Combined Linkage Mapping and Genome-Wide Association Study Identified QTLs Associated with Grain Shape and Weight in Rice (Oryza sativa L.)

Reviewer 1

Line 73 etc. should be deleted because the clause starts with such as

Page 2, line 69: we replaced such as with molecular markers “that include…”. Therefore, the rest of the clause remain the same, but the punctuation is changed to a “period” not “etc.”

Line 82 replace Permanent with Fixed homozygous

Page 2, line 80: “Permanent” populations has been replaced with “Fixed homozygous” populations as per reviewer’s suggestion.

Line 101 state the country of origin for both parents and brief detail about their contrasting grain length or weight

We appreciate the concern raised by the reviewer. We have included the following statement on page 3, lines 101-103: “The japonica cv. Milyang352 (P2 in our study) was developed from a cross between C18/Ungwang. C18 is a cultivar originated from China, which is also the same origin of the cv. 93-11 used as P1.”

To the second part of the reviewer’s concern, we would like to indicate the differential phenotypes of parental lines in presented and described on (Page 5, lines 227-234; page 8, lines 253-259: Figure 3).

Line 112 add details of the experimental design/layout for both planting dates (including number of reps if any)

Page 3, lines 112-116: we have inserted the following text: “A total of 100 seedlings per  rice line were transplanted in four rows with 25 plants per row and the spacing between and within the lines of , respectively. Parental lines were planted after every 20 DH lines, starting from the first row. The weather parameters and conditions during the early– (first season) and late–transplanting periods (second season) can be found in the Figure S1.”

Line 122 This needs much more detailed clarification to explain sampling strategy: did you evaluate 10 replications of individual grains for one plant or from 10 different panicles from different individual plants or individual plots?

Authors appreciate the concern raised by worthy reviewer. We would like to specify that sampling for phenotypic observations was done as follows, and included on page 3, lines 125-127: “The samples for the phenotypic observations were randomly pooled from the inside rows, excluding the border rows to avoid the border effects on the traits studied and competition between lines. Ten individual panicles from different plants were used to evaluated the grain phenotype.”

In addition, we would like to indicate that sampling was done randomly. Moreover, the method for evaluation grain length, width, grain length-width is different from the one used for estimating the thousand grain weight. For the latter, it is known that 100 seeds are weighed in eight replications, the means values are used to calculate the coefficient of variance and then the thousand weight is calculated. For the grain shape, only measuring at least 10 individual seeds randomly picked would give an indication of the observed trait in each line. Therefore, we considered that too much details in this section would inflate the manuscript.

Line 131 How/where were the KASP assays run? Was genotyping outsourced or done in house?

Also I checked to see whether the markers listed in table 1 (line 289) are all given in the information in the reference cited [94, line 131], but there are some that cannot be found there. Please indicate where the all KASP reported in this paper can be found.

Authors appreciate the concern by worthy reviewer. We included new section describing the genotyping essays on page 3, lines 135-159 as follows: “2.3. Genomic DNA Extraction and Molecular Markers Analysis

The genomic DNA was extracted from rice leaves samples following the previously reported CTAB method [1] with slight modifications. Briefly, the frozen leaves samples were crushed in liquid nitrogen in 1.5 mL Eppendorf tubes (e-tubes), and 600 μL of 2X CTAB buffer (D2026, Lot D2618U12K, Biosesang, Seongnam-si, Korea) was added and the mixture was vortexed, and incubated at 65 °C for 30 min in a dry oven. Then 500 μL PCI (Phenol:Chloroform:Isoamylalcohol, 25:24:1, Batch No. 0888k0774; Sigma-Aldrich, St. Louis, MO, USA) solution was added, followed by gentle mixing by inversion. The tubes were centrifuged at 13,000 rpm for 15 min, and the supernatant was transferred to fresh e-tubes, and 500 μL of isopropanol (CAS: 67-63-0, Lot No. SHBC3600V; Sigma-Aldrich, St. Louis, USA) was added, followed by mixing by inversion and incubation for 1 h at −20 °C. Then centrifugation was done at 13,000 rpm for 7 min. The supernatant was removed and the pellet were washed with 70% ethanol (1 mL). Samples were centrifuged at 13,000 rpm for 5 min and ethanol was discarded, followed by drying at room temperature, and re-suspended in 100 mL 1X TE buffer (Lot No. 0000278325; Promega, Madison, WI, USA).

