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Regional genomic heritability mapping for agronomic traits in sugarcane

View ORCID ProfilePedro Marcus Pereira Vidigal, View ORCID ProfileMehdi Momen, View ORCID ProfilePaulo Mafra de Almeida Costa, View ORCID ProfileMárcio Henrique Pereira Barbosa, View ORCID ProfileGota Morota, View ORCID ProfileLuiz Alexandre Peternelli
doi: https://doi.org/10.1101/2020.04.16.045310
Pedro Marcus Pereira Vidigal
1Universidade Federal de Viçosa (UFV), Núcleo de Análise de Biomoléculas (NuBioMol), Viçosa, Minas Gerais, Brazil
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Mehdi Momen
2Virginia Polytechnic Institute and State University (Virginia Tech), Department of Animal and Poultry Sciences, Blacksburg, Virginia, USA
3University of Wisconsin–Madison (UW-Madison), Department of Surgical Sciences, School of Veterinary Medicine, Madison, Wisconsin, USA
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Paulo Mafra de Almeida Costa
4Instituto Federal de Educação, Ciência e Tecnologia Catarinense, Concórdia, Santa Catarina, Brazil
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Márcio Henrique Pereira Barbosa
5Universidade Federal de Viçosa (UFV), Department of Agronomy, Viçosa, Minas Gerais, Brazil
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Gota Morota
2Virginia Polytechnic Institute and State University (Virginia Tech), Department of Animal and Poultry Sciences, Blacksburg, Virginia, USA
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Luiz Alexandre Peternelli
6Universidade Federal de Viçosa (UFV), Department of Statistics, Viçosa, Minas Gerais, Brazil
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  • For correspondence: peternelli@ufv.br
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Abstract

Background The identification of genomic regions involved in agronomic traits is the primary concern for sugarcane breeders. Genome-wide association studies (GWAS) leverage the sequence variations to bridge phenotypes and genotypes. However, their effectiveness is limited in species with high ploidy and large genomes, such as sugarcane. As an alternative, a regional heritability mapping (RHM) method can be used to capture genetic signals that may be missed by GWAS by combining genetic variance from neighboring regions. We used RHM to screen the sugarcane genome aiming to identify regions with higher heritability associated with agronomic traits. We considered percentage of fiber in sugarcane bagasse (FB), apparent percentage of sugarcane sucrose (PC), tonnes of pol per hectare (TPH), and tonnes of stalks per hectare (TSH).

Methods Sequence-capture data of 508 sugarcane (Saccharum spp.) clones from a breeding population under selection were processed for variant calling analysis using the sugarcane genome cultivar R570 as a reference. A set of 375,195 single nucleotide polymorphisms were selected after quality control. RHM was conducted by splitting the sugarcane genome into windows of 2 Mb length.

Results We selected the windows explaining > 20% of the total genomic heritability for TPH (64 windows - 5,654 genes) and TSH (72 windows - 6,050 genes), and > 15% for PC (16 windows - 1,517 genes) and FB (17 windows - 1,615 genes). The top five windows that explained the highest genomic heritability ranged from 20.8 to 24.6% for FB (629 genes), 18.0 to 22.0% for PC (452 genes), 53.8 to 66.0% for TPH (705 genes), and 59.5 to 67.4% for TSH (413 genes). The functional annotation of genes included in those top five windows revealed a set of genes that encode enzymes that integrate carbon metabolism, starch and sucrose metabolism, and phenylpropanoid biosynthesis pathways.

Conclusions The selection of windows that explained the large proportions of genomic heritability allowed us to identify genomic regions containing a set of genes that are related to the agronomic traits in sugarcane. These windows spanned a region of 58.38Mb, which corresponds to 14.28% of the reference assembly in the sugarcane genome. We contend that RHM can be used as an alternative method for sugarcane breeders to reduce the complexity of the sugarcane genome.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted April 18, 2020.
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Regional genomic heritability mapping for agronomic traits in sugarcane
Pedro Marcus Pereira Vidigal, Mehdi Momen, Paulo Mafra de Almeida Costa, Márcio Henrique Pereira Barbosa, Gota Morota, Luiz Alexandre Peternelli
bioRxiv 2020.04.16.045310; doi: https://doi.org/10.1101/2020.04.16.045310
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Regional genomic heritability mapping for agronomic traits in sugarcane
Pedro Marcus Pereira Vidigal, Mehdi Momen, Paulo Mafra de Almeida Costa, Márcio Henrique Pereira Barbosa, Gota Morota, Luiz Alexandre Peternelli
bioRxiv 2020.04.16.045310; doi: https://doi.org/10.1101/2020.04.16.045310

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