Genome-Based Prediction of Time to Curd Induction in Cauliflower

Transcriptome profiling reveals key regulatory factors and metabolic pathways associated with curd formation and development in broccoli

Broccoli, a cruciferous vegetable, has a unique indeterminate inflorescence structure known as curds. It is the main edible organ of broccoli and has a rich nutritional value and health benefits. However, the formation and development mechanism of the curd is still not well understood. In the present study, the shoot apical meristem (SAM) stage and three different development stages of curd (formation stage (FS), expansion stage (ES), and maturation stage (MS)) were identified and subjected to transcriptome sequencing to uncover the potential genes and regulatory networks involved in curd formation and development. The results indicated that the genes associated with the development of SAM such as BolAP1A, BolAP1C, BolCAL, and BolAGL6 play an important role in the abnormal differentiation of the curd apical buds. The genes, BolFRI, BolbHLH89, BolKAN4, BolAGL12, and BolAGL24, displayed significantly differential expression patterns in curd development may function in the regulation of the transition from inflorescence meristem (IM) to floral meristem (FM). Moreover, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the differentially expressed genes (DEGs) indicate that phytohormones, such as auxin (AUX), gibberellins (GA), and abscisic acid (ABA) also play an important role in SAM proliferation and the transition from SAM to IM. In addition, the genes regulating photosynthetic reaction (BolLHCA1, BolLHCB1, BolPsbO, etc.) have a key involvement in the differentiation of secondary IMs during curd expansion. The genes associated with the metabolism of starch and sucrose (e.g., BolSPS4, BolBAM4) were significantly upregulated at the MS should contribute to the maturation of the curd. These findings provide new insights into the potential key regulatory factors and metabolic pathways involved in the formation and development of broccoli curds.

Integration of Crop Growth Models and Genomic Prediction

Crop growth models (CGMs) consist of multiple equations that represent physiological processes of plants and simulate crop growth dynamically given environmental inputs. Because parameters of CGMs are often genotype-specific, gene effects can be related to environmental inputs through CGMs. Thus, CGMs are attractive tools for predicting genotype by environment (G×E) interactions. This chapter reviews CGMs, genetic analyses using these models, and the status of studies that integrate genomic prediction with CGMs. Examples of CGM analyses are also provided.

Understanding population structure and detection of QTLs for curding-related traits in Indian cauliflower by genotyping by sequencing analysis

Curd initiation and development are complex traits and highly responsive for different temperature ranges in cauliflower. The present study was aimed to identify QTLs for eight traits associated with curding behaviour in diverse germplasm of Indian cauliflower. For this, 92 genotypes of cauliflower and 2 each of tropical broccoli and cabbage were genotyped through genotyping by sequencing (GBS). It generated ≈302 million reads (9.1226E + 10 bp) and identified 35,381 SNPs, maximum from chromosome 3 (4735) with a mean value of 3981.1 SNPs. Ts/Tv ratio was 1.74, suggesting transition bias. STRUCTURE analysis revealed delta value of K = 4 and four subpopulations and prominence of population admixture. In total, 121 significant SNPs were detected for eight traits, 38 for Delhi (North Indian plain) and 83 for Barapani (North-East India). Twelve QTLs were detected for traits associated with regulation of curd formation and development, five of which were for marketable curd length, curd width, days to 50% curd harvest and marketable curd weight from Delhi region and seven for curd length, curd width, days to 50% curd harvest, gross plant weight, leaf length, marketable/net curd weight and number of leaves per plant for Barapani area of North East India. The SNPs identified will be useful for development of markers for curding-related traits and their use in breeding varieties with wider curding plasticity.

Validation of a novel associative transcriptomics pipeline in Brassica oleracea: identifying candidates for vernalisation response

BACKGROUND

Associative transcriptomics has been used extensively in Brassica napus to enable the rapid identification of markers correlated with traits of interest. However, within the important vegetable crop species, Brassica oleracea, the use of associative transcriptomics has been limited due to a lack of fixed genetic resources and the difficulties in generating material due to self-incompatibility. Within Brassica vegetables, the harvestable product can be vegetative or floral tissues and therefore synchronisation of the floral transition is an important goal for growers and breeders. Vernalisation is known to be a key determinant of the floral transition, yet how different vernalisation treatments influence flowering in B. oleracea is not well understood.

RESULTS

Here, we present results from phenotyping a diverse set of 69 B. oleracea accessions for heading and flowering traits under different environmental conditions. We developed a new associative transcriptomics pipeline, and inferred and validated a population structure, for the phenotyped accessions. A genome-wide association study identified miR172D as a candidate for the vernalisation response. Gene expression marker association identified variation in expression of BoFLC.C2 as a further candidate for vernalisation response.