For the molecular markers analysis, Kompetitive Allele-Specific PCR (KASP) markers were amplified and allelic discrimination was performed using the Nexar system (LGC Doublas Scientific, Alexandria, VA, USA) at the Seed Industry Promotion Center (Gimje, Korea) of the Foundation of Agri. Tech. Commercialization & Transfer in Korea. An aliquot (0.8 μL) of 2X master mix (LGC Genomics, London, UK), 0.02 μL of KASP assay mix (LGC Genomics), and 5 ng DNA template were mixed in 1.6 μL KASP reaction mixture in a 386-well array plate. KASP amplification was performed as described earlier

Fluidigm markers for SNP genotypes were determined using the BioMark^TM HD system (Fluidign San Fancisco, Cam USA) and 96.96 Dynamic Array IFC (96.96 IFC) chip following the manufacturer’s instructions, at the National Instrumentation Center for Environmental Management, Seoul National University (Pyeongchang, South Korea).

”

We would like to apologize for the inconvenience. We, therefore, provided the reference for other markers, and have included the following text in lines 161-163: “The genotype and the phenotype data consisting of 240 markers, that included KASP markers previously reported [2] specific for detecting polymorphism between japonica ssp. and Fluidigm markers [3] specific for detecting polymorphism between indica and japonica subspecies”

Line 147 Must indicate how the significance threshold for GWAS analyses was selected (most people use the Bonferroni correction for multiple testing)

Authors appreciate the concern raised by the reviewer. The following GAPIT function was applied to the genotype and phenotype formatted data to generate the Genome-Wise Manhattan plots and the kinship matrix, and scree plot for the PCA.

my_GAPIT <- GAPIT(Y=myY, G=myG, Model.selection=TRUE, PCA.total=3, SNP.MAF = 0.05) in RStudio (lines 171-173).

During the GWAS/GAPIT processing, MAF are adjusted and, the FRD, the Bonferroni-correction for significant threshold is applied. Then the significant markers linked specific QTLs are plotted above the suggestive genome line of a particular chromosome.

Line 293 Does the absolute position (d) relate to the centre of the confidence interval or the location with peak LOD score?

We would like to specify that the absolute position of the QTLs (Table 1, line 328) is related to the center of the confidence interval (data not shown in Table 1) also showing the closest marker to the detected QTL.

Line 300 onwards: legend can be shortened, it needs to explain QTL names but does not need to list every QTL or repeat the information such as LOD values and cM that are also given in Table 1.

Also note that only chromosomes with QTLs are shown in the figure (don’t need to call them A-J because they are all labelled in the figure, but could make the chromosome labels bold instead of A-J)

Authors appreciate the suggestion made by the reviewer, and we have modified the caption of Figure 5 accordingly (Lines 337-356)

Authors appreciate the suggestion made by the reviewer. We labelled each mapping figure represented by chromosomes for easy referencing in the description of the results in the main text. We found it useful and convenient. 

Line 339 onwards: legend can be shortened to remove repetition and details that are already clearly indicated in the figure such as trait names. Can refer to Table 1 in the legend for cross-referencing QTLs.

We are thankful to the reviewer for the suggestion. We have modified the caption of Figure 6 accordingly (page 14, lines 372-381).

Lines 353-354 need to be with previous main text. Are any of the KASP listed in Table 2 known to be sited within these genes or are the candidate genes linked to them?

There are no details of the bioinformatics sequence analysis (including reference genome used) used to identify candidate genes in the Methods, so this should be added in order to fully understand how the candidates in Table 2 were identified.

