Genome-wide association mapping of yield and yield components of spring wheat under contrasting moisture regimes

Key message

A stable QTL that may be used in marker-assisted selection in wheat breeding programs was detected for yield, yield components and drought tolerance-related traits in spring wheat association mapping panel.

Abstract

Genome-wide association mapping has become a widespread method of quantitative trait locus (QTL) identification for many crop plants including wheat (Triticum aestivum L.). Its benefit over traditional bi-parental mapping approaches depends on the extent of linkage disequilibrium in the mapping population. The objectives of this study were to determine linkage disequilibrium decay rate and population structure in a spring wheat association mapping panel (n = 285–294) and to identify markers associated with yield and yield components, morphological, phenological, and drought tolerance-related traits. The study was conducted under fully irrigated and rain-fed conditions at Greeley, CO, USA and Melkassa, Ethiopia in 2010 and 2011 (five total environments). Genotypic data were generated using diversity array technology markers. Linkage disequilibrium decay rate extended over a longer genetic distance for the D genome (6.8 cM) than for the A and B genomes (1.7 and 2.0 cM, respectively). Seven subpopulations were identified with population structure analysis. A stable QTL was detected for grain yield on chromosome 2DS both under irrigated and rain-fed conditions. A multi-trait region significant for yield and yield components was found on chromosome 5B. Grain yield QTL on chromosome 1BS co-localized with harvest index QTL. Vegetation indices shared QTL with harvest index on chromosome 1AL and 5A. After validation in relevant genetic backgrounds and environments, QTL detected in this study for yield, yield components and drought tolerance-related traits may be used in marker-assisted selection in wheat breeding programs.     

Detection of favorable alleles for yield and yield components by association mapping in upland cotton

Association mapping based on linkage disequilibrium provides a promising tool for dissecting the genetic basis underlying complex traits. To reveal the genetic variations of yield and yield components traits in upland cotton, 403 upland cotton accessions were collected and analyzed by 560 genome-wide simple sequence repeats (SSRs). A diverse panel consisting of 403 upland cotton accessions was grown in six different environments, and the yield and yield component traits were measured, and 560 SSR markers covering the whole genome were mapped. Association studies were performed to uncover the genotypic and phenotypic variations using a mixed linear model. Favorable alleles and typical accessions for yield traits were identified. A total of 201 markers were polymorphic, revealing 394 alleles. The average gene diversity and polymorphism information content were 0.556 and 0.483, respectively. Based on a population structure analysis, 403 accessions were divided into two subgroups. A mixed linear model analysis of the association mapping detected 43 marker loci according to the best linear unbiased prediction and in at least three of the six environments(??lgP?>?1.30, P?<?0.05). Among the 43 associated markers, five were associated with more than two traits simultaneously and nine were coincident with those identified previously. Based on phenotypic effects, favorable alleles and typical accessions that contained the elite allele loci related to yield traits were identified and are widely used in practical breeding. This study detected favorable quantitative trait loci’s alleles and typical accessions for yield traits, these are excellent genetic resources for future high-yield breeding by marker-assisted selection in upland cotton in China.     

Genome-Wide Association Mapping for Yield and Other Agronomic Traits in an Elite Breeding Population of Tropical Rice (Oryza sativa)

Genome-wide association mapping studies (GWAS) are frequently used to detect QTL in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome. Generally, diversity panels genotyped with high density SNP panels are utilized in order to assay a wide range of alleles and haplotypes and to monitor recombination breakpoints across the genome. By contrast, GWAS have not generally been performed in breeding populations. In this study we performed association mapping for 19 agronomic traits including yield and yield components in a breeding population of elite irrigated tropical rice breeding lines so that the results would be more directly applicable to breeding than those from a diversity panel. The population was genotyped with 71,710 SNPs using genotyping-by-sequencing (GBS), and GWAS performed with the explicit goal of expediting selection in the breeding program. Using this breeding panel we identified 52 QTL for 11 agronomic traits, including large effect QTLs for flowering time and grain length/grain width/grain-length-breadth ratio. We also identified haplotypes that can be used to select plants in our population for short stature (plant height), early flowering time, and high yield, and thus demonstrate the utility of association mapping in breeding populations for informing breeding decisions. We conclude by exploring how the newly identified significant SNPs and insights into the genetic architecture of these quantitative traits can be leveraged to build genomic-assisted selection models.     

