Analysis of QTLs for yield-related traits in Yuanjiang common wild rice (Oryza rufipogon Griff.)

Fine mapping of interspecific secondary CSSL populations revealed key regulators for grain weight at qTGW3.1 locus from Oryza nivara

Grain weight (GW) is the most important stable trait that directly contributes to crop yield in case of cereals. A total of 105 backcross introgression lines (BC2F10 BILs) derived from Swarna/O. nivara IRGC81848 (NPS) and 90 BILs from Swarna/O. nivara IRGC81832 (NPK) were evaluated for thousand-grain weight (TGW) across four years (wet seasons 2014, 2015, 2016 and 2018) and chromosome segment substitution lines (CSSLs) were selected. From significant pair- wise mean comparison with Swarna, a total of 77 positively and 29 negatively significant NPS lines and 62 positively and 29 negatively significant NPK lines were identified. In all 4 years, 14 NPS lines and 9 NPK lines were positively significant and one-line NPS69 (IET22161) was negatively significant for TGW over Swarna consistently. NPS lines and NPK lines were genotyped using 111 and 140 polymorphic SSRs respectively. Quantitative trait locus (QTL) mapping using ICIM v4.2 software showed 13 QTLs for TGW in NPS. Three major effect QTLs qTGW2.1, qTGW8.1 and qTGW11.1 were identified in NPS for two or more years with PVE ranging from 8 to 14%. Likewise, 10 QTLs were identified in NPK and including two major effect QTL qTGW3.1 and qTGW12.1 with 6 to 32% PVE. In all QTLs, O. nivara alleles increased TGW. These consistent QTLs are very suitable for fine mapping and functional analysis of grain weight. Further in this study, CSSLs NPS1 (10-2S) and NPK61 (158 K) with significantly higher grain weight than the recurrent parent, Swarna cv. Oryza sativa were selected from each population and secondary F2 mapping populations were developed. Using Bulked Segregant QTL sequencing, a grain weight QTL, designated as qTGW3.1 was fine mapped from the cross between NPK61 and Swarna. This QTL explained 48% (logarithm of odds = 32.2) of the phenotypic variations and was fine mapped to a 31 kb interval using recombinant analysis. GRAS transcription factor gene (OS03go103400) involved in plant growth and development located at this genomic locus might be the candidate gene for qTGW3.1. The results of this study will help in further functional studies and improving the knowledge related to the molecular mechanism of grain weight in Oryza and lays a solid foundation for the breeding for high yield.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-024-01483-0.

A meta-quantitative trait loci analysis identified consensus genomic regions and candidate genes associated with grain yield in rice

Improving grain yield potential in rice is an important step toward addressing global food security challenges. The meta-QTL analysis offers stable and robust QTLs irrespective of the genetic background of mapping populations and phenotype environment and effectively narrows confidence intervals (CI) for candidate gene (CG) mining and marker-assisted selection improvement. To achieve these aims, a comprehensive bibliographic search for grain yield traits (spikelet fertility, number of grains per panicle, panicles number per plant, and 1000-grain weight) QTLs was conducted, and 462 QTLs were retrieved from 47 independent QTL research published between 2002 and 2022. QTL projection was performed using a reference map with a cumulative length of 2,945.67 cM, and MQTL analysis was conducted on 313 QTLs. Consequently, a total of 62 MQTLs were identified with reduced mean CI (up to 3.40 fold) compared to the mean CI of original QTLs. However, 10 of these MQTLs harbored at least six of the initial QTLs from diverse genetic backgrounds and environments and were considered the most stable and robust MQTLs. Also, MQTLs were compared with GWAS studies and resulted in the identification of 16 common significant loci modulating the evaluated traits. Gene annotation, gene ontology (GO) enrichment, and RNA-seq analyses of chromosome regions of the stable MQTLs detected 52 potential CGs including those that have been cloned in previous studies. These genes encode proteins known to be involved in regulating grain yield including cytochrome P450, zinc fingers, MADs-box, AP2/ERF domain, F-box, ubiquitin ligase domain protein, homeobox domain, DEAD-box ATP domain, and U-box domain. This study provides the framework for molecular dissection of grain yield in rice. Moreover, the MQTLs and CGs identified could be useful for fine mapping, gene cloning, and marker-assisted selection to improve rice productivity.

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.

The Harbinger transposon-derived gene PANDA epigenetically coordinates panicle number and grain size in rice

Transposons significantly contribute to genome fractions in many plants. Although numerous transposon-related mutations have been identified, the evidence regarding transposon-derived genes regulating crop yield and other agronomic traits is very limited. In this study, we characterized a rice Harbinger transposon-derived gene called PANICLE NUMBER AND GRAIN SIZE (PANDA), which epigenetically coordinates panicle number and grain size. Mutation of PANDA caused reduced panicle number but increased grain size in rice, while transgenic plants overexpressing this gene showed the opposite phenotypic change. The PANDA-encoding protein can bind to the core polycomb repressive complex 2 (PRC2) components OsMSI1 and OsFIE2, and regulates the deposition of H3K27me3 in the target genes, thereby epigenetically repressing their expression. Among the target genes, both OsMADS55 and OsEMF1 were negative regulators of panicle number but positive regulators of grain size, partly explaining the involvement of PANDA in balancing panicle number and grain size. Moreover, moderate overexpression of PANDA driven by its own promoter in the indica rice cultivar can increase grain yield. Thus, our findings present a novel insight into the epigenetic control of rice yield traits by a Harbinger transposon-derived gene and provide its potential application for rice yield improvement.

