Validation and identification of promising gene specific markers governing foliar disease resistance in groundnut (Arachis hypogaea L.).

BACKGROUND: Groundnut is vulnerable to the major foliar fungal disease viz., late leaf spot (LLS) and rust in kharif season, which results in severe yield losses. Until now, LLS and rust resistance linked markers were developed based on GPBD 4 as a major donor source and were validated in its derivatives only, which restricted their use in marker assisted selection (MAS) involving other donors. METHODS AND RESULTS: The current study focused to validate LLS and rust resistance linked markers employing advanced breeding lines of F6 generation, derived from nine different crosses involving nine diverse parents, to identify potential markers for marker-assisted breeding of LLS and rust resistance in groundnut. Out of 28-trait linked markers used for validation, 8 were polymorphic (28.57%). Marker-trait association (MTA) and Single Marker Analysis (SMA) revealed that the SSR marker pPGPseq5D05 is significantly associated with both LLS (15.8% PVE) and rust (17.5% PVE) resistance, whereas, the marker IPAHM103 is tightly linked with rust resistance (26.8% PVE) alone. In silico analysis revealed that the marker gene for IPAHM103 is a zinc finger protein and the marker gene for pPGPseq5D05 is an ADP-ribosylation factor GTPase-activating protein. Both these protein products impart resistance or tolerance to biotic stress in crop plants. Two other markers namely, GMLQ975 and pPGPseq13A10 were also found to be associated with LLS resistance explaining MTA up to 60%. CONCLUSION: These gene specific markers will enable us to screen more number of germplasm lines or newly developed lines in MAS schemes for LLS and rust resistance using a wide range of resistant sources.

Single-cell and genome-wide Mendelian randomization identifies causative genes for gout.

BACKGROUND: Gout is a prevalent manifestation of metabolic osteoarthritis induced by elevated blood uric acid levels. The purpose of this study was to investigate the mechanisms of gene expression regulation in gout disease and elucidate its pathogenesis. METHODS: The study integrated gout genome-wide association study (GWAS) data, single-cell transcriptomics (scRNA-seq), expression quantitative trait loci (eQTL), and methylation quantitative trait loci (mQTL) data for analysis, and utilized two-sample Mendelian randomization study to comprehend the causal relationship between proteins and gout. RESULTS: We identified 17 association signals for gout at unique genetic loci, including four genes related by protein-protein interaction network (PPI) analysis: TRIM46, THBS3, MTX1, and KRTCAP2. Additionally, we discerned 22 methylation sites in relation to gout. The study also found that genes such as TRIM46, MAP3K11, KRTCAP2, and TM7SF2 could potentially elevate the risk of gout. Through a Mendelian randomization (MR) analysis, we identified three proteins causally associated with gout: ADH1B, BMP1, and HIST1H3A. CONCLUSION: According to our findings, gout is linked with the expression and function of particular genes and proteins. These genes and proteins have the potential to function as novel diagnostic and therapeutic targets for gout. These discoveries shed new light on the pathological mechanisms of gout and clear the way for future research on this condition.

Bayesian genome-wide TWAS with reference transcriptomic data of brain and blood tissues identified 141 risk genes for Alzheimer's disease dementia.

