Fine mapping of a grain-weight quantitative trait locus in the pericentromeric region of rice chromosome 3

miRNAs and genes as molecular regulators of rice grain morphology and yield

Rice is one of the most consumed crops worldwide and the genetic and molecular basis of its grain yield attributes are well understood. Various studies have identified different yield-related parameters in rice that are regulated by the microRNAs (miRNAs). MiRNAs are endogenous small non-coding RNAs that silence gene expression during or after transcription. They control a variety of biological or genetic activities in plants including growth, development and response to stress. In this review, we have summarized the available information on the genetic control of panicle architecture and grain yield (number and morphology) in rice. The miRNA nodes that are associated with their regulation are also described while focussing on the central role of miR156-SPL node to highlight the co-regulation of two master regulators that determine the fate of panicle development. Since abiotic stresses are known to negatively affect yield, the impact of abiotic stress induced alterations on the levels of these miRNAs are also discussed to highlight the potential of miRNAs for regulating crop yields.

2Gs and plant architecture: breaking grain yield ceiling through breeding approaches for next wave of revolution in rice (Oryza sativa L.)

Rice is a principal food crop for more than half of the global population. Grain number and grain weight (2Gs) are the two complex traits controlled by several quantitative trait loci (QTLs) and are considered the most critical components for yield enhancement in rice. Novel molecular biology and QTL mapping strategies can be utilized in dissecting the complex genetic architecture of these traits. Discovering the valuable genes/QTLs associated with 2Gs traits hidden in the rice genome and utilizing them in breeding programs may bring a revolution in rice production. Furthermore, the positional cloning and functional characterization of identified genes and QTLs may aid in understanding the molecular mechanisms underlying the 2Gs traits. In addition, knowledge of modern genomic tools aids the understanding of the nature of plant and panicle architecture, which enhances their photosynthetic activity. Rice researchers continue to combine important yield component traits (including 2Gs for the yield ceiling) by utilizing modern breeding tools, such as marker-assisted selection (MAS), haplotype-based breeding, and allele mining. Physical co-localization of GW7 (for grain weight) and DEP2 (for grain number) genes present on chromosome 7 revealed the possibility of simultaneous introgression of these two genes, if desirable allelic variants were found in the single donor parent. This review article will reveal the genetic nature of 2Gs traits and use this knowledge to break the yield ceiling by using different breeding and biotechnological tools, which will sustain the world's food requirements.

Identification, Fine Mapping and Application of Quantitative Trait Loci for Grain Shape Using Single-Segment Substitution Lines in Rice (Oryza sativa L.)

Quantitative trait loci (QTLs) and HQTL (heterosis QTLs) for grain shape are two major genetic factors of grain yield and quality in rice (Oryza sativa L.). Although many QTLs for grain shape have been reported, only a few are applied in production. In this study, 54 QTLs for grain shape were detected on 10 chromosomes using 33 SSSLs (single-segment substitution lines) and methods of statistical genetics. Among these, 23 exhibited significant positive additive genetic effects, including some novel QTLs, among which qTGW4-(1,2), qTGW10-2, and qTGW10-3 were three QTLs newly found in this study and should be paid more attention. Moreover, 26 HQTLs for grain shape were probed. Eighteen of these exhibited significant positive dominant genetic effects. Thirty-three QTLs for grain shape were further mapped using linkage analysis. Most of the QTLs for grain shape produced pleiotropic effects, which simultaneously controlled multiple appearance traits of grain shape. Linkage mapping of the F₂ population derived from sub-single-segment substitution lines further narrowed the interval harbouring qTGW10-3 to 75.124 kb between PSM169 and RM25753. The candidate gene was identified and could be applied to breeding applications by molecular marker-assisted selection. These identified QTLs for grain shape will offer additional insights for improving grain yield and quality in rice breeding.

Research on a rapid identification method for counting universal grain crops

Thousand-grain weight is a key indicator of crop yield and an important parameter for evaluating cultivation measures. Existing methods based on image analysis are convenient but lack a counting algorithm that is suitable for multiple types of grains. This research develops an application program based on an Android device to quickly calculate the number of grains. We explore the short axis measurement method of the grains with morphological thought, and determine the relationship between the general corrosion threshold and the short axis. To solve the problem of calculating the number of grains in the connected area, the study proposes a corrosion algorithm based on the short axis and an improved corner point method. After testing a variety of crop grains and equipment, it was found that the method has high universality, supports grain counting with white paper as the background, and has high accuracy and calculation efficiency. The average accuracy rate is 97.9%, and the average time is less than 0.7 seconds. In addition, the difference between the average accuracy for various mobile phones and multiple crops is small. This research proposes a grain counting algorithm with a wide range of applications to meet the requirements of nonglare use in the field. The algorithm provides a fast, accurate, low-cost tool for counting grains of wheat, corn, mung bean, soybean, peanut, rapeseed, etc., which is less constrained by space and power conditions. The algorithm is highly adaptable and can provide a reference for the study of grain counting.

Discovery and Validation of Grain Shape Loci in U.S. Rice Germplasm Through Haplotype Characterization

Rice grain shape is a major determinant of rice market value and the end-use. We mapped quantitative trait loci (QTL) for grain shape traits in a bi-parental recombinant inbred line population (Trenasse/Jupiter) and discovered two major grain length QTLs—qGL3.1 and qGL7.1. Previously, a major grain shape gene GS3 was reported in the qGL3.1 region and grain length gene GL7 was reported to be encompassing qGL7.1 locus. The re-sequencing SNP data on the International Rice Research Institute (IRRI) 3K Rice Genome Project (RGP) panel were obtained from the IRRI SNP-Seek database for both genes and haplotype diversity was characterized for each gene in this diverse panel. United States rice germplasm was not well represented in the IRRI 3K RGP database. Therefore, a minimum SNP set was identified for each gene that could differentiate all the characterized haplotypes. These haplotypes in the 3K RGP panel were screened across 323 elite U.S. genotypes using the minimum SNP set. The screening of haplotypes and phenotype association confirmed the role of GS3 under qGL3.1. However, screening of the GL7 haplotypes in the U.S. germplasm panel showed that GL7 did not play a role in qGL7.1, and in addition, GL7.1 did not segregate in the Trenasse/Jupiter RIL population. This concluded that qGL7.1 is a novel QTL discovered on chr7 for grain shape in the Trenasse/Jupiter RIL population. A high-throughput KASP-based SNP marker for each locus (GS3 and qGL7.1) was identified and validated in elite U.S. rice germplasm to be used in an applied rice breeding program.

