Quantitative Trait Loci Intervals Research Articles

QTL analysis of divergent floral morphology traits between Gilia yorkii and G. capitata.

Speciation is a complex process typically accompanied by significant genetic and morphological differences between sister populations. In plants, divergent floral morphologies and pollinator differences can result in reproductive isolation between populations. Here, we explore floral trait differences between two recently diverged species, Gilia yorkii and G. capitata. The distributions of floral traits in parental, F1, and F2 populations are compared, and groups of correlated traits are identified. We describe the genetic architecture of floral traits through a quantitative trait locus (QTL) analysis using an F2 population of 187 individuals. While all identified QTLs were of moderate (10-25%) effect, interestingly, most QTL intervals were non-overlapping, suggesting that, in general, traits do not share a common genetic basis. Our results provide a framework for future identification of genes involved in the evolution of floral morphology.

QTL Mapping and Candidate Gene Mining for Stem Diameter Using Genetic Basis of Cultivated Soybean and Wild Soybean

Soybean (Glycine max) is a vital food crop, serving as a major source of high-quality protein for human and animal consumption. Stem diameter is one of the primary determinants of the stem lodging resistance of a given plant, but there has been relatively little research to date focused on genes associated with this trait. To address this gap in the literature, 207 chromosome segment substitution lines (CSSLs) were generated in the present study through the crossing and backcrossing of the improved Suinong14 and the wild ZYD00006 soybean varieties. These CSSLs were then used for the mapping of quantitative trait loci (QTLs) associated with stem diameter in two-year field planting materials, leading to the identification of nine QTLs. Whole genome resequencing, RNA-seq, and qPCR were then used to evaluate candidate genes associated with stem diameter within these QTL intervals, ultimately leading to the selection of Glyma.04G004100 as a stem diameter-related gene. Subsequent qPCR analyses revealed that Glyma.04g004100 was upregulated in soybean plants with larger stem diameters, and haplotype analyses yielded results consistent with these stem diameter data in the population used to conduct this study. In summary, a series of QTLs associated with stem diameter were identified in the present study, resulting in the establishment of Glyma.04g004100 as a stem diameter-related gene. Together, these results offer a theoretical foundation for the future molecular-assisted breeding of lodging-resistant soybean varieties, and future functional research focused on Glyma.04g004100 may elucidate the molecular mechanisms and key signaling networks involved in soybean stem development.

Multiomics-assisted characterization of rice-Yellow Stem Borer interaction provides genomic and mechanistic insights into stem borer resistance in rice.

By deploying a multi-omics approach, we unraveled the mechanisms that might help rice to combat Yellow Stem Borer infestation, thus providing insights and scope for developing YSB resistant rice varieties. Yellow Stem Borer (YSB), Scirpophaga incertulas (Walker) (Lepidoptera: Crambidae), is a major pest of rice, that can lead to 20-60% loss in rice production. Effective management of YSB infestation is challenged by the non-availability of adequate sources of resistance and poor understanding of resistance mechanisms, thus necessitating studies for generating resources to breed YSB resistant rice and to understand rice-YSB interaction. In this study, by using bulk-segregant analysis in combination with next-generation sequencing, Quantitative Trait Loci (QTL) intervals in five rice chromosomes were mapped that could be associated with YSB resistance at the vegetative phase in a resistant rice line named SM92. Further, multiple SNP markers that showed significant association with YSB resistance in rice chromosomes 1, 5, 10, and 12 were developed. RNA-sequencing of the susceptible and resistant lines revealedseveral genes present in the candidate QTL intervals to be differentially regulated upon YSB infestation. Comparative transcriptome analysis revealed a putative candidate gene that was predicted to encode an alpha-amylase inhibitor. Analysis of the transcriptome and metabolite profiles further revealed a possible link between phenylpropanoid metabolism and YSB resistance. Taken together, our study provides deeper insights into rice-YSB interaction and enhances the understanding of YSB resistance mechanism. Importantly, a promising breeding line and markers for YSB resistance have been developed that can potentially aid in marker-assisted breeding of YSB resistance among elite rice cultivars.