CONCLUSIONS

This study describes a new pipeline for performing associative transcriptomics studies in B. oleracea. Using flowering time as an example trait, it provides insights into the genetic basis of vernalisation response in B. oleracea through associative transcriptomics and confirms its characterisation as a complex G x E trait. Candidate leads were identified in miR172D and BoFLC.C2. These results could facilitate marker-based breeding efforts to produce B. oleracea lines with more synchronous heading dates, potentially leading to improved yields.

Molecular Tools for Adapting Viticulture to Climate Change

Adaptation of viticulture to climate change includes exploration of new geographical areas, new training systems, new management practices, or new varieties, both for rootstocks and scions. Molecular tools can be defined as molecular approaches used to study DNAs, RNAs, and proteins in all living organisms. We present here the current knowledge about molecular tools and their potential usefulness in three aspects of grapevine adaptation to the ongoing climate change. (i) Molecular tools for understanding grapevine response to environmental stresses. A fine description of the regulation of gene expression is a powerful tool to understand the physiological mechanisms set up by the grapevine to respond to abiotic stress such as high temperatures or drought. The current knowledge on gene expression is continuously evolving with increasing evidence of the role of alternative splicing, small RNAs, long non-coding RNAs, DNA methylation, or chromatin activity. (ii) Genetics and genomics of grapevine stress tolerance. The description of the grapevine genome is more and more precise. The genetic variations among genotypes are now revealed with new technologies with the sequencing of very long DNA molecules. High throughput technologies for DNA sequencing also allow now the genetic characterization at the same time of hundreds of genotypes for thousands of points in the genome, which provides unprecedented datasets for genotype-phenotype associations studies. We review the current knowledge on the genetic determinism of traits for the adaptation to climate change. We focus on quantitative trait loci and molecular markers available for developmental stages, tolerance to water stress/water use efficiency, sugar content, acidity, and secondary metabolism of the berries. (iii) Controlling the genome and its expression to allow breeding of better-adapted genotypes. High-density DNA genotyping can be used to select genotypes with specific interesting alleles but genomic selection is also a powerful method able to take into account the genetic information along the whole genome to predict a phenotype. Modern technologies are also able to generate mutations that are possibly interesting for generating new phenotypes but the most promising one is the direct editing of the genome at a precise location.

Heterosis and combining ability in cytoplasmic male sterile and doubled haploid based Brassica oleracea progenies and prediction of heterosis using microsatellites

In Brassica oleracea, heterosis is the most efficient tool providing impetus to hybrid vegetable industry. In this context, we presented the first report on identifying superior heterotic crosses for yield and commercial traits in cauliflower involving cytoplasmic male sterile (CMS) and doubled haploid (DH) lines as parents. We studied the suitability of genomic-SSRs and EST-SSRs based genetic distance (GD) and agronomic trait based phenotypic distance (PD) for predicting heterosis in F₁ hybrids using CMS and DH based parents. 120 F₁ hybrids derived from 20Ogura based CMS lines and 6 DH based testers were evaluated for 16 agronomic traits along with the 26 parental lines and 4 commercial standard checks. The genomic-SSRs and EST-SSRs based genetic structure analysis grouped the 26 parental lines into 4 distinct clusters. The CMS lines Ogu118-6A, Ogu33A, Ogu34-1A were good general combiner for developing early maturity hybrids. The SCA effects were significantly associated with heterosis suggesting non-additive gene effects for the heterotic response of hybrids. Less than unity value of σ²A/D coupled with σ²_gca/σ²_sca indicated the predominance of non-additive gene action in the expression of studied traits. The correlation analysis of genetic distance with heterosis for commercial traits suggested that microsatellites based genetic distance estimates can be helpful in heterosis prediction to some extent.

Translating Flowering Time From Arabidopsis thaliana to Brassicaceae and Asteraceae Crop Species

Flowering and seed set are essential for plant species to survive, hence plants need to adapt to highly variable environments to flower in the most favorable conditions. Endogenous cues such as plant age and hormones coordinate with the environmental cues like temperature and day length to determine optimal time for the transition from vegetative to reproductive growth. In a breeding context, controlling flowering time would help to speed up the production of new hybrids and produce high yield throughout the year. The flowering time genetic network is extensively studied in the plant model species Arabidopsis thaliana, however this knowledge is still limited in most crops. This article reviews evidence of conservation and divergence of flowering time regulation in A. thaliana with its related crop species in the Brassicaceae and with more distant vegetable crops within the Asteraceae family. Despite the overall conservation of most flowering time pathways in these families, many genes controlling this trait remain elusive, and the function of most Arabidopsis homologs in these crops are yet to be determined. However, the knowledge gathered so far in both model and crop species can be already exploited in vegetable crop breeding for flowering time control.