Compatibility between snails and schistosomes: insights from new genetic resources, comparative genomics, and genetic mapping

The freshwater snail Biomphalaria glabrata is an important intermediate host of the parasite Schistosoma mansoni that causes human intestinal schistosomiasis. To better understand vector snail biology and help advance innovative snail control strategies, we have developed a new snail model consisting of two homozygous B. glabrata lines (iM line and iBS90) with sharply contrasting schistosome-resistance phenotypes. We produced and compared high-quality genome sequences for iM line and iBS90 which were assembled from 255 (N50 = 22.7 Mb) and 346 (N50 = 19.4 Mb) scaffolds, respectively. Using F2 offspring bred from the two lines and the newly generated iM line genome, we constructed 18 linkage groups (representing the 18 haploid chromosomes) covering 96% of the genome and identified three new QTLs (quantitative trait loci), two involved in snail resistance/susceptibility and one relating to body pigmentation. This study provides excellent genomic resources for unveiling complex vector snail biology, reveals genomic difference between resistant and susceptible lines, and offers novel insights into genetic mechanism of the compatibility between snail and schistosome.

Mapping QTLs for yield and photosynthesis-related traits in three consecutive backcross populations of Oryza sativa cultivar Cottondora Sannalu (MTU1010) and Oryza rufipogon

Identification of trait enhancing QTLs for yield and photosynthesis-related traits in rice using interspecific mapping population and chromosome segment substitution lines derived from a cross between Oryza sativa and Oryza rufipogon. Wild rice contains novel genes which can help in improving rice yield. Common wild rice Oryza rufipogon is a known source for enhanced photosynthesis and yield-related traits. We developed BC₂F_2:3:4 mapping populations using O. rufipogon IC309814 with high photosynthetic rate as donor, and elite cultivar MTU1010 as recurrent parent. Evaluation of 238 BC₂F₂ families for 13 yield-related traits and 208 BC₂F₂ families for seven photosynthesis-related physiological traits resulted in identification of significantly different lines which performed better than MTU1010 for various yield contributing traits. 49 QTLs were identified for 13 yield traits and 7 QTLs for photosynthesis-related traits in BC₂F_2. In addition, 34 QTLs in BC₂F₃ and 26 QTLs in BC₂F₄ were also detected for yield traits.11 common QTLs were identified in three consecutive generations and their trait-increasing alleles were derived from O. rufipogon. Significantly, one major effect common QTL qTGW3.1 for thousand grain weight with average phenotypic variance 8.1% and one novel QTL qBM7.1 for biomass were identified. Photosynthesis-related QTLs qP_N9.1, qP_N12.1, qP_N12.2 qSPAD1.1 and qSPAD6.1 showed additive effect from O. rufipogon. A set of 145 CSSLs were identified in BC₂F₂ which together represented 87% of O. rufipogon genome. In addition, 87 of the 145 CSSLs were significantly different than MTU1010 for at least one trait. The major effect QTLs can be fine mapped for gene discovery. CSSLs developed in this study are a good source of novel alleles from O. rufipogon in the background of Cottondora Sannalu for rapid improvement of any trait in rice.

Validating a Major Quantitative Trait Locus and Predicting Candidate Genes Associated With Kernel Width Through QTL Mapping and RNA-Sequencing Technology Using Near-Isogenic Lines in Maize

Kernel size is an important agronomic trait for grain yield in maize. The purpose of this study was to validate a major quantitative trait locus (QTL), qKW-1, which was identified in the F₂ and F_2:3 populations from a cross between the maize inbred lines SG5/SG7 and to predict candidate genes for kernel width (KW) in maize. A major QTL, qKW-1, was mapped in multiple environments in our previous study. To validate and fine map qKW-1, near-isogenic lines (NILs) with 469 individuals were developed by continuous backcrossing between SG5 as the donor parent and SG7 as the recurrent parent. Marker-assisted selection was conducted from the BC₂F₁ generation with simple sequence repeat (SSR) markers near qKW-1. A secondary linkage map with four markers, PLK12, PLK13, PLK15, and PLK17, was developed and used for mapping the qKW-1 locus. Finally, qKW-1 was mapped between the PLK12 and PLK13 intervals, with a distance of 2.23 cM to PLK12 and 0.04 cM to PLK13, a confidence interval of 5.3 cM and a phenotypic contribution rate of 23.8%. The QTL mapping result obtained was further validated by using selected overlapping recombinant chromosomes on the target segment of maize chromosome 3. Transcriptome analysis showed that a total of 12 out of 45 protein-coding genes differentially expressed between the two parents were detected in the identified qKW-1 physical interval by blasting with the Zea_Mays_B73 v4 genome. GRMZM2G083176 encodes the Niemann-Pick disease type C, and GRMZM2G081719 encodes the nitrate transporter 1 (NRT1) protein. The two genes GRMZM2G083176 and GRMZM2G081719 were predicted to be candidate genes of qKW-1. Reverse transcription-polymerase chain reaction (RT-qPCR) validation was conducted, and the results provide further proof of the two candidate genes most likely responsible for qKW-1. The work will not only help to understand the genetic mechanisms of KW in maize but also lay a foundation for further cloning of promising loci.

Use of laboratory equipment for analysis of external quality of food maize kernel

The purpose of this study was to investigate the influence of the parameters of the grain air-sieve cleaner in laboratory conditions on the external quality of food maize (Zea mays L.)  kernel in terms of the design for the selection of a suitable sieve mesh for cleaning procedures. The object of the research was maize kernel, variety Pionier P0216, year of cultivation 2019. The available laboratory equipment was used in the study. To evaluate the external quality of food maize kernel, indicators were determined, which were investigated before and after cleaning. An Asus notebook computer with software from Microsoft Windows XP and Ofice 2010 was used to evaluate the measurement results. These results were achieved: an average bulk density of 846.77 kg.m-3 was found in the input sample of food maize kernel after harvest, admixtures before cleaning reached an average of 19.1% and impurities of 2.76%, cleanliness of kernels before cleaning averaged 76.9%, the output after cleaning expressed in terms of bulk density reached an average value of 851.15 kg.m-3, admixtures after cleaning reached 0.07% and impurities 4.21%, clean kernels after cleaning reached 94.86% and damage kernels after cleaning decreased slightly by separation of fragments and chipped kernels. In conclusion, it was stated that the laboratory technique for post-harvest treatment of grain is at a high level worldwide. Currently, the issue of post-harvest processing of grain in Slovakia is addressed at an average level. Post-harvest processing and storage of grain in terms of enginery and technological and economic aspects is little researched in the Slovak Republic, so these issues are open to further research.