Elucidating the genetic aspect of yellow shoulder disorder in tomato (Solanum lycopersicum) by QTL-seq and linkage mapping

The color and color uniformity of the fruits are of paramount importance to fresh consumption and the tomato processing industry. This is mostly because consumers often associate vibrant and uniform colors with freshness and quality. Yellow shoulder disorder (YSD) characterized by discolored yellow or green sectors on fruit skin is one of the major concerns for tomato producers worldwide since YSD symptoms adversely affect market value and consumer appeal. Therefore, YSD has been studied for a long time, but the genetic aspect of the problem has not been a major focus and hence, it has remained mostly unknown. So, the objective of this research was to identify the genetic components of the YSD. An F2 mapping population was developed and phenotyped for the YSD Visual Score. The F2 plants showing extreme phenotypes were selected and bulks were created. After whole genome sequencing of these bulks, three Quantitative Trait Loci (QTL)s namely YSD1.1 on chromosome 1, YSD3.1 on chromosome 3, and YSD11.1 on chromosome 11 were identified using QTL-seq and traditional linkage mapping. These three QTLs explained approximately 20 % of the phenotypic variation in the F2 mapping population. Further, candidate genes in each QTL interval were identified based on their expression profile and genetic polymorphisms such as single nucleotide polymorphisms (SNPs) and insertions/deletions (INDELs) on genic/intergenic regions. These genes involve in fruit ripening, cell wall modification, lipid metabolism and starch degradation. The present study reports the first QTLs associated with YSD resistance and 17 KASP markers that can be used in marker-assisted selection for YSD in tomato.

QTL mapping for the flag leaf-related traits using RILs derived from Trititrigia germplasm line SN304 and wheat cultivar Yannong15 in multiple environments

BackgroundDeveloping and enriching genetic resources plays important role in the crop improvement. The flag leaf affects plant architecture and contributes to the grain yield of wheat (Triticum aestivum L.). The genetic improvement of flag leaf traits faces problems such as a limited genetic basis. Among the various genetic resources of wheat, Thinopyrum intermedium has been utilized as a valuable resource in genetic improvement due to its disease resistance, large spikes, large leaves, and multiple flowers. In this study, a recombinant inbred line (RIL) population was derived from common wheat Yannong15 and wheat-Th. intermedium introgression line SN304 was used to identify the quantitative trait loci (QTL) for flag leaf-related traits.ResultsQTL mapping was performed for flag leaf length (FLL), flag leaf width (FLW) and flag leaf area (FLA). A total of 77 QTLs were detected, and among these, 51 QTLs with positive alleles were contributed by SN304. Fourteen major QTLs for flag leaf traits were detected on chromosomes 2B, 3B, 4B, and 2D. Additionally, 28 QTLs and 8 QTLs for flag leaf-related traits were detected in low-phosphorus and drought environments, respectively. Based on major QTLs of positive alleles from SN304, we identified a pair of double-ended anchor primers mapped on chromosome 2B and amplified a specific band of Th. intermedium in SN304. Moreover, there was a major colocated QTL on chromosome 2B, called QFll/Flw/Fla-2B, which was delimited to a physical interval of approximately 2.9 Mb and contained 20 candidate genes. Through gene sequence and expression analysis, four candidate genes associated with flag leaf formation and growth in the QTL interval were identified.ConclusionThese results promote the fine mapping of QFll/Flw/Fla-2B, which have pleiotropic effects, and will facilitate the identification of candidate genes for flag leaf-related traits. Additionally, this work provides a theoretical basis for the application of Th. intermedium in wheat breeding.

