Original article Keywords: Rice (Oryza sativa L.), harvest index, source ability, yield potential, QTL
Posted Date: January 22nd, 2021
DOI: https://doi.org/10.21203/rs.3.rs-56282/v3
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License. Read Full License Version of Record: A version of this preprint was published on February 10th, 2021. See the published
version at https://doi.org/10.1186/s12284-021-00456-1. Page 1/19 Page 1/19 Abstract Background The harvest index (HI) is a measure of the biological success of forming harvestable
products. However, our understanding of the genetic basis of HI in rice (Oryza sativa L.) is limited,
because it is a complex trait consisting of various yield-related traits and physiological attributes. YTH183 is a high-yielding line with large panicles and high HI derived from a cross between the Indica
Group variety IR 64 and the NPT line IR 69093-41-2-3-2 (YP5). Results Here, we detected two novel QTLs for HI, designated qHI5.1 on chromosome 5 and qHI8.1 on
chromosome 8, by using 155 recombinant inbred lines (RILs) derived from the cross between IR 64 and
YTH183. The YTH183 allele at qHI5.1 contributed to a wide grain, resulting in heavy grain weight and
panicle weight, and was consistently effective under the different environmental conditions of subtropica
(Ishigaki) and temperate (Tsukuba) regions. Genetic polymorphism revealed that qHI5.1 was identical to
GSE5/GW5, which is known to control the grain weight. On the other hand, although qHI8.1 functioned
additively with qHI5.1 for higher HI, it did not show any significant effect on grain or panicle weight. In
addition, its effects on HI were shown only in the first seasons at Ishigaki but not at Tsukuba or in the
second season at Ishigaki. Conclusion Our results indicate that qHI5.1 controls the grain size, regardless of whether environmental
conditions are of subtropical or temperate regions, while qHI8.1 might be involved in controlling the
physiological processes of source ability or the translocation of photosynthesis products from vegetative
organs to grains depending on environmental conditions during the maturing stage. These QTLs will be
useful genetic resources for future breeding programs to break through the ceiling of maximum yield in
Indica Group varieties. Background Rice (Oryza sativa L.) is one of the most important cereal crops in the world. More than half of the world’s
population depends on rice as their staple food, and, in Africa, the overall demand for rice has outstripped
local production (Zenna et al. 2017). Moreover, ongoing global warming exposes rice production to
serious risks, such as extreme heavy rain, flooding, and disastrous droughts. To address the demand for
food for over nine billion people by 2050, and, further, to respond to the challenges posed by global
warming, the genetic improvement of yield potential in rice-breeding programs is one of the most
important strategies. Since the release in 1966 of IR 8, the first semi-dwarf variety with high yield potential, the International
Rice Research Institute (IRRI) has aimed to further improve the yield potential of IR-series varieties and
has proposed new-plant-type varieties (NPTs) based on the “plant type (ideotype) concept” (Donald 1968;
Yoshida 1972; Peng et al. 1994, 2008; Khush 1995). NPTs are varieties harboring low tiller number, few
unproductive tillers, and a large number of grains per panicle, and a phenotype expected to result in high
yield potential (Peng et al. 1994). NPTs developed from the crosses between the tropical Japonica Group Page 2/19 Page 2/19 varieties and the improved Indica Group varieties have been released since 1993; however, grain yields
have been disappointing because of low biomass production and poor grain filling (Peng et al. 2008). To
achieve high grain filling and increase yield potential, particularly in terms of improvement of the sink-
source balance, it is necessary to simultaneously improve both sink capacity (a large number of spikelets
per panicle, heavy grains, and stable grain filling) and source ability (carbohydrate supply) to
accommodate the large sink size under high temperatures. An informative indicator of the sink-source balance is the harvest index (HI). HI is defined as the ratio of
harvestable parts to biomass and is taken as a measure of biological success in partitioning
photosynthates to the harvestable product (Donald and Hamblin 1976; Sinclair 1998). Recent breeding
programs have achieved great increases in yield by improving HI. Hay (1995) concluded that yield