Characterization of functional genes GS3 and GW2 and their effect on the grain size of various landraces of rice (Oryza sativa)

BACKGROUND

Grain size is an essential factor of grain quality and yield in rice. The genetic studies have substantially contributed to enhancing yield and maintaining a good quality of rice. The two major genes GS3 (a negative regulator of grain length) and GW2 (a negative regulator of grain width) with functional mutation play a significant role in controlling the grain size of rice. METHODS AND RESULTS: In the study, 17 different widely grown Pakistani landraces of various genetic and geographic backgrounds were evaluated for grain phenotypic traits (1000-grain weight, length, width, and thickness) and also screened for genotypic mutation in GS3 and GW2 genes. Phenotypic data revealed the range for grain weight from 16.86 g (Lateefy) to 26.91 g (PS2), grain length ranged from 7.27 mm (JP-5) to 12.18 mm (PS2), grain width ranged from 2.01 mm (Lateefy) to 3.51 mm (JP5), and grain thickness ranged from 1.79 mm to 2.19. Correlation revealed a negative and significant correlation between grain width and length. There was no significant correlation between grain length and 1000-grain weight and grain width. LSD test displayed that the means of three variables grain length, grain width, and 1000-grain weight were statistically different from one another except grain width and grain breadth. Fifteen accessions carried the domesticated allele of GS3 while JP5 and Fakhr-e-Malakand carried the dominant allele. Similarly, fifteen accessions carried the dominant allele of GW2 while JP-5 and Fakhr-e-Malakand carried the mutant allele.

CONCLUSIONS

The study shows that the mutant alleles of both genes are of significance to pyramid them in any breeding program. However, just incorporating favorable alleles is not the sole solution for improving the grain size. Therefore, further elucidation of GS3 and GW2 genes regulatory network, their interaction, trade-off, and pathways will better coordinate their marker-assisted selection in the future breeding program. Additionally, the study concluded that the selection of grain size was not dependent on 1000-grain weight in the selected germplasm.

Toward Integrated Multi-Omics Intervention: Rice Trait Improvement and Stress Management

Rice (Oryza sativa) is an imperative staple crop for nearly half of the world's population. Challenging environmental conditions encompassing abiotic and biotic stresses negatively impact the quality and yield of rice. To assure food supply for the unprecedented ever-growing world population, the improvement of rice as a crop is of utmost importance. In this era, "omics" techniques have been comprehensively utilized to decipher the regulatory mechanisms and cellular intricacies in rice. Advancements in omics technologies have provided a strong platform for the reliable exploration of genetic resources involved in rice trait development. Omics disciplines like genomics, transcriptomics, proteomics, and metabolomics have significantly contributed toward the achievement of desired improvements in rice under optimal and stressful environments. The present review recapitulates the basic and applied multi-omics technologies in providing new orchestration toward the improvement of rice desirable traits. The article also provides a catalog of current scenario of omics applications in comprehending this imperative crop in relation to yield enhancement and various environmental stresses. Further, the appropriate databases in the field of data science to analyze big data, and retrieve relevant information vis-à-vis rice trait improvement and stress management are described.

QTL Analysis and Fine Mapping of a Major QTL Conferring Kernel Size in Maize (Zea mays)

Kernel size is an important agronomic trait for grain yield in maize. The purpose of this study is to map QTLs and predict candidate genes for kernel size in maize. A total of 199 F2 and its F2 : 3 lines from the cross between SG5/SG7 were developed. A composite interval mapping (CIM) method was used to detect QTLs in three environments of F2 and F2 : 3 populations. The result showed that a total of 10 QTLs for kernel size were detected, among which were five QTLs for kernel length (KL) and five QTLs for kernel width (KW). Two stable QTLs, qKW-1, and qKL-2, were mapped in all three environments. Three QTLs, qKL-1, qKW-1, and qKW-2, were overlapped with the QTLs identified from previous studies. In order to validate and fine map qKL-2, near-isogenic lines (NILs) were developed by continuous backcrossing between SG5 as the donor parent and SG7 as the recurrent parent. Marker-assisted selection was conducted from BC2F1 generation with molecular markers near qKL-2. A secondary linkage map with six markers around the qKL-2 region was developed and used for fine mapping of qKL-2. Finally, qKL-2 was confirmed in a 1.95 Mb physical interval with selected overlapping recombinant chromosomes on maize chromosome 9 by blasting with the Zea_Mays_B73 v4 genome. Transcriptome analysis showed that a total of 11 out of 40 protein-coding genes differently expressed between the two parents were detected in the identified qKL-2 interval. GRMZM2G006080 encoding a receptor-like protein kinase FERONIA, was predicted as a candidate gene to control kernel size. The work will not only help to understand the genetic mechanisms of kernel size of maize but also lay a foundation for further fine mapping and even cloning of the promising loci.

Sorghum qTGW1a encodes a G-protein subunit and acts as a negative regulator of grain size

Grain size is a major determinant of grain yield in sorghum and other cereals. Over 100 quantitative trait loci (QTLs) of grain size have been identified in sorghum. However, no gene underlying any grain size QTL has been cloned. Here, we describe the fine mapping and cloning of one grain size QTL. From an F8 recombinant inbred line population derived from a cross between inbred lines 654 and LTR108, we identified 44 grain size QTLs. One QTL, qTGW1a, was detected consistently on the long arm of chromosome 1 in the span of 4 years. Using the extreme recombinants from an F2:3 fine-mapping population, qTGW1a was delimited within a ~33 kb region containing three predicted genes. One of them, SORBI_3001G341700, predicted to encode a G-protein γ subunit and homologous to GS3 in rice, is likely to be the causative gene for qTGW1a. qTGW1a appears to act as a negative regulator of grain size in sorghum. The functional allele of the putatively causative gene of qTGW1a from inbred line 654 decreased grain size, plant height, and grain yield in transgenic rice. Identification of the gene underlying qTGW1a advances our understanding of the regulatory mechanisms of grain size in sorghum and provides a target to manipulate grain size through genome editing.

Fine-Mapping of Sorghum Stay-Green QTL on Chromosome10 Revealed Genes Associated with Delayed Senescence

This study was conducted to dissect the genetic basis and to explore the candidate genes underlying one of the important genomic regions on an SBI-10 long arm (L), governing the complex stay-green trait contributing to post-flowering drought-tolerance in sorghum. A fine-mapping population was developed from an introgression line cross—RSG04008-6 (stay-green) × J2614-11 (moderately senescent). The fine-mapping population with 1894 F₂ was genotyped with eight SSRs and a set of 152 recombinants was identified, advanced to the F₄ generation, field evaluated with three replications over 2 seasons, and genotyped with the GBS approach. A high-resolution linkage map was developed for SBI-10L using 260 genotyping by sequencing—Single Nucleotide Polymorphism (GBS–SNPs). Using the best linear unpredicted means (BLUPs) of the percent green leaf area (%GL) traits and the GBS-based SNPs, we identified seven quantitative trait loci (QTL) clusters and single gene, mostly involved in drought-tolerance, for each QTL cluster, viz., AP2/ERF transcription factor family (Sobic.010G202700), NBS-LRR protein (Sobic.010G205600), ankyrin-repeat protein (Sobic.010G205800), senescence-associated protein (Sobic.010G270300), WD40 (Sobic.010G205900), CPK1 adapter protein (Sobic.010G264400), LEA2 protein (Sobic.010G259200) and an expressed protein (Sobic.010G201100). The target genomic region was thus delimited from 15 Mb to 8 genes co-localized with QTL clusters, and validated using quantitative real-time (qRT)–PCR.

