Wheat is an essential food commodity cultivated throughout the world. However, this crop faces continuous threats from fungal pathogens, leaf rust (LR) and stripe rust (YR). To continue feeding the growing population, these major destructors of wheat must be effectively countered by enhancing the genetic diversity of cultivated germplasm. In this study, an introgression line with hexaploid background (ILsp3603) carrying resistance against Pt pathotypes 77-5 (121R63-1), 77-9 (121R60-1) and Pst pathotypes 46S119 (46E159), 110S119 (110E159), 238S119 (238E159) was developed from donor wheat wild progenitor, Aegilops speltoides acc pau 3603. To understand the genetic basis of resistance and map these genes (named Lrsp3603 and Yrsp3603), inheritance studies were carried out in F6 and F7 mapping population, developed by crossing ILsp3603 with LR and YR susceptible cultivar WL711, which revealed a monogenic (single gene) inheritance pattern for each of these traits. Bulk segregant analysis combined with 35 K Axiom SNP array genotyping mapped both genes as separate entities on the short arm of chromosome 6B. A genetic linkage map, comprising five markers, 1 SNP, 1 PLUG and three gene based SSRs, covered a genetic distance of 12.65 cM. Lrsp3603 was flanked by markers Tag-SSR14 (located proximally at 2.42 cM) and SNP AX-94542331 (at 3.28 cM) while Yrsp3603 was mapped at one end closest to AX-94542331 at 6.62 cM distance. Functional annotation of Lrsp3603 target region (∼ 1 Mbp) revealed 10 gene IDs associated with disease resistance mechanisms including three encoding typical R gene domains.

Phenolamides are important secondary metabolites in plant species. They play important roles in plant defense responses against pathogens and insect herbivores, protection against UV irradiation and floral induction and development. However, the accumulation and variation in phenolamides content in diverse maize lines and the genes responsible for their biosynthesis remain largely unknown. Here, we combined genetic mapping, protein regulatory network and bioinformatics analysis to further enhance the understanding of maize phenolamides biosynthesis. Sixteen phenolamides were identified in multiple populations, and they were all significantly correlated with one or several of 19 phenotypic traits. By linkage mapping, 58, 58, 39 and 67 QTLs, with an average of 3.9, 3.6, 3.6 and 4.2 QTLs for each trait were mapped in BBE1, BBE2, ZYE1 and ZYE2, explaining 9.47%, 10.78%, 9.51% and 11.40% phenotypic variation for each QTL on average, respectively. By GWAS, 39 and 36 significant loci were detected in two different environments, 3.3 and 2.8 loci for each trait, explaining 10.00% and 9.97% phenotypic variation for each locus on average, respectively. Totally, 58 unique candidate genes were identified, 31% of them encoding enzymes involved in amine and derivative metabolic processes. Gene Ontology term analysis of the 358 protein-protein interrelated genes revealed significant enrichment in terms relating to cellular nitrogen metabolism, amine metabolism. GRMZM2G066142, GRMZM2G066049, GRMZM2G165390 and GRMZM2G159587 were further validated involvement in phenolamides biosynthesis. Our results provide insights into the genetic basis of phenolamides biosynthesis in maize kernels, understanding phenolamides biosynthesis and its nutritional content and ability to withstand biotic and abiotic stress.