Performance of single nucleotide polymorphisms versus haplotypes for genome-wide association analysis in barley

Genome-wide association studies (GWAS) may benefit from utilizing haplotype information for making marker-phenotype associations. Several rationales for grouping single nucleotide polymorphisms (SNPs) into haplotype blocks exist, but any advantage may depend on such factors as genetic architecture of traits, patterns of linkage disequilibrium in the study population, and marker density. The objective of this study was to explore the utility of haplotypes for GWAS in barley (Hordeum vulgare) to offer a first detailed look at this approach for identifying agronomically important genes in crops. To accomplish this, we used genotype and phenotype data from the Barley Coordinated Agricultural Project and constructed haplotypes using three different methods. Marker-trait associations were tested by the efficient mixed-model association algorithm (EMMA). When QTL were simulated using single SNPs dropped from the marker dataset, a simple sliding window performed as well or better than single SNPs or the more sophisticated methods of blocking SNPs into haplotypes. Moreover, the haplotype analyses performed better 1) when QTL were simulated as polymorphisms that arose subsequent to marker variants, and 2) in analysis of empirical heading date data. These results demonstrate that the information content of haplotypes is dependent on the particular mutational and recombinational history of the QTL and nearby markers. Analysis of the empirical data also confirmed our intuition that the distribution of QTL alleles in nature is often unlike the distribution of marker variants, and hence utilizing haplotype information could capture associations that would elude single SNPs. We recommend routine use of both single SNP and haplotype markers for GWAS to take advantage of the full information content of the genotype data.     

Understanding genetic control of root system architecture in soybean: Insights into the genetic basis of lateral root number

Developing crops with better root systems is a promising strategy to ensure productivity in both optimum and stress environments. Root system architectural traits in 397 soybean accessions were characterized and a high‐density single nucleotide polymorphisms (SNPs)‐based genome‐wide association study was performed to identify the underlying genes associated with root structure. SNPs associated with root architectural traits specific to landraces and elite germplasm pools were detected. Four loci were detected in landraces for lateral root number (LRN) and distribution of root thickness in diameter Class I with a major locus on chromosome 16. This major loci was detected in the coding region of unknown protein, and subsequent analyses demonstrated that root traits are affected with mutated haplotypes of the gene. In elite germplasm pool, 3 significant SNPs in alanine‐glyoxalate aminotransferase, Leucine‐Rich Repeat receptor/No apical meristem, and unknown functional genes were found to govern multiple traits including root surface area and volume. However, no major loci were detected for LRN in elite germplasm. Nucleotide diversity analysis found evidence of selective sweeps around the landraces LRN gene. Soybean accessions with minor and mutated allelic variants of LRN gene were found to perform better in both water‐limited and optimal field conditions.     

Genome-Wide Association Studies Using Haplotypes and Individual SNPs in Simmental Cattle

Recent advances in high-throughput genotyping technologies have provided the opportunity to map genes using associations between complex traits and markers. Genome-wide association studies (GWAS) based on either a single marker or haplotype have identified genetic variants and underlying genetic mechanisms of quantitative traits. Prompted by the achievements of studies examining economic traits in cattle and to verify the consistency of these two methods using real data, the current study was conducted to construct the haplotype structure in the bovine genome and to detect relevant genes genuinely affecting a carcass trait and a meat quality trait. Using the Illumina BovineHD BeadChip, 942 young bulls with genotyping data were introduced as a reference population to identify the genes in the beef cattle genome significantly associated with foreshank weight and triglyceride levels. In total, 92,553 haplotype blocks were detected in the genome. The regions of high linkage disequilibrium extended up to approximately 200 kb, and the size of haplotype blocks ranged from 22 bp to 199,266 bp. Additionally, the individual SNP analysis and the haplotype-based analysis detected similar regions and common SNPs for these two representative traits. A total of 12 and 7 SNPs in the bovine genome were significantly associated with foreshank weight and triglyceride levels, respectively. By comparison, 4 and 5 haplotype blocks containing the majority of significant SNPs were strongly associated with foreshank weight and triglyceride levels, respectively. In addition, 36 SNPs with high linkage disequilibrium were detected in the GNAQ gene, a potential hotspot that may play a crucial role for regulating carcass trait components.     

