Multi-parent Advanced Generation Inter-cross Population Research Articles

Genome-wide association mapping in rice MAGIC indica panel detects QTLs and genes for broad-spectrum resistance breeding against African bacterial blight

Rice (Oryza sativa) bacterial blight (BB) is a direct threat to production in Africa. The extent of damage on the continent is not known. We conducted a genome-wide association study (GWAS) to seek out Quantitative trait loci (QTL) that confer the broad-spectrum resistance (BSR) to rice Xanthomonas oryzae pv. oryzae in the rice Multiparent advanced generation intercross (MAGIC) population. The diverse genetic composition and high levels of recombination, are potential resources for the identification of QTL for BSR. Dealing with the ever-evolving Xoo requires identification of novel R gene and resistance quantitative trait loci (QTL). We conducted a genome-wide association study (GWAS) using 250 rice MAGIC indica panel to evaluate for resistance to three Xoo strains from Cote D'Ivoire, namely XooCIkor, XooCIgag and XooCIcii2 which are prevalent highly virulent pathotypes. Using the 3 K RG 4.8mio filtered SNP Dataset, a total of 3 QTL associated with BB resistance on chromosome 9, 6 and 5 were identified. The results of the GWAS identified novel loci that gives useful insight for more investigation and also validated known genes underlying resistance to virulent African strains of BB. Genetic donors identified in this will help plant breeders in improving and broadening resistance to BB.

Quantitative trait loci and genomic prediction for grain sugar and mineral concentrations of cowpea [Vigna unguiculata (L.) Walp.

Development of high yielding cowpea varieties coupled with good taste and rich in essential minerals can promote consumption and thus nutrition and profitability. The sweet taste of cowpea grain is determined by its sugar content, which comprises mainly sucrose and galacto-oligosaccharides (GOS) including raffinose and stachyose. However, GOS are indigestible and their fermentation in the colon can produce excess intestinal gas, causing undesirable bloating and flatulence. In this study, we aimed to examine variation in grain sugar and mineral concentrations, then map quantitative trait loci (QTLs) and estimate genomic-prediction (GP) accuracies for possible application in breeding. Grain samples were collected from a multi-parent advanced generation intercross (MAGIC) population grown in California during 2016-2017. Grain sugars were assayed using high-performance liquid chromatography. Grain minerals were determined by inductively coupled plasma-optical emission spectrometry and combustion. Considerable variation was observed for sucrose (0.6-6.9%) and stachyose (2.3-8.4%). Major QTLs for sucrose (QSuc.vu-1.1), stachyose (QSta.vu-7.1), copper (QCu.vu-1.1) and manganese (QMn.vu-5.1) were identified. Allelic effects of major sugar QTLs were validated using the MAGIC grain samples grown in West Africa in 2017. GP accuracies for minerals were moderate (0.4-0.58). These findings help guide future breeding efforts to develop mineral-rich cowpea varieties with desirable sugar content.

Development of Multi-Parent Advanced Generation Intercross (MAGIC) Mapping Population for QTL Analysis in Rice

