Quantitative trait loci (QTL) analysis for rice grain width and fine mapping of an identified QTL allele gw-5 in a recombination hotspot region on chromosome 5

Allelopathic Molecular Mechanisms of the Two Main Allelochemicals in Sweet Potato

Sweet potato (Ipomoea batatas L.) is one of the most important global food crops. This crop exhibits excellent allelopathic potential against various weeds, but its allelopathic mechanism at the molecular level is unclear. Therefore, metabolomic and transcriptomic analyses were performed to explore the allelopathic effects, metabolic pathway, and associated genes for two major compounds with allelopathic activity, palmitic acid and linoleic acid. The sweet potato variety Ningshu 25 was employed in the current study. The results showed that palmitic acid and linoleic acid had strong allelopathic effects on seed germination, plant growth, antioxidant enzyme activity, and chlorophyll content of two weeds Digitaria sanguinalis and Bidens pilosa. The content of the two targeted metabolites was affected by different environmental conditions and was significantly increased under low temperature (15 °C). Five metabolic pathways involved in the two targeted metabolites of fatty acids were found: fatty acid biosynthesis, fatty acid elongation, fatty acid degradation, biosynthesis of cutin, suberine, and wax, and the linoleic acid metabolism pathway. The synthesis of palmitic acid is significantly enriched in the biosynthesis pathways of fatty acids, cutin, suberine, and wax, and the synthesis of linoleic acid is significantly enriched in the linoleic acid metabolism pathway. Under different environmental conditions, there were three key genes expressed-g4988, g11881, and g19673-located in the biosynthesis pathways of cutin, suberine, and wax; four key genes expressed-g31191, g60956, g49811, and g59542-located in the biosynthesis pathway of fatty acids; and six key expressed genes-g26575, g24787, g23517, g57649, g58562, and g4314-located in biosynthesis pathway of linoleic acid, respectively. Our study advances understanding of the molecular mechanisms behind allelopathic traits in sweet potato and provides a set of candidate genes for use in improving allelopathic potential in sweet potato germplasm resources.

Molecular mechanisms controlling grain size and weight and their biotechnological breeding applications in maize and other cereal crops

BACKGROUND

Cereal crops are a primary energy source for humans. Grain size and weight affect both evolutionary fitness and grain yield of cereals. Although studies on gene mining and molecular mechanisms controlling grain size and weight are constantly emerging in cereal crops, only a few systematic reviews on the underlying molecular mechanisms and their breeding applications are available so far.

AIM OF REVIEW

This review provides a general state-of-the-art overview of molecular mechanisms and targeted strategies for improving grain size and weight of cereals as well as insights for future yield-improving biotechnology-assisted breeding.

KEY SCIENTIFIC CONCEPTS OF REVIEW

In this review, the evolution of research on grain size and weight over the last 20 years is traced based on a bibliometric analysis of 1158 publications and the main signaling pathways and transcriptional factors involved are summarized. In addition, the roles of post-transcriptional regulation and photosynthetic product accumulation affecting grain size and weight in maize and rice are outlined. State-of-the-art strategies for discovering novel genes related to grain size and weight in maize and other cereal crops as well as advanced breeding biotechnology strategies being used for improving yield including marker-assisted selection, genomic selection, transgenic breeding, and genome editing are also discussed.

When Size Matters: New Insights on How Seed Size Can Contribute to the Early Stages of Plant Development

The seed habit is the most complex and successful method of sexual reproduction in vascular plants. It represents a remarkable moment in the evolution of plants that afterward spread on land. In particular, seed size had a pivotal role in evolutionary success and agronomic traits, especially in the field of crop domestication. Given that crop seeds constitute one of the primary products for consumption, it follows that seed size represents a fundamental determinant of crop yield. This adaptative feature is strictly controlled by genetic traits from both maternal and zygotic tissues, although seed development and growth are also affected by environmental cues. Despite being a highly exploited topic for both basic and applied research, there are still many issues to be elucidated for developmental biology as well as for agronomic science. This review addresses a number of open questions related to cues that influence seed growth and size and how they influence seed germination. Moreover, new insights on the genetic-molecular control of this adaptive trait are presented.

Discovering New QTNs and Candidate Genes Associated with Rice-Grain-Related Traits within a Collection of Northeast Core Set and Rice Landraces

Grain-related traits are pivotal in rice cultivation, influencing yield and consumer preference. The complex inheritance of these traits, involving multiple alleles contributing to their expression, poses challenges in breeding. To address these challenges, a multi-locus genome-wide association study (ML-GWAS) utilizing 35,286 high-quality single-nucleotide polymorphisms (SNPs) was conducted. Our study utilized an association panel comprising 483 rice genotypes sourced from a northeast core set and a landraces set collected from various regions in India. Forty quantitative trait nucleotides (QTNs) were identified, associated with four grain-related traits: grain length (GL), grain width (GW), grain aroma (Aro), and length-width ratio (LWR). Notably, 16 QTNs were simultaneously identified using two ML-GWAS methods, distributed across multiple chromosomes. Nearly 258 genes were found near the 16 significant QTNs. Gene annotation study revealed that sixty of these genes exhibited elevated expression levels in specific tissues and were implicated in pathways influencing grain quality. Gene ontology (GO), trait ontology (TO), and enrichment analysis pinpointed 60 candidate genes (CGs) enriched in relevant GO terms. Among them, LOC_Os05g06470, LOC_Os06g06080, LOC_Os08g43470, and LOC_Os03g53110 were confirmed as key contributors to GL, GW, Aro, and LWR. Insights from QTNs and CGs illuminate rice trait regulation and genetic connections, offering potential targets for future studies.

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.

Joint analysis of phenotype-effect-generation identifies loci associated with grain quality traits in rice hybrids

Genetic improvement of grain quality is more challenging in hybrid rice than in inbred rice due to additional nonadditive effects such as dominance. Here, we describe a pipeline developed for joint analysis of phenotypes, effects, and generations (JPEG). As a demonstration, we analyze 12 grain quality traits of 113 inbred lines (male parents), five tester lines (female parents), and 565 (113×5) of their hybrids. We sequence the parents for single nucleotide polymorphisms calling and infer the genotypes of the hybrids. Genome-wide association studies with JPEG identify 128 loci associated with at least one of the 12 traits, including 44, 97, and 13 loci with additive effects, dominant effects, and both additive and dominant effects, respectively. These loci together explain more than 30% of the genetic variation in hybrid performance for each of the traits. The JEPG statistical pipeline can help to identify superior crosses for breeding rice hybrids with improved grain quality.

Identification of Potential QTLs Related to Grain Size in Rice

Rice is a major crop, providing calories and food for most of the world's population. Currently, the global population is rapidly increasing, and securing a yield of rice that can satisfy everyone is an ongoing challenge. The yield of rice can be increased by controlling 1000-grain weight as one of the important determining factors. Grain length, grain width, grain thickness, and 1000-grain weight, which determine grain size, are controlled by QTLs. To identify QTLs related to grain size, we screened and then mapped 88 RIL individuals derived from a cross between JJ625LG, which has a long grain size, long spindle-shaped grains, and low 1000-grain weight, and Namchan, which has short grains with round shape and heavy 1000-grain weight. In 2021 and 2022, 511 SNP markers were used to map QTLs related to grain size to a physical map. The QTLs found to be related to grain size are evenly distributed on chromosomes 2, 3, 5, 10, and 11. The mapping results also show that the QTLs qGl3-2, qRlw3, and qRlw3-2 of chromosome 3, and qGt5 and qRlw5 of chromosome 5 are, respectively, associated with GS3 and qSW5, which are the major genes previously cloned and found to be related to grain size. In addition, qGw10 and qGw10-1, which were additionally detected in this study, were found to be associated with Os10g0525200 (OsCPq10), a potential candidate gene involved in controlling grain size. This gene codes for a cytochrome P450 family protein and is reported to have a positive effect on grain size by interacting with proteins related to mechanisms determining grain size. In particular, OsCPq10 was screened in the same identified QTL region for 2 consecutive years, which is expected to have a positive effect on grain size. These results will be helpful for breeding elite rice cultivars with high yields through additional fine mapping related to grain size.

Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress

Elevated nighttime temperatures resulting from climate change significantly impact the rice crop worldwide. The rice (Oryza sativa L.) plant is highly sensitive to high nighttime temperature (HNT) during grain-filling (reproductive stage). HNT stress negatively affects grain quality traits and has a major impact on the value of the harvested rice crop. In addition, along with grain dimensions determining rice grain market classes, the grain appearance and quality traits determine the rice grain market value. During the last few years, there has been a major concern for rice growers and the rice industry over the prevalence of rice grains opacity and the reduction of grain dimensions affected by HNT stress. Hence, the improvement of heat-stress tolerance to maintain grain quality of the rice crop under HNT stress will bolster future rice value in the market. In this study, 185 F₁₂-recombinant inbred lines (RILs) derived from two US rice cultivars, Cypress (HNT-tolerant) and LaGrue (HNT-sensitive) were screened for the grain quality traits grain length (GL), grain width (GW), and percent chalkiness (%chalk) under control and HNT stress conditions and evaluated to identify the genomic regions associated with the grain quality traits. In total, there were 15 QTLs identified; 6 QTLs represented under control condition explaining 3.33% to 8.27% of the phenotypic variation, with additive effects ranging from - 0.99 to 0.0267 on six chromosomes and 9 QTLs represented under HNT stress elucidating 6.39 to 51.53% of the phenotypic variation, with additive effects ranging from - 8.8 to 0.028 on nine chromosomes for GL, GW, and % chalk. These 15 QTLs were further characterized and scanned for natural genetic variation in a japonica diversity panel (JDP) to identify candidate genes for GL, GW, and %chalk. We found 6160 high impact single nucleotide polymorphisms (SNPs) characterized as such depending on their type, region, functional class, position, and proximity to the gene and/or gene features, and 149 differentially expressed genes (DEGs) in the 51 Mbp genomic region comprising of the 15 QTLs. Out of which, 11 potential candidate genes showed high impact SNP associations. Therefore, the analysis of the mapped QTLs and their genetic dissection in the US grown Japonica rice genotypes at genomic and transcriptomic levels provide deep insights into genetic variation beneficial to rice breeders and geneticists for understanding the mechanisms related to grain quality under heat stress in rice.

A Systemic Investigation of Genetic Architecture and Gene Resources Controlling Kernel Size-Related Traits in Maize

Grain yield is the most critical and complex quantitative trait in maize. Kernel length (KL), kernel width (KW), kernel thickness (KT) and hundred-kernel weight (HKW) associated with kernel size are essential components of yield-related traits in maize. With the extensive use of quantitative trait locus (QTL) mapping and genome-wide association study (GWAS) analyses, thousands of QTLs and quantitative trait nucleotides (QTNs) have been discovered for controlling these traits. However, only some of them have been cloned and successfully utilized in breeding programs. In this study, we exhaustively collected reported genes, QTLs and QTNs associated with the four traits, performed cluster identification of QTLs and QTNs, then combined QTL and QTN clusters to detect consensus hotspot regions. In total, 31 hotspots were identified for kernel size-related traits. Their candidate genes were predicted to be related to well-known pathways regulating the kernel developmental process. The identified hotspots can be further explored for fine mapping and candidate gene validation. Finally, we provided a strategy for high yield and quality maize. This study will not only facilitate causal genes cloning, but also guide the breeding practice for maize.

Identification of QTLs for rice grain size and weight by high-throughput SNP markers in the IR64 x Sadri population

Grain appearance is one of the most important attributes of rice. It is determined by grain size, shape, and weight, which in turn influences the rice yield and market value. In this study, QTLs for grain length, grain width, grain length/width ratio, and grain weight were mapped using the high-throughput indica/indica SNP platforms. The population of the mega indica variety IR64 and the high-quality aromatic variety Sadri from Iran was phenotyped. Based on this phenotypic data, plants of 94 F2:3 families including both parents were selected. A linkage map analysis of 210 SNP markers identified 14 QTLs controlling the grain length, grain width, length/width ratio, and 1,000 grain weight. Among these 14, one important region containing the QTLs for all the four studies’ traits was mapped on chromosome 8. It was derived from Sadri for the decreased length/width ratio and increased grain weight. This study demonstrated the speed and efficiency in using multiplex SNP genotyping for QTL analysis. Moreover, this study identified four novel QTLs (qGL8, qTGW8, qLWR8, and qGW8) sharing the same position on chromosome 8 which were linked with grain quality characteristics between one indica and one aromatic variety. It will enable more precise marker-assisted selection for grain weight, shape, and size. Further in-depth studies are required to dissect this region of interest and identify the related gene(s).

Fine Mapping of qTGW7b, a Minor Effect QTL for Grain Weight in Rice (Oryza sativa L.)

Grain weight is a key trait that determines rice quality and yield, and it is primarily controlled by quantitative trait loci (QTL). Recently, attention has been paid to minor QTLs. A minor effect QTL qTGW7 that controls grain weight was previously identified in a set of chromosomal fragment substitution lines (CSSLs) derived from Nipponbare (NPB)/93-11. Compared to NPB, the single segment substitution line (SSSL) N83 carrying the qTGW7 introgression exhibited an increase in grain length and width and a 4.5% increase in grain weight. Meanwhile, N83 was backcrossed to NPB to create a separating population, qTGW7b, a QTL distinct from qTGW7, which was detected between markers G31 and G32. Twelve near-isogenic lines (NILs) from the BC9F3 population and progeny of five NILs from the BC9F3:4 population were genotyped and phenotyped, resulting in the fine mapping of the minor effect QTL qTGW7b to the approximately 86.2-kb region between markers G72 and G32. Further sequence comparisons and expression analysis confirmed that five genes, including Os07g39370, Os07g39430, Os07g39440, Os07g39450, and Os07g39480, were considered as the candidate genes underlying qTGW7b. These results provide a crucial foundation for further cloning of qTGW7b and molecular breeding design in rice.

Genotyping-by-Sequencing Based Investigation of Population Structure and Genome Wide Association Studies for Seven Agronomically Important Traits in a Set of 346 Oryza rufipogon Accessions

Being one of the most important staple dietary constituents globally, genetic enhancement of cultivated rice for yield, agronomically important traits is of substantial importance. Even though the climatic factors and crop management practices impact complex traits like yield immensely, the contribution of variation by underlying genetic factors surpasses them all. Previous studies have highlighted the importance of utilizing exotic germplasm, landraces in enhancing the diversity of gene pool, leading to better selections and thus superior cultivars. Thus, to fully exploit the potential of progenitor of Asian cultivated rice for productivity related traits, genome wide association study (GWAS) for seven agronomically important traits was conducted on a panel of 346 O. rufipogon accessions using a set of 15,083 high-quality single nucleotide polymorphic markers. The phenotypic data analysis indicated large continuous variation for all the traits under study, with a significant negative correlation observed between grain parameters and agronomic parameters like plant height, culm thickness. The presence of 74.28% admixtures in the panel as revealed by investigating population structure indicated the panel to be very poorly genetically differentiated, with rapid LD decay. The genome-wide association analyses revealed a total of 47 strong MTAs with 19 SNPs located in/close to previously reported QTL/genic regions providing a positive analytic proof for our studies. The allelic differences of significant MTAs were found to be statistically significant at 34 genomic regions. A total of 51 O. rufipogon accessions harboured combination of superior alleles and thus serve as potential candidates for accelerating rice breeding programs. The present study identified 27 novel SNPs to be significantly associated with different traits. Allelic differences between cultivated and wild rice at significant MTAs determined superior alleles to be absent at 12 positions implying substantial scope of improvement by their targeted introgression into cultivars. Introgression of novel significant genomic regions into breeder's pool would broaden the genetic base of cultivated rice, thus making the crop more resilient.

KNOX II transcription factor HOS59 functions in regulating rice grain size

Plant Knotted1-like homeobox (KNOX) genes encode homeodomain-containing transcription factors. In rice (Oryza sativa L.), little is known about the downstream target genes of KNOX Class II subfamily proteins. Here we generated chromatin immunoprecipitation (ChIP)-sequencing datasets for HOS59, a member of the rice KNOX Class II subfamily, and characterized the genome-wide binding sites of HOS59. We conducted trait ontology (TO) analysis of 9705 identified downstream target genes, and found that multiple TO terms are related to plant structure morphology and stress traits. ChIP-quantitative PCR (qPCR) was conducted to validate some key target genes. Meanwhile, our IP-MS datasets showed that HOS59 was closely associated with BELL family proteins, some grain size regulators (OsSPL13, OsSPL16, OsSPL18, SLG, etc.), and some epigenetic modification factors such as OsAGO4α and OsAGO4β, proteins involved in small interfering RNA-mediated gene silencing. Furthermore, we employed CRISPR/Cas9 editing and transgenic approaches to generate hos59 mutants and overexpression lines, respectively. Compared with wild-type plants, the hos59 mutants have longer grains and increased glume cell length, a loose plant architecture, and drooping leaves, while the overexpression lines showed smaller grain size, erect leaves, and lower plant height. The qRT-PCR results showed that mutation of the HOS59 gene led to upregulation of some grain size-related genes such as OsSPL13, OsSPL18, and PGL2. In summary, our results indicate that HOS59 may be a repressor of the downstream target genes, negatively regulating glume cell length, rice grain size, plant architecture, etc. The identified downstream target genes and possible interaction proteins of HOS59 improve our understanding of the KNOX regulatory networks.