Validation of mega-environment universal and specific QTL associated with seed yield and agronomic traits in soybeans

The value of quantitative trait loci (QTL) is dependant on the strength of association with the traits of interest, allelic diversity at the QTL and the effect of the genetic background on the expression of the QTL. A number of recent studies have identified QTL associated with traits of interest that appear to be independent of the environment but dependant on the genetic background in which they are found. Therefore, the objective of this study was to validate universal and/or mega-environment-specific seed yield QTL that have been previously reported in an independent recombinant inbred line (RIL) population derived from the cross between an elite Chinese and Canadian parent. The population was evaluated at two field environments in China and in five environments in Canada in 2005 and 2006. Of the seven markers linked to seed yield QTL reported by our group in a previous study, four were polymorphic between the two parents. No association between seed yield and QTL was observed. The result could imply that seed yield QTL were either not stable in this particular genetic background or harboured different alleles than the ones in the original mapping population. QTL_U Satt162 was associated with several agronomic traits of which lodging was validated. Both the non-adapted and adapted parent contributed favourable alleles to the progeny. Therefore, plant introductions have been validated as a source of favourable alleles that could increase the genetic variability of the soybean germplasm pool and lead to further improvements in seed yield and other agronomic traits.     

Identification of functional genetic variations underlying drought tolerance in maize using SNP markers

Single nucleotide polymorphism (SNP) is a common form of genetic variation and popularly exists in maize genome. An Illumina GoldenGate assay with 1 536 SNP markers was used to genotype maize inbred lines and identified the functional genetic variations underlying drought tolerance by association analysis. Across 80 lines, 1 006 polymorphic SNPs (65.5% of the total) in the assay with good call quality were used to estimate the pattern of genetic diversity, population structure, and familial relatedness. The analysis showed the best number of fixed subgroups was six, which was consistent with their original sources and results using only simple sequence repeat markers. Pairwise linkage disequilibrium (LD) and association mapping with phenotypic traits investigated under water-stressed and well-watered regimes showed rapid LD decline within 100-500 kb along the physical distance of each chromosome, and that 29 SNPs were associated with at least two phenotypic traits in one or more environments, which were related to drought-tolerant or drought-responsive genes. These drought-tolerant SNPs could be converted into functional markers and then used for maize improvement by marker-assisted selection.     

Molecular evaluation of genetic diversity and association studies in rice (<Emphasis Type="BoldItalic">Oryza sativa</Emphasis> L.)

In the present study, we tested rice genotypes that included un(der)exploited landraces of Tamil Nadu along with indica and japonica test cultivars to ascertain their genetic diversity structure. Highly polymorphic microsatellite markers were used for generating marker segregation data. A novel measure, allele discrimination index, was used to determine subpopulation differentiation power of each marker. Phenotypic data were collected for yield and component traits. Pattern of molecular differentiation separated indica and japonica genotypes; indica genotypes had two subpopulations within. Landraces were found to have indica genome, but formed a separate subgroup with low linkage disequilibrium. The landraces further separated into distinct group in both hierarchical clustering analysis using neighbour-joining method as well as in the model based population structure analysis. Japonica and the remaining indica cultivars formed two other distinct groups. Linkage disequilibrium observed in the whole population was considerably reduced in subpopulations. Low linkage disequilibrium of landforms suggests their narrow adaptation in local geographical niche. Many population specific alleles could be identified particularly for japonica cultivars and landraces. Association analysis revealed nine marker-trait associations with three agronomic traits, of which 67% were previously reported. Although the testing landraces together with known cultivars had permitted genomewide association mapping, the experiment offers scope to study more landraces collected from the entire geographical region for drawing more reliable information.     

Identification of genetic variants associated with maize flowering time using an extremely large multi‐genetic background population

Flowering time is one of the major adaptive traits in domestication of maize and an important selection criterion in breeding. To detect more maize flowering time variants we evaluated flowering time traits using an extremely large multi‐ genetic background population that contained more than 8000 lines under multiple Sino‐United States environments. The population included two nested association mapping (NAM) panels and a natural association panel. Nearly 1 million single‐nucleotide polymorphisms (SNPs) were used in the analyses. Through the parallel linkage analysis of the two NAM panels, both common and unique flowering time regions were detected. Genome wide, a total of 90 flowering time regions were identified. One‐third of these regions were connected to traits associated with the environmental sensitivity of maize flowering time. The genome‐wide association study of the three panels identified nearly 1000 flowering time‐associated SNPs, mainly distributed around 220 candidate genes (within a distance of 1 Mb). Interestingly, two types of regions were significantly enriched for these associated SNPs – one was the candidate gene regions and the other was the approximately 5 kb regions away from the candidate genes. Moreover, the associated SNPs exhibited high accuracy for predicting flowering time.     

