Stable Quantitative Trait Loci Research Articles

Construction of a genetic linkage map and QTL mapping of fruit quality traits in guava (Psidium guajava L.).

Guava (Psidium guajava L.) is an important fruit crop of the Indian sub-continent, with potential for improvements in quality and yield. The goal of the present study was to construct a genetic linkage map in an intraspecific cross between the elite cultivar 'Allahabad Safeda' and the Purple Guava landrace to identify the genomic regions responsible for important fruit quality traits, viz., total soluble solids, titratable acidity, vitamin C, and sugars. This population was phenotyped in field trials (as a winter crop) for three consecutive years, and showed moderate-to-high values of heterogeneity coefficients along with higher heritability (60.0%-97.0%) and genetic-advance-over-mean values (13.23%-31.17%), suggesting minimal environmental influence on the expression of fruit-quality traits and indicating that these traits can be improved by phenotypic selection methods. Significant correlations and strong associations were also detected among fruit physico-chemical traits in segregating progeny. The constructed linkage map consisted of 195 markers distributed across 11 chromosomes, spanning a length of 1,604.47 cM (average inter-loci distance of 8.80 markers) and with 88.00% coverage of the guava genome. Fifty-eight quantitative trait loci (QTLs) were detected in three environments with best linear unbiased prediction (BLUP) values using the composite interval mapping algorithm of the BIP (biparental populations) module. The QTLs were distributed on seven different chromosomes, explaining 10.95%-17.77% of phenotypic variance, with the highest LOD score being 5.96 for qTSS.AS.pau-6.2. Thirteen QTLs detected across multiple environments with BLUPs indicate stability and utility in a future breeding program for guava. Furthermore, seven QTL clusters with stable or common individual QTLs affecting two or more different traits were located on six linkage groups (LGs), explaining the correlation among fruit-quality traits. Thus, the multiple environmental evaluations conducted here have increased our understanding of the molecular basis of phenotypic variation, providing the basis for future high-resolution fine-mapping and paving the way for marker-assisted breeding of fruit-quality traits.

A stable quantitative trait locus on chromosome A10 improves the oil content of a backbone parent in Brassica napus L.

One of the most important breeding goals for rapeseed (Brassica napus L.) is improving the oil content (OC) to increase edible or industrial oil quality. Using backbone parents as research materials to excavate OC genetic loci is not only helpful in enhancing the understanding of the genetic basis of OC in rapeseed but also offers a promising approach to improve backbone parents. In this study, a doubled haploid population constructed using the backbone parent 19514 A (with low OC) and the inbred line ZY50 (with high OC) were investigated in eight environments. A total of 30 quantitative trait loci (QTLs) were identified, among which qOC.A10 was detected in six environments. Local QTL scanning for the BC4F2 population showed that qOC.A10 accounted for 22.77% of the phenotypic variance and 0.97% of the additive effect. Further, we improved the parent 19514 A on qOC.A10 by marker-assisted selection, and the background response rate of the improved line A10–19514A reached 97.5%. The phenotypic identification results showed that the OC of A10–19514A and its hybrid significantly increased compared with that of the control, with no negative effects on other agronomic traits. Transcriptome analysis and sequence difference analysis facilitated the prediction of potential functional genes of qOC.A10. This study increases the knowledge regarding the genetic foundation of OC in rapeseed. Furthermore, it identified and confirmed a stable QTL that can be detected in various studies and possesses practical breeding significance.

Identification of candidate genes for soybean seed coat-related traits using QTL mapping and GWAS.

