Composite Interval Mapping Method Research Articles

Identification and Mapping of QTLs for Adult Plant Resistance in Wheat Line XK502.

Stripe rust is a serious wheat disease occurring worldwide. At present, the most effective way to control it is to grow resistant cultivars. In this study, a population of 221 recombinant inbred lines (RILs) derived via single-seed descent from a hybrid of a susceptible wheat line, SY95-71, and a resistant line, XK502, was tested in three crop seasons from 2022 to 2024 in five environments. A genetic linkage map was constructed using 12,577 single-nucleotide polymorphisms (SNPs). Based on the phenotypic data of infection severity and the linkage map, five quantitative trait loci (QTL) for adult plant resistance (APR) were detected using the inclusive composite interval mapping (ICIM) method. These five loci are QYrxk502.swust-1BL, QYrxk502.swust-2BL, QYrxk502.swust-3AS, QYrxk502.swust-3BS, and QYrxk502.swust-7BS, explaining 5.67-19.64%, 9.63-36.74%, 9.58-11.30%, 9.76-23.98%, and 8.02-12.41% of the phenotypic variation, respectively. All these QTL originated from the resistant parent XK502. By comparison with the locations of known stripe rust resistance genes, three of the detected QTL, QYrxk502.swust-3AS, QYrxk502.swust-3BS, and QYrxk502.swust-7BS, may harbor new, unidentified genes. From among the tested RILs, 16 lines were selected with good field stripe rust resistance and acceptable agronomic traits for inclusion in breeding programs.

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

G. barbadense is renowned for its high-quality fiber and is highly regarded as a natural material in the textile industry. However, research on cotton has mainly focused on G. hirsutum, and progress in sea island cotton has been relatively slow. There was limited understanding of the genetic loci and transcriptional regulatory mechanisms of important traits, and the genetic basis for the development of superior traits remains unclear. In this study, a recombinant inbred line (RIL) population was constructed using two sea island cotton parents from different cotton regions. The phenotypic characteristics of the two parents and the RIL population, as well as the phenotypic correlations, heritability, and genetic models of the RIL population, were comprehensively analyzed. The RIL population was genotyped using whole-genome resequencing technology, and a high-density intraspecific linkage map was constructed, consisting of 5295 bin markers and a total genetic map distance of 2721.79 centimorgans (cM). Phenotypic data collected from five different environments were used to detect 169 quantitative trait loci (QTLs) using the composite interval mapping method. Among these QTLs, 30 were related to agronomic traits, 61 were related to yield traits, and 78 were related to fiber quality traits. Additionally, 17 QTL clusters were detected, and the additive effects of these clusters explained the correlation between different phenotypic traits. Candidate genes for stable QTLs related to agronomic and yield traits were identified through variant annotation and functional prediction. Two bin markers associated with lint percentage (LP) were validated as potential breeding markers. Furthermore, using RNA-seq data of cotton fiber from the RIL population parents, the dynamic changes in gene expression during different developmental stages of cotton fiber were revealed, and important differentially expressed genes in the secondary cell wall development and metabolism network of fibers were identified. Importantly, through the combined analysis of fiber trait QTLs and transcriptomes, eight candidate genes involved in regulating fiber quality traits were predicted, and the genetic basis of the excellent allele site qFL_D04_1 in the breeding history of Chinese sea island cotton was elucidated. In summary, this study provides new genetic resources and potential breeding markers for cotton variety improvement, valuable theoretical information for understanding the genetic basis of important traits in sea island cotton, and effectively promotes the development of cotton biotechnology breeding.

QTL Mapping Using RIL Population.

Genetic maps are an excellent tool for the analysis of important traits, the development of which is the result of the combined expression of several genes, enabling the genomic localization of the factors determining them. Such features, characterized by a normal distribution of values, are referred to as quantitative or polygenic. The analysis of their genetic background using a chromosome map is called the mapping of quantitative traits loci (QTL). QTL analysis is a statistical method of determining the genetic association of phenotypic data (trait measurements) with genotypic data (DNA markers assigned to linkage groups).There are numerous tools developed for QTL mapping. This chapter introduces Windows QTL Cartographer with Composite Interval Mapping (CIM) method, which estimates the QTL position by combining interval mapping with multiple regression. The genotypic and phenotypic data used in the exemplary QTL mapping procedure were obtained for the recombinant inbred line (RIL) population of rye. Plant height, assessed in three seasons, was the exemplary trait under study.