A Genome-Wide Association Study of the Maize Hypersensitive Defense Response Identifies Genes That Cluster in Related Pathways

Much remains unknown of molecular events controlling the plant hypersensitive defense response (HR), a rapid localized cell death that limits pathogen spread and is mediated by resistance (R-) genes. Genetic control of the HR is hard to quantify due to its microscopic and rapid nature. Natural modifiers of the ectopic HR phenotype induced by an aberrant auto-active R-gene (Rp1-D21), were mapped in a population of 3,381 recombinant inbred lines from the maize nested association mapping population. Joint linkage analysis was conducted to identify 32 additive but no epistatic quantitative trait loci (QTL) using a linkage map based on more than 7000 single nucleotide polymorphisms (SNPs). Genome-wide association (GWA) analysis of 26.5 million SNPs was conducted after adjusting for background QTL. GWA identified associated SNPs that colocalized with 44 candidate genes. Thirty-six of these genes colocalized within 23 of the 32 QTL identified by joint linkage analysis. The candidate genes included genes predicted to be in involved programmed cell death, defense response, ubiquitination, redox homeostasis, autophagy, calcium signalling, lignin biosynthesis and cell wall modification. Twelve of the candidate genes showed significant differential expression between isogenic lines differing for the presence of Rp1-D21. Low but significant correlations between HR-related traits and several previously-measured disease resistance traits suggested that the genetic control of these traits was substantially, though not entirely, independent. This study provides the first system-wide analysis of natural variation that modulates the HR response in plants.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

Identification of QTLs for seed and pod traits in soybean and analysis for additive effects and epistatic effects of QTLs among multiple environments

Soybean seed and pod traits are important yield components. Selection for high yield style in seed and pod along with agronomic traits is a goal of many soybean breeders. The intention of this study was to identify quantitative trait loci (QTL) underlying seed and pod traits in soybean among eleven environments in China. 147 recombinant inbred lines were advanced through single-seed-descent method. The population was derived from a cross between Charleston (an American high yield soybean cultivar) and DongNong594 (a Chinese high yield soybean cultivar). A total of 157 polymorphic simple sequence repeat markers were used to construct a genetic linkage map. The phenotypic data of seed and pod traits [number of one-seed pod, number of two-seed pod, number of three-seed pod, number of four-seed pod, number of (two plus three)-seed pod, number of (three plus four)-seed pod, seed weight per plant, number of pod per plant] were recorded in eleven environments. In the analysis of single environment, fourteen main effect QTLs were identified. In the conjoint analysis of multiple environments, twenty-four additive QTLs were identified, and additive QTLs by environments interactions (AE) were evaluated and analyzed at the same time among eleven environments; twenty-three pairs of epistatic QTLs were identified, and epistasis (additive by additive) by environments interactions (AAE) were also analyzed and evaluated among eleven environments. Comparing the results of identification between single environment mapping and multiple environments conjoint mapping, three main effect QTLs with positive additive values and another three main effect QTLs with negative additive values, had no interactions with all environments, supported that these QTLs could be used in molecular assistant breeding in the future. These different effect QTLs could supply a good foundation to the gene clone and molecular asisstant breeding of soybean seed and pod traits.     

Genome-wide association study for flowering time,maturity dates and plant height in early maturing soybean (Glycine max) germplasm

Background

Soybean (Glycine max) is a photoperiod-sensitive and self-pollinated species. Days to flowering (DTF) and maturity (DTM), duration of flowering-to-maturity (DFTM) and plant height (PH) are crucial for soybean adaptability and yield. To dissect the genetic architecture of these agronomically important traits, a population consisting of 309 early maturity soybean germplasm accessions was genotyped with the Illumina Infinium SoySNP50K BeadChip and phenotyped in multiple environments. A genome-wide association study (GWAS) was conducted using a mixed linear model that involves both relative kinship and population structure.

