Literature DB >> 23136505

Effects on flowering and seed yield of dominant alleles at maturity loci E2 and E3 in a Japanese cultivar, Enrei.

Tetsuya Yamada1, Makita Hajika, Naohiro Yamada, Kaori Hirata, Akinori Okabe, Nobuhiko Oki, Koji Takahashi, Kousuke Seki, Katsunori Okano, Yoichi Fujita, Akito Kaga, Takehiko Shimizu, Takashi Sayama, Masao Ishimoto.   

Abstract

'Enrei' is the second leading variety of soybean (Glycine max (L.) Merr.) in Japan. Its cultivation area is mainly restricted to the Hokuriku region. In order to expand the adaptability of 'Enrei', we developed two near-isogenic lines (NILs) of 'Enrei' for the dominant alleles controlling late flowering at the maturity loci, E2 and E3, by backcrossing with marker-assisted selection. The resultant NILs and the original variety were evaluated for flowering, maturity, seed productivity and other agronomic traits in five different locations. Expectedly, NILs with E2 or E3 alleles flowered later than the original variety in most locations. These NILs produced comparatively larger plants in all locations. Seed yields were improved by E2 and E3 in the southern location or in late-sowing conditions, whereas the NIL for E2 exhibited almost the same or lower productivity in the northern locations due to higher degrees of lodging. Seed quality-related traits, such as 100-seed weight and protein content, were not significantly different between the original variety and its NILs. These results suggest that the modification of genotypes at maturity loci provides new varieties that are adaptive to environments of different latitudes while retaining almost the same seed quality as that of the original.

Entities:  

Keywords:  Glycine max (L.) Merr.; backcrossing; marker-assisted selection; maturity gene; near-isogenic lines; seed productivity; soybean

Year:  2012        PMID: 23136505      PMCID: PMC3406789          DOI: 10.1270/jsbbs.61.653

Source DB:  PubMed          Journal:  Breed Sci        ISSN: 1344-7610            Impact factor:   2.086


Introduction

‘Enrei’ is the second leading variety of soybean (Glycine max L. Merr.) in Japan; its production area accounts for 12.3% of the total soybean production area [Ministry of Agriculture, Forestry and Fisheries (2011)]. This variety was registered in 1971 and has been used preferably for tofu production because of its high protein content; however, its production area is limited to the Hokuriku region around Niigata Prefecture because of its narrow-ranged adaptability to latitudes. Most of the total production area of ‘Enrei’ (99.3%) is occupied by three prefectures in the Hokuriku region (Niigata, Toyama and Ishikawa) and Yamagata Prefecture [Ministry of Agriculture, Forestry and Fisheries (2011)]. The modification of flowering and maturing habits is thus very important to extend the adaptability of ‘Enrei’, toward the southern regions of lower latitudes and/or the northern regions of higher latitudes. Cober and Morrison (2010) exemplified the usefulness of modified maturity genotypes of soybean varieties to adapt to a wide range of latitudes. They evaluated flowering and maturating habits and seed yield for 20 near-isogenic lines (NILs) of cv. Harosoy for the five maturity loci (E1, E2, E3, E4 and E7) and growth habit loci (Dt1) in Ottawa, Canada, and observed that the seed yield increased linearly with maturity until about 112 days, and then reached a plateau. They concluded that variations in the photoperiod sensitivity and growth habit alleles give rise to a range of maturities, with pleiotropic effects on seed yield and agronomic characteristics, and that the variations play an important role in providing adaptation across latitudes (Cober and Morrison 2010). Time to flowering and maturity in soybeans is controlled by E1, E2 (Bernard 1971), E3 (Buzzell 1971), E4 (Buzzell and Voldeng 1980), E5 (McBlain ), E6 (Bonato and Vello 1999), E7 (Cober and Voldeng 2001), E8 (Cober ) and J (Ray ). In addition to these major genes, a number of quantitative trait loci (QTL) have been known to control the time to flowering (review by Watanabe ). Of the major E genes, E1 to E4 were mapped on a fine scale on linkage groups (LGs) C2 for E1 (Yamanaka , Watanabe ), O for E2 (Watanabe ), L for E3 (Watanabe ) and I for E4 (Matsumura , Liu ). Furthermore, resent molecular assays have identified the genes responsible for some of the E genes; E2 is a GIGANTEA ortholog, GmGIa (Watanabe ), E3 and E4 are genes encoding phytochrome A (phyA), GmphyA3 (Watanabe ) and GmphyA2 (Liu ), respectively. The information on the exact position in linkage maps and physical maps and the molecular bases may facilitate the use of DNA markers tagging agronomically important genes in the tailor-made breeding of soybean varieties. In this paper, we report the development of NILs for maturity genes, E2 and E3, of ‘Enrei’, and the results of field evaluations on agronomic traits, such as flowering and maturing times, seed productivity and plant morphology, under various environmental conditions.