A High-Resolution Linkage Map Construction and QTL Analysis for Morphological Traits in Anthurium (Anthurium andraeanum Linden).

Anthurium andraeanum Linden is a prominent ornamental plant belonging to the family Araceae and is cultivated worldwide. The morphology characteristics are crucial because they significantly impact ornamental values, commercial properties, and the efficiency of space utilization in production. However, only a few related investigations have been conducted in anthurium to date. In this study, an F1 genetic segregation population containing 160 progenies was generated through hybridization between potted and cut anthurium varieties. Fifteen morphological traits were assessed and revealed substantial levels of genetic variation and widespread positive correlation. Based on specific length amplified fragment (SLAF) sequencing technology, 8171 single nucleotide polymorphism (SNP) markers were developed, and the high-density linkage map of 2202.27 cM in length distributed on 15 linkage groups was constructed successfully, with an average distance of 0.30 cM. Using the inclusive composite interval mapping (ICIM) method, 59 QTLs related to 15 key morphological traits were successfully identified, which explained phenotypic variance (PVE) ranging from 6.21% to 17.74%. Thirty-three of those associated with 13 traits were designated as major QTLs with PVE > 10%. These findings offer valuable insights into the genetic basis of quantitative traits and are beneficial for molecular marker-assisted selection (MAS) in anthurium breeding.

Genetic Mapping for QTL Associated with Seed Nickel and Molybdenum Accumulation in the Soybean 'Forrest' by 'Williams 82' RIL Population.

Understanding the genetic basis of seed Ni and Mo is essential. Since soybean is a major crop in the world and a major source for nutrients, including Ni and Mo, the objective of the current research was to map genetic regions (quantitative trait loci, QTL) linked to Ni and Mo concentrations in soybean seed. A recombinant inbred line (RIL) population was derived from a cross between 'Forrest' and 'Williams 82' (F × W82). A total of 306 lines was used for genotyping using 5405 single nucleotides polymorphism (SNP) markers using Infinium SNP6K BeadChips. A two-year experiment was conducted and included the parents and the RIL population. One experiment was conducted in 2018 in North Carolina (NC), and the second experiment was conducted in Illinois in 2020 (IL). Logarithm of the odds (LOD) of ≥2.5 was set as a threshold to report identified QTL using the composite interval mapping (CIM) method. A wide range of Ni and Mo concentrations among RILs was observed. A total of four QTL (qNi-01, qNi-02, and qNi-03 on Chr 2, 8, and 9, respectively, in 2018, and qNi-01 on Chr 20 in 2020) was identified for seed Ni. All these QTL were significantly (LOD threshold > 2.5) associated with seed Ni, with LOD scores ranging between 2.71-3.44, and with phenotypic variance ranging from 4.48-6.97%. A total of three QTL for Mo (qMo-01, qMo-02, and qMo-03 on Chr 1, 3, 17, respectively) was identified in 2018, and four QTL (qMo-01, qMo-02, qMo-03, and qMo-04, on Chr 5, 11, 14, and 16, respectively) were identified in 2020. Some of the current QTL had high LOD and significantly contributed to the phenotypic variance for the trait. For example, in 2018, Mo QTL qMo-01 on Chr 1 had LOD of 7.8, explaining a phenotypic variance of 41.17%, and qMo-03 on Chr 17 had LOD of 5.33, with phenotypic variance explained of 41.49%. In addition, one Mo QTL (qMo-03 on Chr 14) had LOD of 9.77, explaining 51.57% of phenotypic variance related to the trait, and another Mo QTL (qMo-04 on Chr 16) had LOD of 7.62 and explained 49.95% of phenotypic variance. None of the QTL identified here were identified twice across locations/years. Based on a search of the available literature and of SoyBase, the four QTL for Ni, identified on Chr 2, 8, 9, and 20, and the five QTL associated with Mo, identified on Chr 1, 17, 11, 14, and 16, are novel and not previously reported. This research contributes new insights into the genetic mapping of Ni and Mo, and provides valuable QTL and molecular markers that can potentially assist in selecting Ni and Mo levels in soybean seeds.

