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Grain-related traits are pivotal in rice cultivation, influencing yield and consumer preference. The complex inheritance of these traits, involving multiple alleles contributing to their expression, poses challenges in breeding. To address these challenges, a multi-locus genome-wide association study (ML-GWAS) utilizing 35,286 high-quality single-nucleotide polymorphisms (SNPs) was conducted. Our study utilized an association panel comprising 483 rice genotypes sourced from a northeast core set and a landraces set collected from various regions in India. Forty quantitative trait nucleotides (QTNs) were identified, associated with four grain-related traits: grain length (GL), grain width (GW), grain aroma (Aro), and length–width ratio (LWR). Notably, 16 QTNs were simultaneously identified using two ML-GWAS methods, distributed across multiple chromosomes. Nearly 258 genes were found near the 16 significant QTNs. Gene annotation study revealed that sixty of these genes exhibited elevated expression levels in specific tissues and were implicated in pathways influencing grain quality. Gene ontology (GO), trait ontology (TO), and enrichment analysis pinpointed 60 candidate genes (CGs) enriched in relevant GO terms. Among them, LOC_Os05g06470, LOC_Os06g06080, LOC_Os08g43470, and LOC_Os03g53110 were confirmed as key contributors to GL, GW, Aro, and LWR. Insights from QTNs and CGs illuminate rice trait regulation and genetic connections, offering potential targets for future studies.

Adzuki bean, an underutilized grain legume, has a significant potential for enhancing food and nutritional security. The main obstacles to developing new cultivars and promoting the adzuki bean as a mainstream pulse crop are a lack of awareness about its potential and insufficient information on crop its genetic diversity. Here, we aimed to explore the untapped potential of adzuki bean germplasm by evaluating its agro-morphological traits and diversity at the molecular level and also to identify trait-specific germplasm by utilizing 100 adzuki bean accessions conserved in the Indian National Genebank. Significant variations was recorded for the morphological traits and identified promising accessions exhibiting desirable traits, such as early flowering (IC341945, EC340257 and EC340283), number of primary branches (IC341945 and IC469175), number of clusters per plant (EC000264, IC167611 and IC341939), number of pods per plant (IC469175, EC34264, EC000264), early maturity (EC340283; EC120460; IC341941) and number of seeds per pod (EC340240, IC455396 and IC341955). Molecular characterization of diverse accessions using 22 polymorphic SSR markers identified a total of 50 alleles, with a mean of 2.27 alleles per loci. The polymorphic information content (PIC) ranged from 0.03 to 0.46, indicating informativeness of markers in distinguishing diverse accessions. Further, the gene diversity among the accessions ranged from 0.03 to 0.57 with a mean of 0.19. Population structure analysis grouped the accessions into three genetic groups, supported by Principal Coordinate Analysis (PCoA) and a phylogenetic tree. Additionally, Analysis of Molecular Variance (AMOVA) confirmed a substantial genetic diversity among the adzuki bean accessions. Thus, the combined assessment of agro-morphological traits and molecular markers effectively distinguished adzuki bean accessions and provided valuable insights in understanding untapped variation at both morphological and molecular levels. The promising accessions identified in the study hold potential for integration into legume improvement programs through introgression breeding, contributing to the development of adzuki bean varieties with target trait.

Quality of living is a multidimensional concept of an individual or a society. It has been influenced by different factors such as housing conditions, health conditions, education, assets, and other basic amenities. This research deals with assessing the level of household Quality of Living (QoL) of Berhampore Town (city) in Murshidabad district in West Bengal, India. Household Quality of Living is measured based on twenty indicators. These indicators are used as different domains like Human Capital Index, Assets Index, Basic Amenities Index, and Housing Index. Quality of living conditions is determined based on composite scores. The result shows that living conditions differ in different parts of this town. The living condition of the central part is better than other parts of this city.

India is blessed with an abundance of diverse rice landraces in its traditional cultivated areas. Two marker systems (simple sequence repeats (SSR) and single nucleotide polymorphism (SNP)) were used to study a set of 298 rice landrace accessions collected from six different regions of India (Andaman and Nicobar Islands, Chhattisgarh, Jharkhand, Uttar Pradesh, Uttarakhand, and West Bengal). Thirty hyper-variable simple sequence repeats (HvSSRs) and 32,782 single nucleotide polymorphisms (SNPs) were used in inferring genetic structure and geographical isolation. Rice landraces from Uttar Pradesh were the most diverse, with a gene diversity value of 0.42 and 0.49 with SSR and SNP markers, respectively. Neighbor-joining trees classified the rice landraces into two major groups with SSR and SNP markers, and complete geographical isolation was observed with SSR markers. Fast STRUCTURE analysis revealed four populations for SSR markers and three populations for SNP markers. The population structure with SSR markers showed that few individuals from Uttarakhand and Andaman and Nicobar Islands were grouped in small clusters. Population structure analysis with SNP markers showed not very distinct region-wise clustering among the rice landraces. Discriminant analysis of principal components (DAPC) and minimum spanning network (MSN) using SSR markers showed region-wise grouping of landraces with some intermixing, but DAPC and MSN with SNP markers showed very clear region-wise clustering. Genetic differentiation of rice landraces between the regions was significant with both SSR (Fst 0.094–0.487) and SNP markers (Fst 0.047–0.285). A Mantel test revealed a positive correlation between the genetic and geographic distance of rice landraces. The present study concludes that rice landraces investigated in this study were very diverse, and unlinked SSR markers show better geographical isolation than a large set of SNP markers.