A major advantage for researchers in plant and animal genetics lies in the ability to create experimental populations. Such populations mix well characterized founder genomes in controlled pedigrees, and facilitate the investigation of both the genome itself and its relationship with traits and the environment. Traditional experimental populations combine the genomes of two parents with contrasting phenotypes to identify regions of the genome affecting the trait. However, each of these populations captures only a small snapshot of the factors affecting the trait due to the narrow genetic base. It is only possible to detect those genomic regions which differ between the two founders, and all alleles occur with high frequency in the population. Recently, a multi-parent advanced generation intercross (MAGIC) strategy has been proposed to interrogate multiple alleles and to provide increased recombination and mapping resolution. The main objective of developing MAGIC populations is to promote intercrossing and shuffling of the genome, thus increased precision and resolution with which QTLs can be detected due to the increased level of recombination. The Global MAGIC is an attempt to combine traits from several gene pools that have been adapted to different environments. In addition to being a source of potential novel variation, the Global MAGIC population provides useful materials for studying the relative contributions from different crop ecotypes and the level of recombination among exploited genomes constituting this population. An eight Parent-based rice MAGIC population was initiated to develop by employing 2-way, 4-way and 8-way cross along with 8-way intercross hybridization. Nonetheless, the 2-way (Single cross), 4-way (Double cross hybrid) cross has completed during the first year of research program (2018-2019) and subsequently, 8-way cross giving rise to 2 sets (8-wcp set1) having genome ABCDEFGH and 8-wcp set-2 with genome EFGHABCD) of 8-way cross F1 genotypes has accomplished at Aman season of second year (2019-2020) of the project. The eight-way crosses of set 1 (8-wcp set-1) were further intercrossed (Boro 2019) with the reciprocal eight-way crosses set 2 (8-wcp set -2) for establishing altogether 85 eight-way intercross combinations (ABCDEFGH/EFGHABCD) and then, we render this 1-85 group as BUMpop (Bangabandhu University Mapping Population). Progeny from each of the eighty-five 8-way intercrosses were grown, keeping ~ 4 offspring per cross constituting the population size as 85 × 4 = 340 lines. The seeds of BUMpop were progressed to the F6 generation via single seed descent (SSD) method in the field.

Development and evaluation of the utility of GenoBaits Peanut 40K for a peanut MAGIC population

Population and genotype data are essential for genetic mapping. The multi-parent advanced generation intercross (MAGIC) population is a permanent mapping population used for precisely mapping quantitative trait loci. Moreover, genotyping-by-target sequencing (GBTS) is a robust high-throughput genotyping technology characterized by its low cost, flexibility, and limited requirements for information management and support. In this study, an 8-way MAGIC population was constructed using eight elite founder lines. In addition, GenoBaits Peanut 40K was developed and utilized for the constructed MAGIC population. A subset (297 lines) of the MAGIC population at the S2 stage was genotyped using GenoBaits Peanut 40K. Furthermore, these lines and the eight parents were analyzed in terms of pod length, width, area, and perimeter. A total of 27 single nucleotide polymorphisms (SNPs) were revealed to be significantly associated with peanut pod size-related traits according to a genome-wide association study. The GenoBaits Peanut 40K provided herein and the constructed MAGIC population will be applicable for future research to identify the key genes responsible for important peanut traits.

Uncovering the genetic architecture of parallel evolution.

Identifying the genetic architecture underlying adaptive traits is exceptionally challenging in natural populations. This is because associations between traits not only mask the targets of selection but also create correlated patterns of genomic divergence that hinder our ability to isolate causal genetic effects. Here, we examine the repeated evolution of components of the auxin pathway that have contributed to the replicated loss of gravitropism (i.e. the ability of a plant to bend in response to gravity) in multiple populations of the Senecio lautus species complex in Australia. We use a powerful approach which combines parallel population genomics with association mapping in a Multiparent Advanced Generation Inter-Cross (MAGIC) population to break down genetic and trait correlations to reveal how adaptive traits evolve during replicated evolution. We sequenced auxin and shoot gravitropism-related gene regions in 80 individuals from six natural populations (three parallel divergence events) and 133 individuals from a MAGIC population derived from two of the recently diverged natural populations. We show that artificial tail selection on gravitropism in the MAGIC population recreates patterns of parallel divergence in the auxin pathway in the natural populations. We reveal a set of 55 auxin gene regions that have evolved repeatedly during the evolution of the species, of which 50 are directly associated with gravitropism divergence in the MAGIC population. Our work creates a strong link between patterns of genomic divergence and trait variation contributing to replicated evolution by natural selection, paving the way to understand the origin and maintenance of adaptations in natural populations.

Identifying developmental QTL alleles with favorable effect on grain yield components under late-terminal drought in spring barley MAGIC population.

