Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. AVAILABILITY: The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc.     

Insyght: navigating amongst abundant homologues,syntenies and gene functional annotations in bacteria,it's that symbol!

High-throughput techniques have considerably increased the potential of comparative genomics whilst simultaneously posing many new challenges. One of those challenges involves efficiently mining the large amount of data produced and exploring the landscape of both conserved and idiosyncratic genomic regions across multiple genomes. Domains of application of these analyses are diverse: identification of evolutionary events, inference of gene functions, detection of niche-specific genes or phylogenetic profiling. Insyght is a comparative genomic visualization tool that combines three complementary displays: (i) a table for thoroughly browsing amongst homologues, (ii) a comparator of orthologue functional annotations and (iii) a genomic organization view designed to improve the legibility of rearrangements and distinctive loci. The latter display combines symbolic and proportional graphical paradigms. Synchronized navigation across multiple species and interoperability between the views are core features of Insyght. A gene filter mechanism is provided that helps the user to build a biologically relevant gene set according to multiple criteria such as presence/absence of homologues and/or various annotations. We illustrate the use of Insyght with scenarios. Currently, only Bacteria and Archaea are supported. A public instance is available at http://genome.jouy.inra.fr/Insyght. The tool is freely downloadable for private data set analysis.     

SESAME (SEquence Sorter & AMplicon Explorer): genotyping based on high-throughput multiplex amplicon sequencing

SUMMARY: Characterizing genetic diversity through genotyping short amplicons is central to evolutionary biology. Next-generation sequencing (NGS) technologies changed the scale at which these type of data are acquired. SESAME is a web application package that assists genotyping of multiplexed individuals for several markers based on NGS amplicon sequencing. It automatically assigns reads to loci and individuals, corrects reads if standard samples are available and provides an intuitive graphical user interface (GUI) for allele validation based on the sequences and associated decision-making tools. The aim of SESAME is to help allele identification among a large number of sequences. AVAILABILITY: SESAME and its documentation are freely available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported Licence for Windows and Linux from http://www1.montpellier.inra.fr/CBGP/NGS/ or http://tinyurl.com/ngs-sesame.     

Reversal of Salt Preference Is Directed by the Insulin/PI3K and Gq/PKC Signaling in Caenorhabditis elegans