increase in rice was a consequence of the incorporation of dwarfing genes that increased the harvest
index by around 0.3 to 0.5. Therefore, HI is a useful indicator to consider in the breeding of new high-
yielding varieties. Background Molecular genetic research has detected several QTLs for HI in rice (Hittalmani et al. 2003; Zhang et al. 2004, 2017; Marri et al. 2005; Sabouri et al. 2009; Li et al. 2012). HI is a quantitative trait controlled by
multiple genes (QTLs) for numbers of panicles, grain weight, grain numbers, plant biomass, and
photosynthetic carbohydrate accumulation and translocation, and the expressions of these QTLs for HI
are affected by the environment (Hittalmani et al. 2003; Li et al. 2012; Zhang et al. 2017). However, there
are few studies on the beneficial genetic basis of HI independent of environmental factors. A total of 334 introgression lines with a genetic background of IR 64 were developed with NPTs under the
IRRI-Japan Collaborative Research Project (Fujita et al. 2009). Among them, YTH183 exhibited higher
yield and HI than those of IR 64 under various environmental conditions, such as water-saving (aerobic),
tropical wet and dry, irrigated lowland and upland, and temperate climate conditions (Kato et al. 2011;
Uddin et al. 2016; Ishimaru et al. 2017; Takai et al. 2019). It has been demonstrated that the higher yield
potential and greater dehydration avoidance in YTH183 might be conferred, at least in part, by
introgressed segments on chromosomes 5 and 6, respectively (Kato et al. 2011). Fujita et al. (2010) and
Ishimaru et al. (2017) reported that one QTL for grain weight was mapped on chromosome 5. Thus,
genetic analysis using YTH183 is expected to reveal another genetic factor for the sink-source balance or
the source ability in addition to grain weight (i.e., sink capacity). In this study, we attempted to identify QTLs for HI by using recombinant inbred lines (RILs) derived from
crosses between IR 64 and YTH183. To confirm the regional effects of detected QTLs on yield-related
traits and physiological attributes, a cross-locational investigation was conducted in locations with
subtropical and temperate climates in Japan. The present study provides novel information to improve
the HI of the Indica Group varieties through better sink-source balance or source ability. Materials And Methods Plant materials and cultivation Plant materials and cultivation An Indica Group variety IR 64 and YTH183 (IR84636-13-12-2-6-3-3-2-2-B), harboring chromosome
segments from the Tropical Group varieties in Indonesia (Fujita et al. 2009), were used as parental lines
to develop recombinant inbred lines (RILs) for QTL analysis. YTH183 is one of the introgression lines
derived from the cross between IR 64 and an NPT accession (IR69093-41-2-3-2, designated as YP5)
(Fujita et al. 2010), and therefore has a limited number of genomic regions introduced into IR 64 (Obara
et al. 2014). A total of 155 RILs and their parents were grown in paddy fields at JIRCAS in Ishigaki,
Okinawa, Japan (24.38°N,124.19°E) and in Tsukuba, Ibaraki, Japan (36.05°N,140.08°E) with the cropping
schedule described in Table 1. Ishigaki and Tsukuba are classified as having subtropical and temperate
climates, respectively. Note that two cropping seasons per year are possible in Ishigaki. A total of four
trials—three years (2016, 2017, and 2018) in the first cropping at Ishigaki and a single year (2017) at
Tsukuba—were performed to identify QTLs for HI. Additionally, to confirm the effects of the detected QTLs on HI in the different cropping season at Ishigaki,
six lines each of four different genotype combinations at two QTLs for HI were selected from those RILs,
and we cultivated at Ishigaki in the second cropping season of 2018. Twenty 28-day-old seedlings per
line were transplanted, one per hill, 18 cm apart, in two rows 36 cm apart. An organic slow-release
fertilizer (5.2-5.2-5.2 g/m2 N-P-K at Ishigaki and 4.8-6.4-3.2 g/m2 N-P-K at Tsukuba) was applied as a
basal fertilizer. Evaluation of yield-related traits We investigated three yield-related traits in all cropping seasons at Ishigaki and Tsukuba—total weight per
plant (TW), culm weight per plant (CW), and panicle weight per plant (PW)—which were used to calculate
the ratio of panicle weight to total weight (PW/TW = harvest index [HI]) (Table 1). In the first cropping
season of 2018 at Ishigaki, in addition to the above three traits, we investigated other traits: panicle
number per plant (PN), total number of spikelets per panicle (TS), number of filled grains per panicle (GN),