QTL cluster analysis and marker development for kernel traits based on DArT markers in spring bread wheat (Triticum aestivum L.).

Genetic dissection of yield component traits including kernel characteristics is essential for the continuous improvement in wheat yield. In the present study, one recombinant inbred line (RIL) F6 population derived from a cross between Avocet and Chilero was used to evaluate the phenotypes of kernel traits of thousand-kernel weight (TKW), kernel length (KL), and kernel width (KW) in four environments at three experimental stations during the 2018-2020 wheat growing seasons. The high-density genetic linkage map was constructed with the diversity arrays technology (DArT) markers and the inclusive composite interval mapping (ICIM) method to identify the quantitative trait loci (QTLs) for TKW, KL, and KW. A total of 48 QTLs for three traits were identified in the RIL population on the 21 chromosomes besides 2A, 4D, and 5B, accounting for 3.00%-33.85% of the phenotypic variances. Based on the physical positions of each QTL, nine stable QTL clusters were identified in the RILs, and among these QTL clusters, TaTKW-1A was tightly linked to the DArT marker interval 3950546-1213099, explaining 10.31%-33.85% of the phenotypic variances. A total of 347 high-confidence genes were identified in a 34.74-Mb physical interval. TraesCS1A02G045300 and TraesCS1A02G058400 were among the putative candidate genes associated with kernel traits, and they were expressed during grain development. Moreover, we also developed high-throughput kompetitive allele-specific PCR (KASP) markers of TaTKW-1A, validated in a natural population of 114 wheat varieties. The study provides a basis for cloning the functional genes underlying the QTL for kernel traits and a practical and accurate marker for molecular breeding.

Identification of novel and stable genomic regions associated with barley resistance to spot form net blotch disease under different temperature conditions during the reproductive stage

AbstractSpot form net blotch (SFNB) is one of the most important barley diseases in the world; abiotic stresses caused by climate change are also a problem for cultivation of cereals, including barley, on a global level. Identifying stable genomic regions associated with resistance to SFNB in different temperature conditions at the reproductive stage can accelerate the process of producing new cultivars resistant to this disease. In this study, 103 F8 lines, resulting from the cross of cultivars Kavir and Badia, were cultivated in three years on three different dates. After artificial inoculation with Pyrenophora teres f. maculata Gonbad Kavous isolate, the plants were evaluated at the adult stage. The planting dates were chosen so that during early, conventional and delayed planting dates, the reproductive stage of the lines coincided with cold, non‐thermal and heat stress conditions, respectively. A genome‐wide composite interval mapping method was used to identify quantitative trait loci (QTLs) controlling SFNB and estimate the effect of each of them. In the cold, non‐thermal and heat stress conditions at the reproductive stage, three (three major), four (two major) and six (one major) stable resistance QTLs against SFNB were detected, respectively. The stable QTLs of resistance including QRPtma‐2H, QRPtma‐3H and QRPtma‐7H were located on chromosomes 2H, 3H and 7H, respectively. After flanking markers confirm the resistance of QTLs to SFNB, the SCoT7‐C, ISJ17‐B and Bmac0144k markers can be used in the screening resistance of cultivars under non‐thermal and heat stress conditions. Moreover, the Bmac0282b and Ebmatc0016 markers can be used for screening resistance of cultivars under cold stress conditions in marker‐assisted selection projects.

Mapping quantitative trait loci and predicting candidate genes for Striga resistance in maize using resistance donor line derived from Zea diploperennis.

