AGN populations in GOODS-N through eMERGE ultra-deep JVLA observations

Multi-wavelength studies of deep radio fields show a composite population of star-forming galaxies, radio-quiet and radio-loud AGNs, with the formers dominating at the lowest flux densities (In my talk I will report about the e-MERLIN Galaxy Evolution Survey (eMERGE, PI: Muxlow), a legacy project which aims at undertaking a spatially-resolved study of AGN and star formation processes up to high redshift in a 30 arcmin diameter field in the GOODS-N region, through ultra-deep (sub-microJy rms), sub-arcsec (50-500 mas) imaging at 1.4 and 5 GHz, using combined JVLA and eMERLIN observations. I will focus on the 5 GHz JVLA mosaic observations and catalogue of GOODS-N (94 sources), in the framework of the eMERGE project, and on the study of a larger sample of GOODS-N galaxies (300 objects) selected at 1.4 GHz to constrain the presence of AGN cores in moderate-to-high redshift (1<z<5) galaxies, via radio spectra-morphological analysis with the additional help of multi-wavelength information

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40–50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10–20% (14–24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries. © 2022, The Author(s)