A haplotype inference algorithm for trios based on deterministic sampling

Background

The three-dimensional shape of grain, measured as grain length, width, and thickness (GL, GW, and GT), is one of the most important components of grain appearance in rice. Determining the genetic basis of variations in grain shape could facilitate efficient improvements in grain appearance. In this study, an F_7:8 recombinant inbred line population (RIL) derived from a cross between indica and japonica cultivars (Nanyangzhan and Chuan7) contrasting in grain size was used for quantitative trait locus (QTL) mapping. A genetic linkage map was constructed with 164 simple sequence repeat (SSR) markers. The major aim of this study was to detect a QTL for grain shape and to fine map a minor QTL, qGL7.

Results

Four QTLs for GL were detected on chromosomes 3 and 7, and 10 QTLs for GW and 9 QTLs for GT were identified on chromosomes 2, 3, 5, 7, 9 and 10, respectively. A total of 28 QTLs were identified, of which several are reported for the first time; four major QTLs and six minor QTLs for grain shape were also commonly detected in both years. The minor QTL, qGL7, exhibited pleiotropic effects on GL, GW, GT, 1000-grain weight (TGW), and spikelets per panicle (SPP) and was further validated in a near isogenic F₂ population (NIL-F₂). Finally, qGL7 was narrowed down to an interval between InDel marker RID711 and SSR marker RM6389, covering a 258-kb region in the Nipponbare genome, and cosegregated with InDel markers RID710 and RID76.

Conclusion

Materials with very different phenotypes were used to develop mapping populations to detect QTLs because of their complex genetic background. Progeny tests proved that the minor QTL, qGL7, could display a single mendelian characteristic. Therefore, we suggested that minor QTLs for traits with high heritability could be isolated using a map-based cloning strategy in a large NIL-F₂ population. In addition, combinations of different QTLs produced diverse grain shapes, which provide the ability to breed more varieties of rice to satisfy consumer preferences.     

Identification of quantitative trait loci for grain size and the contributions of major grain-size QTLs to grain weight in rice

Grain weight, one of the three major components of rice yield, is largely determined by grain size, which is controlled by quantitative trait loci (QTLs). In a previous study, we identified qGS5 as a major QTL for grain width. Here, we report our identification of two more major grain-size QTLs (qGL3 and qGW2a) by using a recombinant inbred line (RIL) population from a cross of two indica varieties, ‘Zhenshan 97’ and ‘SLG’. To investigate the contribution of the three grain-size QTLs to final grain weight, we developed near-isogenic lines (NILs) NIL-qGL3, NIL-qGW2a, and NIL-qGS5 and used these to build the combined QTLs–NIL in the genetic background of ‘Zhenshan 97’ by marker-assisted selection and conventional backcrossing, respectively. A BCF₂ population of 957 individuals was developed from the combined QTLs-NIL for further study of the genetic control of grain size. The QTL analysis revealed that qGW2a and qGL3 played more important roles in grain weight gain than qGS5. All three QTLs showed additive effects with respect to grain weight, with no interaction. These results clearly indicate that pyramiding of major grain-size QTLs is a useful approach for improving rice yield.     

QTL mapping of grain weight in rice and the validation of the QTL qTGW3.2

A recombinant inbred line (RIL) population bred from a cross between a javanica type (cv. D50) and an indica type (cv. HB277) rice was used to map seven quantitative trait loci (QTLs) for thousand grain weight (TGW). The loci were distributed on chromosomes 2, 3, 5, 6, 8 and 10. The chromosome 3 QTL qTGW3.2 was stably expressed over two years, and contributed 9–10% of the phenotypic variance. A residual heterozygous line (RHL) was selected from the RIL population and its selfed progeny was used to fine map qTGW3.2. In this “F₂” population, the QTL explained about 23% of the variance, rising to nearly 33% in the subsequent “F_2:3” generation. The physical location of qTGW3.2 was confined to a ~ 556 kb region flanked by the microsatellite loci RM16162 and RM16194. The region also contains other factors influencing certain yield-related traits, although it is also possible that qTGW3.2 affects these in a pleiotropic fashion.     