BACKGROUND: Transcriptome-wide association study (TWAS) is an influential tool for identifying genes associated with complex diseases whose genetic effects are likely mediated through transcriptome. TWAS utilizes reference genetic and transcriptomic data to estimate effect sizes of genetic variants on gene expression (i.e., effect sizes of a broad sense of expression quantitative trait loci, eQTL). These estimated effect sizes are employed as variant weights in gene-based association tests, facilitating the mapping of risk genes with genome-wide association study (GWAS) data. However, most existing TWAS of Alzheimer's disease (AD) dementia are limited to studying only cis-eQTL proximal to the test gene. To overcome this limitation, we applied the Bayesian Genome-wide TWAS (BGW-TWAS) method to leveraging both cis- and trans- eQTL of brain and blood tissues, in order to enhance mapping risk genes for AD dementia. METHODS: We first applied BGW-TWAS to the Genotype-Tissue Expression (GTEx) V8 dataset to estimate cis- and trans- eQTL effect sizes of the prefrontal cortex, cortex, and whole blood tissues. Estimated eQTL effect sizes were integrated with the summary data of the most recent GWAS of AD dementia to obtain BGW-TWAS (i.e., gene-based association test) p-values of AD dementia per gene per tissue type. Then we used the aggregated Cauchy association test to combine TWAS p-values across three tissues to obtain omnibus TWAS p-values per gene. RESULTS: We identified 85 significant genes in prefrontal cortex, 82 in cortex, and 76 in whole blood that were significantly associated with AD dementia. By combining BGW-TWAS p-values across these three tissues, we obtained 141 significant risk genes including 34 genes primarily due to trans-eQTL and 35 mapped risk genes in GWAS Catalog. With these 141 significant risk genes, we detected functional clusters comprised of both known mapped GWAS risk genes of AD in GWAS Catalog and our identified TWAS risk genes by protein-protein interaction network analysis, as well as several enriched phenotypes related to AD. CONCLUSION: We applied BGW-TWAS and aggregated Cauchy test methods to integrate both cis- and trans- eQTL data of brain and blood tissues with GWAS summary data, identifying 141 TWAS risk genes of AD dementia. These identified risk genes provide novel insights into the underlying biological mechanisms of AD dementia and potential gene targets for therapeutics development.

Genetic control of root morphology in response to nitrogen across rapeseed diversity.

Rapeseed (Brassica napus L.) is an oil-containing crop of great economic value but with considerable nitrogen requirement. Breeding root systems that efficiently absorb nitrogen from the soil could be a driver to ensure genetic gains for more sustainable rapeseed production. The aim of this study is to identify genomic regions that regulate root morphology in response to nitrate availability. The natural variability offered by 300 inbred lines was screened at two experimental locations. Seedlings grew hydroponically with low or elevated nitrate levels. Fifteen traits related to biomass production and root morphology were measured. On average across the panel, a low nitrate level increased the root-to-shoot biomass ratio and the lateral root length. A large phenotypic variation was observed, along with important heritability values and genotypic effects, but low genotype-by-nitrogen interactions. Genome-wide association study and bulk segregant analysis were used to identify loci regulating phenotypic traits. The first approach nominated 319 SNPs that were combined into 80 QTLs. Three QTLs identified on the A07 and C07 chromosomes were stable across nitrate levels and/or experimental locations. The second approach involved genotyping two groups of individuals from an experimental F2 population created by crossing two accessions with contrasting lateral root lengths. These individuals were found in the tails of the phenotypic distribution. Co-localized QTLs found in both mapping approaches covered a chromosomal region on the A06 chromosome. The QTL regions contained some genes putatively involved in root organogenesis and represent selection targets for redesigning the root morphology of rapeseed.

Transcriptome-wide association mapping provides insights into the genetic basis and candidate genes governing flowering, maturity and seed weight in rice bean (Vigna umbellata).

BACKGROUND: Rice bean (Vigna umbellata), an underrated legume, adapts to diverse climatic conditions with the potential to support food and nutritional security worldwide. It is used as a vegetable, minor food crop and a fodder crop, being a rich source of proteins, minerals, and essential fatty acids. However, little effort has been made to decipher the genetic and molecular basis of various useful traits in this crop. Therefore, we considered three economically important traits i.e., flowering, maturity and seed weight of rice bean and identified the associated candidate genes employing an associative transcriptomics approach on 100 diverse genotypes out of 1800 evaluated rice bean accessions from the Indian National Genebank. RESULTS: The transcriptomics-based genotyping of one-hundred diverse rice bean cultivars followed by pre-processing of genotypic data resulted in 49,271 filtered markers. The STRUCTURE, PCA and Neighbor-Joining clustering of 100 genotypes revealed three putative sub-populations. The marker-trait association analysis involving various genome-wide association study (GWAS) models revealed significant association of 82 markers on 48 transcripts for flowering, 26 markers on 22 transcripts for maturity and 22 markers on 21 transcripts for seed weight. The transcript annotation provided information on the putative candidate genes for the considered traits. The candidate genes identified for flowering include HSC80, P-II PsbX, phospholipid-transporting-ATPase-9, pectin-acetylesterase-8 and E3-ubiquitin-protein-ligase-RHG1A. Further, the WRKY1 and DEAD-box-RH27 were found to be associated with seed weight. Furthermore, the associations of PIF3 and pentatricopeptide-repeat-containing-gene with maturity and seed weight, and aldo-keto-reductase with flowering and maturity were revealed. CONCLUSION: This study offers insights into the genetic basis of key agronomic traits in rice bean, including flowering, maturity, and seed weight. The identified markers and associated candidate genes provide valuable resources for future exploration and targeted breeding, aiming to enhance the agronomic performance of rice bean cultivars. Notably, this research represents the first transcriptome-wide association study in pulse crop, uncovering the candidate genes for agronomically useful traits.

