Ancient DNA from the Andes reveals a complex picture of human adaptation from early settlement to the colonial period.

Patagonia was the last region of the Americas reached by humans who entered the continent from Siberia ∼15,000–20,000 y ago. Despite recent genomic approaches to reconstruct the continental evolutionary history, regional characterization of ancient and modern genomes remains understudied. Exploring the genomic diversity within Patagonia is not just a valuable strategy to gain a better understanding of the history and diversification of human populations in the southernmost tip of the Americas, but it would also improve the representation of Native American diversity in global databases of human variation. Here, we present genome data from four modern populations from Central Southern Chile and Patagonia (n = 61) and four ancient maritime individuals from Patagonia (∼1,000 y old). Both the modern and ancient individuals studied in this work have a greater genetic affinity with other modern Native Americans than to any non-American population, showing within South America a clear structure between major geographical regions. Native Patagonian Kawéskar and Yámana showed the highest genetic affinity with the ancient individuals, indicating genetic continuity in the region during the past 1,000 y before present, together with an important agreement between the ethnic affiliation and historical distribution of both groups. Lastly, the ancient maritime individuals were genetically equidistant to a ∼200-y-old terrestrial hunter-gatherer from Tierra del Fuego, which supports a model with an initial separation of a common ancestral group to both maritime populations from a terrestrial population, with a later diversification of the maritime groups. Significance Recent genomic studies of ancient and modern humans from the Americas have given a comprehensive view of the peopling of the continent. However, regional characterization of ancient and modern individuals is lacking, being key to unveiling fine-scale differences within the continent. We present genome-wide analyses of ancient and modern individuals from South America from Western Patagonia. We found a strong affinity between modern and ancient individuals from the region, providing evidence of continuity in the region for the last ∼1,000 years and regional genetic structure within Southern South America. In particular, the analysis of these ancient genomes helps address questions related to the maritime tradition in the region and its diversification posterior to the split from terrestrial hunter-gatherers.

Summary: Visualizing genomic data in chromosomal context can help detecting errors in data processing and may suggest new hypotheses to be tested. Here, we report a new tool for displaying large and diverse genomic data along chromosomes. The software is implemented in R so that visualization can be easily integrated with its numerous packages for processing genomic data. It supports simultaneous visualization of multiple tracks of data. Large genomic regions such as QTLs or synteny tracts may be shown along histograms of number of genes, genetic variants, or any other type of genomic element. Tracks can also contain values for continuous or categorical variables and the user can choose among points, connected lines, colored segments, or histograms for representing data. chromPlot takes data from tables in data.frame in GRanges formats. The information necessary to draw chromosomes for mouse and human is included with the package. For other organisms, chromPlot can read Gap and cytoBandIdeo tables from the UCSC Genome Browser. We present common use cases here, and a full tutorial is included as the package’s vignette. Availability and Implementation: chromPlot is distributed under a GLP2 licence at http://www.bioconductor.org. Contact:raverdugo@u.uchile.cl Supplementary information: Supplementary data are available at Bioinformatics online.

Whole transcriptome RNA variant analyses have shown that adenosine deaminases acting on RNA (ADAR) enzymes modify a large proportion of cellular RNAs, contributing to transcriptome diversity and cancer evolution. Despite the advances in the understanding of ADAR function in breast cancer, ADAR RNA editing functional consequences are not fully addressed. We characterized A to G(I) mRNA editing in 81 breast cell lines, showing increased editing at 3′UTR and exonic regions in breast cancer cells compared to immortalized non-malignant cell lines. In addition, tumors from the BRCA TCGA cohort show a 24% increase in editing over normal breast samples when looking at 571 well-characterized UTRs targeted by ADAR1. Basal-like subtype breast cancer patients with high level of ADAR1 mRNA expression shows a worse clinical outcome and increased editing in their 3′UTRs. Interestingly, editing was particularly increased in the 3′UTRs of ATM, GINS4 and POLH transcripts in tumors, which correlated with their mRNA expression. We confirmed the role of ADAR1 in this regulation using a shRNA in a breast cancer cell line (ZR-75-1). Altogether, these results revealed a significant association between the mRNA editing in genes related to cancer-relevant pathways and clinical outcomes, suggesting an important role of ADAR1 expression and function in breast cancer.

Background: The identification of novel genes is critical to understanding the molecular basis of body weight. Towards this goal, we have identified secretogranin V (Scg5; also referred to as Sgne1), as a candidate gene for growth traits. Results: Through a combination of DNA microarray analysis and quantitative PCR we identified a strong expression quantitative trait locus (eQTL) regulating Scg5 expression in two mouse chromosome 2 congenic strains and three additional F2 intercrosses. More importantly, the eQTL was coincident with a body weight QTL in congenic mice and Scg5 expression was negatively correlated with body weight in two of the F2 intercrosses. Analysis of haplotype blocks and genomic sequencing of Scg5 in high (C3H/HeJ, DBA/2J, BALB/cByJ, CAST/EiJ) and low (C57BL/6J) expressing strains revealed mutations unique to C57BL/6J and possibly responsible for the difference in mRNA abundance. To evaluate the functional consequence of Scg5 overexpression we measured the pituitary levels of 7B2 protein and PCSK2 activity and found both to be increased. In spite of this increase, the level of pituitary α-MSH, a PCSK2 processing product, was unaltered. Conclusion: Together, these data support a role for Scg5 in the modulation of body weight.

Measurements of gene expression from microarray experiments are highly dependent on experimental design. Systematic noise can be introduced into the data at numerous steps. On Illumina BeadChips, multiple samples are assayed in an ordered series of arrays. Two experiments were performed using the same samples but different hybridization designs. An experiment confounding genotype with BeadChip and treatment with array position was compared to another experiment in which these factors were randomized to BeadChip and array position. An ordinal effect of array position on intensity values was observed in both experiments. We demonstrate that there is increased rate of false-positive results in the confounded design and that attempts to correct for confounded effects by statistical modeling reduce power of detection for true differential expression. Simple analysis models without post hoc corrections provide the best results possible for a given experimental design. Normalization improved differential expression testing in both experiments but randomization was the most important factor for establishing accurate results. We conclude that lack of randomization cannot be corrected by normalization or by analytical methods. Proper randomization is essential for successful microarray experiments.