Multi-Environmental Genetic Analysis of Grain Size Traits Based on Chromosome Segment Substitution Line in Rice (<i>Oryza sativa</i> L.)

Grain size traits are critical agronomic traits which directly determine grain yield, but the genetic bases of these traits are still not well understood. In this study, a total of 154 chromosome segment substitution lines (CSSLs) population derived from a cross between a japonica variety Koshihikari and an indica variety Nona Bokra was used to investigate grain length (GL), grain width (GW), length-width ratio (LWR), grain perimeter (GP), grain area (GA), and thousand grain weight (TGW) under four environments. QTL mapping analysis of six grain size traits was performed by QTL IciMapping 4.2 with an inclusive composite interval mapping (ICIM) model. A total of 64 QTLs were identified for these traits, which mapped to chromosomes 1, 2, 3, 4, 6, 7, 8, 10, 11, and 12 and accounted for 1.6%–27.1% of the total phenotypic variations. Among these QTLs, thirty-six loci were novel and seven QTLs were identified under four environments. One locus containing the known grain size gene, qGL3/GL3.1/OsPPKL1, also have been found. Moreover, five pairs of digenic epistatic interactions were identified except for GL and GP. These findings will facilitate fine mapping of the candidate gene and QTL pyramiding to genetically improve grain yield in rice.     

Mapping and validation of quantitative trait loci for spikelets per panicle and 1,000-grain weight in rice (Oryza sativa L.)

This study identified four and five quantitative trait loci (QTLs) for 1,000-grain weight (TGW) and spikelets per panicle (SPP), respectively, using rice recombinant inbred lines. QTLs for the two traits (SPP3a and TGW3a, TGW3b and SPP3b) were simultaneously identified in the two intervals between RM3400 and RM3646 and RM3436 and RM5995 on chromosome 3. To validate QTLs in the interval between RM3436 and RM5995, a BC₃F₂ population was obtained, in which TGW3b and SPP3b were simultaneously mapped to a 2.6-cM interval between RM15885 and W3D16. TGW3b explained 50.4% of the phenotypic variance with an additive effect of 1.81 g. SPP3b explained 29.1% of the phenotypic variance with an additive effect of 11.89 spikelets. The interval had no effect on grain yield because it increased SPP but decreased TGW and vice versa. Grain shape was strongly associated with TGW and was used for QTL analysis in the BC₃F₂ population. Grain length, grain width, and grain thickness were also largely controlled by TGW3b. At present, it is not clear whether one pleiotropic QTL or two linked QTLs were located in the interval. However, the conclusion could be made ultimately by isolation of TGW3b. The strategy for TGW3b isolation is discussed.     

High-Density Genetic Linkage Map Construction and QTL Mapping of Grain Shape and Size in the Wheat Population Yanda1817 × Beinong6

