The Agricultural Genome to Phenome Initiative (AG2PI): creating a shared vision across crop and livestock research communities

Predicting phenotype from genotype is a central challenge in biology. By understanding genomic information to predict and improve traits, scientists can address the challenges and opportunities of achieving sustainable genetic improvement of complex, economically important traits in agriculturally relevant species. Converting the enormous, recent technical advances in all areas of genomics and phenomics into sustained and ecologically responsible improvements in food and fuel production is complex. It will require engaging agricultural genome to phenome (G2P) experts, drawing from a broad community, including crop and livestock scientists and essential integrative disciplines (e.g., engineers, economists, data and social scientists). To achieve this vision, the USDA NIFA-funded project inaugurating the Agricultural Genome to Phenome Initiative (AG2PI) is working to: Develop a cohesive vision for agricultural G2P research by identifying research gaps and opportunities; advancing community solutions to these challenges and gaps; and rapidly disseminating findings to the broader community. Towards these ends, this AG2PI project is organizing virtual field days, conferences, training workshops, and awarding seed grants to conceive new insights (details at www.ag2pi.org). Since October 2020, more than 10,000 unique participants from every inhabited continent have engaged in these activities. To illustrate AG2PI’s scope, we present survey results on agricultural G2P research needs and opportunities, highlighting opinions and suggestions for the future. We invite stakeholders interested in this complex but critical effort to help create an optimal, sustainable food supply for society and challenge the community to add to our vision for future accomplishments by a fully actualized AG2PI enterprise

Identification of seedling resistance in wild oat relatives against oat crown rust

Faculty advisor: Melania FigueroaThis research was supported by the Undergraduate Research Opportunities Program (UROP)

Reduced amino acid alphabets exhibit an improved sensitivity and selectivity in fold assignment

Motivation: Many proteins with vastly dissimilar sequences are found to share a common fold, as evidenced in the wealth of structures now available in the Protein Data Bank. One idea that has found success in various applications is the concept of a reduced amino acid alphabet, wherein similar amino acids are clustered together. Given the structural similarity exhibited by many apparently dissimilar sequences, we undertook this study looking for improvements in fold recognition by comparing protein sequences written in a reduced alphabet. Results: We tested over 150 of the amino acid clustering schemes proposed in the literature with all-versus-all pairwise sequence alignments of sequences in the Distance matrix alignment (DALI) database. We combined several metrics from information retrieval popular in the literature: mean precision, area under the Receiver Operating Characteristic curve and recall at a fixed error rate and found that, in contrast to previous work, reduced alphabets in many cases outperform full alphabets. We find that reduced alphabets can perform at a level comparable to full alphabets in correct pairwise alignment of sequences and can show increased sensitivity to pairs of sequences with structural similarity but low-sequence identity. Based on these results, we hypothesize that reduced alphabets may also show performance gains with more sophisticated methods such as profile and pattern searches

Integrated genomic characterization of pancreatic ductal adenocarcinoma

We performed integrated genomic, transcriptomic, and proteomic profiling of 150 pancreatic ductal adenocarcinoma (PDAC) specimens, including samples with characteristic low neoplastic cellularity. Deep whole-exome sequencing revealed recurrent somatic mutations in KRAS, TP53, CDKN2A, SMAD4, RNF43, ARID1A, TGFβR2, GNAS, RREB1, and PBRM1. KRAS wild-type tumors harbored alterations in other oncogenic drivers, including GNAS, BRAF, CTNNB1, and additional RAS pathway genes. A subset of tumors harbored multiple KRAS mutations, with some showing evidence of biallelic mutations. Protein profiling identified a favorable prognosis subset with low epithelial-mesenchymal transition and high MTOR pathway scores. Associations of non-coding RNAs with tumor-specific mRNA subtypes were also identified. Our integrated multi-platform analysis reveals a complex molecular landscape of PDAC and provides a roadmap for precision medicine

Integrated genomic characterization of oesophageal carcinoma

Oesophageal cancers are prominent worldwide; however, there are few targeted therapies and survival rates for these cancers remain dismal. Here we performed a comprehensive molecular analysis of 164 carcinomas of the oesophagus derived from Western and Eastern populations. Beyond known histopathological and epidemiologic distinctions, molecular features differentiated oesophageal squamous cell carcinomas from oesophageal adenocarcinomas. Oesophageal squamous cell carcinomas resembled squamous carcinomas of other organs more than they did oesophageal adenocarcinomas. Our analyses identified three molecular subclasses of oesophageal squamous cell carcinomas, but none showed evidence for an aetiological role of human papillomavirus. Squamous cell carcinomas showed frequent genomic amplifications of CCND1 and SOX2 and/or TP63, whereas ERBB2, VEGFA and GATA4 and GATA6 were more commonly amplified in adenocarcinomas. Oesophageal adenocarcinomas strongly resembled the chromosomally unstable variant of gastric adenocarcinoma, suggesting that these cancers could be considered a single disease entity. However, some molecular features, including DNA hypermethylation, occurred disproportionally in oesophageal adenocarcinomas. These data provide a framework to facilitate more rational categorization of these tumours and a foundation for new therapies

RamDog: A graphical user interface program to interactively analyze 2D Diffraction Images.

<p>A graphical user interface program to interactively analyze 2D Diffraction Images. Initial project setup; bugs throughout the software exist. Development in progress, use at own risk! Contact: (Developer) Dr. Eric Dill [email protected]; (Principal Investigator) Dr. James Martin [email protected]</p

Ka-Band Radiometer Weilheim - Theoretische Betrachtungen zur Bandbreite eines Ka-Band Radiometers zur Messung der atmosphärischen Dämpfung am DLR-Standort Weilheim

Am Standort Weilheim soll für IOT Messungen im Ka-Band die atmospärische Dämpfung durch ein Radiometer gemessen werden. Die notwendige radiometrische Bandbreite wird hergeleitet