Introgression Lines: Valuable Resources for Functional Genomics Research and Breeding in Rice (Oryza sativa L.)

The narrow base of genetic diversity of modern rice varieties is mainly attributed to the overuse of the common backbone parents that leads to the lack of varied favorable alleles in the process of breeding new varieties. Introgression lines (ILs) developed by a backcross strategy combined with marker-assisted selection (MAS) are powerful prebreeding tools for broadening the genetic base of existing cultivars. They have high power for mapping quantitative trait loci (QTLs) either with major or minor effects, and are used for precisely evaluating the genetic effects of QTLs and detecting the gene-by-gene or gene-by-environment interactions due to their low genetic background noise. ILs developed from multiple donors in a fixed background can be used as an IL platform to identify the best alleles or allele combinations for breeding by design. In the present paper, we reviewed the recent achievements from ILs in rice functional genomics research and breeding, including the genetic dissection of complex traits, identification of elite alleles and background-independent and epistatic QTLs, analysis of genetic interaction, and genetic improvement of single and multiple target traits. We also discussed how to develop ILs for further identification of new elite alleles, and how to utilize IL platforms for rice genetic improvement.

Identification and Fine-Mapping of a New Bacterial Blight Resistance Gene, Xa47(t), in G252, an Introgression Line of Yuanjiang Common Wild Rice (Oryza rufipogon)

Bacterial blight (BB) disease caused by Xanthomonas oryzae pv. oryzae is a common, widespread, and highly devastating disease that affects rice yield. Breeding resistant cultivars is considered the most effective measure for controlling this disease. The introgression line G252 derived from Yuanjiang common wild rice (Oryza rufipogon) was highly resistant to all tested strains, including C5, C9, PXO99, PB, T7147Y8, Hzhj19, YM1, YM187, YJdp-2, and YJws-2. To identify the BB resistance gene(s) of G252, we developed an F₂ population from the cross between G252 and 02428. A linkage analysis was performed for the phenotype and genotype of the population. A segregation ratio of 3:1 was observed between the resistant and susceptible individuals in the F₂ progeny, indicating a dominant resistance gene, Xa47(t), in G252. The resistance gene was mapped within an approximately 26.24-kb physical region on chromosome 11 between two InDel markers, R13I14 and 13rbq-71. Moreover, one InDel marker, Hxjy-1, co-segregated with Xa47(t). Three genes were predicted within the target region, including a promising candidate gene encoding a nucleotide-binding domain and leucine-rich repeat (NLR) protein (LOC_Os11g46200) by combining the structure and expression analysis. Physical mapping data suggested that Xa47(t) is a new broad-spectrum BB resistance gene without identified allelic genes.

A major pleiotropic QTL identified for yield components and nitrogen content in rice (Oryza sativa L.) under differential nitrogen field conditions

To identify the genomic regions for yield and NUE of rice genotypes and lines with promising yield under low N, a recombinant inbred population (RIL) developed between BPT5204 (a mega variety known for its quality) and PTB1 (variety with high NUE) was evaluated for consecutive wet and dry seasons under low nitrogen (LN) and recommended nitrogen (RN) field conditions. A set of 291 RILs were characterized for 24 traits related to leaf, agro-morphological, yield, N content and nitrogen use efficiency indices. More than 50 RILs were found promising with grain yield >10 g under LN. Parental polymorphism survey with 297 SSRs and selective genotyping revealed five genomic regions associated with yield under LN, which were further saturated with polymorphic SSRs. Thirteen promising SSRs were identified out of 144 marker trait associations under LN using single marker analysis. Composite interval mapping showed 37 QTL under LN with five pleiotropic QTL. A major stable pleiotropic (RM13201—RM13209) from PTB1 spanning 825.4 kb region associated with straw N % (SNP) in both treatments across seasons and yield and yield related traits in WS appears to be promising for the MAS. Another major QTL (RM13181-RM13201) was found to be associated with only relative trait parameters of biomass, grain and grain nitrogen. These two major pleiotropic QTL (RM13201-RM13209 and RM13181-RM13201) on chromosome 2 were characterized for their positive allele effect and could be deployed for the development of rice varieties with NUE.