Materials and Methods

Plant materials and development of NILs

Two NILs for E2 and E3, and their parental varieties, ‘Enrei’, ‘Sachiyutaka’ and ‘Fukuyutaka’, and three leading varieties, ‘Suzuyutaka’, ‘Tachinagaha’ and ‘Tamahomare’, were used in this study. ‘Sachiyutaka’ had been bred from BC2 progeny between ‘Fukuyutaka’ and ‘Enrei’, in which the latter was used as a recurrent parent (Takahashi ). The NILs for E2 and E3 used in this study were developed by backcrossing between ‘Enrei’ and ‘Sachiyutaka’ or ‘Fukuyutaka’ (Table 1). The maturity genotypes at E2 and E3 were estimated as e2e2e3e3 for ‘Enrei’, E2E2e3e3 for ‘Sachiyutaka’ and E2E2E3E3 for ‘Fukuyutaka’, based on the functional DNA markers developed for E2 (Watanabe ) and E3 (Watanabe ) (personal communication from Dr. Yasutaka Tsubokura). F1 hybrids between ‘Enrei’ and ‘Sachiyutaka’ and between ‘Enrei’ and ‘Fukuyutaka’ were backcrossed with ‘Enrei’, and in each backcrossing, plants heterozygous for the maturity locus were selected based on the marker genotypes (Table 2). In the BC2F1 generation, polymorphic SSR markers covering the whole genome were surveyed. In the subsequent generations, plants heterozygous at the maturity locus but homozygous for the allele from ‘Enrei’ at as many SSR loci as possible were selected as a pollen parent in backcrossing.
Table 1

Summary of back-crossing for E2 and E3 in ‘Enrei’

ParentaBC0bBC1BC2BC3BC4
Name of parent carrying E2Sachiyutaka
Number of plants genotyped at F12019280
Number of plants developing next generation after DNA marker-assisted selection20921
Sowing year and month2007.22007.72007.112008.22008.7

Number of plants genotyped at F273
Number of samples carrying donor allele in homozygote at E219
Sowing year and month2008.11

‘Enrei’ was crossed as recurrent parent in every generation.

BC0 indicates single-cross.

Table 2

The marker panels for estimating E2 and E3 genotypes used in the multiplex PCRs

Marker nameDyeaForward sequence (5′ to 3′)Reverse sequence (5′ to 3′)Location in Phytozome databasebAmplicon size (bp)c

EnreiFukuyutaka
E2at_U46k6-FAMGGATAATTTTCTGCAGCCATGTCGAACCTTTGAGTGCATTTC34 kb upstream away from E2 region214204
E2atPETGTGCCTTTCCTGCCTTTTCATCGGCCATTTTTAACTTGTGInside of E2 region305311
E2at_D82kNEDCGTCTATTCTATGTTTCGTGGAATGGACATTTTGTTGGATC70 kb downstream away from E2 region223225
GMES4019PETTCAATTCGTTAAATCTGTTGTTCCATGGTACGTGTGTGTGGTCC189 kb downstream away from E2 regionNDd155
E3at-U113kNEDCAACCTAACTCGTGACCACCACAAAGCCGTTGTTATCCTTA113 kb upstream away from E3 region379352
FT3SSR4VICGCCTATTTAGAAACCAATCCACCGCTAGCAACTTTACTG1 kb upstream away from E3 region306304
FT3SSR1domVICATTAATTCGTTGACTCGGTACTCCGGACTTAGAATGGAGGGCATAAA1 kb downstream away from E3 regionND283
FT3SSR3PETCATTTCCATTTGTGCCTACCACTTTCTTCCTTCTCTCACCCACT19 kb downstream away from E3 regionND344

Fluorescent material referred to Applied Biosystems was attached together with the tail of several nucleotides before 5′ end of forward primer.

http://www.phytozome.net/soybean (Schmutz ).

