Fine Mapping of a Vigor QTL in Chickpea (Cicer arietinum L.) Reveals a Potential Role for Ca4_TIFY4B in Regulating Leaf and Seed Size

Unlocking protein-protein interactions in plants: a comprehensive review of established and emerging techniques

Protein-protein interactions orchestrate plant development and serve as crucial elements for cellular and environmental communication. Understanding these interactions offers a gateway to unravel complex protein networks that will allow a better understanding of nature. Methods for the characterization of protein-protein interactions have been around over 30 years, yet the complexity of some of these interactions has fueled the development of new techniques that provide a better understanding of the underlying dynamics. In many cases, the application of these techniques is limited by the nature of the available sample. While some methods require an in vivo set-up, others solely depend on protein sequences to study protein-protein interactions via an in silico set-up. The vast number of techniques available to date calls for a way to select the appropriate tools for the study of specific interactions. Here, we classify widely spread tools and new emerging techniques for the characterization of protein-protein interactions based on sample requirements while providing insights into the information that they can potentially deliver. We provide a comprehensive overview of commonly used techniques and elaborate on the most recent developments, showcasing their implementation in plant research.

Exploring novel SNPs and candidate genes associated with seed allometry in Pisum sativum L

Seed size is an important agronomic trait that indicates seed quality. In legumes, pods with equal and larger seeds remain the first preference of farmers and consumers. Genetic understanding related to seed size including seed allometric traits has been limited in the case of peas. To fill this void the findings presented here used the genome-wide association studies (GWAS) to identify novel candidate gene(s) putatively linked with seed size in Pisum sativum L. The study was conducted on 240 Pea Single Plant Plus Collection (PSPPC) panels of pea germplasm. Allometric traits measured included seed_length, seed_width, seed_thickness, seed_volume, seed_biomass, and seed_biomass by volume (SB_V). GWAS was performed using the Genome Association and Prediction Integrated Tool (GAPIT) on R-studio. The Bayesian information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) model provided significant single nucleotide polymorphisms (SNPs) linked with all the seed allometric traits. When analyzed the genomic regions of these SNPs provided a list of candidate genes that may be related to seed size. The present study thus provides a list of significant SNPs and relevant genes viz. Psat2g072000 for seed_length, Psat4g104320 for seed_width, Psat6g125800 and Psat6g125840 for seed_thickness, Psat6g228320 for seed_volume, Psat2g143920 for seed_biomass, and Psat2g120400 for SB_V which may prove useful in the improvement of pea seed size using breeding programs or CRISPR intervention. Understanding the genetic basis of seed size could lead to crop development with desirable seed characteristics, such as equal and larger-sized seeds with maximum yield and higher nutritional content.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-024-01499-6.

Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.

Genetic mapping and transcriptome profiling of a chickpea (Cicer arietinum L.) mutant identifies a novel locus (CaEl) regulating organ size and early vigor

Chickpea is among the top three legumes produced and consumed worldwide. Early plant vigor, characterized by good germination and rapid seedling growth, is an important agronomic trait in many crops including chickpea, and shows a positive correlation with seed size. In this study, we report a gamma-ray-induced chickpea mutant with a larger organ and seed size. The mutant (elm) exhibits increased early vigor and contains higher proline that contributes to a better tolerance under salt stress at germination, seedling, and early vegetative phase. The trait is governed as monogenic recessive, with wild-type allele being incompletely dominant over the mutant. Genetic mapping of this locus (CaEl) identified it as a previously uncharacterized gene (101503252) in chromosome 1 of the chickpea genome. There is a deletion of this gene in the mutant with a complete loss of expression. In silico analysis suggests that the gene is present as a single copy in chickpea and related legumes of the galegoid clade. In the mutant, cell division and expansion are affected. Transcriptome profiling identified differentially regulated transcripts related to cell division, expansion, cell wall organization, and metabolism in the mutant. The mutant can be exploited in chickpea breeding programs for increasing plant vigor and seed size.

The translatability of genetic networks from model to crop species: lessons from the past and perspectives for the future

Comparative analyses of growth-regulatory mechanisms between Arabidopsis and maize revealed that even when the gene space is conserved, the translation of knowledge from model species to crops is not trivial. Based on these insights, we formulate future opportunities to improve the interpretation of curiosity-driven research towards crop improvement.

Ensuring Global Food Security by Improving Protein Content in Major Grain Legumes Using Breeding and 'Omics' Tools

Grain legumes are a rich source of dietary protein for millions of people globally and thus a key driver for securing global food security. Legume plant-based 'dietary protein' biofortification is an economic strategy for alleviating the menace of rising malnutrition-related problems and hidden hunger. Malnutrition from protein deficiency is predominant in human populations with an insufficient daily intake of animal protein/dietary protein due to economic limitations, especially in developing countries. Therefore, enhancing grain legume protein content will help eradicate protein-related malnutrition problems in low-income and underprivileged countries. Here, we review the exploitable genetic variability for grain protein content in various major grain legumes for improving the protein content of high-yielding, low-protein genotypes. We highlight classical genetics-based inheritance of protein content in various legumes and discuss advances in molecular marker technology that have enabled us to underpin various quantitative trait loci controlling seed protein content (SPC) in biparental-based mapping populations and genome-wide association studies. We also review the progress of functional genomics in deciphering the underlying candidate gene(s) controlling SPC in various grain legumes and the role of proteomics and metabolomics in shedding light on the accumulation of various novel proteins and metabolites in high-protein legume genotypes. Lastly, we detail the scope of genomic selection, high-throughput phenotyping, emerging genome editing tools, and speed breeding protocols for enhancing SPC in grain legumes to achieve legume-based dietary protein security and thus reduce the global hunger risk.