Evaluation and Multivariate Analysis of Cowpea [Vigna unguiculata (L.) Walp] Germplasm for Selected Nutrients—Mining for Nutri-Dense Accessions

A total of 120 highly diverse cowpea [Vigna unguiculata (L.) Walp] genotypes, including indigenous and exotic lines, were evaluated for different biochemical traits using AOAC official methods of analysis and other standard methods. The results exhibited wide variability in the content of proteins (ranging from 19.4 to 27.9%), starch (from 27.5 to 42.7 g 100 g−1), amylose (from 9.65 to 21.7 g 100 g−1), TDF (from 13.7 to 21.1 g 100 g−1), and TSS (from 1.30 to 8.73 g 100 g−1). The concentration of anti-nutritional compounds like phenols and phytic acid ranged from 0.026 to 0.832 g 100 g−1 and 0.690 to 1.88 g 100 g−1, respectively. The correlation coefficient between the traits was calculated to understand the inter-trait relationship. Multivariate analysis (PCA and HCA) was performed to identify the major traits contributing to variability and group accessions with a similar profile. The first three principal components, i.e., PC1, PC2, and PC3, contributed to 62.7% of the variation, where maximum loadings were from starch, followed by protein, phytic acid, and dietary fiber. HCA formed six distinct clusters at a squared Euclidean distance of 5. Accessions in cluster I had high TDF and low TSS content, while cluster II was characterized by low amylose content. Accessions in cluster III had high starch, low protein, and phytic acid, whereas accessions in cluster IV contained high TSS, phenol, and low phytic acid. Cluster V was characterized by high protein, phytic acid, TSS, and phenol content and low starch content, and cluster VI had a high amount of amylose and low phenol content. Some nutri-dense accessions were identified from the above-mentioned clusters, such as EC169879 and IC201086 with high protein (>27%), TSS, amylose, and TDF content. These compositions are promising to provide practical support for developing high-value food and feed varieties using effective breeding strategies with a higher economic value

Genetic dissection of thousand-seed weight in linseed (Linum usitatissimum L.) using multi-locus genome-wide association study

Flaxseed/linseed is an important oilseed crop having applications in the food, nutraceutical, and paint industry. Seed weight is one of the most crucial determinants of seed yield in linseed. Here, quantitative trait nucleotides (QTNs) associated with thousand-seed weight (TSW) have been identified using multi-locus genome-wide association study (ML-GWAS). Field evaluation was carried out in five environments in multi-year-location trials. SNP genotyping information of the AM panel of 131 accessions comprising 68,925 SNPs was employed for ML-GWAS. From the six ML-GWAS methods employed, five methods helped identify a total of 84 unique significant QTNs for TSW. QTNs identified in ≥ 2 methods/environments were designated as stable QTNs. Accordingly, 30 stable QTNs have been identified for TSW accounting up to 38.65% trait variation. Alleles with positive effect on trait were analyzed for 12 strong QTNs with r2 ≥ 10.00%, which showed significant association of specific alleles with higher trait value in three or more environments. A total of 23 candidate genes have been identified for TSW, which included B3 domain-containing transcription factor, SUMO-activating enzyme, protein SCARECROW, shaggy-related protein kinase/BIN2, ANTIAUXIN-RESISTANT 3, RING-type E3 ubiquitin transferase E4, auxin response factors, WRKY transcription factor, and CBS domain-containing protein. In silico expression analysis of candidate genes was performed to validate their possible role in different stages of seed development process. The results from this study provide significant insight and elevate our understanding on genetic architecture of TSW trait in linseed

Development and optimization of NIRS prediction models for simultaneous multi-trait assessment in diverse cowpea germplasm

Cowpea (Vigna unguiculata (L.) Walp.) is one such legume that can facilitate achieving sustainable nutrition and climate change goals. Assessing nutritional traits conventionally can be laborious and time-consuming. NIRS is a technique used to rapidly determine biochemical parameters for large germplasm. NIRS prediction models were developed to assess protein, starch, TDF, phenols, and phytic acid based on MPLS regression. Higher RSQexternal values such as 0.903, 0.997, 0.901, 0.706, and 0.955 were obtained for protein, starch, TDF, phenols, and phytic acid respectively. Models for all the traits displayed RPD values of >2.5 except phenols and low SEP indicating the excellent prediction of models. For all the traits worked, p-value ≥ 0.05 implied the accuracy and reliability score >0.8 (except phenol) ensured the applicability of the models. These prediction models will facilitate high throughput screening of large cowpea germplasm in a non-destructive way and the selection of desirable chemotypes in any genetic background with huge application in cowpea crop improvement programs across the world

Rice mitogen activated protein kinase kinase and mitogen activated protein kinase interaction network revealed by in-silico docking and yeast two-hybrid approaches.