‘Sachiyutaka’ showed the same pattern as ‘Fukuyutaka’ around E2 and ‘Enrei’ around E3.

No amplicons.

Marker analysis

Total DNA was extracted from young leaves using Biorobot EZ1 (Qiagen, Valencia, CA, USA) or Biosprint 96 (Qiagen). To estimate the E2 or E3 genotype, we developed several DNA markers based on sequence information on the E2 or E3 gene and their flanking regions (Table 2). These markers were labeled by different fluorescence dyes and multiplex polymerase chain reactions (PCRs) were performed in a 5.5 μl reaction mixture [containing 50 nM of each fluorescent primer pair, 5 ng total genomic DNA, and 2.5 μl of 2X Qiagen Multiplex PCR Master Mix (Qiagen, Hilden, Germany)] using a GeneAmp PCR System 9700 thermal cycler (Applied Biosystems, Foster City, CA, USA). The amplification protocol and detection of the resulting amplicons using a fluorescence-based DNA sequencer followed the method described by Sayama . We screened the polymorphism between ‘Enrei’ and ‘Fukuyutaka’ for 245 simple sequence repeat (SSR) markers with high polymorphism information content values, which were selected at approximately every 12 cM (Hwang ). The method of detection for SSR genotypes followed the method described by Sayama .

Growth conditions

Field experiments were conducted in 2009 and 2010 at the five agricultural experimental stations shown in Fig. 1 and Table 3. In each experiment, soybeans were grown using common cultivation methods at the stations (Table 3). ‘Enrei’ and ‘Enrei-E2’ were examined in all of the experiments, whereas ‘Enrei-E3’ was examined in three experiments conducted in a field of the National Agriculture and Food Research Organization Institute of Crop Science (Tsukubamirai, Ibaraki) in 2009 and 2010 and in a field of the National Agriculture and Food Research Organization Western Region Agricultural Research Center (Zentsuji, Kagawa). Each line was planted in two replications in accordance with the breeding methods for the primary yield test.
Fig. 1

Locations of experimental sites and cultivation areas of Enrei, Sachiyutaka and Fukuyutaka

Table 3

Experimental sites and growth conditions

Experimental sitesGPSYearDay of sowingInter-low (cm)Intra-low (cm)Number of plants per hillMeasurement areaSoil typeAmount of fertilizer apried


Low length (m)Number of lowsNumber of plantsPlot area (m−2)Number of replicationN : P : K (kg/ha)MgCl2 (kg/ha)Compost (t/ha)
Niigata Agricultural Research Institute (Nagaoka, Niigata)37°26′14N, 138°52′26E200921-May751513.036011.252Andosol16 : 40 : 60
Nagano Vegetable and Ornamental Crops Experiment Station (Shiojiri, Nagano)36°6′11N, 137°56′0E20101-Jun7516.712.02249.002Andosol36 : 144 : 7260010
Plant Biotechnology Institute, Ibaraki Agricultural Center (Mito, Ibaraki)36°26′24N, 140°26′57E201022-Jun601512.75309.002Andosol30 : 100 : 10010
National Agriculture and Food Research Organization Institute of Crop Science (Tsukubamirai, Ibaraki in 2009)36°0′26N, 140°1′19E200926-Jun701313.04928.402gray lowland soil30 : 100 : 1001000
National Agriculture and Food Research Organization Institute of Crop Science (Tsukubamirai, Ibaraki in 2010)36°0′26N, 140°1′19E201015-Jul701313.04928.402gray lowland soil30 : 100 : 100100
National Agriculture and Food Research Organization Western Region Agricultural Research Center (Zentsuji, Kagawa)34°13′47N, 133°46′36E201011-Jun701312.53905.252gray lowland soil30 : 100 : 100100010

Evaluation of agronomic traits

Flowering time was defined as the number of days from sowing to flowering of 50% of the plants in a plot. Maturity was defined as the number of days from sowing to maturation of 80% of the plants in a plot. The seed-filling period was defined as the number of days from flowering to maturity. The number of nodes on the main stem (MSN) was measured as the number of nodes from the cotyledonary node to the top node without the top peduncle for ten normally grown plants. The main stem length (MSL) was measured as the length from the cotyledonary node to the top node without the top peduncle for ten normally grown plants. Seed productivity was measured for each plot and converted to a 15% water content value. The 100-seed weight was measured twice, and the average value was used. The seed protein content was determined by a near-infrared spectrophotometer (Infratec 1241 Grain Analyzer; FOSS Tecator AB, Höganäs, Sweden) for each plot.