Seed coat color is a typical morphological trait that can be used to reveal the evolution of soybean. The study of seed coat color-related traits in soybeans is of great significance for both evolutionary theory and breeding practices. In this study, 180 F10 recombinant inbred lines (RILs) derived from the cross between the yellow-seed coat cultivar Jidou12 (ZDD23040, JD12) and the wild black-seed coat accession Y9 (ZYD02739) were used as materials. Three methods, single-marker analysis (SMA), interval mapping (IM), and inclusive composite interval mapping (ICIM), were used to identify quantitative trait loci (QTLs) controlling seed coat color and seed hilum color. Simultaneously, two genome-wide association study (GWAS) models, the generalized linear model (GLM) and mixed linear model (MLM), were used to jointly identify seed coat color and seed hilum color QTLs in 250 natural populations. By integrating the results from QTL mapping and GWAS analysis, we identified two stable QTLs (qSCC02 and qSCC08) associated with seed coat color and one stable QTL (qSHC08) related to seed hilum color. By combining the results of linkage analysis and association analysis, two stable QTLs (qSCC02, qSCC08) for seed coat color and one stable QTL (qSHC08) for seed hilum color were identified. Upon further investigation using Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, we validated the previous findings that two candidate genes (CHS3C and CHS4A) reside within the qSCC08 region and identified a new QTL, qSCC02. There were a total of 28 candidate genes in the interval, among which Glyma.02G024600, Glyma.02G024700, and Glyma.02G024800 were mapped to the glutathione metabolic pathway, which is related to the transport or accumulation of anthocyanin. We considered the three genes as potential candidate genes for soybean seed coat-related traits. The QTLs and candidate genes detected in this study provide a foundation for further understanding the genetic mechanisms underlying soybean seed coat color and seed hilum color and are of significant value in marker-assisted breeding.

Dynamic growth QTL action in diverse light environments: characterization of light regime-specific and stable QTL in Arabidopsis.

Plant growth is a complex process affected by a multitude of genetic and environmental factors and their interactions. To identify genetic factors influencing plant performance under different environmental conditions, vegetative growth was assessed in Arabidopsis thaliana cultivated under constant or fluctuating light intensities, using high-throughput phenotyping and genome-wide association studies. Daily automated non-invasive phenotyping of a collection of 382 Arabidopsis accessions provided growth data during developmental progression under different light regimes at high temporal resolution. Quantitative trait loci (QTL) for projected leaf area, relative growth rate, and PSII operating efficiency detected under the two light regimes were predominantly condition-specific and displayed distinct temporal activity patterns, with active phases ranging from 2 d to 9 d. Eighteen protein-coding genes and one miRNA gene were identified as potential candidate genes at 10 QTL regions consistently found under both light regimes. Expression patterns of three candidate genes affecting projected leaf area were analysed in time-series experiments in accessions with contrasting vegetative leaf growth. These observations highlight the importance of considering both environmental and temporal patterns of QTL/allele actions and emphasize the need for detailed time-resolved analyses under diverse well-defined environmental conditions to effectively unravel the complex and stage-specific contributions of genes affecting plant growth processes.

QTL mapping and improvement of pre-harvest sprouting resistance using japonica weedy rice.

The stability of cultivation and production in terms of crop yield has been threatened by climate change due to global warming. Pre-harvest sprouting (PHS) is a threat to crops, especially staple foods, including rice, because of reductions in yield and quality. To address the problem of precocious germination before harvest, we performed quantitative trait loci (QTL) analysis for PHS using F8 RILs populations derived from japonica weedy rice in Korea. QTL analysis revealed that two stable QTLs, qPH7 and qPH2, associated with PHS resistance were identified on chromosomes 7 and 2, respectively, explaining approximately 38% of the phenotypic variation. The QTL effect in the tested lines significantly decreased the degree of PHS, based on the number of QTLs included. Through fine mapping for main QTL qPH7, the region for the PHS was found to be anchored within 23.575-23.785 Mbp on chromosome 7 using 13 cleaved amplified sequence (CAPS) markers. Among 15 open reading frames (ORFs) within the detected region, one ORF, Os07g0584366, exhibited upregulated expression in the resistant donor, which was approximately nine times higher than that of susceptible japonica cultivars under PHS-inducing conditions. Japonica lines with QTLs related to PHS resistance were developed to improve the characteristics of PHS and design practical PCR-based DNA markers for marker-assisted backcrosses of many other PHS-susceptible japonica cultivars.