Identification of candidate genes and molecular markers for late leaf spot (LLS) disease resistance in peanut (Arachis hypogaea) has been a focus of molecular breeding for the U.S. industry-funded peanut genome project. Efforts have been hindered by limited mapping resolution due to low levels of genetic recombination and marker density available in traditional biparental mapping populations. To address this, a multi-parental nested association mapping population has been genotyped with the peanut 58K single-nucleotide polymorphism (SNP) array and phenotyped for LLS severity in the field for 3 years. Joint linkage-based quantitative trait locus (QTL) mapping identified nine QTLs for LLS resistance with significant phenotypic variance explained up to 47.7%. A genome-wide association study identified 13 SNPs consistently associated with LLS resistance. Two genomic regions harboring the consistent QTLs and SNPs were identified from 1,336 to 1,520 kb (184 kb) on chromosome B02 and from 1,026.9 to 1,793.2 kb (767 kb) on chromosome B03, designated as peanut LLS resistance loci, PLLSR-1 and PLLSR-2, respectively. PLLSR-1 contains 10 nucleotide-binding site leucine-rich repeat disease resistance genes. A nucleotide-binding site leucine-rich repeat disease resistance gene, Arahy.VKVT6A, was also identified on homoeologous chromosome A02. PLLSR-2 contains five significant SNPs associated with five different genes encoding callose synthase, pollen defective in guidance protein, pentatricopeptide repeat, acyl-activating enzyme, and C2 GRAM domains-containing protein. This study highlights the power of multi-parent populations such as nested association mapping for genetic mapping and marker-trait association studies in peanuts. Validation of these two LLS resistance loci will be needed for marker-assisted breeding.

Plant architecture is one of the key factors affecting maize yield formation and can be divided into secondary traits, such as plant height (PH), ear height (EH), and leaf number (LN). It is a viable approach for exploiting genetic resources to improve plant density. In this study, one natural panel of 226 inbred lines and 150 family lines derived from the offspring of T32 crossed with Qi319 were genotyped by using the MaizeSNP50 chip and the genotyping by sequence (GBS) method and phenotyped under three different environments. Based on the results, a genome-wide association study (GWAS) and linkage mapping were analyzed by using the MLM and ICIM models, respectively. The results showed that 120 QTNs (quantitative trait nucleotides) and 32 QTL (quantitative trait loci) related to plant architecture were identified, including four QTL and 40 QTNs of PH, eight QTL and 41 QTNs of EH, and 20 QTL and 39 QTNs of LN. One dominant QTL, qLN7-2, was identified in the Zhangye environment. Six QTNs were commonly identified to be related to PH, EH, and LN in different environments. The candidate gene analysis revealed that Zm00001d021574 was involved in regulating plant architecture traits through the autophagy pathway, and Zm00001d044730 was predicted to interact with the male sterility-related gene ms26. These results provide abundant genetic resources for improving maize plant architecture traits by using approaches to biological breeding.

The genetic regulatory basis of qualitative and quantitative phenotypes of watermelon is being investigated in different types of molecular and genetic breeding studies around the world. In this study, biparental F2 mapping populations were developed over two experimental years, and the collected datasets of fruit and seed traits exhibited highly significant correlations. Whole-genome resequencing of comparative parental lines was performed and detected single nucleotide polymorphism (SNP) loci were converted into cleaved amplified polymorphic sequence (CAPS) markers. The screened polymorphic markers were genotyped in segregating populations and two genetic linkage maps were constructed, which covered a total of 2834.28 and 2721.45 centimorgan (cM) genetic lengths, respectively. A total of 22 quantitative trait loci (QTLs) for seven phenotypic traits were mapped; among them, five stable and major-effect QTLs (PC-8-1, SL-9-1, SWi-9-1, SSi-9-1, and SW-6-1) and four minor-effect QTLs (PC-2-1 and PC-2-2; PT-2-1 and PT-2-2; SL-6-1 and SSi-6-2; and SWi-6-1 and SWi-6-2) were observed with 3.77-38.98% PVE. The adjacent QTL markers showed a good fit marker-trait association, and a significant allele-specific contribution was also noticed for genetic inheritance of traits. Further, a total of four candidate genes (Cla97C09G179150, Cla97C09G179350, Cla97C09G180040, and Cla97C09G180100) were spotted in the stable colocalized QTLs of seed size linked traits (SL-9-1 and SWi-9-1) that showed non-synonymous type mutations. The gene expression trends indicated that the seed morphology had been formed in the early developmental stage and showed the genetic regulation of seed shape formation. Hence, we think that our identified QTLs and genes would provide powerful genetic insights for marker-assisted breeding aimed at improving the quality traits of watermelon.