Estimation of genetic variance contributed by a quantitative trait locus: correcting the bias associated with significance tests

The Beavis effect in quantitative trait locus (QTL) mapping describes a phenomenon that the estimated effect size of a statistically significant QTL (measured by the QTL variance) is greater than the true effect size of the QTL if the sample size is not sufficiently large. This is a typical example of the Winners' curse applied to molecular quantitative genetics. Theoretical evaluation and correction for the Winners' curse have been studied for interval mapping. However, similar technologies have not been available for current models of QTL mapping and genome-wide association studies where a polygene is often included in the linear mixed models to control the genetic background effect. In this study, we developed the theory of the Beavis effect in a linear mixed model using a truncated noncentral Chi-square distribution. We equated the observed Wald test statistic of a significant QTL to the expectation of a truncated noncentral Chi-square distribution to obtain a bias-corrected estimate of the QTL variance. The results are validated from replicated Monte Carlo simulation experiments. We applied the new method to the grain width (GW) trait of a rice population consisting of 524 homozygous varieties with over 300 k single nucleotide polymorphism markers. Two loci were identified and the estimated QTL heritability were corrected for the Beavis effect. Bias correction for the larger QTL on chromosome 5 (GW5) with an estimated heritability of 12% did not change the QTL heritability due to the extremely large test score and estimated QTL effect. The smaller QTL on chromosome 9 (GW9) had an estimated QTL heritability of 9% reduced to 6% after the bias-correction.

Effects of Grain Shape Genes Editing on Appearance Quality of Erect-Panicle Geng/Japonica Rice

Long grain geng/japonica rice has a higher market preference due its excellent appearance quality. The dense and erect-panicle 1 (dep1) gene has been widely used in the breeding of high-yielding geng/japonica rice cultivars in China. However, this gene causes short and round grain shape thus making it less attractive in global rice markets. Therefore, breeding of high-yielding long-grain geng/japonica rice cultivars by incorporating dep1 with major-effect grain shape gene is of high priority in rice industry. Up to now, multiple grain shape genes' effect mechanism has been clearly elaborated, however, under the background of erect-panicle geng/japonica rice, the effect of major grain shape genes on the appearance quality need to be further clarified, as detailed reports are limited. Utilizing CRISPR/Cas9 technology, a series of near-isogenic lines (NILs) (YF47^dep1-gw8, YF47^dep1-gs3, YF47^dep1-gl7, YF47^dep1-qgl3 and YF47^dep1-tgw6) in Yanfeng 47(YF47^dep1) background were created. Grain appearance and yield components analysis showed that: (1) All NILs' grain length to width ratio was significantly increased compared to that of YF47^dep1, excepted YF47^dep1-gs3, (2) The chalkiness degree was significantly reduced in all of the NILs, (3) In all of the NILs, YF47^dep1-gw8 grains exhibited the greatest length to width ratio and the lowest chalkiness degree, (4) The composition of glume cells and filling characteristics of the endosperm were two key factors contributing grain shape and grain chalk variations, respectively, and v) Owning to a substantial increase in the thousand grain weight, the yields of YF47^dep1-gs3 and YF47^dep1-tgw6 were significantly higher than that of YF47^dep1, whereas YF47^dep1-qgl3 exhibited the lowest yield because of a dramatic decrease in the effective panicle number and thousand grain weight. All the results revealed that pyramiding dep1 with major-effect grain shape alleles was an effective approach to improving the appearance quality of erect-panicle geng/japonica rice, owning to both of the appearance quality and yield improvement, GS3 and TGW6 alleles can be applied directly for breeding long-grain shape geng/japonica rice, and editing GW8 resulted in excellent appearance quality but low yield, therefore, this gene would be difficult to use directly but can be considered as the core germplasm resource.

Understanding the fundamentals of microbial remediation with emphasize on metabolomics

The post-genomic tool metabolomics is a great advancement in science and technology which acquires novel strategies and pathways to analyze various biological compounds. Metabolomics aids in retrieving the qualitative and quantitative data from the various biological system. The current review is focused on the application of metabolomics in bioremediation and helps to focus on the xenobiotic compounds which are discharged into the environment and have long term impact. The microbial based biodegradation can be effectively used along with the combination of metabolomic approach for a better understanding of the breakdown of certain recalcitrant. Additionally, this review also discusses the candidate gene approach which helps to comprehend the functional analysis of microbial genes in response to different contaminants. Therefore, this review intends to discuss the metabolomics in bioremediation by studying the complete set of metabolites involved during the process of degradation and their interaction with the environment.

Development of Chromosome Segment Substitution Lines (CSSLs) Derived from Guangxi Wild Rice (Oryza rufipogon Griff.) under Rice (Oryza sativa L.) Background and the Identification of QTLs for Plant Architecture, Agronomic Traits and Cold Tolerance

Common wild rice contains valuable resources of novel alleles for rice improvement. It is well known that genetic populations provide the basis for a wide range of genetic and genomic studies. In particular, chromosome segment substitution lines (CSSLs) ais a powerful tool for fine mapping of quantitative traits, new gene discovery and marker-assisted breeding. In this study, 132 CSSLs were developed from a cultivated rice (Oryza sativa) cultivar (93-11) and common wild rice (Oryza rufipogon Griff. DP30) by selfing-crossing, backcrossing and marker-assisted selection (MAS). Based on the high-throughput sequencing of the 93-11 and DP30, 285 pairs of Insertion-deletions (InDel) markers were selected with an average distance of 1.23 Mb. The length of this DP30-CSSLs library was 536.4 cM. The coverage rate of substitution lines cumulatively overlapping the whole genome of DP30 was about 91.55%. DP30-CSSLs were used to analyze the variation for 17 traits leading to the detection of 36 quantitative trait loci (QTLs) with significant phenotypic effects. A cold-tolerant line (RZ) was selected to construct a secondary mapping F2 population, which revealed that qCT2.1 is in the 1.7 Mb region of chromosome 2. These CSSLs may, therefore, provide powerful tools for genome wide large-scale gene discovery in wild rice. This research will also facilitate fine mapping and cloning of QTLs and genome-wide study of wild rice. Moreover, these CSSLs will provide a foundation for rice variety improvement.

Genome-wide analysis of polymorphisms identified domestication-associated long low-diversity region carrying important rice grain size/weight quantitative trait loci

Rice grain size and weight are major determinants of grain quality and yield and so have been under rigorous selection since domestication. However, the genetic basis for contrasting grain size/weight trait among Indian germplasms and their association with domestication-driven evolution is not well understood. In this study, two long (LGG) and two short grain (SGG) genotypes were resequenced. LGG (LGR and PB 1121) differentiated from SGG (Sonasal and Bindli) by 504 439 single nucleotide polymorphisms (SNPs) and 78 166 insertion-and-deletion polymorphisms. The LRK gene cluster was different and a truncation mutation in the LRK8 kinase domain was associated with LGG. Phylogeny with 3000 diverse rice accessions revealed that the four sequenced genotypes belonged to the japonica group and were at the edge of the clades indicating them to be the potential source of genetic diversity available in Indian rice germplasm. Six SNPs were significantly associated with grain size/weight and the top four of these could be validated in mapping a population, suggesting this study as a valuable resource for high-throughput genotyping. A contiguous long low-diversity region (LDR) of approximately 6 Mb carrying a major grain weight quantitative trait loci (harbouring OsTOR gene) was identified on Chromosome 5. This LDR was identified as an evolutionary important site with significant positive selection and multiple selection sweeps, and showed association with many domestication-related traits, including grain size/weight. The aus population retained more allelic variations in the LDR than the japonica and indica populations, suggesting it to be one of the divergence loci. All the data and analyses can be accessed from the RiceSzWtBase database.

Marker-assisted selection for grain number and yield-related traits of rice (Oryza sativa L.)