Genetic dissection of popping quality traits in tropical popcorn (Zea mays L. var. everta)

Mapping quantitative trait loci (QTL) for popping-related traits viz., popping percentage (PP), popping expansion volume (PEV), flake volume (FV) and seed index (SI), is important in popcorn breeding. Therefore, 198 recombinant inbred lines (RILs) developed from a cross of popcorn and field corn lines were phenotyped for popping traits and genotyped using genotyping-by-sequencing (GBS). In the RILs, mean values for PP, FV, PEV and SI ranged from 15.7 to 95.4%, 14.0–484.4 cm, 1.6–21.4 cm and 9.0–28.6 g, respectively. The broad sense heritability (H2%) of the target traits ranged from 82.2 to 96.1% within and 58.9–71.0% between environments. The linkage map based on 6627 filtered single nucleotide polymorphism (SNP) was 2124.30 cM with an average markers interval of 0.33 cM. We mapped four major stable QTLs, one for each SI, PEV, PP and FV on chromosomes 3, 5, 6 and 9, and one minor stable QTL for FV on Chromosome 9 explaining 9.30–29.29% of the phenotypic variance. One major and two minor environment-specific QTLs were mapped on chromosomes 1 and 4 for PEV and SI. In addition, genes involved in kernel endosperm development and metabolic processes were identified and these all can be explored in popcorn improvement.

Introgression of QTL from Aegilops tauschii enhances yield-related traits in common wheat

To break the narrow diversity bottleneck of the wheat D genome, a set of Aegilops tauschii-wheat introgression (A-WI) lines was developed by crossing Ae. tauschii accession T015 with common wheat elite cultivar Zhoumai 18 (Zhou18). A high-density genetic map was constructed based on Single Nucleotide Polymorphism (SNP) markers and 15 yield-related traits were evaluated in 11 environments for detecting quantitative trait loci (QTL). A total of 27 environmentally stable QTL were identified in at least five environments, 20 of which were derived from Ae. tauschii T015, explaining up to 24.27% of the phenotypic variations. The major QTL for kernel length (KL), QKl-2D.5, was delimited to a physical interval of approximately 2.6 Mb harboring 52 candidate genes. Three Kompetitive Allele Specific PCR (KASP) markers were successfully developed based on nonsynonymous nucleotide mutations of candidate gene AetT093_2Dv1G100900.1 and showed that A-WI lines with the T015 haplotype had significantly longer KL than the Zhou18 haplotype across all 11 environments. Four primary valuable A-WIs with good trait performance and carrying yield-related QTL were selected for breeding improvement. The results will facilitate the efficient transfer of beneficial genes from Ae. tauschii into wheat cultivars to improve wheat yield and other traits.

Construction of the first high-density genetic linkage map and QTL mapping of flavonoid and leaf-size related traits in Epimedium

BackgroundLeaves are the main medicinal organ in Epimedium herbs, and leaf flavonoid content is an important criterion of Epimedium herbs. However, the underlying genes that regulate leaf size and flavonoid content are unclear, which limits the use of breeding for Epimedium development. This study focuses on QTL mapping of flavonoid and leaf-size related traits in Epimedium.ResultsWe constructed the first high-density genetic map (HDGM) using 109 F1 hybrids of Epimedium leptorrhizum and Epimedium sagittatum over three years (2019–2021). Using 5,271 single nucleotide polymorphism (SNP) markers, an HDGM with an overall distance of 2,366.07 cM and a mean gap of 0.612 cM was generated by utilizing genotyping by sequencing (GBS) technology. Every year for three years, 46 stable quantitative trait loci (QTLs) for leaf size and flavonoid contents were discovered, including 31 stable loci for Epimedin C (EC), one stable locus for total flavone content (TFC), 12 stable loci for leaf length (LL), and two stable loci for leaf area (LA). For flavonoid content and leaf size, the phenotypic variance explained for these loci varied between 4.00 and 16.80% and 14.95 and 17.34%, respectively.ConclusionsForty-six stable QTLs for leaf size and flavonoid content traits were repeatedly detected over three years. The HDGM and stable QTLs are laying the basis for breeding and gene investigation in Epimedium and will contribute to accelerating the identification of desirable genotypes for Epimedium breeding.