Results

The linkage disequilibrium (LD) decayed slowly in soybean, and a substantial difference in LD pattern was observed between euchromatic and heterochromatic regions. A total of 27, 6, 18 and 27 loci for DTF, DTM, DFTM and PH were detected via GWAS, respectively. The Dt1 gene was identified in the locus strongly associated with both DTM and PH. Ten candidate genes homologous to Arabidopsis flowering genes were identified near the peak single nucleotide polymorphisms (SNPs) associated with DTF. Four of them encode MADS-domain containing proteins. Additionally, a pectin lyase-like gene was also identified in a major-effect locus for PH where LD decayed rapidly.

Conclusions

This study identified multiple new loci and refined chromosomal regions of known loci associated with DTF, DTM, DFTM and/or PH in soybean. It demonstrates that GWAS is powerful in dissecting complex traits and identifying candidate genes although LD decayed slowly in soybean. The loci and trait-associated SNPs identified in this study can be used for soybean genetic improvement, especially the major-effect loci associated with PH could be used to improve soybean yield potential. The candidate genes may serve as promising targets for studies of molecular mechanisms underlying the related traits in soybean.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1441-4) contains supplementary material, which is available to authorized users.     

Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping

Kernel size‐related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10^?6) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10^?3) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable‐effect SNPs and the co‐localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co‐localized SNPs, of which zma‐miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma‐miR164e resulted in the down‐regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker‐assisted selection (MAS) for high‐yield breeding in maize.     

Determination of the genetic architecture of seed size and shape via linkage and association analysis in soybean (Glycine max L. Merr.)

Seed-size traits, which are controlled by multiple genes in soybean, play an important role in determining seed yield, quality and appearance. However, the molecular mechanisms controlling the size of soybean seeds remain unclear, and little research has been done to investigate these mechanisms. In this study, we performed a genetic analysis to determine the genetic architecture of soybean seed size and shape via linkage and association analyses. We used 184 recombinant inbred lines (RILs) and 219 cultivated soybean accessions to evaluate seed length, seed width and seed height as seed-size traits, and their ratios of these values as seed-shape traits. Our results showed that all six traits had high heritability ranging from 92.46 to 98.47 %. Linkage analysis in the RILs identified 12 quantitative traits loci (QTLs), with five of these QTLs being associated with seed size, five with seed shape and two with the two first principal components of our principal component analysis (PCA). Association analysis in the 219 accessions detected 41 single nucleotide polymorphism (SNP)-trait associations, with 20 of these SNPs being associated with seed-size traits, seven with seed-shape traits and 14 with the two first principal components of our PCA. This analysis reveals that seed-size and seed-shape may be controlled by different genetic factors. Our results provide a greater understanding of phenotypic structure and genetic architecture of soybean seed, and the QTLs detected in this study form a basis for future fine mapping, quantitative trait gene cloning and molecular breeding in soybean.     

Evaluation of Clustering and Genotype Distribution for Replication in Genome Wide Association Studies: The Age-Related Eye Disease Study

Genome-wide association studies (GWASs) assess correlation between traits and DNA sequence variation using large numbers of genetic variants such as single nucleotide polymorphisms (SNPs) distributed across the genome. A GWAS produces many trait-SNP associations with low p-values, but few are replicated in subsequent studies. We sought to determine if characteristics of the genomic loci associated with a trait could be used to identify initial associations with a higher chance of replication in a second cohort. Data from the age-related eye disease study (AREDS) of 100,000 SNPs on 395 subjects with and 198 without age-related macular degeneration (AMD) were employed. Loci highly associated with AMD were characterized based on the distribution of genotypes, level of significance, and clustering of adjacent SNPs also associated with AMD suggesting linkage disequilibrium or multiple effects. Forty nine loci were highly associated with AMD, including 3 loci (CFH, C2/BF, LOC387715/HTRA1) already known to contain important genetic risks for AMD. One additional locus (C3) reported during the course of this study was identified and replicated in an additional study group. Tag-SNPs and haplotypes for each locus were evaluated for association with AMD in additional cohorts to account for population differences between discovery and replication subjects, but no additional clearly significant associations were identified. Relying on a significant genotype tests using a log-additive model would have excluded 57% of the non-replicated and none of the replicated loci, while use of other SNP features and clustering might have missed true associations.     

