Genetic dissection of soybean lodging tolerance in recombinant inbred-line populations of major Japanese and modern US varieties

Khanal, R., Navabi, A. and Lukens, L. 2015. Linkage map construction and quantitative trait loci (QTL) mapping using intermated vs. selfed recombinant inbred maize line (Zea mays L.). Can. J. Plant Sci. 95: 1133–1144. Intermating of individuals in an F2 population increases genetic recombination between markers, which is useful for linkage map construction and quantitative trait loci (QTL) mapping. The objectives of this study were to compare the linkage maps and precision of QTL detection in an intermated recombinant inbred line (IRIL) population and a selfed recombinant inbred line (RIL) population. Both, IRIL and RIL, populations were developed from Zea mays inbred lines CG60 and CG102. The populations were grown in two environments to evaluate traits, and inbred lines from each population were genotyped with SSR and SNP markers for linkage map construction and QTL identification. In addition, we simulated RIL and IRIL populations from two inbred parents to compare the precision of QTL detection between simulated RIL and IRIL populations. In the empirical study, the linkage map was longer in RIL as compared with IRIL, and the average QTL support interval was reduced by 1.37-fold in the IRIL population compared with the RIL population. We detected 16 QTL for flowering time, plant height, leaf number, and stay green in at least one recombinant inbred line population. Two out of 16 QTL were shared between two recombinant inbred line populations. In the simulation study, the QTL support interval was reduced by 1.66-fold in the IRIL population as compared with the RIL population and linked QTL were identified more frequently in IRIL population as compared with RIL population. This study supports the utility of intermated RIL populations for precise QTL mapping.

Two genetic linkage maps based on doubled haploid (DH) and recombinant inbred lines (RILs) populations, derived from the same indica-japonica cross ‘Samgang × Nagdong’, were constructed to analyze the quantitative trait loci (QTLs) affecting agronomic traits in rice. The segregations of agronomic traits in RILs population showed larger variations than those in DH population. A total of 10 and 12 QTLs were identified on six chromosomes using DH population and seven chromosomes using RILs population, respectively. Three stable QTLs including pl9.1, ph1.1, and gwp11.1 were detected through different years. The percentages of phenotypic variation explained by individual QTLs ranged from 8 to 18% in the DH population and 9 to 33% in the RILs population. Twenty-three epistatic QTLs were identified in the DH population, while 21 epistatic QTLs were detected in the RILs population. Epistatic interactions played an important role in controlling the agronomic traits genetically. Four significant main-effect QTLs were involved in the digenic interactions. Significant interactions between QTLs and environments (QE) were identified in two populations. The QTLs affecting grain weight per panicle (GWP) were more sensitive to the environmental changes. The comparison and QTLs analysis between two populations across different years should help rice breeders to comprehend the genetic mechanisms of quantitative traits and improve breeding programs in marker-assisted selection (MAS).

Doubled haploid (DH) and recombinant inbred line (RIL) populations are two types of permanent populations for rice (Oryza sativa L.) breeding and genetic mapping. In this study, we report the comparison of molecular maps and mapped agronomic trait loci between DH and RIL populations derived from the same rice cross, ZYQ8 (indica) × JXI7 (japonica). We investigated six agronomic traits (days to heading, plant height, number of spikelets per panicle, number of grains per panicle, 1000‐grain weight, and seed set percentage) and found that five of them did not show significant differences between the two populations. Restriction fragment length polymorphism (RFLP) and microsatellite markers were selected to construct two linkage maps of the DH and RIL populations. All the DNA markers except G39 showed the same linkage groups and orders between the two populations. The genetic distance per chromosome in the RIL population was shorter than that in the DH population, and the total genetic distance of genome in the RIL population (1465 cM) was 70.5% of that in the DH population (2079 cM). In the RIL population, 27.3% markers showed distorted segregation at P < 0.01 level, of which 90% markers favored indica alleles, while in the DH population, the skewed markers favoring indica and japonica alleles were in accordance with 1:1 ratio. Eight commonly distorted regions on chromosomes 1, 3, 4, 7, 8, 10, 11, and 12 were detected in both RIL and DH populations, of which seven skewed toward indica alleles and one toward japonica allele. Five of them were located near gametophytic gene loci (ga) and/or sterility gene loci (S). We also compared the quantitative trait locus (QTL) mapping results between the DH and RIL populations and found a number of similarities in the QTL locations between these two populations. So both RIL and DH populations are equally effective in rice breeding and genetic analysis.