Meta-QTL analysis reveals the important genomics regions for biotic stresses, nutritional quality and yield related traits in pearl millet

AbstractPearl millet (Cenchrus americanus) is the sixth most significant cereal crop cultivated on 30 million ha and a staple diet for 90 million poor people across the globe. Besides abiotic stresses several biotic stresses have been limiting production of pearl millet in the semi-arid and arid regions. Although, the Quantitative Trait Loci (QTLs) associated with key diseases like blast, rust and downy mildew resistance and nutritional content has been reported, the use of these QTLs is limited in breeding programs. To identify highly stable consensus genomic regions, we conducted Meta-QTL analysis using 191 QTLs reported in 12 independent studies over the last two decades. As a result, we report 34 Meta-QTLs regions on a consensus genetic map comprising of 692 markers and spanning 2070.7 cM. The confidence interval of Meta-QTLs was reduced by 3.63 folds (0.18–7.49 cM), in contrast to projected QTLs interval of 1.11–60.63 cM. Further, a total of 1198 genes were identified in 34 Meta-QTL regions. Among 34 Meta-QTL regions, Meta-QTL1.1 is found to be region of significant importance as it harbours genes for enhanced biotic stress tolerance, plant growth and development as well as genes related with enhanced seed development. Meta-QTL2.4 has highest number of genes with a significant role in disease resistance which contains basic leucine zipper domain, zinc family, leucine rich repeat regions. Meta-QTL3.1 has ABC transporter like activity coupled with the ATPase activity which has a role in Fe and Zn uptake in leaves and root tissues. These Meta-QTL regions can be used in genomics-assisted breeding for enhancing the blast, rust downy mildew resistance as well as yield and nutritional traits.

Mapping QTLs for blight resistance and morpho-phenological traits in inter-species hybrid families of chestnut (Castanea spp.).

Chestnut blight (caused by Cryphonectria parasitica), together with Phytophthora root rot (caused by Phytophthora cinnamomi), has nearly extirpated American chestnut (Castanea dentata) from its native range. In contrast to the susceptibility of American chestnut, many Chinese chestnut (C. mollissima) genotypes are resistant to blight. In this research, we performed a series of genome-wide association studies for blight resistance originating from three unrelated Chinese chestnut trees (Mahogany, Nanking and M16) and a Quantitative Trait Locus (QTL) study on a Mahogany-derived inter-species F2 family. We evaluated trees for resistance to blight after artificial inoculation with two fungal strains and scored nine morpho-phenological traits that are the hallmarks of species differentiation between American and Chinese chestnuts. Results support a moderately complex genetic architecture for blight resistance, as 31 QTLs were found on 12 chromosomes across all studies. Additionally, although most morpho-phenological trait QTLs overlap or are adjacent to blight resistance QTLs, they tend to aggregate in a few genomic regions. Finally, comparison between QTL intervals for blight resistance and those previously published for Phytophthora root rot resistance, revealed five common disease resistance regions on chromosomes 1, 5, and 11. Our results suggest that it will be difficult, but still possible to eliminate Chinese chestnut alleles for the morpho-phenological traits while achieving relatively high blight resistance in a backcross hybrid tree. We see potential for a breeding scheme that utilizes marker-assisted selection early for relatively large effect QTLs followed by genome selection in later generations for smaller effect genomic regions.

Mapping QTL controlling count traits with excess zeros and ones using a zero-and-one-inflated generalized Poisson regression model.

The research on the quantitative trait locus (QTL) mapping of count data has aroused the wide attention of researchers. There are frequent problems in applied research that limit the application of the conventional Poisson model in the analysis of count phenotypes, which include the overdispersion and excess zeros and ones. In this article, a novel model, that is, the zero-and-one-inflated generalized Poisson (ZOIGP) model, is proposed to deal with these problems. Based on the proposed model, a score test is performed for the inflation parameter, in which the ZOIGP model with a constant proportion of excess zeros and ones is compared with a standard generalized Poisson model. To illustrate the practicability of the ZOIGP model, we extend it to the QTL interval mapping application that underpins count phenotype with excess zeros and excess ones. The genetic effects are estimated utilizing the expectation-maximization algorithm embedded with the Newton-Raphson algorithm, and the genome-wide scan and likelihood ratio test is performed to map and test the potential QTLs. The statistical properties exhibited by the proposed method are investigated through simulation. Finally, a real data analysis example is used to illustrate the utility of the proposed method for QTLmapping.