Molecular mapping of QTLs for yield related traits in recombinant inbred line (RIL) population derived from the popular rice hybrid KRH-2 and their validation through SNP genotyping

The study was undertaken to identify the quantitative trait loci (QTLs) governing yield and its related traits using a recombinant inbred line (RIL) population derived from the popular rice hybrid, KRH-2 (IR58025A/KMR3R). A genetic map spanning 294.2 cM was constructed with 126 simple sequence repeats (SSR) loci uniformly distributed across the rice genome. QTL analysis using phenotyping and genotyping information identified a total of 22 QTLs. Of these, five major effect QTLs were identified for the following traits: total grain yield/plant (qYLD3-1), panicle weight (qPW3-1), plant height (qPH12-1), flag leaf width (qFLW4-1) and panicle length (qPL3-1), explaining 20.23–22.76% of the phenotypic variance with LOD scores range of 6.5–10.59. Few genomic regions controlling several traits (QTL hotspot) were identified on chromosome 3 for total grain yield/plant (qYLD3-1) and panicle length (qPL3-1). Significant epistatic interactions were also observed for total grain yield per plant (YLD) and panicle length (PL). While most of these QTLs were observed to be co-localized with the previously reported QTL regions, a novel, major QTL associated with panicle length (qPL3-1) was also identified. SNP genotyping of selected high and low yielding RILs and their QTL mapping with 1,082 SNPs validated most of the QTLs identified through SSR genotyping. This facilitated the identification of novel major effect QTLs with much better resolution and precision. In-silico analysis of novel QTLs revealed the biological functions of the putative candidate gene (s) associated with selected traits. Most of the high-yielding RILs possessing the major yield related QTLs were identified to be complete restorers, indicating their possible utilization in development of superior rice hybrids.

Identification of QTLs for high grain yield and component traits in new plant types of rice

A panel of 60 genotypes comprising New Plant Types (NPTs) along with indica, tropical and temperate japonica genotypes was phenotypically evaluated for four seasons in irrigated situation for grain yield per se and component traits. Twenty NPT genotypes were found promising with an average grain yield varying from 5.45 to 8.8 t/ha. A total of 85 SSR markers were used in the study to identify QTLs associated with grain yield per se and related traits. Sixty-six (77.65%) markers were found to be polymorphic. The PIC values varied from 0.516 to 0.92 with an average of 0.704. A moderate level of genetic diversity (0.39) was detected among genotypes. Variation to the tune of 8% within genotypes, 68% among the genotypes within the population and 24% among the populations were observed (AMOVA). This information may help in identification of potential parents for development of transgressive segregants with very high yield. The association analysis using GLM and MLM models led to the identification of 30 and 10 SSR markers associated with 70 and 16 QTLs, respectively. Thirty novel QTLs linked with 16 SSRs were identified to be associated with eleven traits, namely tiller number (qTL-6.1, qTL-11.1, qTL-4.1), panicle length (qPL-1.1, qPL-5.1, qPL-7.1, qPL-8.1), flag leaf length (qFLL-8.1, qFLL-9.1), flag leaf width (qFLW-6.2, qFLW-5.1, qFLW-8.1, qFLW-7.1), total no. of grains (qTG-2.2, qTG-a7.1), thousand-grain weight (qTGW-a1.1, qTGW-a9.2, qTGW-5.1, qTGW-8.1), fertile grains (qFG-7.1), seed length-breadth ratio (qSlb-3.1), plant height (qPHT-6.1, qPHT-9.1), days to 50% flowering (qFD-1.1) and grain yield per se (qYLD-5.1, qYLD-6.1a, qYLD-11.1).Some of the SSRs were co-localized with more than two traits. The highest co-localization was identified with RM5709 linked to nine traits, followed by RM297 with five traits. Similarly, RM5575, RM204, RM168, RM112, RM26499 and RM22899 were also recorded to be co-localized with more than one trait and could be rated as important for marker-assisted backcross breeding programs, for pyramiding of these QTLs for important yield traits, to produce new-generation rice for prospective increment in yield potentiality and breaking yield ceiling.

Genome-wide transcriptome profile of rice hybrids with and without Oryza rufipogon introgression reveals candidate genes for yield

In this study, we compared genome-wide transcriptome profile of two rice hybrids, one with (test hybrid IR79156A/IL50-13) and the other without (control hybrid IR79156A/KMR3) O. rufipogon introgressions to identify candidate genes related to grain yield in the test hybrid. IL50-13 (Chinsurah Nona2 IET21943) the male parent (restorer) used in the test hybrid, is an elite BC₄F₈ introgression line of KMR3 with O. rufipogon introgressions. We identified 2798 differentially expressed genes (DEGs) in flag leaf and 3706 DEGs in panicle. Overall, 78 DEGs were within the major yield QTL qyld2.1 and 25 within minor QTL qyld8.2. The DEGs were significantly (p < 0.05) enriched in starch synthesis, phenyl propanoid pathway, ubiquitin degradation and phytohormone related pathways in test hybrid compared to control hybrid. Sequence analysis of 136 DEGs from KMR3 and IL50-13 revealed 19 DEGs with SNP/InDel variations. Of the 19 DEGs only 6 showed both SNP and InDel variations in exon regions. Of these, two DEGs within qyld2.1, Phenylalanine ammonia- lyase (PAL) (Os02t0626400-01, OsPAL2) showed 184 SNPs and 11 InDel variations and Similar to phenylalanine ammonia- lyase (Os02t0627100-01, OsPAL4) showed 205 SNPs and 13 InDel variations. Both PAL genes within qyld2.1 and derived from O. rufipogon are high priority candidate genes for increasing grain yield in rice.