Continuous rise in the human population has resulted in an upsurge in food demand, which in turn demand grain yield enhancement of cereal crops, including rice. Rice yield is estimated via the number of tillers, grain number per panicles, and the number of spikes present per panicle. Marker-assisted selection (MAS) serve as one of the best ways to introduce QTLs/gene associated with yield in the rice plant. MAS has also been employed effectively in dissecting several other complex agricultural traits, for instance, drought, cold tolerance, salinity, etc. in rice plants. Thus, in this review, authors attempted to collect information about various genes/QTLs associated with high yield, including grain number, in rice and how different scheme of MAS can be employed to introduce them in rice (Oryza sativa L.) plant, which in turn will enhance rice yield. Information obtained to date suggest that, numerous QTLs, e.g., Gn1a, Dep1, associated with grain number and yield-related traits, have been identified either via mapping or cloning approaches. These QTLs have been successfully introduced into rice plants using various schemes of MAS for grain yield enhancement in rice. However, sometimes, MAS does not perform well in breeding, which might be due to lack of resources, skilled labors, reliable markers, and high costs associated with MAS. Thus, by overcoming these problems, we can enhance the application of MAS in plant breeding, which, in turn, may help us in increasing yield, which subsequently may help in bridging the gap between demand and supply of food for the continuously growing population.

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.

Genotyping-by-sequencing and multilocation evaluation of two interspecific backcross populations identify QTLs for yield-related traits in pigeonpea

This study has identified single-nucleotide polymorphism (SNP) markers associated with nine yield-related traits in pigeonpea by using two backcross populations (BP) developed through interspecific crosses and evaluating them at two locations and 3 years. In both the populations, markers have shown strong segregation distortion; therefore, a quantitative trait locus (QTL) mapping mixed model was used. A total of 86 QTLs explaining 12-21% phenotypic variation were detected in BP-1. On the other hand, 107 QTLs explaining 11-29% phenotypic variation were detected in BP-2. Although most QTLs were environment and trait specific, few stable and consistent QTLs were also detected. Interestingly, 11 QTLs in BP-2 were associated with more than one trait. Among these QTLs, eight QTLs associated with days to 50% flowering and days to 75% maturity were located on CcLG07. One SNP "S7_14185076" marker in BP-2 population has been found associated with four traits, namely days to 50% flowering, days to 75% maturity, primary branches per plant and secondary branches per plant with positive additive effect. Hence, the present study has not only identified QTLs for yield-related traits, but also discovered novel alleles from wild species, which can be used for improvement of traits through genomics-assisted breeding.

Rice quality: How is it defined by consumers, industry, food scientists, and geneticists?

BACKGROUND

Quality is a powerful engine in rice value chain upgrading. However, there is no consensus on how "rice quality" should be defined and measured in the rice sector.

SCOPE AND APPROACH

We adopt a Lancasterian definition of rice quality as a bundle of intrinsic and extrinsic attributes. We then review how rice quality is (i) perceived and defined by consumers and industry stakeholders in rice value chains in Southeast and South Asia; (ii) measured and defined by food technologists; and (iii) predicted through genetics.

KEY FINDINGS AND CONCLUSIONS

Consumers are heterogeneous with respect to their perceived differentiation of rice quality among regions, countries, cities, and urbanization levels. Premium quality is defined by nutritional benefits, softness and aroma in Southeast Asia, and by the physical appearance of the grains (uniformity, whiteness, slenderness), satiety, and aroma in South Asia. These trends are found to be consistent with industry perceptions and have important implications for regional and national breeding programs in terms of tailoring germplasm to regions and rice varieties to specific local market segments. Because rice is traded internationally, there is a need to standardize definitions of rice quality. However, food technologists have not reached unanimity on quality classes and measurement; routine indicators need to be complemented by descriptive profiles elicited through sensory evaluation panels. Finally, because rice quality is controlled by multiple interacting genes expressed through environmental conditions, predicting grain quality requires associating genetic information with grain quality phenotypes in different environments.

QTL mapping and genetic effect of chromosome segment substitution lines with excellent fiber quality from Gossypium hirsutum × Gossypium barbadense

Chromosome segment substitution lines (CSSLs) are ideal materials for identifying genetic effects. In this study, CSSL MBI7561 with excellent fiber quality that was selected from BC₄F_3:5 of CCRI45 (Gossypium hirsutum) × Hai1 (Gossypium barbadense) was used to construct 3 secondary segregating populations with 2 generations (BC₅F₂ and BC₅F_2:3). Eighty-one polymorphic markers related to 33 chromosome introgressive segments on 18 chromosomes were finally screened using 2292 SSR markers which covered the whole tetraploid cotton genome. A total of 129 quantitative trait loci (QTL) associated with fiber quality (103) and yield-related traits (26) were detected on 17 chromosomes, explaining 0.85-30.35% of the phenotypic variation; 39 were stable (30.2%), 53 were common (41.1%), 76 were new (58.9%), and 86 had favorable effects on the related traits. More QTL were distributed in the Dt subgenome than in the At subgenome. Twenty-five stable QTL clusters (with stable or common QTL) were detected on 22 chromosome introgressed segments. Finally, the 6 important chromosome introgressed segments (Seg-A02-1, Seg-A06-1, Seg-A07-2, Seg-A07-3, Seg-D07-3, and Seg-D06-2) were identified as candidate chromosome regions for fiber quality, which should be given more attention in future QTL fine mapping, gene cloning, and marker-assisted selection (MAS) breeding.

Identifying a wild allele conferring small seed size, high protein content and low oil content using chromosome segment substitution lines in soybean

KEY MESSAGE

A wild soybean allele conferring 100-seed weight, protein content and oil content simultaneously was fine-mapped to a 329-kb region on Chromosome 15, in which Glyma.15g049200 was predicted a candidate gene. Annual wild soybean characterized with small 100-seed weight (100SW), high protein content (PRC), low oil content (OIC) may contain favourable alleles for broadening the genetic base of cultivated soybeans. To evaluate these alleles, a population composed of 195 chromosome segment substitution lines (SojaCSSLP4), with wild N24852 as donor and cultivated NN1138-2 as recurrent parent, was tested. In SojaCSSLP4, 10, 9 and 8 wild segments/QTL were detected for 100SW, PRC and OIC, respectively. Using a backcross-derived secondary population, one segment for the three traits (q100SW15, qPro15 and qOil15) and one for 100SW (q100SW18.2) were fine-mapped into a 329-kb region on chromosome 15 and a 286-kb region on chromosome 18, respectively. Integrated with the transcription data in SoyBase, 42 genes were predicted in the 329-kb region where Glyma.15g049200 showed significant expression differences at all seed development stages. Furthermore, the Glyma.15g049200 segments of the two parents were sequenced and compared, which showed two base insertions in CDS (coding sequence) in the wild N24852 comparing to the NN1138-2. Since only Glyma.15g049200 performed differential CDS between the two parents but related to the three traits, Glyma.15g049200 was predicted a pleiotropic candidate gene for 100SW, PRC and OIC. The functional annotation of Glyma.15g049200 indicated a bidirectional sucrose transporter belonging to MtN3/saliva family which might be the reason that this gene provides a same biochemical basis for 100SW, PRC and OIC, therefore, is responsible for the three traits. This result may facilitate isolation of the specific gene and provide prerequisite for understanding the other two pleiotropic QTL.

Analysis of trait heritability in functionally partitioned rice genomes

Knowledge of the genetic architecture of importantly agronomical traits can speed up genetic improvement in cultivated rice (Oryza sativa L.). Many recent investigations have leveraged genome-wide association studies (GWAS) to identify single nucleotide polymorphisms (SNPs), associated with agronomic traits in various rice populations. The reported trait-relevant SNPs appear to be arbitrarily distributed along the genome, including genic and nongenic regions. Whether the SNPs in different genomic regions play different roles in trait heritability and which region is more responsible for phenotypic variation remains opaque. We analyzed a natural rice population of 524 accessions with 3,616,597 SNPs to compare the genetic contributions of functionally distinct genomic regions for five agronomic traits, i.e., yield, heading date, plant height, grain length, and grain width. An analysis of heritability in the functionally partitioned rice genome showed that regulatory or intergenic regions account for the most trait heritability. A close look at the trait-associated SNPs (TASs) indicated that the majority of the TASs are located in nongenic regions, and the genetic effects of the TASs in nongenic regions are generally greater than those in genic regions. We further compared the predictabilities using the genetic variants from genic regions with those using nongenic regions. The results revealed that nongenic regions play a more important role than genic regions in trait heritability in rice, which is consistent with findings in humans and maize. This conclusion not only offers clues for basic research to disclose genetics behind these agronomic traits, but also provides a new perspective to facilitate genomic selection in rice.