Barley is the fourth most cultivated cereal worldwide, and drought is a major cause of its yield loss by negatively affecting its development. Hence, better understanding developmental mechanisms that control complex polygenic yield-related traits under drought is essential to uncover favorable yield regulators. This study evaluated seven above-ground yield-related traits under well-watered (WW) and late-terminal drought(TD) treatment using 534 spring barley multiparent advanced generation intercross double haploid (DH) lines. The analysis of quantitative trait loci (QTL) for WW, TD, marker by treatment interaction, and drought stress tolerance identified 69, 64, 25, and 25 loci, respectively, for seven traits from which 15 loci were common for at least three traits and 17 were shared by TD and drought stress tolerance. Evaluation of allelic effects for a QTL revealed varying effect of parental alleles. Results showed prominent QTL located on major flowering time gene Ppd-H1 with favorable effects for grain weight under TD when flowering time was not significantly affected, suggesting that this gene might be linked with increasing grain weight by ways other than timing of flowering under late-terminal drought stress. Furthermore, a desirable novel QTL allele was identified on chromosome 5H for grain number under TD nearby sucrose transporter gene HvSUT2. The findings indicated that spring barley multiparent advanced generation intercross population can provide insights to improve yield under complex condition of drought.

Enchanting Insights and Exploring the Relevance of the Magic Population in Advancing Cereal Crop Improvement

Multiparent Advanced Generation Inter-cross Populations (MAGIC) populations are portrayed as inbred recombinant sets that were created by inter-crossing certain numerous parents. However it takes a lot of work to produce MAGIC populations but Its more effective approach for detecting QTL’s (Quantitative Trait Loci) when we involves MAGIC populations. The availability of more genetic variety in the germplasms due to various founder lines is one of the main benefits of employing a MAGIC population. In order to identify QTL’s for crop improvement under biotic and abiotic stress conditions, MAGIC populations were developed for the indica and japonica rice cultivars as well as MAGIC plus and Global MAGIC populations. Also the employment of MAGIC populations for the improvement of rice grain size also improves the yield and quality aspects of rice. Utilization of rice MAGIC plus populations for the improvement of nutrient profile of rice which is prime important in the biofortification program of rice as a goal of united nations. Where the utilization of association mapping and MAGIC populations in maize crop for improving saccharification efficiency results in higher biofuel production. Various institutes and universities are involved in production of MAGIC populations in respective specialised crops. This article gives the idea of MAGIC populations and their applications in different and diverse applications for the ultimate benefit of yield improvement.

Interrelationships between cotton fiber quality traits and fluid handling and moisture management properties of nonwoven textiles

Cotton fibers represent a sustainable and environmentally responsible raw material for the production of nonwoven textiles which are currently dominated by synthetic fibers derived from petrochemicals. Natural variation in quality parameters such as fineness, length, and strength present a challenge for cotton fiber conversion to yarns and in weaving and knitting for conventional textiles. The grading process for cotton fibers addresses this issue by allowing converters to select fibers suitable for specific woven textile applications. However, there has been little attempt to correlate cotton fiber quality traits with nonwoven textiles performance. This study examined the relationship of cotton fiber quality and fluid handling and moisture management performance properties of nonwoven textiles for personal hygiene and disposable applications. This includes potential end-use in diapers and incontinence products as well as disposable textiles for use in clinical settings. Ten recombinant inbred lines of cotton with a broad distribution of fiber quality traits were selected from a multiparent advanced generation intercross population. Fibers were harvested, converted into nonwoven textiles, and subjected to a series of standardized testing protocols. The results indicated that inferior quality coarse cotton fibers subjected to discount market pricing can be selectively utilized for nonwoven applications that benefit from improved moisture management and fluid handling performance.

Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea.

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.

Rice3K56 is a high-quality SNP array for genome-based genetic studies and breeding in rice (Oryza sativa L.)

Single nucleotide polymorphism (SNP) genotyping arrays provide an optimal high-throughput platform for genetic research and molecular breeding programs in both animals and plants. In this study, a high-quality and custom-designed Rice3K56 SNP array was developed with the resequencing data of 3024 rice accessions worldwide, which was then tested extensively in 192 representative rice samples. Printed on the GeneTitan chips of Affymetrix Axiom each containing 56,606 SNP markers, the Rice3K56 array has a high genotyping reliability (99.6%), high and uniform genome coverage (an average of 6.7-kb between adjacent SNPs), abundant polymorphic information and easy automation, compared with previously developed rice SNP arrays. When applied in rice varietal differentiation, population diversity analysis, gene mapping of 13 complex traits by a genome-wide association study analysis (GWAS), and genome selection experiments in a recombinant inbred line and a multi-parent advanced generation inter-cross populations, these properties of the Rice3K56 array were well demonstrated for its power and great potential to be a highly efficient tool for rice genetic research and genomic breeding.

