INTROGRESSING PHEROMONE QTL BETWEEN SPECIES: TOWARDS AN EVOLUTIONARY UNDERSTANDING OF DIFFERENTIATION IN SEXUAL COMMUNICATION

As a first step toward understanding how noctuid moths evolve species-specific pheromone communication systems, we hybridized and backcrossed two closely related moth species, Heliothis virescens (Hv) and H. subflexa (Hs), which differ qualitatively and quantitatively in their multi-component sex pheromone blends. We used amplified fragment length polymorphism (AFLP) marker-based mapping of backcross families to determine which of the 30 autosomes in these moths contained quantitative trait loci (QTL) controlling the percentages of specific chemical components in the pheromone blends. In two previous backcrosses to Hs, we found a strong depressive effect of Hv-chromosome 22 on the percentage of three acetate components in the pheromone gland. These acetates are present in Hs and absent in Hv. Here, we describe how we introgressed Hv-chromosome 22 into the genomic background of Hs. Selection for Hv-chromosome 22 started from backcross 3 (BC₃) females. All females that had Hv-chromosome 22 and a low percentage of acetates (< 3% of the total amount of pheromone components present) were backcrossed to Hs males. In BC₅ to BC₈, we determined whether Hv-chromosome 22 was present by a) running only the primer pairs that would yield the markers for that chromosome, and/or b) determining the relative percentages of acetates in the pheromone glands. Either or both genotype and phenotype were used as a criterion to continue to backcross these females to Hs males. In BC₉, we confirmed the isolation of Hv-chromosome 22 in the Hs genomic background, and backcrossed the males to Hs females to eliminate the Hv-sex chromosome as well as mitochondrial DNA. The pheromone composition was determined in BC₃, BC₅, and BC₁₁ females with and without Hv-chromosome 22. All backcross females with Hv-chromosome 22 contained significantly less acetates than females without this chromosome. In addition, BC₃ females with Hv-chromosome 22 contained significantly more Z11-16:OH than BC₃ females without Hv-chromosome 22. However, in BC₅ and BC₁₁ females, the correlation between Z11-16:OH and Hv-chromosome 22 was lost, suggesting that there are separate QTL for the acetates and for Z11-16:OH, and that the relative amount of the alcohol component is only affected in epistasis with other (minor) QTL. Now that we have succeeded in isolating the chromosome that has a major effect on acetate production, we can test in behavioral experiments whether the presence of acetates may have been a driving force for a shift in pheromone composition. Such tests are necessary to move towards an evolutionary understanding of the differentiation in sexual communication in Heliothis spp. moths.     

Fine Mapping and Functional Analysis of Major Regulatory Genes of Soluble Solids Content in Wax Gourd (Benincasa hispida)

Soluble solids content (SSC) is an important quality trait of wax gourd, but reports about its regulatory genes are scarce. In this study, the SSC regulatory gene BhSSC2.1 in wax gourd was mined via quantitative trait locus (QTL) mapping based on high-density genetic mapping containing 12 linkage groups (LG) and bulked segregant analysis (BSA)-seq. QTL mapping and BSA-seq revealed for the first time that the SSC QTL (107.658–108.176 cM) of wax gourd was on Chr2 (LG2). The interpretable phenotypic variation rate and maximum LOD were 16.033% and 6.454, respectively. The QTL interval contained 13 genes. Real-time fluorescence quantitative expression analysis, functional annotation, and sequence analysis suggested that Bch02G016960, named BhSSC2.1, was a candidate regulatory gene of the SSC in wax gourd. Functional annotation of this gene showed that it codes for a NADP-dependent malic enzyme. According to BhSSC2.1 sequence variation, an InDel marker was developed for molecular marker-assisted breeding of wax gourd. This study will lay the foundation for future studies regarding breeding and understanding genetic mechanisms of wax gourd.     

A Quantitative Genetic Study of Sclerotinia Head Rot Resistance Introgressed from the Wild Perennial Helianthus maximiliani into Cultivated Sunflower (Helianthus annuus L.)

Sclerotinia head rot (HR), caused by Sclerotinia sclerotiorum, is an economically important disease of sunflower with known detrimental effects on yield and quality in humid climates worldwide. The objective of this study was to gain insight into the genetic architecture of HR resistance from a sunflower line HR21 harboring HR resistance introgressed from the wild perennial Helianthus maximiliani. An F₂ population derived from the cross of HA 234 (susceptible-line)/HR21 (resistant-line) was evaluated for HR resistance at two locations during 2019–2020. Highly significant genetic variations (p < 0.001) were observed for HR disease incidence (DI) and disease severity (DS) in both individual and combined analyses. Broad sense heritability (H²) estimates across environments for DI and DS were 0.51 and 0.62, respectively. A high-density genetic map of 1420.287 cM was constructed with 6315 SNP/InDel markers developed using genotype-by-sequencing technology. A total of 16 genomic regions on eight sunflower chromosomes, 1, 2, 10, 12, 13, 14, 16 and 17 were associated with HR resistance, each explaining between 3.97 to 16.67% of the phenotypic variance for HR resistance. Eleven of these QTL had resistance alleles from the HR21 parent. Molecular markers flanking the QTL will facilitate marker-assisted selection breeding for HR resistance in sunflower.     

Mapping QTLs Controlling Beneficial Fatty Acids Based on the Embryo and Maternal Plant Genomes in Brassica napus L.