High-density genetic linkage maps are necessary for precisely mapping quantitative trait loci (QTLs) controlling grain shape and size in wheat. By applying the Infinium iSelect 9K SNP assay, we have constructed a high-density genetic linkage map with 269 F ₈ recombinant inbred lines (RILs) developed between a Chinese cornerstone wheat breeding parental line Yanda1817 and a high-yielding line Beinong6. The map contains 2431 SNPs and 128 SSR & EST-SSR markers in a total coverage of 3213.2 cM with an average interval of 1.26 cM per marker. Eighty-eight QTLs for thousand-grain weight (TGW), grain length (GL), grain width (GW) and grain thickness (GT) were detected in nine ecological environments (Beijing, Shijiazhuang and Kaifeng) during five years between 2010–2014 by inclusive composite interval mapping (ICIM) (LOD≥2.5). Among which, 17 QTLs for TGW were mapped on chromosomes 1A, 1B, 2A, 2B, 3A, 3B, 3D, 4A, 4D, 5A, 5B and 6B with phenotypic variations ranging from 2.62% to 12.08%. Four stable QTLs for TGW could be detected in five and seven environments, respectively. Thirty-two QTLs for GL were mapped on chromosomes 1B, 1D, 2A, 2B, 2D, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6B, 7A and 7B, with phenotypic variations ranging from 2.62% to 44.39%. QGl.cau-2A.2 can be detected in all the environments with the largest phenotypic variations, indicating that it is a major and stable QTL. For GW, 12 QTLs were identified with phenotypic variations range from 3.69% to 12.30%. We found 27 QTLs for GT with phenotypic variations ranged from 2.55% to 36.42%. In particular, QTL QGt.cau-5A.1 with phenotypic variations of 6.82–23.59% was detected in all the nine environments. Moreover, pleiotropic effects were detected for several QTL loci responsible for grain shape and size that could serve as target regions for fine mapping and marker assisted selection in wheat breeding programs.     

Genome-Wide Association Study of Grain Appearance and Milling Quality in a Worldwide Collection of Indica Rice Germplasm

Grain appearance quality and milling quality are the main determinants of market value of rice. Breeding for improved grain quality is a major objective of rice breeding worldwide. Identification of genes/QTL controlling quality traits is the prerequisite for increasing breeding efficiency through marker-assisted selection. Here, we reported a genome-wide association study in indica rice to identify QTL associated with 10 appearance and milling quality related traits, including grain length, grain width, grain length to width ratio, grain thickness, thousand grain weight, degree of endosperm chalkiness, percentage of grains with chalkiness, brown rice rate, milled rice rate and head milled rice rate. A diversity panel consisting of 272 indica accessions collected worldwide was evaluated in four locations including Hangzhou, Jingzhou, Sanya and Shenzhen representing indica rice production environments in China and genotyped using genotyping-by-sequencing and Diversity Arrays Technology based on next-generation sequencing technique called DArTseq™. A wide range of variation was observed for all traits in all environments. A total of 16 different association analysis models were compared to determine the best model for each trait-environment combination. Association mapping based on 18,824 high quality markers yielded 38 QTL for the 10 traits. Five of the detected QTL corresponded to known genes or fine mapped QTL. Among the 33 novel QTL identified, qDEC1.1 (qGLWR1.1), qBRR2.2 (qGL2.1), qTGW2.1 (qGL2.2), qGW11.1 (qMRR11.1) and qGL7.1 affected multiple traits with relatively large effects and/or were detected in multiple environments. The research provided an insight of the genetic architecture of rice grain quality and important information for mining genes/QTL with large effects within indica accessions for rice breeding.     

Genetic dissection of large grain shape in rice cultivar ‘Nanyangzhan’ and validation of a grain thickness QTL (<Emphasis Type="Italic">qGT3.1</Emphasis>) and a grain length QTL (<Emphasis Type="Italic">qGL3.4</Emphasis>)

Grain shape is an important agronomic trait in rice, which influences the yield and quality. In order to dissect the genetic basis of the large grain shape in ‘Nanyangzhan’, a recombinant inbred line (RIL) population derived from Nanyangzhan (NYZ) and Zhenshan 97B (ZS97) was used to map quantitative trait loci (QTLs) for grain length (GL), width (GW), thickness (GT), length-to-width ratio (LWR) and kilo-grain weight (KGW). A total of 53 QTLs were detected and distributed on 11 chromosomes in 2 years. Among those, QTLs for GW and GL showed a concentrated distribution on chromosome 2 and chromosome 3, respectively. NYZ, the parent with large grain shape, carried 44 alleles showing positive effects on the studied traits. In addition, the near-isogenic lines (NILs) of two novel QTLs, qGT3.1 and qGL3.4, were constructed with the background of ZS97. Results showed that NIL-qGT3.1 ^NYZ , the NIL carrying homozygous qGT3.1 regions from NYZ, showed an increased value of 0.12 mm in grain thickness on average as compared to NIL-qGT3.1 ^ZS . Similarly, NIL-qGL3.4 ^NYZ increased the length of each grain by 0.47 mm on average as compared to NIL-qGL3.4 ^ZS . Taken together, these results would be of great use in breeding rice cultivars with desirable grain shape.     