QTL mapping and genetic effect of chromosome segment substitution lines with excellent fiber quality from Gossypium hirsutum × Gossypium barbadense

Chromosome segment substitution lines (CSSLs) are ideal materials for identifying genetic effects. In this study, CSSL MBI7561 with excellent fiber quality that was selected from BC₄F_3:5 of CCRI45 (Gossypium hirsutum) × Hai1 (Gossypium barbadense) was used to construct 3 secondary segregating populations with 2 generations (BC₅F₂ and BC₅F_2:3). Eighty-one polymorphic markers related to 33 chromosome introgressive segments on 18 chromosomes were finally screened using 2292 SSR markers which covered the whole tetraploid cotton genome. A total of 129 quantitative trait loci (QTL) associated with fiber quality (103) and yield-related traits (26) were detected on 17 chromosomes, explaining 0.85-30.35% of the phenotypic variation; 39 were stable (30.2%), 53 were common (41.1%), 76 were new (58.9%), and 86 had favorable effects on the related traits. More QTL were distributed in the Dt subgenome than in the At subgenome. Twenty-five stable QTL clusters (with stable or common QTL) were detected on 22 chromosome introgressed segments. Finally, the 6 important chromosome introgressed segments (Seg-A02-1, Seg-A06-1, Seg-A07-2, Seg-A07-3, Seg-D07-3, and Seg-D06-2) were identified as candidate chromosome regions for fiber quality, which should be given more attention in future QTL fine mapping, gene cloning, and marker-assisted selection (MAS) breeding.

Molecular Networks of Seed Size Control in Plants

The size of seeds affects not only evolutionary fitness but also grain yield of crops. Understanding the mechanisms controlling seed size has become an important research field in plant science. Seed size is determined by the integrated signals of maternal and zygotic tissues, which control the coordinated growth of the embryo, endosperm, and seed coat. Recent advances have identified several signaling pathways that control seed size through maternal tissues, including or involving the ubiquitin-proteasome pathway, G-protein signaling, mitogen-activated protein kinase (MAPK) signaling, phytohormone perception and homeostasis, and some transcriptional regulators. Meanwhile, growth of the zygotic tissues is regulated in part by the HAIKU (IKU) pathway and phytohormones. This review provides a general overview of current findings in seed size control and discusses the emerging molecular mechanisms and regulatory networks found to be involved.

Genetic Mapping and Validation of Quantitative Trait Loci (QTL) for the Grain Appearance and Quality Traits in Rice (Oryza sativa L.) by Using Recombinant Inbred Line (RIL) Population

Rice grain shape and nutritional quality traits have high economic value for commercial production of rice and largely determine the market price, besides influencing the global food demand for high-quality rice. In order to understand the genetic components of grain appearance traits in paddy, brown, and head rice, 15 traits were evaluated by using 157 recombinant inbred lines (RILs) derived from a cross between two Iranian rice cultivars Ali-Kazemi (A) and Kadous (K). A significant variation was observed and showed transgressive segregation among the RILs. Correlations between the visual appearances of grain traits were studied. A linkage map with 65 polymorphic SSR markers was constructed, which covered 1517.32 cM of the rice genome. A total of seven QTLs were identified on four chromosomes, 1, 6, 9, and 12, associated with four traits, which are explained by the total phenotypic variation of 44.27% and LOD score of 32.77 in 2014 and 2015, respectively. Among these, four QTLs for two traits were consistently flanked by RM23904 and RM24432 on chromosome 9. Single QTL for head grain length (HGL) expressed in both the years on chromosomes 1 and 9. A major QTL for seed weight was detected on chromosome 9, which explained 10.18% of the phenotypic variation. The additive effect of all the QTLs was positively contributed by Ali-Kazemi allele, except one QTL on chromosome 6 (qBGL_6) that showed a negative additive effect being contributed by the Kadous allele. The study also validated the identified QTLs with the polymorphic SSR markers that were previously reported. Novel QTLs were identified on chromosomes 6 and 9, and many of the polymorphic markers were found to be associated with milling processing of grain quality, cooking, and nutraceutical properties of rice by extensive literature and database analysis. Therefore, these validated QTLs and marker information could be utilized in the marker-assisted selection to improve grain appearance and nutritional grain quality traits in rice.

Applications of the CRISPR/Cas9 System for Rice Grain Quality Improvement: Perspectives and Opportunities

Grain quality improvement is a key target for rice breeders, along with yield. It is a multigenic trait that is simultaneously influenced by many factors. Over the past few decades, breeding for semi-dwarf cultivars and hybrids has significantly contributed to the attainment of high yield demands but reduced grain quality, which thus needs the attention of researchers. The availability of rice genome sequences has facilitated gene discovery, targeted mutagenesis, and revealed functional aspects of rice grain quality attributes. Some success has been achieved through the application of molecular markers to understand the genetic mechanisms for better rice grain quality; however, researchers have opted for novel strategies. Genomic alteration employing genome editing technologies (GETs) like clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) for reverse genetics has opened new avenues of research in the life sciences, including for rice grain quality improvement. Currently, CRISPR/Cas9 technology is widely used by researchers for genome editing to achieve the desired biological objectives, because of its simple targeting. Over the past few years many genes that are related to various aspects of rice grain quality have been successfully edited via CRISPR/Cas9 technology. Interestingly, studies on functional genomics at larger scales have become possible because of the availability of GETs. In this review, we discuss the progress made in rice by employing the CRISPR/Cas9 editing system and its eminent applications. We also elaborate possible future avenues of research with this system, and our understanding regarding the biological mechanism of rice grain quality improvement.

High-resolution insight into recombination events at the SD1 locus in rice

Recombination during meiosis plays an important role in genome evolution by reshuffling existing genetic variations into fresh combinations with the possibility of recovery of lost ancestral genotypes. While crossover (CO) events have been well studied, gene conversion events (GCs), which represent non-reciprocal information transfer between chromosomes, are poorly documented and difficult to detect due to their relatively small converted tract size. Here, we document these GC events and their phenotypic effects at an important locus in rice containing the SD1 gene, where multiple defective alleles contributed to the semi-dwarf phenotype of rice in the 'Green Revolution' of the 1960s. Here, physical separation of two defects allows recombination to generate the wild-type SD1 gene, for which plant height can then be used as a reporter. By screening 18 000 F₂ progeny from a cross between two semi-dwarf cultivars that carry these different defective alleles, we detected 24 GC events, indicating a conversion rate of ~3.3 × 10^-4 per marker per generation in a single meiotic cycle in rice. Furthermore, our data show that indels and single-nucleotide polymorphisms (SNPs) do not differ significantly in GC rates, at least at the SD1 locus. Our results provide strong evidence that GC by itself can regain an ancestral phenotype that was lost through mutation. This GC detection approach is likely to be broadly applicable to natural or artificial alleles of other phenotype-related functional genes, which are abundant in other plant genomes.

Systems model-guided rice yield improvements based on genes controlling source, sink, and flow

A large number of genes related to source, sink, and flow have been identified after decades of research in plant genetics. Unfortunately, these genes have not been effectively utilized in modern crop breeding. This perspective paper aims to examine the reasons behind such a phenomenon and propose a strategy to resolve this situation. Specifically, we first systematically survey the currently cloned genes related to source, sink, and flow; then we discuss three factors hindering effective application of these identified genes, which include the lack of effective methods to identify limiting or critical steps in a signaling network, the misplacement of emphasis on properties, at the leaf, instead of the whole canopy level, and the non-linear complex interaction between source, sink, and flow. Finally, we propose the development of systems models of source, sink and flow, together with a detailed simulation of interactions between them and their surrounding environments, to guide effective use of the identified elements in modern rice breeding. These systems models will contribute directly to the definition of crop ideotype and also identification of critical features and parameters that limit the yield potential in current cultivars.