Data analysis

Results were analyzed by analysis of variance (ANOVA) using the statistical program SPSS Statistics 17.0 (SPSS 2008; SPSS Inc., Tokyo, Japan). The F-test using a mixed model for lines and experimental sites was performed for agronomic traits. Coefficients of correlations were calculated between seed productivity and other agronomical traits. One-way ANOVA was conducted according to Tukey’s test for seed productivity among lines and cultivars.

Results and Discussion

Development of NILs for the E2 and E3 alleles

‘Enrei’ and ‘Fukuyutaka’ showed polymorphisms at 206 of 245 SSR markers tested. BC2F1 plants were polymorphic for 12 and 51 of the 206 markers tested in the cross between ‘Enrei’ and ‘Sachiyutaka’ and between ‘Enrei’ and ‘Fukuyutaka’, respectively. Those polymorphic SSR markers were distributed over 8 and 17 linkage groups. In the BC3F1 generation, single plants were selected from 80 plants for ‘Enrei-E2’ and from 30 plants for ‘Enrei-E3’, respectively, based on the genotypes for maturity locus and SSRs (Table 1). No genomic region of the donor parent (‘Sachiyutaka’) was left in the selected BC3F1 plant for E2 for the markers tested, so BC3F2 plants homozygous for E2 were used as NIL ‘Enrei-E2’. Thirty-five of the 51 markers tested were homozygous for the allele from ‘Enrei’ in the selected BC3F1 plant for E3, which was used for further back-crossing to generate BC4F1 plants. Of 98 BC4F1 plants obtained, only one plant was homozygous at 15 of the 16 markers for the alleles from ‘Enrei’. The BC4F1 plant was used to develop BC4F2 progeny. Among them, BC4F2 plants homozygous for E3 were used as NIL ‘Enrei-E3’. The developed NILs for E2 and E3 were registered as ‘Sakukei 74 (Enrei-E2)’ and ‘Sakukei 78 (Enrei-E3)’. The NILs had the same morphological phenotypes as ‘Enrei’: determinant growth, round leaflets, purple flowers, gray pubescence, yellow hilum, yellow seed coats, and spherical seeds. As shown in Table 1, in this study, backcrossing combined with marker-assisted selection was repeated three times a year. This method could provide sufficient seeds for BC3 or BC4 lines for a primary yield test in three years and could shorten the period of the breeding program by several years. In particular, DNA marker-assisted selection had the advantages that we could identify the degree to which the genome had been restored for the recurrent parent, where a backcrossed line had residual regions from the donor parent including the target region, and when it would reach the anticipated degree of similarity to the recurrent parent.

Effects of maturity genes on flowering, maturity and seed productivity

Both NILs flowered significantly later than ‘Enrei’ in all of the experiments, as expected (Tables 4, 5, 6). Accordingly, the substitution of early-maturity by late alleles was effective in modifying the flowering time of ‘Enrei’. Similarly, the seed-filling period and maturity showed significant differences between ‘Enrei’ and ‘Enrei-E2’, although the interaction between lines and experimental sites was also significant. The E2 allele delayed the seed-filling period and maturity compared to the e2 allele, particularly in three locations, Niigata, Nagano and Mito/Ibaraki, in 2009, whereas there was no clear difference in Kagawa and late-sowing experiments in Tsukubamirai/Ibaraki (Table 4), in which maturation proceeded under a relatively shorter daylength. The effect of E3 on the seed-filling period and maturity were also not clear; the order of the seed-filling period varied with the locations tested (Table 4). The absence of an effect of E3 over e3 on the seed-filling period and maturity may be due to a shorter daylength in the environmental conditions tested. McBlain indicated that post-flowering development (R1 to R8) was slowed by E2 and E3 relative to their respective recessive alleles. The effect of E3 on maturity should thus be evaluated under a longer photoperiod condition as in Niigata and Nagano.
Table 4

Averages and standard deviations of agronomic traits of ‘Enrei’ and its NIL for maturity genes, E2 and E3

