@article {149951, title = {Genome-wide association study reveals effect of nsSNPs on candidate genes in rice during iron deficiency.}, journal = {Funct Integr Genomics}, volume = {24}, year = {2024}, month = {2024 Oct 25}, pages = {198}, abstract = {

Resource-poor areas with moisture deficit lands following aerobic and direct seeded rice (DSR) methods of cultivation face severe problems of iron deficiency. In this study, Bengal and Assam Aus rice panel was phenotyped at the seedling stage using an iron-deprived hydroponic medium for various shoot and root traits. A novel iron deficiency scoring scale was used to classify the tolerance reaction and could range anywhere between 0 and 9, indicating the most tolerant and susceptible, respectively. The GWAS results identified four putative candidate genes; OsFLA for number of leaves and shoot length, OsBIDK1 for root traits; average diameter, volume, biomass, projected area, and surface area, OsHPL3 for chlorophyll index of the third leaf and AKR2B (XBOS252) was for Fe score, (which was earlier reported in relation to Xa21). The nsSNP (nsSNPs) variations in these gene sequences were used to group the panel and identify superior haplotypes and donors. BR16 was identified as a superior donor, with higher chlorophyll index and shoot length than RA23, also higher values for root traits like root average diameter, root volume, root projected area and root surface area followed by Shete Bhado. The impact of identified nsSNPs on protein structure and stability was investigated. The conserved domains detected in the mutated proteins of the superior haplotypes are very informative, highlighting that natural selection favors abiotic stress tolerant variants in resource poor areas. Thus, justifying our choice of Aus landraces for association mapping of Fe deficiency tolerant genes in rice.

}, keywords = {Chlorophyll, Genome-Wide Association Study, Iron Deficiencies, Oryza, Plant Proteins, Plant Roots, Polymorphism, Single Nucleotide}, issn = {1438-7948}, doi = {10.1007/s10142-024-01478-w}, author = {Panda, Siddharth and Anandan, Annamalai and Shafi, K Mohamed and Naika, Mahantesha B N and Sowdhamini, R and Vanishree, G and Sarkar, Sutapa and Travis, Anthony J and Norton, Gareth J and Price, Adam H} } @article {115259, title = {Exploring the medicinally important secondary metabolites landscape through the lens of transcriptome data in fenugreek (Trigonella foenum graecum L.).}, journal = {Sci Rep}, volume = {12}, year = {2022}, month = {2022 Aug 08}, pages = {13534}, abstract = {

Fenugreek (Trigonella foenum-graecum L.) is a self-pollinated leguminous crop belonging to the Fabaceae family. It is a multipurpose crop used as herb, spice, vegetable and forage. It is a traditional medicinal plant in India attributed with several nutritional and medicinal properties including antidiabetic and anticancer. We have performed a combined transcriptome assembly from RNA sequencing data derived from leaf, stem and root tissues. Around 209,831 transcripts were deciphered from the assembly of 92\% completeness and an N50 of 1382 bases. Whilst secondary metabolites of medicinal value, such as trigonelline, diosgenin, 4-hydroxyisoleucine and quercetin, are distributed in several tissues, we report transcripts that bear sequence signatures of enzymes involved in the biosynthesis of such metabolites and are highly expressed in leaves, stem and roots. One of the antidiabetic alkaloid, trigonelline and its biosynthesising enzyme, is highly abundant in leaves. These findings are of value to nutritional and the pharmaceutical industry.

}, keywords = {Diosgenin, Hypoglycemic Agents, Plant Extracts, Plants, Medicinal, Transcriptome, Trigonella}, issn = {2045-2322}, doi = {10.1038/s41598-022-17779-8}, author = {Naika, Mahantesha B N and Sathyanarayanan, Nitish and Sajeevan, Radha Sivarajan and Bhattacharyya, Teerna and Ghosh, Pritha and Iyer, Meenakshi S and Jarjapu, Mahita and Joshi, Adwait G and Harini, K and Shafi, K Mohamed and Kalmankar, Neha and Karpe, Snehal D and Mam, Bhavika and Pasha, Shaik Naseer and Sowdhamini, Ramanathan} } @article {48884, title = {Decoding systems biology of plant stress for sustainable agriculture development and optimized food production.}, journal = {Prog Biophys Mol Biol}, volume = {145}, year = {2019}, month = {2018 Dec 15}, pages = {19-39}, abstract = {

Plants are essential facilitators of human life on planet earth. Plants play a critical functional role in mediating the quality of air, availability of food and the sustainability of agricultural resources. However, plants are in constant interaction with its environment and often hampered by various types of stresses like biotic and abiotic ones. Biotic stress is a significant reason for crop-loss and causes yield loss in the range of 31-42\%, post-harvest loss due to biotic stress is in the range of 6-20\%, and abiotic stress causes 6-20\% of the crop damage. Recognizing the molecular factors driving plant stress-related events, and developing molecular strategies to aid plants to tolerate, resist or adapt to biotic and abiotic stress are critical for sustainable agriculture practice. In this review, we discuss how recent advances in bioinformatics, plant genomics, and data science could help to improve our understanding of plant stress biology and improve the scale of global food production. We present various areas of scientific and technological advances, such as increased availability of genomics data through whole genome sequencing that require attention. We also discuss emerging techniques including CRISPR-Cas9 based genome engineering systems to develop plant varieties that can handle combinatorial stress signals. Growing trend of converging multiple omics technologies and availability of accurate, multi-scale models of plant stress through the study of orthologs and synteny studies, would improve our knowledge of how plants perceive, respond, and manage stress to thrive as resilient crop species and thus help to reduce global food crisis.

}, issn = {1873-1732}, doi = {10.1016/j.pbiomolbio.2018.12.002}, author = {Shameer, Khader and Naika, Mahantesha B N and Shafi, K Mohamed and Sowdhamini, Ramanathan} } @article {3545, title = {An Approach to Function Annotation for Proteins of Unknown Function (PUFs) in the Transcriptome of Indian Mulberry.}, journal = {PLoS One}, volume = {11}, year = {2016}, month = {2016}, pages = {e0151323}, abstract = {

The modern sequencing technologies are generating large volumes of information at the transcriptome and genome level. Translation of this information into a biological meaning is far behind the race due to which a significant portion of proteins discovered remain as proteins of unknown function (PUFs). Attempts to uncover the functional significance of PUFs are limited due to lack of easy and high throughput functional annotation tools. Here, we report an approach to assign putative functions to PUFs, identified in the transcriptome of mulberry, a perennial tree commonly cultivated as host of silkworm. We utilized the mulberry PUFs generated from leaf tissues exposed to drought stress at whole plant level. A sequence and structure based computational analysis predicted the probable function of the PUFs. For rapid and easy annotation of PUFs, we developed an automated pipeline by integrating diverse bioinformatics tools, designated as PUFs Annotation Server (PUFAS), which also provides a web service API (Application Programming Interface) for a large-scale analysis up to a genome. The expression analysis of three selected PUFs annotated by the pipeline revealed abiotic stress responsiveness of the genes, and hence their potential role in stress acclimation pathways. The automated pipeline developed here could be extended to assign functions to PUFs from any organism in general. PUFAS web server is available at http://caps.ncbs.res.in/pufas/ and the web service is accessible at http://capservices.ncbs.res.in/help/pufas.

}, issn = {1932-6203}, doi = {10.1371/journal.pone.0151323}, author = {Dhanyalakshmi, K H and Naika, Mahantesha B N and Sajeevan, R S and Mathew, Oommen K and Shafi, K Mohamed and Sowdhamini, Ramanathan and N Nataraja, Karaba} }