Based on two recombinant inbred line (RIL) populations, two corresponding backcross (BC) populations were constructed to elucidate the genetic basis of heterosis in Upland cotton (Gossypium hirsutum L.). The yield, and yield components, of these populations were evaluated in three environments. At the single-locus level, 78 and 66 quantitative trait loci (QTL) were detected using composite interval mapping in RIL and BC populations, respectively, and 29 QTL were identified based on mid-parental heterosis (MPH) data of two hybrids. Considering all traits together, a total of 50 (64.9%) QTL with partial dominance effect, and 27 (35.1%) QTL for overdominance effect were identified in two BC populations. At the two-locus level, 120 and 88 QTL with main effects (M-QTL), and 335 and 99 QTL involved in digenic interactions (E-QTL), were detected by inclusive composite interval mapping in RIL and BC populations, respectively. A large number of QTL by environment interactions (QEs) for M-QTL and E-QTL were detected in three environments. For most traits, average E-QTL explained a larger proportion of phenotypic variation than did M-QTL in two RIL populations and two BC populations. It was concluded that partial dominance, overdominance, epistasis, and QEs all contribute to heterosis in Upland cotton, and that partial dominance resulting from single loci and epistasis play a relatively more important role than other genetic effects in heterosis in Upland cotton.

genetic basis for postharvest chilling tolerance in tomato fruit

This study describes the generation and test of a genetic resource suited to identify determinants of cell biological traits in plants. The use of quantitative trait loci (QTL) mapping for a better genetic understanding of cell biological traits is still at an early stage, even for biotechnologically important cell properties, such as the dimensions of fiber cells. A common strategy, the mapping of QTLs in recombinant inbred line (RIL) populations, is limited by the fact that the existing RIL populations exploit only a small fraction of the existing natural variation. Here, we report the mapping of QTLs impacting on the length of fiber cells in Arabidopsis inflorescence stems in a newly generated RIL population derived from a cross between the accessions Berkeley and the little known Lz-0. Through inbreeding of individual F(2) plants, a total of 159 new F8 lines were produced and genotyped with a set of 49 single nucleotide polymorphism markers. The population was successfully used not only for the mapping of three QTLs controlling fiber length, but also to map five QTL controlling flowering time under short and long-day conditions. Our study demonstrates the usefulness of this new genetic resource by mapping in it QTLs underlying a poorly explored cellular trait as well as an already better explored regulatory pathway. The new RIL population and an online platform for the continuous supplementation of genetic markers will be generally available to substantially broaden the genetic diversity through which loci with impact on plant quantitative traits can be identified.

The southwestern corn borer (SWCB, Diatraea grandiosella Dyar) and sugarcane borer (SCB, Diatraea saccharalis Fabricius) are two related insect species that cause serious damage in maize production in subtropical and tropical regions of Central and Latin America. We analyzed quantitative trait loci (QTL) involved in resistance to the first generation of both borer species in two recombinant inbred line (RIL) populations from crosses CML131 (susceptible) × CML67 (resistant) and Ki3 (susceptible) × CML139 (resistant). Resistance was evaluated as leaf feeding damage (LFD) in replicated field trials across several environments under artificial infestation. Leaf protein concentration and leaf toughness were evaluated in one environment as putative components of resistance. The method of composite interval mapping was employed for QTL detection with RFLP linkage maps derived for each population of RIL. Estimates of the genotypic and genotype × environment interaction variances for SWCB LFD and SCB LFD were highly significant in both populations. Heritabilities ranged from 0.50 to 0.75. In Population CML131 × CML67, nine and eight mostly identical QTL were found for SWCB LFD and SCB LFD, respectively, explaining about 52% of the phenotypic variance () for each trait. In Population Ki3 × CML139, five QTL for SWCB LFD were detected, explaining 35.5% of . Several of these QTL were found in regions containing QTL for leaf protein concentration or leaf toughness. A low number of QTL in common between the two RIL populations and between RIL and corresponding populations of F2:3 indicated that the detection of QTL depended highly on the germplasm and population type. Consequently, chances of successful application of marker‐based selection (MBS) for corn borer resistance are reduced when QTL are not identified in the germplasm in which the final selection will be carried out.