Fine mapping of a major QTL, qKl-1BL controlling kernel length in common wheat.

A major stable QTL, qKl-1BL, for kernel length of wheat was narrowed down to a 2.04-Mb interval on chromosome 1BL; the candidate genes were predicated and the genetic effects on yield-related traits were characterized. As a key factor influencing kernel weight, wheat kernel shape is closely related to yield formation, and in turn affects both wheat processing quality and market value. Fine mapping of the major quantitative trait loci (QTL) for kernel shape could provide genetic resources and a theoretical basis for the genetic improvement of wheat yield-related traits. In this study, a major QTL for kernel length (KL) on 1BL, named qKl-1BL, was identified from the recombinant inbred lines (RIL) in multiple environments based on the genetic map and physical map, with 4.76-21.15% of the phenotypic variation explained. To fine map qKl-1BL, the map-based cloning strategy was used. By using developed InDel markers, the near-isogenic line (NIL) pairs and eight key recombinants were identified from a segregating population containing 3621 individualsderived from residual heterozygous lines (RHLs)self-crossing. In combination with phenotype identification, qKl-1BL was finely positioned into a 2.04-Mb interval, KN1B:698.15-700.19Mb, with eight differentially expressed genes enriched at the key period of kernel elongation. Based on transcriptome analysis and functional annotation information, two candidate genes for qKl-1BL controlling kernel elongation were identified. Additionally, genetic effect analysis showed that the superior allele of qKl-1BL from Jing411 could increase KL, thousand kernel weight (TKW), and yield per plant (YPP) significantly, as well as kernel bulk density and stability time. Taken together, this study identified a QTL interval for controlling kernel length with two possible candidate genes, whichprovides an important basis for qKl-1BL cloning, functional analysis, and application in molecular breeding programs.

Identification of a major QTL and candidate genes analysis for branch angle in rapeseed (Brassica napus L.) using QTL-seq and RNA-seq.

Branching angle is an essential trait in determining the planting density of rapeseed (Brassica napus L.) and hence the yield per unit area. However, the mechanism of branching angle formation in rapeseed is not well understood. In this study, two rapeseed germplasm with extreme branching angles were used to construct an F2 segregating population; then bulked segregant analysis sequencing (BSA-seq) and quantitative trait loci (QTL) mapping were utilized to localize branching anglerelated loci and combined with transcriptome sequencing (RNA-seq) and quantitative real-time PCR (qPCR) for candidate gene mining. A branching angle-associated quantitative trait loci (QTL) was mapped on chromosome C3 (C3: 1.54-2.65 Mb) by combining BSA-seq as well as traditional QTL mapping. A total of 54 genes had SNP/Indel variants within the QTL interval were identified. Further, RNA-seq of the two parents revealed that 12 of the 54 genes were differentially expressed between the two parents. Finally, we further validated the differentially expressed genes using qPCR and found that six of them presented consistent differential expression in all small branching angle samples and large branching angles, and thus were considered as candidate genes related to branching angles in rapeseed. Our results introduce new candidate genes for the regulation of branching angle formation in rapeseed, and provide an important reference for the subsequent exploration of its formation mechanism.