Animals search for foods and decide their behaviors according to previous experience. Caenorhabditis elegans detects chemicals with a limited number of sensory neurons, allowing us to dissect roles of each neuron for innate and learned behaviors. C. elegans is attracted to salt after exposure to the salt (NaCl) with food. In contrast, it learns to avoid the salt after exposure to the salt without food. In salt-attraction behavior, it is known that the ASE taste sensory neurons (ASEL and ASER) play a major role. However, little is known about mechanisms for learned salt avoidance. Here, through dissecting contributions of ASE neurons for salt chemotaxis, we show that both ASEL and ASER generate salt chemotaxis plasticity. In ASER, we have previously shown that the insulin/PI 3-kinase signaling acts for starvation-induced salt chemotaxis plasticity. This study shows that the PI 3-kinase signaling promotes aversive drive of ASER but not of ASEL. Furthermore, the G_q signaling pathway composed of G_qα EGL-30, diacylglycerol, and nPKC (novel protein kinase C) TTX-4 promotes attractive drive of ASER but not of ASEL. A putative salt receptor GCY-22 guanylyl cyclase is required in ASER for both salt attraction and avoidance. Our results suggest that ASEL and ASER use distinct molecular mechanisms to regulate salt chemotaxis plasticity.ANIMALS show various behaviors in response to environmental cues and modulate behaviors according to previous experience. To understand neuronal plasticity underlying learning, it is important to dissect neurons and molecules for sensing environmental stimuli, storing memory, and executing learned behaviors.The nematode Caenorhabditis elegans has only 302 neurons and functions of sensory neurons are well characterized (White et al. 1986; Bargmann 2006). C. elegans is attracted to odorants sensed by the AWC olfactory neurons or to salts sensed by the ASE gustatory neurons (Bargmann and Horvitz 1991; Bargmann et al. 1993). The ASE neuron class consists of a bilaterally symmetrical pair, ASE-left (ASEL) and ASE-right (ASER), which sense different sets of ions including Na⁺ and Cl⁻, respectively (Pierce-Shimomura et al. 2001; Suzuki et al. 2008; Ortiz et al. 2009). ASEL is activated by an increase in salt concentration, whereas ASER is activated by a decrease in salt concentration (Suzuki et al. 2008). In the ASE gustatory neurons, a cyclic GMP (cGMP) signaling pathway mediates sensory transduction (Komatsu et al. 1996; Suzuki et al. 2008; Ortiz et al. 2009). ASEL and ASER express different sets of receptor-type guanylyl cyclases (gcys) (Ortiz et al. 2006). Of these, gcy-22, which is specifically expressed in ASER, is important for attraction to ASER-sensed ions such as Cl⁻ (Ortiz et al. 2009).Preference for salts changes according to previous experience (known as gustatory plasticity or salt chemotaxis learning) (Saeki et al. 2001; Jansen et al. 2002; Tomioka et al. 2006). When worms are grown on a medium that contains sodium chloride (NaCl) and food (Escherichia coli), they show attraction to NaCl by using ASE neurons (Bargmann and Horvitz 1991; Suzuki et al. 2008). In contrast, after exposure to the salt under starvation conditions, they show reduced attraction to or even avoid the salt (Saeki et al. 2001; Jansen et al. 2002; Tomioka et al. 2006). In C. elegans, it was proposed that preference for a sensory cue is defined by the sensory neuron that detects the cue (Troemel et al. 1997). ASE neurons play a major role for salt attraction (Bargmann and Horvitz 1991; Suzuki et al. 2008; Ortiz et al. 2009). However, little is known about sensory neurons that drive the learned salt avoidance; it remains unclear whether ASE neurons act as salt receptors for the learned avoidance.We have previously shown that an insulin/PI 3-kinase signaling pathway is essential for salt chemotaxis learning (Tomioka et al. 2006). In C. elegans, the insulin-like signaling is composed of daf-2, age-1, and akt-1, which encode homologs of insulin receptor, PI 3-kinase, and protein kinase B, respectively (Morris et al. 1996; Kimura et al. 1997; Paradis and Ruvkun 1998). Mutants of daf-2, age-1, and akt-1 show attraction to salt even after starvation/NaCl conditioning (Tomioka et al. 2006).daf-18 encodes a homolog of phosphatase PTEN (phosphatase and tensin homolog deleted on chromosome ten), which dephosphorylates phosphatidylinositol (3,4,5)-triphosphate and counteracts the insulin/PI 3-kinase signaling (Ogg and Ruvkun 1998; Gil et al. 1999; Mihaylova et al. 1999; Rouault et al. 1999; Solari et al. 2005). Mutants of daf-18, in which the PI 3-kinase signaling is activated, show reduced attraction to NaCl even without conditioning. Since the insulin/PI 3-kinase signaling acts in ASER, we proposed that the insulin/PI 3-kinase signaling attenuates the attractive drive of ASER (Tomioka et al. 2006).In C. elegans, diacylglycerol (DAG) regulates functions of motor neurons and sensory neurons. egl-30, which encodes the α-subunit of heterotrimeric G-protein G_q, facilitates production of DAG and enhances locomotory movements (Brundage et al. 1996; Lackner et al. 1999). In the AWC olfactory neurons, a novel protein kinase C-ɛ/η (nPKC-ɛ/η) ortholog TTX-4 (also known as PKC-1), which is one of DAG targets, plays an essential role in attraction behavior to AWC-sensed odors (Okochi et al. 2005; Tsunozaki et al. 2008). GOA-1 G_oα regulates olfactory adaptation by antagonizing G_qα–DAG signaling (Matsuki et al. 2006).This study investigated the involvement of the ASE taste receptor neurons in the starvation-induced salt avoidance. We show that both ASEL and ASER contribute to salt chemotaxis learning. Activation of the PI 3-kinase signaling and the G_q/DAG/PKC signaling acted antagonistically in reversal of ASER function, whereas these signaling pathways did not have prominent effects on ASEL function. In ASER, GCY-22 was required for both salt attraction and avoidance. These results suggest that ASE neurons are important for bidirectional chemotaxis and also suggest that distinct molecular mechanisms regulate functions of ASEL and ASER in salt chemotaxis learning.     