The parasitic weed, Striga is a major biological constraint to cereal production in sub-Saharan Africa (SSA) and threatens food and nutrition security. Two hundred and twenty-three (223) F2:3 mapping population involving individuals derived from TZdEI 352 x TZEI 916 were phenotyped for four Striga-adaptive traits and genotyped using the Diversity Arrays Technology (DArT) to determine the genomic regions responsible for Striga resistance in maize. After removing distorted SNP markers, a genetic linkage map was constructed using 1,918 DArTseq markers which covered 2092.1cM. Using the inclusive composite interval mapping method in IciMapping, twenty-three QTLs influencing Striga resistance traits were identified across four Striga-infested environments with five stable QTLs (qGY4, qSC2.1, qSC2.2, qSC5, and qSC6) detected in more than one environment. The variations explained by the QTLs ranged from 4.1% (qSD2.3) to 14.4% (qSC7.1). Six QTLs each with significant additive × environment interactions were also identified for grain yield and Striga damage. Gene annotation revealed candidate genes underlying the QTLs, including the gene models GRMZM2G077002 and GRMZM2G404973 which encode the GATA transcription factors, GRMZM2G178998 and GRMZM2G134073 encoding the NAC transcription factors, GRMZM2G053868 and GRMZM2G157068 which encode the nitrate transporter protein and GRMZM2G371033 encoding the SBP-transcription factor. These candidate genes play crucial roles in plant growth and developmental processes and defense functions. This study provides further insights into the genetic mechanisms of resistance to Striga parasitism in maize. The QTL detected in more than one environment would be useful for further fine-mapping and marker-assisted selection for the development of Striga resistant and high-yielding maize cultivars.

Identification of a genomic region linked with sex determination of Undaria pinnatifida (Alariaceae) through genomic resequencing and genetic linkage analyses of a segregating gametophyte family.

Different from the traditional knowledge about kelp, three sexual phenotypes (female, male, and monoecious) exist in the haploid gametophytes of Undaria pinnatifida. However, the sex-determining mechanisms remain unknown. Genetic linkage mapping is an efficient tool to identify sex-linked regions. In the present study, we resequenced a segregating gametophyte family based on the male genome of U. pinnatifida. A high-density genetic linkage map was constructed using 9887 SNPs, with an average distance of 0.41 cM between adjacent SNPs. On the basis of this genetic map and using the composite interval mapping method, we identified 62 SNPs significantly linked with the sexual phenotype. They were located at a position of 67.67 cM on the linkage group 23, corresponding to a physical range of 14.67 Mbp on the HiC_Scaffold_23 of the genome. Reanalysis of the previous specific length amplified fragment sequencing data according to the reference genome led to the identification of a sex-linked genomic region that encompassed the above-mentioned 14.67 Mbp region. Hence, this overlapped genomic range was likely the sex-determining region. Within this region, 129 genes were retrieved and 39 of them were annotated with explicit function, including the potential male sex-determining gene-encoding high mobility group (HMG) domain protein. Relative expression analysis of the HMG gene showed that its expression was higher in male gametophytes during the vegetative phase and monoecious gametophytes during both the vegetative and gametogenesis phases, but significantly lower in male gametophytes during the gametogenesis phase. These results provide a foundation for deciphering the sex-determining mechanism of U. pinnatifida.

QTL mapping and genomic prediction of resistance to wheat head blight caused by Fusarium verticillioides.

Fusarium head blight (FHB), is one of the destructive fugue diseases of wheat worldwide caused by the Fusarium verticillioides (F.v). In this study, a population consisting of 262 recombinant inbred lines (RILs) derived from Zhongmai 578 and Jimai 22 was used to map Quantitative Trait Locus (QTL) for FHB resistance, with the genotype data using the wheat 50K single nucleotide polymorphism (SNP) array. The percentage of symptomatic spikelet (PSS) and the weighted average of PSS (PSSW) were collected for each RIL to represent their resistance to wheat head blight caused by F.v. In total, 22 QTL associated with FHB resistance were identified on chromosomes 1D, 2B, 3B, 4A, 5D, 7A, 7B, and 7D, respectively, from which 10 and 12 QTL were detected from PSS and PSSW respectively, explaining 3.82%-10.57% of the phenotypic variances using the inclusive composite interval mapping method. One novel QTL, Qfhb. haust-4A.1, was identified, explaining 10.56% of the phenotypic variation. One stable QTL, Qfhb. haust-1D.1 was detected on chromosome 1D across multiple environments explaining 4.39%-5.70% of the phenotypic variation. Forty-seven candidate genes related to disease resistance were found in the interval of Qfhb. haust-1D.1 and Qfhb. haust-4A.1. Genomic prediction accuracies were estimated from the five-fold cross-validation scheme ranging from 0.34 to 0.40 for PSS, and from 0.34 to 0.39 for PSSW in in-vivo inoculation treatment. This study provided new insight into the genetic analysis of resistance to wheat head blight caused by F.v, and genomic selection (GS) as a potential approach for improving the resistance of wheat head blight.

