Gazaldeep Kaur

GENCODE produces comprehensive reference gene annotation for human and mouse. Entering its twentieth year, the project remains highly active as new technologies and methodologies allow us to catalog the genome at ever-increasing granularity. In particular, long-read transcriptome sequencing enables us to identify large numbers of missing transcripts and to substantially improve existing models, and our long non-coding RNA catalogs have undergone a dramatic expansion and reconfiguration as a result. Meanwhile, we are incorporating data from state-of-the-art proteomics and Ribo-seq experiments to fine-tune our annotation of translated sequences, while further insights into function can be gained from multi-genome alignments that grow richer as more species' genomes are sequenced. Such methodologies are combined into a fully integrated annotation workflow. However, the increasing complexity of our resources can present usability challenges, and we are resolving these with the creation of filtered genesets such as MANE Select and GENCODE Primary. The next challenge is to propagate annotations throughout multiple human and mouse genomes, as we enter the pangenome era. Our resources are freely available at our web portal www.gencodegenes.org, and via the Ensembl and UCSC genome browsers.

Enhancement of micronutrient bioavailability is crucial to address the malnutrition in the developing countries. Various approaches employed to address the micronutrient bioavailability are showing promising signs, especially in cereal crops. Phytic acid (PA) is considered as a major antinutrient due to its ability to chelate important micronutrients and thereby restricting their bioavailability. Therefore, manipulating PA biosynthesis pathway has largely been explored to overcome the negative impact in different crop species. Recently, we reported that functional wheat inositol pentakisphosphate kinase (TaIPK1) is involved in PA biosynthesis, however the functional roles of the IPK1 gene in wheat remains elusive. In this study, RNAi-mediated gene silencing was performed for IPK1 transcripts in hexaploid wheat. Four non-segregating RNAi lines of wheat were selected for detailed study (S3-D-6-1; S6-K-3-3; S6-K-6-10 and S16-D-9-5). Homozygous transgenic RNAi lines at T4 seeds with a decreased transcript of TaIPK1 showed 28%-56% reduction of the PA. Silencing of IPK1 also resulted in increased free phosphate in mature grains. Although, no phenotypic changes in the spike was observed but, lowering of grain PA resulted in the reduced number of seeds per spikelet. The lowering of grain PA was also accompanied by a significant increase in iron (Fe) and zinc (Zn) content, thereby enhancing their molar ratios (Zn:PA and Fe:PA). Overall, this work suggests that IPK1 is a promising candidate for employing genome editing tools to address the mineral accumulation in wheat grains.

Iron (Fe) is an essential micronutrient for all organisms. In crop plants, Fe deficiency can decrease crop yield significantly; however, our current understanding of how major crops respond to Fe deficiency remains limited. Herein, the effect of Fe deprivation at both the transcriptomic and metabolic level in hexaploid wheat was investigated. Genome-wide gene expression reprogramming was observed in wheat roots subjected to Fe starvation, with a total of 5854 genes differentially expressed. Homoeologue and subgenome-specific analysis unveiled the induction-biased contribution from the A and B genomes. In general, the predominance of genes coding for nicotianamine synthase, yellow stripe-like transporters, metal transporters, ABC transporters, and zinc-induced facilitator-like protein was noted. Expression of genes related to the Strategy II mode of Fe uptake was also predominant. Our transcriptomic data were in agreement with the GC-MS analysis that showed the enhanced accumulation of various metabolites such as fumarate, malonate, succinate, and xylofuranose, which could be contributing to Fe mobilization. Interestingly, Fe starvation leads to a significant temporal increase of glutathione S-transferase at both the transcriptional level and enzymatic activity level, which indicates the involvement of glutathione in response to Fe stress in wheat roots. Taken together, our result provides new insight into the wheat response to Fe starvation at the molecular level and lays the foundation to design new strategies for the improvement of Fe nutrition in crops.

Viral infections constantly jeopardize the global public health due to lack of effective antiviral therapeutics. Therefore, there is an imperative need to speed up the drug discovery process to identify novel and efficient drug candidates. In this study, we have developed quantitative structure-activity relationship (QSAR)-based models for predicting antiviral compounds (AVCs) against deadly viruses like human immunodeficiency virus (HIV), hepatitis C virus (HCV), hepatitis B virus (HBV), human herpesvirus (HHV) and 26 others using publicly available experimental data from the ChEMBL bioactivity database. Support vector machine (SVM) models achieved a maximum Pearson correlation coefficient of 0.72, 0.74, 0.66, 0.68, and 0.71 in regression mode and a maximum Matthew's correlation coefficient 0.91, 0.93, 0.70, 0.89, and 0.71, respectively, in classification mode during 10-fold cross-validation. Furthermore, similar performance was observed on the independent validation sets. We have integrated these models in the AVCpred web server, freely available at http://crdd.osdd.net/servers/avcpred. In addition, the datasets are provided in a searchable format. We hope this web server will assist researchers in the identification of potential antiviral agents. It would also save time and cost by prioritizing new drugs against viruses before their synthesis and experimental testing.