ratio of filled grains per panicle (GN/TS = fertility ratio [FR]), and 1000-grain weight (GWt). Further, we
also investigated grain length (GL) and grain width (GWd) of approximately 50 grains per plant each
using the software SmartGrain (Tanabata et al. 2012) in the first cropping season of 2018 at Ishigaki. In
the 2017 cropping season at Tsukuba, we investigated PW, CW, TW, and PN. In the first cropping season of 2017 at Ishigaki, we also investigated the developmental transition of the
ratio of panicle weight to total weight in two parental lines at two-day intervals from four weeks before
heading until harvest. Six undamaged plants from each line were investigated in all trials, and the
average value was taken to be representative for each line. Whole plants at 35 days after heading were
harvested and dried in a well-ventilated storage house for measurement. QTL analysis Page 4/19 Genomic DNA was extracted from frozen leaves of individual plants from the RILs by the method
described in Monna et al. 2002 with slight modifications. A total of 22 SSR markers and 74 KASP
markers (McCouch et al. 2010; LGC Genomics, Teddington, UK), which were located on the chromosome
segment from YP5, were used for genotyping of the 155 RILs (Table 2, Supplemental Fig. 3). QTL analyses for yield-related traits were performed using the R/qtl software package (Broman et al. 2003). Interval mapping (IM) was performed for each trait using the “scanone” function with default
settings to calculate the LOD value for each marker. The LOD threshold was obtained based on the
permutation test (1000 permutations, P = 0.05) for each trait. The additive effect was calculated as (the
mean value of the AA genotype) – (the mean value of the AA genotype + the mean value of the BB
genotype) / 2. Results HI and yield-related traits in the two parental lines The heading dates of IR 64 at Ishigaki were on May 30 in 2016, June 3 in 2017, and May 30  in 2018; on
the other hand, the heading dates of YTH183 at Ishigaki were on May 28 in 2016, June 2 in 2017, and
May 28 in 2018 (Supplemental Table 1). For three years from 2016 to 2018, HIs of YTH183 were
significantly higher than those of IR 64 both at Ishigaki and at Tsukuba in 2017 (Fig. 1a). PWs of YTH183
were similar or higher than those of IR 64, and CWs varied from lower to higher than those of IR 64
among four trials. This means that PW is a more stable trait than CW. The dry matter productions of PW
and CW at Ishigaki in 2017 and 2018 were lower than in the other two trials at Ishigaki in 2016 and at
Tsukuba in 2017, and the HIs at Ishigaki in 2017 and 2018 were also higher than these. These results
indicate that HIs became bigger under the condition of low dry matter production compared with high. The condition of the fertilizer (4.8 kg/10a, nitrogen basis: N) applied for cultivations was the same in
these four investigations, but the basic soil fertility conditions between Ishigaki and Tsukuba were
different, and the fields were also different among the three trials at Ishigaki. Basically, the variations in
dry matter productions of IR 64 and TH183 might be influenced by the soil fertility conditions. Comparing
the developmental transitions in the ratio of panicle weight to total weight between YTH183 and IR 64,
remarkably significant differences were found in the late maturing stage (Fig. 1b). In the yield-related
traits, although there was no significant difference in PN or TS between YTH183 and IR 64, GWt and FR
were higher in YTH183 than in IR 64, resulting in a higher PW in YTH183 (Fig. 1c). Furthermore, GWd was
higher in YTH183 than in IR 64, while GL was lower (Fig. 1c). It is therefore considered that the large grain
size in YTH183 contributes to the higher HI and yield than that of IR 64. Evaluation of yield-related traits The phenotypic variance explained (PVE) by each QTL was estimated by 1 − 10−2LOD/n,
where n indicates the sample size and LOD indicates the LOD value from “scanone.” QTL analyses The HIs of RILs in the three years were continuously distributed with transgressive segregates (Fig. 2,
Supplemental Table 2). In addition, significant positive correlations were observed between each cropping Page 5/19 season (Table 3). Compared with the correlations among the three cropping seasons at Ishigaki, the
correlations between the cropping season at Tsukuba and the cropping seasons at Ishigaki were low
(Table 3). season (Table 3). Compared with the correlations among the three cropping seasons at Ishigaki, the