Protein-protein interaction is one of the crucial ways to decipher the functions of proteins and to understand their role in complex pathways at cellular level. Such a protein-protein interaction network in many crop plants remains poorly defined owing largely to the involvement of high costs, requirement for state of the art laboratory, time and labour intensive techniques. Here, we employed computational docking using ZDOCK and RDOCK programmes to identify interaction network between members of Oryza sativa mitogen activated protein kinase kinase (MAPKK) and mitogen activated protein kinase (MAPK). The 3-dimentional (3-D) structures of five MAPKKs and eleven MAPKs were determined by homology modelling and were further used as input for docking studies. With the help of the results obtained from ZDOCK and RDOCK programmes, top six possible interacting MAPK proteins were predicted for each MAPKK. In order to assess the reliability of the computational prediction, yeast two-hybrid (Y2H) analyses were performed using rice MAPKKs and MAPKs. A direct comparison of Y2H assay and computational prediction of protein interaction was made. With the exception of one, all the other MAPKK-MAPK pairs identified by Y2H screens were among the top predictions by computational dockings. Although, not all the predicted interacting partners could show interaction in Y2H, yet, the harmony between the two approaches suggests that the computational predictions in the present work are reliable. Moreover, the present Y2H analyses per se provide interaction network among MAPKKs and MAPKs which would shed more light on MAPK signalling network in rice

ZDOCK and RDOCK score of OsMKK5 against each of eleven rice MAPKs.

<p>E_R – Energy RDOCK score. Lower values of ZRANK score and E_RDOCK and higher ZDOCK score indicate top/better docking of the complex. Clash ‘0′ indicates no stearic clash between the proteins after refinement by RDOCK protocol.</p

Genome-Wide Identification and Characterization of Trihelix Gene Family in Asian and African <i>Vigna</i> Species

Trihelix transcription factors play a crucial role in varied stress responses as well as in the growth and development of plants. The role of trihelix transcription factors in the non-shattering phenotype in domesticated rice is known. The Vigna group of crops has different degrees of shattering phenotypes in different species. To understand the evolutionary conservation or divergence of the trihelix gene family in important Vigna species here, the genome-wide identification and characterization of the trihelix gene family in four Vigna species including the cowpea (Vigna unguiculata), mung bean (V. radiata), adzuki bean (V. angularis) and rice bean (V. umbellata) was performed. A total of 39, 35, 41 and 50 trihelix genes were identified in the cowpea, mung bean, adzuki bean and rice bean, respectively. The trihelix genes in each of the four Vigna species were classified into five subgroups: GT, GTγ, SH4, S1P1 and GTδ. The members of each subgroup shared similar patterns of gene structure and motif across the four species. The cross-species positional relationships of the cowpea, adzuki bean and mung bean vis-a-vis rice trihelix genes were studied. Further, the Ka/Ks ratio for the trihelix genes in the four Vigna species indicated the purifying or stabilizing selection of the family. The gene expression analysis of the trihelix gene family in the cowpea showed that most of the genes express in at least some of the seed and/or pod developmental stages, although at varying degrees. Based on detailed bioinformatic analysis, a potential target for gene editing towards a possible non-shattering phenotype in the four important Vigna crops was discussed

Ramachandran plot analysis of theoretical 3D structure of rice MAPKKs and MAPKs.

<p>The 3D Structures of eleven rice MAP kinases (OsMPK3, OsMPK4, OsMPK6, OsMPK7, OsMPK14, OsMPK16-1, OsMPK17-1, OsMPK20-2, OsMPK20-3, OsMPK20-5 and OsMPK21-2) and five MAP kinase kinases (OsMKK3, OsMKK4, OsMKK5, OsMKK6, OsMKK10-2) were validated using Ramachandran plot. The green dots/yellow dots show the amino acids that are in the most favoured regions and additionally allowed region while red dots show the amino acids that are in generously allowed region or disallowed regions. The regions covered by sky blue line show most favoured regions, while the regions covered by pink line show additionally allowed regions. Other regions of the plot show the generously allowed or disallowed region.</p