Page 15, lines 383-385: we specified that the candidate genes were pooled form the major QTLs on chromosome 5 only.

“Candidate genes (Table 2) were pooled from the genetic regions covered by the QTLs co-detected by both linkage mapping and Genome-Wide Association Studies (GWAS) on chromosome 5 flanked by KJ05_17 (4,783,888bp) and KJ05_13 (5,984,919)  markers.”

We have included the following statement on page 4, lines 182-184 : “The publicly available rice genome annotation database (http://rice.plantbiology.msu.edu/) browser was used to identify candidate genes within the genetic region flanked by KASP marker KJ05_17 (4,783,888bp) and KJ05_13 (5,984,919bp) on chromosome 5 (major QTL).”

We also indicated in line 465 that the QTL on chromosome 5 flanked by KJ05_17 and KJ05_13 covers about 1.201Mb.

Line 363 add ratio after length-width

Page 16, line 414, we have added “ratio” after grain length-width as recommended.

Line 477 The conclusion section could be more succinctly written.

Page 18, lines 528-541: we have edited the conclusion, and have kept a minimum text to maintain the flow and key message as suggested.

Reviewer 2

The manuscript presented for review has several advantages and disadvantages. As more important I draw attention to the disadvantages, because they are so crucial that they may eventually prevent publication of this manuscript.

The manuscript is an interesting study, especially the idea of planting plants at different dates and comparing QTL obtained for the same characteristics growing at different times. The attempt to link QTL with candidate genes also seems to be interesting, but not very precise. The work requires significant changes.

Methodology:

1.       It is widely accepted that research on genetic control of quantitative traits should be carried out in different environments. The research described in the manuscript has only been carried out in one year (this is shown in the text). If it is not, please correct me.

Authors appreciate the pertinence of the concern raised by worthy reviewer. We would like to specify that generally, rice cultivation in Korea covers only one cropping season due to the local environmental and weather conditions. Although the experiments were conducted during the year 2018, under two environments (early- and late-cultivation) periods, which is not common in the Korean conditions for rice cultivation. This can be observed in the Figure S1 presenting the changes in the weather parameters and conditions. The first period coincides with the formal season and the second coincides with the mid-season. During the mid-season, most of farmers do horticulture. Also, we intended to investigate and explore the season commonly used for other crops to cultivar rice and eventually have more cultivation periods.

Besides, ripening of the early rice cultivation coincides with high temperatures period; the grain weight is usually affected, and during late cultivation, ripening is slow but grain weight is increased.

2.       The number of objects tested in one replication should be enough to make the mean value is representative for the tested genotypes. By the way, the authors did not specify the number of plants in the replication, I assume that it was only one plant. The article specifies that the experiment was assumed in 10 replications. This is good, but the next question is: does it mean that 10 blocks were created and each one consisted of a set of DH + parents? Or was it one block and 10 plants of each DH were planted in one row and each plant was treated as a replication? Unfortunately, the last case disqualifies the study.

Authors appreciate the interest showed by the reviewer to clarify and improve the manuscript.

On page 3, lines 112-116, we have inserted the following text: “A total of 100 seedlings per rice line were transplanted in four rows with 25 plants per row and the spacing between and within the lines of 30 cm × 15 cm, respectively. Parental lines were planted after every 20 DH lines, starting from the first row. The weather parameters and conditions during the early– (first season) and late–transplanting periods (second season) can be found in the Figure S1.”

We also included the follows text in lines 125-127: “The samples for the phenotypic observations were randomly pooled from the inside rows, excluding the border rows to avoid the border effects on the traits studied and competition between lines. Ten individual panicles from different plants were used to evaluated the grain phenotype.”

In addition, as we replied to another anonymous reviewer, we would like to indicate that sampling was done randomly. Moreover, the method for evaluating the grain length, width, grain length-width ratio is different from the one used for estimating the thousand grain weight. For the latter, it is known that 100 seeds are weighed in eight replications, the means values are used to calculate the coefficient of variance and then the thousand weight is calculated. For the grain shape, only measuring at least 10 individual seeds randomly picked would give an indication of the observed trait in each line. Therefore, we considered that too much details in this section would inflate the manuscript.