Fine mapping of a major QTL qHYF_B06 for peanut yield

High yield is a major objective for peanut (Arachis hypogaea L.) breeding worldwide. However, fewer yield-related quantitative trait loci (QTL) have been reported in peanut than in other staple food crops such as rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays). This study aimed to identify stable major-effect QTL associated with pod yield per plant, hundred-pod weight for double-seeded pods, hundred-seed weight, shelling percentage, and pod number per plant, allowing us to predict candidate genes by means of transcriptome and genome sequencing. To this end, we used a population of recombinant inbred lines comprising 192 F9:11 families derived from a JH6 × KX01-6 cross to construct a high-resolution genetic map (1705.7 cM) consisting of 2273 polymorphic SNPs, with 0.75 cM (on average) between adjacent SNPs. We identified two high-confidence, yield-related QTL, qHYF_A08 and qHYF_B06, explaining 5.78%–31.40% of phenotypic variation and with LOD values of 5.10–24.48, in six environments. qHYF_A08 mainly explained the variation in shelling percentage, whereas qHYF_B06 explained variation in hundred-pod weight and hundred-seed weight and accounted for 8.77%–31.40% of the variation in effective pod number per plant, pod number per plant, and shelling percentage. We narrowed down qHYF_B06 to an 890-kb interval using an advanced mapping population. Transcriptome and genome analyses revealed that only Arahy.129FS0 and Arahy.3R9A5K in the candidate mapping interval were differentially expressed between JH6 and KX01-6, with substantial structural variations in their promoter and coding regions. Genotypes of 208 peanut accessions determined using a diagnostic CAPS marker suggested that the two haplotypes of Arahy.3R9A5K were highly associated with hundred-seed weight and hundred-pod weight; this diagnostic CAPs marker could therefore be useful for selecting high-yielding lines during peanut breeding. Overall, our results provide valuable information for cloning alleles with favorable effects on peanut yield.

Systematic Characterization of Multi-Rust Resistance Genes from a 'Parula × Thatcher' Population with a High-Density Genetic Map.

Pyramiding multiple resistant genes has been proposed as the most effective way to control wheat rust diseases globally. Identifying the most effective pyramids is challenged by the large pool of rust resistance genes and limited information about their mechanisms of resistance and interactions. Here, using a high-density genetic map, a double haploid population, and multi-rust field testing, we aimed to systematically characterize the most effective gene pyramids for rust resistance from the durable multi-rust resistant CIMMYT cultivar Parula. We revealed that the Parula resistance gene pyramid contains Lr34/Yr18/Sr57 (Lr34), Lr46/Yr29/Sr58 (Lr46), Lr27/Yr30/Sr2 (Sr2), and Lr68. The efficacy, magnitude of effect, and interactions varied for the three rust diseases. A subpopulation mapping approach was applied to characterize the complex interactions of the resistance genes by controlling for the effect of Lr34. Using this approach, we found that Lr34 and Lr68 have a strong additive effect for leaf rust, whereas no additive effects were observed for any rusts between Lr34 and Lr46. Lr34 combined synergistically with Sr12 from Thatcher for stem rust, whereas the additive effect of Lr34 and Sr2 was dependent on the type of rust and environment. Two novel leaf rust quantitative trait loci (QTLs) from Parula were identified in this study, a stable QTL QLr-7BS and QLr-5AS, which showed Lr34 dependent expression. With these findings, we propose combining two to three high-value genes from Canadian wheat (e.g., Sr12 from Thatcher) with a foundational multi-adult plant resistance cassette for desirable and durable resistance to all three rusts in Canadian wheat.