This study was mainly carried out to detect the quantitative trait loci (QTLs) located simultaneously in embryo and maternal plant nuclear genomes for beneficial fatty acid contents of rapeseed under different environments by using a mapping model and mapping populations from a cross of ‘Tapidor’ × ‘Ningyou7.’ Eight, three, six, seven and three QTLs respectively for palmitic, oleic, linoleic, linolenic and eicosenoic acid contents were identified and subsequently mapped on chromosomes A1, A3, A4, A6, A8, A9, C1, C3, C5, C7, C8 and C9. Among them, 12 QTLs were major ones that could respectively explain more than 10 % of phenotypic variation. Two specific genomic regions on A8 and C3 were associated with several QTLs relating to multiple fatty acid contents. Some of the markers such as HBr015 and JICB0633 showed tight linkage with the QTLs, which could be used for improving the fatty acid component(s) of rapeseed.     

Genetic Diversity and Association Analysis for Carotenoid Content among Sprouts of Cowpea (Vigna unguiculata L. Walp)

The development and promotion of biofortified foods plants are a sustainable strategy for supplying essential micronutrients for human health and nutrition. We set out to identify quantitative trait loci (QTL) associated with carotenoid content in cowpea sprouts. The contents of carotenoids, including lutein, zeaxanthin, and β-carotene in sprouts of 125 accessions were quantified via high-performance liquid chromatography. Significant variation existed in the profiles of the different carotenoids. Lutein was the most abundant (58 ± 12.8 mg/100 g), followed by zeaxanthin (14.7 ± 3.1 mg/100 g) and β-carotene (13.2 ± 2.9 mg/100 g). A strong positive correlation was observed among the carotenoid compounds (r ≥ 0.87), indicating they can be improved concurrently. The accessions were distributed into three groups, following their carotenoid profiles, with accession C044 having the highest sprout carotenoid content in a single cluster. A total of 3120 genome-wide SNPs were tested for association analysis, which revealed that carotenoid biosynthesis in cowpea sprouts is a polygenic trait controlled by genes with additive and dominance effects. Seven loci were significantly associated with the variation in carotenoid content. The evidence of variation in carotenoid content and genomic regions controlling the trait creates an avenue for breeding cowpea varieties with enhanced sprouts carotenoid content.     

Candidate Genes and Pathways in Rice Co-Responding to Drought and Salt Identified by gcHap Network

Drought and salinity stresses are significant abiotic factors that limit rice yield. Exploring the co-response mechanism to drought and salt stress will be conducive to future rice breeding. A total of 1748 drought and salt co-responsive genes were screened, most of which are enriched in plant hormone signal transduction, protein processing in the endoplasmic reticulum, and the MAPK signaling pathways. We performed gene-coding sequence haplotype (gcHap) network analysis on nine important genes out of the total amount, which showed significant differences between the Xian/indica and Geng/japonica population. These genes were combined with related pathways, resulting in an interesting mechanistic draft called the ‘gcHap-network pathway’. Meanwhile, we collected a lot of drought and salt breeding varieties, especially the introgression lines (ILs) with HHZ as the parent, which contained the above-mentioned nine genes. This might imply that these ILs have the potential to improve the tolerance to drought and salt. In this paper, we focus on the relationship of drought and salt co-response gene gcHaps and their related pathways using a novel angle. The haplotype network will be helpful to explore the desired haplotypes that can be implemented in haplotype-based breeding programs.     

Quantitative trait Loci for health traits in Finnish Ayrshire cattle

A whole-genome scan was conducted to search for quantitative trait loci (QTL) affecting health traits in Finnish Ayrshire dairy cattle. The mapping population consisted of 12 bulls and their 491 sons in a granddaughter design. A total of 150 markers were typed covering all 29 autosomes. The traits under study were somatic cell score, mastitis, and a group of other veterinary treatments. Effects of the QTL and positions were estimated with the regression method. When carrying out interval mapping on each chromosome, cofactors were used to adjust for QTL identified at other chromosomes. Empirical P-values were obtained by permutation. Altogether 17 QTL were detected with genomewise significant P-values in the across family analysis. Quantitative trait loci affecting SCS were identified on chromosomes 1, 3, 11, 18, 21, 24, 27, 29, and QTL for mastitis on chromosomes 14, 18. Quantitative trait loci for other veterinary treatments were found on chromosomes 1, 2, 5, 8, 15, 22, and 23. The allele substitution effects were from 0.5 to 1.7 genetic standard deviations. The positions of these health QTL did not overlap with milk QTL detected in previous studies of the same population.     

Genetic evaluation of dairy cattle using a simple heritable genetic ground

The evaluation of an animal is based on production records, adjusted for environmental effects, which gives a reliable estimation of its breeding value. Highly reliable daughter yield deviations are used as inputs for genetic marker evaluation. Genetic variability is explained by particular loci and background polygenes, both of which are described by the genomic breeding value selection index. Automated genotyping enables the determination of many single‐nucleotide polymorphisms (SNPs) and can increase the reliability of evaluation of young animals (from 0.30 if only the pedigree value is used to 0.60 when the genomic breeding value is applied). However, the introduction of SNPs requires a mixed model with a large number of regressors, in turn requiring new algorithms for the best linear unbiased prediction and BayesB. Here, we discuss a method that uses a genomic relationship matrix to estimate the genomic breeding value of animals directly, without regressors. A one‐step procedure evaluates both genotyped and ungenotyped animals at the same time, and produces one common ranking of all animals in a whole population. An augmented pedigree–genomic relationship matrix and the removal of prerequisites produce more accurate evaluations of all connected animals. Copyright © 2010 Society of Chemical Industry