Genome-Wide Association Study of Grain Size Traits in Indica Rice Multiparent Advanced Generation Intercross (MAGIC) Population

Rice grain size plays a crucial role in determining grain quality and yield. In this study, two multiparent advanced generation intercross (MAGIC) populations, DC1 and BIM, were evaluated for grain size across three environments and genotyped with 55K array-based SNP detection and genotype-by-sequencing (GBS), respectively, to identify QTLs and SNPs associated with grain length, grain width, grain length-width ratio, grain thickness, and thousand grain weight. A total of 18 QTLs were identified for the five grain size-related traits and explained 6.43-63.35% of the total phenotypic variance. Twelve of these QTLs colocalized with the cloned genes, GS3, GW5/qSW5, GW7/GL7/SLG7, and GW8/OsSPL16, of which the first two genes showed the strongest effect for grain length and grain width, respectively. Four potential new genes were also identified from the QTLs, which exhibited both genetic background independency and environment stability and could be validated in future studies. Moreover, the significant SNP markers identified are valuable for direct utilization in marker-assisted breeding to improve rice grain size.

Novel cis-acting regulatory elements in wild Oryza species impart improved rice bran quality by lowering the expression of phospholipase D alpha1 enzyme (OsPLDα1)

Rice bran oil is good quality edible oil, rich in antioxidants and comprised typically of oleic-linoleic type fatty acids. However, presence of a highly lipolytic enzyme Phospholipase D alpha1 (OsPLDα1) increases free fatty acid content in the oil which further leads to stale flavor and rancidity of the oil, making it unfit for human consumption. In this study, we compared the upstream regions of OsPLDα1 orthologs across 34 accessions representing 5 wild Oryza species and 8 cultivars, to uncover sequence variations and identify cis-elements involved in differential transcription of orthologs. Alignment of the upstream sequences to the Nipponbare OsPLDα1 reference sequence revealed the presence of 39 SNPs. Phylogenetic analysis showed that all the selected cultivars and wild species accessions are closely related to the reference except for three accessions of O. rufipogon (IRGC89224, IRGC104425, and IRGC105902). Furthermore, using exon-specific qRT-PCR, OsPLDα1 expression patterns in immature grains indicated significant differences in transcript abundance between the wild species accessions. In comparison to the control, lowest gene expression was observed in IRGC89224 accession (0.20-fold) followed by IRGC105902 (0.26-fold) and IRGC104425 (0.41-fold) accessions. In-silico analysis of the OsPLDα1 promoter revealed that the copy number variations of CGCGBOXAT, GT1CONSENSUS, IBOXCORE, NODCON2GM, OSE2ROOTNODULE, SURECOREATSULTR11, and SORLIP1AT cis-elements play an important role in the transcriptional activities of orthologous genes. Owing to the presence of ARFAT and SEBF elements only in the IRGC89224 accession, which had the lowest gene expression as well, these putative upstream regulatory sequences have been identified as novel cis-elements which may act as repressors in regulating the OsPLDα1 gene expression. The accessions identified with low OsPLDα1 expressions could be further deployed as potential donors of ideal OsPLDα1 allele for transfer of the desired trait into elite rice cultivars.

Molecular insights into the regulation of rice kernel elongation

A large number of rice agronomic traits are complex, multi factorial and polygenic. As the mechanisms and genes determining grain size and yield are largely unknown, the identification of regulatory genes related to grain development remains a preeminent approach in rice genetic studies and breeding programs. Genes regulating cell proliferation and expansion in spikelet hulls and participating in endosperm development are the main controllers of rice kernel elongation and grain size. We review here and discuss recent findings on genes controlling rice grain size and the mechanisms, epialleles, epigenomic variation, and assessment of controlling genes using genome-editing tools relating to kernel elongation.

Evaluation of differential qPE9-1/DEP1 protein domains in rice grain length and weight variation

BACKGROUND

qPE9-1/DEP1, encoding a G protein γ subunit, has multiple effects on plant architecture, grain size, and yield in rice. The qPE9-1 protein contains an N-terminal G gamma-like (GGL) domain, a putative transmembrane domain, and a C-terminal cysteine-rich domain. However, the roles of each domain remain unclear.

RESULTS

In the present study, we focused on the genetic effects of different domains of qPE9-1 in the regulation of grain length and weight. We generated a series of transgenic plants expressing different truncated qPE9-1 proteins through constitutive expression and clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated protein 9 strategies. Phenotypic analysis indicated that the complete or long-tailed qPE9-1 contributed to the elongation of grains, while the GGL domain alone and short-tailed qPE9-1 led to short grains. The long C-terminus of qPE9-1 including two or three C-terminal von Willebrand factor type C domains effectively repressed the negative effects of the GGL domain on grain length and weight. qPE9-1-overexpressing lines in a Wuxianggeng 9 (carrying a qpe9-1 allele) background showed increased grain yield per plant, but lodging occurred in some years.

CONCLUSIONS

Manipulation of the C-terminal length of qPE9-1 through genetic engineering can be used to generate varieties with various grain lengths and weights according to different requirements in rice breeding. The genetic effects of qPE9-1/qpe9-1 are multidimensional, and breeders should take into account other factors including genetic backgrounds and planting conditions in the use of qPE9-1/qpe9-1.

Image analysis-based recognition and quantification of grain number per panicle in rice

BACKGROUND

The number grain per panicle of rice is an important phenotypic trait and a significant index for variety screening and cultivation management. The methods that are currently used to count the number of grains per panicle are manually conducted, making them labor intensive and time consuming. Existing image-based grain counting methods had difficulty in separating overlapped grains.

RESULTS

In this study, we aimed to develop an image analysis-based method to quickly quantify the number of rice grains per panicle. We compared the counting accuracy of several methods among different image acquisition devices and multiple panicle shapes on both Indica and Japonica subspecies of rice. The linear regression model developed in this study had a grain counting accuracy greater than 96% and 97% for Japonica and Indica rice, respectively. Moreover, while the deep learning model that we used was more time consuming than the linear regression model, the average counting accuracy was greater than 99%.

CONCLUSIONS

We developed a rice grain counting method that accurately counts the number of grains on a detached panicle, and believe this method can be a huge asset for guiding the development of high throughput methods for counting the grain number per panicle in other crops.

GainTKW: A Measurement System of Thousand Kernel Weight Based on the Android Platform

Thousand kernel weight (TKW) is an important parameter for the evaluation of grain yield. The traditional measurement method relies on manual steps: weighing and counting. In this paper, we developed a system for the automated evaluation of thousand kernel weight that combines a weighing module and Android devices, called “gainTKW”. The system is able to collect the weight information from the weighing module through a serial port using the RS232-micro USB cable. In the imaging process, we adopt a k-means clustering segmentation algorithm to solve the problem of uneven lighting. We used the marker-controlled watershed algorithm and area threshold method to count the number of kernels that are touching one another. These algorithms were implemented based on the OpenCV (Open Source Computer Vision) libraries. The system tested kernel images of six species taken with the Android device under different lighting conditions. The algorithms in this study can solve the segmentation problems caused by shadows, as well. The appropriate numbers of kernels, of different species, are counted with an error ratio upper limit of 3%. The application is convenient and easy to operate. For the experiments, we can prove the efficiency and accuracy of the developed system by comparing the results between the manual method and the proposed application.

