Haplotype-based breeding: A new insight in crop improvement.

Haplotype-based breeding (HBB) is one of the cutting-edge technologies in the realm of crop improvement due to the increasing availability of Single Nucleotide Polymorphisms identified by Next Generation Sequencing technologies. The complexity of the data can be decreased with fewer statistical tests and a lower probability of spurious associations by combining thousands of SNPs into a few hundred haplotype blocks. The presence of strong genomic regions in breeding lines of most crop species facilitates the use of haplotypes to improve the efficiency of genomic and marker-assisted selection. Haplotype-based breeding as a Genomic Assisted Breeding (GAB) approach harnesses the genome sequence data to pinpoint the allelic variation used to hasten the breeding cycle and circumvent the challenges associated with linkage drag. This review article demonstrates ways to identify candidate genes, superior haplotype identification, haplo-pheno analysis, and haplotype-based marker-assisted selection. The crop improvement strategies that utilize superior haplotypes will hasten the breeding progress to safeguard global food security.

Pilot-scale genome-wide association mapping in diverse sorghum germplasms identified novel genetic loci linked to major agronomic, root and stomatal traits.

This genome-wide association studies (GWAS) used a subset of 96 diverse sorghum accessions, constructed from a large collection of 219 accessions for mining novel genetic loci linked to major agronomic, root morphological and physiological traits. The subset yielded 43,452 high quality single nucleotide polymorphic (SNP) markers exhibiting high allelic diversity. Population stratification showed distinct separation between caudatum and durra races. Linkage disequilibrium (LD) decay was rapidly declining with increasing physical distance across all chromosomes. The initial 50% LD decay was ~ 5 Kb and background level was within ~ 80 Kb. This study detected 42 significant quantitative trait nucleotide (QTNs) for different traits evaluated using FarmCPU, SUPER and 3VmrMLM which were in proximity with candidate genes related and were co-localized in already reported quantitative trait loci (QTL) and phenotypic variance (R2) of these QTNs ranged from 3 to 20%. Haplotype validation of the candidate genes from this study resulted nine genes showing significant phenotypic difference between different haplotypes. Three novel candidate genes associated with agronomic traits were validated including Sobic.001G499000, a potassium channel tetramerization domain protein for plant height, Sobic.010G186600, a nucleoporin-related gene for dry biomass, and Sobic.002G022600 encoding AP2-like ethylene-responsive transcription factor for plant yield. Several other candidate genes were validated and associated with different root and physiological traits including Sobic.005G104100, peroxidase 13-related gene with root length, Sobic.010G043300, homologous to Traes_5BL_8D494D60C, encoding inhibitor of apoptosis with iWUE, and Sobic.010G125500, encoding zinc finger, C3HC4 type domain with Abaxial stomatal density. In this study, 3VmrMLM was more powerful than FarmCPU and SUPER for detecting QTNs and having more breeding value indicating its reliable output for validation. This study justified that the constructed subset of diverse sorghums can be used as a panel for mapping other key traits to accelerate molecular breeding in sorghum.

Plant Metabolomics: Current Initiatives and Future Prospects.

Plant metabolomics is a rapidly advancing field of plant sciences and systems biology. It involves comprehensive analyses of small molecules (metabolites) in plant tissues and cells. These metabolites include a wide range of compounds, such as sugars, amino acids, organic acids, secondary metabolites (e.g., alkaloids and flavonoids), lipids, and more. Metabolomics allows an understanding of the functional roles of specific metabolites in plants' physiology, development, and responses to biotic and abiotic stresses. It can lead to the identification of metabolites linked with specific traits or functions. Plant metabolic networks and pathways can be better understood with the help of metabolomics. Researchers can determine how plants react to environmental cues or genetic modifications by examining how metabolite profiles change under various crop stages. Metabolomics plays a major role in crop improvement and biotechnology. Integrating metabolomics data with other omics data (genomics, transcriptomics, and proteomics) provides a more comprehensive perspective of plant biology. This systems biology approach enables researchers to understand the complex interactions within organisms.

Molecular characterization and SNP identification using genotyping-by-sequencing in high-yielding mutants of proso millet.

