Study of the Transcriptome of the Uterine Fundus, Lower Uterine Segment, and Cervix in Women Not in Labor (Left) and in Labor (Right)

<p>This is a diagrammatic representation of the results reported by Bukowski et al. (Illustration: Giovanni Maki)</p

Understanding the pathogenesis of abdominal aortic aneurysms

<div><p>An aortic aneurysm is a dilatation in which the aortic diameter is ≥3.0 cm. If left untreated, the aortic wall continues to weaken and becomes unable to withstand the forces of the luminal blood pressure resulting in progressive dilatation and rupture, a catastrophic event associated with a mortality of 50–80%. Smoking and positive family history are important risk factors for the development of abdominal aortic aneurysms (AAA). Several genetic risk factors have also been identified. On the histological level, visible hallmarks of AAA pathogenesis include inflammation, smooth muscle cell apoptosis, extracellular matrix degradation and oxidative stress. We expect that large genetic, genomic, epigenetic, proteomic and metabolomic studies will be undertaken by international consortia to identify additional risk factors and biomarkers, and to enhance our understanding of the pathobiology of AAA. Collaboration between different research groups will be important in overcoming the challenges to develop pharmacological treatments for AAA.</p></div

Comparison of true positive hits (left) and false positive hits (right) for the SAC with true ancestry used in GWAS models.

The average hits for three runs with different causal SNPs are shown. The simulated phenotypes are denoted as “phenotype-ancestral source of association”, e.g.,LAAA-CHB means the LAAA phenotype with the CHB ancestral components as the ancestral source of association. The various GWAS models used are indicated in different colours. Grey represents the APA model, yellow represents the GA model, blue represents the LA model, green represents the LAAA model and the orange represents the Standard model.</p

Overview of the methods used to simulate genotypes using the software msprime and phenotypes using the software PhenotypeSimulator.

Overview of the methods used to simulate genotypes using the software msprime and phenotypes using the software PhenotypeSimulator.</p

Additional file 4: Figure S2. of The complete genome sequence of the African buffalo (Syncerus caffer)

Simulations to estimate heterozygosity ratio. (PDF 72 kb

Breakdown of the effect sizes that make up the phenotypes simulated for the SAC.

Breakdown of the effect sizes that make up the phenotypes simulated for the SAC.</p

Additional file 5: Figure S5. of The complete genome sequence of the African buffalo (Syncerus caffer)

Phylogeny and divergence of 13 mammals. (PDF 352 kb

The ancestral proportions and the accuracy of the inferred local ancestry for the Nama.

The ancestral proportions and the accuracy of the inferred local ancestry for the Nama.</p

Additional file 11: Table S6. of The complete genome sequence of the African buffalo (Syncerus caffer)

Summary of function annotation for African buffalo. (PDF 45 kb

Additional file 6: Figure S3. of The complete genome sequence of the African buffalo (Syncerus caffer)

Distribution of the read depth for the de novo assembled S. caffer genome. (PDF 86 kb