In India, rice (Oryza sativa L.) is cultivated under a variety of climatic conditions. Due to the fragility of the coastal ecosystem, rice farming in these areas has lagged behind. Salinity coupled with floods has added to this trend. Hence, to prevent genetic erosion, conserving and characterizing the coastal rice, is the need of the hour. This work accessed the genetic variation and population structure among 2,242 rice accessions originating from India’s east coast comprising Andhra Pradesh, Orissa, and Tamil Nadu, using 36 SNP markers, and have generated a core set (247 accessions) as well as a mini-core set (30 accessions) of rice germplasm. All the 36 SNP loci were biallelic and 72 alleles found with average two alleles per locus. The genetic relatedness of the total collection was inferred using the un-rooted neighbor-joining tree, which grouped all the genotypes (2,242) into three major clusters. Two groups were obtained with a core set and three groups obtained with a mini core set. The mean PIC value of total collection was 0.24, and those of the core collection and mini core collection were 0.27 and 0.32, respectively. The mean heterozygosity and gene diversity of the overall collection were 0.07 and 0.29, respectively, and the core set and mini core set revealed 0.12 and 0.34, 0.20 and 0.40 values, respectively, representing 99% of distinctiveness in the core and mini core sets. Population structure analysis showed maximum population at K = 4 for total collection and core collection. Accessions were distributed according to their population structure confirmed by PCoA and AMOVA analysis. The identified small and diverse core set panel will be useful in allele mining for biotic and abiotic traits and managing the genetic diversity of the coastal rice collection. Validation of the 36-plex SNP assay was done by comparing the genetic diversity parameters across two different rice core collections, i.e., east coast and northeast rice collection. The same set of SNP markers was found very effective in deciphering diversity at different genetic parameters in both the collections; hence, these marker sets can be utilized for core development and diversity analysis studies.

Abstract Background Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorders in the world. Studying PD from systems biology perspective involving genes and their regulators might provide deeper insights into the complex molecular interactions associated with this disease. Result We have studied gene co-expression network obtained from a PD-specific microarray data. The co-expression network identified 11 hub genes, of which eight genes are not previously known to be associated with PD. Further study on the functionality of these eight novel hub genes revealed that these genes play important roles in several neurodegenerative diseases. Furthermore, we have studied the tissue-specific expression and histone modification patterns of the novel hub genes. Most of these genes possess several histone modification sites those are already known to be associated with neurodegenerative diseases. Regulatory network namely mTF-miRNA-gene-gTF involves microRNA Transcription Factor (mTF), microRNA (miRNA), gene and gene Transcription Factor (gTF). Whereas long noncoding RNA (lncRNA) mediated regulatory network involves miRNA, gene, mTF and lncRNA. mTF-miRNA-gene-gTF regulatory network identified a novel feed-forward loop. lncRNA-mediated regulatory network identified novel lncRNAs of PD and revealed the two-way regulatory pattern of PD-specific miRNAs where miRNAs can be regulated by both the TFs and lncRNAs. SNP analysis of the most significant genes of the co-expression network identified 20 SNPs. These SNPs are present in the 3′ UTR of known PD genes and are controlled by those miRNAs which are also involved in PD. Conclusion Our study identified eight novel hub genes which can be considered as possible candidates for future biomarker identification studies for PD. The two regulatory networks studied in our work provide a detailed overview of the cellular regulatory mechanisms where the non-coding RNAs namely miRNA and lncRNA, can act as epigenetic regulators of PD. SNPs identified in our study can be helpful for identifying PD at an earlier stage. Overall, this study may impart a better comprehension of the complex molecular interactions associated with PD from systems biology perspective.

