Genetic effects on the skin methylome in healthy older twins.

Whole-skin DNA methylation variation has been implicated in several diseases, including melanoma, but its genetic basis has not yet been fully characterized. Using bulk skin tissue samples from 414 healthy female UK twins, we performed twin-based heritability and methylation quantitative trait loci (meQTL) analyses for >400,000 DNA methylation sites. We find that the human skin DNA methylome is on average less heritable than previously estimated in blood and other tissues (mean heritability: 10.02%). meQTL analysis identified local genetic effects influencing DNA methylation at 18.8% (76,442) of tested CpG sites, as well as 1,775 CpG sites associated with at least one distal genetic variant. As a functional follow-up, we performed skin expression QTL (eQTL) analyses in a partially overlapping sample of 604 female twins. Colocalization analysis identified over 3,500 shared genetic effects affecting thousands of CpG sites (10,067) and genes (4,475). Mediation analysis of putative colocalized gene-CpG pairs identified 114 genes with evidence for eQTL effects being mediated by DNA methylation in skin, including in genes implicating skin disease such as ALOX12 and CSPG4. We further explored the relevance of skin meQTLs to skin disease and found that skin meQTLs and CpGs under genetic influence were enriched for multiple skin-related genome-wide and epigenome-wide association signals, including for melanoma and psoriasis. Our findings give insights into the regulatory landscape of epigenomic variation in skin.

Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content.

To counter the rising incidence of diabetes and to meet the daily protein needs, we created low glycemic index (GI) rice varieties with protein content (PC) surpassing 14%. In the development of recombinant inbred lines using Samba Mahsuri and IR36 amylose extender (IR36ae) as parental lines, we identified quantitative trait loci and genes associated with low GI, high amylose content (AC), and high PC. By integrating genetic techniques with classification models, this comprehensive approach identified candidate genes on chromosome 2 (qGI2.1/qAC2.1 spanning the region from 18.62 Mb to 19.95 Mb), exerting influence on low GI and high amylose. Notably, the phenotypic variant with high value was associated with the recessive allele of the starch branching enzyme 2b (sbeIIb). The genome-edited sbeIIb line confirmed low GI phenotype in milled rice grains. Further, combinations of alleles created by the highly significant SNPs from the targeted associations and epistatically interacting genes showed ultralow GI phenotypes with high amylose and high protein. Metabolomics analysis of rice with varying AC, PC, and GI revealed that the superior lines of high AC and PC, and low GI were preferentially enriched in glycolytic and amino acid metabolisms, whereas the inferior lines of low AC and PC and high GI were enriched with fatty acid metabolism. The high amylose high protein recombinant inbred line (HAHP_101) was enriched in essential amino acids like lysine. Such lines may be highly relevant for food product development to address diabetes and malnutrition.

Genome-wide association study of trace elements in maize kernels.

Maize (Zea mays L.), a staple food and significant economic crop, is enriched with riboflavin, micronutrients and other compounds that are beneficial for human health. As emphasis on the nutritional quality of crops increases maize research has expanded to focus on both yield and quality. This study exploreed the genetic factors influencing micronutrient levels in maize kernels through a comprehensive genome-wide association study (GWAS). We utilized a diverse panel of 244 inbred maize lines and approximately 3 million single nucleotide polymorphisms (SNPs) to investigate the accumulation of essential and trace elements including cadmium (Cd), cobalt (Co), copper (Cu), nickel (Ni), selenium (Se) and zinc (Zn). Our analysis identified 842 quantitative trait loci (QTLs), with 12 QTLs shared across multiple elements and pinpointed 524 potential genes within a 100 kb radius of these QTLs. Notably ZmHMA3 has emerged as a key candidate gene previously reported to influence the Cd accumulation. We highlighted ten pivotal genes associated with trace element transport including those encoding heavy metal ATPases, MYB transcription factors, ABC transporters and other crucial proteins involved in metal handling. Additionally, haplotype analysis revealed that eight inbred linesaccumulated relatively high levels of beneficial elements while harmful elements were minimized. These findings elucidate the genetic mechanisms underlying trace element accumulation in maize kernels and provide a foundation for the breeding of nutritionally enhanced maize varieties.