correlations between the cropping season at Tsukuba and the cropping seasons at Ishigaki were low
(Table 3). QTL analyses identified a total of twenty QTLs for eight agricultural traits, including HI, on chromosomes
5, 8, 9, and 12 (Fig. 3, Table 4). Among them, QTLs for HI were identified in the regions on chromosomes 5
and 8 for the three years at Ishigaki. At Tsukuba, only the QTL on the region of chromosome 5 was
identified, and that on chromosome 8 was not (Fig. 3, Table 4, Supplemental Fig. 1). We designated the
two QTLs on chromosomes 5 and 8 as qHI5.1 and qHI8.1, respectively. Both of the YTH183 alleles at
these QTLs additively contributed to the high HI without any genetic interactions in the three years of
cropping at Ishigaki (Fig. 4). In the region where qHI5.1 is located, a QTL for PW was detected (by analyses in 2017 and 2018). Further,
QTLs for GWt, GL, and GWd were also located in the same region. In this region, the GSE5/GW5 gene for
grain weight is reported (Duan et al. 2017; Liu et al. 2017). Therefore, we investigated genomic
polymorphism of the GSE5 gene between YTH183 and IR 64, and found that YTH183 harbored an
insertion at the promoter region of this gene (Supplemental Fig. 2). On the other hand, in the region where qHI8.1 is located, QTLs for CW, FR, and GL were detected (by
analysis in 2018). However, we did not detect any QTLs, including for HI, at this region in the cropping at
Tsukuba (Fig. 3, Table 4). Interestingly, although qHI5.1 showed a significant effect on the HI in the
second cropping season at Ishigaki in 2018, qHI8.1 did not (Fig. 4). During the maturing stage in the
second cropping season at Ishigaki in 2018, the average daily temperature was as low as it was in the
cropping season at Tsukuba. QTL analyses The average temperatures during the maturing stage at Tsukuba and the
second cropping at Ishigaki were remarkably lower than those of the three first cropping seasons at
Ishigaki (Supplemental Table 3). This difference in temperatures during the maturing stage might have
influenced the effect of qHI8.1. Discussion The harvest index (HI) is used to measure biological success in the formation of harvestable products. However, the genetic basis of HI in rice is not well understood because it is a complex trait comprising a
number of yield-related traits and physiological attributes. Under the IRRI-Japan Collaborative Research
Project, 334 introgression lines with the genetic background of IR 64 were developed to enhance yield
potential by backcrossing between nine NPT varieties and one Japanese high-yielding cultivar as the
donor parents and IR 64 as the recurrent parent (Fujita et al. 2009). Among those introgression lines,
YTH183 showed remarkably higher yield and greater adaptability to both tropical and temperate regions
than IR 64 (Takai et al. 2019). In this study, we genetically analyzed the yield potential of YTH183 from
the perspective of HI. Our results showed that high correlations were found among the three years of HI at
Ishigaki, whereas low correlations were found between the three years of HI at Ishigaki and the HI at
Tsukuba (Table 3), suggesting that RILs showed different performances between Ishigaki and Tsukuba. Page 6/19 Page 6/19 HI is a complex trait and susceptible to environmental conditions, and it is difficult to find a genetic factor. Nonetheless, our results clarified the fact that two major QTLs for HI (qHI5.1 and qHI8.1 detected on
chromosomes 5 and 8, respectively) contributed to the yield potential of YTH183. It is noteworthy that
qHI5.1 was consistently detected under the different climatic conditions of Ishigaki (subtropical) and
Tsukuba (temperate) (Fig. 3, Table 4), suggesting that qHI5.1 may be a useful genetic factor for the
genetic improvement of HI in Indica Group varieties grown in both temperate and subtropical regions. In
the same region on chromosome 5, QTLs for panicle weight (PW), grain weight (GWt), and grain width
(GWd) were also identified, indicating that this QTL increased the total sink size through increasing grain
size. This QTL did not have any negative effect on yield-related traits, such as culm weight (CW) or
fertility rate (FR). Our results are consistent with those of previous research showing that the improved HI
of YTH183 is attributable to the enlarged sink capacity due to large grain size (Kato et al. 2011). Further,
previous studies have shown that an introgressed segment in YTH183 contains a major QTL for grain
size (qSW5) on chromosome 5 (Shomura et al. Discussion 2008), and using the 334 introgression lines identified a
