Advances in "Omics" Approaches for Improving Toxic Metals/Metalloids Tolerance in Plants.

Food safety has emerged as a high-urgency matter for sustainable agricultural production. Toxic metal contamination of soil and water significantly affects agricultural productivity, which is further aggravated by extreme anthropogenic activities and modern agricultural practices, leaving food safety and human health at risk. In addition to reducing crop production, increased metals/metalloids toxicity also disturbs plants' demand and supply equilibrium.

Differential Physio-Biochemical and Metabolic Responses of Peanut ( L.) under Multiple Abiotic Stress Conditions.

The frequency and severity of extreme climatic conditions such as drought, salinity, cold, and heat are increasing due to climate change. Moreover, in the field, plants are affected by multiple abiotic stresses simultaneously or sequentially. Thus, it is imperative to compare the effects of stress combinations on crop plants relative to individual stresses.

Analysis of Small RNA Sequencing Data in Plants.

Over the past decades, next-generation sequencing (NGS) has been employed extensively for investigating the regulatory mechanisms of small RNAs. Several bioinformatics tools are available for aiding biologists to extract meaningful information from enormous amounts of data generated by NGS platforms. This chapter describes a detailed methodology for analyzing small RNA sequencing data using different open source tools.

QTL-seq for the identification of candidate genes for days to flowering and leaf shape in pigeonpea.

To identify genomic segments associated with days to flowering (DF) and leaf shape in pigeonpea, QTL-seq approach has been used in the present study. Genome-wide SNP profiling of extreme phenotypic bulks was conducted for both the traits from the segregating population (F) derived from the cross combination- ICP 5529 × ICP 11605. A total of 126.

CRISPR/Cas9 gene editing and natural variation analysis demonstrate the potential for HvARE1 in improvement of nitrogen use efficiency in barley.

Nitrogen is a major determinant of grain yield and quality. As excessive use of nitrogen fertilizer leads to environmental pollution and high production costs, improving nitrogen use efficiency (NUE) is fundamental for a sustainable agriculture. Here, we dissected the role of the barley abnormal cytokinin response1 repressor 1 (HvARE1) gene, a candidate for involvement in NUE previously identified in a genome-wide association study, through natural variation analysis and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-mediated gene editing.

Phenotypic Evaluation and Genetic Analysis of Seedling Emergence in a Global Collection of Wheat Genotypes ( L.) Under Limited Water Availability.

The challenge in establishing an early-sown wheat crop in southern Australia is the need for consistently high seedling emergence when sowing deep in subsoil moisture (>10 cm) or into dry top-soil (4 cm). However, the latter is strongly reliant on a minimum soil water availability to ensure successful seedling emergence. This study aimed to: (1) evaluate 233 Australian and selected international wheat genotypes for consistently high seedling emergence under limited soil water availability when sown in 4 cm of top-soil in field and glasshouse (GH) studies; (2) ascertain genetic loci associated with phenotypic variation using a genome-wide association study (GWAS); and (3) compare across loci for traits controlling coleoptile characteristics, germination, dormancy, and pre-harvest sprouting.

A New Deep Learning Calibration Method Enhances Genome-Based Prediction of Continuous Crop Traits.

Genomic selection (GS) has the potential to revolutionize predictive plant breeding. A reference population is phenotyped and genotyped to train a statistical model that is used to perform genome-enabled predictions of new individuals that were only genotyped. In this vein, deep neural networks, are a type of machine learning model and have been widely adopted for use in GS studies, as they are not parametric methods, making them more adept at capturing nonlinear patterns.

Translational Chickpea Genomics Consortium to Accelerate Genetic Gains in Chickpea ( L.).

The Translational Chickpea Genomics Consortium (TCGC) was set up to increase the production and productivity of chickpea ( L.). It represents research institutes from six major chickpea growing states (Madhya Pradesh, Maharashtra, Andhra Pradesh, Telangana, Karnataka and Uttar Pradesh) of India.

Peanut Seed Coat Acts as a Physical and Biochemical Barrier against Infection.

Aflatoxin contamination is a global menace that adversely affects food crops and human health. Peanut seed coat is the outer layer protecting the cotyledon both at pre- and post-harvest stages from biotic and abiotic stresses. The aim of the present study is to investigate the role of seed coat against infection.

Genetic, Epigenetic, Genomic and Microbial Approaches to Enhance Salt Tolerance of Plants: A Comprehensive Review.

Globally, soil salinity has been on the rise owing to various factors that are both human and environmental. The abiotic stress caused by soil salinity has become one of the most damaging abiotic stresses faced by crop plants, resulting in significant yield losses. Salt stress induces physiological and morphological modifications in plants as a result of significant changes in gene expression patterns and signal transduction cascades.

Non-detection of mycoviruses in amphibian chytrid fungus (Batrachochytrium dendrobatidis) from Australia.

Mycoviruses may influence the pathogenicity of disease-causing fungi. Although mycoviruses have been found in some chytrid fungi, limited testing has not detected them in Batrachochytrium dendrobatidis (Bd), the cause of the devastating amphibian disease, chytridiomycosis. Here we conducted a survey for mycovirus presence in 38 Bd isolates from Australia (n = 31), Brazil (n = 5) and South Korea (n = 2) with a combination of modern high-throughput sequencing and conventional dsRNA cellulose chromatography.

