Identification of candidate genes for dissecting complex branch number trait in chickpea

Triumphs of genomic-assisted breeding in crop improvement

Conventional breeding approaches have played a significant role in meeting the food demand remarkably well until now. However, the increasing population, yield plateaus in certain crops, and limited recombination necessitate using genomic resources for genomics-assisted crop improvement programs. As a result of advancements in the next-generation sequence technology, GABs have developed dramatically to characterize allelic variants and facilitate their rapid and efficient incorporation in crop improvement programs. Genomics-assisted breeding (GAB) has played an important role in harnessing the potential of modern genomic tools, exploiting allelic variation from genetic resources and developing cultivars over the past decade. The availability of pangenomes for major crops has been a significant development, albeit with varying degrees of completeness. Even though adopting these technologies is essentially determined on economic grounds and cost-effective assays, which create a wealth of information that can be successfully used to exploit the latent potential of crops. GAB has been instrumental in harnessing the potential of modern genomic resources and exploiting allelic variation for genetic enhancement and cultivar development. GAB strategies will be indispensable for designing future crops and are expected to play a crucial role in breeding climate-smart crop cultivars with higher nutritional value.

Genome-wide association study as a powerful tool for dissecting competitive traits in legumes

Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.

Exploring Chickpea Germplasm Diversity for Broadening the Genetic Base Utilizing Genomic Resourses

Legume crops provide significant nutrition to humans as a source of protein, omega-3 fatty acids as well as specific macro and micronutrients. Additionally, legumes improve the cropping environment by replenishing the soil nitrogen content. Chickpeas are the second most significant staple legume food crop worldwide behind dry bean which contains 17%–24% protein, 41%–51% carbohydrate, and other important essential minerals, vitamins, dietary fiber, folate, β-carotene, anti-oxidants, micronutrients (phosphorus, calcium, magnesium, iron, and zinc) as well as linoleic and oleic unsaturated fatty acids. Despite these advantages, legumes are far behind cereals in terms of genetic improvement mainly due to far less effort, the bottlenecks of the narrow genetic base, and several biotic and abiotic factors in the scenario of changing climatic conditions. Measures are now called for beyond conventional breeding practices to strategically broadening of narrow genetic base utilizing chickpea wild relatives and improvement of cultivars through advanced breeding approaches with a focus on high yield productivity, biotic and abiotic stresses including climate resilience, and enhanced nutritional values. Desirable donors having such multiple traits have been identified using core and mini core collections from the cultivated gene pool and wild relatives of Chickpea. Several methods have been developed to address cross-species fertilization obstacles and to aid in inter-specific hybridization and introgression of the target gene sequences from wild Cicer species. Additionally, recent advances in “Omics” sciences along with high-throughput and precise phenotyping tools have made it easier to identify genes that regulate traits of interest. Next-generation sequencing technologies, whole-genome sequencing, transcriptomics, and differential genes expression profiling along with a plethora of novel techniques like single nucleotide polymorphism exploiting high-density genotyping by sequencing assays, simple sequence repeat markers, diversity array technology platform, and whole-genome re-sequencing technique led to the identification and development of QTLs and high-density trait mapping of the global chickpea germplasm. These altogether have helped in broadening the narrow genetic base of chickpeas.

The key regulator LcERF056 enhances salt tolerance by modulating reactive oxygen species-related genes in Lotus corniculatus

BACKGROUND

The APETALA2/ethylene response factor (AP2/ERF) family are important regulatory factors involved in plants' response to environmental stimuli. However, their roles in salt tolerance in Lotus corniculatus remain unclear.

RESULTS

Here, the key salt-responsive transcription factor LcERF056 was cloned and characterised. LcERF056 belonging to the B3-1 (IX) subfamily of ERFs was considerably upregulated by salt treatment. LcERF056-fused GFP was exclusively localised to nuclei. Furthermore, LcERF056- overexpression (OE) transgenic Arabidopsis and L. corniculatus lines exhibited significantly high tolerance to salt treatment compared with wild-type (WT) or RNA interference expression (RNAi) transgenic lines at the phenotypic and physiological levels. Transcriptome analysis of OE, RNAi, and WT lines showed that LcERF056 regulated the downstream genes involved in several metabolic pathways. Chromatin immunoprecipitation-quantitative polymerase chain reaction (ChIP-qPCR) and yeast one-hybrid (Y1H) assay demonstrated that LcERF056 could bind to cis-element GCC box or DRE of reactive oxygen species (ROS)-related genes such as lipid-transfer protein, peroxidase and ribosomal protein.