Mapping and validation of quantitative trait loci associated with dorsal aleurone thickness in rice (Oryza sativa)

Mapping of QTLs for dorsal aleurone thickness (DAT) was performed using chromosome segment substitution lines in rice. Three QTLs, qDAT3.1, qDAT3.2, and qDAT7.1, were detected in multiple environments. As a specified endosperm cell type, the aleurone has an abundance of various nutrients. Increasing the number of aleurone layers is a practicable way of developing highly nutritious cereals. Identifying genes that can increase aleurone thickness is useful for the breeding of aleurone traits to improve the nutritional and health values of rice. Here, we found that iodine staining could efficiently distinguish the aleurone layers, which revealed great variation of the aleurone thickness in rice, especially at the dorsal side of the seed. Therefore, we used a population of chromosome segmental substitution lines (CSSLs) derived from Koshihikari and Nona Bokra for quantitative trait locus (QTL) analysis of the dorsal aleurone thickness (DAT). Three QTLs, qDAT3.1, qDAT3.2, and qDAT7.1, were detected in multiple seasons. Among these, qDAT3.2 colocalizes with Hd6 and Hd16, two QTLs previously identified to regulate the heading date of Koshihikari, explaining the negative correlation between the DAT and days to heading (DTH) in rice. We also provide evidence that early-heading ensures the filling of rice seed under a relatively high temperature to promote aleurone thickening. qDAT7.1, the most stable QTL expressed in different environments, functions independently from heading date. Although Nona Bokra has a lower DAT, its qDAT7.1 allele significantly increased DAT in rice, which was further validated using two near-isogenic lines (NILs). These findings pave the way for further gene cloning of aleurone-related QTLs and may aid the development of highly nutritious rice.

Fine mapping and validation of a stable QTL for thousand-kernel weight in wheat (Triticum aestivum L.)

Thousand-kernel weight (TKW) is a measure of grain weight, a target of wheat breeding. The object of this study was to fine-map a stable quantitative trait loci (QTL) for TKW and identify its candidate gene in a recombinant inbred line (RIL) population derived from the cross of Kenong 9204 (KN9204) and Jing 411 (J411). On a high-density genetic linkage map, 24, 26 and 25 QTL were associated with TKW, kernel length (KL), and kernel width (KW), respectively. A major and stable QTL, QTkw-2D, was mapped to an 8.3 cM interval on chromosome arm 2DL. By saturation of polymorphic markers in its target region, QTkw-2D was confined to a 9.13 Mb physical interval using a secondary mapping population derived from a residually heterozygous line (F6:7). This interval was further narrowed to 2.52 Mb using QTkw-2D near-isogenic lines (NILs). NILsKN9204 had higher fresh and dry weights than NILsJ411 at various grain-filling stages. The TKW and KW of NILsKN9204 were much higher than those of NILsJ411 in field trials. By comparison of both DNA sequence and expression between KN9204 and J411, TraesCS2D02G460300.1 (TraesKN2D01HG49350) was assigned as a candidate gene for QTkw-2D. This was confirmed by RNA sequencing (RNA-seq) of QTkw-2D NILs. These results provide the basis of map-based cloning of QTkw-2D, and DNA markers linked to the candidate gene may be used in marker-assisted selection.

Lint percentage and boll weight QTLs in three excellent upland cotton (Gossypium hirsutum): ZR014121, CCRI60, and EZ60

BackgroundUpland cotton (Gossypium hirsutum L.) is the most economically important species in the cotton genus (Gossypium spp.). Enhancing the cotton yield is a major goal in cotton breeding programs. Lint percentage (LP) and boll weight (BW) are the two most important components of cotton lint yield. The identification of stable and effective quantitative trait loci (QTLs) will aid the molecular breeding of cotton cultivars with high yield.ResultsGenotyping by target sequencing (GBTS) and genome-wide association study (GWAS) with 3VmrMLM were used to identify LP and BW related QTLs from two recombinant inbred line (RIL) populations derived from high lint yield and fiber quality lines (ZR014121, CCRI60 and EZ60). The average call rate of a single locus was 94.35%, and the average call rate of an individual was 92.10% in GBTS. A total of 100 QTLs were identified; 22 of them were overlapping with the reported QTLs, and 78 were novel QTLs. Of the 100 QTLs, 51 QTLs were for LP, and they explained 0.29–9.96% of the phenotypic variation; 49 QTLs were for BW, and they explained 0.41–6.31% of the phenotypic variation. One QTL (qBW-E-A10-1, qBW-C-A10-1) was identified in both populations. Six key QTLs were identified in multiple-environments; three were for LP, and three were for BW. A total of 108 candidate genes were identified in the regions of the six key QTLs. Several candidate genes were positively related to the developments of LP and BW, such as genes involved in gene transcription, protein synthesis, calcium signaling, carbon metabolism, and biosynthesis of secondary metabolites. Seven major candidate genes were predicted to form a co-expression network. Six significantly highly expressed candidate genes of the six QTLs after anthesis were the key genes regulating LP and BW and affecting cotton yield formation.ConclusionsA total of 100 stable QTLs for LP and BW in upland cotton were identified in this study; these QTLs could be used in cotton molecular breeding programs. Putative candidate genes of the six key QTLs were identified; this result provided clues for future studies on the mechanisms of LP and BW developments.

