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Main conclusionGenomic selection and its importance in crop breeding. Integration of GS with new breeding tools and developing SOP for GS to achieve maximum genetic gain with low cost and time.The success of conventional breeding approaches is not sufficient to meet the demand of a growing population for nutritious food and other plant-based products. Whereas, marker assisted selection (MAS) is not efficient in capturing all the favorable alleles responsible for economic traits in the process of crop improvement. Genomic selection (GS) developed in livestock breeding and then adapted to plant breeding promised to overcome the drawbacks of MAS and significantly improve complicated traits controlled by gene/QTL with small effects. Large-scale deployment of GS in important crops, as well as simulation studies in a variety of contexts, addressed G × E interaction effects and non-additive effects, as well as lowering breeding costs and time. The current study provides a complete overview of genomic selection, its process, and importance in modern plant breeding, along with insights into its application. GS has been implemented in the improvement of complex traits including tolerance to biotic and abiotic stresses. Furthermore, this review hypothesises that using GS in conjunction with other crop improvement platforms accelerates the breeding process to increase genetic gain. The objective of this review is to highlight the development of an appropriate GS model, the global open source network for GS, and trans-disciplinary approaches for effective accelerated crop improvement. The current study focused on the application of data science, including machine learning and deep learning tools, to enhance the accuracy of prediction models. Present study emphasizes on developing plant breeding strategies centered on GS combined with routine conventional breeding principles by developing GS-SOP to achieve enhanced genetic gain.

Rice blast disease is the most devastating disease constraining crop productivity. Vertical resistance to blast disease is widely studied despite its instability. Clusters of genes or QTLs conferring blast resistance that offer durable horizontal resistance are important in resistance breeding. In this study, we aimed to refine the reported QTLs and identify stable meta-QTLs (MQTLs) associated with rice blast resistance. A total of 435 QTLs were used to project 71 MQTLs across all the rice chromosomes. As many as 199 putative rice blast resistance genes were identified within 53 MQTL regions. The genes included 48 characterized resistance gene analogs and related proteins, such as NBS–LRR type, LRR receptor-like kinase, NB-ARC domain, pathogenesis-related TF/ERF domain, elicitor-induced defense and proteins involved in defense signaling. MQTL regions with clusters of RGA were also identified. Fifteen highly significant MQTLs included 29 candidate genes and genes characterized for blast resistance, such as Piz , Nbs-Pi9 , pi55-1, pi55-2, Pi3/Pi5-1, Pi3/Pi5-2, Pikh, Pi54, Pik/Pikm/Pikp , Pb1 and Pb2 . Furthermore, the candidate genes (42) were associated with differential expression (in silico) in compatible and incompatible reactions upon disease infection. Moreover, nearly half of the genes within the MQTL regions were orthologous to those in O. sativa indica, Z. mays and A. thaliana, which confirmed their significance. The peak markers within three significant MQTLs differentiated blast-resistant and susceptible lines and serve as potential surrogates for the selection of blast-resistant lines. These MQTLs are potential candidates for durable and broad-spectrum rice blast resistance and could be utilized in blast resistance breeding.

Quantitative trait loci (QTL) for rice grain weight identified using bi-parental populations in various environments were found inconsistent and have a modest role in marker assisted breeding and map-based cloning programs. Thus, the identification of a consistent consensus QTL region across populations is critical to deploy in marker aided breeding programs. Using the QTL meta-analysis technique, we collated rice grain weight QTL information from numerous studies done across populations and in diverse environments to find constitutive QTL for grain weight. Using information from 114 original QTL in meta-analysis, we discovered three significant Meta-QTL (MQTL) for grain weight on chromosome 3. According to gene ontology, these three MQTL have 179 genes, 25 of which have roles in developmental functions. Amino acid sequence BLAST of these genes indicated their orthologue conservation among core cereals with similar functions. MQTL3.1 includes the OsAPX1 , PDIL , SAUR , and OsASN1 genes, which are involved in grain development and have been discovered to play a key role in asparagine biosynthesis and metabolism, which is crucial for source-sink regulation. Five potential candidate genes were identified and their expression analysis indicated a significant role in early grain development. The gene sequence information retrieved from the 3 K rice genome project revealed the deletion of six bases coding for serine and alanine in the last exon of OsASN1 led to an interruption in the synthesis of α-helix of the protein, which negatively affected the asparagine biosynthesis pathway in the low grain weight genotypes. Further, the MQTL3.1 was validated using linked marker RM7197 on a set of genotypes with extreme phenotypes. MQTL that have been identified and validated in our study have significant scope in MAS breeding and map-based cloning programs for improving rice grain weight.

