Genetics of a diverse soft winter wheat population for pre-harvest sprouting, agronomic, and flour quality traits

Soft winter wheat has been adapted to the north-central, north-western, and south-central United States over hundreds of years for optimal yield, height, heading date, and pathogen and pest resistance. Environmental factors like weather affect abiotic traits such as pre-harvest sprouting resistance. However, pre-harvest sprouting has rarely been a target for breeding. Owing to changing weather patterns from climate change, pre-harvest sprouting resistance is needed to prevent significant crop losses not only in the United States, but worldwide. Twenty-two traits including age of breeding line as well as agronomic, flour quality, and pre-harvest sprouting traits were studied in a population of 188 lines representing genetic diversity over 200 years of soft winter wheat breeding. Some traits were correlated with one another by principal components analysis and Pearson's correlations. A genome-wide association study using 1,978 markers uncovered a total of 102 regions encompassing 226 quantitative trait nucleotides. Twenty-six regions overlapped multiple traits with common significant markers. Many of these traits were also found to be correlated by Pearson's correlation and principal components analyses. Most pre-harvest sprouting regions were not co-located with agronomic traits and thus useful for crop improvement against climate change without affecting crop performance. Six different genome-wide association statistical models (GLM, MLM, MLMM, FarmCPU, BLINK, and SUPER) were utilized to search for reasonable models to analyze soft winter wheat populations with increased markers and/or breeding lines going forward. Some flour quality and agronomic traits seem to have been selected over time, but not pre-harvest sprouting. It appears possible to select for pre-harvest sprouting resistance without impacting flour quality or the agronomic value of soft winter wheat.

Differential responses of Phaseolus vulgaris cultivars following mungbean yellow mosaic India virus infection

Phaseolus vulgaris, commonly known as French bean is a vital leguminous crop worldwide and India stood 1st rank in dry bean and 4th rank in green bean production worldwide (FAOSTAT 2017). However, this production is severely affected by Mungbean yellow mosaic India virus (MYMIV) infection. Hence it is very important to identify MYMIV tolerant P. vulgaris cultivars. MYMIV infection results in the production of reactive oxygen species and plant cells have evolved complex defense mechanisms at different levels to overcome the damage. Our study for the first time focused on the changes at the morphological and biochemical level, as well as on the relative quantification of MYMIV genes in nine cultivars of P. vulgaris after MYMIV infection. Highest growth and the highest accumulation of four antioxidants of cv. 'Anupam' after MYMIV infection, established that cv. 'Anupam' was less affected by MYMIV infection amongst all nine cultivars. Relative quantification studies also correlated well with these results. Additionally, there is a consistent level of photosynthetic pigments content in mock- and MYMIV-treated seedlings of cv. 'Anupam' over early infection period. Combining all the results we conclude that cv. 'Anupam' is a MYMIV tolerant cultivar.

Identification and characterization of differentially expressed Phaseolus vulgaris miRNAs and their targets during mungbean yellow mosaic India virus infection reveals new insight into Phaseolus-MYMIV interaction

Phaseolus vulgaris is an economically important legume in tropical and subtropical regions of Asia, Africa, Latin-America and parts of USA and Europe. However, its production gets severely affected by mungbean yellow mosaic India virus (MYMIV). We aim to identify and characterize differentially expressed miRNAs during MYMIV-infection in P. vulgaris. A total of 422 miRNAs are identified of which 292 are expressed in both MYMIV-treated and mock-treated samples, 109 are expressed only in MYMIV-treated and 21 are expressed only in mock-treated samples. Selected up- and down-regulated miRNAs are validated by RT-qPCR. 3367 target ORFs are identified for 270 miRNAs. Selected targets are validated by 5' RLM-RACE. Differentially expressed miRNAs regulate transcription factors and are involved in improving stress tolerance to MYMIV. These findings will provide an insight into the role of miRNAs during MYMIV infection in P. vulgaris in particular and during any biotic stress conditions in Leguminosae family in general.

Computational prediction of miRNAs and their targets in Phaseolus vulgaris using simple sequence repeat signatures

BACKGROUND

MicroRNAs (miRNAs) are endogenous, noncoding, short RNAs directly involved in regulating gene expression at the post-transcriptional level. In spite of immense importance, limited information of P. vulgaris miRNAs and their expression patterns prompted us to identify new miRNAs in P. vulgaris by computational methods. Besides conventional approaches, we have used the simple sequence repeat (SSR) signatures as one of the prediction parameter. Moreover, for all other parameters including normalized Shannon entropy, normalized base pairing index and normalized base-pair distance, instead of taking a fixed cut-off value, we have used 99% probability range derived from the available data.

RESULTS

We have identified 208 mature miRNAs in P. vulgaris belonging to 118 families, of which 201 are novel. 97 of the predicted miRNAs in P. vulgaris were validated with the sequencing data obtained from the small RNA sequencing of P. vulgaris. Randomly selected predicted miRNAs were also validated using qRT-PCR. A total of 1305 target sequences were identified for 130 predicted miRNAs. Using 80% sequence identity cut-off, proteins coded by 563 targets were identified. The computational method developed in this study was also validated by predicting 229 miRNAs of A. thaliana and 462 miRNAs of G. max, of which 213 for A. thaliana and 397 for G. max are existing in miRBase 20.

CONCLUSIONS

There is no universal SSR that is conserved among all precursors of Viridiplantae, but conserved SSR exists within a miRNA family and is used as a signature in our prediction method. Prediction of known miRNAs of A. thaliana and G. max validates the accuracy of our method. Our findings will contribute to the present knowledge of miRNAs and their targets in P. vulgaris. This computational method can be applied to any species of Viridiplantae for the successful prediction of miRNAs and their targets.