Mapping QTLs and gene validation studies for Mg2+ uptake and translocation using a MAGIC population in rice.

Magnesium (Mg) is an essential element for plant growth and development. Rice is an important food crop in the world, but there are few studies on the uptake and translocation of Mg2+ in rice. We used a multi-parent advanced generation inter-cross (MAGIC) population constructed using four parental lines and genotyped by a 55K rice SNP array for association analysis to locate QTLs related to Mg2+ uptake and translocation in rice at the seedling stage. Four QTLs (qRMg1, qRMg2, qRMg7 and qRMg8) were detected for the root Mg2+ concentration, which explained 11.45-13.08% of the phenotypic variation. The Mg2+ transporter gene, OsMGT1, was within the region of qRMg1. Three QTLs (qSMg3, qSMg7 and qSMg10) were detected for the shoot Mg2+ concentration, which explained 4.30-5.46% of the phenotypic variation. Two QTLs (qTrMg3 and qTrMg8) were found to affect the translocation of Mg2+ from the roots to the shoots, and explained 10.91% and 9.63% of phenotypic variation. qSMg3 and qTrMg3 might be the same, since they are very close to each other on chromosome 3. Analysis of candidate genes in the region of qSMg3 and qTrMg3 through qRT-PCR, complementation assay in the yeast Mg2+ transport-defective mutant CM66, and sequence analysis of the parental lines suggested that LOC_Os03g04360 may play important roles in Mg2+ uptake, translocation and accumulation in rice. Overexpression of LOC_Os03g04360 can significantly increase the Mg2+ concentration in rice seedlings, especially under the condition of low Mg2+ supply.

Development and characterization of a sorghum multi-parent advanced generation intercross (MAGIC) population for capturing diversity among seed parent gene pool.

Multiparent advanced eneration inter-cross (MAGIC) populations improve the precision of quantitative trait loci (QTL) mapping over biparental populations by incorporating increased diversity and opportunities to reduce linkage disequilibrium among variants. Here, we describe the development of a MAGIC B-Line (MBL) population from an inter-cross among 4 diverse founders of grain sorghum [Sorghum bicolor (L.) Moench] across different races (kafir, guinea, durra, and caudatum). These founders were selected based on genetic uniqueness and several distinct qualitative features including panicle architecture, plant color, seed color, endosperm texture, and awns. A whole set of MBL (708 F6) recombinant inbred lines along with their founders were genotyped using Diversity Arrays Technology (DArTseq) and 5,683 single-nucleotide polymorphisms (SNPs) were generated. A genetic linkage map was constructed using a set of polymorphic, quality-filtered markers (2,728 SNPs) for QTL interval-mapping. For population validation, 3 traits (seed color, plant color, and awns) were used for QTL mapping and genome-wide association study (GWAS). QTL mapping and GWAS identified 4 major genomic regions located across 3 chromosomes (Chr1, Chr3, and Chr6) that correspond to known genetic loci for the targeted traits. Founders of this population consist of the fertility maintainer (A/B line) gene pool and derived MBL lines could serve as female/seed parents in the cytoplasmic male sterility breeding system. The MBL population will serve as a unique genetic and genomic resource to better characterize the genetics of complex traits and potentially identify superior alleles for crop improvement efforts to enrich the seed parent gene pool.