CONCLUSION

Our results suggested that the key regulator LcERF056 plays important roles in salt tolerance in L. corniculatus by modulating ROS-related genes. Therefore, it may be a useful target for engineering salt-tolerant L. corniculatus or other crops.

Genomic Analysis of Vavilov's Historic Chickpea Landraces Reveals Footprints of Environmental and Human Selection

A defining challenge of the 21st century is meeting the nutritional demands of the growing human population, under a scenario of limited land and water resources and under the specter of climate change. The Vavilov seed bank contains numerous landraces collected nearly a hundred years ago, and thus may contain ‘genetic gems’ with the potential to enhance modern breeding efforts. Here, we analyze 407 landraces, sampled from major historic centers of chickpea cultivation and secondary diversification. Genome-Wide Association Studies (GWAS) conducted on both phenotypic traits and bioclimatic variables at landraces sampling sites as extended phenotypes resulted in 84 GWAS hits associated to various regions. The novel haploblock-based test identified haploblocks enriched for single nucleotide polymorphisms (SNPs) associated with phenotypes and bioclimatic variables. Subsequent bi-clustering of traits sharing enriched haploblocks underscored both non-random distribution of SNPs among several haploblocks and their association with multiple traits. We hypothesize that these clusters of pleiotropic SNPs represent co-adapted genetic complexes to a range of environmental conditions that chickpea experienced during domestication and subsequent geographic radiation. Linking genetic variation to phenotypic data and a wealth of historic information preserved in historic seed banks are the keys for genome-based and environment-informed breeding intensification.

Plant Inflorescence Architecture: The Formation, Activity, and Fate of Axillary Meristems

The above-ground plant body in different plant species can have very distinct forms or architectures that arise by recurrent redeployment of a finite set of building blocks-leaves with axillary meristems, stems or branches, and flowers. The unique architectures of plant inflorescences in different plant families and species, on which this review focuses, determine the reproductive success and yield of wild and cultivated plants. Major contributors to the inflorescence architecture are the activity and developmental trajectories adopted by axillary meristems, which determine the degree of branching and the number of flowers formed. Recent advances in genetic and molecular analyses in diverse flowering plants have uncovered both common regulatory principles and unique players and/or regulatory interactions that underlie inflorescence architecture. Modulating activity of these regulators has already led to yield increases in the field. Additional insight into the underlying regulatory interactions and principles will not only uncover how their rewiring resulted in altered plant form, but will also enhance efforts at optimizing plant architecture in desirable ways in crop species.

CLAVATA signaling pathway genes modulating flowering time and flower number in chickpea

A combinatorial genomic strategy delineated functionally relevant natural allele of a CLAVATA gene and its marker (haplotype)-assisted introgression led to development of the early-flowering chickpea cultivars with high flower number and enhanced yield/productivity. Unraveling the genetic components involved in CLAVATA (CLV) signaling is crucial for modulating important shoot apical meristem (SAM) characteristics and ultimately regulating diverse SAM-regulated agromorphological traits in crop plants. A genome-wide scan identified 142 CLV1-, 28 CLV2- and 6 CLV3-like genes, and their comprehensive genomic constitution and phylogenetic relationships were deciphered in chickpea. The QTL/fine mapping and map-based cloning integrated with high-resolution association analysis identified SNP loci from CaCLV3_01 gene within a major CaqDTF1.1/CaqFN1.1 QTL associated with DTF (days to 50% flowering) and FN (flower number) traits in chickpea, which was further ascertained by quantitative expression profiling. Molecular haplotyping of CaCLV3_01 gene, expressed specifically in SAM, constituted two major haplotypes that differentiated the early-DTF and high-FN chickpea accessions from late-DTF and low-FN. Enhanced accumulation of transcripts of superior CaCLV3_01 gene haplotype and known flowering promoting genes was observed in the corresponding haplotype-introgressed early-DTF and high-FN near-isogenic lines (NILs) with narrow SAM width. The superior haplotype-introgressed NILs exhibited early-flowering, high-FN and enhanced seed yield/productivity without compromising agronomic performance. These delineated molecular signatures can regulate DTF and FN traits through SAM proliferation and differentiation and thereby will be useful for translational genomic study to develop early-flowering cultivars with enhanced yield/productivity.