QTL for grain weight (qGW5) in the same region as qSW5 (Fujita et al. 2009). Recently, Duan et al. (2017)
and Liu et al. (2017) identified a previously unrecognized gene (GSE5/GW5) at the qSW5/qGW5 locus. They showed that natural variations in the promoter of GSE5/GW5 contribute to grain size diversity. In
this study, we found a DNA polymorphism between IR 64 and YTH183 (an insertion in YTH183) in the
promoter region of the GSE5/GW5 gene (Supplemental Fig. 2). The sib lines derived from the same parent
(YP5) as YTH183 with the insertion significantly showed heavier grain weight than those without the
insertion (Supplemental Fig. 4). We therefore consider that qHI5.1 is identical to GSE5/GW5. Shomura et al. (2008) compared the rice varieties of the Japonica and Indica Groups, and they then
identified a major QTL for grain size as qSW5, which is identical to GSE5/GW5, and the Japonica allele
clearly contributed heavier grain weight. YTH183 was developed by the backcross breeding between a
new plant type variety, IR69093-41-2-3-2(YP5) harboring chromosome segments from the Tropical
Japonica Group rice varieties and IR 64 as the recurrent parent. We therefore consider that qHI5.1 is
identical to GSE5/GW5, which might be widely harbored in Japonica Group varieties from tropical to
temperate, and that the allele of YTH183 contributes to the wide grain, resulting in the higher GWt, PW,
and HI in YTH183 than in IR 64. Further, because qHI5.1 was stably identified under different
environmental conditions, it is possible that this QTL could become one of the widely useful genetic
factors to increase HI without the negative effect of environmental conditions, especially high
temperatures during the maturing stage such as in tropical or subtropical regions. It still needs to be
considered that qHI5.1 might be co-located with GSE5/GW5 in the same chromosome region, and the
identity will have to be confirmed based on the gene isolation of qHI5.1. Shomura et al. (2008) compared the rice varieties of the Japonica and Indica Groups, and they then
identified a major QTL for grain size as qSW5, which is identical to GSE5/GW5, and the Japonica allele
clearly contributed heavier grain weight. YTH183 was developed by the backcross breeding between a
new plant type variety, IR69093-41-2-3-2(YP5) harboring chromosome segments from the Tropical Shomura et al. Discussion (2008) compared the rice varieties of the Japonica and Indica Groups, and they then
identified a major QTL for grain size as qSW5, which is identical to GSE5/GW5, and the Japonica allele
clearly contributed heavier grain weight. YTH183 was developed by the backcross breeding between a
new plant type variety, IR69093-41-2-3-2(YP5) harboring chromosome segments from the Tropical
Japonica Group rice varieties and IR 64 as the recurrent parent. We therefore consider that qHI5.1 is
identical to GSE5/GW5, which might be widely harbored in Japonica Group varieties from tropical to p
yp
y,
(
)
g
g
p
Japonica Group rice varieties and IR 64 as the recurrent parent. We therefore consider that qHI5.1 is
identical to GSE5/GW5, which might be widely harbored in Japonica Group varieties from tropical to
temperate, and that the allele of YTH183 contributes to the wide grain, resulting in the higher GWt, PW,
and HI in YTH183 than in IR 64. Further, because qHI5.1 was stably identified under different
environmental conditions, it is possible that this QTL could become one of the widely useful genetic
factors to increase HI without the negative effect of environmental conditions, especially high
temperatures during the maturing stage such as in tropical or subtropical regions. It still needs to be
considered that qHI5.1 might be co-located with GSE5/GW5 in the same chromosome region, and the
identity will have to be confirmed based on the gene isolation of qHI5.1. At the qHI8.1 region, no other QTLs were identified other than a QTL for leaf weight (LW) in 2018. Kato
et al. (2011) demonstrated that the source supply for grain growth, i.e., the concentration and amount of
non-structural carbohydrate in vegetative organs at anthesis, was largely not improved in YTH183. On the
other hand, Ishimaru et al. (2017) suggested that the higher HI in YTH183 is supported by greater
photosynthate translocation from sources to sinks during the maturing stage. They showed greater non-
structural carbohydrate depletion during the grain-filling stage and a higher number of vascular bundles Page 7/19 in the panicle neck of YTH183, suggesting enhanced capacity for assimilate transport to the developing