Genomic insights into the genetic basis of cotton breeding in China

The excellent Upland cotton (Gossypium hirsutum) cultivars developed since 1949 have made a huge contribution to cotton production in China, the world’s largest producer and consumer of cotton. However, the genetic and genomic basis for the improvements of these cotton cultivars remains largely unclear. In this study, we selected 16 Upland cotton cultivars with important historical status in Chinese cotton breeding and constructed a multiparent, advanced generation, intercross (MAGIC) population comprising 920 recombinant inbred lines. A genome-wide association study using the MAGIC population identified 54 genomic loci associated with lint yield and fiber quality. Of them, 25 (46.30%) pleiotropic genomic loci cause simultaneous changes of lint yield and/or fiber quality traits, revealing complex trade-offs and linkage drags in Upland cotton agronomic traits. Deep sequencing data of 11 introduced ancestor cultivars and publicly available resequencing datasets of 839 cultivars developed in China during the past 70 years were integrated to explore the historical distribution and origin of the elite or selected alleles. Interestingly, 85% of these elite alleles were selected and fixed from different American ancestors, consistent with cotton breeding practices in China. However, seven elite alleles of native origin that are responsible for Fusarium wilt resistance, early maturing, good-quality fiber, and other characteristics were not found in American ancestors but have greatly contributed to Chinese cotton breeding and wide cultivation. Taken together, these results provide a genetic basis for further improving cotton cultivars and reveal that the genetic composition of Chinese cotton cultivars is narrow and mainly derived from early introduced American varieties.

Flame resistant cotton lines generated by synergistic epistasis in a MAGIC population.

Textiles made from cotton fibers are flammable and thus often include flame retardant additives for consumer safety. Transgressive segregation in multi-parent populations facilitates new combinations of alleles of genes and can result in traits that are superior to those of any of the parents. A screen of 257 recombinant inbred lines from a multi-parent advanced generation intercross (MAGIC) population for naturally enhance flame retardance (FR) was conducted. All eleven parents, like all conventional white fiber cotton cultivars produce flammable fabric. MAGIC recombinant inbred lines (RILs) that produced fibers with significantly lower heat release capacities (HRC) as measured by microscale combustion calorimetry (MCC) were identified and the stability of the phenotypes of the outliers were confirmed when the RILs were grown at an additional location. Of the textiles fabricated from the five superior RILs, four exhibited the novel characteristic of inherent flame resistance. When exposed to open flame by standard 45° incline flammability testing, these four fabrics self-extinguished. To determine the genetic architecture of this novel trait, linkage, epistatic and multi-locus genome wide association studies (GWAS) were conducted with 473k SNPs identified by whole genome sequencing (WGS). Transcriptomes of developing fiber cells from select RILs were sequenced (RNAseq). Together, these data provide insight into the genetic mechanism of the unexpected emergence of flame-resistant cotton by transgressive segregation in a breeding program. The incorporation of this trait into global cotton germplasm by breeding has the potential to greatly reduce the costs and impacts of flame-retardant chemicals.

Development of a MAGIC population and high-resolution quantitative trait mapping for nicotine content in tobacco.

Multiparent Advanced Generation Inter-Cross (MAGIC) population is an ideal genetic and breeding material for quantitative trait locus (QTL) mapping and molecular breeding. In this study, a MAGIC population derived from eight tobacco parents was developed. Eight parents and 560 homozygous lines were genotyped by a 430K single-nucleotide polymorphism (SNP) chip assay and phenotyped for nicotine content under different conditions. Four QTLs associated with nicotine content were detected by genome-wide association mapping (GWAS), and one major QTL, named qNIC7-1, was mapped repeatedly under different conditions. Furthermore, by combining forward mapping, bioinformatics analysis and gene editing, we identified an ethylene response factor (ERF) transcription factor as a candidate gene underlying the major QTL qNIC7-1 for nicotine content in tobacco. A presence/absence variation (PAV) at qNIC7-1 confers changes in nicotine content. Overall, the large size of this MAGIC population, diverse genetic composition, balanced parental contributions and high levels of recombination all contribute to its value as a genetic and breeding resource. The application of the tobacco MAGIC population for QTL mapping and detecting rare allelic variation was demonstrated using nicotine content as a proof of principle.