Genome-wide cis-regulatory signatures for modulation of agronomic traits as exemplified by drought yield index (DYI) in chickpea

Developing functional molecular tags from the cis-regulatory sequence components of genes is vital for their deployment in efficient genetic dissection of complex quantitative traits in crop plants including chickpea. The current study identified 431,194 conserved non-coding SNP (CNSNP) from the cis-regulatory element regions of genes which were annotated on a chickpea genome. These genome-wide CNSNP marker resources are made publicly accessible through a user-friendly web-database ( http://www.cnsnpcicarbase.com ). The CNSNP-based quantitative trait loci (QTL) and expression QTL (eQTL) mapping and genome-wide association study (GWAS) were further integrated with global gene expression landscapes, molecular haplotyping, and DNA-protein interaction study in the association panel and recombinant inbred lines (RIL) mapping population to decode complex genetic architecture of one of the vital seed yield trait under drought stress, drought yield index (DYI), in chickpea. This delineated two constituted natural haplotypes and alleles from a histone H3 protein-coding gene and its transcriptional regulator NAC transcription factor (TF) harboring the major QTLs and trans-acting eQTL governing DYI in chickpea. The effect of CNSNPs in TF-binding cis-element of a histone H3 gene in altering the binding affinity and transcriptional activity of NAC TF based on chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) assay was evident. The CNSNP-led promising molecular tags scanned will essentially have functional significance to decode transcriptional gene regulatory function and thus can drive translational genomic analysis in chickpea.

Genome-wide generation and genotyping of informative SNPs to scan molecular signatures for seed yield in chickpea

We discovered 2150 desi and 2199 kabuli accessions-derived SNPs by cultivar-wise individual assembling of sequence-reads generated through genotyping-by-sequencing of 92 chickpea accessions. Subsequent large-scale validation and genotyping of these SNPs discovered 619 desi accessions-derived (DAD) SNPs, 531 kabuli accessions-derived (KAD) SNPs, 884 multiple accessions-derived (MAD) SNPs and 1083 two accessions (desi ICC 4958 and kabuli CDC Frontier)-derived (TAD) SNPs that were mapped on eight chromosomes. These informative SNPs were annotated in coding/non-coding regulatory sequence components of genes. The MAD-SNPs were efficient to detect high intra-specific polymorphic potential and wide natural allelic diversity level including high-resolution admixed-population genetic structure and precise phylogenetic relationship among 291 desi and kabuli accessions. This signifies their effectiveness in introgression breeding and varietal improvement studies targeting useful agronomic traits of chickpea. Six trait-associated genes with SNPs including quantitative trait nucleotides (QTNs) in combination explained 27.5% phenotypic variation for seed yield per plant (SYP). A pentatricopeptide repeat (PPR) gene with a synonymous-coding SNP/QTN significantly associated with SYP trait was found most-promising in chickpea. The essential information delineated can be of immense utility in genomics-assisted breeding applications to develop high-yielding chickpea cultivars.

Current advances in chickpea genomics: applications and future perspectives

Chickpea genomics promises to illuminate our understanding of genome organization, structural variations, evolutionary and domestication-related insights and fundamental biology of legume crops. Unprecedented advancements of next generation sequencing (NGS) technologies have enabled in decoding of multiple chickpea genome sequences and generating huge genomic resources in chickpea both at functional and structural level. This review is aimed to update the current progress of chickpea genomics ranging from high density linkage map development, genome-wide association studies (GWAS), functional genomics resources for various traits, emerging role of abiotic stress responsive coding and non-coding RNAs after the completion of draft chickpea genome sequences. Additionally, the current efforts of whole genome re-sequencing (WGRS) approach of global chickpea germplasm to capture the global genetic diversity existing in the historically released varieties across the world and increasing the resolution of the previously identified candidate gene(s) of breeding importance have been discussed. Thus, the outcomes of these genomics resources will assist in genomics-assisted selection and facilitate breeding of climate-resilient chickpea cultivars for sustainable agriculture.