Main ConclusionThe Ustilaginoidea virens –rice pathosystem has been used as a model for flower-infecting fungal pathogens. The molecular biology of the interactions between U. virens and rice, with an emphasis on the attempt to get a deeper comprehension of the false smut fungus's genomes, proteome, host range, and pathogen biology, has been investigated. Meta-QTL analysis was performed to identify potential QTL hotspots for use in marker-assisted breeding.The Rice False Smut (RFS) caused by the fungus Ustilaginoidea virens currently threatens rice cultivators across the globe. RFS infects rice panicles, causing a significant reduction in grain yield. U. virens can also parasitize other hosts though they play only a minor role in its life cycle. Furthermore, because it produces mycotoxins in edible rice grains, it puts both humans and animals at risk of health problems. Although fungicides are used to control the disease, some fungicides have enabled the pathogen to develop resistance, making its management challenging. Several QTLs have been reported but stable gene(s) that confer RFS resistance have not been discovered yet. This review offers a comprehensive overview of the pathogen, its virulence mechanisms, the genome and proteome of U. virens, and its molecular interactions with rice. In addition, information has been compiled on reported resistance QTLs, facilitating the development of a consensus genetic map using meta-QTL analysis for identifying potential QTL hotspots. Finally, this review highlights current developments and trends in U. virens–rice pathosystem research while identifying opportunities for future investigations.

Genebanks maintain a rich source of variation for resistance against many pests and diseases and tolerance to abiotic stresses. However, identifying appropriate germplasm from the collection is frequently impeded by incomplete phenotyping of voluminous collections. The focused identification of germplasm strategy (FIGS) helps to overcome the limitations of phenotyping genebank collections for a target trait. FIGS utilizes a priory information of the evolutionary relationship between trait and environment and helps to phenotype only those accessions with a high probability of having new allelic variation for the target trait. FIGS selects only those accessions that are likely to have evolved in the environments under natural selection pressure. Further, crop genomics and data analytics models can be trained with different filters to identify the best subset with novel alleles. A combination of genomics and data science with FIGS has the potential to improve the efficiency and precision of identifying the best accession to use in pre-breeding for target traits. This review discusses in detail the rationale, importance, strategies, integration with genomics, and applications of FIGS for pre-breeding programs.

As a prelude to exploit DNA methylation-induced variation, we hypothesized the existence of substantial natural DNA methylation variation and its association with economically important traits in dolichos bean, and tested it using amplified methylation polymorphism-polymerase chain reaction (AMP-PCR) assay. DNA methylation patterns such as internal, external, full and non-methylation were amplified in a set of 64 genotypes using 26 customized randomly amplified polymorphic DNA (RAPD) primers containing 5′CCGG3′ sequence. The 64 genotypes included 60 germplasm accessions (GA), two advanced breeding lines (ABLs) and two released varieties. The ABLs and released varieties are referred to as improved germplasm accessions (IGA) in this study. The association of DNA methylation patterns with economically important traits such as days to 50% flowering, raceme length, fresh pods plant−1, fresh pod yield plant−1 and 100-fresh seed weight was explored. At least 50 genotypes were polymorphic for DNA methylation patterns at 10 loci generated by seven of the 26 RAPD primers. The GA and IGA differed significantly for total, full and external methylation and the frequency of methylation was higher in GA compared to that in IGA. The genotypes with external methylation produced longer racemes than those with full, internal and non-methylation in that order at polymorphic RAPD-11–242 locus. High pod yielding genotypes had significantly lower frequency of full methylation than low yielding ones. On the contrary, the genotypes that produced heavier fresh seeds harboured higher frequencies of total and externally methylated loci than those that produced lighter fresh seeds.

Late wilt disease (LWD) caused by Harpophora maydis (Samra, Sabet and Hing) is emerging as major production constraint in maize across the world. As a prelude to develop maize hybrid resistance to LWD, genetic basis of resistance was investigated. Two F2:3 mapping populations (derived from CV156670 × 414-33 (P-1) and CV156670 × CV143587 (P-2)) were challenged with LWD at two locations (Kallinayakanahalli and Muppadighatta) during 2017 post-rainy season. A wider range of LWD scores was observed at both locations in both the populations. LWD response was influenced by significant genotype × location interaction. Six and 56 F2:3 progeny families showed resistance level better than resistant parent. A total of 150 and 199 polymorphic single nucleotide polymorphism markers were used to genotype P-1 and P-2, respectively. Inclusive composite interval mapping was performed to detect significant Quantitative Trait Loci (QTL), QTL × QTL, QTL × location interaction effects. Three major and four minor QTL controlling LWD resistance were detected on chromosome-1. The position and effect of the QTL varied with the location. Significant di-QTL interactions involving QTL (with significant and/or non-significant effects) located within and between all the ten chromosomes were detected. Five of the seven detected QTL showed significant QTL × location interaction. Though two major QTL (q-lw-1.5 and q-lw-1.6) with lower Q×L interaction effects could be considered as stable, their phenotypic variance is not large enough to deploy them in Marker Assisted Selection (MAS). However, these QTL are of paramount importance in accumulating positive alleles for LWD resistance breeding.