QTL analysis of early flowering of female flowers in zucchini (Cucurbita pepo L.)

Early flowering promotes early maturity, production, and the capacity to counteract biotic and abiotic stresses, making it an important agronomic trait in zucchini. The present study demonstrated that the zucchini inbred line ‘19’ consistently flowered early, taking significantly fewer days to bloom the first female flower (DFF) than the inbred line ‘113’. Genetic analysis revealed that DFF, an inheritable quantitative trait, is controlled by multiple genes. Based on the strategy of quantitative trait locus (QTL) sequencing (QTL-seq) combined with linkage analysis, three QTLs for DFF were identified on chromosomes 4, 11, and 20. This study used additional F2 populations grown under different environmental conditions for QTL mapping analysis of DFF with insertion/deletion (InDel) markers to validate these results. Using the composite interval mapping (CIM) method of R/qtl software, we only identified one major locus under all environmental conditions, located in a 117-kb candidate region on chromosome 20. Based on gene annotation, gene sequence alignment, and qRT-PCR analysis, we found that the Cp4.1LG20g08050 gene encoding a RING finger protein may be a candidate gene for the opposite regulation of early flowering in zucchini. In summary, these results lay a foundation for a better understanding of early flowering and improving early flowering-based breeding strategies in zucchini.

Analyses and identifications of quantitative trait loci and candidate genes controlling mesocotyl elongation in rice

Rice direct seeding has the significant potential to save labor and water, conserve environmental resources, and reduce greenhouse gas emissions tremendously. Therefore, rice direct seeding is becoming the major cultivation technology applied to rice production in many countries. Identifying and utilizing genes controlling mesocotyl elongation is an effective approach to accelerate breeding procedures and meet the requirements for direct-seeded rice (DSR) production. This study used a permanent mapping population with 144 recombinant inbred lines (RILs) and 2 828 bin-markers to detect quantitative trait loci (QTLs) associated with mesocotyl length in 2019 and 2020. The mesocotyl lengths of the rice RILs and their parents, Lijiangxintuanheigu (LTH) and Shennong 265 (SN265), were measured in a growth chamber at 30°C in a dark environment. A total of 16 QTLs for mesocotyl length were identified on chromosomes 1(2), 2(4), 3(2), 4, 5, 6, 7, 9, 11(2), and 12. Seven of these QTLs, including qML1a, qML1b, qML2d, qML3a, qML3b, qML5, and qML11b, were reproducibly detected in both years via the interval mapping method. The major QTL, qML3a, was reidentified in two years via the composite interval mapping method. A total of 10 to 413 annotated genes for each QTL were identified in their smallest genetic intervals of 37.69 kb to 2.78 Mb, respectively. Thirteen predicted genes within a relatively small genetic interval (88.18 kb) of the major mesocotyl elongation QTL, qML3a, were more thoroughly analyzed. Finally, the coding DNA sequence variations among SN265, LTH, and Nipponbare indicated that the LOC_Os03g50550 gene was the strongest candidate gene for the qML3a QTL controlling the mesocotyl elongation. This LOC_Os03g50550 gene encodes a mitogen-activated protein kinase. Relative gene expression analysis using qRT-RCR further revealed that the expression levels of the LOC_Os03g50550 gene in the mesocotyl of LTH were significantly lower than in the mesocotyl of SN265. In conclusion, these results further strengthen our knowledge about rice's genetic mechanisms of mesocotyl elongation. This investigation's discoveries will help to accelerate breeding programs for new DSR variety development.

Genetic Analysis of Adult Plant Resistance to Stripe Rust in Common Wheat Cultivar "Pascal".