Genome-wide Association Study Identifies Candidate Loci with Major Contributions to the Genetic Control of Pod Morphological Traits in Snap Bean

Snap beans are cultivars of common bean (Phaseolus vulgaris) that are cultivated for their fleshy immature pods that exhibit a wide diversity of pod shapes and sizes. The genetic basis of the snap bean pod shape is complex and involves the interaction of multiple genes. This study used a snap bean diversity panel composed of heirloom and improved cultivars used in North America and genome-wide association studies (GWAS) to investigate the genetic basis of pod morphological characteristics, including length, width, height, width/height ratio, and coefficients of variation (CVs). The GWAS detected multiple genomic regions associated with each pod trait, with a total of 20 quantitative trait loci (QTLs) for pod length, 9 for pod width, 14 for pod height, and 10 for pod width/height ratio. Regarding the CV of each pod trait, genome-wide association analyses detected six QTL for length CVs, five for width CVs, 15 for height CVs, and six for width/height ratio CVs. Thirteen regions in seven chromosomes were associated with two or more pod traits. Eighteen QTLs for pod traits in this study colocated with previously reported QTLs for pod and seed traits. The QTL intervals encompass gene models with homologues in other species that are involved in the control of developmental processes. These results capture the complex nature of the genetic control of snap bean pod traits and confirm the significance of genomic regions harboring overlapping QTLs identified in this and other studies. The phenotypic expression of pod traits in snap bean appears to be under the control of a few genomic regions with a strong effect with additional contributions of multiple small-effect regions. Validation of the function of the candidate genes identified in associated regions will contribute to our understanding of legume pod development.

The MADS-box transcription factor CsAGL9 plays essential roles in seed setting in Camellia sinensis

The number of seed setting (NSS) is an important biological trait that affects tea propagation and yield. In this study, the NSS of an F1 tea population (n = 324) generated via a cross between ‘Longjing 43’ and ‘Baihaozao’ was investigated at two locations in two consecutive years. Quantitative trait locus (QTL) mapping of the NSS was performed, and 10 major QTLs were identified. In total, 318 genes were found in these 10 QTLs intervals, and 11 key candidate genes were preliminarily identified. Among them, the MADS-box transcription factor AGAMOUS LIKE 9 (CsAGL9, CSS0037962) located in the most stable QTL (qNSS2) was identified as a key gene affecting the NSS. CsAGL9 overexpression in Arabidopsis promoted early flowering and significantly decreased the length and number of pods and number of seeds per pod. Transcriptome analysis demonstrated that the auxin pathway, a key hormone pathway regulating plant reproduction, was highly affected in the transgenic lines. The auxin pathway was likewise the most prominent in the gene co-expression network study of CsAGL9 in tea plants. In summary, we identified CsAGL9 is essential for seed setting using QTL mapping integrated with RNA-seq, which shed a new light on the mechanism NSS of seed setting in tea plants.

Identification of major QTLs for seed size by combining QTL-mapping and RNAseq in an electron beam induced mutant of groundnut (Arachis hypogaea L.)

Combining QTL-mapping using SNP markers generated with genotyping by sequencing and RNA-seq identified a major QTL and candidate genes for enhanced seed size and leaf size in groundnut, respectively. Towards this, we conducted quantitative trait locus (QTL) analysis for hundred kernel weight in F2 mapping population derived from electron beam induced large seed mutant, TG 89 and normal seed genotype, ICGV 15007. A major QTL for seed size was identified in Arahy.05 chromosome between flanking markers AhMITE470 and SNP05_103140987. This QTL interval harboured a groundnut ortholog of TIFY gene. Of the 29 TIFY family genes in groundnut, the gene arahy.5M7JWE is the identified within the QTL interval on chromosome A05 and was down regulated in the mutant, indicating its putative role for large seed phenotype in the mutant.