|SE|S|AM|E| Barcode: NGS‐oriented software for amplicon characterization – application to species and environmental barcoding

Progress in NGS technologies has opened up new opportunities for characterizing biodiversity, both for individual specimen identification and for environmental barcoding. Although the amount of data available to biologist is increasing, user‐friendly tools to facilitate data analysis have yet to be developed. Our aim, with |SE|S|AM|E| Barcode, is to provide such support through a unified platform. The sequences are analysed through a pipeline that (i) processes NGS amplicon runs, filtering markers and samples, (ii) builds reference libraries and finally (iii) identifies (barcodes) the sequences in each amplicon from the reference library. We use a simulated data set for specimen identification and a recently published data set for environmental barcoding to validate the method. The results obtained are consistent with the expected characterizations (in silico and previously published, respectively). |SE|S|AM|E| Barcode and its documentation are freely available under the Creative Commons Attribution‐NonCommercial‐ShareAlike 3.0 Unported Licence for Windows and Linux from http://www1.montpellier.inra.fr/CBGP/NGS/ .     

A Ubiquitin E2 Variant Protein Acts in Axon Termination and Synaptogenesis in Caenorhabditis elegans

In the developing nervous system, cohorts of events regulate the precise patterning of axons and formation of synapses between presynaptic neurons and their targets. The conserved PHR proteins play important roles in many aspects of axon and synapse development from C. elegans to mammals. The PHR proteins act as E3 ubiquitin ligases for the dual-leucine-zipper-bearing MAP kinase kinase kinase (DLK MAPKKK) to regulate the signal transduction cascade. In C. elegans, loss-of-function of the PHR protein RPM-1 (Regulator of Presynaptic Morphology-1) results in fewer synapses, disorganized presynaptic architecture, and axon overextension. Inactivation of the DLK-1 pathway suppresses these defects. By characterizing additional genetic suppressors of rpm-1, we present here a new member of the DLK-1 pathway, UEV-3, an E2 ubiquitin-conjugating enzyme variant. We show that uev-3 acts cell autonomously in neurons, despite its ubiquitous expression. Our genetic epistasis analysis supports a conclusion that uev-3 acts downstream of the MAPKK mkk-4 and upstream of the MAPKAPK mak-2. UEV-3 can interact with the p38 MAPK PMK-3. We postulate that UEV-3 may provide additional specificity in the DLK-1 pathway by contributing to activation of PMK-3 or limiting the substrates accessible to PMK-3.CHEMICAL synapses are specialized cellular junctions that enable neurons to communicate with their targets. An electrical impulse causes calcium channel opening and consequently stimulates synaptic vesicles in the presynaptic terminals to fuse at the plasma membrane. Neurotransmitter activates receptors on the postsynaptic membrane and triggers signal transduction in the target cell. For this communication to occur efficiently, the organization of the proteins within these juxtaposed pre- and postsynaptic terminals must be tightly regulated (Jin and Garner 2008). Previous studies in Caenorhabditis elegans have identified RPM-1, a member of the conserved PHR (Pam/Highwire/RPM-1) family of proteins, as an important regulator for the synapse (Schaefer et al. 2000; Zhen et al. 2000). Recent functional studies of other PHR proteins have shown that they are also required for a number of steps during nervous system development including axon guidance, growth, and termination (Wan et al. 2000; D''souza; et al. 2005; Bloom et al. 2007; Grill et al. 2007; Lewcock et al. 2007; Li et al. 2008).The signaling cascades regulated by the PHR proteins have been identified using genetic modifier screens (Diantonio et al. 2001; Liao et al. 2004; Nakata et al. 2005; Collins et al. 2006) and biochemical approaches (Grill et al. 2007; Wu et al. 2007). These studies reveal that a