Genome-wide association study for grain zinc concentration in bread wheat (Triticum aestivum L.).

Zinc (Zn) deficiency causes serious diseases in people who rely on cereals as their main food source. However, the grain zinc concentration (GZnC) in wheat is low. Biofortification is a sustainable strategy for reducing human Zn deficiency. In this study, we constructed a population of 382 wheat accessions and determined their GZnC in three field environments. Phenotype data was used for a genome-wide association study (GWAS) using a 660K single nucleotide polymorphism (SNP) array, and haplotype analysis identified an important candidate gene for GZnC. We found that GZnC of the wheat accessions showed an increasing trend with their released years, indicating that the dominant allele of GZnC was not lost during the breeding process. Nine stable quantitative trait loci (QTLs) for GZnC were identified on chromosomes 3A, 4A, 5B, 6D, and 7A. And an important candidate gene for GZnC, namely, TraesCS6D01G234600, and GZnC between the haplotypes of this gene showed, significant difference (P ≤ 0.05) in three environments. A novel QTL was first identified on chromosome 6D, this finding enriches our understanding of the genetic basis of GZnC in wheat. This study provides new insights into valuable markers and candidate genes for wheat biofortification to improve GZnC.

QTL detection and candidate gene analysis of grape white rot resistance by interspecific grape (Vitis vinifera L. × Vitis davidii Foex.) crossing.

Grape white rot, a devastating disease of grapevines caused by Coniella diplodiella (Speg.) Sacc., leads to significant yield losses in grape. Breeding grape cultivars resistant to white rot is essential to reduce the regular use of chemical treatments. In recent years, Chinese grape species have gained more attention for grape breeding due to their high tolerance to various biotic and abiotic factors along with changing climatic conditions. In this study, we employed whole-genome resequencing (WGR) to genotype the parents of 'Manicure Finger' (Vitis vinifera, female) and '0940' (Vitis davidii, male), along with 101 F1 mapping population individuals, thereby constructing a linkage genetic map. The linkage map contained 9337 single-nucleotide polymorphism (SNP) markers with an average marker distance of 0.3cM. After 3years of phenotypic evaluation of the progeny for white rot resistance, we confirmed one stable quantitative trait locus (QTL) for white rot resistance on chromosome 3, explaining up to 17.9% of the phenotypic variation. For this locus, we used RNA-seq to detect candidate gene expression and identified PR1 as a candidate gene involved in white rot resistance. Finally, we demonstrated that recombinant PR1 protein could inhibit the growth of C. diplodiella and that overexpression of PR1 in susceptible V. vinifera increased grape resistance to the pathogen.

Fine mapping of the grain chalkiness quantitative trait locus qCGP6 reveals the involvement of Wx in grain chalkiness formation.