Linkage disequilibrium mapping for grain Fe and Zn enhancing QTLs useful for nutrient dense rice breeding

BACKGROUND

High yielding rice varieties are usually low in grain iron (Fe) and zinc (Zn) content. These two micronutrients are involved in many enzymatic activities, lack of which cause many disorders in human body. Bio-fortification is a cheaper and easier way to improve the content of these nutrients in rice grain.

RESULTS

A population panel was prepared representing all the phenotypic classes for grain Fe-Zn content from 485 germplasm lines. The panel was studied for genetic diversity, population structure and association mapping of grain Fe-Zn content in the milled rice. The population showed linkage disequilibrium showing deviation of Hardy-Weinberg's expectation for Fe-Zn content in rice. Population structure at K = 3 categorized the panel population into distinct sub-populations corroborating with their grain Fe-Zn content. STRUCTURE analysis revealed a common primary ancestor for each sub-population. Novel quantitative trait loci (QTLs) namely qFe3.3 and qFe7.3 for grain Fe and qZn2.2, qZn8.3 and qZn12.3 for Zn content were detected using association mapping. Four QTLs, namely qFe3.3, qFe7.3, qFe8.1 and qFe12.2 for grain Fe content were detected to be co-localized with qZn3.1, qZn7, qZn8.3 and qZn12.3 QTLs controlling grain Zn content, respectively. Additionally, some Fe-Zn controlling QTLs were co-localized with the yield component QTLs, qTBGW, OsSPL14 and qPN. The QTLs qFe1.1, qFe3.1, qFe5.1, qFe7.1, qFe8.1, qZn6, qZn7 and gRMm9-1 for grain Fe-Zn content reported in earlier studies were validated in this study.

CONCLUSION

Novel QTLs, qFe3.3 and qFe7.3 for grain Fe and qZn2.2, qZn8.3 and qZn12.3 for Zn content were detected for these two traits. Four Fe-Zn controlling QTLs and few yield component QTLs were detected to be co-localized. The QTLs, qFe1.1, qFe3.1, qFe5.1, qFe7.1, qFe8.1, qFe3.3, qFe7.3, qZn6, qZn7, qZn2.2, qZn8.3 and qZn12.3 will be useful for biofortification of the micronutrients. Simultaneous enhancement of Fe-Zn content may be possible with yield component traits in rice.

Identification of Quantitative Trait Loci Associated with Nutrient Use Efficiency Traits, Using SNP Markers in an Early Backcross Population of Rice (Oryza sativa L.)

The development of rice cultivars with nutrient use efficiency (NuUE) is highly crucial for sustaining global rice production in Asia and Africa. However, this requires a better understanding of the genetics of NuUE-related traits and their relationship to grain yield. In this study, simultaneous efforts were made to develop nutrient use efficient rice cultivars and to map quantitative trait loci (QTLs) governing NuUE-related traits in rice. A total of 230 BC₁F₅ introgression lines (ILs) were developed from a single early backcross population involving Weed Tolerant Rice 1, as the recipient parent, and Hao-an-nong, as the donor parent. The ILs were cultivated in field conditions with a different combination of fertilizer schedule under six nutrient conditions: minus nitrogen (–N), minus phosphorus (–P), (–NP), minus nitrogen phosphorus and potassium (–NPK), 75% of recommended nitrogen (75N), and NPK. Analysis of variance revealed that significant differences (p < 0.01) were noted among ILs and treatments for all traits. A high-density linkage map was constructed by using 704 high-quality single nucleotide polymorphism (SNP) markers. A total of 49 main-effect QTLs were identified on all chromosomes, except on chromosome 7, 11 and 12, which are showing 20.25% to 34.68% of phenotypic variation. With further analysis of these QTLs, we refined them to four top hotspot QTLs (QTL harbor-I to IV) located on chromosomes 3, 5, 9, and 11. However, we identified four novel putative QTLs for agronomic efficiency (AE) and 22 QTLs for partial factor productivity (PFP) under –P and 75N conditions. These interval regions of QTLs, several transporters and genes are located that were involved in nutrient uptake from soil to plant organs and tolerance to biotic and abiotic stresses. Further, the validation of these potential QTLs, genes may provide remarkable value for marker-aided selection and pyramiding of multiple QTLs, which would provide supporting evidence for the enhancement of grain yield and cloning of NuUE tolerance-responsive genes in rice.

NOG1 increases grain production in rice

During rice domestication and improvement, increasing grain yield to meet human needs was the primary objective. Rice grain yield is a quantitative trait determined by multiple genes, but the molecular basis for increased grain yield is still unclear. Here, we show that NUMBER OF GRAINS 1 (NOG1), which encodes an enoyl-CoA hydratase/isomerase, increases the grain yield of rice by enhancing grain number per panicle without a negative effect on the number of panicles per plant or grain weight. NOG1 can significantly increase the grain yield of commercial high-yield varieties: introduction of NOG1 increases the grain yield by 25.8% in the NOG1-deficient rice cultivar Zhonghua 17, and overexpression of NOG1 can further increase the grain yield by 19.5% in the NOG1-containing variety Teqing. Interestingly, NOG1 plays a prominent role in increasing grain number, but does not change heading date or seed-setting rate. Our findings suggest that NOG1 could be used to increase rice production.

