PONE-D-19-15031

Comparison of shape quantification methods for genomic prediction, and genome-wide association study of sorghum seed morphology

PLOS ONE

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This research was supported by grant (JPMJCR12B5) from the JST/CREST. The first author, L.S., was supported by grant (17J05431) from the JSPS.

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Reviewers' comments:

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Reviewer #1: Partly

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: No

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Reviewer #1: No

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: This MS with goal to compare different seed shape quantification methods and identify the genomic loci associated with seed shape. Authors found the scaling and the direction standardization procedures would cause different PC scores, average shape, GWAS and GP results. Before published, there are some points authors need to clarification and correct.

In the abstract, authors highlighted the methods, it would be better to give more background, and while the detailed comparison is important in introduction.

Is the genome sequencing data (RAD-Seq data) generated in the present study? If yes, I think authors need to provide more detailer results. If not, please cite where the data from. Because I did not find any germplasm information in the MS.

In row 158, 168 and 190, for "function ef2cood in shape on R", authors cited two different papers. need to be corrected.

In row 225, authors used rrBLUP to run GWAS, the paper need to be cited. And authors used Q and K in the GWAS, while not mention where the Q and K from.

In the table 1, authors need to show more information, such as P value for the association.

In rpw 375, authors wrote "The best procedure for the genetic analysis of biological shape should be chosen based on the shape features", can authors point out which procedure is the best one based on the results of this MS

Reviewer #2: Title: Comparison of shape quantification methods for genomic prediction, and genome-wide association study of sorghum seed morphology

Sorghum seed shape and size directly impact its grain yield. As seed shape cannot be reliably quantified, previous sorghum research used 100-seed mass from common garden experiments to understand the genetic basis of seed shape/size. In this study, Sakamoto et al., used two shape quantification methods [elliptic Fourier analysis (EF) and semi-landmark analysis (SLA)], previously used in rice and wheat, to quantify sorghum seed shape. This data was used to determine the genetic architecture of sorghum seed shape. The authors quantified seed shape of 329 diverse sorghum accessions using EF and SLA methods and genotyped these accessions by sequencing (GBS). Principal component analysis of EF and SLA analysis revealed both methods produced similar results. GWAS with seed shape data identified a significant peak on chromosome 4, validating this QTL was a seed weight QTL mapped recently by Wang et al., (2019, https://www.nature.com/articles/s41437-019-0249-4).

These results are interesting and potentially important for crop improvement. However, there are some minor concerns.

1. The authors used ~329 sorghum diverse accessions in this study. However, geo-reference and their race information are not provided in the manuscript. Including this information as a supplemental file will be helpful for future studies with different traits from this population. Also, include a PCA plot of these accessions plotted with the sorghum association panel (Morris et al. 2013. PNAS), and NJ tree depicting their origin and race. These figures will be helpful for sorghum genetics and genomics audience to understand the genetic diversity present in the sorghum germplasm used for this research.

2. Recently, sorghum seed mass (with ~1900 geo-referenced accessions) mapped a QTL on chromosome 4 at ~58 Mb (Wang et al., 2019). As findings from Wang et al. (2019) validate the seed shape QTL mapped in this study, cite Wang et al. in the discussion section.

Minor points:

Line 87: change Sorghum × almum to Sorghum x almum

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Reviewer #1: No

Reviewer #2: No

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Comparison of shape quantification methods for genomic prediction, and genome-wide association study of sorghum seed morphology

PONE-D-19-15031R1

Dear Dr. Iwata,

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Sujan Mamidi, Ph.D.

Academic Editor

PLOS ONE

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