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

BACKGROUND: Developing 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. RESULTS: QTL 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. CONCLUSION: These 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.

Ustilaginoidea virens, an emerging pathogen of rice: the dynamic interplay between the pathogen virulence strategies and host defense.

MAIN CONCLUSION: The Ustilaginoidea virens -rice pathosystem has been used as a model for flower-infecting fungal pathogens. The molecular biology of the interactions between U. virens and rice, with an emphasis on the attempt to get a deeper comprehension of the false smut fungus's genomes, proteome, host range, and pathogen biology, has been investigated. Meta-QTL analysis was performed to identify potential QTL hotspots for use in marker-assisted breeding. The Rice False Smut (RFS) caused by the fungus Ustilaginoidea virens currently threatens rice cultivators across the globe. RFS infects rice panicles, causing a significant reduction in grain yield. U. virens can also parasitize other hosts though they play only a minor role in its life cycle. Furthermore, because it produces mycotoxins in edible rice grains, it puts both humans and animals at risk of health problems. Although fungicides are used to control the disease, some fungicides have enabled the pathogen to develop resistance, making its management challenging. Several QTLs have been reported but stable gene(s) that confer RFS resistance have not been discovered yet. This review offers a comprehensive overview of the pathogen, its virulence mechanisms, the genome and proteome of U. virens, and its molecular interactions with rice. In addition, information has been compiled on reported resistance QTLs, facilitating the development of a consensus genetic map using meta-QTL analysis for identifying potential QTL hotspots. Finally, this review highlights current developments and trends in U. virens-rice pathosystem research while identifying opportunities for future investigations.

A compressed variance component mixed model framework for detecting small and linked QTL-by-environment interactions.

Detecting small and linked quantitative trait loci (QTLs) and QTL-by-environment interactions (QEIs) for complex traits is a difficult issue in immortalized F2 and F2:3 design, especially in the era of global climate change and environmental plasticity research. Here we proposed a compressed variance component mixed model. In this model, a parametric vector of QTL genotype and environment combination effects replaced QTL effects, environmental effects and their interaction effects, whereas the combination effect polygenic background replaced the QTL and QEI polygenic backgrounds. Thus, the number of variance components in the mixed model was greatly reduced. The model was incorporated into our genome-wide composite interval mapping (GCIM) to propose GCIM-QEI-random and GCIM-QEI-fixed, respectively, under random and fixed models of genetic effects. First, potentially associated QTLs and QEIs were selected from genome-wide scanning. Then, significant QTLs and QEIs were identified using empirical Bayes and likelihood ratio test. Finally, known and candidate genes around these significant loci were mined. The new methods were validated by a series of simulation studies and real data analyses. Compared with ICIM, GCIM-QEI-random had 29.77 ± 18.20% and 24.33 ± 10.15% higher average power, respectively, in 0.5-3.0% QTL and QEI detection, 43.44 ± 9.53% and 51.47 ± 15.70% higher average power, respectively, in linked QTL and QEI detection, and identified 30 more known genes for four rice yield traits, because GCIM-QEI-random identified more small genes/loci, being 2.69 ± 2.37% for additional genes. GCIM-QEI-random was slightly better than GCIM-QEI-fixed. In addition, the new methods may be extended into backcross and genome-wide association studies. This study provides effective methods for detecting small-effect and linked QTLs and QEIs.

Deciphering temporal growth patterns in maize: integrative modeling of phenotype dynamics and underlying genomic variations.