Locating QTLs controlling overwintering trait in Chinese perennial Dongxiang wild rice

Overwintering (OW) is the process by which rice passes through the winter season and germinates in the following spring. OW is also a typical quantitative inheritance trait. Currently, the molecular genetic basis of OW trait in Chinese perennial Dongxiang wild rice (DXWR) still remains to be known. In this study, a linkage map consisting of 139 simple sequence repeat (SSR) markers was constructed using an F₂ population derived from a cross between DXWR and 93-11. This map covered the rice genome by approximately 1778.72 cM with approximately 12.80 cM average interval. The phenotype data of OW trait were investigated for QTL analysis in the following spring of 2017. The gene ontology (GO) annotation of the M-QTL was performed through the rice genome annotation project system. A major QTL-qOW6 was flanked by RM20069 (16,542,428 bp) and RM3498 (20,982,059 bp) on chromosome 6 and detected repeatedly by both inclusive composite interval and single-marker analysis mapping with an LOD score of 9.45 and explained 22.22% of phenotypic variance. In addition, two small QTLs (qOW2 and qOW3) controlling OW trait were detected on the second and third chromosomes, respectively. No epistatic interaction was detected between these QTLs, suggesting their unique genetic model. A total of 183 candidate genes at qOW6 locus were involved in 887 GO terms. Among them, 52 candidate genes were involved in response to stress. The other 28 candidate genes were related to cell membrane, which might affect the OW trait in perennial DXWR. These results may establish the foundation for understanding the genetic mechanism about OW trait and provide a novel gene resource for OW rice variety improvement.

Identification of QTL Associated with Nitrogen Uptake and Nitrogen Use Efficiency Using High Throughput Genotyped CSSLs in Rice (Oryza sativa L.)

Nitrogen (N) availability is a major factor limiting crop growth and development. Identification of quantitative trait loci (QTL) for N uptake (NUP) and N use efficiency (NUE) can provide useful information regarding the genetic basis of these traits and their associated effects on yield production. In this study, a set of high throughput genotyped chromosome segment substitution lines (CSSLs) derived from a cross between recipient 9311 and donor Nipponbare were used to identify QTL for rice NUP and NUE. Using high throughput sequencing, each CSSL were genotyped and an ultra-high-quality physical map was constructed. A total of 13 QTL, seven for NUP and six for NUE, were identified in plants under hydroponic culture with all nutrients supplied in sufficient quantities. The proportion of phenotypic variation explained by these QTL for NUP and NUE ranged from 3.16-13.99% and 3.76-12.34%, respectively. We also identified several QTL for biomass yield (BY) and grain yield (GY), which were responsible for 3.21-45.54% and 6.28-7.31%, respectively, of observed phenotypic variation. GY were significantly positively correlated with NUP and NUE, with NUP more closely correlated than NUE. Our results contribute information to NUP and NUE improvement in rice.

Back into the wild-Apply untapped genetic diversity of wild relatives for crop improvement

Deleterious effects of climate change and human activities, as well as diverse environmental stresses, present critical challenges to food production and the maintenance of natural diversity. These challenges may be met by the development of novel crop varieties with increased biotic or abiotic resistance that enables them to thrive in marginal lands. However, considering the diverse interactions between crops and environmental factors, it is surprising that evolutionary principles have been underexploited in addressing these food and environmental challenges. Compared with domesticated cultivars, crop wild relatives (CWRs) have been challenged in natural environments for thousands of years and maintain a much higher level of genetic diversity. In this review, we highlight the significance of CWRs for crop improvement by providing examples of CWRs that have been used to increase biotic and abiotic stress resistance/tolerance and overall yield in various crop species. We also discuss the surge of advanced biotechnologies, such as next-generation sequencing technologies and omics, with particular emphasis on how they have facilitated gene discovery in CWRs. We end the review by discussing the available resources and conservation of CWRs, including the urgent need for CWR prioritization and collection to ensure continuous crop improvement for food sustainability.

Identification of QTLs for yield-related traits in RILs derived from the cross between pLIA-1 carrying Oryza longistaminata chromosome segments and Norin 18 in rice

To improve rice yield, a wide genetic pool is necessary. It is therefore important to explore wild rice relatives. Oryza longistaminata is a distantly related wild rice relative that carries the AA genome. Its potential for improving agronomic traits is not well studied. Introgression line (pLIA-1) that carries Oryza longistaminata's chromosome segments, showed high performance in yield-related traits under non-fertilized conditions. Therefore, to illustrate Oryza longistaminata's potential for improving yield-related traits, RILs from the F₁ of a cross between pLIA-1 and Norin 18 were developed and QTL analysis was done using the RAD-Seq method. In total, 36 QTLs for yield-related traits were identified on chromosomes 1, 2, 3, 5, 6, 7, 8, 10, and 11. Clusters of QTLs for strongly correlated traits were also identified on chromosomes 1, 3, 6, and 8. Phenotypic data from recombinant plants for chromosomes 1 and 8 QTL clusters revealed that the pLIA-1 genotype on chromosome 1 region was more important for panicle-related traits and a combination of pLIA-1 genotypes on chromosomes 1 and 8 showed a favorable phenotype under non-fertilized conditions. These results suggest that Oryza longistaminata's chromosome segments carry important alleles that can be used to improve yield-related traits of rice.

