Whole-genome analysis of recombinant inbred rice lines reveals a quantitative trait locus on chromosome 3 with genotype-by-environment interaction effects

Alfatih A, Wu J, Zhang Z-S, Xia J-Q, Jan SU, Yu LH, Xiang CB. Rice

NIN-LIKE PROTEIN 1 rapidly responds to nitrogen deficiency

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Fang et al. 2019). Here, we showed that when the genotype of this

locus was from the Hitomebore parent, heading date was delayed

compared to the heading date conferred by the allele from the

tropical japonica cultivar URASAN1 at all 3 trial locations (Fig. 3a).

Our results are also in line with the finding of Fang et al. that the

effect of Ef-cd on heading date depends on environmental factors

(Fig. 3a) (Fang et al. 2019). Our results suggest that the Ef-cd locus of

tropical japonica cultivar URASAN1 has a similar function as that of

the indica cultivar.

The locus we identified also showed GxE interaction effects for

grain number and leaf length (Fig. 3, b and c). Phenotypes related to

plant growth and heading date are normally correlated because a

long growth period leads to higher yields (Wang et al. 2018; Yu and

Qian 2019). However, the Ef-cd locus causes a shortened matur­

ation period with no yield penalty (Fang et al. 2019). We determined

that when plants had the URASAN1 allele at this locus, their head­

ing date was earlier compared to that of plants with the

Hitomebore allele at all 3 trial locations (Fig. 3a). At Aomori and

Fukushima, grain number and leaf length did not vary depending

on heading date (Fig. 3, b and c), which is consistent with the

finding that the Ef-cd locus accelerates maturation without a yield

penalty (Fang et al. 2019). However, at the Iwate location, grain

number and leaf length decreased with earlier heading date

(Fig. 3). Therefore, our results suggest that the relationship be­

tween Ef-cd-mediated maturation period and plant growth traits

is modulated by environmental factors. Alternatively, it is possible

that other genes located in this genomic region have effects on

plant growth traits, with GxE interaction effects.

Several genes that facilitate nitrogen utilization are upregu­

lated via the function of the Ef-cd locus (Fang et al. 2019).

Nitrogen utilization is closely related to the photosynthetic cap­

acity and yield potential of crops (Chen et al. 2016, 2017; Wang

et al. 2018). Our analysis showed that the soil NO3 concentration

might contribute to the GxE interaction effect of our QTL for grain

number and leaf length (Supplementary Table 9). It is possible that

the concentration of available nitrogen in the soil influences the

genetic effects of the Ef-cd locus on grain number and leaf length.

However, the genomic region identified by our GxE analysis also

contains OsNLP1 (Supplementary Table 8), which enhances nitro­

gen utilization to improve plant growth and grain yield under ni­

trogen limitation conditions (Alfatih et al. 2020). Therefore,

OsNLP1 is also a candidate with a possible GxE interaction effect

on grain number and leaf length in the RIL1 population.

Several genes of unknown function are also located in the gen­

omic region we identified. Furthermore, our analysis of environ­

mental factors revealed several factors that showed significant

GxE interaction effects, including lowest and highest tempera­

tures, precipitation, and sunshine duration (Supplementary

Table 9). Therefore, additional experiments under more con­

trolled environmental conditions are needed to identify gene

sets and environmental factors that contribute to the GxE inter­

action. Identifying relevant environmental factors is easier under

controlled laboratory conditions than under natural conditions;

however, controlled conditions do not reflect the natural environ­

ments where crops are actually grown (Anderson et al. 2014; de

Leon et al. 2016). Thus, to understand the genetic and environmen­

tal factors involved in GxE interactions, it will be important to

measure the effects of environmental factors under both natural

and controlled laboratory conditions (Xu 2016; Xu et al. 2017).

Our results show that the effects of QTLs on yield traits such as

grain number vary with environmental factors (Fig. 3b). Numerous

GWASs have identified QTLs associated with agronomically im­

portant traits in rice (Huang et al. 2010; Yano et al. 2019).

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