major function of PHR proteins is to act as ubiquitin E3 ligases (Jin and Garner 2008). In C. elegans, RPM-1 (Regulator of Presynaptic Morphology-1) regulates the abundance of its substrate, the dual-leucine-zipper-bearing MAP kinase kinase kinase (DLK MAPKKK), and controls the activity of the MAP kinase cascade composed of three additional kinases, MAPKK MKK-4, p38 MAPK PMK-3, and MAPKAPK MAK-2 (Nakata et al. 2005; Yan et al. 2009). This signaling cascade further regulates the activity of the CCAAT/enhancer binding protein (C/EBP), CEBP-1, via a mechanism involving 3′-UTR-mediated mRNA decay.Signal transduction involving MAP kinases can be fine tuned using multiple mechanisms to ensure optimal signaling outputs (Raman et al. 2007). For example, scaffold proteins for MAP kinases can provide spatial regulation of kinase activation in response to different stimuli (Remy and Michnick 2004; Whitmarsh 2006). Small protein tags such as ubiquitin have also been shown to control the activation of kinases. Specifically, in the IKK pathway ubiquitination via Lys63 chain formation catalyzed by the Ubc13/Uev1a E2 complex and TRAF6 E3 ligase is required for TAK1 kinase activation (Skaug et al. 2009).To further the understanding of the DLK-1 pathway in the development of the nervous system, we characterized a new complementation group of rpm-1(lf) suppressors. These mutations affect the gene uev-3, a ubiquitin E2 conjugating (UBC) enzyme variant (UEV). UEV proteins belong to the UBC family, but lack the catalytic active cysteine necessary for conjugating ubiquitin (Sancho et al. 1998). The best characterized UEV proteins are yeast Mms2 and mammalian Uev1A, both of which act as the obligatory partner for the active E2 Ubc13 and function in DNA repair and IKB pathways, respectively (Deng et al. 2000; Hurley et al. 2006). In addition, UEV proteins, such as Tsg101, can also regulate endosomal trafficking (Babst et al. 2000). We find that similar to other members of the DLK-1 pathway, uev-3 functions cell autonomously in neurons. uev-3 genetically acts downstream of mkk-4 and upstream of mak-2. UEV-3 can bind PMK-3 in heterologous protein interaction assays. We hypothesize that UEV-3 may add specificity to the DLK-1 pathway by binding to PMK-3 for its activation or for selecting specific downstream targets.     

Trait-Associated SNPs Are More Likely to Be eQTLs: Annotation to Enhance Discovery from GWAS

Although genome-wide association studies (GWAS) of complex traits have yielded more reproducible associations than had been discovered using any other approach, the loci characterized to date do not account for much of the heritability to such traits and, in general, have not led to improved understanding of the biology underlying complex phenotypes. Using a web site we developed to serve results of expression quantitative trait locus (eQTL) studies in lymphoblastoid cell lines from HapMap samples (http://www.scandb.org), we show that single nucleotide polymorphisms (SNPs) associated with complex traits (from http://www.genome.gov/gwastudies/) are significantly more likely to be eQTLs than minor-allele-frequency–matched SNPs chosen from high-throughput GWAS platforms. These findings are robust across a range of thresholds for establishing eQTLs (p-values from 10⁻⁴–10⁻⁸), and a broad spectrum of human complex traits. Analyses of GWAS data from the Wellcome Trust studies confirm that annotating SNPs with a score reflecting the strength of the evidence that the SNP is an eQTL can improve the ability to discover true associations and clarify the nature of the mechanism driving the associations. Our results showing that trait-associated SNPs are more likely to be eQTLs and that application of this information can enhance discovery of trait-associated SNPs for complex phenotypes raise the possibility that we can utilize this information both to increase the heritability explained by identifiable genetic factors and to gain a better understanding of the biology underlying complex traits.     