panicles during the maturing stage. Laza et al. (2006) identified QTLs for HI on chromosomes 8 and 11
by using RILs derived from a cross between IR 72 and an NPT variety that was a sibling of the donor
variety (YP5) of YTH183. Discussion They indicated that these QTLs might be involved in the difference in grain-
filling abilities between the Indica and Japonica Groups. Therefore, qHI8.1 might be involved in the ability
of the photosynthate to be translocated from the source to the sink organs. Interestingly, qHI8.1 did not
have a significant effect on HI in the cropping at Tsukuba or in the second cropping at Ishigaki. This
result might be explained by differences in the environmental conditions during the maturing stage: The
daily average temperature during the maturing stage was higher in the first cropping season at Ishigaki
than in the second cropping at Ishigaki and the cropping at Tsukuba (Supplemental Table 3); therefore,
the effectiveness of qHI8.1 might be temperature dependent. Welch et al. (2010) reported that a higher
minimum temperature reduced yield by analyzing data from 227 intensively managed irrigated rice farms
in six important rice-producing countries. Peng et al. (2004) also reported direct evidence of decreased
rice yields from increased nighttime temperature associated with global warming. In the metabolic
process of grain filling, Yamakawa et al. (2007) showed that the expression level of genes encoding
starch- or carbohydrate-metabolizing enzymes and translocators was diminished to 89% of the control on
average by exposure to high temperature, suggesting that ripening under high temperature induced the
occurrence of grains with various degrees of chalky appearance and decreased weight. Therefore, qHI8.1
is expected to enhance source ability or the translocation of photosynthesis products from shoots to
grains under conditions of higher temperature during the maturing stage. Introgression of qHI8.1, in
addition to qHI5.1, into Indica Group varieties would contribute to enhancement of HI in tropical regions,
and in temperate regions where air temperatures during the maturing stage have been progressively
increasing (Iizumi et al. 2011). The effects of the two QTLs, qHI5.1 and qHI8.1, under various
environmental conditions need to be confirmed using the isogeneic lines for qHI5.1 and qHI8.1 and the
accumulated line for qHI5.1 and qHI8.1 with an IR 64 genetic background. Studies on inheritance of the HI trait are limited, because it is a complex trait that incorporates the
number of grains, grain weight, and number of panicles as the sink capacity, and also incorporates culm
and leaf weight, photosynthetic rate, and translocation of the assimilated carbon as the source activity. In
addition, although some of these traits are highly genetically controlled, most are environment sensitive. Discussion Consequently, it is difficult to identify the QTLs for HI independent of environmental effects. Multi-
location or multi-year trials are essential for identifying effective and stable QTLs. Hittalmani et al. (2003)
identified eleven QTLs for HI at nine locations in Asia representing different environments; however, no
common QTL was detected in all nine locations. Li et al. (2012) identified genetic markers associated
with HI in both temperate (Arkansas) and subtropical (Texas) climates, but detected no associated
markers in common. In our study, two stable QTLs (qHI5.1 and qHI8.1) for HI were identified by three
multi-year field trials in the first cropping season at Ishigaki. Among them, qHI5.1 was found to contribute
to the grain size independent of the environmental conditions, whereas qHI8.1 was efficient for maturing
under high temperatures. Further, YTH183 shows superior performance when cultivated under water-
saving conditions and shows high plasticity in root elongation in response to re-watering after drought Page 8/19 Page 8/19 (Kato et al. 2011; Kano-Nakata et al. 2013). Furthermore, Obara et al. (2014) identified a QTL on
chromosome 6 for root length under N-deficient conditions in YTH183. Thus, YTH183 is remarkable for
its excellent response to water- and N-deficient conditions in addition to its enhanced sink capacity owing
to its enlarged grain size. Our current findings and previous work suggest that YTH183 will likely be a
noteworthy source of breeding material that can be exploited in rice-breeding efforts in the near future for
breaking through the ceiling of maximum yield in response to environmental change under global