Proso millet (Panicummiliaceum L.) is a short-duration C4 crop that is drought tolerant and nutritionally rich and can grow well in marginal lands. Though the crop has many climate-resilient traits like tolerance to drought and heat, its yield is lower than that of common cereals like rice, wheat, and maize. Being an underutilized crop, the molecular resources in the crop are limited. The main aim of the present study was to develop and characterize contrasting mutants for yield and generate functional genomic information for the trait in proso millet. Gamma irradiation-induced mutant population was screened to identify high-yielding mutants, which were evaluated up to M4 generation. One mutant with a dense panicle and high yield (ATL_hy) and one with a lax panicle and low yield (ATL_ly) along with the wild type were sequenced using the genotyping-by-sequencing approach. The variants detected as single nucleotide polymorphisms (SNPs) and insertions-deletions (InDels) were annotated against the reference genome of proso millet. Bioinformatic analyses using the National Center for Biotechnology Information (NCBI) and UniProt databases were performed to elucidate genetic information related to the SNP variations. A total of 25,901, 30,335, and 31,488 SNPs, respectively, were detected in the wild type, ATL_hy mutants, and ATL_ly mutants. The total number of functional SNPs identified in high-yielding and low-yielding mutants was 84 and 171, respectively. Two functional SNPs in the high-yielding mutant (ATL_hy) and one in the low-yielding mutant (ATL_ly) corresponded to the gene coding for "E3 ubiquitin-protein ligase UPL7". Pathway mapping of the functional SNPs identified that two SNPs in ATL_ly were involved in the starch biosynthetic pathway coding for the starch synthase enzyme. This information can be further used in identifying genes responsible for various metabolic processes in proso millet and in designing useful genetic markers.

Altering Stomatal Density for Manipulating Transpiration and Photosynthetic Traits in Rice through CRISPR/Cas9 Mutagenesis.

Stomata regulates conductance, transpiration and photosynthetic traits in plants. Increased stomatal density may contribute to enhanced water loss and thereby help improve the transpirational cooling process and mitigate the high temperature-induced yield losses. However, genetic manipulation of stomatal traits through conventional breeding still remains a challenge due to problems involved in phenotyping and the lack of suitable genetic materials. Recent advances in functional genomics in rice identified major effect genes determining stomatal traits, including its number and size. Widespread applications of CRISPR/Cas9 in creating targeted mutations paved the way for fine tuning the stomatal traits for enhancing climate resilience in crops. In the current study, attempts were made to create novel alleles of OsEPF1 (Epidermal Patterning Factor), a negative regulator of stomatal frequency/density in a popular rice variety, ASD 16, using the CRISPR/Cas9 approach. Evaluation of 17 T0 progenies identified varying mutations (seven multiallelic, seven biallelic and three monoallelic mutations). T0 mutant lines showed a 3.7-44.3% increase in the stomatal density, and all the mutations were successfully inherited into the T1 generation. Evaluation of T1 progenies through sequencing identified three homozygous mutants for one bp insertion. Overall, T1 plants showed 54-95% increased stomatal density. The homozygous T1 lines (# E1-1-4, # E1-1-9 and # E1-1-11) showed significant increase in the stomatal conductance (60-65%), photosynthetic rate (14-31%) and the transpiration rate (58-62%) compared to the nontransgenic ASD 16. Results demonstrated that the genetic alterations in OsEPF1 altered the stomatal density, stomatal conductance and photosynthetic efficiency in rice. Further experiments are needed to associate this technology with canopy cooling and high temperature tolerance.

Comparative Metabolomics Profiling Reveals Key Metabolites and Associated Pathways Regulating Tuber Dormancy in White Yam (Dioscorea rotundata Poir.).

Yams are economic and medicinal crops with a long growth cycle, spanning between 9-11 months due to their prolonged tuber dormancy. Tuber dormancy has constituted a major constraint in yam production and genetic improvement. In this study, we performed non-targeted comparative metabolomic profiling of tubers of two white yam genotypes, (Obiaoturugo and TDr1100873), to identify metabolites and associated pathways that regulate yam tuber dormancy using gas chromatography-mass spectrometry (GC-MS). Yam tubers were sampled between 42 days after physiological maturity (DAPM) till tuber sprouting. The sampling points include 42-DAPM, 56-DAPM, 87DAPM, 101-DAPM, 115-DAPM, and 143-DAPM. A total of 949 metabolites were annotated, 559 in TDr1100873 and 390 in Obiaoturugo. A total of 39 differentially accumulated metabolites (DAMs) were identified across the studied tuber dormancy stages in the two genotypes. A total of 27 DAMs were conserved between the two genotypes, whereas 5 DAMs were unique in the tubers of TDr1100873 and 7 DAMs were in the tubers of Obiaoturugo. The differentially accumulated metabolites (DAMs) spread across 14 major functional chemical groups. Amines and biogenic polyamines, amino acids and derivatives, alcohols, flavonoids, alkaloids, phenols, esters, coumarins, and phytohormone positively regulated yam tuber dormancy induction and maintenance, whereas fatty acids, lipids, nucleotides, carboxylic acids, sugars, terpenoids, benzoquinones, and benzene derivatives positively regulated dormancy breaking and sprouting in tubers of both yam genotypes. Metabolite set enrichment analysis (MSEA) revealed that 12 metabolisms were significantly enriched during yam tuber dormancy stages. Metabolic pathway topology analysis further revealed that six metabolic pathways (linoleic acid metabolic pathway, phenylalanine metabolic pathway, galactose metabolic pathway, starch and sucrose metabolic pathway, alanine-aspartate-glutamine metabolic pathways, and purine metabolic pathway) exerted significant impact on yam tuber dormancy regulation. This result provides vital insights into molecular mechanisms regulating yam tuber dormancy.