Experimental sitesLinesFlowering time (day)Seed-filling period (day)Maturity (day)MSNa (plant−1)MSLb (cm)Seed productivity (kg/a)100-seed weight (g)Protein (%)
Nagaoka, NiigataEnrei-E267.0 ± 1.482.0 ± 2.8149.0 ± 4.276.7 ± 5.631.1 ± 4.035.7 ± 2.445.9 ± 1.8
Enrei59.0 ± 0.073.5 ± 0.7132.5 ± 0.766.0 ± 3.632.3 ± 2.434.7 ± 2.544.6 ± 0.5

Shiojiri, NaganoEnrei-E262.0 ± 2.895.0 ± 2.8157.0 ± 0.017.5 ± 0.275.0 ± 4.031.5 ± 1.130.6 ± 0.146.1 ± 0.4
Enrei53.0 ± 0.078.0 ± 0.0131.0 ± 0.015.2 ± 0.266.1 ± 0.835.1 ± 2.930.1 ± 0.146.5 ± 0.1

Mito, IbarakiEnrei-E244.5 ± 0.778.0 ± 4.2122.5 ± 3.515.8 ± 0.771.1 ± 4.532.9 ± 0.628.6 ± 2.644.2 ± 1.8
Enrei39.0 ± 0.069.5 ± 0.7108.5 ± 0.712.7 ± 0.150.5 ± 4.036.6 ± 1.229.9 ± 1.843.9 ± 1.3

Tsukubamirai, Ibaraki in 2009Enrei-E245.5 ± 0.769.0 ± 0.0114.5 ± 0.716.2 ± 0.276.5 ± 3.344.0 ± 5.133.0 ± 0.646.9 ± 1.5
Enrei-E343.5 ± 0.769.0 ± 1.4112.5 ± 2.115.0 ± 0.771.7 ± 0.235.6 ± 1.731.2 ± 2.946.6 ± 1.2
Enrei39.0 ± 0.065.0 ± 2.8104.0 ± 2.812.2 ± 0.253.8 ± 0.831.5 ± 6.829.6 ± 2.846.2 ± 1.5

Zentsuji, KagawaEnrei-E244.0 ± 0.088.0 ± 0.0132.0 ± 0.014.1 ± 0.159.3 ± 0.440.9 ± 2.228.7 ± 0.644.2 ± 0.0
Enrei-E344.0 ± 0.085.5 ± 2.1129.5 ± 2.113.7 ± 0.661.6 ± 4.133.3 ± 2.829.3 ± 0.646.7 ± 0.5
Enrei38.0 ± 0.091.5 ± 2.1129.5 ± 2.112.1 ± 0.350.2 ± 3.524.6 ± 3.930.7 ± 0.347.7 ± 0.6

Tsukubamirai, Ibaraki in 2010Enrei-E239.0 ± 0.072.5 ± 4.9111.5 ± 4.913.9 ± 0.459.5 ± 6.924.8 ± 1.028.1 ± 1.944.1 ± 0.1
Enrei-E337.5 ± 0.770.0 ± 0.0107.5 ± 0.713.3 ± 0.854.2 ± 1.822.1 ± 0.827.8 ± 0.844.6 ± 0.3
Enrei33.0 ± 0.069.0 ± 0.0102.0 ± 0.011.9 ± 0.149.4 ± 0.416.3 ± 1.629.1 ± 1.045.8 ± 1.1

The number of nodes on the main stem (MSN) was measured as the number of nodes on main stem from the cotyledonary node to the top node without the top peduncle for ten normally grown plants.

Main stem length (MSL) was measured as the length from the cotyledonary node to the top node without the top peduncle for ten normally grown plants.

Table 5

Mean squares of agronomic traits of ‘Enrei’ and its NIL for maturity gene, E2

Mean squareFlowering time (day)Seed-filling period (day)Maturity (day)MSN (plant−1)MSL (cm)Seed productivity (kg/a)100-seed weight (g)Protein (%)
Line280.2 ***a240.7 **1040.2 ***36.7 ***1127.5 ***151.5 *0.11.7
Experimental site458.7 ***320.8 ***1049.6 ***7.5 ***221.4 **225.6 **22.4 *3.6
Line * Experimental site1.946.7 **62.2 ***0.7 **39.272.4 **3.93.1
Error0.96.05.80.114.110.73.01.2

F-test using mixed model.

indicate significant difference at 5%, 1% and 0.1% levels, respectively.

