SMBE 2013 abstracts

Some abstracts from the SMBE 2013 conference that will take place next week. 

Legacy of Early Migrants in Neolithic East Asian Hunter-Gatherer from Fukushima, Japan

K.K. Hideaki et al.   

Clarifying the genetic relationship between Neolithic East Asian Hunter-Gatherer, Jomon people, and modern human populations is one of the Keystones to understand the controversial history of modern East Asian populations. Jomon people inhabited in the Japanese archipelago from 16,000 years ago, and their origin and the relationship with modern humans have been debated for a long time. To solve these questions, we obtained 20 million base pairs of genomic DNA from a ~4,000-year-old Jomon male tooth, excavated in Sanganji shell mound, Fukushima, Japan. We compared his genetic components with the data of modern worldwide populations. Our major findings are: (1) Sanganji Jomon was very similar with modern East Asians when we compared the worldwide populations in the PCA plot; (2) when only East Asians were compared, Sanganji Jomon was distant from both modern Northeast and Southeast Asians, indicating that Sanganji Jomon people were already isolated from other continental populations for a long time; (3) the Sanganji Jomon male shared more SNP alleles with southern and northern minorities in China than geographically close Han Chinese, implying a complex history of people in China after the divergence between Jomon ancestors and Eurasian continent people; (4) Sanganji Jomon is genetically closer to modern mainland Japanese than continental populations, indicating that some of their components were transmitted to modern Japanese; (5) within Japanese archipelago, Ainu and Ryukyuan (the populations of northern and southern edges of the Japanese archipelago) have more Jomon components than mainland Japanese, indicating that the genetic effect of agricultural people who migrated from the Eurasian continent in and after the Yayoi period is stronger in Mainland Japanese than Ainu and Ryukyuan.

Extensive Gene Gain in Human Brain Evolution

Yong E. Zhang et al.
The genetic changes contributing to the evolution of the human brain have always attracted wide interest. A emerging consensus view is that while there have been no major patterns of genome-wide changes to the coding regions of brain-related genes, cis-regulatory changes of these genes have played a key role. Here, motivated by anecdotal studies of primate-specific genes implicated in brain function, we identified thousands of lineage-specific (primate-specific or rodent-specific) genes by mining syntenic vertebrate genomic alignments and examined the expression profile of these genes in both fetal and adult brains of human and mouse across different transcriptome profiling platforms. We found that an excess of lineage-specific genes are expressed in the early (fetal or infant) developing human brain compared with those in mouse brain. Expression data covering numerous subregions of the developing brain further demonstrate that these young genes are mainly transcribed in the neocortex. They originated in the evolutionary period during which the neocortex was expanding, suggesting the functional association of new genes with this newly evolving brain structure. Our data reveal that evolutionary change in the development of the human brain happened at the protein level by gene origination and also via evolution of regulatory networks, as hinted by the enrichment of primate-specific transcriptional regulators in our dataset. More than that, these ?ndings suggest that genomes are continually evolving in both sequence and content, eroding the conservation endowed by common ancestry. Despite increasing recognition of the importance of new genes, these genes are still seriously under-characterized in functional studies and that new gene annotation is inconsistent in current practice. We propose an integrative approach based on functional and evolutionary genomic methods to better annotate these non-conserved genes.

Recent Human Demography Impacts the Architecture of Genetic Disease in Populations but Not Individual Genetic Load

Yuval Simons et al.
Human populations have undergone dramatic changes in population sizes in the past 100,000 years, including a severe bottleneck of non-African populations and recent explosive population growth. There is currently great interest in how these demographic events may have affected the burden of deleterious mutations in individuals and the allele frequency spectrum of disease mutations in populations. Here we use population genetic models to show that--contrary to previous conjectures--recent human demography likely had very little impact on the average burden of deleterious mutations carried by individuals. This prediction is supported by exome sequence data showing that African American and European American individuals carry very similar burdens of damaging mutations. We next considered whether recent population growth has increased the importance of very rare mutations in disease. Our analysis predicts that, even given recent growth, it is unlikely that very rare mutations contribute a large fraction of disease heritability except for diseases that are largely due to strongly deleterious mutations. In summary, demographic history has dramatically impacted patterns of variation in different human populations, but these changes likely had little impact on either genetic load or on the importance of rare variants in most complex traits.