Strategies to improve a crop depend on a better understanding of its genetic architecture. In the era of genomics, it is important to develop new efficient genomic resources for orphan crops, considering the growing demand for the crop. Dolichos bean, a high-potential, nutrient-rich orphan legume crop, is gaining importance in many parts of the world. Hence, accelerating breeding activity with marker-assisted approaches is much needed. We developed a total of 670 simple sequence repeat (SSR) markers from the genome sequence information as new genomic resources for the crop. In order to assess the effectiveness of markers to use in genetic research, ensuring the informativeness of new genomic resources is a prerequisite. Hence, new markers were assayed on 96 diverse accessions and examined for their potential to explain population genomics. These new markers consisted of both di- and tri-nucleotide repeats in equal proportions. The population genetic parameters estimated with this marker information proved their efficiency in delineating genetic variations in the population. Results reinforced the relationships between the effective number of alleles, gene diversity, and polymorphic information content, thereby suggesting the informativeness of new markers as genomic resources. Population structure and gene flow information generated will be useful to understand the population dynamics of the dolichos bean. The classification of genotypes into clusters using marker information and the comparison of cluster phenotypes indicated the effectiveness of marker alleles in assessing genome diversity. At the outset, the results of the present study strongly prove the effectiveness of new genomic SSR markers to utilize in genomics-assisted breeding in dolichos bean.

Crop breeders conduct trials to assess performance of elite breeding lines/germplasm accessions across locations and/or years to identify promising ones for use as cultivars and/or for use in breeding programmes. It is hypothesized that in a given location, genotypes’ multi-year performance are more predictive of their performance in the next/future years. However, only a few researchers have examined this hypothesis. To test this hypothesis, we predicted genotypes’ present-year’s performance based on their previous 1-, 2-, 3- and 4-years’ performance using fresh pod yield data from 53 dolichos bean genotypes evaluated across 5 years. We used two statistics, namely yield relative to environment (year) maximum (YREM) and best linear unbiased predictors (BLUP) as measures of genotypes’ performance for fresh pod yield in dolichos bean. Correlation coefficients of genotypes’ present-year’s performance with previous 1-, 2-, 3- and 4-years’ performance were used as measures of predictive power. The results of our study provided adequate evidence to show that that single-year dolichos bean genotypes’ YREM and BLUP have sufficient power to predict their future 1-year/multiple-years’ performance and to identify superior genotypes. These findings adequately support the common practice by breeders/cultivar sponsors of withdrawing their cultivars from the tests based on a single-year trial.

Purpose The role of aspirin in cancer prevention has been well defined; the last decade revealed its therapeutic role with improved efficacy when aspirin was added to capecitabine in heavily pre-treated metastatic colorectal cancer. Aspirin affects tumour growth through the PI3K pathway, which regulates apoptosis and autophagy. The objective was to compare the efficacy of aspirin plus epirubicin, oxaliplatin, capecitabine (EOX) chemotherapy versus EOX alone in locally advanced and metastatic gastric cancer. Methods All patients with advanced gastric cancer reporting to the Department of Medical oncology between March 2017 and May 2019 were screened for study eligibility. They were randomly assigned to standard EOX with or without aspirin at a daily dose of 150 mg. Tumour measurements were assessed at baseline and after 3–4 cycles by an independent blinded radiologist according to RECIST criteria 1.1. Toxicity profiles were recorded as per CTCAE v 4.03. Per-protocol group was identified as 70 patients. The primary endpoint was overall response rates in the per-protocol group (defined as patients who received a minimum of 3 cycles and had an evaluable response after randomization). The secondary endpoints included toxicity analysis, progression-free survival, and overall survival. Results Ninety-five patients who fulfilled the study inclusion and exclusion criteria were randomized to group 1 EOX (50) or group 2 EOX plus aspirin (45). Seventy patients were included for the per-protocol analysis. The overall response rate in group 1 was 27% compared to group 2, which was 42%, P  = 0.176. The median duration of follow was 29 (18.56–39.45) months. The median overall survival ( n  = 95) of group 1 versus group 2 was 11 (8.58–13.42) months and 10 (6.86–13.14) months, respectively, P  = 0.90. There was no statistical significance in the overall survival per-protocol analysis ( n  = 70) between group one 12 (8.75–15.25) months versus group two 12 (6.21–17.79) months, P  = 0.50. Conclusions There was no improvement in the response rates, progression-free survival, and overall survival on adding aspirin to EOX chemotherapy in locally advanced and metastatic gastric cancer in an unselected population. A further role of PI3K mutation as a biomarker needs to be evaluated in this setting.