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.     

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.     

Dissecting the Genetic Basis of Extremely Large Grain Shape in Rice Cultivar ＇JZ1560＇

Rice grain shape,grain length(GL),width(GW),thickness(GT)and length-to-width ratio(LWR),are usually controlled by multiple quantitative trait locus(QTL).To elucidate the genetic basis of extremely large grain shape,QTL analysis was performed using an F2 population derived from a cross between a japonica cultivar ’JZ1560’(extremely large grain)and a contrasting indica cultivar ’FAZ1’(small grain).A total number of 24 QTLs were detected on seven different chromosomes.QTLs for GL,GW,GT and LWR explained 11.6%,95.62%,91.5%and 89.9%of total phenotypic variation,respectively.Many QTLs pleiotropically controlled different grain traits,contributing complex traits correlation.GW2 and qSW5/GW5,which have been cloned previously to control GW,showed similar chromosomal locations with qGW2-I/qGT2-I/qLWR2-2 and qGW5-2/qLWR5-l and should be the right candidate genes.Plants pyramiding GW2 and qSW5/GW5 showed a significant increase in GW compared with those carrying one of the two major QTLs.Furthermore,no significant QTL interaction was observed between GW2 and qSW5/GW5.These results suggested that GW2 and qSW5/GW5 might work in independent pathways to regulate grain traits.’JZ1560’ alleles underlying all QTLs contributed an increase in GW and GT and the accumulation of additive effects generates the extremely large grain shape in ’JZ1560’.     

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.     

Genetic mapping and confirmation of quantitative trait loci for grain chalkiness in rice

Grain chalkiness is a highly undesirable trait affecting rice grain quality and milled rice yield. In order to clarify the genetic basis of chalkiness, a recombinant inbred line population (RIL) derived from a cross between Beilu130 (a japonica cultivar with high chalkiness) and Jin23B (an indica cultivar with low chalkiness) was developed for quantitative trait locus (QTL) mapping. A total of 10 QTLs for white belly rate (WBR) and white core rate (WCR) were detected on eight different chromosomes over 2 years. Two QTLs for WBR (qWBR2 and qWBR5) showed similar chromosomal locations with GW2 and qSW5/GW5, which have been cloned previously to control the grain width and should be the right candidate genes. Three novel minor QTLs controlling WCR, qWCR1, qWCR3, and qWCR4 were further validated in near isogenic F₂ populations (NIL-F₂) and explained 26.1, 18.3, and 21.1% of the phenotypic variation, respectively. These QTLs could be targets for map-based cloning of the candidate genes to elucidate the molecular mechanism of chalkiness and for marker-assisted selection (MAS) in rice grain quality improvement.     

Fine mapping and identification of a novel locus <Emphasis Type="Italic">qGL12.2</Emphasis> control grain length in wild rice (<Emphasis Type="Italic">Oryza rufipogon</Emphasis> Griff.)

Key message

A wild rice QTL qGL12.2 for grain length was fine mapped to an 82-kb interval in chromosome 12 containing six candidate genes and none was reported previously.

Abstract

Grain length is an important trait for yield and commercial value in rice. Wild rice seeds have a very slender shape and have many desirable genes that have been lost in cultivated rice during domestication. In this study, we identified a quantitative trait locus, qGL12.2, which controls grain length in wild rice. First, a wild rice chromosome segment substitution line, CSSL41, was selected that has longer glume and grains than does the Oryza sativa indica cultivar, 9311. Next, an F₂ population was constructed from a cross between CSSL41 and 9311. Using the next-generation sequencing combined with bulked-segregant analysis and F₃ recombinants analysis, qGL12.2 was finally fine mapped to an 82-kb interval in chromosome 12. Six candidate genes were found, and no reported grain length genes were found in this interval. Using scanning electron microscopy, we found that CSSL41 cells are significantly longer than those of 9311, but there is no difference in cell widths. These data suggest that qGL12.2 is a novel gene that controls grain cell length in wild rice. Our study provides a new genetic resource for rice breeding and a starting point for functional characterization of the wild rice GL gene.

     

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.     

Fine mapping of qHd1, a minor heading date QTL with pleiotropism for yield traits in rice (Oryza sativa L.)

Key message

A minor QTL for heading date located on the long arm of rice chromosome 1 was delimitated to a 95.0-kb region using near isogenic lines with sequential segregating regions.