Wild-type alleles of Rht-B1 and Rht-D1 as independent determinants of thousand-grain weight and kernel number per spike in wheat

The utilization of dwarfing genes Rht-B1b and Rht-D1b in wheat significantly increased grain yield and contributed to the “green revolution”. However, the benefit of Rht-B1b and Rht-D1b in drought environments has been debated. Although quantitative trait loci (QTL) for kernel number per spike (KN) and thousand-grain weight (TGW) have been found to be associated with Rht-B1 and Rht-D1, the confounding effect of environmental variation has made a direct association difficult to find. In this study, we used a doubled haploid population (225 lines) of Westonia × Kauz, in which both Rht-B1b (Kauz) and Rht-D1b (Westonia) segregated. The purpose of the study was to determine the interaction of Rht-B1 and Rht-D1 with grain yield components, namely KN and TGW, and to investigate genotype-by-environment interactions in glasshouse and field trials conducted in 2010 and 2011 in Western Australia. A genetic map of 1,156 loci was constructed using 195 microsatellite markers, two gene-based markers for Rht-B1 and Rht-D1, and 959 single nucleotide polymorphisms. The major QTL for TGW and KN were strongly linked to Rht-B1 and Rht-D1 loci and the positive effects were associated with the wild-type alleles, Rht-B1a and Rht-D1a. The major QTL of TGW were on chromosome 2D and 4B. The significant genetic effects (14.6–22.9 %) of TGW indicated that marker-assisted selection for TGW is possible, and markers gwm192a (206 bp) or gwm192b (236 bp) can be used as indicators of high TGW. For KN, one major QTL was detected on chromosome 4D in the analysis across three environments. The association of the wild-type alleles Rht-B1a and Rht-D1a in drought environments is discussed.     

Genetic insight into yield-associated traits of wheat grown in multiple rain-fed environments

Background

Grain yield is a key economic driver of successful wheat production. Due to its complex nature, little is known regarding its genetic control. The goal of this study was to identify important quantitative trait loci (QTL) directly and indirectly affecting grain yield using doubled haploid lines derived from a cross between Hanxuan 10 and Lumai 14.

Methodology/Principal Findings

Ten yield-associated traits, including yield per plant (YP), number of spikes per plant (NSP), number of grains per spike (NGS), one-thousand grain weight (TGW), total number of spikelets per spike (TNSS), number of sterile spikelets per spike (NSSS), proportion of fertile spikelets per spike (PFSS), spike length (SL), density of spikelets per spike (DSS) and plant height (PH), were assessed across 14 (for YP) to 23 (for TGW) year × location × water regime environments in China. Then, the genetic effects were partitioned into additive main effects (a), epistatic main effects (aa) and their environment interaction effects (ae and aae) by using composite interval mapping in a mixed linear model.

Conclusions/Significance

Twelve (YP) to 33 (PH) QTLs were identified on all 21 chromosomes except 6D. QTLs were more frequently observed on chromosomes 1B, 2B, 2D, 5A and 6B, and were concentrated in a few regions on individual chromosomes, exemplified by three striking yield-related QTL clusters on chromosomes 2B, 1B and 4B that explained the correlations between YP and other traits. The additive main-effect QTLs contributed more phenotypic variation than the epistasis and environmental interaction. Consistent with agronomic analyses, a group of progeny derived by selecting TGW and NGS, with higher grain yield, had an increased frequency of QTL for high YP, NGS, TGW, TNSS, PFSS, SL, PH and fewer NSSS, when compared to low yielding progeny. This indicated that it is feasible by marker-assisted selection to facilitate wheat production.     