Specific α- and β-Tubulin Isotypes Optimize the Functions of Sensory Cilia in Caenorhabditis elegans

Primary cilia have essential roles in transducing signals in eukaryotes. At their core is the ciliary axoneme, a microtubule-based structure that defines cilium morphology and provides a substrate for intraflagellar transport. However, the extent to which axonemal microtubules are specialized for sensory cilium function is unknown. In the nematode Caenorhabditis elegans, primary cilia are present at the dendritic ends of most sensory neurons, where they provide a specialized environment for the transduction of particular stimuli. Here, we find that three tubulin isotypes—the α-tubulins TBA-6 and TBA-9 and the β-tubulin TBB-4—are specifically expressed in overlapping sets of C. elegans sensory neurons and localize to the sensory cilia of these cells. Although cilia still form in mutants lacking tba-6, tba-9, and tbb-4, ciliary function is often compromised: these mutants exhibit a variety of sensory deficits as well as the mislocalization of signaling components. In at least one case, that of the CEM cephalic sensory neurons, cilium architecture is disrupted in mutants lacking specific ciliary tubulins. While there is likely to be some functional redundancy among C. elegans tubulin genes, our results indicate that specific tubulins optimize the functional properties of C. elegans sensory cilia.THE fitness of all organisms depends on an ability to appropriately sense and respond to the environment. At the cellular level, many specific architectures have evolved to optimize these sensory functions. Prominent among these is the sensory cilium, a tubulin-based cytoplasmic extension that interrogates the extracellular environment in many biological contexts (Davenport and Yoder 2005; Berbari et al. 2009). Cilia are important for the transduction of a broad range of visual, auditory, mechanical, thermal, and chemical stimuli. They also function during development to receive a variety of signals, both chemical and mechanical, that regulate proliferation and differentiation (Goetz and Anderson 2010). Indeed, the disruption of cilium assembly and function can give rise to a spectrum of human diseases collectively known as ciliopathies (Berbari et al. 2009; Lancaster and Gleeson 2009). These disorders, which include autosomal dominant polycystic kidney disease (ADPKD) and autosomal recessive polycystic kidney disease (ARPKD), Bardet–Biedl syndrome, Meckel–Gruber syndrome, and Joubert syndrome, are associated with a variety of pathogenic conditions including polycystic kidneys and neurological impairments.At the core of all cilia and flagella is the microtubule axoneme. This characteristic structural element comprises nine doublet outer microtubules that may surround a central pair, the presence of which often indicates a motile cilium/flagellum. Like all microtubule-based structures, ciliary axonemes are built of heterodimers of α- and β-tubulins, highly conserved small GTP-binding proteins. The recruitment of other cilium components, including signal transduction machinery, requires a conserved assembly and maintenance process called intraflagellar transport (IFT) (Blacque et al. 2008; Pedersen and Rosenbaum 2008). IFT employs two major complexes that transport ciliary cargo bidirectionally by traveling along the axonemal microtubules. Loss of individual IFT components can cause a broad spectrum of defects in the assembly, maintenance, and function of cilia.Important insights into cilium structure and function have come from studies of genetically tractable organisms, particularly the green alga Chlamydomonas and the nematode Caenorhabditis elegans (Bae and Barr 2008; Pedersen and Rosenbaum 2008). In C. elegans, sensory cilia are found exclusively at the dendritic ends of sensory neurons. These cilia constitute a highly specialized sensory environment characterized by localized sensory receptors and specific signaling components. Cilium morphology is quite distinctive in many of these cells and likely contributes to their functional specialization (Ward et al. 1975). Recent progress has shed light on the mechanisms that confer this specialization onto more general pan-ciliary pathways (Evans et al. 2006; Mukhopadhyay et al. 2007; Jauregui et al. 2008; Mukhopadhyay et al. 2008; Silverman and