Identifying a large number of high-yield genes in rice by pedigree analysis, whole-genome sequencing, and CRISPR-Cas9 gene knockout

Repeated artificial selection of a complex trait facilitates the identification of genes underlying the trait, especially if multiple selected descendant lines are available. Here we developed a pedigree-based approach to identify genes underlying the Green Revolution (GR) phenotype. From a pedigree analysis, we selected 30 cultivars including the "miracle rice" IR8, a GR landmark, its ancestors and descendants, and also other related cultivars for identifying high-yield genes. Through sequencing of these genomes, we identified 28 ancestral chromosomal blocks that were maintained in all the high-yield cultivars under study. In these blocks, we identified six genes of known function, including the GR gene sd1, and 123 loci with genes of unknown function. We randomly selected 57 genes from the 123 loci for knockout or knockdown studies and found that a high proportion of these genes are essential or have phenotypic effects related to rice production. Notably, knockout lines have significant changes in plant height (P < 0.003), a key GR trait, compared with wild-type lines. Some gene knockouts or knockdowns were especially interesting. For example, knockout of Os10g0555100, a putative glucosyltransferase gene, showed both reduced growth and altered panicle architecture. In addition, we found that in some retained chromosome blocks several GR-related genes were clustered, although they have unrelated sequences, suggesting clustering of genes with similar functions. In conclusion, we have identified many high-yield genes in rice. Our method provides a powerful means to identify genes associated with a specific trait.

An EMS-induced new sequence variant, TEMS5032, in the coding region of SRS3 gene leads to shorter grain length in rice (Oryza sativa L.)

Grain shape and size influence yield and consumer preferences in rice. In the present study, we characterized and mapped a short and bold grained mutant and named it as TEMS5032, as the mutant is a result of EMS-induced transition from C to T at the 5032nd bp of SRS3 gene, which is known to affect grain size in rice. The substitution led to creation of a stop codon in the motor domain of SRS3, a kinesin 13 family gene, translating into a truncated protein product. However, transcription of this gene remained unaffected in TEMS5032 compared to the wild type, N22. Further, the mutation was found to affect 13 of the 25 cell cycle-related genes as they showed differential expression with respect to N22. Based on rate of grain filling, dry matter accumulation in the endosperm and histological studies, the effect of mutation in TEMS5032 was found to be similar to a known variant, TCM758, but less severe than sar1 mutant. Sequencing of 88 rice germplasm lines in the kinesin motor domain region did not reveal the presence of this mutation, establishing it as a new variant of SRS3 gene.

Map-based cloning and characterization of Zea mays male sterility33 (ZmMs33) gene, encoding a glycerol-3-phosphate acyltransferase

Map-based cloning of maize ms33 gene showed that ZmMs33 encodes a sn-2 glycerol-3-phosphate acyltransferase, the ortholog of rice OsGPAT3, and it is essential for male fertility in maize. Genetic male sterility has been widely studied for its biological significance and commercial value in hybrid seed production. Although many male-sterile mutants have been identified in maize (Zea mays L.), it is likely that most genes that cause male sterility are unknown. Here, we report a recessive genetic male-sterile mutant, male sterility33 (ms33), which displays small, pale yellow anthers, and complete male sterility. Using a map-based cloning approach, maize GRMZM2G070304 was identified as the ms33 gene (ZmMs33). ZmMs33 encodes a novel sn-2 glycerol-3-phosphate acyltransferase (GPAT) in maize. A functional complementation experiment showed that GRMZM2G070304 can rescue the male-sterile phenotype of the ms33-6029 mutant. GRMZM2G070304 was further confirmed to be the ms33 gene via targeted knockouts induced by the clustered regularly interspersed short palindromic repeats (CRISPR)/Cas9 system. ZmMs33 is preferentially expressed in the immature anther from the quartet to early-vacuolate microspore stages and in root tissues at the fifth leaf growth stage. Phylogenetic analysis indicated that ZmMs33 and OsGPAT3 are evolutionarily conserved for anther and pollen development in monocot species. This study reveals that the monocot-specific GPAT3 protein plays an important role in male fertility in maize, and ZmMs33 and mutants in this gene may have value in maize male-sterile line breeding and hybrid seed production.

Combining QTL-seq and linkage mapping to fine map a wild soybean allele characteristic of greater plant height

BACKGROUND

Plant height (PH) is an important agronomic trait and is closely related to yield in soybean [Glycine max (L.) Merr.]. Previous studies have identified many QTLs for PH. Due to the complex genetic background of PH in soybean, there are few reports on its fine mapping.

RESULTS

In this study, we used a mapping population derived from a cross between a chromosome segment substitution line CSSL3228 (donor N24852 (G. Soja), a receptor NN1138-2 (G. max)) and NN1138-2 to fine map a wild soybean allele of greater PH by QTL-seq and linkage mapping. We identified a QTL for PH in a 1.73 Mb region on soybean chromosome 13 through QTL-seq, which was confirmed by SSR marker-based classical QTL mapping in the mapping population. The linkage analysis showed that the QTLs of PH were located between the SSR markers BARCSOYSSR_13_1417 and BARCSOYSSR_13_1421 on chromosome 13, and the physical distance was 69.3 kb. RT-PCR and sequence analysis of possible candidate genes showed that Glyma.13 g249400 revealed significantly higher expression in higher PH genotypes, and the gene existed 6 differences in the amino acids encoding between the two parents.

CONCLUSIONS

Data presented here provide support for Glyma.13 g249400 as a possible candidate genes for higher PH in wild soybean line N24852.

Intragenic recombination between two non-functional semi-dwarf 1 alleles produced a functional SD1 allele in a tall recombinant inbred line in rice

Intragenic recombination is one of the most important sources of genetic variability. In our previous study, RI92 a tall line (160 cm of plant height) was observed in the cross progeny between two semi-dwarf indica cultivars Zhenshan 97 and Minghui 63. Genome-wide genotyping and sequencing indicated that the genome constitution of RI92 was completely from both parents. Bulk segregant analysis in a BC₃F₂ population revealed that “green revolution gene” semi-dwarf 1 (sd1) was most likely the gene controlling the tall plant height in RI92. Sequencing analysis of SD1 revealed that an intragenic recombination occurred between two parental non-functional sd1 alleles and generated a functional SD1 in RI92. Four-fold high recombination rate in SD1 located bins to the genome-wide average was observed in two RIL populations, indicating recombination hotspot in the SD1 region. Intragenic recombination creates new alleles in the progeny distinct from parental alleles and diversifies natural variation.

TaFlo2-A1, an ortholog of rice Flo2, is associated with thousand grain weight in bread wheat (Triticum aestivum L.)

BACKGROUND

The Flo2 gene is a member of a conserved gene family in plants. This gene has been found to be related to thousand grain weight (TGW) in rice. Its orthologs in hexaploid wheat were cloned, and the haplotype variation in TaFlo2-A1 was tested for association with TGW.

RESULTS

The cloned sequences of TaFlo2-A1, TaFlo2-B1 and TaFlo2-D1 contained 23, 23 and 24 exons, respectively. The deduced proteins of TaFlo2-A1 (1734 aa), TaFlo2-B1 (1698 aa) and TaFlo2-D1 (1682 aa) were highly similar (>94%) and exhibited >77% similarity with the rice FLO2 protein. Like the rice FLO2 protein, four tetratricopeptide repeat (TPR) motifs were observed in the deduced TaFLO2 protein. An 8-bp InDel (-10 to -17 bp) in the promoter region and five SNPs in first intron of TaFlo2-A1 together formed two haplotypes, TaFlo2-A1a and TaFlo2-A1b, in bread wheat. TaFlo2 was located on homeologous group 2 chromosomes. TaFlo2-A1 was inferred to be located on deletion bin '2AL1-0.85-1.00'. The TaFlo2-A1 haplotypes were characterized in the Chinese Micro Core Collection (MCC) and Pakistani wheat collection using the molecular marker TaFlo2-Indel8. TaFlo2-A1 was found to be associated with TGW but not with grain number per spike (GpS) in both the MCC and Pakistani wheat collections. The frequency of TaFlo2-A1b (positive haplotype) was low in commercial wheat cultivars; thus this haplotype can be selected to improve grain weight without negatively affecting GpS. The expression level of TaFlo2-A1 in developing grains at 5 DAF (days after flowering) was positively correlated with TGW in cultivars carrying the positive haplotype.

CONCLUSION

This study will likely lead to additional investigations to understand the regulatory mechanism of the Flo2 gene in hexaploid wheat. Furthermore, the newly developed molecular marker 'TaFlo2-InDel8' could be incorporated into the kit of wheat breeders for use in marker-assisted selection.