Table 6

Mean squares of agronomic traits of ‘Enrei’ and its NIL for maturity gene, E3

Mean squareFlowering time (day)Seed-filling period (day)Maturity (day)MSN (plant−1)MSL (cm)Seed productivity (kg/a)100-seed weight (g)Protein (%)
Line75.0 **a0.365.311.6 *387.6115.3 *0.41.0
Experimental site46.1 *553.0 *717.6 *1.0121.8213.8 *4.24.0
Line * Experimental site0.826.3 *18.60.643.2 *5.63.00.7
Error0.23.23.70.35.512.53.11.0

F-test using mixed model.

indicate significant difference at 5%, 1% and 0.1% levels, respectively.

MSN and MSL, plant size-related traits, showed higher values in NILs than ‘Enrei’ in all of the experiments, indicating that NILs produced larger plants than ‘Enrei’ (Table 4). Seed productivity also showed significant differences between ‘Enrei’ and NILs (Tables 5, 6); however, in the comparison of the E2 locus, the interaction between lines and experimental sites was significant at 1% probability; seed productivity was increased in ‘Enrei-E2’ relative to ‘Enrei’ in three experiments, Kagawa and two in Tsukubamirai/Ibaraki, whereas ‘Enrei-E2’ showed almost the same or lower seed productivity than ‘Enrei’ in three locations, Niigata, Nagano and Mito/Ibaraki (Table 4). Particularly in Kagawa and Tsukubamirai/Ibaraki in 2009, the seed productivity of ‘Enrei-E2’ was comparable to that of other high-yielding varieties, ‘Sachiyutaka’ or ‘Tamahomare’ (Fig. 2A, 2B), although later-maturing varieties, such as ‘Tamahomare’ and ‘Fukuyutaka’, showed greater productivity than ‘Enrei-E2’ under delayed sowing conditions (July, 15) of Tsukubamirai/Ibaraki in 2010 (Fig. 2C).
Fig. 2

Seed productivity of ‘Enrei’ and its NILs for maturity genes, E2 and E3 and leading varieties

The relationships between seed productivity and other agronomical traits are shown in Fig. 3 and Table 7. Generally, later maturing varieties are expected to have an advantage in seed productivity because the total amount of insolation received from the canopy is greater than for early maturing varieties; however, the correlation was not significant for any agronomical traits in all lines combined (Table 7). As mentioned above, seed productivity for ‘Enrei-E2’ and ‘Enrei’ showed opposite trends among the location/experiments tested; ‘Enrei-E2’ produced higher seed production relative to ‘Enrei’ under environmental conditions where the daylength was relatively short, whereas seed productivity was lower in ‘Enrei-E2’ than ‘Enrei’ when day-length was relatively long (Table 4). We classified the five experiments into two groups: southern environment with shorter daylength and northern environment with longer daylength, and reevaluated relationships between flowering and maturity times and seed productivity. As a result, the correlation between flowering time and seed productivity was significantly positive only in the southern environment; a similar but non-significant correlation was observed between maturity and seed productivity (Fig. 3 and Table 7). On the other hand, correlations were negative for these traits in the northern environment (Fig. 3 and Table 7).
Fig. 3

Relationship between agronomical traits and seed productivity for ‘Enrei’ and its near-isogenic lines (NILs) for maturity gene, E2 and E3. Circle, Square and triangle legends indicate ‘Enrei’, ‘Enrei-E2’ and ‘Enrei-E3’, respectively. Open and closed legends indicate southern and northern sites, respectively. MSN, number of nodes on the main stem; MSL, main stem length.

Table 7

Coefficient of correlation between seed productivity and other agronomical traits

Lines/sitesFlowering time (day)Seed-filling period (day)Maturity (day)MSN (plant−1)MSL (cm)100-seed weight (g)Protein (%)
Total0.03−0.14−0.070.130.270.290.02

Northern sites−0.44−0.72 **−0.64 *−0.73 *−0.410.20−0.55
Southern sites0.91 ***a0.130.430.70 **0.71 **0.510.26

indicate significant difference at 5%, 1% and 0.1% levels, respectively.

As indicated, some agronomic traits related to plant shape, such as MSN and MSL, of ‘Enrei-E2’ were greater than those of ‘Enrei’ (Tables 4, 5). The differences in plant shape appear to lead to differences in lodging and self-shading because severe lodging was more frequently observed for ‘Enrei-E2’ than for ‘Enrei’ in the northern environment. The adverse effect of the E2 allele on seed productivity is most likely due to severe lodging and self-shading.