Quantitative trait loci mapping for survival of virus infection and virus levels in honey bees

Israeli acute paralysis virus (IAPV) is a highly virulent, Varroa-vectored virus that is of global concern for honey bee health. Little is known about the genetic basis of honey bees to withstand infection with IAPV or other viruses. We set up and analyzed a backcross between preselected honey bee colonies of low and high IAPV susceptibility to identify quantitative trait loci (QTL) associated with IAPV susceptibility. Experimentally inoculated adult worker bees were surveyed for survival and selectively sampled for QTL analysis based on SNPs identified by whole-genome resequencing and composite interval mapping. Additionally, natural titers of other viruses were quantified in the abdomen of these workers via qPCR and also used for QTL mapping. In addition to the full dataset, we analyzed distinct subpopulations of susceptible and non-susceptible workers separately. These subpopulations are distinguished by a single, suggestive QTL on chromosome 6, but we identified numerous other QTL for different abdominal virus titers, particularly in the subpopulation that was not susceptible to IAPV. The pronounced QTL differences between the susceptible and non-susceptible subpopulations indicate either an interaction between IAPV infection and the bees' interaction with other viruses or heterogeneity among workers of a single cohort that manifests itself as IAPV susceptibility and results in distinct subgroups that differ in their interaction with other viruses. Furthermore, our results indicate that low susceptibility of honey bees to viruses can be caused by both, virus tolerance and virus resistance. QTL were partially overlapping among different viruses, indicating a mixture of shared and specific processes that control viruses. Some functional candidate genes are located in the QTL intervals, but their genomic co-localization with numerous genes of unknown function delegates any definite characterization of the underlying molecular mechanisms to future studies.

QTL mapping of nitrogen use efficiency traits at the seedling and maturity stages under different nitrogen conditions in barley (Hordeum vulgare L.)

AbstractNitrogen (N) is an essential element for plant growth and development. The identification and utilization of N use efficiency (NUE) loci are essential for breeding high NUE cultivars. In this study, 15 NUE traits were measured in a recombinant inbred line population containing 121 lines derived from the cross between a cultivated barley (Baudin) and a wild barley (CN4027). The hydroponic culture was conducted with normal N and low N treatments in one‐time frame, and field trials were conducted with N sufficiency and N deficiency treatments in two growing seasons. Twenty‐two quantitative trait loci (QTLs) and four clusters were detected. Of them, the five stable QTLs Qgna.sau‐3H for grain N concentration, Qtna.sau‐3H for total N accumulation per plant, Qnhi.sau‐3H for N harvest index, Qnutegy.sau‐3H for N utilization efficiency for grain yield and Qanutedm.sau‐3H.1 for N utilization efficiency for aboveground dry matter were co‐located on chromosome 3H flanked by the markers bpb6282426 and bpb4786261. These two novel QTL clusters simultaneously controlled NUE traits at the seedling and maturity stages. Some genes related to NUE traits in intervals of the major QTLs were predicted. The significant relationships between NUE traits and agronomic and physiological traits were detected and discussed. In conclusion, this study uncovers the most promising genomic regions for the marker‐assisted selection of NUE traits to improve NUE in barley.

Transcriptome Analysis and QTL Mapping Identify Candidate Genes and Regulatory Mechanisms Related to Low-Temperature Germination Ability in Maize.