Genetic dissection of plant growth habit in chickpea

A combinatorial genomics-assisted breeding strategy encompassing association analysis, genetic mapping and expression profiling is found most promising for quantitative dissection of complex traits in crop plants. The present study employed GWAS (genome-wide association study) using 24,405 SNPs (single nucleotide polymorphisms) obtained with genotyping-by-sequencing (GBS) of 92 sequenced desi and kabuli accessions of chickpea. This identified eight significant genomic loci associated with erect (E)/semi-erect (SE) vs. spreading (S)/semi-spreading (SS)/prostrate (P) plant growth habit (PGH) trait differentiation regardless of diverse desi and kabuli genetic backgrounds of chickpea. These associated SNPs in combination explained 23.8% phenotypic variation for PGH in chickpea. Five PGH-associated genes were validated successfully in E/SE and SS/S/P PGH-bearing parental accessions and homozygous individuals of three intra- and interspecific RIL (recombinant inbred line) mapping populations as well as 12 contrasting desi and kabuli chickpea germplasm accessions by selective genotyping through Sequenom MassARRAY. The shoot apical, inflorescence and floral meristems-specific expression, including upregulation (seven-fold) of five PGH-associated genes especially in germplasm accessions and homozygous RIL mapping individuals contrasting with E/SE PGH traits was apparent. Collectively, this integrated genomic strategy delineated diverse non-synonymous SNPs from five candidate genes with strong allelic effects on PGH trait variation in chickpea. Of these, two vernalization-responsive non-synonymous SNP alleles carrying SNF2 protein-coding gene and B3 transcription factor associated with PGH traits were found to be the most promising in chickpea. The SNP allelic variants associated with E/SE/SS/S PGH trait differentiation were exclusively present in all cultivated desi and kabuli chickpea accessions while wild species/accessions belonging to primary, secondary and tertiary gene pools mostly contained prostrate PGH-associated SNP alleles. This indicates strong adaptive natural/artificial selection pressure (Tajima's D 3.15 to 4.57) on PGH-associated target genomic loci during chickpea domestication. These vital leads thus have potential to decipher complex transcriptional regulatory gene function of PGH trait differentiation and for understanding the selective sweep-based PGH trait evolution and domestication pattern in cultivated and wild chickpea accessions adapted to diverse agroclimatic conditions. Collectively, the essential inputs generated will be of profound use in marker-assisted genetic enhancement to develop cultivars with desirable plant architecture of erect growth habit types in chickpea.

Regional Association Analysis of MetaQTLs Delineates Candidate Grain Size Genes in Rice

Molecular mapping studies which aim to identify genetic basis of diverse agronomic traits are vital for marker-assisted crop improvement. Numerous Quantitative Trait Loci (QTLs) mapped in rice span long genomic intervals with hundreds to thousands of genes, which limits their utilization for marker-assisted genetic enhancement of rice. Although potent, fine mapping of QTLs is challenging task as it requires screening of large number of segregants to identify suitable recombination events. Association mapping offers much higher resolution as compared to QTL mapping, but detects considerable number of spurious QTLs. Therefore, combined use of QTL and association mapping strategies can provide advantages associated with both these methods. In the current study, we utilized meta-analysis approach to identify metaQTLs associated with grain size/weight in diverse Indian indica and aromatic rice accessions. Subsequently, attempt has been made to narrow-down identified grain size/weight metaQTLs through individual SNP- as well as haplotype-based regional association analysis. The study identified six different metaQTL regions, three of which were successfully revalidated, and substantially scaled-down along with GS3 QTL interval (positive control) by regional association analysis. Consequently, two potential candidate genes within two reduced metaQTLs were identified based on their differential expression profiles in different tissues/stages of rice accessions during seed development. The developed strategy has broader practical utility for rapid delineation of candidate genes and natural alleles underlying QTLs associated with complex agronomic traits in rice as well as major crop plants enriched with useful genetic and genomic information.