Grain chalkiness is an important index of rice appearance quality and is negatively associated with rice processing and eating quality. However, the genetic mechanism underlying chalkiness formation is largely unknown. To identify the genetic basis of chalkiness, 410 recombinant inbred lines (RILs) derived from two representative indica rice varieties, Shuhui498 (R498) and Yihui3551 (R3551), were used to discover quantitative trait loci (QTLs). The two parental lines and RILs were grown in three locations in China under three controlled fertilizer application levels. Analyses indicated that chalkiness was significantly affected by genotype, the environment, and the interaction between the two, and that heritability was high. Several QTLs were isolated, including the two stable QTLs qCGP6 and qCGP8. Fine mapping and candidate gene verification of qCGP6 showed that Wx may play a key role in chalkiness formation. Chromosomal segment substitution lines (CSSLs) and near-isogenic lines (NILs) carrying the Wxa or Wxin allele produced more chalky grain than the R498 parent. A similar result was also observed in the 3611 background. Notably, the effect of the Wx genotype on rice chalkiness was shown to be dependent on environmental conditions, and Wx alleles exhibited different sensitivities to shading treatment. Using clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9), the Wxa promoter region was successfully edited; down-regulating Wx alleviates chalkiness formation in NILR498-Wxa. This study developed a new strategy for synergistic improvement of eating and appearance qualities in rice, and created a novel Wx allele with great potential in breeding applications.

Combining quantitative trait locus mapping with multiomics profiling reveals genetic control of corn leaf aphid (Rhopalosiphum maidis) resistance in maize.

The corn leaf aphid (Rhopalosiphum maidis) is a major maize pest that frequently causes substantial yield losses. Exploring the genetic basis of resistance to aphids is important for improving maize yield and quality. Here, we used a maize recombinant inbred line population derived from two parents with different susceptibility to aphids, B73 (susceptible) and Abe2 (resistant), and performed quantitative trait locus (QTL) mapping using aphid resistance scores as an indicator. We mapped a stable QTL, qRTA6, to chromosome 6 using data from 2 years of field trials, which explained 40.12-55.17% of the phenotypic variation. To further investigate the mechanism of aphid resistance in Abe2, we constructed transcriptome and metabolome libraries from Abe2 and B73 leaves with or without aphid infestation at different time points. Integrating QTL mapping and transcriptome data revealed three aphid resistance candidate genes (Zm00001d035736, Zm00001d035751, and Zm00001d035767) associated with the hypersensitive response, the jasmonic acid pathway, and protein ubiquitination. Integrated transcriptomic and metabolomic analysis revealed that the differentially expressed genes and metabolites were enriched in flavonoid biosynthesis. These findings extend our understanding of the molecular mechanisms controlling aphid resistance in maize, and the QTL and candidate genes are valuable resources for increasing this resistance.

Identification of a stable major sucrose-related QTL and diagnostic marker for flavor improvement in peanut.

An InDel marker closely linked with a major and stable quantitative trait locus (QTL) on chromosome A08, qSUCA08.2, controlling sucrose content will benefit peanut flavor improvement. Sucrose is the main soluble sugar in mature peanut kernel, and its content is a key determinant of flavor. However, the genetic basis of sucrose content in peanut remains poorly understood, which limits the progress of flavor improvement. In the present study, two genomic regions (qSUCA08a and qSUCB06a) for sucrose content on chromosomes A08 and B06 were identified by QTL-seq in a RIL population derived from a cross between Zhonghua 10 and ICG 12625. In the interval of qSUCB06a, QTL qSUCB06.2 was detected through QTL mapping in a single environment. The qSUCA08a was further dissected into 3 adjacent genomic regions using linkage analysis including a major QTL qSUCA08.2 explaining 5.43-17.84% phenotypic variation across five environments. A 61-bp insertion at position 35,099,320 in the higher sucrose parent ICG 12625 was found in qSUCA08.2. An InDel marker SUC.InDel.A08 based on the insertion/deletion polymorphism was developed and validated within a natural population containing 172 peanut cultivars in two environments. The mean sucrose content of 93 cultivars with ICG 12625 allele was significantly higher than that of 79 cultivars with Zhonghua 10 allele. The qSUCA08.2 corresponding to a 2.11Mb interval harbored 110 genes. Among these genes, a total of 19 genes were considered as candidate genes including 5 non-synonymous mutation genes and 14 differentially expressed genes during seed development. These results provide new insights into the genetic basis of sucrose regulation in peanut and benefit the breeding program for developing new varieties with excellent flavor.