Complete Genome Sequence Analysis of Bacillus subtilis Bbv57, a Promising Biocontrol Agent against Phytopathogens.

Plant growth-promoting rhizobacteria (PGPR) are a group of root-associated beneficial bacteria emerging as one of the powerful agents in sustainable plant disease management. Among the PGPR, Bacillus sp. has become a popular biocontrol agent for controlling pests and the diseases of several crops of agricultural and horticultural importance. Understanding the molecular basis of the plant growth-promoting and biocontrol abilities of Bacillus spp. will allow us to develop multifunctional microbial consortia for sustainable agriculture. In our study, we attempted to unravel the genome complexity of the potential biocontrol agent Bacillus subtilis Bbv57 (isolated from the betelvine's rhizosphere), available at TNAU, Coimbatore. A WGS analysis generated 26 million reads, and a de novo assembly resulted in the generation of 4,302,465 bp genome of Bacillus subtilis Bbv57 containing 4363 coding sequences (CDS), of which 4281 were functionally annotated. An analysis of 16S rRNA revealed its 100% identity to Bacillus subtilis IAM 12118. A detailed data analysis identified the presence of >100 CAZymes and nine gene clusters involved in the production of secondary metabolites that exhibited antimicrobial properties. Further, Bbv57 was found to harbor 282 unique genes in comparison with 19 other Bacillus strains, requiring further exploration.

A Comparative Metabolomic Analysis Reveals the Nutritional and Therapeutic Potential of Grains of the Traditional Rice Variety Mappillai Samba.

Rice (Oryza sativa L.) is the staple food of the majority of the population, particularly in Asia and Africa. Enriching rice with nutritional and therapeutic contents can improve its benefits for patients with lifestyle disorders. This study aimed to profile the phytochemical contents of the therapeutically known traditional rice Mappillai Samba against white rice CBMAS 14065 using non-targeted gas chromatography-mass spectrometry (GC-MS/MS). An analysis of the data using a mass spectrometry-data independent analysis (MS-DIAL) and MetaboAnalyst identified 113 metabolites belonging to 21 different classes of metabolites. A partial least square-discriminant analysis (PLS-DA) revealed 43 variable importance in projection (VIP) metabolites. This study identified therapeutically important metabolites, including phenylpropanoids, phytosterols, flavonoids, and polyamines, in the grains of Mappillai Samba. Three significant metabolic pathways, viz., phenylpropanoid biosynthesis, ubiquinone and other terpenoid-quinone biosynthesis, and steroid biosynthesis, were responsible for the grain metabolome variation between CBMAS 14065 and Mappillai Samba. Overall, the results of this study unravelled the biochemical complexity of Mappillai Samba, paving the way for the genetic mapping of the therapeutic compound accumulation in rice and the development of similar therapeutic rice varieties through molecular breeding.

Prevalence, Patterns, and Genetic Association Analysis of Modic Vertebral Endplate Changes.

STUDY DESIGN: A prospective genetic association study. PURPOSE: The etiology of Modic changes (MCs) is unclear. Recently, the role of genetic factors in the etiology of MCs has been evaluated. However, studies with a larger patient subset are lacking, and candidate genes involved in other disc degeneration phenotypes have not been evaluated. We studied the prevalence of MCs and genetic association of 41 candidate genes in a large Indian cohort. OVERVIEW OF LITERATURE: MCs are vertebral endplate signal changes predominantly observed in the lumbar spine. A significant association between MCs and lumbar disc degeneration and nonspecific low back pain has been described, with the etiopathogenesis implicating various mechanical, infective, and biochemical factors. METHODS: We studied 809 patients using 1.5-T magnetic resonance imaging to determine the prevalence, patterns, distribution, and type of lumbar MCs. Genetic association analysis of 71 single nucleotide polymorphisms (SNPs) of 41 candidate genes was performed based on the presence or absence of MCs. SNPs were genotyped using the Sequenome platform, and an association test was performed using PLINK software. RESULTS: The mean age of the study population (n=809) was 36.7±10.8 years. Based on the presence of MCs, the cohort was divided into 702 controls and 107 cases (prevalence, 13%). MCs were more commonly present in the lower (149/251, 59.4%) than in the upper (102/251, 40.6%) endplates. L4-5 endplates were the most commonly affected levels (30.7%). Type 2 MCs were the most commonly observed pattern (n=206, 82%). The rs2228570 SNP of VDR (p=0.02) and rs17099008 SNP of MMP20 (p=0.03) were significantly associated with MCs. CONCLUSIONS: Genetic polymorphisms of SNPs of VDR and MMP20 were significantly associated with MCs. Understanding the etiopathogenetic mechanisms of MCs is important for planning preventive and therapeutic strategies.