Genomics of crop wild relatives: expanding the gene pool for crop improvement

Plant breeders require access to new genetic diversity to satisfy the demands of a growing human population for more food that can be produced in a variable or changing climate and to deliver the high-quality food with nutritional and health benefits demanded by consumers. The close relatives of domesticated plants, crop wild relatives (CWRs), represent a practical gene pool for use by plant breeders. Genomics of CWR generates data that support the use of CWR to expand the genetic diversity of crop plants. Advances in DNA sequencing technology are enabling the efficient sequencing of CWR and their increased use in crop improvement. As the sequencing of genomes of major crop species is completed, attention has shifted to analysis of the wider gene pool of major crops including CWR. A combination of de novo sequencing and resequencing is required to efficiently explore useful genetic variation in CWR. Analysis of the nuclear genome, transcriptome and maternal (chloroplast and mitochondrial) genome of CWR is facilitating their use in crop improvement. Genome analysis results in discovery of useful alleles in CWR and identification of regions of the genome in which diversity has been lost in domestication bottlenecks. Targeting of high priority CWR for sequencing will maximize the contribution of genome sequencing of CWR. Coordination of global efforts to apply genomics has the potential to accelerate access to and conservation of the biodiversity essential to the sustainability of agriculture and food production.

An Efficient Strategy Combining SSR Markers- and Advanced QTL-seq-driven QTL Mapping Unravels Candidate Genes Regulating Grain Weight in Rice

Development and use of genome-wide informative simple sequence repeat (SSR) markers and novel integrated genomic strategies are vital to drive genomics-assisted breeding applications and for efficient dissection of quantitative trait loci (QTLs) underlying complex traits in rice. The present study developed 6244 genome-wide informative SSR markers exhibiting in silico fragment length polymorphism based on repeat-unit variations among genomic sequences of 11 indica, japonica, aus, and wild rice accessions. These markers were mapped on diverse coding and non-coding sequence components of known cloned/candidate genes annotated from 12 chromosomes and revealed a much higher amplification (97%) and polymorphic potential (88%) along with wider genetic/functional diversity level (16-74% with a mean 53%) especially among accessions belonging to indica cultivar group, suggesting their utility in large-scale genomics-assisted breeding applications in rice. A high-density 3791 SSR markers-anchored genetic linkage map (IR 64 × Sonasal) spanning 2060 cM total map-length with an average inter-marker distance of 0.54 cM was generated. This reference genetic map identified six major genomic regions harboring robust QTLs (31% combined phenotypic variation explained with a 5.7-8.7 LOD) governing grain weight on six rice chromosomes. One strong grain weight major QTL region (OsqGW5.1) was narrowed-down by integrating traditional QTL mapping with high-resolution QTL region-specific integrated SSR and single nucleotide polymorphism markers-based QTL-seq analysis and differential expression profiling. This led us to delineate two natural allelic variants in two known cis-regulatory elements (RAV1AAT and CARGCW8GAT) of glycosyl hydrolase and serine carboxypeptidase genes exhibiting pronounced seed-specific differential regulation in low (Sonasal) and high (IR 64) grain weight mapping parental accessions. Our genome-wide SSR marker resource (polymorphic within/between diverse cultivar groups) and integrated genomic strategy can efficiently scan functionally relevant potential molecular tags (markers, candidate genes and alleles) regulating complex agronomic traits (grain weight) and expedite marker-assisted genetic enhancement in rice.

Association mapping of yield-related traits and SSR markers in wild soybean (Glycine soja Sieb. and Zucc.)

Wild soybean, the progenitor of cultivated soybean, is an important gene pool for ongoing soybean breeding efforts. To identify yield-enhancing quantitative trait locus (QTL) or gene from wild soybean, 113 wild soybeans accessions were phenotyped for five yield-related traits and genotyped with 85 simple sequence repeat (SSR) markers to conduct association mapping. A total of 892 alleles were detected for the 85 SSR markers, with an average 10.49 alleles; the corresponding PIC values ranged from 0.07 to 0.92, with an average 0.73. The genetic diversity of each SSR marker ranged from 0.07 to 0.93, with an average 0.75. A total of 18 SSR markers were identified for the five traits. Two SSR markers, sct_010 and satt316, which are associated with the yield per plant were stably expressed over two years at two experimental locations. Our results suggested that association mapping can be an effective approach for identifying QTL from wild soybean.

