Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Shreedharan Sriram is active.

Publication


Featured researches published by Shreedharan Sriram.


Plant Cell Reports | 2017

Integration of omics approaches to understand oil/protein content during seed development in oilseed crops

Manju Gupta; Pudota Bala Bhaskar; Shreedharan Sriram; Pohao Wang

Oilseed crops, especially soybean (Glycine max) and canola/rapeseed (Brassica napus), produce seeds that are rich in both proteins and oils and that are major sources of energy and nutrition worldwide. Most of the nutritional content in the seed is accumulated in the embryo during the seed filling stages of seed development. Understanding the metabolic pathways that are active during seed filling and how they are regulated are essential prerequisites to crop improvement. In this review, we summarize various omics studies of soybean and canola/rapeseed during seed filling, with emphasis on oil and protein traits, to gain a systems-level understanding of seed development. Currently, most (80–85%) of the soybean and rapeseed reference genomes have been sequenced (950 and 850 megabases, respectively). Parallel to these efforts, extensive omics datasets from different seed filling stages have become available. Transcriptome and proteome studies have detected preponderance of starch metabolism and glycolysis enzymes to be the possible cause of higher oil in B. napus compared to other crops. Small RNAome studies performed during the seed filling stages have revealed miRNA-mediated regulation of transcription factors, with the suggestion that this interaction could be responsible for transitioning the seeds from embryogenesis to maturation. In addition, progress made in dissecting the regulation of de novo fatty acid synthesis and protein storage pathways is described. Advances in high-throughput omics and comprehensive tissue-specific analyses make this an exciting time to attempt knowledge-driven investigation of complex regulatory pathways.


Nature plants | 2017

GC-rich coding sequences reduce transposon-like, small RNA-mediated transgene silencing

Lyudmila Sidorenko; Tzuu-fen Lee; Aaron T. Woosley; William A. Moskal; Scott Bevan; P. Ann Owens Merlo; Terence A. Walsh; Xiujuan Wang; Staci Weaver; Todd P. Glancy; Pohao Wang; Xiaozeng Yang; Shreedharan Sriram; Blake C. Meyers

The molecular basis of transgene susceptibility to silencing is poorly characterized in plants; thus, we evaluated several transgene design parameters as means to reduce heritable transgene silencing. Analyses of Arabidopsis plants with transgenes encoding a microalgal polyunsaturated fatty acid (PUFA) synthase revealed that small RNA (sRNA)-mediated silencing, combined with the use of repetitive regulatory elements, led to aggressive transposon-like silencing of canola-biased PUFA synthase transgenes. Diversifying regulatory sequences and using native microalgal coding sequences (CDSs) with higher GC content improved transgene expression and resulted in a remarkable trans-generational stability via reduced accumulation of sRNAs and DNA methylation. Further experiments in maize with transgenes individually expressing three crystal (Cry) proteins from Bacillus thuringiensis (Bt) tested the impact of CDS recoding using different codon bias tables. Transgenes with higher GC content exhibited increased transcript and protein accumulation. These results demonstrate that the sequence composition of transgene CDSs can directly impact silencing, providing design strategies for increasing transgene expression levels and reducing risks of heritable loss of transgene expression.The molecular basis underlying transgene susceptibility to silencing remains elusive. Now, using multiple examples, a study shows that higher GC content of coding sequences can reduce susceptibility of transgenes to heritable silencing.


Plant Biotechnology Journal | 2013

Trait stacking via targeted genome editing

William Michael Ainley; Lakshmi Sastry-Dent; Mary E. Welter; Michael G. Murray; Bryan Zeitler; Rainier Amora; David R. Corbin; Rebecca Ruth Miles; Nicole L. Arnold; Tonya L. Strange; Matthew Simpson; Zehui Cao; Carley Carroll; Katherine S. Pawelczak; Ryan C. Blue; Kim West; Lynn M. Rowland; Douglas Perkins; Pon Samuel; Cristie M. Dewes; Liu Shen; Shreedharan Sriram; Steven L. Evans; Edward J. Rebar; Lei Zhang; Phillip D. Gregory; Fyodor D. Urnov; Steven R. Webb; Joseph F. Petolino


Archive | 2013

Data analysis of dna sequences

Lakshmi Sastry-Dent; Shreedharan Sriram; Navin Elango; Zehui Cao; Karthik Narayan Muthuranman


Archive | 2015

Optimal Maize Loci

Lakshmi Sastry-Dent; Zehui Cao; Shreedharan Sriram; Steven R. Webb; Debra L Camper; Navin Elango


Archive | 2016

Optimal soybean loci

Lakshmi Sastry-Dent; Zehui Cao; Shreedharan Sriram; Steven R. Webb; Debra L Camper; Michael W. Ainley


Archive | 2018

MÉTODOS Y SISTEMAS PARA PRONOSTICAR EL RIESGO DEL SILENCIAMIENTO DEL TRANSGÉN

Lakshmi Sastry Dent; Shreedharan Sriram; Pohao Wang


Archive | 2018

Modulation of Transgene Expression in Plants

Sandeep Kumar; Marcelo A German; Pohao Wang; Todd P. Glancy; Shreedharan Sriram; Carla N. Yerkes; Andrew J. Bowling; Heather E. Pence; Andrew E. Robinson


Archive | 2016

LOCI DE MAÍZ ÓPTIMOS

Lakshmi Sastry-Dent; Shreedharan Sriram; Steven R. Webb; Debra L Camper; Zehui Cao; Navin Elango


Archive | 2016

análise de dados de sequências de dna

Karthik Narayan Muthuranman; Lakshmi Sastry Dent; Navin Elango; Shreedharan Sriram; Zehui Cao

Collaboration


Dive into the Shreedharan Sriram's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge