Drought tolerance genes in rice

Quantitative trait loci (QTLs) for drought tolerance (DT) can be readily identified in available databases and in this paper, these QTLs were summarized in the form of a consensus map. An in silico strategy was then deployed to mine for candidate genes associated with DT QTLs using rice dbEST and rice genome databases. DT QTLs on rice chromosomes 1, 2, 4, 8, and 9 were selected to test the method. The result showed candidate genes associated with DT could be readily identified.     

Identification of QTLs for Yield and Associated Traits in F₂ Population of Rice

Identification of quantitative trait loci (QTLs) controlling yield and yield-related traits in rice was performed in the F₂ mapping population derived from parental rice genotypes DHMAS and K343. A total of 30 QTLs governing nine different traits were identified using the composite interval mapping (CIM) method. Four QTLs were mapped for number of tillers per plant on chromosomes 1 (2 QTLs), 2 and 3; three QTLs for panicle number per plant on chromosomes 1 (2 QTLs) and 3; four QTLs for plant height on chromosomes 2, 4, 5 and 6; one QTL for spikelet density on chromosome 5; four QTLs for spikelet fertility percentage (SFP) on chromosomes 2, 3 and 5 (2 QTLs); two QTLs for grain length on chromosomes 1 and 8; three QTLs for grain width on chromosomes1, 3 and 8; three QTLs for 1000-grain weight (TGW) on chromosomes 1, 4 and 8 and six QTLs for yield per plant (YPP) on chromosomes 2 (3 QTLs), 4, 6 and 8. Most of the QTLs were detected on chromosome 2, so further studies on chromosome 2 could help unlock some new chapters of QTL for this cross of rice variety. Identified QTLs elucidating high phenotypic variance can be used for marker-assisted selection (MAS) breeding. Further, the exploitation of information regarding molecular markers tightly linked to QTLs governing these traits will facilitate future crop improvement strategies in rice.     

Genome-wide association mapping of salinity tolerance in rice (Oryza sativa)

Salinity tolerance in rice is highly desirable to sustain production in areas rendered saline due to various reasons. It is a complex quantitative trait having different components, which can be dissected effectively by genome-wide association study (GWAS). Here, we implemented GWAS to identify loci controlling salinity tolerance in rice. A custom-designed array based on 6,000 single nucleotide polymorphisms (SNPs) in as many stress-responsive genes, distributed at an average physical interval of <100 kb on 12 rice chromosomes, was used to genotype 220 rice accessions using Infinium high-throughput assay. Genetic association was analysed with 12 different traits recorded on these accessions under field conditions at reproductive stage. We identified 20 SNPs (loci) significantly associated with Na⁺/K⁺ ratio, and 44 SNPs with other traits observed under stress condition. The loci identified for various salinity indices through GWAS explained 5–18% of the phenotypic variance. The region harbouring Saltol, a major quantitative trait loci (QTLs) on chromosome 1 in rice, which is known to control salinity tolerance at seedling stage, was detected as a major association with Na⁺/K⁺ ratio measured at reproductive stage in our study. In addition to Saltol, we also found GWAS peaks representing new QTLs on chromosomes 4, 6 and 7. The current association mapping panel contained mostly indica accessions that can serve as source of novel salt tolerance genes and alleles. The gene-based SNP array used in this study was found cost-effective and efficient in unveiling genomic regions/candidate genes regulating salinity stress tolerance in rice.     

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 224ppm 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.     

QTL mapping and GWAS reveal candidate genes controlling capsaicinoid content in Capsicum

Capsaicinoids are unique compounds produced only in peppers (Capsicum spp.). Several studies using classical quantitative trait loci (QTLs) mapping and genomewide association studies (GWAS) have identified QTLs controlling capsaicinoid content in peppers; however, neither the QTLs common to each population nor the candidate genes underlying them have been identified due to the limitations of each approach used. Here, we performed QTL mapping and GWAS for capsaicinoid content in peppers using two recombinant inbred line (RIL) populations and one GWAS population. Whole‐genome resequencing and genotyping by sequencing (GBS) were used to construct high‐density single nucleotide polymorphism (SNP) maps. Five QTL regions on chromosomes 1, 2, 3, 4 and 10 were commonly identified in both RIL populations over multiple locations and years. Furthermore, a total of 109 610 SNPs derived from two GBS libraries were used to analyse the GWAS population consisting of 208 C. annuum‐clade accessions. A total of 69 QTL regions were identified from the GWAS, 10 of which were co‐located with the QTLs identified from the two biparental populations. Within these regions, we were able to identify five candidate genes known to be involved in capsaicinoid biosynthesis. Our results demonstrate that QTL mapping and GBS‐GWAS represent a powerful combined approach for the identification of loci controlling complex traits.     

Coincidence in map positions between pathogen-induced defense-responsive genes and quantitative resistance loci in rice

Quantitative disease resistance conferred by quantitative trait loci (QTLs) is presumably of wider spectrum and durable. Forty-four cDNA clones, representing 44 defense-responsive genes, were fine mapped to 56 loci distributed on 9 of the 12 rice chromosomes. The locations of 32 loci detected by 27 cDNA clones were associated with previously identified resistance QTLs for different rice diseases, including blast, bacterial blight, sheath blight and yellow mottle virus. The loci detected by the same multiple-copy cDNA clones were frequently located on similar locations of different chromosomes. Some of the multiple loci detected by the same clones were all associated with resistance QTLs. These results suggest that some of the genes may be important components in regulation of defense responses against pathogen invasion and they may be the candidates for studying the mechanism of quantitative disease resistance in rice.     

Coincidence in map positions between pathogen-induced defense-responsive genes and quantitative resistance loci in rice

Quantitative disease resistance conferred by quantitative trait loci (QTLs) is presumably of wider spectrum and durable. Forty-four cDNA clones, representing 44 defense-responsive genes, were fine mapped to 56 loci distributed on 9 of the 12 rice chromosomes. The locations of 32 loci detected by 27 cDNA clones were associated with previously identified resistance QTLs for different rice diseases, including blast, bacterial blight, sheath blight and yellow mottle virus. The loci detected by the same multiple-copy cDNA clones were frequently located on similar locations of different chromosomes. Some of the multiple loci detected by the same clones were all associated with resistance QTLs. These results suggest that some of the genes may be important components in regulation of defense responses against pathogen invasion and they may be the candidates for studying the mechanism of quantitative disease resistance in rice.     

RFLP mapping of isozymes,RAPD and QTLs for grain shape,brown planthopper resistance in a doubled haploid rice population

We have developed an RFLP framework map with 146 RFLP markers based on a doubled haploid population derived from a cross between an indica variety IR64 and a japonica variety Azucena. The population carries 50.2% of IR64 loci and 49.8% of Azucena loci, indicating an equal amount of genetic materials from each parent has been transmitted to the progenies through anther culture. However, some markers show segregation distortion. These distorted marker loci are located on 10 chromosomal segments. Using this map we were able to place 8 isozymes, 14 RAPDs, 12 cloned genes, 1 gene for brown planthopper (BPH) resistance, and 12 QTLs for grain length, grain width and length/width ratio onto rice chromosomes. The major gene for BPH resistance was mapped on chromosome 12 near RG463 and isozyme Sdh-1. Most of the QTLs identified for the three grain characters were closely linked on chromosomes 1, 2, 3 and 10. We concluded that the RFLP framework map presented here will be useful for mapping other genes segregating in this doubled haploid population. Thus rapid generation of doubled haploid lines and their unbiased segregation make it very attractive for gene mapping.     

Differences in DBA/1J and DBA/2J reveal lipid QTL genes

Recent advances in mouse genomics have revealed considerable variation in the form of single-nucleotide polymorphisms (SNPs) among common inbred strains. This has made it possible to characterize closely related strains and to identify genes that differ; such genes may be causal for quantitative phenotypes. The mouse strains DBA/1J and DBA/2J differ by just 5.6% at the SNP level. These strains exhibit differences in a number of metabolic and lipid phenotypes, such as plasma levels of triglycerides (TGs) and HDL. A cross between these strains revealed multiple quantitative trait loci (QTLs) in 294 progeny. We identified significant TG QTLs on chromosomes (Chrs) 1, 2, 3, 4, 8, 9, 10, 11, 12, 13, 14, 16, and 19, and significant HDL QTLs on Chrs 3, 9, and 16. Some QTLs mapped to chromosomes with limited variability between the two strains, thus facilitating the identification of candidate genes. We suggest that Tshr is the QTL gene for Chr 12 TG and HDL levels and that Ihh may account for the TG QTL on Chr 1. This cross highlights the advantage of crossing closely related strains for subsequent identification of QTL genes.     

Identification of stably expressed quantitative trait loci for cooked rice elongation in non-Basmati varieties.