The International Oryza Map Alignment Project: development of a genus-wide comparative genomics platform to help solve the 9 billion-people question

The wild relatives of rice contain a virtually untapped reservoir of traits that can be used help drive the 21st century green revolution aimed at solving world food security issues by 2050. To better understand and exploit the 23 species of the Oryza genus the rice research community is developing foundational resources composed of: 1) reference genomes and transcriptomes for all 23 species; 2) advanced mapping populations for functional and breeding studies; and 3) in situ conservation sites for ecological, evolutionary and population genomics. To this end, 16 genome sequencing projects are currently underway, and all completed assemblies have been annotated; and several advanced mapping populations have been developed, and more will be generated, mapped, and phenotyped, to uncover useful alleles. As wild Oryza populations are threatened by human activity and climate change, we also discuss the urgent need for sustainable in situ conservation of the genus.

Effects of an exogenous xylanase gene expression on the growth of transgenic rice and the expression level of endogenous xylanase inhibitor gene RIXI

BACKGROUND

Xylanases have attracted considerable interest in recent years owing to their various applications in industry and agriculture. The use of transgenic plants to produce xylanases is a less expensive alternative to biotechnological programmes. The aim of this study was to elucidate whether introducing a foreign xylanase gene ATX into rice had any adverse effect on plant growth and development.

RESULTS

A recombinant xylanase gene ATX was introduced into rice variety Zhonghua 11 through Agrobacterium-mediated transformation. The T₂ generation of transgenic rice was compared with the control (non-transgenic plants). Exogenous xylanase gene ATX was expressed in rice, and all examined transgenic lines exhibited xylanase activity. The transgenic lines (T₂, 'X1-3' and 'X2-5') appeared to grow and develop normally. There were no differences in net photosynthetic rate between transgenic rice lines ('X1-3' and 'X2-5') and wild type (WT) rice plants at the heading/flowering stage. Xylanases are key enzymes in the degradation of plant cell walls. Cell wall composition analysis showed that that there were no changes in cell wall polysaccharides in the root apex but some alterations in leaves in transgenic rice plants. The results also showed that the expression of exogenous xylanase gene ATX in rice would increase the expression of endogenous xylanase inhibitor gene RIXI, which could play a role in plant defence. Thus the stress resistance of transgenic rice plants might be improved.

CONCLUSION

Exogenous xylanase gene ATX could be successfully expressed in rice, and the exogenous protein had no apparent harmful effects on growth and development in transgenic rice plants.

Mapping QTLs and candidate genes for iron and zinc concentrations in unpolished rice of Madhukar×Swarna RILs

Identifying QTLs/genes for iron and zinc in rice grains can help in biofortification programs. 168 F(7) RILs derived from Madhukar×Swarna were used to map QTLs for iron and zinc concentrations in unpolished rice grains. Iron ranged from 0.2 to 224 ppm and zinc ranged from 0.4 to 104ppm. Genome wide mapping using 101 SSRs and 9 gene specific markers showed 5 QTLs on chromosomes 1, 3, 5, 7 and 12 significantly linked to iron, zinc or both. In all, 14 QTLs were identified for these two traits. QTLs for iron were co-located with QTLs for zinc on chromosomes 7 and 12. In all, ten candidate genes known for iron and zinc homeostasis underlie 12 of the 14 QTLs. Another 6 candidate genes were close to QTLs on chromosomes 3, 5 and 7. Thus the high priority candidate genes for high Fe and Zn in seeds are OsYSL1 and OsMTP1 for iron, OsARD2, OsIRT1, OsNAS1, OsNAS2 for zinc and OsNAS3, OsNRAMP1, Heavy metal ion transport and APRT for both iron and zinc together based on our genetic mapping studies as these genes strictly underlie QTLs. Several elite lines with high Fe, high Zn and both were identified.

[Discovery of QTLs increasing yield related traits in common wild rice]

Common wild rice (Oryza rufipogon) is an important genetic resource. Discovery of desirable alleles in wild rice will make important contributions to rice genetic improvement. In this study, Zhenshan 97 as the recurrent parent and wild rice as the donor parent were used to develop a BC2F1 population. One plant BC2F1-15 in the population showed distinct phenotype from Zhenshan 97 was selected to produce a population of BC2F5 by continuous self-crossing. The genotype assay of the plant BC2F1-15 with 126 polymorphic SSR markers evenly distributed on 12 chromosomes showed that it was heterozygous at 30% of the control marker loci. Four, 3, 4, 2, and 1 QTLs were detected for heading date, plant height, spikelets per panicle, grain weight, and single plant yield in the BC2F5 population, respectively. One QTL region flanked by the marker interval of RM481-RM2 on chromosome 7 had pleiotropic effects on heading date, spikelets per panicle, and grain yield per plant, and the alleles of wild rice increased phenotypic values. At the other 3 QTLs for spikelets per panicle, common wild rice had positive effects. These results clearly showed that common wild rice carried desirable alleles for yield related traits. The favorable alleles from common wild rice are new valuable genes for rice breeding.