Low-temperature germination ability (LTGA) is an important characteristic for spring sowing maize. However, few maize genes related to LTGA were confirmed, and the regulatory mechanism is less clear. Here, maize-inbred lines Ye478 and Q1 with different LTGA were used to perform transcriptome analysis at multiple low-temperature germination stages, and a co-expression network was constructed by weighted gene co-expression network analysis (WGCNA). Data analysis showed that 7964 up- and 5010 down-regulated differentially expressed genes (DEGs) of Ye478 were identified at low-temperature germination stages, while 6060 up- and 2653 down-regulated DEGs of Q1 were identified. Gene ontology (GO) enrichment analysis revealed that ribosome synthesis and hydrogen peroxide metabolism were enhanced and mRNA metabolism was weakened under low-temperature stress for Ye478, while hydrogen peroxide metabolism was enhanced and mRNA metabolism was weakened for Q1. DEGs pairwise comparisons between the two genotypes found that Ye478 performed more ribosome synthesis at low temperatures compared with Q1. WGCNA analysis based on 24 transcriptomes identified 16 co-expressed modules. Of these, the MEbrown module was highly correlated with Ye478 at low-temperature stages and catalase and superoxide dismutase activity, and the MEred, MEgreen, and MEblack modules were highly correlated with Ye478 across low-temperature stages, which revealed a significant association between LTGA and these modules. GO enrichment analysis showed the MEbrown and MEred modules mainly functioned in ribosome synthesis and cell cycle, respectively. In addition, we conducted quantitative trait loci (QTL) analysis based on a doubled haploid (DH) population constructed by Ye478 and Q1 and identified a major QTL explanting 20.6% of phenotype variance on chromosome 1. In this QTL interval, we found three, four, and three hub genes in the MEbrown, MEred, and MEgreen modules, of which two hub genes (Zm00001d031951, Zm00001d031953) related to glutathione metabolism and one hub gene (Zm00001d031617) related to oxidoreductase activity could be the candidate genes for LTGA. These biological functions and candidate genes will be helpful in understanding the regulatory mechanism of LTGA and the directional improvement of maize varieties for LTGA.

BSA-Seq for the Identification of Major Genes for EPN in Rice.

Improving rice yield is one of the most important food issues internationally. It is an undeniable goal of rice breeding, and the effective panicle number (EPN) is a key factor determining rice yield. Increasing the EPN in rice is a major way to increase rice yield. Currently, the main quantitative trait locus (QTL) for EPN in rice is limited, and there is also limited research on the gene for EPN in rice. Therefore, the excavation and analysis of major genes related to EPN in rice is of great significance for molecular breeding and yield improvement. This study used japonica rice varieties Dongfu 114 and Longyang 11 to construct an F5 population consisting of 309 individual plants. Two extreme phenotypic pools were constructed by identifying the EPN of the population, and QTL-seq analysis was performed to obtain three main effective QTL intervals for EPN. This analysis also helped to screen out 34 candidate genes. Then, EPN time expression pattern analysis was performed on these 34 genes to screen out six candidate genes with higher expression levels. Using a 3K database to perform haplotype analysis on these six genes, we selected haplotypes with significant differences in EPN. Finally, five candidate genes related to EPN were obtained.

Identification of QTL for kernel weight and size and analysis of the pentatricopeptide repeat (PPR) gene family in cultivated peanut (Arachis hypogaea L.)

Peanut (Arachis hypogaea L.) is an important oilseed crop worldwide. Improving its yield is crucial for sustainable peanut production to meet increasing food and industrial requirements. Deciphering the genetic control underlying peanut kernel weight and size, which are essential components of peanut yield, would facilitate high-yield breeding. A high-density single nucleotide polymorphism (SNP)-based linkage map was constructed using a recombinant inbred lines (RIL) population derived from a cross between the variety Yuanza9102 and a germplasm accession wt09-0023. Kernel weight and size quantitative trait loci (QTLs) were co-localized to a 0.16 Mb interval on Arahy07 using inclusive composite interval mapping (ICIM). Analysis of SNP, and Insertion or Deletion (INDEL) markers in the QTL interval revealed a gene encoding a pentatricopeptide repeat (PPR) superfamily protein as a candidate closely linked with kernel weight and size in cultivated peanut. Examination of the PPR gene family indicated a high degree of collinearity of PPR genes between A. hypogaea and its diploid progenitors, Arachis duranensis and Arachis ipaensis. The candidate PPR gene, Arahy.JX1V6X, displayed a constitutive expression pattern in developing seeds. These findings lay a foundation for further fine mapping of QTLs related to kernel weight and size, as well as validation of candidate genes in cultivated peanut.