Maize genetic diversity and association mapping using transposable element insertion polymorphisms

Transposable elements are the major component of the maize genome and presumably highly polymorphic yet they have not been used in population genetics and association analyses. Using the Transposon Display method, we isolated and converted into PCR-based markers 33 Miniature Inverted Repeat Transposable Elements (MITE) polymorphic insertions. These polymorphisms were genotyped on a population-based sample of 26 American landraces for a total of 322 plants. Genetic diversity was high and partitioned within and among landraces. The genetic groups identified using Bayesian clustering were in agreement with published data based on SNPs and SSRs, indicating that MITE polymorphisms reflect maize genetic history. To explore the contribution of MITEs to phenotypic variation, we undertook an association mapping approach in a panel of 367 maize lines phenotyped for 26 traits. We found a highly significant association between the marker ZmV1-9, on chromosome 1, and male flowering time. The variance explained by this association is consistent with a flowering delay of +123 degree-days. This MITE insertion is located at only 289 nucleotides from the 3′ end of a Cytochrome P450-like gene, a region that was never identified in previous association mapping or QTL surveys. Interestingly, we found (i) a non-synonymous mutation located in the exon 2 of the gene in strong linkage disequilibrium with the MITE polymorphism, and (ii) a perfect sequence homology between the MITE sequence and a maize siRNA that could therefore potentially interfere with the expression of the Cytochrome P450-like gene. Those two observations among others offer exciting perspectives to validate functionally the role of this region on phenotypic variation.     

Mapping quantitative trait loci for yield,yield components and morphological traits in an advanced backcross population between <Emphasis Type="Italic">Oryza rufipogon</Emphasis> and the <Emphasis Type="Italic">Oryza sativa</Emphasis> cultivar Jefferson

An advanced backcross population between an accession of Oryza rufipogon (IRGC 105491) and the U.S. cultivar Jefferson (Oryza sativa ssp. japonica) was developed to identify quantitative trait loci (QTLs) for yield, yield components and morphological traits. The genetic linkage map generated for this population consisted of 153 SSR and RFLP markers with an average interval size of 10.3 cM. Thirteen traits were examined, nine of which were measured in multiple environments. Seventy-six QTLs above an experiment-wise significance threshold of P<0.01 (corresponding to an interval mapping LOD>3.6 or a composite interval mapping LOD>3.9) were identified. For the traits measured in multiple environments, 47% of the QTLs were detected in at least two environments. The O. rufipogon allele was favorable for 53% of the yield and yield component QTLs, including loci for yield, grains per panicle, panicle length, and grain weight. Morphological traits related to the domestication process and/or weedy characteristics, including plant height, shattering, tiller type and awns, were found clustered on chromosomes 1 and 4. Comparisons to previous studies involving wild x cultivated crosses revealed O. rufipogon alleles with stable effects in multiple genetic backgrounds and environments, several of which have not been detected in studies between Oryza sativa cultivars, indicating potentially novel alleles from O. rufipogon. Some O. rufipogon-derived QTLs, however, were in similar regions as previously reported QTLs from Oryza sativa cultivars, providing evidence for conservation of these QTLs across the Oryza genus. In addition, several QTLs for grain weight, plant height, and flowering time were localized to putative homeologous regions in maize where QTLs for these traits have been previously reported, supporting the hypothesis of functional conservation of QTLs across the grasses.     

Applications of single nucleotide polymorphisms in crop genetics

The discovery of single nucleotide polymorphisms (SNPs) and insertions/deletions, which are the basis of most differences between alleles, has been simplified by recent developments in sequencing technology. SNP discovery in many crop species, such as corn and soybean, is relatively straightforward because of their high level of intraspecific nucleotide diversity, and the availability of many gene and expressed sequence tag (EST) sequences. For these species, direct readout of SNP haplotypes is possible. Haplotype-based analysis is more informative than analysis based on individual SNPs, and has more power in analyzing association with phenotypes. The elite germplasm of some crops may have been subjected to bottlenecks relatively recently, increasing the amount of linkage disequilibrium (LD) present and facilitating the association of SNP haplotypes at candidate gene loci with phenotypes. Whole-genome scans may help identify genome regions that are associated with interesting phenotypes if sufficient LD is present. Technological improvements make the use of SNP and indel markers attractive for high-throughput use in marker-assisted breeding, EST mapping and the integration of genetic and physical maps.