Os11Gsk gene from a wild rice, Oryza rufipogon improves yield in rice

Chromosomal segments from wild rice species Oryza rufipogon, introgressed into an elite indica rice restorer line (KMR3) using molecular markers, resulted in significant increase in yield. Here we report the transcriptome analysis of flag leaves and fully emerged young panicles of one of the high yielding introgression lines IL50-7 in comparison to KMR3. A 66-fold upregulated gene Os11Gsk, which showed no transcript in KMR3 was highly expressed in O. rufipogon and IL50-7. A 5-kb genomic region including Os11Gsk and its flanking regions could be PCR amplified only from IL50-7, O. rufipogon, japonica varieties of rice-Nipponbare and Kitaake but not from the indica varieties, KMR3 and Taichung Native-1. Three sister lines of IL50-7 yielding higher than KMR3 showed presence of Os11Gsk, whereas the gene was absent in three other ILs from the same cross having lower yield than KMR3, indicating an association of the presence of Os11Gsk with high yield. Southern analysis showed additional bands in the genomic DNA of O. rufipogon and IL50-7 with Os11Gsk probe. Genomic sequence analysis of ten highly co-expressed differentially regulated genes revealed that two upregulated genes in IL50-7 were derived from O. rufipogon and most of the downregulated genes were either from KMR3 or common to KMR3, IL50-7, and O. rufipogon. Thus, we show that Os11Gsk is a wild rice-derived gene introduced in KMR3 background and increases yield either by regulating expression of functional genes sharing homology with it or by causing epigenetic modifications in the introgression line.

Unraveling the complex trait of harvest index with association mapping in rice (Oryza sativa L.)

Harvest index is a measure of success in partitioning assimilated photosynthate. An improvement of harvest index means an increase in the economic portion of the plant. Our objective was to identify genetic markers associated with harvest index traits using 203 O. sativa accessions. The phenotyping for 14 traits was conducted in both temperate (Arkansas) and subtropical (Texas) climates and the genotyping used 154 SSRs and an indel marker. Heading, plant height and weight, and panicle length had negative correlations, while seed set and grain weight/panicle had positive correlations with harvest index across both locations. Subsequent genetic diversity and population structure analyses identified five groups in this collection, which corresponded to their geographic origins. Model comparisons revealed that different dimensions of principal components analysis (PCA) affected harvest index traits for mapping accuracy, and kinship did not help. In total, 36 markers in Arkansas and 28 markers in Texas were identified to be significantly associated with harvest index traits. Seven and two markers were consistently associated with two or more harvest index correlated traits in Arkansas and Texas, respectively. Additionally, four markers were constitutively identified at both locations, while 32 and 24 markers were identified specifically in Arkansas and Texas, respectively. Allelic analysis of four constitutive markers demonstrated that allele 253 bp of RM431 had significantly greater effect on decreasing plant height, and 390 bp of RM24011 had the greatest effect on decreasing panicle length across both locations. Many of these identified markers are located either nearby or flanking the regions where the QTLs for harvest index have been reported. Thus, the results from this association mapping study complement and enrich the information from linkage-based QTL studies and will be the basis for improving harvest index directly and indirectly in rice.

Nutrigenomics and personalized diets: What will they mean for food?

The modern food system feeds six billion people with remarkable diversity, safety, and nutrition. Yet, the current rise in diet-related diseases is compromising health and devaluing many aspects of modern agriculture. Steps to increase the nutritional quality of individual foods will assist in personalizing health and in guiding individuals to achieve superior health. Nutrigenomics is the scientific field of the genetic basis for varying susceptibilities to disease and the diverse responses to foods. Although some of these genetic determinants will be simple and amenable to personal genotyping as the means to predict health, in practice most will not. As a result, genotyping will not be the secret to personalizing diet and health. Human assessment technologies from imaging to proteomics and metabolomics are providing tools to both understand and accurately assess the nutritional phenotype of individuals. The business models are also emerging to bring these assessment capabilities to industrial practice, in which consumers will know more about their personal health and seek personal solutions.

Mapping QTLs for improving grain yield using the USDA rice mini-core collection

Yield is the most important and complex trait for genetic improvement in crops, and marker-assisted selection enhances the improvement efficiency. The USDA rice mini-core collection derived from over 18,000 accessions of global origins is an ideal panel for association mapping. We phenotyped 203 O. sativa accessions for 14 agronomic traits and identified 5 that were highly and significantly correlated with grain yield per plant: plant height, plant weight, tillers, panicle length, and kernels/branch. Genotyping with 155 genome-wide molecular markers demonstrated 5 main cluster groups. Linkage disequilibrium (LD) decayed at least 20 cM and marker pairs with significant LD ranged from 4.64 to 6.06% in four main groups. Model comparisons revealed that different dimensions of principal component analysis affected yield and its correlated traits for mapping accuracy, and kinship did not improve the mapping in this collection. Thirty marker-trait associations were highly significant, 4 for yield, 3 for plant height, 6 for plant weight, 9 for tillers, 5 for panicle length and 3 for kernels/branch. Twenty-one markers contributed to the 30 associations, because 8 markers were co-associated with 2 or more traits. Allelic analysis of OSR13, RM471 and RM7003 for their co-associations with yield traits demonstrated that allele 126 bp of RM471 and 108 bp of RM7003 should receive greater attention, because they had the greatest positive effect on yield traits. Tagging the QTLs responsible for multiple yield traits may simultaneously help dissect the complex yield traits and elevate the efficiency to improve grain yield using marker-assisted selection in rice.