Colour is often used as an aposematic warning signal, with predator learning expected to lead to a single colour pattern within a population. However, there are many puzzling cases where aposematic signals are also polymorphic. The wood tiger moth, Arctia plantaginis, displays bright hindwing colours associated with unpalatability, and males have discrete colour morphs which vary in frequency between localities. In Finland, both white and yellow morphs can be found, and these colour morphs also differ in behavioural and life-history traits. Here, we show that male colour is linked to an extra copy of a yellow family gene that is only present in the white morphs. This white-specific duplication, which we name valkea, is highly upregulated during wing development. CRISPR targeting valkea resulted in editing of both valkea and its paralog, yellow-e, and led to the production of yellow wings. We also characterise the pigments responsible for yellow, white, and black colouration, showing that yellow is partly produced by pheomelanins, while black is dopamine-derived eumelanin. Our results add to a growing number of studies on the genetic architecture of complex and seemingly paradoxical polymorphisms, and the role of gene duplications and structural variation in adaptive evolution.

White mold (WM) is a major disease in common bean (Phaseolus vulgaris L.), and its complex quantitative genetic control limits the development of WM resistant cultivars. WM2.2, one of the nine meta-QTL with a major effect on WM tolerance, explains up to 35% of the phenotypic variation and was previously mapped to a large genomic interval on Pv02. Our objective was to narrow the interval of this QTL using combined approach of classic QTL mapping and QTL-based bulk segregant analysis (BSA), and confirming those results with Khufu de novo QTL-seq. The phenotypic and genotypic data from two RIL populations, \'Raven\'/I9365-31 (R31) and \'AN-37\'/PS02-029C-20 (Z0726-9), were used to select resistant and susceptible lines to generate subpopulations for bulk DNA sequencing. The QTL physical interval was determined by considering overlapping interval of the identified QTL or peak region in both populations by three independent QTL mapping analyses. Our findings revealed that meta-QTL WM2.2 consists of three regions, WM2.2a (4.27-5.76 Mb; euchromatic), WM 2.2b (12.19 to 17.61 Mb; heterochromatic), and WM2.2c (23.01-25.74 Mb; heterochromatic) found in both populations. Gene models encoding for gibberellin 2-oxidase 8, pentatricopeptide repeat, and heat-shock proteins are the likely candidate genes associated with WM2.2a resistance. A TIR-NBS-LRR class of disease resistance protein (Phvul.002G09200) and LRR domain containing family proteins are potential candidate genes associated with WM2.2b resistance. Nine gene models encoding disease resistance protein [pathogenesis-related thaumatin superfamily protein and disease resistance-responsive (dirigent-like protein) family protein etc] found within the WM2.2c QTL interval are putative candidate genes. WM2.2a region is most likely associated with avoidance mechanisms while WM2.2b and WM2.2c regions trigger physiological resistance based on putative candidate genes.

Flag leaf senescence is a critical factor affecting the yield and quality of wheat. The aim of this study was to identify QTLs associated with flag leaf senescence in an F10 recombinant inbred line population derived from durum wheats UC1113 and Kofa. Bulked segregant analysis using the wheat 660K SNP array identified 3225 SNPs between extreme-phenotype bulks, and the differential SNPs were mainly clustered on chromosomes 1A, 1B, 3B, 5A, 5B, and 7A. BSR-Seq indicated that the significant SNPs were mainly located in two intervals of 354.0-389.0 Mb and 8.0-15.0 Mb on 1B and 3B, respectively. Based on the distribution of significant SNPs on chromosomes 1B and 3B, a total of 109 insertion/deletion (InDel) markers were developed, and 8 of them were finally used to map QTL in UC1113/Kofa population for flag leaf senescence. Inclusive composite interval mapping identified two major QTL in marker intervals Mar2005-Mar2116 and Mar207-Mar289, explaining 14.2-15.4% and 31.4-68.6% of the phenotypic variances across environments, respectively. Using BSR-Seq, gene expression and sequence analysis, the TraesCS1B02G211600 and TraesCS3B02G023000 were identified as candidate senescence-associated genes. This study has potential to be used in cloning key genes for flag leaf senescence and provides available molecular markers for genotyping and marker-assisted selection breeding.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s11032-023-01410-3.