Seed quality of NILs

The differences in 100-seed weights and protein contents were not significant between ‘Enrei’ and NILs (Tables 5, 6), although a significant effect of the experimental locations was detected in 100-seed weight in the comparison of the E2 locus. In addition, a significant difference was not observed in the processing suitability for tofu, which was evaluated by breaking stress and other seed quality-related traits (data not shown). These results suggest that the NILs had a similar seed quality to ‘Enrei’.

Concluding remarks

The present study revealed that modification of maturity genes in a Japanese variety ‘Enrei’ improved seed productivity to different degrees, depending on the environment evaluated. The later flowering and longer seed-filling period resulted in higher seed productivity only in relatively southern locations or under late-sowing conditions, whereas the E2 allele provided no clear or adverse effect on seed productivity in relatively northern locations. As suggested by Cober and Morisson (2010), there may be flowering and maturing habits that are most suitable for each environment. Furthermore, the earlier maturation of ‘Enrei’ might be rather advantageous for rotation cropping in non-snow-covered areas, such as Nagano and Mito/Ibaraki, and for escaping the risk of being covered with snow during harvesting in Niigata; thus, different genotypic combinations at maturity loci may be preferred in each location. In order to identify the most adaptive genotype in each region, it is very important to develop NILs for various maturity genotypes and to evaluate their seed productivity in diverse environments. In addition to E2 and E3 loci, DNA markers tagging E1 (Yamanaka ) and E4 (Liu ) are available to modify genotypes at these loci. Furthermore, such NILs would be useful to supply the same lot of seeds on a larger scale by cultivating more adaptive NILs in each region, if seed quality such as for tofu processing is retained at the same level as the original, as suggested in our present study. Further studies are required for our better understanding of the effects of alternating the maturity genotype on all types of agronomic traits.
  11 in total

1.  An informative linkage map of soybean reveals QTLs for flowering time, leaflet morphology and regions of segregation distortion.

Authors:  N Yamanaka; S Ninomiya; M Hoshi; Y Tsubokura; M Yano; Y Nagamura; T Sasaki; K Harada
Journal:  DNA Res       Date:  2001-04-27       Impact factor: 4.458

2.  AFLP mapping of soybean maturity gene E4.

Authors:  Hisakazu Matsumura; Baohui Liu; Jun Abe; Ryoji Takahashi
Journal:  J Hered       Date:  2008-02-21       Impact factor: 2.645

3.  Fine mapping of the FT1 locus for soybean flowering time using a residual heterozygous line derived from a recombinant inbred line.

Authors:  Naoki Yamanaka; Satoshi Watanabe; Kyoko Toda; Masaki Hayashi; Hiroki Fuchigami; Ryoji Takahashi; Kyuya Harada
Journal:  Theor Appl Genet       Date:  2005-01-19       Impact factor: 5.699

4.  Regulation of seed yield and agronomic characters by photoperiod sensitivity and growth habit genes in soybean.

Authors:  Elroy R Cober; Malcolm J Morrison
Journal:  Theor Appl Genet       Date:  2009-12-13       Impact factor: 5.699

5.  Genetic redundancy in soybean photoresponses associated with duplication of the phytochrome A gene.

Authors:  Baohui Liu; Akira Kanazawa; Hisakazu Matsumura; Ryoji Takahashi; Kyuya Harada; Jun Abe
Journal:  Genetics       Date:  2008-09-09       Impact factor: 4.562

6.  Map-based cloning of the gene associated with the soybean maturity locus E3.

Authors:  Satoshi Watanabe; Rumiko Hideshima; Zhengjun Xia; Yasutaka Tsubokura; Shusei Sato; Yumi Nakamoto; Naoki Yamanaka; Ryoji Takahashi; Masao Ishimoto; Toyoaki Anai; Satoshi Tabata; Kyuya Harada
Journal:  Genetics       Date:  2009-05-27       Impact factor: 4.562