Diversity analysis and genome-wide association studies of grain shape and eating quality traits in rice (Oryza sativa L.) using DArT markers

Microarray-based markers such as Diversity Arrays Technology (DArT) have become the genetic markers of choice for construction of high-density maps, quantitative trait loci (QTL) mapping and genetic diversity analysis based on their efficiency and low cost. More recently, the DArT technology was further developed in combination with high-throughput next-generation sequencing (NGS) technologies to generate the DArTseq platform representing a new sequencing tool of complexity-reduced representations. In this study, we used DArTseq markers to investigate genetic diversity and genome-wide association studies (GWAS) of grain quality traits in rice (Oryza sativa L.). The study was performed using 59 rice genotypes with 525 SNPs derived from DArTseq platform. Population structure analysis revealed only two distinct genetic clusters where genotypes were grouped based on environmental adaptation and pedigree information. Analysis of molecular variance indicated a low degree of differentiation among populations suggesting the need for broadening the genetic base of the current germplasm collection. GWAS revealed 22 significant associations between DArTseq-derived SNP markers and rice grain quality traits in the test genotypes. In general, 2 of the 22 significant associations were in chromosomal regions where the QTLs associated with the given traits had previously been reported, the other 20 significant SNP marker loci were indicative of the likelihood discovery of novel alleles associated with rice grain quality traits. DArTseq-derived SNP markers that include SNP12_100006178, SNP13_3052560 and SNP14_3057360 individually co-localised with two functional gene groups that were associated with QTLs for grain width and grain length to width ratio on chromosome 3, indicating trait dependency or pleiotropic-effect loci. This study demonstrated that DArTseq markers were useful genomic resources for genome-wide association studies of rice grain quality traits to accelerate varietal development and release.

Combination of twelve alleles at six quantitative trait loci determines grain weight in rice

Grain weight, which is controlled by quantitative trait loci (QTLs), is one of the most important determinants of rice yield. Although many QTLs for grain weight have been identified, little is known about how different alleles in different QTLs coordinate to determine grain weight. In the present study, six grain-weight-QTLs were detected in seven mapping populations (two F₂, one F₃, and four recombinant inbred lines) developed by crossing ‘Lemont’, a United States japonica variety, with ‘Yangdao 4’, a Chinese indica variety. In each of the six loci, one allele from one parent increased grain weight and one allele from another parent decreased it. Thus, the 12 alleles at the six QTLs were subjected to regression analysis to examine whether they acted additively across loci leading to a linear relationship between the predicted breeding value of QTL and phenotype. Results suggested that a combination of the 12 alleles determined grain weight. In addition, plants carrying more grain-weight-increasing alleles had heavier grains than those carrying more grain-weight-decreasing alleles. This trend was consistent in the seven mapping populations. Thus, these six QTLs might be used in marker-assisted selection of grain weight, by stacking different grain-weight-increasing or -decreasing alleles.

Combination of Eight Alleles at Four Quantitative Trait Loci Determines Grain Length in Rice

Grain length is an important quantitative trait in rice (Oryza sativa L.) that influences both grain yield and exterior quality. Although many quantitative trait loci (QTLs) for grain length have been identified, it is still unclear how different alleles from different QTLs regulate grain length coordinately. To explore the mechanisms of QTL combination in the determination of grain length, five mapping populations, including two F₂ populations, an F₃ population, an F₇ recombinant inbred line (RIL) population, and an F₈ RIL population, were developed from the cross between the U.S. tropical japonica variety ‘Lemont’ and the Chinese indica variety ‘Yangdao 4’ and grown under different environmental conditions. Four QTLs (qGL-3-1, qGL-3-2, qGL-4, and qGL-7) for grain length were detected using both composite interval mapping and multiple interval mapping methods in the mapping populations. In each locus, there was an allele from one parent that increased grain length and another allele from another parent that decreased it. The eight alleles in the four QTLs were analyzed to determine whether these alleles act additively across loci, and lead to a linear relationship between the predicted breeding value of QTLs and phenotype. Linear regression analysis suggested that the combination of eight alleles determined grain length. Plants carrying more grain length-increasing alleles had longer grain length than those carrying more grain length-decreasing alleles. This trend was consistent in all five mapping populations and demonstrated the regulation of grain length by the four QTLs. Thus, these QTLs are ideal resources for modifying grain length in rice.

Overexpression of Peptide-Encoding OsCEP6.1 Results in Pleiotropic Effects on Growth in Rice (O. sativa)

Plant peptide hormones play an important role in regulating plant developmental programs via cell-to-cell communication in a non-cell autonomous manner. To characterize the biological relevance of C-TERMINALLY ENCODED PEPTIDE (CEP) genes in rice, we performed a genome-wide search against public databases using a bioinformatics approach and identified six additional CEP members. Expression analysis revealed a spatial-temporal pattern of OsCEP6.1 gene in different tissues and at different developmental stages of panicle. Interestingly, the expression level of the OsCEP6.1 was also significantly up-regulated by exogenous cytokinin. Application of a chemically synthesized 15-amino acid OsCEP6.1 peptide showed that OsCEP6.1 had a negative role in regulating root and seedling growth, which was further confirmed by transgenic lines. Furthermore, the constitutive expression of OsCEP6.1 was sufficient to lead to panicle architecture and grain size variations. Scanning electron microscopy analysis revealed that the phenotypic variation of OsCEP6.1 overexpression lines resulted from decreased cell size but not reduced cell number. Moreover, starch accumulation was not significantly affected. Taken together, these data suggest that the OsCEP6.1 peptide might be involved in regulating the development of panicles and grains in rice.

Prioritization of candidate genes in "QTL-hotspot" region for drought tolerance in chickpea (Cicer arietinum L.)

A combination of two approaches, namely QTL analysis and gene enrichment analysis were used to identify candidate genes in the “QTL-hotspot” region for drought tolerance present on the Ca4 pseudomolecule in chickpea. In the first approach, a high-density bin map was developed using 53,223 single nucleotide polymorphisms (SNPs) identified in the recombinant inbred line (RIL) population of ICC 4958 (drought tolerant) and ICC 1882 (drought sensitive) cross. QTL analysis using recombination bins as markers along with the phenotyping data for 17 drought tolerance related traits obtained over 1–5 seasons and 1–5 locations split the “QTL-hotspot” region into two subregions namely “QTL-hotspot_a” (15 genes) and “QTL-hotspot_b” (11 genes). In the second approach, gene enrichment analysis using significant marker trait associations based on SNPs from the Ca4 pseudomolecule with the above mentioned phenotyping data, and the candidate genes from the refined “QTL-hotspot” region showed enrichment for 23 genes. Twelve genes were found common in both approaches. Functional validation using quantitative real-time PCR (qRT-PCR) indicated four promising candidate genes having functional implications on the effect of “QTL-hotspot” for drought tolerance in chickpea.

