The genetic structure of the indigenous hunter-gatherer peoples of southern Africa, the oldest known lineage of modern human, is important for understanding human diversity. Studies based on mitochondrial1 and small sets of nuclear markers2 have shown that these hunter-gatherers, known as Khoisan, San, or Bushmen, are genetically divergent from other humans1,3. However, until now, fully sequenced human genomes have been limited to recently diverged populations4–8. Here we present the complete genome sequences of an indigenous hunter-gatherer from the Kalahari Desert and a Bantu from southern Africa, as well as protein-coding regions from an additional three hunter-gatherers from disparate regions of the Kalahari. We characterize the extent of whole-genome and exome diversity among the five men, reporting 1.3 million novel DNA differences genome-wide, including 13,146 novel amino acid variants. In terms of nucleotide substitutions, the Bushmen seem to be, on average, more different from each other than, for example, a European and an Asian. Observed genomic differences between the hunter-gatherers and others may help to pinpoint genetic adaptations to an agricultural lifestyle. Adding the described variants to current databases will facilitate inclusion of southern Africans in medical research efforts, particularly when family and medical histories can be correlated with genome-wide data.

The authors note that, due to a printer's error, on page 5054, right column, second paragraph, eighth line, "Within this clade, we estimated the mean age of the split between the ABC bears and the polar bears to be 152 ky, and the mean age for all polar bears as 134 ky, near the end of the Eemian interglacial period and completely in line with the stratigraphically determined age of the Poolepynten subfossil (11)," should instead appear as "Within this clade, we estimated the mean age of the split between the ABC bears and the polar bears to be 152 ky, and the mean age for all polar bears as 134 ky, near the beginning of the Eemian interglacial period and completely in line with the stratigraphically determined age of the Poolepynten subfossil (11)." This error does not affect the conclusions of the article. This error has been corrected online and in print.www.pnas.org/cgi

From transcriptional noise to dark matter of biology, the rapidly changing view of long non-coding RNA (lncRNA) leads to deep understanding of human complex diseases induced by abnormal expression of lncRNAs. There is urgent need to discern potential functional roles of lncRNAs for further study of pathology, diagnosis, therapy, prognosis, prevention of human complex disease and disease biomarker detection at lncRNA level. Computational models are anticipated to be an effective way to combine current related databases for predicting most potential lncRNA functions and calculating lncRNA functional similarity on the large scale. In this review, we firstly illustrated the biological function of lncRNAs from five biological processes and briefly depicted the relationship between mutations or dysfunctions of lncRNAs and human complex diseases involving cancers, nervous system disorders and others. Then, 17 publicly available lncRNA function-related databases containing four types of functional information content were introduced. Based on these databases, dozens of developed computational models are emerging to help characterize the functional roles of lncRNAs. We therefore systematically described and classified both 16 lncRNA function prediction models and 9 lncRNA functional similarity calculation models into 8 types for highlighting their core algorithm and process. Finally, we concluded with discussions about the advantages and limitations of these computational models and future directions of lncRNA function prediction and functional similarity calculation. We believe that constructing systematic functional annotation systems is essential to strengthen the prediction accuracy of computational models, which will accelerate the identification process of novel lncRNA functions in the future.

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Plants establish mutualistic associations with beneficial microbes while deploying the immune system to defend against pathogenic ones. Little is known about the interplay between mutualism and immunity and the mediator molecules enabling such crosstalk. Here, we show that plants respond differentially to a volatile bacterial compound through integral modulation of the immune system and the phosphate-starvation response (PSR) system, resulting in either mutualism or immunity. We found that exposure of Arabidopsis thaliana to a known plant growth-promoting rhizobacterium can unexpectedly have either beneficial or deleterious effects to plants. The beneficial-to-deleterious transition is dependent on availability of phosphate to the plants and is mediated by diacetyl, a bacterial volatile compound. Under phosphate-sufficient conditions, diacetyl partially suppresses plant production of reactive oxygen species (ROS) and enhances symbiont colonization without compromising disease resistance. Under phosphate-deficient conditions, diacetyl enhances phytohormone-mediated immunity and consequently causes plant hyper-sensitivity to phosphate deficiency. Therefore, diacetyl affects the type of relation between plant hosts and certain rhizobacteria in a way that depends on the plant's phosphate-starvation response system and phytohormone-mediated immunity.