Quantifying the temporal or longitudinal growth dynamics of crops in diverse environmental conditions is crucial for understanding plant development, requiring further modeling techniques. In this study, we analyzed the growth patterns of two different maize (Zea mays L.) populations using high-throughput phenotyping with a maize population consisting of 515 recombinant inbred lines (RILs) grown in Texas and a hybrid population containing 1090 hybrids grown in Missouri. Two models, Gaussian peak and functional principal component analysis (FPCA), were employed to study the Normalized Green-Red Difference Index (NGRDI) scores. The Gaussian peak model showed strong correlations (c. 0.94 for RILs and c. 0.97 for hybrids) between modeled and non-modeled temporal trajectories. Functional principal component analysis differentiated NGRDI trajectories in RILs under different conditions, capturing substantial variability (75%, 20%, and 5% for RILs; 88% and 12% for hybrids). By comparing these models with conventional BLUP values, common quantitative trait loci (QTLs) were identified, containing candidate genes of brd1, pin11, zcn8 and rap2. The harmony between these loci's additive effects and growing degree days, as well as the differentiation of RIL haplotypes across growth stages, underscores the significant interplay of these loci in driving plant development. These findings contribute to advancing understanding of plant-environment interactions and have implications for crop improvement strategies.

Grain yield trade-offs in spike-branching wheat can be mitigated by elite alleles affecting sink capacity and post-anthesis source activity.

Introducing variations in inflorescence architecture, such as the 'Miracle-Wheat' (Triticum turgidum convar. compositum (L.f.) Filat.) with a branching spike, has relevance for enhancing wheat grain yield. However, in the spike-branching genotypes, the increase in spikelet number is generally not translated into grain yield advantage because of reduced grains per spikelet and grain weight. Here, we investigated if such trade-offs might be a function of source-sink strength by using 385 recombinant inbred lines developed by intercrossing the spike-branching landrace TRI 984 and CIRNO C2008, an elite durum (T. durum L.) cultivar; they were genotyped using the 25K array. Various plant and spike architectural traits, including flag leaf, peduncle, and spike senescence rate, were phenotyped under field conditions for 2 consecutive years. On chromosome 5AL, we found a new modifier QTL for spike branching, branched headt3 (bht-A3), which was epistatic to the previously known bht-A1 locus. Besides, bht-A3 was associated with more grains per spikelet and a delay in flag leaf senescence rate. Importantly, favourable alleles, viz. bht-A3 and grain protein content (gpc-B1) that delayed senescence, are required to improve grain number and grain weight in the spike-branching genotypes. In summary, achieving a balanced source-sink relationship might minimize grain yield trade-offs in Miracle-Wheat.

Mapping and candidate gene analysis of QTLs for grain shape in a rice chromosome segment substitution line Z485 and breeding of SSSLs.

Grain shape is one of the most important factors that affects rice yield. Cloning novel grain shape genes and analyzing their genetic mechanisms are crucial for high yield breeding. In this study, a slender grain CSSL-Z485 with 3-segments substitution in the genetic background of Nipponbare was constructed in rice. Cytological analysis showed that the longer grain length of Z485 was related to the increase in glume cell numbers, while the narrower grain width was associated with the decrease in cell width. Three grain shape-related quantitative trait locus (QTLs), including qGL12, qGW12, and qRLW12, were identified through the F2 population constructed from a cross between Nipponbare and Z485. Furthermore, four single segment substitution lines (SSSLs, S1-S4) carrying the target QTLs were dissected from Z485 by MAS. Finally, three candidate genes of qGL12 for grain length and qGW12 for grain width located in S3 were confirmed by DNA sequencing, RT-qPCR, and protein structure prediction. Specifically, candidate gene 1 encodes a ubiquitin family protein, while candidate genes 2 and 3 encode zinc finger proteins. The results provide valuable germplasm resources for cloning novel grain shape genes and molecular breeding by design. Supplementary information: The online version contains supplementary material available at 10.1007/s11032-024-01480-x.

QTL Mapping for Adult-Plant Resistance to Leaf Rust in Italian Wheat Cultivar Libellula.