A novel allele of <Emphasis Type="Italic">TaGW2</Emphasis>-<Emphasis Type="Italic">A1</Emphasis> is located in a finely mapped QTL that increases grain weight but decreases grain number in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Key message

A novel TaGW2-A1 allele was identified from a stable, robust QTL region, which is pleiotropic for thousand grain weight, grain number per spike, and grain morphometric parameters in wheat.

Abstract

Thousand grain weight (TGW) and grain number per spike (GNS) are two crucial determinants of wheat spike yield, and genetic dissection of their relationships can help to fine-tune these two components and maximize grain yield. By evaluating 191 recombinant inbred lines in 11 field trials, we identified five genomic regions on chromosomes 1B, 3A, 3B, 5B, or 7A that solely influenced either TGW or GNS, and a further region on chromosome 6A that concurrently affected TGW and GNS. The QTL of interest on chromosome 6A, which was flanked by wsnp_BE490604A_Ta_2_1 and wsnp_RFL_Contig1340_448996 and designated as QTgw/Gns.cau-6A, was finely mapped to a genetic interval shorter than 0.538 cM using near isogenic lines (NILs). The elite NILs of QTgw/Gns.cau-6A increased TGW by 8.33%, but decreased GNS by 3.05% in six field trials. Grain Weight 2 (TaGW2-A1), a well-characterized gene that negatively regulates TGW and grain width in wheat, was located within the finely mapped interval of QTgw/Gns.cau-6A. A novel and rare TaGW2-A1 allele with a 114-bp deletion in the 5′ flanking region was identified in the parent with higher TGW, and it reduced TaGW2-A1 promoter activity and expression. In conclusion, these results expand our knowledge of the genetic and molecular basis of TGW-GNS trade-offs in wheat. The QTLs and the novel TaGW2-A1 allele are likely useful for the development of cultivars with higher TGW and/or higher GNS.

     

Validation of QTL for grain weight using MAS-derived pairs of NILs in bread wheat (Triticum aestivum L.)

Near isogenic lines (NILs) are ideal material for a variety of genetic studies including validation of specific QTL. In the present study, eight pairs of NILs for grain weight were developed, seven in the background of Raj3765, and one in the background of K9107. For this purpose, marker-assisted selection (MAS) was used for the transfer of three grain weight QTL (QGw.ccsu-1A.2, QGw.ccsu-1A.3 and QGw.ccsu-1B.1) that were earlier identified in our laboratory. Two genotypes of each of the eight pairs of NILs, differed for QTL alleles (QTL_Hgw derived from the donor parent and the QTL_Lgw derived from the recipient parent). Each pair of NILs involved a solitary QTL except one NIL, which differed for all the three QTL. The difference in thousand grain weight (TGW) in two NILs of an individual pair ranged from 2.8 to 7.5 g, thus validating the effect of the QTL for TGW, although the quantum of difference did not always match the phenotypic variance of the corresponding QTL. As expected, the NILs which involved all the three QTL had the maximum difference of 7.5 g in TGW, and the NILs which involved QTL, QGw.ccsu-1A.2 had minimum average difference of 2.8 g for TGW. The NILs produced during the present study may be used in future for MAS and for fine mapping of TGW QTL.

     

Gene editing and mutagenesis reveal inter-cultivar differences and additivity in the contribution of <Emphasis Type="Italic">TaGW2</Emphasis> homoeologues to grain size and weight in wheat

Key message

CRISPR-Cas9-based genome editing and EMS mutagenesis revealed inter-cultivar differences and additivity in the contribution of TaGW2 homoeologues to grain size and weight in wheat.