warming. (Kato et al. 2011; Kano-Nakata et al. 2013). Furthermore, Obara et al. (2014) identified a QTL on
chromosome 6 for root length under N-deficient conditions in YTH183. Thus, YTH183 is remarkable for
its excellent response to water- and N-deficient conditions in addition to its enhanced sink capacity owing
to its enlarged grain size. Our current findings and previous work suggest that YTH183 will likely be a
noteworthy source of breeding material that can be exploited in rice-breeding efforts in the near future for
breaking through the ceiling of maximum yield in response to environmental change under global
warming. Conclusion Here, we demonstrate that two novel QTLs for HI (qHI5.1 on chromosome 5 and qHI8.1 on
chromosome 8) contribute to the higher HI in YTH183 than in IR 64. qHI5.1 is identical to GSE5/GW5 and
controls the grain size, regardless of whether environmental conditions are of subtropical or temperate
regions. qHI8.1 functioned additively with qHI5.1 for higher HI, but showed significant effects on yield-
related traits only in the first cropping season in Ishigaki, where the air temperatures were higher during
the maturing stage. Therefore, qHI8.1 may be associated with regulation of the physiological processes
of the source ability or the translocation of photosynthesis products from shoots to grains according to
temperature at the maturing stage. These two QTLs are therefore anticipated to be effective genetic
resources in breeding programs attempting to surmount the maximum yield in Indica Group varieties. Author information
Affiliations Tropical Agriculture Research Front (TARF), Japan International Research 
(JIRCAS), Okinawa 907-0002, Japan Hiroki Saito, Yoshimichi Fukuta, Asami Tomita Hiroki Saito, Yoshimichi Fukuta, Asami Tomita Mitsuhiro Obara Mitsuhiro Obara Declarations
Funding Page 10/19
Declarations
Funding
This study was performed under the Japan International Research Center for Agricultural Sciences
Research Project “Food security in Africa” (2016 onward). Author information
Affiliations
Tropical Agriculture Research Front (TARF), Japan International Research Center for Agricultural Scienc
(JIRCAS), Okinawa 907-0002, Japan
Hiroki Saito, Yoshimichi Fukuta, Asami Tomita
 
Japan International Research Center for Agricultural Sciences (JIRCAS), Ibaraki 305-8686, Japan
Mitsuhiro Obara
 
Japan International Research Center for Agricultural Sciences (JIRCAS), Ibaraki 305-8686, Japan, and
International Rice Research Institute, DAPO Box 7777, Metro Manila, Philippines
Tsutomu Ishimaru, Kazuhiro Sasaki, Daisuke Fuita, Nobuya Kobayashi
 
Current address
Faculty of Agriculture, Okayama University, Okayama 700-8530, Japan
Asami Tomita
 
Hokuriku Research Station, Central Region Agricultural Research Center (CARC), National Agriculture an
Food Research Organization (NARO), Niigata 943-0193, Japan List Of Abbreviations List Of Abbreviations
NTPs: New-plant-type varieties
HI: Harvest index
RILs: Recombinant inbred lines
TW: Total weight per plant
CW: Culm weight per plant
PW: Panicle weight per plant
PN: Panicle number per plant
TS: total number of spikelets per panicle
GN: Number of filled grains per panicle
FR: Fertility ratio
GWt: 1000-grain weight Page 9/19 GL: Grain length
GWd: Grain width GL: Grain length Funding This study was performed under the Japan International Research Center for Agricultural Sciences
Research Project “Food security in Africa” (2016 onward). Authors’ contributions HS and YF designed this research project, performed field trials, analyzed data, and wrote the original
draft. MO performed field trials in Tsukuba and wrote/reviewed manuscript. AT performed field trials in
Ishigaki and wrote/reviewed the manuscript. TI performed data curation, developed materials, and
reviewed/edited the manuscript. KS, DF, and NK developed materials and reviewed/edited the manuscript. All authors approved the manuscript. Corresponding Author Yoshimichi Fukuta Tropical Agriculture Research Front (TARF), Japan International Research Center Agricultural Science
(JIRCAS), Okinawa 907-0002, Japan. E-mail: zen@affrc.go.jp Current address Asami Tomita Tsutomu Ishimaru Japan International Research Center for Agricultural Sciences (JIRCAS), Ibaraki 305-8686, Japan
Kazuhiro Sasaki Kazuhiro Sasaki Faculty of Agriculture, Saga University, Saga 840-8502, Japan Daisuke Fuita Institute of Crop Science, National Agriculture and Food Research Organization (NARO), Tsukuba 305-