Pangenomics in crop improvement-from coding structural variations to finding regulatory variants with pangenome graphs.

Since the first reported crop pangenome in 2014, advances in high-throughput and cost-effective DNA sequencing technologies facilitated multiple such studies including the pangenomes of oilseed rape (Brassica napus L.), soybean [Glycine max (L.) Merr.

Bayesian multitrait kernel methods improve multienvironment genome-based prediction.

When multitrait data are available, the preferred models are those that are able to account for correlations between phenotypic traits because when the degree of correlation is moderate or large, this increases the genomic prediction accuracy. For this reason, in this article, we explore Bayesian multitrait kernel methods for genomic prediction and we illustrate the power of these models with three-real datasets. The kernels under study were the linear, Gaussian, polynomial, and sigmoid kernels; they were compared with the conventional Ridge regression and GBLUP multitrait models.

Chromatin spatial organization of wild type and mutant peanuts reveals high-resolution genomic architecture and interaction alterations.

Background: Three-dimensional (3D) chromatin organization provides a critical foundation to investigate gene expression regulation and cellular homeostasis.

Results: Here, we present the first 3D genome architecture maps in wild type and mutant allotetraploid peanut lines, which illustrate A/B compartments, topologically associated domains (TADs), and widespread chromatin interactions. Most peanut chromosomal arms (52.

A chickpea genetic variation map based on the sequencing of 3,366 genomes.

Zero hunger and good health could be realized by 2030 through effective conservation, characterization and utilization of germplasm resources. So far, few chickpea (Cicer arietinum) germplasm accessions have been characterized at the genome sequence level. Here we present a detailed map of variation in 3,171 cultivated and 195 wild accessions to provide publicly available resources for chickpea genomics research and breeding.

Features and applications of haplotypes in crop breeding.

Climate change with altered pest-disease dynamics and rising abiotic stresses threatens resource-constrained agricultural production systems worldwide. Genomics-assisted breeding (GAB) approaches have greatly contributed to enhancing crop breeding efficiency and delivering better varieties. Fast-growing capacity and affordability of DNA sequencing has motivated large-scale germplasm sequencing projects, thus opening exciting avenues for mining haplotypes for breeding applications.

Differential Symptom Development and Viral RNA Loads in 10 Accessions Infected with the Tobamovirus Yellow Tailflower Mild Mottle Virus.

Yellow tailflower mild mottle virus (YTMMV, genus ) was identified from wild plants of solanaceous species in Australia. is a species indigenous to the arid north of Australia. accession RA-4 (the lab type), which has a mutant, functionally defective, RNA-dependent RNA polymerase 1 () gene (), has played a significant role in plant virology, but little study has been done regarding responses to virus infection by other accessions of .

Multivariate genomic analysis and optimal contributions selection predicts high genetic gains in cooking time, iron, zinc, and grain yield in common beans in East Africa.

Common bean (Phaseolus vulgaris L.) is important in African diets for protein, iron (Fe), and zinc (Zn), but traditional cultivars have long cooking time (CKT), which increases the time, energy, and health costs of cooking. Genomic selection was used to predict genomic estimated breeding values (GEBV) for grain yield (GY), CKT, Fe, and Zn in an African bean panel of 358 genotypes in a two-stage analysis.

Characterization of the Durum Wheat- 4D(4B) Disomic Substitution Line YL-443 With Superior Characteristics of High Yielding and Stripe Rust Resistance.

Durum wheat is one of the important food and cash crops. The main goals in current breeding programs are improving its low yield potential, kernel characteristics, and lack of resistance or tolerance to some biotic and abiotic stresses. In this study, a nascent synthesized hexaploid wheat Lanmai/AT23 is used as the female parent in crosses with its AB genome donor Lanmai.

The genetics of vigour-related traits in chickpea (Cicer arietinum L.): insights from genomic data.

QTL controlling vigour and related traits were identified in a chickpea RIL population and validated in diverse sets of germplasm. Robust KASP markers were developed for marker-assisted selection. To understand the genetic constitution of vigour in chickpea (Cicer arietinum L.

Reap the crop wild relatives for breeding future crops.

Crop wild relatives (CWRs) have provided breeders with several 'game-changing' traits or genes that have boosted crop resilience and global agricultural production. Advances in breeding and genomics have accelerated the identification of valuable CWRs for use in crop improvement. The enhanced genetic diversity of breeding pools carrying optimum combinations of favorable alleles for targeted crop-growing regions is crucial to sustain genetic gain.

Breeding custom-designed crops for improved drought adaptation.

The current pace of crop improvement is inadequate to feed the burgeoning human population by 2050. Higher, more stable, and sustainable crop production is required against a backdrop of drought stress, which causes significant losses in crop yields. Tailoring crops for drought adaptation may hold the key to address these challenges and provide resilient production systems for future harvests.

Fast-forward breeding for a food-secure world.

Crop production systems need to expand their outputs sustainably to feed a burgeoning human population. Advances in genome sequencing technologies combined with efficient trait mapping procedures accelerate the availability of beneficial alleles for breeding and research. Enhanced interoperability between different omics and phenotyping platforms, leveraged by evolving machine learning tools, will help provide mechanistic explanations for complex plant traits.