Report Writing on Genes, Genomics And Human Health With Mendelian And Complex Genetics - Nursing Assignment Help

Assignment Task

Genes, Genomics And Human Health With Mendelian And Complex Genetics 

Note: the same marking rubric is applied to Assessments 1 and 2 to emphasize that all scientific reports have a common structure. There is NO statistical analysis required in Assessment 1  (Analytical Skills, note the use of “where appropriate”). However, in the “Analytical Skills,” it is  expected that “the summary or conclusion of the report interprets the results in the context of appropriate published studies”

Figures, Figure Legends, and Text Describing the Figures 

Figure 3 The cellular phenotype is attributable to reduced BACH2 protein expression. (a)  BACH2 protein expression in primary immune cells from affected subjects and healthy controls. Shown are representative flow cytometry plots (left; numbers indicate the mean  fluorescence intensity) and cumulative BACH2 protein [removed]right) in affected subjects  relative to controls (n = 3 independent experiments) 

In the example above, you can see that the text is describing what the figure is showing. Below is the text in the paper that interprets the figure: 

BACH2 silencing mimics immunodeficient cell phenotypes 

“We next measured BACH2 protein expression by flow cytometry and found that it was reduced in CD4+, CD8+ and B lymphocytes in affected subjects, despite normal mRNA expression in these people compared with that in healthy controls (Fig. 3a, b)”.  

The authors then interpret the rest of Figure 3, before concluding: 

“These observations suggested a causal relationship between reduced BACH2 expression and cellular phenotype”.  

Asthma is a complex disease affecting hundreds of millions of people worldwide. The prevalence of asthma varies across populations and ancestral origins; for example, in the US,  the prevalence ranges from 3.9% in Mexican Americans to 12.5% in  African Americans1. The contribution of genetic factors to asthma  

risk has been demonstrated in family studies, in which heritabil ity estimates range from 25% to 80% (ref. 2). The high variability in prevalence and heritability estimates reflects the roles of envi ronmental exposure in the disease risk and phenotypic heterogene ity that are hallmarks of asthma. These features may explain why genome-wide association studies (GWAS) have identified a smaller  number of asthma loci than have been found in similarly sized stud ies of other multifactorial diseases3. Indeed, at the time of analysis,  only 21 loci have been associated with asthma per se in 20 stud ies, and these loci explain only part of the genetic risk. Although  an exome-array study has shown no evidence of low-frequency  or rare variants with large effects on asthma risk4, the role of rare noncoding variants in asthma remains unknown. Future stud ies based on whole-genome sequencing may clarify the respective  influence of common and rare variants on asthma risk. To generate  larger sample sizes for GWAS meta-analysis of asthma and thereby  enable the discovery of new common risk loci, we established the  Trans-National Asthma Genetic Consortium (TAGC), comprising  worldwide groups of investigators, which has analyzed genome wide data available in 142,000 individuals of diverse ancestries. We  constructed a comprehensive catalog of asthma risk variants that  are robust across populations and environmental-exposure condi tions. By combining TAGC meta-analysis results with data from  existing databases, we assessed the genetic architecture of asthma  risk alleles with respect to functional effects and shared effects with  other diseases. 

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