Multi-trait ensemble genomic prediction and simulations of recurrent selection highlight importance of complex trait genetic architecture for long-term genetic gains in wheat

AbstractCereal crop breeders have achieved considerable genetic gain in genetically complex traits, such as grain yield, while maintaining genetic diversity. However, focus on selection for yield has negatively impacted other important traits. To better understand multi-trait selection within a breeding context, and how it might be optimized, we analysed genotypic and phenotypic data from a genetically diverse, 16-founder wheat multi-parent advanced generation inter-cross population. Compared to single-trait models, multi-trait ensemble genomic prediction models increased prediction accuracy for almost 90 % of traits, improving grain yield prediction accuracy by 3–52 %. For complex traits, non-parametric models (Random Forest) also outperformed simplified, additive models (LASSO), increasing grain yield prediction accuracy by 10–36 %. Simulations of recurrent genomic selection then showed that sustained greater forward prediction accuracy optimized long-term genetic gains. Simulations of selection on grain yield found indirect responses in related traits, involving optimized antagonistic trait relationships. We found multi-trait selection indices could effectively optimize undesirable relationships, such as the trade-off between grain yield and protein content, or combine traits of interest, such as yield and weed competitive ability. Simulations of phenotypic selection found that including Random Forest rather than LASSO genetic models, and multi-trait rather than single-trait models as the true genetic model accelerated and extended long-term genetic gain whilst maintaining genetic diversity. These results (i) suggest important roles of pleiotropy and epistasis in the wider context of wheat breeding programmes, and (ii) provide insights into mechanisms for continued genetic gain in a limited genepool and optimization of multiple traits for crop improvement.

Interrelationships between cotton fiber quality traits and tensile properties of hydroentangled nonwoven fabrics

Cotton fibers can be used to produce nonwovens suitable for numerous single use applications including hygiene, wipes, and medical products among others. Cotton comprises a relatively small amount of total raw materials used in nonwovens production compared to the synthetic fibers of polyester and polypropylene, but the use of cotton fibers in nonwovens continues to increase due to demand for disposable products containing natural, sustainable, and biodegradable materials. However, the relationship between cotton fiber classification measurements and nonwoven fabric physical and functional properties are not well characterized. A better understanding of the effects of cotton fiber properties on nonwovens fabric properties will facilitate fiber selection for specific end-use applications. In this study, cotton fibers with broad distributions of fiber quality measurements from 10 recombinant inbred lines of a multi parent advanced generation intercross multiparent advanced generation intercross population were harvested and processed in their greige state into hydroentangled nonwoven fabrics of two distinct basis weights. Tensile testing of lightweight nonwovens indicated fiber length and tensile strength at break were positively correlated with fabric strength, whereas micronaire (air permeability of a fiber bundle) was negatively correlated indicating finer fibers contributed to increased fabric strength. Increased strength of heavyweight fabrics was mainly correlated with higher fiber uniformity index. These results suggest that cotton fibers could be selectively sourced based on fiber quality for specific nonwoven applications and establishes alternative market opportunities for cotton fibers classified as inferior and subject to discount pricing in the woven textile market.

A multi-locus linear mixed model methodology for detecting small-effect QTLs for quantitative traits in MAGIC, NAM, and ROAM populations

Although multi-parent populations (MPPs) integrate the advantages of linkage and association mapping populations in the genetic dissection of complex traits and especially combine genetic analysis with crop breeding, it is difficult to detect small-effect quantitative trait loci (QTL) for complex traits in multiparent advanced generation intercross (MAGIC), nested association mapping (NAM), and random-open-parent association mapping (ROAM) populations. To address this issue, here we proposed a multi-locus linear mixed model method, namely mppQTL, to detect QTLs, especially small-effect QTLs, in these MPPs. The new method includes two steps. The first is genome-wide scanning based on a single-locus linear mixed model; the P-values are obtained from likelihood-ratio test, the peaks of negative logarithm P-value curve are selected by group-lasso, and all the selected peaks are regarded as potential QTLs. In the second step, all the potential QTLs are placed on a multi-locus linear mixed model, all the effects are estimated using expectation-maximization empirical Bayes algorithm, and all the non-zero effect vectors are further evaluated via likelihood-ratio test for significant QTLs. In Monte Carlo simulation studies, the new method has higher power in QTL detection, lower false positive rate, lower mean absolute deviation for QTL position estimate, and lower mean squared error for the estimate of QTL size (r2) than existing methods because the new method increases the power of detecting small-effect QTLs. In real dataset analysis, the new method (19) identified five more known genes than the existing three methods (14). This study provides an effective method for detecting small-effect QTLs in any MPPs.

