liu et al, 2020;Qin et al, 2021;Li et al, 2022;Bayer et al, 2022), and metagenomics (Zhong et al, 2021). Also, when studying animals like bovines (Leonard et al, 2021;Talenti et al, 2022;Bovine Pan-Genome Consortium, 2022).…”