The patterns of population differentiation in a Brassica rapa core collection

With the recent advances in high throughput profiling techniques the amount of genetic and phenotypic data available has increased dramatically. Although many genetic diversity studies combine morphological and genetic data, metabolite profiling has yet to be integrated into these studies. For our study we selected 168 accessions representing the different morphotypes and geographic origins of Brassica rapa. Metabolite profiling was performed on all plants of this collection in the youngest expanded leaves, 5 weeks after transplanting and the same material was used for molecular marker profiling. During the same season a year later, 26 morphological characteristics were measured on plants that had been vernalized in the seedling stage. The number of groups and composition following a hierarchical clustering with molecular markers was highly correlated to the groups based on morphological traits (r = 0.420) and metabolic profiles (r = 0.476). To reveal the admixture levels in B. rapa, comparison with the results of the programme STRUCTURE was needed to obtain information on population substructure. To analyze 5546 metabolite (LC–MS) signals the groups identified with STRUCTURE were used for random forests classification. When comparing the random forests and STRUCTURE membership probabilities 86% of the accessions were allocated into the same subgroup. Our findings indicate that if extensive phenotypic data (metabolites) are available, classification based on this type of data is very comparable to genetic classification. These multivariate types of data and methodological approaches are valuable for the selection of accessions to study the genetics of selected traits and for genetic improvement programs, and additionally provide information on the evolution of the different morphotypes in B. rapa. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00122-010-1516-1) contains supplementary material, which is available to authorized users

Comparative Methods for Association Studies: A Case Study on Metabolite Variation in a Brassica rapa Core Collection

Background Association mapping is a statistical approach combining phenotypic traits and genetic diversity in natural populations with the goal of correlating the variation present at phenotypic and allelic levels. It is essential to separate the true effect of genetic variation from other confounding factors, such as adaptation to different uses and geographical locations. The rapid availability of large datasets makes it necessary to explore statistical methods that can be computationally less intensive and more flexible for data exploration. Methodology/Principal Findings A core collection of 168 Brassica rapa accessions of different morphotypes and origins was explored to find genetic association between markers and metabolites: tocopherols, carotenoids, chlorophylls and folate. A widely used linear model with modifications to account for population structure and kinship was followed for association mapping. In addition, a machine learning algorithm called Random Forest (RF) was used as a comparison. Comparison of results across methods resulted in the selection of a set of significant markers as promising candidates for further work. This set of markers associated to the metabolites can potentially be applied for the selection of genotypes with elevated levels of these metabolites. Conclusions/Significance The incorporation of the kinship correction into the association model did not reduce the number of significantly associated markers. However incorporation of the STRUCTURE correction (Q matrix) in the linear regression model greatly reduced the number of significantly associated markers. Additionally, our results demonstrate that RF is an interesting complementary method with added value in association studies in plants, which is illustrated by the overlap in markers identified using RF and a linear mixed model with correction for kinship and population structure. Several markers that were selected in RF and in the models with correction for kinship, but not for population structure, were also identified as QTLs in two bi-parental DH populations

Outcome of Endoscopic Variceal Band Ligation

Introduction: Bleeding from esophageal varices in cirrhosis is an emergent condition with high mortality. One of the preferred modality of treating esophageal varices is EVL. We aimed to find out the outcome of EVL in controlling acute esophageal variceal bleeding, prophylactic banding to prevent future bleeding and the number of sessions required for complete eradication of varices. Methods: This descriptive observational study was carried out in Gastroenterology and Hepatology unit of Bir Hospital, NAMS from June 2016 to May 2017. Consecutive cases who presented in emergency room with acute variceal bleeding due to liver cirrhosis and cases of liver cirrhosis with large varices and red color signs on endoscopic examination were enrolled. They underwent EVL and subsequent re-endoscope at one month interval till the eradication of varices was achieved.  Results: Among 83 patients, 15 (18.1%) were of Child Pugh class A, 29 (34.9%) B and 39 (47%) were of C. In 20 (24.1%) cases varices could be eradicated in one session of EVL while 57 (68.7%) required two sessions and in 6 (7.2%) cases it took three sessions. Total average EVL session required for obliteration of esophageal varices was 1.84±0.53. There was only one (1.2%) of early re-bleeding post EVL. Conclusions: EVL is an effective modality of treatment in controlling acute esophageal variceal bleeding, in preventing future variceal bleeding as well as in eradicating esophageal varices, with very few complications. Keywords: acute variceal bleeding; cirrhosis; endoscopic variceal ligation; large varices; red color sign. [PubMed