Identification and validation of quantitative trait loci for fertile spikelet number per spike and grain number per fertile spikelet in bread wheat (Triticum aestivum L.)

A major and stable QTL for fertile spikelet number per spike and grain number per fertile spikelet identified in a 4.96-Mb interval on chromosome 2A was validated in different genetic backgrounds. Fertile spikelet number per spike (FSN) and grain number per fertile spikelet (GNFS) contribute greatly to wheat yield improvement. To detect quantitative trait loci (QTL) associated with FSN and GNFS, we used a recombinant inbred line population crossed by Zhongkemai 13F10 and Chuanmai 42 in eight environments. Two Genomic regions associated with FSN were detected on chromosomes 2A and 6A using bulked segregant exome sequencing analysis. After the genetic linkage maps were constructed, four QTL QFsn.cib-2A, QFsn.cib-6A, QGnfs.cib-2A and QGnfs.cib-6A were identified in three or more environments. Among them, two major QTL QFsn.cib-2A (LOD = 4.67-9.34, PVE = 6.66-13.05%) and QGnfs.cib-2A (LOD = 5.27-11.68, PVE = 7.95-16.71%) were detected in seven and six environments, respectively. They were co-located in the same region, namely QFsn/Gnfs.cib-2A. The developed linked Kompetitive Allele Specific PCR (KASP) markers further validated this QTL in a different genetic background. QFsn/Gnfs.cib-2A showed pleiotropic effects on grain number per spike (GNS) and spike compactness (SC), and had no effect on grain weight. Since QFsn/Gnfs.cib-2A might be a new locus, it and the developed KASP markers can be used in wheat breeding. According to haplotype analysis, QFsn/Gnfs.cib-2A was identified as a target of artificial selection during wheat improvement. Based on haplotype analysis, sequence differences, spatiotemporal expression patterns, and gene annotation, the potential candidate genes for QFsn/Gnfs.cib-2A were predicted. These results provide valuable information for fine mapping and cloning gene(s) underlying QFsn/Gnfs.cib-2A.

Genome-wide survey identified superior and rare haplotypes for plant height in the north-eastern soybean germplasm of China

The proper and efficient utilization of natural genetic diversity can significantly impact crop improvements. Plant height is a quantitative trait governing the plant type as well as the yield and quality of soybean. Here, we used a combined approach including a genome-wide association study (GWAS) and haplotype and candidate gene analyses to explore the genetic basis of plant height in diverse natural soybean populations. For the GWAS analysis, we used the whole-genome resequencing data of 196 diverse soybean cultivars collected from different accumulated temperature zones of north-eastern China to detect the significant single-nucleotide polymorphisms (SNPs) associated with plant height across three environments (E1, E2, and E3). A total of 33 SNPs distributed on four chromosomes, viz., Chr.02, Chr.04, Chr.06, and Chr.19, were identified to be significantly associated with plant height across the three environments. Among them, 23 were consistently detected in two or more environments and the remaining 10 were identified in only one environment. Interestingly, all the significant SNPs detected on the respective chromosomes fell within the physical interval of linkage disequilibrium (LD) decay (± 38.9 kb). Hence, these genomic regions were considered to be four quantitative trait loci (QTLs), viz., qPH2, qPH4, qPH6, and qPH19, regulating plant height. Moreover, the genomic region flanking all significant SNPs on four chromosomes exhibited strong LD. These significant SNPs thus formed four haplotype blocks, viz., Hap-2, Hap-4, Hap-6, and Hap-19. The number of haplotype alleles underlying each block varied from four to six, and these alleles regulate the different phenotypes of plant height ranging from dwarf to extra-tall heights. Nine candidate genes were identified within the four haplotype blocks, and these genes were considered putative candidates regulating soybean plant height. Hence, these stable QTLs, superior haplotypes, and candidate genes (after proper validation) can be deployed for the development of soybean cultivars with desirable plant heights.