Wheat stripe rust is an important foliar disease that affects the wheat yield globally. Breeding for resistant wheat varieties is one of the most economically and environmentally effective ways to control this disease. The common wheat (Triticum aestivum L.) cultivar “Pascal” exhibited susceptibility to stripe rust at the seedling stage but it showed high resistance to stripe rust at the adult plant stage over 20 years in Gansu, a hotspot of the disease in northwestern China. To understand the genetic mechanism of stripe rust resistance in this cultivar, a 55K SNP array was used to analyze the two parents and the 220 recombinant inbred lines (RILs) derived from the cross of “Huixianhong” × “Pascal.” We detected three new stripe rust adult plant resistance (APR) quantitative trait locus (QTL) contributed by Pascal, viz. QYr.gaas-1AL, QYr.gaas-3DL, and QYr.gaas-5AS, using the inclusive composite interval mapping method. They were flanked by SNP markers AX-111218361—AX-110577861, AX-111460455—AX-108798599, and AX-111523523—AX-110028503, respectively, and explained the phenotypic variation ranging from 11.0 to 23.1%. Bulked segregant exome capture sequencing (BSE-Seq) was used for fine mapping of QYr.gaas-1AL and selection of candidate genes, TraesCS1A02G313700, TraesCS1A02G313800, and TraesCS1A02G314900 for QYr.gaas-1AL. KASP markers BSE-1A-12 and HXPA-3D for QYr.gaas-1AL and QYr.gaas-3DL were developed for breeders to develop durable stripe rust-resistant wheat varieties.

Genetic basis of heterosis in a common wheat cross withstrong-heterosis

<p indent="0mm">Heterosis refers to the phenomenon that a heterozygous hybrid exhibits superior performances over its parents, which has been suggested as a solution to overcome yield stagnation of wheat. However, the molecular basis of wheat heterosis is still poorly understood. We have previously found that a cross derived from the winter common wheat Nongda3338 (ND3338) and Jingdong 6 (JD6) showed strong mid-parent heteroses on plant height (PH) and thousand grain weight (TGW). In this study, we further aimed to investigate the genetic underpinnings of PH and TGW using an “immortalized F₂” (IF₂) derived from the ND3338/JD6 doubled haploid (DH) population. The PH and TGW of DH and IF₂ populations were evaluated across two different environments, and the mid-parent heterosis value (HV) was used to measure heterosis. The direction and magnitude of HV greatly varied between PH and TGW across the environments. A two-way analysis of variance (ANOVA) was performed for PH and TGW in the IF₂ population, revealing that genetic variation was the main source, despite the significant variations found from the environments and genotype by environment interaction. The broad sense heritability of PH and TGW in IF₂ population was 94.05% and 88.14%, respectively. Pearson’s correlation coefficients of PH, TGW, HV_PH and HV_TGW in the IF₂ population were estimated based on the best linear unbiased prediction (BLUP) values of two environments, showing that PH was significantly positively correlated with TGW and HV_TGW, TGW was significantly positively correlated with HV_TGW and negatively correlated with HV_PH, while HV_PH had a strong positive correlation with HV_TGW. The genotypes of the IF₂ population were deduced from corresponding DH parents. Based on the inclusive composite interval mapping method, quantitative trait locus (QTL) mapping was separately conducted with PH, TGW, HV_PH and HV_TGW using the QTL IciMapping software. We identified a total of 32 and 25 QTL that exhibited additive, dominant and overdominant pattern associated with PH and TGW, which accounted for 0.54%–36.05% and 0.87%–25.78% of the variance, respectively. Consistent with the results found in the ND3338/JD6 DH population, major and stable QTL on chromosomes 2D (<italic>QPh</italic>.<italic>2D</italic>.<italic>1</italic> and <italic>QTgw</italic>.<italic>2D</italic>), 4B (<italic>QPh</italic>.<italic>4B</italic>.<italic>1</italic> and <italic>QTgw</italic>.<italic>4B</italic>.<italic>1</italic>) and 4D (<italic>QPh</italic>.<italic>4D </italic>and <italic>QTgw</italic>.<italic>4D</italic>) that were coincident with the dwarfing genes <italic>Rht1</italic>, <italic>Rht2</italic> and <italic>Rht8</italic> were detected, suggesting that the IF₂ population design is feasible and reliable for identifying the genetic components of heterosis. Furthermore, 13 QTL for HV_PH and 15 QTL for HV_TGW were identified, of which most of these loci exhibited overdominant pattern. However, only few of the QTL controlling PH and TGW were overlapped with those controlling HV_PH and HV_TGW, suggesting potentially different genetic mechanisms between phenotypic traits and heterosis. In addition, epistasis analysis for PH and TGW revealed that four types of digenic interactions, including additive by additive (AA), additive by dominance (AD), dominance by additive (DA) and dominance by dominance (DD), were involved in the genetic basis of hybrid performance and heterosis in the IF₂ population. Notably, the DD-oriented QTL with the greatest interactive effects possessed the highest frequency. Overall, this study provides strong evidence for supporting the classical genetic hypotheses of heterosis (dominance, overdominance, and epistasis) with an IF₂ population, establishing the foundation to develop and select crosses with strong heterosis.