3.       I understand that the method of DNA isolation, genotyping, selection of KASP markers was described in an earlier article [94]. However, it is necessary to make the precision so that it does not raise any doubts.

By the way, why, in fact, only 240 KASP markers were used in the study? This also needs to explain.

Authors appreciate the concern by worthy reviewer. We included new section describing the genotyping essays on page 3, lines 135-159 as follows: “2.3. Genomic DNA Extraction and Molecular Markers Analysis

The genomic DNA was extracted from rice leaves samples following the previously reported CTAB method [1] with slight modifications. Briefly, the frozen leaves samples were crushed in liquid nitrogen in 1.5 mL Eppendorf tubes (e-tubes), and 600 μL of 2X CTAB buffer (D2026, Lot D2618U12K, Biosesang, Seongnam-si, Korea) was added and the mixture was vortexed, and incubated at 65 °C for 30 min in a dry oven. Then 500 μL PCI (Phenol:Chloroform:Isoamylalcohol, 25:24:1, Batch No. 0888k0774; Sigma-Aldrich, St. Louis, MO, USA) solution was added, followed by gentle mixing by inversion. The tubes were centrifuged at 13,000 rpm for 15 min, and the supernatant was transferred to fresh e-tubes, and 500 μL of isopropanol (CAS: 67-63-0, Lot No. SHBC3600V; Sigma-Aldrich, St. Louis, USA) was added, followed by mixing by inversion and incubation for 1 h at −20 °C. Then centrifugation was done at 13,000 rpm for 7 min. The supernatant was removed and the pellet were washed with 70% ethanol (1 mL). Samples were centrifuged at 13,000 rpm for 5 min and ethanol was discarded, followed by drying at room temperature, and re-suspended in 100 mL 1X TE buffer (Lot No. 0000278325; Promega, Madison, WI, USA).

For the molecular markers analysis, Kompetitive Allele-Specific PCR (KASP) markers were amplified and allelic discrimination was performed using the Nexar system (LGC Doublas Scientific, Alexandria, VA, USA) at the Seed Industry Promotion Center (Gimje, Korea) of the Foundation of Agri. Tech. Commercialization & Transfer in Korea. An aliquot (0.8 μL) of 2X master mix (LGC Genomics, London, UK), 0.02 μL of KASP assay mix (LGC Genomics), and 5 ng DNA template were mixed in 1.6 μL KASP reaction mixture in a 386-well array plate. KASP amplification was performed as described earlier

Fluidigm markers for SNP genotypes were determined using the BioMark^TM HD system (Fluidign San Fancisco, Cam USA) and 96.96 Dynamic Array IFC (96.96 IFC) chip following the manufacturer’s instructions, at the National Instrumentation Center for Environmental Management, Seoul National University (Pyeongchang, South Korea).

”

Initially, 568 markers, including 372 KAPS markers and 192 Fluidigm SNP markers were used, but only polymorphic markers were finally included in the study for QTL analysis and GWAS experiments.

We have included on page 4, lines the following: “The genotype and the phenotype data consisting of 240 markers, that included KASP markers previously reported [2] specific for detecting polymorphism between japonica ssp. and Fluidigm markers [3] specific for detecting polymorphism between indica and japonica subspecies”

4.       In the results chapter, the authors give (Table 2) a list of candidate genes. Unfortunately, in the chapter the methods do not mention it. It would be good to write a few sentences that such analysis will be performed and how the candidate genes will be selected, the source of the reference sequence, etc.

We are thankful to the reviewer for the suggestion. We have included the following on page 4, lines 182-184:” The publicly available rice genome annotation database (http://rice.plantbiology.msu.edu/) browser was used to identify candidate genes within the genetic region flanked by KASP marker KJ05_17 and KJ05_13 on chromosome 5. ”

We also indicated in line 465 that the QTL on chromosome 5 flanked by KJ05_17 (4,783,888bp) and KJ05_13 (5,984,919) covers about 1.201Mb.