Abstract Background Kala bhat (Black soybean) is an important legume crop in Uttarakhand state, India, due to its nutritional and medicinal properties. In the current study, the genetic variabilities present in Kala bhat were estimated using SSR markers and its variability was compared with other improved soybean varieties cultivated in Uttarakhand state, India. Results Seventy-five genotypes cultivated in different districts of Uttarakhand were collected, and molecular analysis was done using 21 SSR markers. A total of 60 alleles were amplified with an average of 2.85 alleles per locus. The mean value of gene diversity and PIC was estimated to be 0.43 and 0.36, respectively. The unrooted phylogenetic tree grouped soybean genotypes into three major clusters, where, yellow seed coat (improved varieties) genotypes were grouped in one cluster, while reddish brown (improved varieties) and Kala bhat showed intermixing. Population structure divided the soybean genotypes into six different populations. AMOVA analysis showed 12% variance among the population, 66% variance among individual and 22% variance was observed within individuals. Principal Coordinate Analysis (PCoA) also showed that yellow seed coat genotypes were grouped in one cluster, whereas, the Kala bhat showed scattered distribution and few genotypes of Kala bhat showed grouping with red and yellow genotypes. Conclusions The different genetic diversity parameters used in the present study indicate that Kala bhat genotypes were more diverse than the yellow seed coat and brown seed coat colour genotypes. Therefore, Kala bhat genotypes can be a good source for the soybean breeding programme due to its better genetic diversity as well as its medicinal properties.

Kalmegh (Andrographis paniculata (Burm. F.) Nees) is one of the most important medicinal plants and has been widely explored as traditional medicine. To exploit its natural genetic diversity and initiations of molecular breeding to develop novel cultivars or varieties, developments of genomic resources are essential. Four microsatellite-enriched genomic libraries—(CT)14, (GT)12, (AG)15 and (AAC)8—were constructed using the genomic DNA of A. paniculata. Initially, 183 recombinant colonies were screened for the presence of CT, GT, AG, and AAC microsatellite repeats, out of which 47 clones found positive for the desired simple sequence repeats (SSRs). It was found that few colonies had more than one desirable SSR. Thus, a sum of 67 SSRs were designed and synthesized for their validation among 42 A. paniculata accessions. Out of the 67 SSRs used for genotyping, only 41 were found to be polymorphic. The developed set of g-SSR markers showed substantial genetic variability among the selected A. paniculata accessions, with an average polymorphic information content (PIC) value of 0.32. Neighbor-joining tree analysis, population structure analysis, analysis of molecular variance (AMOVA), and principal coordinate analysis (PCoA) illustrated the considerable genetic diversity among them. The novel g-SSR markers developed in the present study could be important genomic resources for future applications in A. paniculata.

BACKGROUND: Parkinson's Disease (PD) is a progressive neurologic disorder that affects movement and balance. Recent studies have revealed the importance of microRNA (miR) in PD. However, the detailed role of miR and its regulation by Transcription Factor (TF) remain unexplored. In this work for the first time we have studied TF-miR-mRNA regulatory network as well as miR co-expression network in PD. RESULT: We compared the 204 differentially expressed miRs from microarray data with 73 PD related miRs obtained from literature, Human MicroRNA Disease Database and found a significant overlap of 47 PD related miRs (p-value

The North-Eastern region (NER) of India, comprising of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland and Tripura, is a hot spot for genetic diversity and the most probable origin of rice. North-east rice collections are known to possess various agronomically important traits like biotic and abiotic stress tolerance, unique grain and cooking quality. The genetic diversity and associated population structure of 6,984 rice accessions, originating from NER, were assessed using 36 genome wide unlinked single nucleotide polymorphism (SNP) markers distributed across the 12 rice chromosomes. All of the 36 SNP loci were polymorphic and bi-allelic, contained five types of base substitutions and together produced nine types of alleles. The polymorphic information content (PIC) ranged from 0.004 for Tripura to 0.375 for Manipur and major allele frequency ranged from 0.50 for Assam to 0.99 for Tripura. Heterozygosity ranged from 0.002 in Nagaland to 0.42 in Mizoram and gene diversity ranged from 0.006 in Arunachal Pradesh to 0.50 in Manipur. The genetic relatedness among the rice accessions was evaluated using an unrooted phylogenetic tree analysis, which grouped all accessions into three major clusters. For determining population structure, populations K = 1 to K = 20 were tested and population K = 3 was present in all the states, with the exception of Meghalaya and Manipur where, K = 5 and K = 4 populations were present, respectively. Principal Coordinate Analysis (PCoA) showed that accessions were distributed according to their population structure. AMOVA analysis showed that, maximum diversity was partitioned at the individual accession level (73% for Nagaland, 58% for Arunachal Pradesh and 57% for Tripura). Using POWERCORE software, a core set of 701 accessions was obtained, which accounted for approximately 10% of the total NE India collections, representing 99.9% of the allelic diversity. The rice core set developed will be a valuable resource for future genomic studies and crop improvement strategies.