Key message Combined linkage and association mapping analyses facilitate the emphasis on the candidate genes putatively involved in maize husk growth. The maize (Zea mays L.) husk consists of multiple leafy layers and plays important roles in protecting the ear from pathogen infection and in preventing grain dehydration. Although husk morphology varies widely among different maize inbred lines, the genetic basis of such variation is poorly understood. In this study, we used three maize recombinant inbred line (RIL) populations to dissect the genetic basis of three husk traits: i.e., husk length (HL), husk width (HW), and the number of husk layers (HN). Three husk traits in all three RIL populations showed wide phenotypic variation and high heritability. The HL showed stronger correlations with ear traits than did HW and HN. A total of 21 quantitative trait loci (QTL) were identified for the three traits in three RIL populations, and some of them were commonly observed for the same trait in different populations. The proportions of total phenotypic variation explained by QTL in three RIL populations were 31.8, 35.3, and 44.5% for HL, HW, and HN, respectively. The highest proportions of phenotypic variation explained by a single QTL were 14.7% for HL in the By815/K22 RIL population (BYK), 13.5% for HW in the By815/DE3 RIL population (BYD), and 19.4% for HN in the BYD population. A combined analysis of linkage mapping with a previous genome-wide association study revealed five candidate genes related to husk morphology situated within three QTL loci. These five genes were related to metabolism, gene expression regulation, and signal transduction.

Boron (B) is an essential micronutrient for higher plants. There is wide genetic variation in the response to B deficiency among plant species and cultivars. The objective of this study was to identify quantitative trait loci (QTL) that control B efficiency in natural Arabidopsis accessions. The B efficiency coefficient (BEC) and seed yield under low B conditions (SYLB) were investigated by solution culture in two separate experiments in an Arabidopsis recombinant inbred line (RIL) population. Both of the traits studied exhibited high transgressive variation in the RIL population, and, in total, five and three QTL were identified for BEC and SYLB, respectively. Three of the five QTL, including the QTL, AtBE1-2, that has a large effect on the BEC, were found at the interval of the corresponding QTL for SYLB in both experiments. The close genetic relationship between BEC and SYLB was further confirmed by conditional QTL mapping in the RIL population and unconditional QTL mapping in an AtBE1-2-segregated F(2) population. Epistatic interactions for the tested traits were analysed, and were found to be widespread in the detected QTL of Arabidopsis in the RIL population. Comparison of the QTL interval for B efficiency with reported B-related genes showed that 10 B-related genes, together with one BOR1 homolog (BOR5, At1g74810) were located in the QTL region of AtBE1-2. These results suggest that natural variation in B efficiency in Arabidopsis has a complex molecular basis. They also provide a basis for fine mapping and cloning of the B-efficiency genes, with the ultimate aim of discovering the physiological mechanism of action of the genes.

BackgroundSeed aging in soybean is a serious challenge for agronomic production and germplasm preservation. However, its genetic basis remains largely unclear in soybean. Unraveling the genetic mechanism involved in seed aging, and enhancing seed storability is an imperative goal for soybean breeding. The aim of this study is to identify quantitative trait loci (QTLs) using high-density genetic linkage maps of soybean for seed storability. In this regard, two recombinant inbred line (RIL) populations derived from Zhengyanghuangdou × Meng 8206 (ZM6) and Linhefenqingdou × Meng 8206 (LM6) crosses were evaluated for three seed-germination related traits viz., germination rate (GR), normal seedling length (SL) and normal seedling fresh weight (FW) under natural and artificial aging conditions to map QTLs for seed storability.ResultsA total of 34 QTLs, including 13 QTLs for GR, 11 QTLs for SL and 10 QTLs for FW, were identified on 11 chromosomes with the phenotypic variation ranged from 7.30 to 23.16% under both aging conditions. All these QTLs were novel, and 21 of these QTLs were clustered in five QTL-rich regions on four different chromosomes viz., Chr3, Chr5, Chr17 &Chr18, among them the highest concentration of seven and six QTLs were found in “QTL hotspot A” (Chr17) and “QTL hotspot B” (Chr5), respectively. Furthermore, QTLs within all the five QTL clusters are linked to at least two studied traits, which is also supported by highly significant correlation between the three germination-related traits. QTLs for seed-germination related traits in “QTL hotspot B” were found in both RIL populations and aging conditions, and also QTLs underlying “QTL hotspot A” are identified in both RIL populations under artificial aging condition. These are the stable genomic regions governing the inheritance of seed storability in soybean, and will be the main focus for soybean breeders.ConclusionThis study uncovers the genetic basis of seed storability in soybean. The newly identified QTLs provides valuable information, and will be main targets for fine mapping, candidate gene identification and marker-assisted breeding. Hence, the present study is the first report for the comprehensive and detailed investigation of genetic architecture of seed storability in soybean.

