“Orangutan” is derived from the Malay term “man of the forest” and aptly describes the Southeast Asian great apes native to Sumatra and Borneo. The orangutan species, Pongo abelii (Sumatran) and Pongo pygmaeus (Bornean), are the most phylogenetically distant great apes from humans, thereby providing an informative perspective on hominid evolution. Here we present a Sumatran orangutan draft genome assembly and short read sequence data from five Sumatran and five Bornean orangutan genomes. Our analyses reveal that, compared to other primates, the orangutan genome has many unique features. Structural evolution of the orangutan genome has proceeded much more slowly than other great apes, evidenced by fewer rearrangements, less segmental duplication, a lower rate of gene family turnover and surprisingly quiescent Alu repeats, which have played a major role in restructuring other primate genomes. We also describe the first primate polymorphic neocentromere, found in both Pongo species, emphasizing the gradual evolution of orangutan genome structure. Orangutans have extremely low energy usage for a eutherian mammal1, far lower than their hominid relatives. Adding their genome to the repertoire of sequenced primates illuminates new signals of positive selection in several pathways including glycolipid metabolism. From the population perspective, both Pongo species are deeply diverse; however, Sumatran individuals possess greater diversity than their Bornean counterparts, and more species-specific variation. Our estimate of Bornean/Sumatran speciation time, 400k years ago (ya), is more recent than most previous studies and underscores the complexity of the orangutan speciation process. Despite a smaller modern census population size, the Sumatran effective population size (Ne) expanded exponentially relative to the ancestral Ne after the split, while Bornean Ne declined over the same period. Overall, the resources and analyses presented here offer new opportunities in evolutionary genomics, insights into hominid biology, and an extensive database of variation for conservation efforts.

Human populations have experienced dramatic growth since the Neolithic revolution. Recent studies that sequenced a very large number of individuals observed an extreme excess of rare variants and provided clear evidence of recent rapid growth in effective population size, although estimates have varied greatly among studies. All these studies were based on protein-coding genes, in which variants are also impacted by natural selection. In this study, we introduce targeted sequencing data for studying recent human history with minimal confounding by natural selection. We sequenced loci far from genes that meet a wide array of additional criteria such that mutations in these loci are putatively neutral. As population structure also skews allele frequencies, we sequenced 500 individuals of relatively homogeneous ancestry by first analyzing the population structure of 9,716 European Americans. We used very high coverage sequencing to reliably call rare variants and fit an extensive array of models of recent European demographic history to the site frequency spectrum. The best-fit model estimates ∼3.4% growth per generation during the last ∼140 generations, resulting in a population size increase of two orders of magnitude. This model fits the data very well, largely due to our observation that assumptions of more ancient demography can impact estimates of recent growth. This observation and results also shed light on the discrepancy in demographic estimates among recent studies.A rcheological and historical records reveal that modern human populations have experienced dramatic growth, likely driven by the Neolithic revolution about 10,000 y ago (1, 2). Since then, the worldwide human population size has increased at a fast pace, and faster yet in the last ∼2,000 y, giving rise to today's population in excess of 7 billion people (3, 4). A central question in population genetics is how such demographic events affect the effective size (N e ) of populations over time, and as a consequence, how they have shaped extant patterns of genetic variation. [Effective population size, which is typically smaller than the census size, determines the genetic properties of a population (5).] Focusing often on human populations of European descent, estimates of N e from genetic variation have been traditionally on the order of 10,000 individuals (6-11), although higher and lower estimates have also been obtained (12-16). More recent studies based on sequencing data from a relatively small number of individuals have considered recent population growth in fitting models to the observed site frequency spectrum (SFS) and reported as much as a 0.5% increase in N e per generation, culminating in a N e of a few tens of thousands today (13,14). It has been recently hypothesized that these studies could not capture the full scope of population growth because a larger sample size of individuals is needed to observe single nucleotide variants (SNVs) that arose during the recent epoch of growth (4).With extreme recent population growth as experie...

The application of high-throughput plant phenotyping (HTPP) to continuously study plant populations under relevant growing conditions creates the possibility to more efficiently dissect the genetic basis of dynamic adaptive traits. Toward this end, we employed a field-based HTPP system that deployed sets of sensors to simultaneously measure canopy temperature, reflectance, and height on a cotton (Gossypium hirsutum L.) recombinant inbred line mapping population. The evaluation trials were conducted under well-watered and water-limited conditions in a replicated field experiment at a hot, arid location in central Arizona, with trait measurements taken at different times on multiple days across 2010–2012. Canopy temperature, normalized difference vegetation index (NDVI), height, and leaf area index (LAI) displayed moderate-to-high broad-sense heritabilities, as well as varied interactions among genotypes with water regime and time of day. Distinct temporal patterns of quantitative trait loci (QTL) expression were mostly observed for canopy temperature and NDVI, and varied across plant developmental stages. In addition, the strength of correlation between HTPP canopy traits and agronomic traits, such as lint yield, displayed a time-dependent relationship. We also found that the genomic position of some QTL controlling HTPP canopy traits were shared with those of QTL identified for agronomic and physiological traits. This work demonstrates the novel use of a field-based HTPP system to study the genetic basis of stress-adaptive traits in cotton, and these results have the potential to facilitate the development of stress-resilient cotton cultivars.

Primate intron divergence

An analysis of human-chimpanzee intron divergence shows strong correlations between intron length and divergence and GC-content.