Chromosome segment detection for seed size and shape traits using an improved population of wild soybean chromosome segment substitution lines

Size and shape of soybean seeds are closely related to seed yield and market value. Annual wild soybeans have the potential to improve cultivated soybeans, but their inferior seed characteristics should be excluded. To detect quantitative trait loci (QTLs)/segments of seed size and shape traits in annual wild soybean, its chromosome segment substitution lines (CSSLs) derived from NN1138-2 (recurrent parent, Glycine max) and N24852 (donor parent, Glycine soja) and then modified 2 iterations (coded SojaCSSLP3) were improved further to contain more lines (diagonal segments) and less heterozygous and missing portions. The new population (SojaCSSLP4) composed of 195 CSSLs was evaluated under four environments, and 11, 13, 7, 15 and 14 QTLs/segments were detected for seed length (SL), seed width (SW), seed roundness (SR), seed perimeter (SP) and seed cross section area (SA), respectively, with all 60 wild allele effects negative. Among them, 16 QTLs/segments were shared by 2-5 traits, respectively, but 0-3 segments for each of the 5 traits were independent. The non-shared Satt274 and shared Satt305, Satt540 and Satt239 were major segments, along with other segments composed of two different but related sets of genetic systems for SR and the other 4 traits, respectively. Compared with the literature, 7 SL, 5 SW and 2 SR QTLs/segments were also detected in cultivated soybeans; allele distinction took place between cultivated and wild soybeans, and also among cultivated parents. The present mapping is understood as macro-segment mapping, the segments may be further dissected into smaller segments as well as corresponding QTLs/genes.

Construction of rice chromosome segment substitution lines harboring Oryza barthii genome and evaluation of yield-related traits

Rice (Oryza sativa L.) is one of the most important staple food in the world. To meet the increasing demand for food, a strategy for improving rice yield is needed. Alleles of wild relatives are useful because they confer adaptation to plants under diverse harsh environments and have the potential to improve rice. O. barthii is a wild rice species endemic to Africa and the known progenitor of the African cultivated rice, O. glaberrima. To explore the genetic potential of the O. barthii as a genetic resource, 40 chromosome segment substitution lines (CSSL) of O. barthii in the background of the elite japonica cultivar Koshihikari were developed and evaluated to identify QTLs associated with 10 traits related to flag leaf morphology, grain yield and other agronomic traits. More than 90% of the entire genome of the donor parent was represented in contiguous or overlapping chromosome segments in the CSSLs. Evaluation of the CSSLs for several agriculturally important traits identified candidate chromosome segments that harbors QTLs associated with yield and yield-related traits. These results suggest that alleles from O. barthii might be used as a novel genetic resource for improving the yield-related traits in cultivars of O. sativa.

Overexpression of the 16-kDa α-amylase/trypsin inhibitor RAG2 improves grain yield and quality of rice

Increasing grain yield and improving grain quality are two important goals for rice breeding. A better understanding of the factors that contribute to the overall grain quantity and nutritional quality of rice will lay the foundation for developing new breeding strategies. RAG2 is a member of 14-to-16-kDa α-amylase/trypsin inhibitors in rice, which belong to the albumin of seed storage proteins. We found that RAG2 was specifically expressed in ripening seed and its transcription peak was between 14 and 21 days after flowering. Grain size and 1000-grain weight were obviously increased in RAG2-overexpressed lines compared with wild type, and grain size was reduced in RAG2-suppressed lines. In addition, the major storage substances of the seeds differed significantly in RAG2-overexpressed and RAG2-suppressed lines compared to wild type. The protein content and amount of total lipids were increased and decreased, respectively, in the seeds of RAG2-overexpressed and RAG2-suppressed lines. Overexpression of RAG2 significantly increased grain size and improved grain quality and yield simultaneously. These results imply that RAG2 might play an important role in regulating grain weight and seed quality of rice. The functional characterization of rice RAG2 facilitates a further understanding of the mechanisms involved in grain size and seed quality and may be helpful in improving grain yield and quantity in cereal crops.

Identification of Chromosome Segment Substitution Lines of Gossypium barbadense Introgressed in G. hirsutum and Quantitative Trait Locus Mapping for Fiber Quality and Yield Traits

Chromosome segment substitution lines MBI9804, MBI9855, MBI9752, and MBI9134, which were obtained by advanced backcrossing and continuously inbreeding from an interspecific cross between CCRI36, a cultivar of upland cotton (Gossypium hirsutum) as the recurrent parent, and Hai1, a cultivar of sea island cotton (G. barbadense) as the donor parent, were used to construct a multiple parent population of (MBI9804×MBI9855)×(MBI9752×MBI9134). The segregating generations of double-crossed F1 and F2 and F2:3 were used to map the quantitative trait locus (QTL) for fiber quality and yield-related traits. The recovery rate of the recurrent parent CCRI36 in the four parental lines was from 94.3%-96.9%. Each of the parental lines harbored 12-20 introgressed segments from Hai1across 21 chromosomes. The number of introgressed segments ranged from 1 to 27 for the individuals in the three generations, mostly from 9 to 18, which represented a genetic length of between 126 cM and 246 cM. A total of 24 QTLs controlling fiber quality and 11 QTLs controlling yield traits were detected using the three segregating generations. These QTLs were distributed across 11 chromosomes and could collectively explain 1.78%-20.27% of the observed phenotypic variations. Sixteen QTLs were consistently detected in two or more generations, four of them were for fiber yield traits and 12 were for fiber quality traits. One introgressed segment could significantly reduce both lint percentage and fiber micronaire. This study provides useful information for gene cloning and marker-assisted breeding for excellent fiber quality.

Multi-environment QTL analysis of grain morphology traits and fine mapping of a kernel-width QTL in Zheng58 × SK maize population

Sixteen major QTLs regulating maize kernel traits were mapped in multiple environments and one of them, qKW - 9.2 , was restricted to 630 Kb, harboring 28 putative gene models. To elucidate the genetic basis of kernel traits, a quantitative trait locus (QTL) analysis was conducted in a maize recombinant inbred line population derived from a cross between two diverse parents Zheng58 and SK, evaluated across eight environments. Construction of a high-density linkage map was based on 13,703 single-nucleotide polymorphism markers, covering 1860.9 cM of the whole genome. In total, 18, 26, 23, and 19 QTLs for kernel length, width, thickness, and 100-kernel weight, respectively, were detected on the basis of a single-environment analysis, and each QTL explained 3.2-23.7 % of the phenotypic variance. Sixteen major QTLs, which could explain greater than 10 % of the phenotypic variation, were mapped in multiple environments, implying that kernel traits might be controlled by many minor and multiple major QTLs. The major QTL qKW-9.2 with physical confidence interval of 1.68 Mbp, affecting kernel width, was then selected for fine mapping using heterogeneous inbred families. At final, the location of the underlying gene was narrowed down to 630 Kb, harboring 28 putative candidate-gene models. This information will enhance molecular breeding for kernel traits and simultaneously assist the gene cloning underlying this QTL, helping to reveal the genetic basis of kernel development in maize.

Characterization of three wheat grain weight QTLs that differentially affect kernel dimensions

The QGw.nau - 2D, QGw.nau - 4B and QGw.nau - 5A intervals were investigated for their effects on weight, length, width, and thickness of kernels and their differential roles in determining kernel size and shape were demonstrated. Grain weight (GW) contributes greatly to wheat yield and is directly related to kernel size and shape. Although over 100 quantitative trait loci (QTLs) for GW have been reported in the literatures, few have been well characterized for their association with kernel traits. In this study, three GW QTLs identified in elite cultivar 'Nanda2419' ('Mentana'), including QGw.nau-2D, QGw.nau-4B and QGw.nau-5A, were investigated through near isogenic line (NIL) development and evaluation. NILs for all three QTLs and one NIL with both QGw.nau-4B and QGw.nau-5A were developed with the help of marker-assisted selection after two to three generations of backcross using cultivar 'Wangshuibai' as the recurrent parent. One NIL with QGw.nau-4B in the background of cultivar 'Wenmai6' was also obtained. In four different field trials, these NILs consistently produced heavier kernels than the recurrent parents. QGw.nau-4B showed the largest effect on GW; its presence resulted in 0.4-0.5 g increase of hundred-grain weight, depending on genetic backgrounds. QGw.nau-4B and QGw.nau-5A functioned additively in conditioning GW. These three QTL intervals showed pleiotropic effects on, or close linkage with genes for, spike length, plant height and flag leaf width, respectively, and acted differentially in determining the kernel dimensions that are the major GW determinants. They all conditioned wider kernels with QGw.nau-5A displaying the largest effect. QGw.nau-4B and QGw.nau-5A also conditioned thicker kernels but had opposite effects on kernel length. This study demonstrated that marker-assisted selection is effective for GW improvement. The availability of GW NILs could facilitate cloning of GW genes and unraveling of kernel development mechanisms.