Abstract

Heading date and grain yield are two key factors determining the commercial potential of a rice variety. In this study, rice populations with sequential segregating regions were developed and used for mapping a minor QTL for heading date, qHd1. A total of 18 populations in six advanced generations through BC₂F₆ to BC₂F₁₁ were derived from a single BC₂F₃ plant of the indica rice cross Zhenshan 97 (ZS97)///ZS97//ZS97/Milyang 46. The QTL was delimitated to a 95.0-kb region flanked by RM12102 and RM12108 in the terminal region of the long arm of chromosome 1. Results also showed that qHd1 was not involved in the photoperiodic response, having an additive effect ranging from 2.4 d to 2.9 d observed in near isogenic lines grown in the paddy field and under the controlled conditions of either short day or long day. The QTL had pleiotropic effects on yield traits, with the ZS97 allele delaying heading and increasing the number of spikelets per panicle, the number of grains per panicle and grain yield per plant. The candidate region contains ten annotated genes including two genes with functional information related to the control of heading date. These results lay a foundation for the cloning of qHd1. In addition, this kind of minor QTLs could be of great significance in rice breeding for allowing minor adjustment of heading date and yield traits.     

Mapping and validation of quantitative trait loci associated with concentrations of 16 elements in unmilled rice grain

Key Message

QTLs controlling the concentrations elements in rice grain were identified in two mapping populations. The QTLs were clustered such that most genomic regions were associated with more than one element.

Abstract

In this study, quantitative trait loci (QTLs) affecting the concentrations of 16 elements in whole, unmilled rice (Oryza sativa L.) grain were identified. Two rice mapping populations, the ‘Lemont’ × ‘TeQing’ recombinant inbred lines (LT-RILs), and the TeQing-into-Lemont backcross introgression lines (TILs) were used. To increase opportunity to detect and characterize QTLs, the TILs were grown under two contrasting field conditions, flooded and irrigated-but-unflooded. Correlations between the individual elements and between each element with grain shape, plant height, and time of heading were also studied. Transgressive segregation was observed among the LT-RILs for all elements. The 134 QTLs identified as associated with the grain concentrations of individual elements were found clustered into 39 genomic regions, 34 of which were found associated with grain element concentration in more than one population and/or flooding treatment. More QTLs were found significant among flooded TILs (92) than among unflooded TILs (47) or among flooded LT-RILs (40). Twenty-seven of the 40 QTLs identified among the LT-RILs were associated with the same element among the TILs. At least one QTL per element was validated in two or more population/environments. Nearly all of the grain element loci were linked to QTLs affecting additional elements, supporting the concept of element networks within plants. Several of the grain element QTLs co-located with QTLs for grain shape, plant height, and days to heading; but did not always differ for grain elemental concentration as predicted by those traits alone. A number of interesting patterns were found, including a strong Mg–P–K complex.     

Fine mapping of a preharvest sprouting QTL interval on chromosome 2B in white wheat

Key message

Fine mapping by recombinant backcross populations revealed that a preharvest sprouting QTL on 2B contained two QTLs linked in coupling with different effects on the phenotype.

Abstract

Wheat preharvest sprouting (PHS) occurs when grain germinates on the plant before harvest, resulting in reduced grain quality. Previous mapping of quantitative trait locus (QTL) revealed a major PHS QTL, QPhs.cnl-2B.1, located on chromosome 2B significant in 16 environments that explained from 5 to 31 % of the phenotypic variation. The objective of this project was to fine map the QPhs.cnl-2B.1 interval. Fine mapping was carried out in recombinant backcross populations (BC₁F₄ and BC₁F₅) that were developed by backcrossing selected doubled haploids to a recurrent parent and self-pollinating the BC₁F₄ and BC₁F₅ generations. In each generation, three markers in the QPhs.cnl-2B.1 interval were used to screen for recombinants. Fine mapping revealed that the QPhs.cnl-2B.1 interval contained two PHS QTLs linked in coupling. The distal PHS QTL, located between Wmc453c and Barc55, contributed 8 % of the phenotypic variation and also co-located with a major seed dormancy QTL determined by germination index. The proximal PHS QTL, between Wmc474 and CNL415-rCDPK, contributed 16 % of the variation. Several candidate genes including Mg-chelatase H subunit family protein, GTP-binding protein and calmodulin/Ca²⁺-dependent protein kinase were linked to the PHS QTL. Although many recombinant lines were identified, the lack of polymorphism for markers in the QTL interval prevented the localization of the recombination breakpoints and identification of the gene underlying the phenotype.     