Leroux 2009).The genomes of many eukaryotes harbor multiple α- and β-tubulin genes. Two hypotheses, which are not mutually exclusive, have been proposed to account for these paralogs (Cleveland 1987; Wade 2007). At one extreme, different tubulin isotypes might be functionally redundant, such that their minor coding differences are largely irrelevant. According to this model, multiple genes allow the maintenance of a stable pool of available monomers and dimers. The small amount of sequence variation within the α- and β-tubulin families supports this idea, as do studies of functionally redundant mitotic tubulins in C. elegans (Ellis et al. 2004; Lu et al. 2004; Phillips et al. 2004; Lu and Mains 2005). The alternative hypothesis proposes that specific structures, e.g., ciliary axonemes or axonal microtubules, rely on tubulins optimized for specific roles. Support for this idea has come from studies of cultured mammalian neurons (Joshi and Cleveland 1989), Drosophila (Hutchens et al. 1997; Raff et al. 1997), and human tubulins (Vent et al. 2005; Jaglin et al. 2009). In Drosophila, studies of motile sperm flagella have revealed that the sperm-specific β2 tubulin isoform builds not only the specialized motile axoneme but also all other tubulin-based structures (Kemphues et al. 1982). However, sequences both within and outside the axoneme motif in the C-terminal tail of this tubulin isoform are required for the flagellar axoneme, and other closely related β-tubulins cannot support this role (Fuller et al. 1987; Raff et al. 1997; Popodi et al. 2008). Genetic interactions have provided evidence that β2 tubulin heterodimerizes with the α-tubulin 84B (Hays et al. 1989), which also possesses specific functional properties not provided by structurally similar α-tubulins (Hutchens et al. 1997). In C. elegans, a specific role for tubulin isoforms has been described in the six touch receptor neurons. These nonciliated cells harbor unusual 15-filament microtubules composed of dimers of the α-tubulin MEC-12 and the β-tubulin MEC-7. The loss of mec-7 or mec-12, the expression of which is largely restricted to these cells, results in the conversion of 15-filament microtubules to the standard 11-microfilament variety and a commensurate loss of light-touch response (Savage et al. 1989; Fukushige et al. 1999; Bounoutas et al. 2009). Thus experimental support exists for both of these opposing views, and it seems likely that the role of specific tubulin isoforms in regulating microtubule structure and function differs according to cell and organelle type.The C. elegans genome encodes nine α- and six β-tubulin genes (Gogonea et al. 1999). Some of these genes, particularly tba-1, tba-2, tbb-1, and tbb-2, are expressed broadly during embryogenesis and function redundantly in spindle assembly and positioning (Ellis et al. 2004; Lu et al. 2004; Phillips et al. 2004; Lu and Mains 2005). tba-1 and tbb-2 have also been recently shown to be important for axon outgrowth and synaptogenesis (Baran et al. 2010). Several others, including mec-7, mec-12, and the β-tubulin ben-1, have been identified through genetic screens for particular phenotypes, such as touch insensitivity or benzimidazole resistance (Driscoll et al. 1989; Savage et al. 1989; Fukushige et al. 1999). However, the extent to which specific tubulin isoforms are required for structural and functional diversity in the C. elegans nervous system remains unknown. Here, taking advantage of several existing genome-wide data sets, we identify the α-tubulins TBA-6 and TBA-9 and the β-tubulin TBB-4 as strong candidates for tubulins that have roles in sensory cilia. We find that each of these genes are expressed in characteristic, partially overlapping, sets of sensory neurons, where their products localize to ciliary axonemes. While the loss of any one (or all three) of these genes does not abolish ciliogenesis, tubulin mutants exhibit significant defects in the localization of cilium proteins and in some cilium-dependent behavioral responses. Together, our results indicate that specific α- and β-tubulin isoforms are important, although not essential, for the efficient assembly and function of specific classes of C. elegans sensory cilia. Sensory cilia throughout the animal kingdom may therefore employ specific tubulin isoforms to optimize their function.     