Abstract

The TaGW2 gene homoeologues have been reported to be negative regulators of grain size (GS) and thousand grain weight (TGW) in wheat. However, the contribution of each homoeologue to trait variation among different wheat cultivars is not well documented. We used the CRISPR-Cas9 system and TILLING to mutagenize each homoeologous gene copy in cultivars Bobwhite and Paragon, respectively. Plants carrying single-copy nonsense mutations in different genomes showed different levels of GS/TGW increase, with TGW increasing by an average of 5.5% (edited lines) and 5.3% (TILLING mutants). In any combination, the double homoeologue mutants showed higher phenotypic effects than the respective single-genome mutants. The double mutants had on average 12.1% (edited) and 10.5% (TILLING) higher TGW with respect to wild-type lines. The highest increase in GS and TGW was shown for triple mutants of both cultivars, with increases in 16.3% (edited) and 20.7% (TILLING) in TGW. The additive effects of the TaGW2 homoeologues were also demonstrated by the negative correlation between the functional gene copy number and GS/TGW in Bobwhite mutants and an F₂ population. The highest single-genome increases in GS and TGW in Paragon and Bobwhite were obtained by mutations in the B and D genomes, respectively. These inter-cultivar differences in the phenotypic effects between the TaGW2 gene homoeologues coincide with inter-cultivar differences in the homoeologue expression levels. These results indicate that GS/TGW variation in wheat can be modulated by the dosage of homoeologous genes with inter-cultivar differences in the magnitude of the individual homoeologue effects.

     

Fine mapping of grain weight QTL, tgw11 using near isogenic lines from a cross between Oryza sativa and O. grandiglumis

In our previous study, we reported the grain weight (GW) QTL, tgw11 in isogenic lines derived from a cross between Oryza sativa ssp. Japonica cv. Hwaseong and O. grandiglumis. The O. grandiglumis allele at tgw11 decreased GW in the Hwaseong background. To fine-map tgw11, one F₅ plant homozygous for the O. grandiglumis DNA in the target region on chromosome 11 was selected from F₄ line, CR1242 segregating for tgw11 and crossed with Hwaseong to produce secondary F₂ and F₃ populations. QTL analysis using 760 F₂ plants confirmed the existence of tgw11 with an R² value of 15.0%. This QTL explained 32.2% of the phenotypic variance for GW in 91 F₃ lines. Substitution mapping with 65 F₃ lines with informative recombination breakpoints in the target region was carried out to narrow down the position of the tgw11. The result indicated that tgw11 was located in the 900-kb interval between two SSR markers, RM224 and RM27358. QTLs for grain width and grain thickness were also located in the same interval suggesting that a single gene is involved in controlling these three traits. Analysis of F₃ lines indicated that the variation in TGW is associated with variation in grain shape, specifically grain thickness and grain width. Genetic analysis indicated that the O. grandiglumis allele for small seed was dominant over the Hwaseong allele. SSR markers tightly linked to the GW QTL would be useful in marker-assisted selection for variation in GW in breeding program.     

TaGS-D1, an ortholog of rice OsGS3, is associated with grain weight and grain length in common wheat

The OsGS3 gene plays a principal role in controlling grain weight and grain length in rice. However, the function of an orthologous gene TaGS in wheat has not been analyzed to date. In the present study, we cloned the gDNA of TaGS gene, designated TaGS-D1, with four exons and three introns on chromosome 7DS by a comparative genomics approach. The cDNA of TaGS-D1 is 255 bp, and it encodes 85 amino acids. We also found a plant-specific organ size regulation domain in the deduced polypeptide, indicating that TaGS-D1, like OsGS3, does not belong to the PEBP family. DNA sequencing of the TaGS-D1 locus revealed no diversity in the coding sequence of exons, but there was a single nucleotide polymorphism (SNP) in the first intron, and 30 SNPs, a 40-bp InDel and a 3-bp InDel were found in the second intron between genotypes with higher and lower thousand grain weights (TGW). Based on the 40-bp InDel, a co-dominant STS marker, designated GS7D, was developed to discriminate the two alleles. GS7D was 8.0 cM from Xbarc184 located on chromosome 7DS by linkage mapping. A QTL for TGW and grain length at GS7D locus explained up to 16.3 and 7.7 %, respectively, of the phenotypic variances in a RIL population derived from Doumai/Shi 4185 grown in Shijiazhuang and Beijing. One hundred and seventy-five Chinese wheat cultivars were genotyped with GS7D, indicating that TaGS-D1 was significantly associated with grain weight. The allelic distribution at the TaGS-D1 locus showed that the frequencies of TaGS-D1a were high in cultivars from Serbia, Japan, Australia, Canada, and the Northeastern Spring Wheat and Northern Winter Wheat Regions of China.     