Results:

1.       I have serious objections to interpret of the distributions of the examined traits and their compatibility with the normal distribution. This is especially true for B, C, L, M (fig. 1). Of course, Q-Q plots can be used, but the authors did not give the measure they followed claiming that the distributions of traits are consistent with normal distribution

Authors agree with the concern raise by the reviewer. We have therefore, improved the description of the Figure 1 by adding the following text in lines 191-194: ” therefore, suggesting a normal distribution for grain length (Figure 1A, K), grain length–width ratio (Figure 1D, N), thousand grain weight (Figure 1E, O) but grain width (Figure 1B, L), and grain thickness (Figure 1C, M) exhibited a positive skewness and negative skewness, respectively.”

2.       In rice, a number of genetic maps were published, consisting of thousands of markers. In this work only 240 markers were used, which resulted in large gaps. This interferes with the possibility of precise marker coverage of the genome and obtaining precise QTL locations. So, is it reasonable to deduce on the basis of an incomplete genetic map?

Next question: is the order of markers on the genetic map compatible with their physical location on rice chromosomes?

We appreciate the interest of the reviewer to improve the quality of the manuscript. Therefore, we would like to specify that we in part replied to a similar concern raised above concerning the number of markers used in the study as follows:” Initially, 568 markers, including 372 KAPS markers and 192 Fluidigm SNP markers were used for polymorphism analysis, but only polymorphic markers were finally included in the study for QTL analysis and GWAS experiments.

In addition, although 240 polymorphic markers were used. It could be true that compared to other studies, there could be some gaps, which may not be considered as incomplete genetic maps, considering that an increasing number of makers may result in the detection of same QTLs.

An illustration, in our previous study, we investigated the response of the same mapping population towards potassium chlorate (KClO₃) in order to study the nitrogen metabolism in plants [4]. A similar number of KASP markers were used and allowed the detection of novel QTL for chlorate resistance in rice.

Besides, these gaps could be seen as the regions with similar genotypes of the parental counterpart. In particular, 93-11 is an indica variety and Milyang352 is a japonica variety, but infertility was observed to be low during the development of the DH lines. In general, infertility occurs in the posterior generation of indica/japonica cultivars. The possible reason for the low fertility in these combinations implies that there is an existing similar genetic region. This could be also observed in the kinship matrix in Figure 4A (page 10, line 318).

The major QTL on chromosome 5 is flanked by

KJ05_17 (4,783,888bp) and KJ05_13 (5,984,919bp). The same order could be seen on the genetic map.

3.       If the authors intended to search for candidate genes in QTL-GWAS areas, they should show in detail (e.g. in the additional Suppl. File) which of the candidate genes is assigned to which QTL. There is no such description after present Table 2. Such a description is only found in the discussion chapter, which is not understandable.

Authors appreciate the interest of the reviewer to improve the manuscript. We would like to specify that candidate genes listed in Table 2 were pooled from the region covered by the  flanking markers KJ05_17 and KJ05_13 on chromosome 5 only. As explained early, we specified that Candidate genes (Table 2) were pooled from the genetic regions covered by the QTLs co-detected by both linkage mapping and Genome-Wide Association Studies (GWAS) on chromosome 5 flanked KJ05_17 (4,783,888bp) and KJ05_13 (5,984,919) KASP markers (Lines 383-385). A short description of the method is indicated on page 4, lines 192-184.

Discussion:

1.       Some elements of the discussion (especially the one about selecting candidate genes for chosen and confirmed loci in QTL-GWAS) I propose move it to the chapter results.

We appreciate the suggestion made by the reviewer. We have moved to the result section, page 15, lines 386-404 the discussion related to some of the candidate genes. However, we have kept a minimum discussion regarding the candidates genes to main a flow in the discussion (lines 505-521).