Identification of stable quantitative trait loci underlying waterlogging tolerance post-anthesis in common wheat (Triticum aestivum)

Waterlogging is a growing threat to wheat production in high-rainfall areas. In this study, a doubled haploid (DH) population developed from a cross between Yangmai 16 (waterlogging-tolerant) and Zhongmai 895 (waterlogging-sensitive) was used to map quantitative trait loci (QTL) for waterlogging tolerance using a high-density 660K single-nucleotide polymorphism (SNP) array. Two experimental designs, waterlogging concrete tank (CT) and waterlogging plastic tank (PT), were used to simulate waterlogging during anthesis in five environments across three growing seasons. Waterlogging significantly decreased thousand-kernel weight (TKW) relative to non-waterlogged controls, although the degree varied across lines. Three QTL for waterlogging tolerance were identified on chromosomes 4AL, 5AS, and 7DL in at least two environments. All favorable alleles were contributed by the waterlogging-tolerant parent Yangmai 16. QWTC.caas-4AL exhibited pleiotropic effects on both enhancing waterlogging tolerance and decreasing plant height. Six high-confidence genes were annotated within the QTL interval. The combined effects of QWTC.caas-4AL and QWTC.caas-5AS greatly improved waterlogging tolerance, while the combined effects of all three identified QTL (QWTC.caas-4AL, QWTC.caas-5AS, and QWTC.caas-7DL) exhibited the most significant effect on waterlogging tolerance. Breeder-friendly kompetitive allele-specific PCR (KASP) markers (K_AX_111523809, K_AX_108971224, and K_AX_110553316) flanking the interval of QWTC.caas-4AL, QWTC.caas-5AS, and QWTC.caas-7DL were produced. These markers were tested in a collection of 240 wheat accessions, and three superior polymorphisms of the markers distributed over 67 elite cultivars in the test population, from the Chinese provinces of Jiangsu, Anhui, and Hubei. The three KASP markers could be used for marker-assisted selection (MAS) to improve waterlogging tolerance in wheat.

Mapping and Identifying Candidate Genes Enabling Cadmium Accumulation in Brassica napus Revealed by Combined BSA-Seq and RNA-Seq Analysis.

Rapeseed has the ability to absorb cadmium in the roots and transfer it to aboveground organs, making it a potential species for remediating soil cadmium (Cd) pollution. However, the genetic and molecular mechanisms underlying this phenomenon in rapeseed are still unclear. In this study, a 'cadmium-enriched' parent, 'P1', with high cadmium transport and accumulation in the shoot (cadmium root: shoot transfer ratio of 153.75%), and a low-cadmium-accumulation parent, 'P2', (with a cadmium transfer ratio of 48.72%) were assessed for Cd concentration using inductively coupled plasma mass spectrometry (ICP-MS). An F2 genetic population was constructed by crossing 'P1' with 'P2' to map QTL intervals and underlying genes associated with cadmium enrichment. Fifty extremely cadmium-enriched F2 individuals and fifty extremely low-accumulation F2 individuals were selected based on cadmium content and cadmium transfer ratio and used for bulk segregant analysis (BSA) in combination with whole genome resequencing. This generated a total of 3,660,999 SNPs and 787,034 InDels between these two segregated phenotypic groups. Based on the delta SNP index (the difference in SNP frequency between the two bulked pools), nine candidate Quantitative trait loci (QTLs) from five chromosomes were identified, and four intervals were validated. RNA sequencing of 'P1' and 'P2' in response to cadmium was also performed and identified 3502 differentially expressed genes (DEGs) between 'P1' and 'P2' under Cd treatment. Finally, 32 candidate DEGs were identified within 9 significant mapping intervals, including genes encoding a glutathione S-transferase (GST), a molecular chaperone (DnaJ), and a phosphoglycerate kinase (PGK), among others. These genes are strong candidates for playing an active role in helping rapeseed cope with cadmium stress. Therefore, this study not only sheds new light on the molecular mechanisms of Cd accumulation in rapeseed but could also be useful for rapeseed breeding programs targeting this trait.