Molecular mapping and validation of quantitative trait loci for spike-related traits and plant height in wheat

<p id="C3">Spike-related traits and plant height are important target traits in wheat breeding. In the present study, a population of 198 recombinant inbred lines (RILs) derived from the cross between a CIMMYT wheat line C615 and Yangmai 13 (YM13) was constructed, followed by genotyping with Wheat 90K SNP array and phenotyping of spike-related traits and plant height in three environments to excavate QTLs (quantitative trait loci) for these traits. Using composite interval mapping method, we identified one QTL for total spikelet number per spike (TSS), two QTLs for spike length (SL), two QTLs for spikelet compactness (SC), and three QTLs for plant height (PH). <italic>QSN.yaas-3B</italic> and <italic>QPH.yaas-3B</italic> overlapped on the chromosome 3B. <italic>QSL.yaas-5A</italic>, <italic>QSC.yaas-5A</italic> and <italic>QPH.yaas-5A</italic> overlapped on the chromosome 5A. <italic>QSL.yaas-6A</italic> and <italic>QSC.yaas-6A</italic> overlapped on the chromosome 6A. <italic>QSN.yaas-3B</italic>/<italic>QPH.yaas-3B</italic> and <italic>QSL.yaas-6A</italic>/<italic>QSC.yaas-6A</italic> had not been reported yet, and were likely to be novel loci. The SNP marker closely linked to <italic>QSL.yaas-5A</italic>/<italic>QSC.yaas-5A</italic>/<italic>QPH.yaas-5A</italic> was then converted into one Kompetitive Allele Specific PCR (KASP) marker (QC615-5A-KASP), and validated in a panel of 105 wheat lines. The results would be useful for improvement of yield related traits in wheat breeding.

Identification and mapping of QTL associated with some traits related for drought tolerance in wheat using SSR markers

BackgroundWheat is the most important crop around the world. Drought stresses affect wheat production and their characterization. Most of the traits that are affected by drought are quantitative traits, so detection of the quantitative trait’s loci (QTLs) related to these traits is very important for breeder and wheat producers. In this trend, 285 F2 individuals from crosses between four bread wheat genotypes (Triticum aestivum L.), i.e., Sakha93, Sids1, Sakha94, and Gemmiza9, were used for identified QTLs associated with plant height (PH) and leaf wilting (LW). Single marker analysis and composite interval mapping (CIM) were used.ResultsA total of 116 QTLs loci were detected which covered 19 chromosomes out of the 21 chromosomes of wheat. PH and LW had 74 and 42 QTLs loci, respectively. On the other hand, chromosome 7A showed to bear the highest number of QTLs loci (15 loci). While chromosome 1A beard the highest number of QTLs loci related to PH (10 loci), chromosome 2B and 7A beard the highest number of QTLs related LW. We highly recommend our finding to help breeders in wheat breeding programs to improve plant height and leaf wilting.ConclusionOur investigation concluded that SSR markers have high efficiency in the identification of QTLs related to abiotic stress; also the CIM method had more advanced priority for QTLs mapping.

Genetics of seed protein and oil inherited from “BARC-7” soybean in two F2-derived mapping populations

ABSTRACT Soybean [Glycine max (L.) Merr.] seed protein inheritance has been extensively studied; however, genetics of high-protein “BARC-7” soybean are still unknown. In this study, we used 250 F2-derived lines from each of two soybean populations for quantitative trait loci (QTL) mapping. UA 5814HP, with high-protein content, tracing to BARC-7 as maternal grandfather, was a common parent. Field experiments were conducted using a randomized complete block design with one replication across four environments. Seed protein and oil were quantified using near-infrared (NIR) instrument. Genetic linkage maps were constructed using the Infinium Soy6KSNP Beadchips. QTL analysis was performed using a composite interval mapping method. QTL for protein and oil were identified on chromosomes 6, 13, and 20. The known major QTL on chromosome 20 was not detected, but a novel QTL further downstream on chromosome 20 (only detected in population two) had high-protein alleles inherited from BARC-7-derived parent. Fine mapping efforts are currently ongoing for confirmation of these results.