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.     

QTL mapping of root traits in phosphorus-deficient soils reveals important genomic regions for improving NDVI and grain yield in barley

Key message

Major QTLs for root rhizosheath size are not correlated with grain yield or yield response to phosphorus. Important QTLs were found to improve phosphorus efficiency.

Abstract

Root traits are important for phosphorus (P) acquisition, but they are often difficult to characterize and their breeding values are seldom assessed under field conditions. This has shed doubts on using seedling-based criteria of root traits to select and breed for P efficiency. Eight root traits were assessed under controlled conditions in a barley doubled-haploid population in soils differing in P levels. The population was also phenotyped for grain yield, normalized difference vegetation index (NDVI), grain P uptake and P utilization efficiency at maturity (PutE_GY) under field conditions. Several quantitative traits loci (QTLs) from the root screening and the field trials were co-incident. QTLs for root rhizosheath size and root diameter explained the highest phenotypic variation in comparison to QTLs for other root traits. Shared QTLs were found between root diameter and grain yield, and total root length and PutE_GY. A common major QTL for rhizosheath size and NDVI was mapped to the HvMATE gene marker on chromosome 4H. Collocations between major QTLs for NDVI and grain yield were detected on chromosomes 6H and 7H. When results from BIP and MET were combined, QTLs detected for grain yield were also those QTLs found for NDVI. QTLs qGY5H, qGY6H and qGY7Hb on 7H were robust QTLs in improving P efficiency. A selection of multiple loci may be needed to optimize the breeding outcomes due to the QTL x Environment interaction. We suggest that rhizosheath size alone is not a reliable trait to predict P efficiency or grain yield.

     

Genetic dissection of developmental behavior of grain weight in wheat under diverse temperature and water regimes

As a quantitatively inherited trait related to high yield potential, grain weight (GW) development in wheat is constrained by abiotic stresses such as limited water supply and high temperature. Data from a doubled haploid population, derived from a cross of (Hanxuan 10?×?Lumai 14), grown in four environments were used to explore the genetic basis of GW developmental behavior in unconditional and conditional quantitative trait locus (QTL) analyses using a mixed linear model. Thirty additive QTLs and 41 pairs of epistatic QTLs were detected, and were more frequently observed on chromosomes 1B, 2A, 2D, 4A, 4B and 7B. No single QTL was continually active during all stages or periods of grain growth. The QTLs with additive effects (A-QTLs) expressed in the period S1|S0 (the period from the flowering to the seventh day after) formed a foundation for GW development. GW development at these stages can be used as an index for screening superior genotypes under diverse abiotic stresses in a wheat breeding program. One QTL, i.e. Qgw.cgb-6A.2, showed high adaptability for water-limited and heat-stress environments. Many A-QTLs interacted with more than one other QTL in the two genetic models, such as Qgw.cgb-4B.2 interacted with five QTLs, showing that the genetic architecture underlying GW development involves a collective expression of genes with additive and epistatic effects.     

水稻粒长QTL定位与主效基因的遗传分析

该研究利用短粒普通野生稻矮杆突变体和长粒栽培稻品种KJ01组配杂交组合F_1,构建分离群体F_2;并对该群体粒长进行性状遗传分析,利用平均分布于水稻的12条染色体上的132对多态分子标记对该群体进行QTL定位及主效QTLs遗传分析,为进一步克隆新的主效粒长基因奠定基础,并为水稻粒形育种提供理论依据。结果表明:(1)所构建的水稻杂交组合分离群体F_2的粒长性状为多基因控制的数量性状。(2)对543株F_2分离群体进行QTL连锁分析,构建了控制水稻粒长的连锁遗传图谱,总长为1 713.94 cM,共检测出24个QTLs,只有3个表现为加性遗传效应,其余位点均表现为遗传负效应。(3)检测到的3个主效QTLs分别位于3号染色体的分子标记PSM379～RID24455、RID24455～RM15689和RM571～RM16238之间,且三者对表型的贡献率分别为54.85%、31.02%和7.62%。(4)在标记PSM379～RID24455之间已克隆到的粒长基因为该研究新发现的主效QTL位点。     

Rapid Identification of Major QTLs Associated with Rice Grain Weight and Their Utilization