Candidate gene selection and detailed morphological evaluations of fs8.1, a quantitative trait locus controlling tomato fruit shape

fs8.1 is a major quantitative trait locus (QTL) that controls the elongated shape of tomato (Solanum lycopersicum) fruit. In this study, we fine-mapped the locus from a 47Mb to a 3.03Mb interval on the long arm of chromosome 8. Of the 122 annotated genes found in the fs8.1 region, 51 were expressed during floral development and six were differentially expressed in anthesis-stage ovaries in fs8.1 and wild-type (WT) lines. To identify possible nucleotide polymorphisms that may underlie the fruit shape phenotype, genome sequence analyses between tomato cultivars carrying the mutant and WT allele were conducted. This led to the identification of 158 single-nucleotide polymorphisms (SNPs) and five small indels in the fs8.1 interval, including 31 that could be associated with changes in gene expression or function. Morphological and histological analyses showed that the effects of fs8.1 were mainly on reproductive organ elongation by increasing cell number in the proximal-distal direction. Fruit weight was also increased in fs8.1 compared with WT, which was predominantly attributed to the increased fruit length. By combining the findings from the different analyses, we consider 12 likely candidate genes to underlie fs8.1, including Solyc08g062580 encoding a pentatricopeptide repeat protein, Solyc08g061560 encoding a putative orthologue of ERECTA, which is known to control fruit morphology and inflorescence architecture in Arabidopsis, Solyc08g061910 encoding a GTL2-like trihelix transcription factor, Solyc08g061930 encoding a protein that regulates cytokinin degradation, and two genes, Solyc08g062340 and Solyc08g062450, encoding 17.6kDa class II small heat-shock proteins.

Advanced backcross QTL analysis reveals complicated genetic control of rice grain shape in a japonica × indica cross

Grain shape is an important trait for improving rice yield. A number of quantitative trait loci (QTLs) for this trait have been identified by using primary F2 mapping populations and recombinant inbred lines, in which QTLs with a small effect are harder to detect than they would be in advanced generations. In this study, we developed two advanced mapping populations (chromosome segment substitution lines [CSSLs] and BC4F2 lines consisting of more than 2000 individuals) in the genetic backgrounds of two improved cultivars: a japonica cultivar (Koshihikari) with short, round grains, and an indica cultivar (IR64) with long, slender grains. We compared the ability of these materials to reveal QTLs for grain shape with that of an F2 population. Only 8 QTLs for grain length or grain width were detected in the F2 population, versus 47 in the CSSL population and 65 in the BC4F2 population. These results strongly suggest that advanced mapping populations can reveal QTLs for agronomic traits under complicated genetic control, and that DNA markers linked with the QTLs are useful for choosing superior allelic combinations to enhance grain shape in the Koshihikari and IR64 genetic backgrounds.

Discovery and mapping of genomic regions governing economically important traits of Basmati rice

BACKGROUND

Basmati rice, originated in the foothills of Himalayas, commands a premium price in the domestic and international markets on account of its unique quality traits. The complex genetic nature of unique traits of Basmati as well as tedious screening methodologies involved in quality testing have been serious constraints to breeding quality Basmati. In the present study, we made an attempt to identify the genomic regions governing unique traits of Basmati rice.

RESULTS

A total of 34 Quantitative Trait Loci (QTLs) for 16 economically important traits of Basmati rice were identified employing F(2), F(3) and Recombinant Inbred Line (RIL) mapping populations derived from a cross between Basmati370 (traditional Basmati) and Jaya (semi-dwarf rice). Out of which, 12 QTLs contributing to more than 15 % phenotypic variance were identified and considered as major effect QTLs. Four major effect QTLs coincide with the already known genes viz., sd1, GS3, alk1 and fgr governing plant height, grain size, alkali spreading value and aroma, respectively. For the remaining major QTLs, candidate genes were predicted as auxin response factor for filled grains, soluble starch synthase 3 for chalkiness and VQ domain containing protein for grain breadth and grain weight QTLs, based on the presence of non-synonymous single nucleotide polymorphism (SNPs) that were identified by comparing Basmati genome sequence with that of Nipponbare.

CONCLUSIONS

To the best of our knowledge, the current study is the first attempt ever made to carry out genome-wide mapping for the dissection of the genetic basis of economically important traits of Basmati rice. The promising QTLs controlling important traits in Basmati rice, identified in this study, can be used as candidates for future marker-assisted breeding.

A Single-Nucleotide Polymorphism of TaGS5 Gene Revealed its Association with Kernel Weight in Chinese Bread Wheat

TaGS5 genes were cloned from bread wheat and were physically mapped on 3AS and 3DS. Sequencing results revealed that a SNP was found in the sixth exon of TaGS5-A1 gene. The SNP resulted in amino acid change from alanine to serine at the 303 bp position of TaGS5-A1. These two alleles were designated as TaGS5-A1a (alanine at the 303 bp position) and TaGS5-A1b genes (serine at the 303-bp position). Analysis of association of TaGS5-A1 alleles with agronomic traits indicated that cultivars with TaGS5-A1b possessed wider kernel width and higher thousand-kernel weight, as well as significantly lower plant height, spike length, and internode length below spike than those of cultivars with TaGS5-A1a over 3 years. These trait differences between TaGS5-A1a and TaGS5-A1b genotypes were larger in landraces than in modern cultivars. This finding suggested that TaGS5 gene played an important role in modulating yield-related traits in the landraces, which possibly resulted from numerous superior genes gathering in modern cultivars after strong artificial selection. The preferred TaGS5-A1b haplotype underwent very strong positive selection in Chinese modern wheat breeding, but not in Chinese landraces. Expression analysis of the TaGS5-A1 gene indicated that TaGS5-A1b allele possessed significantly higher expression level than TaGS5-A1b allele in differently developmental seeds. This study could provide relatively superior genotype in view of agronomic traits in wheat breeding programs. Likewise, this study could offer important information for the dissection of molecular and genetic basis of yield-related traits.

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

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. 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.

QTL analysis on rice grain appearance quality, as exemplifying the typical events of transgenic or backcrossing breeding

Rice grain shape and yield are usually controlled by multiple quantitative trait loci (QTL). This study used a set of F9-10 recombinant inbred lines (RILs) derived from a cross of Huahui 3 (Bt/Xa21) and Zhongguoxiangdao, and detected 27 QTLs on ten rice chromosomes. Among them, twelve QTLs responsive for grain shape/ or yield were mostly reproducibly detected and had not yet been reported before. Interestingly, the two known genes involved in the materials, with one insect-resistant Bt gene, and the other disease-resistant Xa21 gene, were found to closely link the QTLs responsive for grain shape and weight. The Bt fragment insertion was firstly mapped on the chromosome 10 in Huahui 3 and may disrupt grain-related QTLs resulting in weaker yield performance in transgenic plants. The introgression of Xa21 gene by backcrossing from donor material into receptor Minghui 63 may also contain a donor linkage drag which included minor-effect QTL alleles positively affecting grain shape and yield. The QTL analysis on rice grain appearance quality exemplified the typical events of transgenic or backcrossing breeding. The QTL findings in this study will in the future facilitate the gene isolation and breeding application for improvement of rice grain shape and yield.