Seed size and shape traits are important determinants of seed yield and appearance quality in soybean [Glycine max (L.) Merr.]. Understanding the genetic architecture of these traits is important to enable their genetic improvement through efficient and targeted selection in soybean breeding, and for the identification of underlying causal genes. To map seed size and shape traits in soybean, a recombinant inbred line (RIL) population developed from K099 (small seed size) × Fendou 16 (large seed size), was phenotyped in three growing seasons. A genetic map of the RIL population was developed using 1,485 genotyping by random amplicon sequencing-direct (GRAS-Di) and 177 SSR markers. Quantitative trait locus (QTL) mapping was conducted by inclusive composite interval mapping. As a result, 53 significant QTLs for seed size traits and 27 significant QTLs for seed shape traits were identified. Six of these QTLs (qSW8.1, qSW16.1, qSLW2.1, qSLT2.1, qSWT1.2, and qSWT4.3) were identified with LOD scores of 3.80–14.0 and R2 of 2.36%–39.49% in at least two growing seasons. Among the above significant QTLs, 24 QTLs were grouped into 11 QTL clusters, such as, three major QTLs (qSL2.3, qSLW2.1, and qSLT2.1) were clustered into a major QTL on Chr.02, named as qSS2. The effect of qSS2 was validated in a pair of near isogenic lines, and its candidate genes (Glyma.02G269400, Glyma.02G272100, Glyma.02G274900, Glyma.02G277200, and Glyma.02G277600) were mined. The results of this study will assist in the breeding programs aiming at improvement of seed size and shape traits in soybean.

Genetic analysis of maize shank length by QTL mapping in three recombinant inbred line populations

Data generated for initial quantitative trait loci (QTL) mapping using recombinant inbred line (RIL) populations are usually ignored during subsequent fine-mapping using near-isogenic lines (NILs). Combining both datasets would increase the number of recombination events sampled and generate better position and effect estimates. Previously, several QTL for resistance to southern leaf blight of maize were mapped in two RIL populations, each independently derived from a cross between the lines B73 and Mo17. In each case the largest QTL was in bin 3.04. Here, two NIL pairs differing for this QTL were derived and used to create two distinct F2:3 family populations that were assessed for southern leaf blight (SLB) resistance. By accounting for segregation of the other QTL in the original RIL data, we were able to combine these data with the new genotypic and phenotypic data from the F2:3 families. Joint analysis yielded a narrower QTL support interval compared to that derived from analysis of any one of the data sets alone, resulting in the localization of the QTL to a less than 0.5 cM interval. Candidate genes identified within this interval are discussed. This methodology allows combined QTL analysis in which data from RIL populations is combined with data derived from NIL populations segregating for the same pair of alleles. It improves mapping resolution over the conventional approach with virtually no additional resources. Because data sets of this type are commonly produced, this approach is likely to prove widely applicable.

Stripe rust is a destructive disease that affects plant growth and substantially reduces wheat yields globally. An economically and environmentally friendly way to control this disease is to use resistant cultivars. 'N2496' is a synthetic hexaploid wheat derivative that exhibits high resistance and could serve as a source of resistance for breeding programs. We developed three recombinant inbred lines (RILs) populations by crossing 'N2496' with common wheat cultivars 'CN16', 'CM107', and 'MM37'. Stripe rust responses were evaluated in all three populations using a mixture of current predominant Chinese Puccinia striiformis f. sp. tritici races. A stripe rust resistance quantitative trait locus (QTL) in the 'N2496'/'CN16' RIL population was mapped on chromosome arm 6BL at 519.35 to 526.55 Mb using bulked segregant RNA sequencing. The population was genotyped using simple sequence repeats and kompetitive allele-specific polymerase (KASP) markers. The QTL QYr.sicau-6B was localized to a 1.19-cM interval flanked by markers KASP-TXK-10 and KASP-TXK-6. The genetic effect of QYr.sicau-6B was validated in the 'N2496' × 'CM107' and 'N2496' × 'MM37' RILs populations and explained up to 63.16% of the phenotypic variation. RNA sequencing and quantitative real-time polymerase chain reaction identified two differentially expressed candidate genes in the physical interval of QYr.sicau-6B.

Unraveling the genetic basis of superior traits in Gossypium barbadense: From phenotype to genotype