RT2T: A Global Collaborative Project to Study Chromosomal Evolution in the Suborder Ruminantia

Abstract

The publication of the first complete, haploid telomere-to-telomere (T2T) human genome revealed new insights into the structure and function of the heretofore “invisible” parts of the genome including centromeres, tandem repeat arrays, and segmental duplications. Refinement of T2T processes now enables comparative analyses of complete genomes across entire clades to gain a broader understanding of the evolution of chromosome structure and function. The human T2T project involved a unique ad hoc effort involving many researchers and laboratories, serving as a model for collaborative open science. Subsequent generation and analysis of diploid, near T2T assemblies for multiple species represents a substantial increase in scale and would be daunting for any single laboratory. Efforts focused on the primate lineage continue to employ the successful open collaboration strategy and are revealing details of chromosomal evolution, species-specific gene content, and genomic adaptations, which may be general or lineage-specific features. The suborder Ruminantia has a rich history within the field of chromosome biology and includes a broad range of species at varying evolutionary distances with separation of tens of millions of years to subspecies that are still able to interbreed. We propose an open collaborative effort dubbed the “Ruminant T2T Consortium” (RT2T) to generate complete diploid assemblies for species in the Artiodactyla order, focusing on suborder Ruminantia. Here we present the initial near T2T assemblies of cattle, gaur, domestic goat, bighorn sheep, and domestic sheep, and describe the motivation, goals, and proposed comparative analyses to examine chromosomal evolution in the context of natural selection and domestication of species for use as livestock.

Overcoming Limitations to Deep Learning in Domesticated Animals with TrioTrain

“…Nevertheless, the type and scale of available data continue to change what is possible through genomics-specific, deep-learning (DL) tools. Foundational, large-scale sequencing consortiums for human genomes often initiate similar work in other species (Altshuler et al 2010; Jarvis et al 2022; Liao et al 2023; Kaminow et al 2022; Nurk et al 2022), particularly within the bovine genomics community (Hayes and Daetwyler 2019; Zhou et al 2022a; Smith et al 2023; Kalbeisch et al 2024). However, aspirations of fully understanding genome biology require effectively translating between disciplines.…”