Functional and Population Genetic Analyses of a High-Coverage Neandertal Genome

Fernando Racimo et al.
We have sequenced the genome of a Neandertal from the Altai mountains in Siberia at 50-fold coverage. This Neandertal was located in the same cave as the Denisovan individual, but is phylogenetically closer to Neandertals from Western Eurasia. To avoid confusion, we call this individual the Altai Neandertal. Here we show an assessment of genome data quality and functional and population genetic comparisons with the Denisovan genome and a set of 25 high-coverage modern human genomes. We present an analysis of genes with recent changes in either the modern human lineage or the archaic human lineage (Neandertal+Denisova). We find enrichment for nonsynonymous changes in genes associated with melanosomes in the modern human lineage, and genes associated with particular muscoskeletal morphologies in the archaic human lineage. We utilize a compound deleteriousness scoring that allows us to combine a variety of conservation, regulatory and expression data to rank all modern and archaic-specific single-nucleotide changes and InDels across the genome, and predict which are those that could have been most disruptive in our evolutionary history. Furthermore, we overlap the modern-specific catalog with the top regions of a screen for selective sweeps exclusive to the modern human lineage, and observe enrichments for changes in genes related to ion channel activity, muscle contraction and membrane transport. Finally, we note an excess of ancestral alleles in the Denisovan individual relative to the Altai Neandertal individual, which is strongest at sites where modern humans are fixed derived. We develop an approximate Bayesian computation approach that allows us to test different models, and conclude that gene flow between the Denisovan individual and a more anciently diverged human lineage is most consistent with the patterns observed.

Multiple Episodes of Population Mixture in Southern African History

Joseph K. Pickrell et al.
The history of southern Africa involved interactions between indigenous hunter-gatherers and a range of populations that moved temporarily or permanently into the region. The influence of these interactions on the genetic structure of current populations remains unclear. Here, using patterns of linkage disequilibrium, we show that there are at least two admixture events in the genetic history of southern African hunter-gatherers and pastoralists: one involving populations related to Niger-Congo-speaking African populations, and one which introduced ancestry most closely related to west Eurasian (European or Middle Eastern) populations. We estimate that at least a few percent of ancestry in the Khoisan is derived from this latter admixture event, which occurred on average 1,200-1,800 years ago. We show that a similar signal of west Eurasian ancestry is present throughout eastern Africa; in particular, we also find evidence for two admixture events in the genetic history of several Kenyan, Tanzanian, and Somali populations, the earliest of which involved populations related to southern Europeans and which we date to approximately 2700 - 3300 years ago. We thus suggest that west Eurasian ancestry entered southern Africa indirectly through eastern Africa. These results demonstrate how large-scale genomic datasets can inform complex models of population movements, and highlight the genomic impact of largely uncharacterized back-to-Africa migrations in human history.

Mechanistic Models of Admixture and Approximate-Approximate-Bayesian Computation 

Noah Rosenberg et al.   

Investigations of the history of migrations that underlie admixed populations often use nonmechanistic admixture models rather than a modeling perspective that incorporates a population-genetic history of admixture built from first principles. We build a general model of admixture that mechanistically accounts for complex admixture processes, considering two source populations that contribute to the ancestry of a hybrid population, potentially with variable contributions across generations. For a random individual in the hybrid population at a given point in time, we study the fraction of admixture originating from a specific one of the source populations. Quite different admixture processes can produce identical mean admixture across individuals, but such processes typically produce different values for the variance of admixture. Interestingly, even without considering sex chromosomes, the variance of admixture for autosomes captures information about sex-specific migration in the contributions of the source populations to the admixed group. To perform inference under the model, we use approximate-approximate-Bayesian computation (AABC), a modification of approximateBayesian computation well-suited to estimation under complex mechanistic models that are computationally intensive to simulate. The model and inference method can contribute to an understanding of the theory and analysis of the history of admixed populations.

Inferring Human Population History and Migration Patterns from Multiple Genome Sequences

Stephan Schiffels, Richard Durbin
The availability of human genomes from populations across the world has given rise to new inference methods that exploit high-coverage sequence data. Among the most influential recent developments is the Pairwise Sequentially Markovian Coalescenct (PSMC) by Li and Durbin, 2011. While PSMC infers the demographic history for times between 20kya and 2mya with high resolution, neither the more recent evolutionary history nor migration patterns across populations can be adressed. Here we present a new method that overcomes both of these shortcomings. The Multiple Sequentially Markovian Coalescent (MSMC) infers the recent evolutionary history within and across populations only a few thousand years ago and younger. MSMC models the pattern of mutations in multiple genome sequences under the coalescent with recombination. It fits local genealogical trees to the observed pattern, focussing on the first coalescence among any two individuals. We apply our method to the genome sequences from several family trios from the 1000 Genomes project with African, European, Asian and SouthAmerican ancestry. We infer population sizes and migration rates as a function of time with high resolution. In particular, our method resolves the more recent evolutionary history of non-African populations after the out-of-Africa event, such as the peopling of the Americas.