The Usefulness of Known Genes/Qtls for Grain Quality Traits in an Indica Population of Diverse Breeding Lines Tested using Association Analysis

BACKGROUND

A number of studies reported major genes/QTLs for rice grain shapes, chalkiness and starch physicochemical properties. For these finely mapped QTLs or cloned genes to make an impact in practical breeding, it is necessary to test their effects in different genetic backgrounds. In this study, two hundred nineteen markers for 20 starch synthesis genes, 41 fine mapped grain shape and related traits QTLs/genes, and 54 chalkiness QTLs/genes plus 15 additional markers and a large indica population of 375 advanced lines were used to identify marker-trait associations under 6 environments that can be used directly in breeding for grain quality traits.

RESULTS

The significant associations detected by the QK model were used to declare the usefulness of the targeted genes/QTLs. A total of 65 markers were detected associations with grain quality trait at least in one environment. More phenotypic variations could be explained by haplotype than single marker, as exemplified by the starch biosynthesising genes. GBSSI was the major gene for AC and explained up to 55 % of the phenotypic variation, which also affected GC and accounted up to 11.31 % of the phenotypic variation. SSIIa was the major gene for chalkiness and explained up to 17 and 21 % of variation of DEC and PGWC, respectively. In addition, RMw513 and RM18068 were associated with DEC in 6 environments as well. Four markers (RGS1, RM15206, RMw513 and Indel1) tightly linked to GS3, gw5, and qGL7-2 were the most important ones for grain shapes. Allelic combinations between SSIIa and RMw513 revealed more variations in DEC.

CONCLUSIONS

The validated markers for genes/QTLs with major effects could be directly used in breeding for grain quality via marker-assisted selection. Creating desirable allelic combinations by gene pyramiding might be an effective approach for the development of high quality breeding lines in rice.

Development of gene-based markers for use in construction of the chickpea (Cicer arietinum L.) genetic linkage map and identification of QTLs associated with seed weight and plant height

Seed weight and plant height are important agronomic traits and contribute to seed yield. The objective of this study was to identify QTLs underlying these traits using an intra-specific mapping population of chickpea. A F11 population of 177 recombinant inbred lines derived from a cross between SBD377 (100-seed weight--48 g and plant height--53 cm) and BGD112 (100-seed weight--15 g and plant height--65 cm) was used. A total of 367 novel EST-derived functional markers were developed which included 187 EST-SSRs, 130 potential intron polymorphisms (PIPs) and 50 expressed sequence tag polymorphisms (ESTPs). Along with these, 590 previously published markers including 385 EST-based markers and 205 genomic SSRs were utilized. Of the 957 markers tested for analysis of parental polymorphism between the two parents of the mapping population, 135 (14.64%) were found to be polymorphic. Of these, 131 polymorphic markers could be mapped to the 8 linkage groups. The linkage map had a total length of 1140.54 cM with an average marker density of 8.7 cM. The map was further used for QTL identification using composite interval mapping method (CIM). Two QTLs each for seed weight, qSW-1 and qSW-2 (explaining 11.54 and 19.24% of phenotypic variance, respectively) and plant height, qPH-1 and qPH-2 (explaining 13.98 and 12.17% of phenotypic variance, respectively) were detected. The novel set of genic markers, the intra-specific linkage map and the QTLs identified in the present study will serve as valuable genomic resources in improving the chickpea seed yield using marker-assisted selection (MAS) strategies.

Genetic dissection on rice grain shape by the two-dimensional image analysis in one japonica × indica population consisting of recombinant inbred lines

KEY MESSAGE

This article used seven characters from the 2D image analysis to dissect the genetic architecture underlying rice grain shape in one japonica × indica population consisting of 215 recombinant inbred lines. Two-dimensional (2D) digital image analysis is efficient for investigating the rice grain shape characters in large genetic and breeding populations. In this study, we used 2D image analysis to investigate seven characters, i.e., grain length (GL), grain width (GW), length-to-width ratio (LW), grain area (GA), grain circumference (GC), grain diameter (GD), and grain roundness (GR), in one japonica × indica genetic population consisting of 215 recombinant inbred lines. GL and GW can be recorded manually as well, and have been extensively used together with LW (i.e., GL/GW) in genetic studies on grain shape. GC and GA can be hardly measured manually, and have not been used together with GD and GR. Results indicated that the seven characters could be precisely measured by 2D image analysis, genotype by environment interaction was low, and heritability was high. Each character was controlled by a few major stable genes and multiple minor additive genes. A total of 51 QTL were detected for the seven characters across four diverse environments, 22 from GL, GW, and LW, the three traditional characters, and 29 from the other four characters. The 51 QTL were clustered in eighteen marker intervals. Comparing with previous studies and analyzing the stability of identified QTL, we found six non-reported marker intervals, one each on chromosomes 2 and 3, and two each on chromosomes 6 and 8. The newly identified loci and the large-scale phenotyping system would greatly improve our knowledge about the genetic architecture and the future rice breeding on grain shape.

Fine Mapping and Characterization of Candidate Genes that Control Resistance to Cercospora sojina K. Hara in Two Soybean Germplasm Accessions

Frogeye leaf spot (FLS), caused by the fungus Cercospora sojina K. Hara, may cause a significant yield loss to soybean growers in regions with a warm and humid climate. Two soybean accessions, PI 594891 and PI 594774, were identified to carry a high level of resistance similar to that conditioned by the Rcs3 gene in 'Davis'. Previously, we reported that the resistance to FLS in these two plant introductions (PIs) was controlled by a novel gene (s) on chromosome 13 that is different from Rcs3. To fine-map the novel FLS resistance gene(s) in these two PIs, F2: 3 seeds from the crosses between PI 594891 and PI 594774, and the FLS susceptible genotype 'Blackhawk' were genotyped with SNP markers that were designed based on the SoySNP50k iSelect BeadChip data to identify recombinant events and locate candidate genes. Analysis of lines possessing key recombination events helped narrow down the FLS-resistance genomic region in PI 594891 from 3.3 Mb to a 72.6 kb region with five annotated genes. The resistance gene in PI 594774 was fine-mapped into a 540 kb region that encompasses the 72.6 kb region found in PI 594891. Sequencing five candidate genes in PI 594891 identified three genes that have several mutations in the promoter, intron, 5', and 3' UTR regions. qPCR analysis showed a difference in expression levels of these genes in both lines compared to Blackhawk in the presence of C. sojina. Based on phenotype, genotype and haplotype analysis results, these two soybean accessions might carry different resistance alleles of the same gene or two different gene(s). The identified SNPs were used to develop Kompetitive Allele Specific PCR (KASP) assays to detect the resistance alleles on chromosome 13 from the two PIs for marker-assisted selection.

Analysis of heterosis and quantitative trait loci for kernel shape related traits using triple testcross population in maize

Kernel shape related traits (KSRTs) have been shown to have important influences on grain yield. The previous studies that emphasize kernel length (KL) and kernel width (KW) lack a comprehensive evaluation of characters affecting kernel shape. In this study, materials of the basic generations (B73, Mo17, and B73 × Mo17), 82 intermated B73 × Mo17 (IBM) individuals, and the corresponding triple testcross (TTC) populations were used to evaluate heterosis, investigate correlations, and characterize the quantitative trait loci (QTL) for six KSRTs: KL, KW, length to width ratio (LWR), perimeter length (PL), kernel area (KA), and circularity (CS). The results showed that the mid-parent heterosis (MPH) for most of the KSRTs was moderate. The performance of KL, KW, PL, and KA exhibited significant positive correlation with heterozygosity but their Pearson’s R values were low. Among KSRTs, the strongest significant correlation was found between PL and KA with R values was up to 0.964. In addition, KW, PL, KA, and CS were shown to be significant positive correlation with 100-kernel weight (HKW). 28 QTLs were detected for KSRTs in which nine were augmented additive, 13 were augmented dominant, and six were dominance × additive epistatic. The contribution of a single QTL to total phenotypic variation ranged from 2.1% to 32.9%. Furthermore, 19 additive × additive digenic epistatic interactions were detected for all KSRTs with the highest total R² for KW (78.8%), and nine dominance × dominance digenic epistatic interactions detected for KL, LWR, and CS with the highest total R² (55.3%). Among significant digenic interactions, most occurred between genomic regions not mapped with main-effect QTLs. These findings display the complexity of the genetic basis for KSRTs and enhance our understanding on heterosis of KSRTs from the quantitative genetic perspective.