Unique genetic architecture of prolificacy in 'Sikkim Primitive' maize unraveled through whole-genome resequencing-based DNA polymorphism.

KEY MESSAGE: 'Sikkim Primitive' maize landrace, unique for prolificacy (7-9 ears per plant) possesses unique genomic architecture in branching and inflorescence-related gene(s), and locus Zm00001eb365210 encoding glycosyltransferases was identified as the putative candidate gene underlying QTL (qProl-SP-8.05) for prolificacy. The genotype possesses immense usage in breeding high-yielding baby-corn genotypes. 'Sikkim Primitive' is a native landrace of North Eastern Himalayas, and is characterized by having 7-9 ears per plant compared to 1-2 ears in normal maize. Though 'Sikkim Primitive' was identified in the 1960s, it has not been characterized at a whole-genome scale. Here, we sequenced the entire genome of an inbred (MGUSP101) derived from 'Sikkim Primitive' along with three non-prolific (HKI1128, UMI1200, and HKI1105) and three prolific (CM150Q, CM151Q and HKI323) inbreds. A total of 942,417 SNPs, 24,160 insertions, and 27,600 deletions were identified in 'Sikkim Primitive'. The gene-specific functional mutations in 'Sikkim Primitive' were classified as 10,847 missense (54.36%), 402 non-sense (2.015%), and 8,705 silent (43.625%) mutations. The number of transitions and transversions specific to 'Sikkim Primitive' were 666,021 and 279,950, respectively. Among all base changes, (G to A) was the most frequent (215,772), while (C to G) was the rarest (22,520). Polygalacturonate 4-α-galacturonosyltransferase enzyme involved in pectin biosynthesis, cell-wall organization, nucleotide sugar, and amino-sugar metabolism was found to have unique alleles in 'Sikkim Primitive'. The analysis further revealed the Zm00001eb365210 gene encoding glycosyltransferases as the putative candidate underlying QTL (qProl-SP-8.05) for prolificacy in 'Sikkim Primitive'. High-impact nucleotide variations were found in ramosa3 (Zm00001eb327910) and zeaxanthin epoxidase1 (Zm00001eb081460) genes having a role in branching and inflorescence development in 'Sikkim Primitive'. The information generated unraveled the genetic architecture and identified key genes/alleles unique to the 'Sikkim Primitive' genome. This is the first report of whole-genome characterization of the 'Sikkim Primitive' landrace unique for its high prolificacy.

From darkness to discovery: evolutionary, adaptive, and translational genetic insights from cavefish.

How genotype determines phenotype is a well-explored question, but genotype-environment interactions and their heritable impact on phenotype over the course of evolution are not as thoroughly investigated. The fish Astyanax mexicanus, consisting of surface and cave ecotypes, is an ideal emerging model to study the genetic basis of adaptation to new environments. This model has permitted quantitative trait locus mapping and whole-genome comparisons to identify the genetic bases of traits such as albinism and insulin resistance and has helped to better understand fundamental evolutionary mechanisms. In this review, we summarize recent advances in A. mexicanus genetics and discuss their broader impact on the fields of adaptation and evolutionary genetics.

Identification of soybean mosaic virus strain SC7 resistance loci and candidate genes in soybean [Glycine max (L.) Merr.].