Wheat leaf rust (Lr), which is caused by Puccinia triticina Eriks. (Pt), is one of the most important wheat diseases affecting wheat production globally. Using resistant wheat cultivars is the most economical and environmentally friendly way to control leaf rust. The Italian wheat cultivar Libellula has demonstrated good resistance to Lr in field studies. To identify the genetic basis of Lr resistance in 'Libellula', 248 F6 recombinant inbred lines from the cross 'Libellula'/'Huixianhong' was phenotyped for Lr severity in seven environments: the 2014/2015, 2016/2017, 2017/2018, and 2018/2019 cropping seasons at Baoding, Hebei Province, and the 2016/2017, 2017/2018, and 2018/2019 crop seasons at Zhoukou, Henan Province. Bulked segregant analysis and simple sequence repeat markers were then used to identify the quantitative trait loci (QTLs) for Lr adult-plant resistance in the population. Six QTLs were consequently detected and designated as QLr.hebau-1AL and QLr.hebau-1AS that were presumed to be new and QLr.hebau-1BL, QLr.hebau-3AL, QLr.hebau-4BL, and QLr.hebau-7DS that were identified at similar physical positions as previously reported QTLs. Based on chromosome positions and molecular marker tests, QLr.hebau-1BL and QLr.hebau-7DS share similar flanking markers with Lr46 and Lr34, respectively. Lr46 and Lr34 are race nonspecific adult plant resistance (APR) genes for leaf rust and stripe rust and powdery mildew. QLr.hebau-4BL showed multiple disease resistance to leaf rust, stripe rust, Fusarium head blight, and powdery mildew. The QTL identified in this study, as well as their closely linked markers, may potentially be used in marker-assisted selection in wheat breeding.

RNA-Seq Bulked Segregant Analysis of an Exotic B. napus ssp. napobrassica (Rutabaga) F2 Population Reveals Novel QTLs for Breeding Clubroot-Resistant Canola.

In this study, a rutabaga (Brassica napus ssp. napobrassica) donor parent FGRA106, which exhibited broad-spectrum resistance to 17 isolates representing 16 pathotypes of Plasmodiophora brassicae, was used in genetic crosses with the susceptible spring-type canola (B. napus ssp. napus) accession FG769. The F2 plants derived from a clubroot-resistant F1 plant were screened against three P. brassicae isolates representing pathotypes 3A, 3D, and 3H. Chi-square (χ2) goodness-of-fit tests indicated that the F2 plants inherited two major clubroot resistance genes from the CR donor FGRA106. The total RNA from plants resistant (R) and susceptible (S) to each pathotype were pooled and subjected to bulked segregant RNA-sequencing (BSR-Seq). The analysis of gene expression profiles identified 431, 67, and 98 differentially expressed genes (DEGs) between the R and S bulks. The variant calling method indicated a total of 12 (7 major + 5 minor) QTLs across seven chromosomes. The seven major QTLs included: BnaA5P3A.CRX1.1, BnaC1P3H.CRX1.2, and BnaC7P3A.CRX1.1 on chromosomes A05, C01, and C07, respectively; and BnaA8P3D.CRX1.1, BnaA8P3D.RCr91.2/BnaA8P3H.RCr91.2, BnaA8P3H.Crr11.3/BnaA8P3D.Crr11.3, and BnaA8P3D.qBrCR381.4 on chromosome A08. A total of 16 of the DEGs were located in the major QTL regions, 13 of which were on chromosome C07. The molecular data suggested that clubroot resistance in FGRA106 may be controlled by major and minor genes on both the A and C genomes, which are deployed in different combinations to confer resistance to the different isolates. This study provides valuable germplasm for the breeding of clubroot-resistant B. napus cultivars in Western Canada.

High-Density Genetic Map Construction and Quantitative Trait Locus Analysis of Fruit- and Oil-Related Traits in Camellia oleifera Based on Double Digest Restriction Site-Associated DNA Sequencing.