To uncover the genetics of rice grain weight, we constructed an RIL population derived from a cross between a large grain accession M201 and a small size variety JY293. Specific Locus Amplified Fragment Sequencing (SLAF-Seq) technology was used to genotype two bulked DNA pools made from individual DNA of the heaviest 30 lines and the lightest 30 lines according to the 1000 grain weight (TGW). Bulked segregant analysis (BSA) was used to identify SLAFs strongly associated with TGW. Two marker-intensive regions at 24,600,000–24,850,000 bp and 25,000,000–25,350,000 bp on chromosome 3 were identified tightly related to the TGW. Then a linkage map of chromosome 3 was constructed with SSR markers and some SLAF derived single nucleotide polymorphisms (SNPs). Quantitative trait locus (QTL) mapping for TGW, grain length, grain width, and grain thickness revealed one major QTL in the second hot-region and two other minor QTLs for grain weight. These three QTLs displayed hierarchical effects on grain length and grain weight in order of qTGW3.2 (qGL3) qTGW3.1 (GS3) qTGW3.3. Multiple comparisons of means among the eight combinations of 3 QTLs revealed that the lines with two of three QTLs deriving from M201 displayed a large grain weight phenotype (TGW 40.2g, average data of three years) and lines with both qTGW3.1 and qTGW3.3 alleles from M201 (42.5g) had similar grain weight to the qTGW3.2 (40.8g) alone. Two strategies with similar effectiveness were proposed to improve grain weight by marker-assisted selection (MAS). One is to introduce the novel qTGW3.2 allele alone, and the other is to pyramid qTGW3.1 and qTGW3.3 alleles together. One new allele of GS3 (39 bp deletion in intron 1) and two SNPs in coding sequence of qGL3 identified in this study from M201 are useful in pyramiding elite alleles for molecular breeding for improvement of rice yield.     

A major QTL associated with Fusarium oxysporum race 1 resistance identified in genetic populations derived from closely related watermelon lines using selective genotyping and genotyping-by-sequencing for SNP discovery

Key message

A major quantitative trait locus (QTL) for Fusarium oxysporum Fr. f. sp. niveum race 1 resistance was identified by employing a “selective genotyping” approach together with genotyping-by-sequencing technology to identify QTLs and single nucleotide polymorphisms associated with the resistance among closely related watermelon genotypes.

Abstract

Fusarium wilt is a major disease of watermelon caused by the soil-borne fungus Fusarium oxysporum Schlechtend.:Fr. f. sp. niveum (E.F. Sm.) W.C. Snyder & H.N. Hans (Fon). In this study, a genetic population of 168 F₃ families (24 plants in each family) exhibited continuous distribution for Fon race 1 response. Using a “selective genotyping” approach, DNA was isolated from 91 F₂ plants whose F₃ progeny exhibited the highest resistance (30 F₂ plants) versus highest susceptibility (32 F₂ plants), or moderate resistance to Fon race 1 (29 F₂ plants). Genotyping-by-sequencing (GBS) technology was used on these 91 selected F₂ samples to produce 266 single nucleotide polymorphism (SNP) markers, representing the 11 chromosomes of watermelon. A major quantitative trait locus (QTL) associated with resistance to Fon race 1 was identified with a peak logarithm of odds (LOD) of 33.31 and 1-LOD confidence interval from 2.3 to 8.4 cM on chromosome 1 of the watermelon genetic map. This QTL was designated “Fo-1.1” and is positioned in a genomic region where several putative pathogenesis-related or putative disease-resistant gene sequences were identified. Additional independent, but minor QTLs were identified on chromosome 1 (LOD 4.16), chromosome 3 (LOD 4.36), chromosome 4 (LOD 4.52), chromosome 9 (LOD 6.8), and chromosome 10 (LOD 5.03 and 4.26). Following the identification of a major QTL for resistance using the “selective genotyping” approach, all 168 plants of the F ₂ population were genotyped using the SNP nearest the peak LOD, confirming the association of this SNP marker with Fon race 1 resistance. The results in this study should be useful for further elucidating the mechanism of resistance to Fusarium wilt and in the development of molecular markers for use in breeding programs of watermelon.     

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.     

Highly efficient genotyping of rice biparental populations by GoldenGate assays based on parental resequencing

Key message

A new time- and cost-effective strategy was developed for medium-density SNP genotyping of rice biparental populations, using GoldenGate assays based on parental resequencing.