The elongation of the cooked grain determines the cooking and eating quality of Basmati rice. The identification of stable quantitative trait loci (QTLs), especially those from non-Basmati types, will extend the genetic basis of the Basmati type and facilitate the breeding of high-quality varieties. A set of recombinant inbred lines derived from an indica x japonica hybrid was used to identify QTLs controlling the elongation ratio (ER), elongation index (EI), and water absorption (WA) of the cooked grain. Three ER QTLs on chromosomes 2, 4, and 12, two EI QTLs on chromosomes 2 and 5, and two WA QTLs on chromosomes 2 and 6 were detected. Four of these QTLs were validated using a set of established chromosome segment substitution lines. The genetic effect of qER-2 was explored in an analysis of segregating generations, using 8 newly developed simple sequence repeat markers. Two tightly linked loci (qER-2a and qER-2b) were identified on chromosome 2.     

Discovery and genetic mapping of single nucleotide polymorphisms in candidate genes for pathogen defence response in perennial ryegrass (<Emphasis Type="Italic">Lolium perenne</Emphasis> L.)

Susceptibility to foliar pathogens commonly causes significant reductions in productivity of the important temperate forage perennial ryegrass. Breeding for durable disease resistance involves not only the deployment of major genes but also the additive effects of minor genes. An approach based on in vitro single nucleotide polymorphism (SNP) discovery in candidate defence response (DR) genes has been used to develop potential diagnostic genetic markers. SNPs were predicted, validated and mapped for representatives of the pathogenesis-related (PR) protein-encoding and reactive oxygen species (ROS)-generating gene classes. The F(1)(NA(6) x AU(6)) two-way pseudo-test cross population was used for SNP genetic mapping and detection of quantitative trait loci (QTLs) in response to a crown rust field infection. Novel resistance QTLs were coincident with mapped DR gene SNPs. QTLs on LG3 and LG7 also coincided with both herbage quality QTLs and candidate genes for lignin biosynthesis. Multiple DR gene SNP loci additionally co-located with QTLs for grey leaf spot, bacterial wilt and crown rust resistance from other published studies. Further functional validation of DR gene SNP loci using methods such as fine-mapping and association genetics will improve the efficiency of parental selection based on superior allele content.     

Nested‐association mapping (NAM)‐based genetic dissection uncovers candidate genes for seed and pod weights in peanut (Arachis hypogaea)

Multiparental genetic mapping populations such as nested‐association mapping (NAM) have great potential for investigating quantitative traits and associated genomic regions leading to rapid discovery of candidate genes and markers. To demonstrate the utility and power of this approach, two NAM populations, NAM_Tifrunner and NAM_Florida‐07, were used for dissecting genetic control of 100‐pod weight (PW) and 100‐seed weight (SW) in peanut. Two high‐density SNP‐based genetic maps were constructed with 3341 loci and 2668 loci for NAM_Tifrunner and NAM_Florida‐07, respectively. The quantitative trait locus (QTL) analysis identified 12 and 8 major effect QTLs for PW and SW, respectively, in NAM_Tifrunner, and 13 and 11 major effect QTLs for PW and SW, respectively, in NAM_Florida‐07. Most of the QTLs associated with PW and SW were mapped on the chromosomes A05, A06, B05 and B06. A genomewide association study (GWAS) analysis identified 19 and 28 highly significant SNP–trait associations (STAs) in NAM_Tifrunner and 11 and 17 STAs in NAM_Florida‐07 for PW and SW, respectively. These significant STAs were co‐localized, suggesting that PW and SW are co‐regulated by several candidate genes identified on chromosomes A05, A06, B05, and B06. This study demonstrates the utility of NAM population for genetic dissection of complex traits and performing high‐resolution trait mapping in peanut.     

QTL mapping of grain quality traits from the interspecific cross <Emphasis Type="Italic">Oryza sativa</Emphasis> × <Emphasis Type="Italic">O. glaberrima</Emphasis>

International rice export markets are increasing demands for rapid improvements in grain quality characteristics. The African rice Oryza glaberrima is a new potential source of genes that will enhance the eating, cooking, and milling properties of the rice grain. The objective of this research was to identify and characterize quantitative trait loci (QTLs) among 312 doubled haploid lines derived from the BC₃F₁ of an interspecific cross of O. sativa × O. glaberrima. Genetic material was planted in replicated plots and evaluated for ten grain quality traits in 2001 in Colombia. A linkage map was constructed with 100 polymorphic microsatellite markers using the mapdisto software program to adjust for segregation distortion. Transgressive segregation was observed for all traits. Interval and composite interval analyses identified 27 QTLs for nine characters located on 11/12 chromosomes. The chromosomal positions of QTLs for percentage amylose, alkali-spreading score, and percentage protein were in agreement with data reported by others, whereas QTL markers for percentage head rice, percentage milled rice, percentage protein, and percentage brown rice were different in our mapping population. Five major QTLs were found to be associated with improved percentage rice bran, percentage amylose, and alkali-spreading score. Seven QTLs for improved percentage rice bran, percentage milled rice, alkali-spreading score, percentage protein, and grain length/width ratio were derived from the O. glaberrima accession. Three new QTLs for percentage rice bran are reported here for the first time. Results from this study suggest that the African rice might be a valuable new source for introgression and improvement of several traits that affect quality traits demanded by the different rice export markets.Approved for publication by the Director of the Louisiana Agricultural Experiment Station as paper no. 04-14-0054.     

Genetic dissection of starch paste viscosity characteristics in waxy maize revealed by high-density SNPs in a recombinant inbred line population

Starch paste viscosity properties are widely used as important indicators for quality estimation in waxy maize. To elucidate the genetic basis of paste viscosity characteristics of waxy maize, seven parameters from the rapid visco analyzer (RVA) profile were analyzed for quantitative trait loci (QTLs) in this study, using a recombinant inbred line population derived from a cross between the inbred lines Tongxi5 and Hengbai522. A high-density linkage map was constructed using 2703 bin markers, covering 1876.20 cM of the whole genome with an average genetic distance of 0.73 cM between adjacent bin markers. Seventy-two QTLs were detected for RVA parameters across 3 years, of which 17 could be identified in 2 years, and 6 identified in all 3 years. Eight QTL clusters were observed to be co-associated with two or more RVA parameters. Three major QTLs, qPV4-1, qTV4-1, and qFV5-2, which explained over 10% of the phenotypic variation, were stably mapped to the chromosomes 4 or 5 in all years. Based on functional annotations, two genes were considered as potential candidate genes for the identified major QTLs. The QTLs and candidate genes identified in this study will be useful for further understanding of the genetic architecture of starch paste viscosity characteristics in waxy maize, and may facilitate molecular breeding for grain quality improvement in breeding programs, and simultaneously provide a basis for cloning of the genes underlying these QTLs.     

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

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

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

Key Message

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

Abstract

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

Genotyping‐by‐sequencing‐based genome‐wide association studies on Verticillium wilt resistance in autotetraploid alfalfa (Medicago sativa L.)

Verticillium wilt (VW) is a fungal disease that causes severe yield losses in alfalfa. The most effective method to control the disease is through the development and use of resistant varieties. The identification of marker loci linked to VW resistance can facilitate breeding for disease‐resistant alfalfa. In the present investigation, we applied an integrated framework of genome‐wide association with genotyping‐by‐sequencing (GBS) to identify VW resistance loci in a panel of elite alfalfa breeding lines. Phenotyping was performed by manual inoculation of the pathogen to healthy seedlings, and scoring for disease resistance was carried out according to the standard test of the North America Alfalfa Improvement Conference (NAAIC). Marker–trait association by linkage disequilibrium identified 10 single nucleotide polymorphism (SNP) markers significantly associated with VW resistance. Alignment of the SNP marker sequences to the M. truncatula genome revealed multiple quantitative trait loci (QTLs). Three, two, one and five markers were located on chromosomes 5, 6, 7 and 8, respectively. Resistance loci found on chromosomes 7 and 8 in the present study co‐localized with the QTLs reported previously. A pairwise alignment (blastn ) using the flanking sequences of the resistance loci against the M. truncatula genome identified potential candidate genes with putative disease resistance function. With further investigation, these markers may be implemented into breeding programmes using marker‐assisted selection, ultimately leading to improved VW resistance in alfalfa.     

Quantitative trait locus analysis for rice panicle and grain characteristics

 The development of molecular genetic maps has accelerated the identification and mapping of genomic regions controlling quantitative characters, referred to as quantitative trait loci or QTLs. A molecular map derived from an F₂ population of a tropical japonica×indica cross (Labelle/Black Gora) consisted of 116 restriction fragment length polymorphism (RFLP) markers. Composite interval mapping was used to identify the QTLs controlling six panicle and grain characteristics. Two QTLs were identified for panicle size at LOD>3.0, with one on chromosome 3 accounting for 16% of the phenotypic variation. Four loci controlling spikelet fertility accounted for 23% of the phenotypic variation. Seven, four, three and two QTLs were detected for grain length, breadth, shape and weight, respectively, with the most prominent QTLs being on chromosomes 3, 4, and 7. Grain shape, measured as the ratio of length to breadth, was mostly controlled by loci on chromosomes 3 and 7 that coincided with the most important QTLs identified for length and breadth, respectively. A model including three loci accounted for 45% of the phenotypic variation for this trait. The identification of economically important QTLs will be useful in breeding for improved grain characteristics. Received: 18 July 1997 / Accepted: 9 December 1997