Camellia oleifera, an important tree species and source of edible oil in China, has received significant attention owing to the oil's high unsaturated fatty acid content, which has benefits for human health. However, the mechanisms underlying C. oleifera yield and oil quality are largely unknown. In this study, 180 F1 progenies were obtained from two parents with obvious differences in fruit- and oil-related traits. We constructed a high-density genetic map using a double digest restriction site-associated DNA sequencing (ddRAD-Seq) strategy in C. oleifera. This map spanned 3327 cM and anchored 2780 markers in 15 linkage groups (LGs), with an average marker interval of 1.20 cM. A total of 221 quantitative trait loci (QTLs) associated with fruit- and oil-related traits were identified across three years' worth of phenotypic data. Nine QTLs were detected simultaneously in at least two different years, located on LG02, LG04, LG05, LG06, and LG11, and explained 8.5-16.6% of the phenotypic variation in the corresponding traits, respectively. Seventeen major QTLs were obtained that explained 13.0-16.6% of the phenotypic variance. Eleven and five flanking SNPs of major QTLs for fruit- and oil-related traits were detected which could be used for marker-assisted selection in C. oleifera breeding programs. Furthermore, 202 potential candidate genes in QTL regions were identified based on the collinearity of the genetic map and the C. oleifera "CON" genome. A potential regulatory network controlling fruit development and oil biosynthesis was constructed to dissect the complex mechanism of oil accumulation. The dissection of these QTLs will facilitate the gene cloning underlying lipid synthesis and increase our understanding in order to enhance C. oleifera oil yield and quality.

Fine mapping of interspecific secondary CSSL populations revealed key regulators for grain weight at qTGW3.1 locus from Oryza nivara.

Grain weight (GW) is the most important stable trait that directly contributes to crop yield in case of cereals. A total of 105 backcross introgression lines (BC2F10 BILs) derived from Swarna/O. nivara IRGC81848 (NPS) and 90 BILs from Swarna/O. nivara IRGC81832 (NPK) were evaluated for thousand-grain weight (TGW) across four years (wet seasons 2014, 2015, 2016 and 2018) and chromosome segment substitution lines (CSSLs) were selected. From significant pair- wise mean comparison with Swarna, a total of 77 positively and 29 negatively significant NPS lines and 62 positively and 29 negatively significant NPK lines were identified. In all 4 years, 14 NPS lines and 9 NPK lines were positively significant and one-line NPS69 (IET22161) was negatively significant for TGW over Swarna consistently. NPS lines and NPK lines were genotyped using 111 and 140 polymorphic SSRs respectively. Quantitative trait locus (QTL) mapping using ICIM v4.2 software showed 13 QTLs for TGW in NPS. Three major effect QTLs qTGW2.1, qTGW8.1 and qTGW11.1 were identified in NPS for two or more years with PVE ranging from 8 to 14%. Likewise, 10 QTLs were identified in NPK and including two major effect QTL qTGW3.1 and qTGW12.1 with 6 to 32% PVE. In all QTLs, O. nivara alleles increased TGW. These consistent QTLs are very suitable for fine mapping and functional analysis of grain weight. Further in this study, CSSLs NPS1 (10-2S) and NPK61 (158 K) with significantly higher grain weight than the recurrent parent, Swarna cv. Oryza sativa were selected from each population and secondary F2 mapping populations were developed. Using Bulked Segregant QTL sequencing, a grain weight QTL, designated as qTGW3.1 was fine mapped from the cross between NPK61 and Swarna. This QTL explained 48% (logarithm of odds = 32.2) of the phenotypic variations and was fine mapped to a 31 kb interval using recombinant analysis. GRAS transcription factor gene (OS03go103400) involved in plant growth and development located at this genomic locus might be the candidate gene for qTGW3.1. The results of this study will help in further functional studies and improving the knowledge related to the molecular mechanism of grain weight in Oryza and lays a solid foundation for the breeding for high yield. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01483-0.

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 Multiple Genetic Loci Related to Low-Temperature Tolerance during Germination in Maize (Zea maize L.) through a Genome-Wide Association Study.