7.  Genome sequence of the palaeopolyploid soybean.

Authors:  Jeremy Schmutz; Steven B Cannon; Jessica Schlueter; Jianxin Ma; Therese Mitros; William Nelson; David L Hyten; Qijian Song; Jay J Thelen; Jianlin Cheng; Dong Xu; Uffe Hellsten; Gregory D May; Yeisoo Yu; Tetsuya Sakurai; Taishi Umezawa; Madan K Bhattacharyya; Devinder Sandhu; Babu Valliyodan; Erika Lindquist; Myron Peto; David Grant; Shengqiang Shu; David Goodstein; Kerrie Barry; Montona Futrell-Griggs; Brian Abernathy; Jianchang Du; Zhixi Tian; Liucun Zhu; Navdeep Gill; Trupti Joshi; Marc Libault; Anand Sethuraman; Xue-Cheng Zhang; Kazuo Shinozaki; Henry T Nguyen; Rod A Wing; Perry Cregan; James Specht; Jane Grimwood; Dan Rokhsar; Gary Stacey; Randy C Shoemaker; Scott A Jackson
Journal:  Nature       Date:  2010-01-14       Impact factor: 49.962

8.  Development and application of a whole-genome simple sequence repeat panel for high-throughput genotyping in soybean.

Authors:  Takashi Sayama; Tae-Young Hwang; Kunihiko Komatsu; Yoshitake Takada; Masakazu Takahashi; Shin Kato; Hiroko Sasama; Ayako Higashi; Yumi Nakamoto; Hideyuki Funatsuki; Masao Ishimoto
Journal:  DNA Res       Date:  2011-03-30       Impact factor: 4.458

9.  A map-based cloning strategy employing a residual heterozygous line reveals that the GIGANTEA gene is involved in soybean maturity and flowering.

Authors:  Satoshi Watanabe; Zhengjun Xia; Rumiko Hideshima; Yasutaka Tsubokura; Shusei Sato; Naoki Yamanaka; Ryoji Takahashi; Toyoaki Anai; Satoshi Tabata; Keisuke Kitamura; Kyuya Harada
Journal:  Genetics       Date:  2011-03-15       Impact factor: 4.562

10.  Genetic and molecular bases of photoperiod responses of flowering in soybean.

Authors:  Satoshi Watanabe; Kyuya Harada; Jun Abe
Journal:  Breed Sci       Date:  2012-02-04       Impact factor: 2.086

View more
  6 in total

1.  Natural variation in the genes responsible for maturity loci E1, E2, E3 and E4 in soybean.

Authors:  Yasutaka Tsubokura; Satoshi Watanabe; Zhengjun Xia; Hiroyuki Kanamori; Harumi Yamagata; Akito Kaga; Yuichi Katayose; Jun Abe; Masao Ishimoto; Kyuya Harada
Journal:  Ann Bot       Date:  2013-11-26       Impact factor: 4.357

2.  Seed yield and its components of indeterminate and determinate lines in recombinant inbred lines of soybean.

Authors:  Shin Kato; Kenichiro Fujii; Setsuzo Yumoto; Masao Ishimoto; Tatsuhiko Shiraiwa; Takashi Sayama; Akio Kikuchi; Takeshi Nishio
Journal:  Breed Sci       Date:  2015-03-01       Impact factor: 2.086

Review 3.  Recent achievement in gene cloning and functional genomics in soybean.

Authors:  Zhengjun Xia; Hong Zhai; Shixiang Lü; Hongyan Wu; Yupeng Zhang
Journal:  ScientificWorldJournal       Date:  2013-11-07

4.  Transfer of the Rsv3 locus from 'Harosoy' for resistance to soybean mosaic virus strains C and D in Japan.

Authors:  Shin Kato; Yoshitake Takada; Satoshi Shimamura; Kaori Hirata; Takashi Sayama; Fumio Taguchi-Shiobara; Masao Ishimoto; Akio Kikuchi; Takeshi Nishio
Journal:  Breed Sci       Date:  2016-03-01       Impact factor: 2.086

5.  Identification of quantitative trait loci associated with boiled seed hardness in soybean.

Authors:  Kaori Hirata; Ryoichi Masuda; Yasutaka Tsubokura; Takeshi Yasui; Tetsuya Yamada; Koji Takahashi; Taiko Nagaya; Takashi Sayama; Masao Ishimoto; Makita Hajika
Journal:  Breed Sci       Date:  2014-12-01       Impact factor: 2.086

6.  The effect of stem growth habit on single seed weight and seed uniformity in soybean (Glycine max (L.) Merrill).

Authors:  Shin Kato; Takashi Sayama; Masao Ishimoto; Setsuzo Yumoto; Akio Kikuchi; Takeshi Nishio
Journal:  Breed Sci       Date:  2018-06-29       Impact factor: 2.086

  6 in total

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