QTL Mapping of Resistance to Bacterial Wilt in Pepper Plants (Capsicum annuum) Using Genotyping-by-Sequencing (GBS)

Bacterial wilt (BW) disease, which is caused by Ralstonia solanacearum, is one globally prevalent plant disease leading to significant losses of crop production and yield with the involvement of a diverse variety of monocot and dicot host plants. In particular, the BW of the soil-borne disease seriously influences solanaceous crops, including peppers (sweet and chili peppers), paprika, tomatoes, potatoes, and eggplants. Recent studies have explored genetic regions that are associated with BW resistance for pepper crops. However, owing to the complexity of BW resistance, the identification of the genomic regions controlling BW resistance is poorly understood and still remains to be unraveled in the pepper cultivars. In this study, we performed the quantitative trait loci (QTL) analysis to identify genomic loci and alleles, which play a critical role in the resistance to BW in pepper plants. The disease symptoms and resistance levels for BW were assessed by inoculation with R. solanacearum. Genotyping-by-sequencing (GBS) was utilized in 94 F2 segregating populations originated from a cross between a resistant line, KC352, and a susceptible line, 14F6002-14. A total of 628,437 single-nucleotide polymorphism (SNP) was obtained, and a pepper genetic linkage map was constructed with putative 1550 SNP markers via the filtering criteria. The linkage map exhibited 16 linkage groups (LG) with a total linkage distance of 828.449 cM. Notably, QTL analysis with CIM (composite interval mapping) method uncovered pBWR-1 QTL underlying on chromosome 01 and explained 20.13 to 25.16% by R2 (proportion of explained phenotyphic variance by the QTL) values. These results will be valuable for developing SNP markers associated with BW-resistant QTLs as well as for developing elite BW-resistant cultivars in pepper breeding programs.

Mapping novel QTLs for yield related traits from a popular rice hybrid KRH-2 derived doubled haploid (DH) population.

The online version contains supplementary material available at 10.1007/s13205-021-03045-7.

Mapping of QTL for agronomic traits using high-density SNPs with an RIL population in maize.

Genome wide association studies (GWAS) have been widely used to identify QTLs underlying quantitative traits in humans and animals, and they have also become a popular method of mapping QTLs in many crops, including maize. Advances in high-throughput genotyping technologies enable construction of high-density linkage maps using SNP markers. High-density genetic mapping must precede to find molecular markers associated with a particular trait. The objectives of this study were to (1) construct a high-density linkage map using SNP markers and (2) detect the QTLs for grain yield and quality related traits of the Mo17/KW7 RIL population. In this study, two parental lines, Mo17 (normal maize inbred line) and KW7 (waxy inbred line) and 80 F7:8 lines in the Mo17/KW7 RIL population were genotyped using the MaizeSNP50 BeadChip, an Illumina BeadChip array of 56,110 maize SNPs. Marker integration and detection of QTLs was performed using the inclusive composite interval mapping (ICIM) method within the QTL IciMapping software. This study was genotyped using the Illumina MaizeSNP50 BeadChip for maize Mo17/KW7 recombinant inbred line (RIL) population. The 2904 SNP markers were distributed along all 10 maize chromosomes. The total length of the linkage map was 3553.7cm, with an average interval of 1.22cm between SNPs. A total of 18 QTLs controlling eight traits were detected in the Mo17/KW7 RIL population. Three QTLs for plant height (PH) were detected on chromosomes 4 and 8 and showed from 16.01% (qPH8) to 19.85% (qPH4a) of phenotypic variance. Five QTLs related to ear height (EH) were identified on chromosomes 3, 4, and 6 and accounted for 3.79% (qEH6) to 27.57% (qEH4b) of phenotypic variance. Five QTLs related to water content (WC) on chromosomes 1, 4, 8, and 9 accounted for 9.55% (qWC8b) to 23.30% (qWC4) of phenotypic variance. One QTL (qAC9) relating to amylose content (AC) on chromosome 9 showed 82.10% of phenotypic variance. The high-density linkage map and putative QTLs of the maize RIL population detected in this study can be effectively utilized in waxy and normal maize breeding programs to facilitate the selection process through marker-assisted selection (MAS) breeding programs.