Low-temperature stress during the germination stage is an important abiotic stress that affects the growth and development of northern spring maize and seriously restricts maize yield and quality. Although some quantitative trait locis (QTLs) related to low-temperature tolerance in maize have been detected, only a few can be commonly detected, and the QTL intervals are large, indicating that low-temperature tolerance is a complex trait that requires more in-depth research. In this study, 296 excellent inbred lines from domestic and foreign origins (America and Europe) were used as the study materials, and a low-coverage resequencing method was employed for genome sequencing. Five phenotypic traits related to low-temperature tolerance were used to assess the genetic diversity of maize through a genome-wide association study (GWAS). A total of 14 SNPs significantly associated with low-temperature tolerance were detected (-log10(P) > 4), and an SNP consistently linked to low-temperature tolerance in the field and indoors during germination was utilized as a marker. This SNP, 14,070, was located on chromosome 5 at position 2,205,723, which explained 4.84-9.68% of the phenotypic variation. The aim of this study was to enrich the genetic theory of low-temperature tolerance in maize and provide support for the innovation of low-temperature tolerance resources and the breeding of new varieties.

Mapping QTLs for Super-Earliness and Agro-Morphological Traits in RILs Population Derived from Interspecific Crosses between Pisum sativum × P. fulvum.

Earliness in crop plants has a vital role in prevention of heat-induced drought stress and in combating global warming, which is predicted to exacerbate in the near future. Furthermore, earliness may expand production into northern areas or higher altitudes, having relatively shorter growing season and may also expand arable lands to meet global food demands. The primary objective of the present study was to investigate quantitative trait loci (QTLs) for super-earliness and important agro-morphological traits in a recombinant inbred line (RIL) population derived from an interspecific cross. A population of 114 RILs developed through single-seed descent from an interspecific cross involving Pisum sativum L. and P. fulvum Sibth. et Sm. was evaluated to identify QTLs for super-earliness and important agro-morphological traits. A genetic map was constructed with 44 SSRs markers representing seven chromosomes with a total length of 262.6 cM. Of the 14 QTLs identified, two were for super-earliness on LG2, one for plant height on LG3, six for number of pods per plant on LG2, LG4, LG5 and LG6, one for number of seeds per pod on LG6, one for pod length on LG4 and three for harvest index on LG3, LG5, and LG6. AA205 and AA372-1 flanking markers for super-earliness QTLs were suggested for marker-assisted selection (MAS) in pea breeding programs due to high heritability of the trait. This is the first study to map QTLs originating from P. sativum and P. fulvum recently identified species with super-earliness character and the markers (AA205 and AA372-1) linked to QTLs were valuable molecular tools for pea breeding.

Metabolic-GWAS provides insights into genetic architecture of seed metabolome in buckwheat.

BACKGROUND: Buckwheat (Fagopyrum spp.), belonging to the Polygonaceae family, is an ancient pseudo-cereal with high nutritional and nutraceutical properties. Buckwheat proteins are gluten-free and show balanced amino acid and micronutrient profiles, with higher content of health-promoting bioactive flavonoids that make it a golden crop of the future. Plant metabolome is increasingly gaining importance as a crucial component to understand the connection between plant physiology and environment and as a potential link between the genome and phenome. However, the genetic architecture governing the metabolome and thus, the phenome is not well understood. Here, we aim to obtain a deeper insight into the genetic architecture of seed metabolome in buckwheat by integrating high throughput metabolomics and genotyping-by-sequencing applying an array of bioinformatics tools for data analysis. RESULTS: High throughput metabolomic analysis identified 24 metabolites in seed endosperm of 130 diverse buckwheat genotypes. The genotyping-by-sequencing (GBS) of these genotypes revealed 3,728,028 SNPs. The Genome Association and Prediction Integrated Tool (GAPIT) assisted in the identification of 27 SNPs/QTLs linked to 18 metabolites. Candidate genes were identified near 100 Kb of QTLs, providing insights into several metabolic and biosynthetic pathways. CONCLUSIONS: We established the metabolome inventory of 130 germplasm lines of buckwheat, identified QTLs through marker trait association and positions of potential candidate genes. This will pave the way for future dissection of complex economic traits in buckwheat.

Mapping of QTLs and meta-QTLs for Heterodera avenae Woll. resistance in common wheat (Triticum aestivum L.).