Association Analysis of Genomic Loci Important for Grain Weight Control in Elite Common Wheat Varieties Cultivated with Variable Water and Fertiliser Supply

Grain weight, an essential yield component, is under strong genetic control and markedly influenced by the environment. Here, by genome-wide association analysis with a panel of 94 elite common wheat varieties, 37 loci were found significantly associated with thousand-grain weight (TGW) in one or more environments differing in water and fertiliser levels. Five loci were stably associated with TGW under all 12 environments examined. Their elite alleles had positive effects on TGW. Four, two, three, and two loci were consistently associated with TGW in the irrigated and fertilised (IF), rainfed (RF), reduced nitrogen (RN), and reduced phosphorus (RP) environments. The elite alleles of the IF-specific loci enhanced TGW under well-resourced conditions, whereas those of the RF-, RN-, or RP-specific loci conferred tolerance to the TGW decrease when irrigation, nitrogen, or phosphorus were reduced. Moreover, the elite alleles of the environment-independent and -specific loci often acted additively to enhance TGW. Four additional loci were found associated with TGW in specific locations, one of which was shown to contribute to the TGW difference between two experimental sites. Further analysis of 14 associated loci revealed that nine affected both grain length and width, whereas the remaining loci influenced either grain length or width, indicating that these loci control grain weight by regulating kernel size. Finally, the elite allele of Xpsp3152 frequently co-segregated with the larger grain haplotype of TaGW2-6A, suggesting probable genetic and functional linkages between Xpsp3152 and GW2 that are important for grain weight control in cereal plants. Our study provides new knowledge on TGW control in elite common wheat lines, which may aid the improvement of wheat grain weight trait in further research.     

Genomic regions for yield and yield parameters in Chinese winter wheat (Triticum aestivum L.) genotypes tested under varying environments correspond to QTL in widely different wheat materials

Field trials with a population of 108 doubled haploid (DH) lines of bread wheat (Triticum aestivum L.) derived from a cross between the Chinese winter wheat cultivars CA9613 and H1488 were carried out at Beijing (China) in 2000/2001 and 2001/2002. In addition, a field trial and a pot experiment were carried out at the experimental field stations of Giessen University (Germany) in the vegetation periods 2004/2005 and 2006/2007. Phenotypic data for major agronomic yield-related traits, i.e. grain weight per ear (GWE), grain number per ear (GNE), plant height and thousand-grain weight (TGW), were recorded in all experiments. In addition, biomass weight per tiller and ear weight were evaluated in the two field trials at Beijing. Based on the phenotypic data and a genetic map comprising 168 SSR markers, an analysis of quantitative trait loci (QTL) was carried out for yield and yield parameters using the composite interval mapping (CIM) approach. A total of 30 QTL were detected for these traits across four environments. Five of these QTL located on chromosomes 1A, 1B, 2B, 2D and 7D exhibited pleiotropic effects. Such pleiotropic gene loci will be very useful for understanding the homologous/homeologous relationships among QTL and designing an appropriate marker-assisted breeding programme including multi-trait selection in order to accumulate (“pyramide”) favorable alleles at different genetic loci.     