Wheat EARLY FLOWERING 3 affects heading date without disrupting circadian oscillations.

Plant breeders have indirectly selected for variation at circadian-associated loci in many of the world's major crops, when breeding to increase yield and improve crop performance. Using an eight-parent Multiparent Advanced Generation Inter-Cross (MAGIC) population, we investigated how variation in circadian clock-associated genes contributes to the regulation of heading date in UK and European winter wheat (Triticum aestivum) varieties. We identified homoeologues of EARLY FLOWERING 3 (ELF3) as candidates for the Earliness per se (Eps) D1 and B1 loci under field conditions. We then confirmed a single-nucleotide polymorphism within the coding region of TaELF3-B1 as a candidate polymorphism underlying the Eps-B1 locus. We found that a reported deletion at the Eps-D1 locus encompassing TaELF3-D1 is, instead, an allele that lies within an introgression region containing an inversion relative to the Chinese Spring D genome. Using Triticum turgidum cv. Kronos carrying loss-of-function alleles of TtELF3, we showed that ELF3 regulates heading, with loss of a single ELF3 homoeologue sufficient to alter heading date. These studies demonstrated that ELF3 forms part of the circadian oscillator; however, the loss of all homoeologues was required to affect circadian rhythms. Similarly, loss of functional LUX ARRHYTHMO (LUX) in T. aestivum, an orthologue of a protein partner of Arabidopsis (Arabidopsis thaliana) ELF3, severely disrupted circadian rhythms. ELF3 and LUX transcripts are not co-expressed at dusk, suggesting that the structure of the wheat circadian oscillator might differ from that of Arabidopsis. Our demonstration that alterations to ELF3 homoeologues can affect heading date separately from effects on the circadian oscillator suggests a role for ELF3 in cereal photoperiodic responses that could be selected for without pleiotropic deleterious alterations to circadian rhythms.

Genetic background- and environment-independent QTL and candidate gene identification of appearance quality in three MAGIC populations of rice.

Many QTL have been identified for grain appearance quality by linkage analysis (LA) in bi-parental mapping populations and by genome-wide association study (GWAS) in natural populations in rice. However, few of the well characterized genes/QTL have been successfully applied in molecular rice breeding due to genetic background (GB) and environment effects on QTL expression and deficiency of favorable alleles. In this study, GWAS and LA were performed to identify QTL for five grain appearance quality-related traits using three multi-parent advanced generation inter-cross (MAGIC) populations. A total of 22 QTL on chromosomes 1-3, 5-8 were identified by GWAS for five traits in DC1, DC2 and 8way, and four combined populations DC12 (DC1+DC2), DC18 (DC1+8way), DC28 (DC2+8way) and DC128 (DC1+DC2+8way). And a total of 42 QTL were identified on all 12 chromosomes except 10 by LA in the three single populations. Among 20 QTL identified by GWAS in DC1, DC2 and 8way, 10, four and three QTL were commonly detected in DC18, DC28, and DC128, respectively. Similarly, among 42 QTL detected by LA in the three populations, four, one and two QTL were commonly detected in DC18, DC28, and DC128, respectively. There was no QTL mapped together in DC12 by both two mapping methods, indicating that GB could greatly affect the mapping results, and it was easier to map the common QTL among populations with similar GB. The 8way population was more powerful for QTL mapping than the DC1, DC2 and various combined populations. Compared with GWAS, LA can not only identify large-effect QTL, but also identify minor-effect ones. Among 11 QTL simultaneously detected by the two methods in different GBs and environments, eight QTL corresponded to known genes, including AqGL3b and AqGLWR3a for GL and GLWR, AqGW5a, AqGLWR5, AqDEC5 and AqPGWC5 for GW, GLWR, DEC and PGWC, and AqDEC6b and AqPGWC6b for DEC and PGWC, respectively. AqGL7, AqGL3c/AqGLWR3b, AqDEC6a/AqPGWC6a, and AqPGWC7 were newly identified and their candidate genes were analyzed and inferred. It was discussed to further improve grain appearance quality through designed QTL pyramiding strategy based on the stable QTL identified in the MAGIC populations.