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

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. 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/Ca(2+)-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.

Genetic and molecular bases of yield-associated traits: a translational biology approach between rice and wheat

Transferring the knowledge bases between related species may assist in enlarging the yield potential of crop plants. Being cereals, rice and wheat share a high level of gene conservation; however, they differ at metabolic levels as a part of the environmental adaptation resulting in different yield capacities. This review focuses on the current understanding of genetic and molecular regulation of yield-associated traits in both crop species, highlights the similarities and differences and presents the putative knowledge gaps. We focus on the traits associated with phenology, photosynthesis, and assimilate partitioning and lodging resistance; the most important drivers of yield potential. Currently, there are large knowledge gaps in the genetic and molecular control of such major biological processes that can be filled in a translational biology approach in transferring genomics and genetics informations between rice and wheat.

Biparental resequencing coupled with SNP genotyping of a segregating population offers insights into the landscape of recombination and fixed genomic regions in elite soybean

Identification of genes underlying agronomic traits is dependent on the segregation of quantitative trait loci (QTL). A popular hypothesis is that elite lines are becoming increasingly similar to each other, resulting in large genomic regions with fixed genes. Here, we resequenced two parental modern elite soybean lines [ZhongHuang13 (ZH) and ZhongPin03-5373 (ZP)] and discovered 794,876 SNPs with reference to the published Williams82 genome. SNPs were distributed unevenly across the chromosomes, with 87.1% of SNPs clustering in 4.9% of the soybean reference genome. Most of the regions with a high density of SNP polymorphisms were located in the chromosome arms. Moreover, seven large regions that were highly similar between parental lines were identified. A GoldenGate SNP genotyping array was designed using 384 SNPs and the 254 recombinant inbred lines (F8) derived from the cross of ZP × ZH were genotyped. We constructed a genetic linkage map using a total of 485 molecular markers, including 313 SNPs from the array, 167 simple sequence repeats (SSRs), 4 expressed sequence tag-derived SSRs, and 1 insertion/deletion marker. The total length of the genetic map was 2594.34 cM, with an average marker spacing of 5.58 cM. Comparing physical and genetic distances, we found 20 hotspot and 14 coldspot regions of recombination. Our results suggest that the technology of resequencing of parental lines coupled with high-throughput SNP genotyping could efficiently bridge the genotyping gap and provide deep insights into the landscape of recombination and fixed genomic regions in biparental segregating populations of soybean with implications for fine mapping of QTL.

Identifying the genes underlying quantitative traits: a rationale for the QTN programme

The goal of identifying the genes or even nucleotides underlying quantitative and adaptive traits has been characterized as the 'QTN programme' and has recently come under severe criticism. Part of the reason for this criticism is that much of the QTN programme has asserted that finding the genes and nucleotides for adaptive and quantitative traits is a fundamental goal, without explaining why it is such a hallowed goal. Here we outline motivations for the QTN programme that offer general insight, regardless of whether QTNs are of large or small effect, and that aid our understanding of the mechanistic dynamics of adaptive evolution. We focus on five areas: (i) vertical integration of insight across different levels of biological organization, (ii) genetic parallelism and the role of pleiotropy in shaping evolutionary dynamics, (iii) understanding the forces maintaining genetic variation in populations, (iv) distinguishing between adaptation from standing variation and new mutation, and (v) the role of genomic architecture in facilitating adaptation. We argue that rather than abandoning the QTN programme, we should refocus our efforts on topics where molecular data will be the most effective for testing hypotheses about phenotypic evolution.

QTL mapping reveals a tight linkage between QTLs for grain weight and panicle spikelet number in rice

BACKGROUND

A number of QTL studies reported that one genomic region was associated with several traits, indicating linkage and/or pleiotropic effects. The question of pleiotropy versus tight linkage in these studies should be solved using a large-size population combined with high-density mapping. For example, if each of the 2 parents has a TGW-increasing or SPP-increasing QTL that is tightly linked, complementary combination of the 2 beneficial QTLs by using molecular markers could produce higher yields compared to the 2 parents. However, a pleiotropic QTL with opposite effects on the SPP and 1,000-grain weight (TGW) is complicated and challenging in terms of its application to rice improvement.

RESULTS

In this study, using a series of BC5F4 nearly isogenic lines (NILs) that were derived from a cross between the Korean japonica cultivar Hwayeongbyeo and Oryza rufipogon, we demonstrated that 2 QTLs, qSPP5 for spikelets per panicle (SPP) and qTGW5 for grain weight (TGW), are tightly linked on chromosome 5. Alleles from the O. rufipogon parent increased the SPP and decreased TGW in the Hwayeongbyeo background. qSPP5 was located within a 803-kb interval between the simple sequence repeat (SSR) markers INDEL3 and RM18076. Based on the map position, qTGW5 seemed to be the same gene as qSW5, which controls grain morphology. The additive effect of the O. rufipogon allele at qSPP5 was 10-15 SPP, and 33.0% of the phenotypic variance could be explained by the segregation of the SSR marker RM18058. Yield trials with BC5F4 NILs showed that lines that contained a homozygous O. rufipogon introgression at the qSPP5 region out-yielded sibling NILs that contained Hwayeongbyeo DNA by 15.3% and out-yielded the Hwayeongbyeo parent by 7.3%.

CONCLUSION

Based on the finding that the O. rufipogon allele for the SPP was beneficial in the japonica and indica cultivar backgrounds, the qSPP5 allele could be valuable for improving rice yields. In addition, the NIL populations and molecular markers are useful for cloning qSPP5.

Characterization of the quantitative trait locus OilA1 for oil content in Brassica napus

Increasing seed oil content has become one of the most important breeding criteria in rapeseed (Brassica napus). However, oil content is a complex quantitative trait. QTL mapping in a double haploid population (SG population) emerging from a cross between a German (Sollux) and Chinese (Gaoyou) cultivars revealed one QTL for oil content on linkage group A1 (OilA1), which was mapped to a 17 cM genetic interval. To further validate and characterize the OilA1, we constructed a high-resolution map using B. rapa sequence resources and developed a set of near-isogenic lines (NILs) by employing a DH line SG-DH267 as donor and Chinese parent Gaoyou as recurrent background. The results showed highly conserved synteny order between B. rapa and B. napus within the linkage group A1 and revealed a possible centromere region between two markers ZAASA1-38 and NTP3 (2.5 cM). OilA1 was firstly validated by 250 BC5F2 plants and was confirmed in a 10.6 cM interval between the markers ZAASA1-47 and ZAASA1-77. Further substitution mapping was conducted by using two generations of QTL-NILs, 283 lines from eight BC5F3:4 families and 428 plants from six BC5F4 sub-NILs and thus narrowed the OilA1 interval to 6.9 cM and 4.3 cM (1.4 Mb), respectively. Field investigations with two replications using homozygous BC5F3:4 sister sub-NILs indicated that NILs, which carry a Sollux chromosome segment across the target region showed significant higher oil content (1.26 %, p < 0.001) than their sister NILs containing Gaoyou chromosome. The OilA1 locus is of particular interest for breeding purpose in China because 80 % of Chinese cultivars do not carry this desirable allele.