8518, Japan Nobuya Kobayashi Competing Interests The authors declare that they have no competing interests. Consent for Publication Not applicable. Ethics declarations Ethics Approval and Consent to Participate Page 11/19 Page 11/19 Not applicable. Availability of Data and Materials The datasets generated during and analyzed during the current study are available from the
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Comparison of HI and yield-related traits b
(n=6 plants). (a) HI, panicle weight, and cu
cropping seasons at Ishigaki in 2016, 201
value indicates statistical analysis by Stud   Figure 1
Comparison of HI and yield-related traits between IR 64 and YTH183. Data are expressed as means ± S
(n=6 plants). (a) HI, panicle weight, and culm (and leaf) weight in Tsukuba (2017TKB) and three first-
cropping seasons at Ishigaki in 2016, 2017, and 2018 (2016ISG_F, 2017ISG_F, and 2018ISG_F). The P
value indicates statistical analysis by Student’s t-test. N.D. indicates no significant difference. (b)
Transitions of HI between IR 64 and YTH183 in the first cropping at Ishigaki in 2017. The asterisks        Figure 1 Figure 1 Comparison of HI and yield-related traits between IR 64 and YTH183. Data are expressed as means ± SD
(n=6 plants). (a) HI, panicle weight, and culm (and leaf) weight in Tsukuba (2017TKB) and three first-
cropping seasons at Ishigaki in 2016, 2017, and 2018 (2016ISG_F, 2017ISG_F, and 2018ISG_F). The P
value indicates statistical analysis by Student’s t-test. N.D. indicates no significant difference. (b)
Transitions of HI between IR 64 and YTH183 in the first cropping at Ishigaki in 2017. The asterisks Page 16/19 Page 16/19 represent a significant difference between the two parents (P < 0.05) based on Student’s t-test. (c)
Comparison of six yield-related traits between IR 64 and YTH183 in the first cropping at Ishigaki in 2018. The P value indicates statistical analysis by Student’s t-test. N.D. indicates no significant difference. represent a significant difference between the two parents (P < 0.05) based on Student’s t-test. (c)
Comparison of six yield-related traits between IR 64 and YTH183 in the first cropping at Ishigaki in 2018. The P value indicates statistical analysis by Student’s t-test. N.D. indicates no significant difference. represent a significant difference between the two parents (P < 0.05) based on Student’s t-test. (c)
Comparison of six yield-related traits between IR 64 and YTH183 in the first cropping at Ishigaki in 2018
The P value indicates statistical analysis by Student’s t-test. N.D. indicates no significant difference. The P value indicates statistical analysis by Students t test. N.D. indicates
Figure 2
F
di t ib ti
f HI
f RIL i
th
i
t I hi
ki  Page 17/19
Figure 2
Frequency distributions of HIs of RILs in the cropping seasons at Ishigaki (ISG) and Tsukuba (TKB). Th
white, black, and gray arrows indicate, respectively, the HI of IR 64, YTH183, and the average of the RIL Figure 4 The mean of harvest index in 2018ISG_F, 2018ISG_S, and 2017TKB for different genotype classes
between qHI5.1 and qHI8.1 in RIL populations. Genotypes are represented by the nearest marker loci,
RM1089 (qHI5.1) and 8099836 (qHI8.1). The P value indicates the statistical analysis by Student’s t-test. N.D. indicates no significant difference. Figure 2 Frequency distributions of HIs of RILs in the cropping seasons at Ishigaki (ISG) and Tsukuba (TKB). The
white, black, and gray arrows indicate, respectively, the HI of IR 64, YTH183, and the average of the RILs. Page 17/19 Page 17/19 Figure 3
Linkage map developed by the genetic analysis of RILs and QTLs identified in this study. The vertical
bars indicate the range in which the LOD value of each QTL exceeds the threshold. The double-headed
arrows on chromosomes 5 and 8 indicate the putative region where the responsible genes for HI would be
located. Abbreviations are as follows: Panicle weight (PW), culm and leaf weight (CW), grain weight
(GWt), grain length (GL), and grain width (GWd). Figure 3 Linkage map developed by the genetic analysis of RILs and QTLs identified in this study. The vertical
bars indicate the range in which the LOD value of each QTL exceeds the threshold. The double-headed
arrows on chromosomes 5 and 8 indicate the putative region where the responsible genes for HI would be
located. Abbreviations are as follows: Panicle weight (PW), culm and leaf weight (CW), grain weight
(GWt), grain length (GL), and grain width (GWd). Page 18/19 Figure 4 Figure 4 Supplementary Files This is a list of supplementary files associated with this preprint. Click to download. Table1.xlsx Table2.xlsx Table3.xlsx Table4.xlsx SupplementalR2.docx Page 19/19 Page 19/19