Abstract

Since the advent of molecular markers, crop researchers and breeders have dedicated huge amounts of effort to detecting quantitative trait loci (QTL) in biparental populations for genetic analysis and marker-assisted selection (MAS). In this study, we developed a new time- and cost-effective strategy for genotyping a population of progeny from a rice cross using medium-density single nucleotide polymorphisms (SNPs). Using this strategy, 728,362 “high quality” SNPs were identified by resequencing Teqing and Lemont, the parents of the population. We selected 384 informative SNPs that were evenly distributed across the genome for genotyping the biparental population using the Illumina GoldenGate assay. 335 (87.2 %) validated SNPs were used for further genetic analyses. After removing segregation distortion markers, 321 SNPs were used for linkage map construction and QTL mapping. This strategy generated SNP markers distributed more evenly across the genome than previous SSR assays. Taking the GW5 gene that controls grain shape as an example, our strategy provided higher accuracy (0.8 Mb) and significance (LOD 5.5 and 10.1) in QTL mapping than SSR analysis. Our study thus provides a rapid and efficient strategy for genetic studies and QTL mapping using SNP genotyping assays.     

Comparative QTL analysis of early short-time drought tolerance in Polish fodder and malting spring barleys

Key message

An effective approach for the further evolution of QTL markers, may be to create mapping populations for locally adapted gene pools, and to phenotype the studied trait under local conditions.

Abstract

Mapping populations of Polish fodder and malting spring barleys (Hordeum vulgare L.) were used to analyze traits describing short-time drought response at the seedlings stage. High-throughput genotyping (Diversity Array Technology (DArT) markers) and phenotyping techniques were used. The results showed high genetic diversity of the studied populations which allowed the creation of high-density linkage maps. There was also high diversity in the physiological responses of the barleys. Quantitative trait locus (QTL) analysis revealed 18 QTLs for nine physiological traits on all chromosomes except 1H in malting barley and 15 QTLs for five physiological traits on chromosomes 2H, 4H, 5H and 6H in fodder barley. Chromosomes 4H and 5H contained QTLs which explained most of the observed phenotypic variations in both populations. There was a major QTL for net photosynthetic rate in the malting barley located on chromosome 5H and two major QTLs for overall photochemical performance (PI) located on 5H and 7H. One major QTL related to photochemical quenching of chlorophyll fluorescence was located on chromosome 4H in fodder barley. Three QTL regions were common to both mapping populations but the corresponding regions explained different drought-induced traits. One region was for QTLs related to PSII photosynthetic activity stress index in malting barley, and the corresponding region in fodder barley was related to the water content stress index. These results are in accordance with previous studies which showed that different traits were responsible for drought tolerance variations in fodder and malting barleys.     

Examining two sets of introgression lines reveals background-independent and stably expressed QTL that improve grain appearance quality in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Key message

A novel QTL cluster for appearance quality on Chr07 was identified using reciprocal introgression populations in different locations in China. Two secondary F ₂ populations validated QTL with significant effect on appearance quality.

Abstract

Appearance quality (AQ) is the main determinants of market value of rice. Identification of QTL affecting AQ is the prerequisite for efficient improvement of AQ through marker-assisted selection (MAS). Two sets of reciprocal introgression lines derived from indica Minghui 63 and japonica 02428 were used to dissect the stability of QTL affecting five AQ traits, including grain length, grain width, length to width ratio, percentage of grains with chalkiness, and degree of endosperm chalkiness using 4568 bin genotype produced from 58,000 SNPs across five different environments. A total of 41 and 30 main-effect QTL were identified in MH63 and 02428 backgrounds, respectively. Among them, 9 background-independent QTL (BI-QTL) were found. There were also 13 and 10 stable-expressed QTL (SE-QTL) across at least two environments in MH63 and 02428 backgrounds, respectively. Two important BI- and SE-QTL regions (BISERs) including BISER-I harboring qPGWC5, qDEC5, qGW5.1, and qLWR5 on chromosome 5 and BISER-II harboring qGL7, qLWR7, qPGWC7, and qDEC7 on chromosome 7 were identified. The BISER-II was newly reported and validated by two secondary F₂ populations in the reciprocal backgrounds. Among 59 epistatic QTL (E-QTL) detected in this study, there were only four SE- but no BI-E-QTL detected in different environments, indicating that genetic background has stronger effect on AQ traits than the environmental factors, especially for percentage of grains with chalkiness (PGWC) and degree of endosperm chalkiness (DEC) with lower heritability. BISER-I and BISER-II harboring many BI- and SE-QTL with favorable alleles from slender grain rice are much important for improvement of rice AQ by MAS.