GS6, a member of the GRAS gene family, negatively regulates grain size in rice

Grain size is an important yield-related trait in rice. Intensive artificial selection for grain size during domestication is evidenced by the larger grains of most of today's cultivars compared with their wild relatives. However, the molecular genetic control of rice grain size is still not well characterized. Here, we report the identification and cloning of Grain Size 6 (GS6), which plays an important role in reducing grain size in rice. A premature stop at the +348 position in the coding sequence (CDS) of GS6 increased grain width and weight significantly. Alignment of the CDS regions of GS6 in 90 rice materials revealed three GS6 alleles. Most japonica varieties (95%) harbor the Type I haplotype, and 62.9% of indica varieties harbor the Type II haplotype. Association analysis revealed that the Type I haplotype tends to increase the width and weight of grains more than either of the Type II or Type III haplotypes. Further investigation of genetic diversity and the evolutionary mechanisms of GS6 showed that the GS6 gene was strongly selected in japonica cultivars. In addition, a "ggc" repeat region identified in the region that encodes the GRAS domain of GS6 played an important historic role in the domestication of grain size in rice. Knowledge of the function of GS6 might aid efforts to elucidate the molecular mechanisms that control grain development and evolution in rice plants, and could facilitate the genetic improvement of rice yield.

Genetic bases of rice grain shape: so many genes, so little known

Rice (Oryza sativa) grain shape is a key determinant of grain yield and market values. Facilitated by advancements in genomics and various molecular markers, more than 400 quantitative trait loci (QTLs) associated with rice grain traits have been identified. In this review, we examine the genetic bases of rice grain shape, focusing on the protein products of 13 genes that have been cloned and the chromosome locations of 15 QTLs that have been fine mapped. Although more genes affecting grain traits are likely to be cloned in the near future, characterizing their functions at the biochemical level and applying these molecular data to rice breeding programs will be a more challenging task.

Kernel elongation in rice

Kernel elongation after cooking is an important character of fine rice and most rice consumers prefer length-wise elongation. Although improvement of aromatic rice began early in the 1970s, until now the mechanisms and genetics of kernel elongation has remained unrevealed. Kernel elongation is considered as a physical phenomenon and is influenced by several physicochemical and genetic factors, including genotypes, aging temperature, aging time, water uptake, amylose content and gelatinization temperature. Recently the complete genetic map of fine rice has been created and the gene responsible for kernel length identified; moreover, this gene is tightly linked with the cooked kernel elongation trait. Several molecular markers linked with cooked kernel elongation have been developed. These tools will be helpful for the improvement of this important trait. For the proper study of cooked kernel elongation of rice, this review paper will provide the basis and directional materials for further studies.

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 characterization of quantitative trait loci for mesocotyl elongation in rice (Oryza sativa L.)

Mesocotyl elongation is an important trait for seedling emergence in direct-seeding cultivation in rice. In this study, a backcross inbred line (BIL) population from a cross between Kasalath and Nipponbare was employed to map quantitative trait loci (QTLs) for mesocotyl elongation. A total of 5 QTLs for mesocotyl length were identified on chromosomes 1, 3, 7, 9, and 12 in 2 independent experiments. At all QTL, the Kasalath alleles contributed to an increase in mesocotyl length. Two QTLs (qMel-1 and qMel-3) on chromosomes 1 and 3 were consistently detected in both experiments. To fine map the QTLs, a cross was made between 2 chromosome segment substitution lines (CSSL-6 and CSSL-15), each harboring the Kasalath allele across the qMel-1 and qMel-3 regions, and an F2:3 population was developed. A two-way ANOVA indicated that no epistatic interaction was detected between the 2 QTLs in the F2 population (P = 0.31). Moreover, analysis of two F3 near-isogenic lines (NILs) derived from the same cross, indicated that the 2 QTLs act additively in distinct or complementary pathways in controlling mesocotyl elongation. Substitution mapping indicated that the qMel-1 QTL was located between the 2 SSR markers RM5448 and RM5310, which are 3,799-kb apart, and that the qMel-3 QTL was located between the 2 SSR markers RM3513 and RM1238, which are 6,964-kb apart. To our knowledge, this is the first report to fine-map QTLs for mesocotyl elongation and to analyze their interaction.

The novel quantitative trait locus GL3.1 controls rice grain size and yield by regulating Cyclin-T1;3

Increased crop yields are required to support rapid population growth worldwide. Grain weight is a key component of rice yield, but the underlying molecular mechanisms that control it remain elusive. Here, we report the cloning and characterization of a new quantitative trait locus (QTL) for the control of rice grain length, weight and yield. This locus, GL3.1, encodes a protein phosphatase kelch (PPKL) family - Ser/Thr phosphatase. GL3.1 is a member of the large grain WY3 variety, which is associated with weaker dephosphorylation activity than the small grain FAZ1 variety. GL3.1-WY3 influences protein phosphorylation in the spikelet to accelerate cell division, thereby resulting in longer grains and higher yields. Further studies have shown that GL3.1 directly dephosphorylates its substrate, Cyclin-T1;3, which has only been rarely studied in plants. The downregulation of Cyclin-T1;3 in rice resulted in a shorter grain, which indicates a novel function for Cyclin-T in cell cycle regulation. Our findings suggest a new mechanism for the regulation of grain size and yield that is driven through a novel phosphatase-mediated process that affects the phosphorylation of Cyclin-T1;3 during cell cycle progression, and thus provide new insight into the mechanisms underlying crop seed development. We bred a new variety containing the natural GL3.1 allele that demonstrated increased grain yield, which indicates that GL3.1 is a powerful tool for breeding high-yield crops.

Can heterotrimeric G proteins help to feed the world?

Recently, two important yield quantitative trait loci (QTLs), GS3 and DEP1, have been cloned in rice (Oryza sativa). Although their relationship has not been established in the 'rice literature', a recent report identified them as heterotrimeric G protein γ subunits. This identification has profound consequences for our current understanding of both QTLs and the plant G protein signaling network and this opinion article discusses how manipulation of G protein signaling may lead to yield improvements in rice and other crop species. Finally, a mechanistic model to explain the seemingly conflicting phenotypes produced by different GS3 and DEP1 alleles is proposed.