Determinants of agriculture biodiversity in Western Terai landscape complex of Nepal

The study explored agriculture biodiversity around protected areas and identified factors affecting diversity of agriculture biodiversity in farming households. The study analyzed the data collected from household survey of about 907 farmers from Western-Terai Landscape Complex of Nepal. Intra-species and inter-species richness and evenness in agriculture landscape were estimated and compared across a spectrum of land-uses. The study identified different social, economic, technological and ecological factors affecting the richness of intra-species and inter-species diversity of agriculture biodiversity using generalized linear regression models. Technology index, information index, food security, animal holding, ethnicity, irrigation facility and land-use were found as major variables affecting agriculture. The results also indicated that buffer zones had higher diversity than other land-uses, indicating positive effects of protected-land on surrounding agriculture biodiversity. Results supported need of coordinated efforts to mainstream agriculture biodiversity conservation with landscape conservation plans and socio-economic developments of the region

Determinants of agriculture biodiversity in Western Terai landscape complex of Nepal

The study explored agriculture biodiversity around protected areas and identified factors affecting diversity of agriculture biodiversity in farming households. The study analyzed the data collected from household survey of about 907 farmers from Western-Terai Landscape Complex of Nepal. Intra-species and inter-species richness and evenness in agriculture landscape were estimated and compared across a spectrum of land-uses. The study identified different social, economic, technological and ecological factors affecting the richness of intra-species and inter-species diversity of agriculture biodiversity using generalized linear regression models. Technology index, information index, food security, animal holding, ethnicity, irrigation facility and land-use were found as major variables affecting agriculture. The results also indicated that buffer zones had higher diversity than other land-uses, indicating positive effects of protected-land on surrounding agriculture biodiversity. Results supported need of coordinated efforts to mainstream agriculture biodiversity conservation with landscape conservation plans and socio-economic developments of the region

Regulatory network of secondary metabolism in Brassica rapa:insight into the glucosinolate pathway

Brassica rapa studies towards metabolic variation have largely been focused on the profiling of the diversity of metabolic compounds in specific crop types or regional varieties, but none aimed to identify genes with regulatory function in metabolite composition. Here we followed a genetical genomics approach to identify regulatory genes for six biosynthetic pathways of health-related phytochemicals, i.e carotenoids, tocopherols, folates, glucosinolates, flavonoids and phenylpropanoids. Leaves from six weeks-old plants of a Brassica rapa doubled haploid population, consisting of 92 genotypes, were profiled for their secondary metabolite composition, using both targeted and LC-MS-based untargeted metabolomics approaches. Furthermore, the same population was profiled for transcript variation using a microarray containing EST sequences mainly derived from three Brassica species: B. napus, B. rapa and B. oleracea. The biochemical pathway analysis was based on the network analyses of both metabolite QTLs (mQTLs) and transcript QTLs (eQTLs). Co-localization of mQTLs and eQTLs lead to the identification of candidate regulatory genes involved in the biosynthesis of carotenoids, tocopherols and glucosinolates. We subsequently focused on the well-characterized glucosinolate pathway and revealed two hotspots of co-localization of eQTLs with mQTLs in linkage groups A03 and A09. Our results indicate that such a large-scale genetical genomics approach combining transcriptomics and metabolomics data can provide new insights into the genetic regulation of metabolite composition of Brassica vegetables

EN-BIRTH Data Collector Training - Handbook and Manual

The EN-BIRTH study aims to validate selected newborn and maternal indicators for routine facility-based tracking of coverage and quality of care for use at district, national and global levels. The item contains the EN-BIRTH_Trainer's Manual (14 June 2017) and EN-BIRTH_Training Handbook (23 May 2017)

EN-BIRTH Data Collector Training - Supporting Annexes

The EN-BIRTH study aims to validate selected newborn and maternal indicators for routine facility-based tracking of coverage and quality of care for use at district, national and global levels. The item contains consent forms and participant information, in addition to standard operating procedures (SOP) for adverse clinical events, and managing distress in interviews. The full complement of annex files used during the training can be requested via this site if required

EN-BIRTH Data Collection Tools

The EN-BIRTH study aims to validate selected newborn and maternal indicators for routine facility-based tracking of coverage and quality of care for use at district, national and global levels. The item contains the following data collection tools: Register data extraction, Observation checklist (labour and delivery ward), Observation checklist (kangaroo mother care), Patient record verification tools for antenatal corticosteroid administration, Patient record verification tools for antibiotic administration, and the Maternal recall survey