Soybean [Glycine max (L.) Merr.] is an important legume crop worldwide, which provides abundant plant protein and oil for human beings. Soybean mosaic virus (SMV) can cause serious damage to the yield and quality of soybean, but it is difficult to control SMV with chemicals, breeding SMV-resistant varieties has become the most effective way to control the disease. Therefore, it is important to identify SMV resistance genes from soybean resources and apply them to soybean breeding. In this study, the disease rates (DRs) of 219 soybean accessions to SMV strain SC7 in two environments were investigated. A high-density NJAU 355 K SoySNP array was used for genome-wide association study (GWAS) of DR. A 274 kb region on chromosome 15 (1,110,567 bp to 1,384,173 bp) was repeatedly detected in two environments. Six new significant single nucleotide polymorphisms (SNPs) on chromosome 15 were identified. Four of these six SNPs were located within two candidate genes, Glyma.15G015700 and Glyma.15G015800. The elite haplotype Glyma.15G015700Hap I with low DR exhibited strong resistance to SC7. The expression of Glyma.15G015700 in the SMV-resistant accession increased significantly after inoculation with SC7. Furthermore, most of the proteins predicted to interact with Glyma.15G015700 are heat shock proteins, which have been shown to be related to disease resistance. In summary, new SMV resistance loci and a new candidate gene, Glyma.15G015700, were identified and might be utilized in further soybean disease resistance breeding.

Selection of rice breeding lines for resistance to biotic and abiotic stresses.

Rice (Oryza sativa L.) grown in many countries around the world with different climatic conditions and a huge number of environmental stresses, both biotic (fungi, bacteria, viruses, insects) and abiotic (cold, drought, salinity) limit rice productivity. In this regard, breeders and scientists are trying to create rice lines that are resistant to multiple stresses. The aim of this work was to screen and select cold and blast resistant rice breeding lines (RBLs) using molecular markers. Molecular screening of RBLs and parental varieties to cold tolerance was carried out using markers RM24545, RM1377, RM231 and RM569 associated with QTLs (qPSST-3, qPSST-7, qPSST-9). It was discovered that the presence of three QTLs characterizes the cold resistance of studied genotypes, and the absence of one of them leads to cold sensitivity. As a result, 21 cold-resistant out of the 28 studied RBLs were identified. These cold resistant 21 RBLs were further tested to blast resistance using markers Pi-ta, Pita3, Z56592, 195R-1, NMSMPi9-1, TRS26, Pikh MAS, MSM6, 9871.T7E2b, RM224 and RM1233. It was revealed that 16 RBLs from 21 studied lines contain 5-6 blast resistance genes. In accordance with the blast resistance strategy, the presence of 5 or more genes ensures the formation of stable resistance to Magnaporthe oryzae. Thus, 16 lines resistant to multiple stresses, such as cold and blast disease were developed. It should be noted that 6 of these selected lines are high-yielding, which is very important in rice breeding program. These RBLs can be used in breeding process as starting lines, germplasm exchange as a source of resistant genes for the development of new rice varieties resistant to multiple stress factors.

Construction of high-density genetic map based on SLAF-seq and QTL analysis of major traits in sweetpotato [Ipomoea batatas (L.) Lam.].

Sweetpotato, Ipomoea batatas (L.) Lam., is an important worldwide crop used as feed, food, and fuel. However, its polyploidy, high heterozygosity and self-incompatibility makes it difficult to study its genetics and genomics. Longest vine length (LVL), yield per plant (YPP), dry matter content (DMC), starch content (SC), soluble sugar content (SSC), and carotenoid content (CC) are some of the major agronomic traits being used to evaluate sweetpotato. However limited research has actually examined how these traits are inherited. Therefore, after selecting 212 F1 from a Xin24 × Yushu10 crossing as the mapping population, this study applied specific-locus amplified fragment sequencing (SLAF-seq), at an average sequencing depth of 26.73 × (parents) and 52.25 × (progeny), to detect single nucleotide polymorphisms (SNPs). This approach generated an integrated genetic map of length 2441.56 cM and a mean distance of 0.51 cM between adjacent markers, encompassing 15 linkage groups (LGs). Based on the linkage map, 26 quantitative trait loci (QTLs), comprising six QTLs for LVL, six QTLs for YPP, ten QTLs for DMC, one QTL for SC, one QTL for SSC, and two QTLs for CC, were identified. Each of these QTLs explained 6.3-10% of the phenotypic variation. It is expected that the findings will be of benefit for marker-assisted breeding and gene cloning of sweetpotato.

