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      Genomic prediction using low-coverage portable Nanopore sequencing

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          Abstract

          Most traits in livestock, crops and humans are polygenic, that is, a large number of loci contribute to genetic variation. Effects at these loci lie along a continuum ranging from common low-effect to rare high-effect variants that cumulatively contribute to the overall phenotype. Statistical methods to calculate the effect of these loci have been developed and can be used to predict phenotypes in new individuals. In agriculture, these methods are used to select superior individuals using genomic breeding values; in humans these methods are used to quantitatively measure an individual’s disease risk, termed polygenic risk scores. Both fields typically use SNP array genotypes for the analysis. Recently, genotyping-by-sequencing has become popular, due to lower cost and greater genome coverage (including structural variants). Oxford Nanopore Technologies’ (ONT) portable sequencers have the potential to combine the benefits genotyping-by-sequencing with portability and decreased turn-around time. This introduces the potential for in-house clinical genetic disease risk screening in humans or calculating genomic breeding values on-farm in agriculture. Here we demonstrate the potential of the later by calculating genomic breeding values for four traits in cattle using low-coverage ONT sequence data and comparing these breeding values to breeding values calculated from SNP arrays. At sequencing coverages between 2X and 4X the correlation between ONT breeding values and SNP array-based breeding values was > 0.92 when imputation was used and > 0.88 when no imputation was used. With an average sequencing coverage of 0.5x the correlation between the two methods was between 0.85 and 0.92 using imputation, depending on the trait. This suggests that ONT sequencing has potential for in clinic or on-farm genomic prediction, however, further work to validate these findings in a larger population still remains.

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          Most cited references56

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Minimap2: pairwise alignment for nucleotide sequences

            Heng Li (2018)
            Recent advances in sequencing technologies promise ultra-long reads of ∼100 kb in average, full-length mRNA or cDNA reads in high throughput and genomic contigs over 100 Mb in length. Existing alignment programs are unable or inefficient to process such data at scale, which presses for the development of new alignment algorithms.
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              A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species

              Advances in next generation technologies have driven the costs of DNA sequencing down to the point that genotyping-by-sequencing (GBS) is now feasible for high diversity, large genome species. Here, we report a procedure for constructing GBS libraries based on reducing genome complexity with restriction enzymes (REs). This approach is simple, quick, extremely specific, highly reproducible, and may reach important regions of the genome that are inaccessible to sequence capture approaches. By using methylation-sensitive REs, repetitive regions of genomes can be avoided and lower copy regions targeted with two to three fold higher efficiency. This tremendously simplifies computationally challenging alignment problems in species with high levels of genetic diversity. The GBS procedure is demonstrated with maize (IBM) and barley (Oregon Wolfe Barley) recombinant inbred populations where roughly 200,000 and 25,000 sequence tags were mapped, respectively. An advantage in species like barley that lack a complete genome sequence is that a reference map need only be developed around the restriction sites, and this can be done in the process of sample genotyping. In such cases, the consensus of the read clusters across the sequence tagged sites becomes the reference. Alternatively, for kinship analyses in the absence of a reference genome, the sequence tags can simply be treated as dominant markers. Future application of GBS to breeding, conservation, and global species and population surveys may allow plant breeders to conduct genomic selection on a novel germplasm or species without first having to develop any prior molecular tools, or conservation biologists to determine population structure without prior knowledge of the genome or diversity in the species.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: Data curationRole: Funding acquisition
                Role: Data curationRole: InvestigationRole: Methodology
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                15 December 2021
                2021
                : 16
                : 12
                : e0261274
                Affiliations
                [1 ] Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD, Australia
                [2 ] School of Veterinary Science, The University of Queensland, Brisbane, QLD, Australia
                Clemson University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-2864-7685
                https://orcid.org/0000-0002-5606-3970
                https://orcid.org/0000-0001-7224-191X
                https://orcid.org/0000-0002-7783-5466
                https://orcid.org/0000-0002-7521-3671
                Article
                PONE-D-21-25145
                10.1371/journal.pone.0261274
                8673642
                34910782
                d14f8784-dece-41a7-acad-98aba06a14a5
                © 2021 Lamb et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 August 2021
                : 26 November 2021
                Page count
                Figures: 5, Tables: 2, Pages: 18
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001054, meat and livestock australia;
                Award ID: B.STU.2001
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001054, meat and livestock australia;
                Award ID: P.PSH.P0833
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001054, meat and livestock australia;
                Award ID: L.GEN.1713
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001054, meat and livestock australia;
                Award ID: L.GEN.1808
                Award Recipient :
                HJL was supported by an MLA Donor Company post graduate top-up scholarship (B.STU.2001). MLA Donor Company also supported this work with grants to BJH (P.PSH.P0833 and L.GEN.1808) and grant L.GEN. 1713 to IASR. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Genetics
                Genomics
                Biology and Life Sciences
                Genetics
                Single Nucleotide Polymorphisms
                Biology and Life Sciences
                Genetics
                Heredity
                Genetic Mapping
                Variant Genotypes
                Biology and Life Sciences
                Molecular Biology
                Molecular Biology Techniques
                Sequencing Techniques
                Genome Sequencing
                Research and Analysis Methods
                Molecular Biology Techniques
                Sequencing Techniques
                Genome Sequencing
                Biology and Life Sciences
                Genetics
                Genomics
                Human Genomics
                Biology and Life Sciences
                Molecular Biology
                Molecular Biology Techniques
                Genotyping
                Research and Analysis Methods
                Molecular Biology Techniques
                Genotyping
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Skeleton
                Pelvis
                Hip
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Skeleton
                Pelvis
                Hip
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Type 2 Diabetes
                Type 2 Diabetes Risk
                Medicine and Health Sciences
                Medical Conditions
                Metabolic Disorders
                Diabetes Mellitus
                Type 2 Diabetes
                Type 2 Diabetes Risk
                Custom metadata
                The sequence data used in this paper can be found in NCBI’s Sequence Read Archive, Bioproject accession number PRJNA770750.

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