The Synaptonemal Complex Shapes the Crossover Landscape Through Cooperative Assembly,Crossover Promotion and Crossover Inhibition During Caenorhabditis elegans Meiosis

The synaptonemal complex (SC) is a highly ordered proteinaceous structure that assembles at the interface between aligned homologous chromosomes during meiotic prophase. The SC has been demonstrated to function both in stabilization of homolog pairing and in promoting the formation of interhomolog crossovers (COs). How the SC provides these functions and whether it also plays a role in inhibiting CO formation has been a matter of debate. Here we provide new insight into assembly and function of the SC by investigating the consequences of reducing (but not eliminating) SYP-1, a major structural component of the SC central region, during meiosis in Caenorhabditis elegans. First, we find an increased incidence of double CO (DCO) meiotic products following partial depletion of SYP-1 by RNAi, indicating a role for SYP-1 in mechanisms that normally limit crossovers to one per homolog pair per meiosis. Second, syp-1 RNAi worms exhibit both a strong preference for COs to occur on the left half of the X chromosome and a significant bias for SYP-1 protein to be associated with the left half of the chromosome, implying that the SC functions locally in promoting COs. Distribution of SYP-1 on chromosomes in syp-1 RNAi germ cells provides strong corroboration for cooperative assembly of the SC central region and indicates that SYP-1 preferentially associates with X chromosomes when it is present in limiting quantities. Further, the observed biases in the distribution of both COs and SYP-1 protein support models in which synapsis initiates predominantly in the vicinity of pairing centers (PCs). However, discontinuities in SC structure and clear gaps between localized foci of PC-binding protein HIM-8 and X chromosome-associated SYP-1 stretches allow refinement of models for the role of PCs in promoting synapsis. Our data suggest that the CO landscape is shaped by a combination of three attributes of the SC central region: a CO-promoting activity that functions locally at CO sites, a cooperative assembly process that enables CO formation in regions distant from prominent sites of synapsis initiation, and CO-inhibitory role(s) that limit CO number.REDUCTION in ploidy during sexual reproduction depends on the ability to form pairwise associations between homologous chromosomes. The homolog pairing process typically culminates in an arrangement in which the homologs are aligned in parallel along their lengths, with a highly ordered proteinaceous structure known as the synaptonemal complex (SC) located at the interface between them. Further, in most organisms, pairwise associations between homologs are solidified through the formation of crossovers (COs) between their DNA molecules, a process that is completed within the context of the SC.The SC has long been recognized as a hallmark cytological feature of meiosis. It was discovered on the basis of its highly ordered structure and location at the interface between aligned chromosomes in electron microscopy images of nuclei at the pachytene stage of meiotic prophase (Moses 1956, 2006). Each of the homologs is associated with one of the two lateral elements (LEs) of the SC, which are composed of cohesin complexes and other meiosis-specific structural and regulatory proteins (reviewed in Mlynarczyk-Evans and Villeneuve 2010). The LEs are connected by a highly ordered latticework of transverse filaments, and often a pronounced central element, that comprise the central region of the SC. The protein components of the SC central region are very poorly conserved at the primary sequence level, but the major central region proteins identified from diverse species share in common extended regions of predicted coiled coil structure.The SC has been demonstrated to have at least two conserved functions in meiotic prophase. First, the SC serves to stabilize and maintain tight associations along the lengths of aligned homologs (reviewed in Mlynarczyk-Evans and Villeneuve 2010). This is true both in organisms in which SC assembly is coupled to formation of recombination intermediates (e.g., budding yeast, mouse, and Arabidopsis) and in organisms in which formation of SC between homologs can occur independently of recombination (e.g., Caenorhabditis elegans and Drosophila). Second, SC central region proteins play a role in promoting maturation of recombination intermediates into crossover products (reviewed in De Boer and Heyting 2006). How the SC functions to promote CO formation is not well understood. Moreover, whether