Identification of candidate genes for Fusarium head blight resistance from QTLs using RIL population in wheat.

Fusarium head blight (FHB) stands out as one of the most devastating wheat diseases and leads to significantly grain yield losses and quality reductions in epidemic years. Exploring quantitative trait loci (QTL) for FHB resistance is a critical step for developing new FHB-resistant varieties. We previously constructed a genetic map of unigenes (UG-Map) according to the physical positions using a set of recombinant-inbred lines (RILs) derived from the cross of 'TN18 × LM6' (TL-RILs). Here, the number of diseased spikelets (NDS) and relative disease index (RDI) for FHB resistance were investigated under four environments using TL-RILs, which were distributed across 13 chromosomes. A number of 36 candidate genes for NDS and RDI from of 19 stable QTLs were identified. The average number of candidate genes per QTL was 1.89, with 14 (73.7%), two (10.5%), and three (15.8%) QTLs including one, two, and 3-10 candidate genes, respectively. Among the 24 candidate genes annotated in the reference genome RefSeq v1.1, the homologous genes of seven candidate genes, including TraesCS4B02G227300 for QNds/Rdi-4BL-4553, TraesCS5B02G303200, TraesCS5B02G303300, TraesCS5B02G303700, TraesCS5B02G303800 and TraesCS5B02G304000 for QNds/Rdi-5BL-9509, and TraesCS7A02G568400 for QNds/Rdi-7AL-14499, were previously reported to be related to FHB resistance in wheat, barely or Brachypodium distachyon. These genes should be closely associated with FHB resistance in wheat. In addition, the homologous genes of five genes, including TraesCS1A02G037600LC for QNds-1AS-2225, TraesCS1D02G017800 and TraesCS1D02G017900 for QNds-1DS-527, TraesCS1D02G018000 for QRdi-1DS-575, and TraesCS4B02G227400 for QNds/Rdi-4BL-4553, were involved in plant defense responses against pathogens. These genes should be likely associated with FHB resistance in wheat.

A novel method for multiple phenotype association studies based on genotype and phenotype network.

Joint analysis of multiple correlated phenotypes for genome-wide association studies (GWAS) can identify and interpret pleiotropic loci which are essential to understand pleiotropy in diseases and complex traits. Meanwhile, constructing a network based on associations between phenotypes and genotypes provides a new insight to analyze multiple phenotypes, which can explore whether phenotypes and genotypes might be related to each other at a higher level of cellular and organismal organization. In this paper, we first develop a bipartite signed network by linking phenotypes and genotypes into a Genotype and Phenotype Network (GPN). The GPN can be constructed by a mixture of quantitative and qualitative phenotypes and is applicable to binary phenotypes with extremely unbalanced case-control ratios in large-scale biobank datasets. We then apply a powerful community detection method to partition phenotypes into disjoint network modules based on GPN. Finally, we jointly test the association between multiple phenotypes in a network module and a single nucleotide polymorphism (SNP). Simulations and analyses of 72 complex traits in the UK Biobank show that multiple phenotype association tests based on network modules detected by GPN are much more powerful than those without considering network modules. The newly proposed GPN provides a new insight to investigate the genetic architecture among different types of phenotypes. Multiple phenotypes association studies based on GPN are improved by incorporating the genetic information into the phenotype clustering. Notably, it might broaden the understanding of genetic architecture that exists between diagnoses, genes, and pleiotropy.

Genome-wide association study for seedling heat tolerance under two temperature conditions in bread wheat (Triticum aestivum L.).

BACKGROUND: As the greenhouse effect intensifies, global temperatures are steadily increasing, posing a challenge to bread wheat (Triticum aestivum L.) production. It is imperative to comprehend the mechanism of high temperature tolerance in wheat and implement breeding programs to identify and develop heat-tolerant wheat germplasm and cultivars. RESULTS: To identify quantitative trait loci (QTL) related to heat stress tolerance (HST) at seedling stage in wheat, a panel of 253 wheat accessions which were re-sequenced used to conduct genome-wide association studies (GWAS) using the factored spectrally transformed linear mixed models (FaST-LMM). For most accessions, the growth of seedlings was found to be inhibited under heat stress. Analysis of the phenotypic data revealed that under heat stress conditions, the main root length, total root length, and shoot length of seedlings decreased by 47.46%, 49.29%, and 15.19%, respectively, compared to those in normal conditions. However, 17 varieties were identified as heat stress tolerant germplasm. Through GWAS analysis, a total of 115 QTLs were detected under both heat stress and normal conditions. Furthermore, 15 stable QTL-clusters associated with heat response were identified. By combining gene expression, haplotype analysis, and gene annotation information within the physical intervals of the 15 QTL-clusters, two novel candidate genes, TraesCS4B03G0152700/TaWRKY74-B and TraesCS4B03G0501400/TaSnRK3.15-B, were responsive to temperature and identified as potential regulators of HST in wheat at the seedling stage. CONCLUSIONS: This study conducted a detailed genetic analysis and successfully identified two genes potentially associated with HST in wheat at the seedling stage, laying a foundation to further dissect the regulatory mechanism underlying HST in wheat under high temperature conditions. Our finding could serve as genomic landmarks for wheat breeding aimed at improving adaptation to heat stress in the face of climate change.

Co-localization and analysis of miR477b with fiber length quantitative trait loci in cotton.

Cotton is an important cash crop for the textile industry. However, the understanding of natural genetic variation of fiber elongation in relation to miRNA is lacking. A miRNA gene (miR477b) was found to co-localize with a previously mapped fiber length (FL) quantitative trait locus (QTL). The miR477b was differentially expressed during fiber elongation between two backcross inbred lines (BILs) differing in FL and its precursor sequences. Bioinformatics and qRT-PCR analysis were further used to analyse the miRNA genes, which could produce mature miR477b. Cotton plants with virus-induced gene silencing (VIGS) constructs to over-express the allele of miR477b from the BIL with longer fibers had significantly longer fibers as compared with negative control plants, while the VIGS plants with suppressed miRNA expression had significantly shorter fibers. The expression level of the target gene (DELLA) and related genes (RDL1 and EXPA1 for DELLA through HOX3 protein) in the two BILs and/or the VIGS plants were generally congruent, as expected. This report represents one of the first comprehensive studies to integrate QTL linkage mapping and physical mapping of small RNAs with both small and mRNA transcriptome analysis, followed by VIGS, to identify candidate small RNA genes affecting the natural variation of fiber elongation in cotton.

Omics-driven utilization of wild relatives for empowering pre-breeding in pearl millet.

MAIN CONCLUSION: Pearl millet wild relatives harbour novel alleles which could be utilized to broaden genetic base of cultivated species. Genomics-informed pre-breeding is needed to speed up introgression from wild to cultivated gene pool in pearl millet. Rising episodes of intense biotic and abiotic stresses challenge pearl millet production globally. Wild relatives provide a wide spectrum of novel alleles which could address challenges posed by climate change. Pre-breeding holds potential to introgress novel diversity in genetically narrow cultivated Pennisetum glaucum from diverse gene pool. Practical utilization of gene pool diversity remained elusive due to genetic intricacies. Harnessing promising traits from wild pennisetum is limited by lack of information on underlying candidate genes/QTLs. Next-Generation Omics provide vast scope to speed up pre-breeding in pearl millet. Genomic resources generated out of draft genome sequence and improved genome assemblies can be employed to utilize gene bank accessions effectively. The article highlights genetic richness in pearl millet and its utilization with a focus on harnessing next-generation Omics to empower pre-breeding.

Genetic mapping of loci affecting seedling and adult-plant resistance to powdery mildew derived from two CIMMYT wheat lines.