Mesocotyl elongation of rice seedlings is a key trait for deep sowing tolerance and well seedling establishment in dry direct sowing rice (DDSR) production. Subsets of the Rice Diversity Panel 1 (RDP1, 294 accessions) and Hanyou 73 (HY73) recombinant inbred line (RIL) population (312 lines) were screened for mesocotyl length (ML) via dark germination. Six RDP1 accessions (Phudugey, Kasalath, CA902B21, Surjamkuhi, Djimoron, and Goria) had an ML longer than 10 cm, with the other 19 accessions being over 4 cm. A GWAS in RDP1 detected 118 associated SNPs on all 12 chromosomes using a threshold of FDR-adjusted p < 0.05, including 11 SNPs on chromosomes 1, 4, 5, 7, 10, and 12 declared by -log10(P) > 5.868 as the Bonferroni-corrected threshold. Using phenotypic data of three successive trials and a high-density bin map from resequencing genotypic data, four to six QTLs were detected on chromosomes 1, 2, 5, 6, and 10, including three loci repeatedly mapped for ML from two or three replicated trials. Candidate genes were predicted from the chromosomal regions covered by the associated LD blocks and the confidence intervals (CIs) of QTLs and partially validated by the dynamic RNA-seq data in the mesocotyl along different periods of light exposure. Potential strategies of donor parent selection for seedling establishment in DDSR breeding were discussed.

Begomoviruses, viz. squash leaf curl China virus and tomato leaf curl New Delhi virus causative diseases are major concerns of quantitative and qualitative losses in pumpkin (Cucurbita moschata) worldwide. Punjab Agricultural University (PAU) in India has identified a resistant source (PVR-1343) against mixed infection (MI-Sq/To) of these begomoviruses. Introgression of resistance in diverse genetic backgrounds requires the identification of quantitative trait loci (QTLs) associated with MI-Sq/To resistance. Phenotyping of 229 F2:3 progenies derived from the PVR-1343 × P-135 cross revealed digenic recessive inheritance against MI-Sq/To resistance in PVR-1343. To identify the genomic region, resistant and susceptible bulks were subjected to whole-genome resequencing along with their parents. The whole-genome resequence analysis of parents and bulks using QTLseq/QTLseqr approaches identified an overlapping 1.52 Mb region on chromosome 7 (qMI-Sq/To7.1), while chromosomal region spanning 0.87 Mb on chromosome17 (qMI-Sq/To17.1) was additionally identified by QTLseqr. However, the highest peak value on chromosome 7 with three algorithms {G\', ∆(SNP-index) and -log10 (P value)} highlighted the major contribution of qMI-Sq/To7.1 in MI-Sq/To resistance. Nine polymorphic SNPs identified within the highly significant qMI-Sq/To7.1 region were converted into KASP markers. KASP genotyping of F2 individuals narrowed down the qMI-Sq/To7.1 interval to 103 kb region flanked by two markers, Cmo3914729 and Cmo4018182, which contained 16 annotated genes and accounted for 59.84% of phenotypic variation. The Cmo4018182 KASP marker accurately predicted disease reaction in 91% of diverse Cucurbita genotypes and showed nonsynonym substitutions in the coding region of putative candidate SYNTAXIN-121 gene. These findings pave the way for marker-assisted breeding and elucidating the underlying mechanism of begomovirus resistance in C. moschata.