Genome-wide association study identifies loci and candidate genes for grain micronutrients and quality traits in wheat (Triticum aestivum L.)

Malnutrition due to micronutrients and protein deficiency is recognized among the major global health issues. Genetic biofortification of wheat is a cost-effective and sustainable strategy to mitigate the global micronutrient and protein malnutrition. Genomic regions governing grain zinc concentration (GZnC), grain iron concentration (GFeC), grain protein content (GPC), test weight (TW), and thousand kernel weight (TKW) were investigated in a set of 184 diverse bread wheat genotypes through genome-wide association study (GWAS). The GWAS panel was genotyped using Breeders' 35 K Axiom Array and phenotyped in three different environments during 2019–2020. A total of 55 marker-trait associations (MTAs) were identified representing all three sub-genomes of wheat. The highest number of MTAs were identified for GPC (23), followed by TKW (15), TW (11), GFeC (4), and GZnC (2). Further, a stable SNP was identified for TKW, and also pleiotropic regions were identified for GPC and TKW. In silico analysis revealed important putative candidate genes underlying the identified genomic regions such as F-box-like domain superfamily, Zinc finger CCCH-type proteins, Serine-threonine/tyrosine-protein kinase, Histone deacetylase domain superfamily, and SANT/Myb domain superfamily proteins, etc. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection

Clinical implications of novel activating EGFR mutations in malignant peritoneal mesothelioma

<p>Abstract</p> <p>Background</p> <p>There is a paucity of information about the molecular perturbations involved in MPM tumor formation. We previously reported that EGFR-TK mutations in MPM were predictive of achieving optimal surgical cytoreduction, but the status of EGFR pathway activation potential of these mutations was not known. Here we present the mutant EGFR activating potential and the matured survival data of the EGFR mutant(mut+) relative to wild type EGFR(mut-) mesothelioma.</p> <p>Methods</p> <p>Twenty-nine patients were evaluated and their tumors were probed for mutations in the catalytic TK-domain. Twenty-five patients were treated with cytoreductive surgery and complete clinical data was available for comparison of the mut+ and mut- groups. A COS-7 cell expression model was used to determine mutation activating profiles and response to erlotinib.</p> <p>Results</p> <p>Functional mutations were found in 31%(9/29) of patients; 7 of these mutations were novel and another was the L858R mutation. All missense mutations were found to be activating mutations and responsive to erlotinib. Of the 25 patients managed surgically, there were 7 mut+ and 18 mut-. Two of 7 (29%) mut+ developed progressive disease and died with a median follow-up time of 22 months; while 13/18 (72%) mut- developed progressive disease and 10/18 (56%) died with median TTP of 12 months and median survival of 14 months.</p> <p>Conclusions</p> <p>The novel EGFR mutations identified are activating mutations responsive to erlotinib. The mut+ subset have a 'relative' improved outcome. Erlotinib may have a role in MPM and exploration for mutations in a larger patient cohort is warranted.</p

Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidatesfor targeted treatment

Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs' recapitulation of human tumors

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

On the trade-offs between collecting packet level forensic evidence and data delivery performance in wireless networks

Transmission Evidence (TE for short) refers to a historic trail of the packet transmissions in the network. TE is collected and maintained in a distributed manner by the nodes in the network and can be queried on demand by a network forensics system to trace past events. The latter can facilitate crucial applications such as identifying malicious or malfunctioning nodes. Recently, we developed an analytical framework towards computing the likelihood of TE availability in wireless networks. Our prior efforts [1] brought to light the impact of the network's operational parameters (such as transmission rate and packet length) on the availability of TE. However, provisioning for TE could impact the network performance in terms of throughput and/or delay. Our objective in this work is to capture and quantify the trade-offs between provisioning transmission evidence and achieving high performance in wireless networks. In particular, we investigate the network performance hit, under the constraint of TE availability guarantees. Our results indicate that the performance remains unaffected up to a certain TE requirement. Beyond this, the throughput could degrade and the delay could increase by as much as 30%. To the best of our knowledge, this is the first study of its kind. © 2013 IEEE