MAIN CONCLUSION: PM3 and PM8 alleles carried by two CIMMYT wheat lines confer powdery mildew resistance in seedlings and/or adult plants. A stage-specific epistatic interaction was observed between PM3 and PM8. Powdery mildew is an important foliar disease of wheat. Major genes for resistance, which have been widely used in wheat breeding programs, are typically effective against only limited numbers of virulence genes of the pathogen. The main aim of this study was to map resistance loci in wheat lines 7HRWSN58 and ZWW09-149 from the International Maize and Wheat Improvement Center (CIMMYT). Doubled haploid populations (Magenta/7HRWSN58 and Emu Rock/ZWW09-149) were developed and grown in controlled environment experiments and inoculated with a composite of Blumeria graminis f.sp. tritici isolates that had been collected at various locations in Western Australia. Plants were assessed for powdery mildew symptoms (percentage leaf area diseased) on seedlings and adult plants. Populations were subjected to genotyping-by-sequencing and assayed for known SNPs in the resistance gene PM3. Linkage maps were constructed, and markers were anchored to the wheat reference genome sequence. In both populations, there were asymptomatic lines that exhibited no symptoms. Among symptomatic lines, disease severity varied widely. In the Magenta/7HRWSN58 population, most of the observed variation was attributed to the PM3 region of chromosome 1A, with the allele from 7HRWSN58 conferring resistance in seedlings and adult plants. In the Emu Rock/ZWW09-149 population, two interacting quantitative trait loci were mapped: one at PM3 and the other on chromosome 1B. The Emu Rock/ZWW09-149 population was confirmed to segregate for a 1BL·1RS translocation that carries the PM8 powdery mildew resistance gene from rye. Consistent with previous reports that PM8-derived resistance can be suppressed by PM3 alleles, the observed interaction between the quantitative trait loci on chromosomes 1A and 1B indicated that the PM3 allele carried by ZWW09-149 suppresses PM8-derived resistance from ZWW09-149, but only at the seedling stage. In adult plants, the PM8 region conferred resistance regardless of the PM3 genotype. The resistance sources and molecular markers that were investigated here could be useful in wheat breeding.

Boosting genome-wide association power and genomic prediction accuracy for date palm fruit traits with advanced statistics.

The date palm is economically vital in the Middle East and North Africa, providing essential fibres, vitamins, and carbohydrates. Understanding the genetic architecture of its traits remains complex due to the tree's perennial nature and long generation times. This study aims to address these complexities by employing advanced genome-wide association (GWAS) and genomic prediction models using previously published data involving fruit acid content, sugar content, dimension, and colour traits. The multivariate GWAS model identified seven QTL, including five novel associations, that shed light on the genetic control of these traits. Furthermore, the research evaluates different genomic prediction models that considered genotype by environment and genotype by trait interactions. While colour- traits demonstrate strong predictive power, other traits display moderate accuracies across different models and scenarios aligned with the expectations when using small reference populations. When designing the cross-validation to predict new individuals, the accuracy of the best multi-trait model was significantly higher than all single-trait models for dimension traits, but not for the remaining traits, which showed similar performances. However, the cross-validation strategy that masked random phenotypic records (i.e., mimicking the unbalanced phenotypic records) showed significantly higher accuracy for all traits except acid contents. The findings underscore the importance of understanding genetic architecture for informed breeding strategies. The research emphasises the need for larger population sizes and multivariate models to enhance gene tagging power and predictive accuracy to advance date palm breeding programs. These findings support more targeted breeding in date palm, improving productivity and resilience to various environments.

Identification of superior haplotypes for flowering time in pigeonpea through candidate gene-based association study of a diverse minicore collection.

KEY MESSAGE: In current study candidate gene (261 genes) based association mapping on 144 pigeonpea accessions for flowering time and related traits and 29 MTAs producing eight superior haplotypes were identified. In the current study, we have conducted an association analysis for flowering-associated traits in a diverse pigeonpea mini-core collection comprising 144 accessions using the SNP data of 261 flowering-related genes. In total, 13,449 SNPs were detected in the current study, which ranged from 743 (ICP10228) to 1469 (ICP6668) among the individuals. The nucleotide diversity (0.28) and Watterson estimates (0.34) reflected substantial diversity, while Tajima's D (-0.70) indicated the abundance of rare alleles in the collection. A total of 29 marker trait associations (MTAs) were identified, among which 19 were unique to days to first flowering (DOF) and/or days to fifty percent flowering (DFF), 9 to plant height (PH), and 1 to determinate (Det) growth habit using 3 years of phenotypic data. Among these MTAs, six were common to DOF and/or DFF, and four were common to DOF/DFF along with the PH, reflecting their pleiotropic action. These 29 MTAs spanned 25 genes, among which 10 genes clustered in the protein-protein network analysis, indicating their concerted involvement in floral induction. Furthermore, we identified eight haplotypes, four of which regulate late flowering, while the remaining four regulate early flowering using the MTAs. Interestingly, haplotypes conferring late flowering (H001, H002, and H008) were found to be taller, while those involved in early flowering (H003) were shorter in height. The expression pattern of these genes, as inferred from the transcriptome data, also underpinned their involvement in floral induction. The haplotypes identified will be highly useful to the pigeonpea breeding community for haplotype-based breeding.

Characterization of chromosomal segment substitution lines developed in the genetic background of rice variety K 343.

In this study, BC3F2 convergent population [(K343*3/RML22 × K343*3/DHMAS) × K343] was constructed by marker-assisted backcross breeding using K343 as the recurrent parent. DHMAS and RML22 were used as donor parents for the rice blast resistance genes Pi54 and Pi9, respectively. The population was first characterized using GGT 2.0 software, which showed 96.7% of the recurrent genome recovery covering 13953.6 cM, while DHMAS and RML22 showed 1.6% (235.5 cM) and 1.2% (177.1 cM) introgression respectively. The chromosomal segment substitution lines (CSSLs) were then identified using CSSL Finder software. A total of 36 CSSLs were identified, including 22 for DHMAS/K343 and 14 for RML22/K343. Introgression rates for donor substituted segments in DHMAS/K343 CSSLs ranged from 0.54% to 5.99%, with donor coverage of 44.5%, while in RML22/K343 CSSLs, introgression rates ranged from 0.54% to 4.75%, with donor coverage of 24.5%. The identified CSSLs would be a valuable genetic pool and could be used as genomic resources for the discovery and mapping of important genes and QTLs in rice genetic improvement.

Sub1 QTL confers submergence tolerance in rice through nitro-oxidative regulation and phytohormonal signaling.

Constant change in global climate has become the most important limiting factor to crop productivity. Asymmetrical precipitations are causing recurrent flood events around the world. Submergence is one of the most detrimental abiotic stresses for sustainable rice production in the rainfed ecosystems of Southeast Asia. Therefore, the development of submergence-tolerant rice is an essential requirement to encounter food security. Submergence tolerance in rice is governed by the major quantitative trait locus (QTL) designated as Submergence1 (Sub1) near the centromere of chromosome 9. The introduction of the Sub1 in high-yielding rice varieties producing near-isogenic lines (NILs) has shown extreme submergence tolerance. The present study aimed to understand the responses of rice genotype IR64 and its Sub1 NIL IR64 Sub1 following one week of complete submergence treatment. Submergence imposed severe nitro-oxidative stress in both the rice genotypes, consequently disrupting the cellular redox homeostasis. In this study, IR64 exhibited higher NADPH oxidase activity accompanied by increased reactive oxygen species, reactive nitrogen species, and malondialdehyde buildups and cell death under submergence. Higher accumulations of 1-Aminocyclopropane-1-carboxylic acid, gibberellic acid, and Indole-3-acetic acid were also observed in IR64 which accelerated the plant growth and root cortical aerenchyma development following submergence. In contrast, IR64 Sub1 had enhanced submergence tolerance associated with an improved antioxidant defense system with sustainable morpho-physiological activities and restricted root aerenchyma formation. The comprehensive analyses of the responses of rice genotypes with contrasting submergence tolerance may demonstrate the intricacies of rice under complete submergence and may potentially contribute to improving stress resilience by advancing our understanding of the mechanisms of submergence tolerance in rice.