A Kelch Motif-Containing Serine/Threonine Protein Phosphatase Determines the Large Grain QTL Trait in Rice

A thorough understanding of the genetic basis of rice grain traits is critical for the improvement of rice (Oryza sativa L.) varieties. In this study, we generated an F₂ population by crossing the large‐grain japonica cultivar CW23 with Peiai 64 (PA64), an elite indica small‐grain cultivar. Using QTL analysis, 17 QTLs for five grain traits were detected on four different chromosomes. Eight of the QTLs were newly‐identified in this study. In particular, qGL3‐1, a newly‐identified grain length QTL with the highest LOD value and largest phenotypic variation, was fine‐mapped to the 17 kb region of chromosome 3. A serine/threonine protein phosphatase gene encoding a repeat domain containing two Kelch motifs was identified as the unique candidate gene corresponding to this QTL. A comparison of PA64 and CW23 sequences revealed a single nucleotide substitution (C→A) at position 1092 in exon 10, resulting in replacement of Asp (D) in PA64 with Glu (E) in CW23 for the 364^th amino acid. This variation is located at the D position of the conserved sequence motif AVLDT of the Kelch repeat. Genetic analysis of a near‐isogenic line (NIL) for qGL3‐1 revealed that the allele qGL3‐1 from CW23 has an additive or partly dominant effect, and is suitable for use in molecular marker‐assisted selection.     

Mapping and analysis of quantitative trait loci for grain oil content and agronomic traits using AFLP and SSR in sunflower ( Helianthus annuus L.)

Crosses were made between two inbred lines of sunflower. Parents and 118 F(3) families were planted in the field in a randomized complete block design in two replications. Genetic control for some agronomical traits: grain weight by plant (GWP), 1,000-grain weight (TGW), percentage of oil in grain (POG) and sowing to flowering date (STF) was investigated in F(3) families and their parents. Genetic variability was observed among the 118 F(3) families for all the traits studied. Genetic gain was obtained when the best F(3) family, or the mean of 10% of the selected families was compared with the best parent for GWP, TWG and POG. Heritability was 0.23 for GWP, 0.55 for TGW, 0.57 for POG and 0.32 for STF. A set of 244 F(3) families from the same cross, including the above 118 mentioned families and their two parents, were screened with 276 AFLP and microsatellite markers and a linkage map was constructed based on 170 markers. Two putative QTLs for the GWP trait ( gmp), one QTL for TGW ( tgw), six QTLs for POG ( pog) and two for STF ( stf) were detected. The percentage of phenotypic variance explained by each QTL ranged from 2.6% to 70.9%. The percentage of total phenotypic variance explained was 50.7% for GWP, 5.4% for TGW, 90.4% for POG and 89.3% for STF. Although these regions need to be more-precisely mapped, the information obtained should help in marker-assisted selection.     

Mapping QTLs controlling grain yield and its components on chromosome 5A of wheat

Chromosome 5A of wheat is known to carry a number of genes affecting adaptability and productivity. To localize quantitative trait loci (QTLs) controlling grain yield and its components, an RFLP map was constructed from 118 single-chromosome recombinant lines derived from the F₁ between Chinese Spring (Cappelle-Desprez 5A) and Chinese Spring (Triticum spelta 5A). The map was combined with the field-trial data scored over 3 years. A total of five regions in chromosome 5A contributed effects on yield traits. Increases in grain yield, 50-grain weight and spikelet number/ear were determined by complementary QTL alleles from both parents. The effects associated with the vernalization requirement gene Vrn-A1 or a closely linked QTL were significant only in the favorable growing season where the later-flowering vrn-A1 allele from Cappelle-Desprez 5A produced a higher tiller number/plant and spikelet number/ear. The effects of the ear morphology gene q or closely linked QTL(s) were detected for grain yield and ear grain weight. Three other QTLs with minor effects were dispersed along chromosome 5A. These QTLs had large interactions with years due to changes in the magnitude of the significant response. The alleles from T. spelta, however, conferred a higher yield performance. Received: 18 August 1999 / Accepted: 25 March 2000