Genomics in animal breeding from the perspectives of matrices and molecules

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Abstract

Background

This paper describes genomics from two perspectives that are in use in animal breeding and genetics: a statistical perspective concentrating on models for estimating breeding values, and a sequence perspective concentrating on the function of DNA molecules.

Main body

This paper reviews the development of genomics in animal breeding and speculates on its future from these two perspectives. From the statistical perspective, genomic data are large sets of markers of ancestry; animal breeding makes use of them while remaining agnostic about their function. From the sequence perspective, genomic data are a source of causative variants; what animal breeding needs is to identify and make use of them.

Conclusion

The statistical perspective, in the form of genomic selection, is the more applicable in contemporary breeding. Animal genomics researchers using from the sequence perspective are still working towards this the isolation of causative variants, equipped with new technologies but continuing a decades-long line of research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-023-00285-w.

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Most cited references 81

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Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps

T Meuwissen, B. Hayes, M. E. Goddard (2001)

Recent advances in molecular genetic techniques will make dense marker maps available and genotyping many individuals for these markers feasible. Here we attempted to estimate the effects of ∼50,000 marker haplotypes simultaneously from a limited number of phenotypic records. A genome of 1000 cM was simulated with a marker spacing of 1 cM. The markers surrounding every 1-cM region were combined into marker haplotypes. Due to finite population size (Ne = 100), the marker haplotypes were in linkage disequilibrium with the QTL located between the markers. Using least squares, all haplotype effects could not be estimated simultaneously. When only the biggest effects were included, they were overestimated and the accuracy of predicting genetic values of the offspring of the recorded animals was only 0.32. Best linear unbiased prediction of haplotype effects assumed equal variances associated to each 1-cM chromosomal segment, which yielded an accuracy of 0.73, although this assumption was far from true. Bayesian methods that assumed a prior distribution of the variance associated with each chromosome segment increased this accuracy to 0.85, even when the prior was not correct. It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.

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An Expanded View of Complex Traits: From Polygenic to Omnigenic

Evan Boyle, Yang I. Li, Jonathan Pritchard (2017)

A central goal of genetics is to understand the links between genetic variation and disease. Intuitively, one might expect disease-causing variants to cluster into key pathways that drive disease etiology. But for complex traits, association signals tend to be spread across most of the genome-including near many genes without an obvious connection to disease. We propose that gene regulatory networks are sufficiently interconnected such that all genes expressed in disease-relevant cells are liable to affect the functions of core disease-related genes and that most heritability can be explained by effects on genes outside core pathways. We refer to this hypothesis as an "omnigenic" model.

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Is Open Access

Ensembl 2018

Daniel Zerbino, Premanand Achuthan, Wasiu Akanni … (2017)

Abstract The Ensembl project has been aggregating, processing, integrating and redistributing genomic datasets since the initial releases of the draft human genome, with the aim of accelerating genomics research through rapid open distribution of public data. Large amounts of raw data are thus transformed into knowledge, which is made available via a multitude of channels, in particular our browser (http://www.ensembl.org). Over time, we have expanded in multiple directions. First, our resources describe multiple fields of genomics, in particular gene annotation, comparative genomics, genetics and epigenomics. Second, we cover a growing number of genome assemblies; Ensembl Release 90 contains exactly 100. Third, our databases feed simultaneously into an array of services designed around different use cases, ranging from quick browsing to genome-wide bioinformatic analysis. We present here the latest developments of the Ensembl project, with a focus on managing an increasing number of assemblies, supporting efforts in genome interpretation and improving our browser.

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Author and article information

Contributors

Martin Johnsson:

ORCID: http://orcid.org/0000-0003-1262-4585

martin.johnsson@slu.se

Journal

Journal ID (nlm-ta): Hereditas

Journal ID (iso-abbrev): Hereditas

Title: Hereditas

Publisher: BioMed Central (London )

ISSN (Print): 0018-0661

ISSN (Electronic): 1601-5223

Publication date (Electronic): 6 May 2023

Publication date PMC-release: 6 May 2023

Publication date Collection: 2023

Volume: 160

Electronic Location Identifier: 20

Affiliations

GRID grid.6341.0, ISNI 0000 0000 8578 2742, Department of Animal Breeding and Genetics, , Swedish University of Agricultural Sciences, ; Box 7023, Uppsala, 75007 Sweden

Author information

Martin Johnsson http://orcid.org/0000-0003-1262-4585

Article

Publisher ID: 285

DOI: 10.1186/s41065-023-00285-w

PMC ID: 10163706

PubMed ID: 37149663

SO-VID: 57de4513-407a-4fc5-8c2f-88f5adc703b5

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 12 January 2023

Date accepted : 3 May 2023

Funding

Funded by: Swedish University of Agricultural Sciences

Open Access :

Open access funding provided by Swedish University of Agricultural Sciences.

Genomics in animal breeding from the perspectives of matrices and molecules

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Abstract

Background

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Supplementary Information

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Arabidopsis genomics

Most cited references 81

Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps

An Expanded View of Complex Traits: From Polygenic to Omnigenic

Ensembl 2018

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