BACKGROUND: In hexaploid wheat, quantitative trait loci (QTL) and meta-QTL (MQTL) analyses were conducted to identify genomic regions controlling resistance to cereal cyst nematode (CCN), Heterodera avenae. A mapping population comprising 149 RILs derived from the cross HUW 468 × C 306 was used for composite interval mapping (CIM) and inclusive composite interval mapping (ICIM). RESULTS: Eight main effect QTLs on three chromosomes (1B, 2A and 3A) were identified using two repeat experiments. One of these QTLs was co-localized with a previously reported wheat gene Cre5 for resistance to CCN. Seven important digenic epistatic interactions (PVE = 5% or more) were also identified, each involving one main effect QTL and another novel E-QTL. Using QTLs earlier reported in literature, two meta-QTLs were also identified, which were also used for identification of 57 candidate genes (CGs). Out of these, 29 CGs have high expression in roots and encoded the following proteins having a role in resistance to plant parasitic nematodes (PPNs): (i) NB-ARC,P-loop containing NTP hydrolase, (ii) Protein Kinase, (iii) serine-threonine/tyrosine-PK, (iv) protein with leucine-rich repeat, (v) virus X resistance protein-like, (vi) zinc finger protein, (vii) RING/FYVE/PHD-type, (viii) glycosyl transferase, family 8 (GT8), (ix) rubisco protein with small subunit domain, (x) protein with SANT/Myb domain and (xi) a protein with a homeobox. CONCLUSION: Identification and selection of resistance loci with additive and epistatic effect along with two MQTL and associated CGs, identified in the present study may prove useful for understanding the molecular basis of resistance against H. avenae in wheat and for marker-assisted selection (MAS) for breeding CCN resistant wheat cultivars.

Quantitative trait loci mapping of polyphenol metabolites from a 'Latham' x 'Glen Moy' red raspberry (Rubus idaeus L) cross.

OBJECTIVE: The objective of this study was to investigate the genetic control of polyphenol accumulation in red raspberry (Rubus idaeus L). METHODS: The levels of total anthocyanins and 37 individual polyphenol metabolites were measured over three years in a raspberry biparental mapping population. Quantitative trait loci (QTLs) for these traits were mapped onto a high-density SNP linkage map. RESULTS: At least one QTL was detected for each trait, with good consistency among the years. On four linkage groups (LG), there were major QTLs affecting several metabolites. On LG1, a QTL had large effects on anthocyanins and flavonols containing a rutinoside or rhamnose group. On LG4, a QTL had large effects on several flavonols and on LG5 and LG6 QTLs had large effects on ellagic acid derivatives. Smaller QTLs were found on LG2 and LG3. CONCLUSION: The identification of robust QTLs for key polyphenols in raspberry provides great potential for marker-assisted breeding for improved levels of potentially health beneficial components.

Linkage and association mapping of ovule number per ovary (ON) in oilseed rape (Brassica napus L.).

Ovule number (ON) produced during flower development determines the maximum number of seeds per silique and thereby affects crop productivity; however, the genetic basis of ON remains poorly understood in oilseed rape (Brassica napus). In this study, we genetically dissected the ON variations in a double haploid (DH) population and in natural population (NP) by linkage mapping and genome-wide association analysis. Phenotypic analysis showed that ON displayed normal distribution in both populations with the broad-sense heritability of 0.861 (DH population) and 0.930 (natural population). Linkage mapping identified 5 QTLs related to ON, including qON-A03, qON-A07, qON-A07-2, qON-A10, and qON-C06. Genome-wide association studies (GWAS) revealed 214, 48, and 40 significant single-nucleotide polymorphisms (SNPs) by individually using the single-locus model GLM and the multiple-locus model MrMLM and FASTMrMLM. The phenotypic variation explained (PVE) by these QTLs and SNPs ranged from 2.00-17.40% to 5.03-7.33%, respectively. Integration of the results from both strategies identified four consensus genomic regions associated with ON from the chromosomes A03, A07, and A10. Our results preliminarily resolved the genetic basis of ON and provides useful molecular markers for plant yield improvement in B. napus. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01355-7.