BACKGROUND: Parkinson's Disease (PD) is one of the most prevailing neurodegenerative diseases. Improving diagnoses and treatments of this disease is essential, as currently there exists no cure for this disease. Microarray and proteomics data have revealed abnormal expression of several genes and proteins responsible for PD. Nevertheless, few studies have been reported involving PD-specific protein-protein interactions. RESULTS: Microarray based gene expression data and protein-protein interaction (PPI) databases were combined to construct the PPI networks of differentially expressed (DE) genes in post mortem brain tissue samples of patients with Parkinson's disease. Samples were collected from the substantia nigra and the frontal cerebral cortex. From the microarray data, two sets of DE genes were selected by 2-tailed t-tests and Significance Analysis of Microarrays (SAM), run separately to construct two Query-Query PPI (QQPPI) networks. Several topological properties of these networks were studied. Nodes with High Connectivity (hubs) and High Betweenness Low Connectivity (bottlenecks) were identified to be the most significant nodes of the networks. Three and four-cliques were identified in the QQPPI networks. These cliques contain most of the topologically significant nodes of the networks which form core functional modules consisting of tightly knitted sub-networks. Hitherto unreported 37 PD disease markers were identified based on their topological significance in the networks. Of these 37 markers, eight were significantly involved in the core functional modules and showed significant change in co-expression levels. Four (ARRB2, STX1A, TFRC and MARCKS) out of the 37 markers were found to be associated with several neurotransmitters including dopamine. CONCLUSION: This study represents a novel investigation of the PPI networks for PD, a complex disease. 37 proteins identified in our study can be considered as PD network biomarkers. These network biomarkers may provide as potential therapeutic targets for PD applications development.

Simple sequence repeat (SSR) and Single Nucleotide Polymorphic (SNP), the two most robust markers for identifying rice varieties were compared for assessment of genetic diversity and population structure. Total 375 varieties of rice from various regions of India archived at the Indian National GeneBank, NBPGR, New Delhi, were analyzed using thirty six genetic markers, each of hypervariable SSR (HvSSR) and SNP which were distributed across 12 rice chromosomes. A total of 80 alleles were amplified with the SSR markers with an average of 2.22 alleles per locus whereas, 72 alleles were amplified with SNP markers. Polymorphic information content (PIC) values for HvSSR ranged from 0.04 to 0.5 with an average of 0.25. In the case of SNP markers, PIC values ranged from 0.03 to 0.37 with an average of 0.23. Genetic relatedness among the varieties was studied; utilizing an unrooted tree all the genotypes were grouped into three major clusters with both SSR and SNP markers. Analysis of molecular variance (AMOVA) indicated that maximum diversity was partitioned between and within individual level but not between populations. Principal coordinate analysis (PCoA) with SSR markers showed that genotypes were uniformly distributed across the two axes with 13.33% of cumulative variation whereas, in case of SNP markers varieties were grouped into three broad groups across two axes with 45.20% of cumulative variation. Population structure were tested using K values from 1 to 20, but there was no clear population structure, therefore Ln(PD) derived Δk was plotted against the K to determine the number of populations. In case of SSR maximum Δk was at K=5 whereas, in case of SNP maximum Δk was found at K=15, suggesting that resolution of population was higher with SNP markers, but SSR were more efficient for diversity analysis.

India is blessed with an abundance of diverse rice landraces in its traditional cultivated areas. Two marker systems (simple sequence repeats (SSR) and single nucleotide polymorphism (SNP)) were used to study a set of 298 rice landrace accessions collected from six different regions of India (Andaman and Nicobar Islands, Chhattisgarh, Jharkhand, Uttar Pradesh, Uttarakhand, and West Bengal). Thirty hyper-variable simple sequence repeats (HvSSRs) and 32,782 single nucleotide polymorphisms (SNPs) were used in inferring genetic structure and geographical isolation. Rice landraces from Uttar Pradesh were the most diverse, with a gene diversity value of 0.42 and 0.49 with SSR and SNP markers, respectively. Neighbor-joining trees classified the rice landraces into two major groups with SSR and SNP markers, and complete geographical isolation was observed with SSR markers. Fast STRUCTURE analysis revealed four populations for SSR markers and three populations for SNP markers. The population structure with SSR markers showed that few individuals from Uttarakhand and Andaman and Nicobar Islands were grouped in small clusters. Population structure analysis with SNP markers showed not very distinct region-wise clustering among the rice landraces. Discriminant analysis of principal components (DAPC) and minimum spanning network (MSN) using SSR markers showed region-wise grouping of landraces with some intermixing, but DAPC and MSN with SNP markers showed very clear region-wise clustering. Genetic differentiation of rice landraces between the regions was significant with both SSR (Fst 0.094–0.487) and SNP markers (Fst 0.047–0.285). A Mantel test revealed a positive correlation between the genetic and geographic distance of rice landraces. The present study concludes that rice landraces investigated in this study were very diverse, and unlinked SSR markers show better geographical isolation than a large set of SNP markers. [ABSTRACT FROM AUTHOR]