the SC might also have additional functions that help to ensure a successful outcome of meiosis has been a matter of debate.In addition to its roles in stabilization of pairing and promoting CO formation, the SC has also been proposed to function in inhibiting CO formation (Egel 1978, 1995; Maguire 1988). This idea of the SC playing an inhibitory role in recombination dates almost as far back as the discovery of the SC itself. Finding a highly ordered structure with a zipper-like appearance extending along the length of each homolog pair naturally gave rise to speculation that it might play a role in the phenomenon of crossover interference, defined as the ability of a (nascent) CO to inhibit the formation of other COs nearby on the same chromosome pair (Muller 1916; Hillers 2004). It was variously proposed either that the SC might serve as a conduit of information along a chromosome pair (e.g., undergoing a distance-dependent “change in state” to inhibit COs) or that SC polymerization might itself confer CO inhibition (Egel 1978; Maguire 1988; Sym and Roeder 1994).Early analysis of the budding yeast mutants lacking Zip1, a major structural component of the SC central region, initially seemed to support the idea that the SC central region played a key role in CO interference, as zip1 mutants formed COs at 30–50% of wild-type levels and the residual COs did not display interference (Sym and Roeder 1994). However, these data were subsequently reinterpreted by postulating that the major interference-sensitive meiotic CO pathway is eliminated in the zip1 mutant and that the residual COs form by an alternative pathway that is not subject to interference (Zalevsky et al. 1999; de los Santos et al. 2003). According to this two-pathway view, the lack of interference in the zip1 mutant can be readily explained without invoking a role for Zip1 in the interference mechanism per se. Conversely, Page and Hawley found that Drosophila females expressing a mutant form of the fly SC central region protein C(3)G retained substantial interference between residual COs despite exhibiting incomplete synapsis, implying that complete SC formation was not required for CO interference (Page and Hawley 2001). In light of these and other findings (e.g., Borner et al. 2004; Fung et al. 2004), the idea that the SC might play a role in inhibiting CO formation fell from favor.In this study, we revisit a potential role for the SC central region in inhibiting CO formation, using the C. elegans experimental system. Several features make this an interesting system for investigating factors that promote and/or inhibit COs during meiosis. First, essentially all COs in C. elegans depend on conserved meiotic CO-promoting machinery (i.e., Msh4 and Msh5) and on SC central region proteins (SYP-1, -2, -3, and -4), so analysis is generally not complicated by residual COs forming by alternative pathways (Zalevsky et al. 1999; Kelly et al. 2000; MacQueen et al. 2002; Colaiacovo et al. 2003; Smolikov et al. 2007a, 2009). Second, C. elegans hermaphrodites exhibit robust CO control, with COs usually being limited to one per homolog pair per meiosis (Hillers and Villeneuve 2003; Nabeshima et al. 2004; Hammarlund et al. 2005). Consequently, circumstances that give rise to double crossover (DCO) meiotic products can be inferred to represent impairment of mechanisms that normally inhibit CO formation. Finally, COs are distributed nonuniformly along the lengths of the chromosomes, with each chromosome containing broad domains of relatively high CO frequency flanking a more central domain where CO frequency is low (Brenner 1974; Barnes et al. 1995; Rockman and Kruglyak 2009), providing an opportunity to evaluate how factors that promote and/or inhibit COs contribute to this landscape.Our strategy was to use RNAi to reduce the levels of wild-type SYP-1 protein without eliminating synapsis entirely and then to examine the effects on CO frequency and distribution. This approach indeed revealed a role for SC central region protein SYP-1 in mechanisms that normally limit the number of COs per homolog pair. Further, it also revealed a role for the SC central region in determining CO distribution, presumably by enabling formation of COs in chromosome regions distant from the dominant site of synapsis initiation. Finally, our experimental design also afforded us the opportunity to evaluate spatial distribution of the SC in the context of limiting amounts of a key central region component. This analysis provided additional insight into the process of SC assembly and the role of cis-acting meiotic pairing centers in this process.     

A Genetic Survey of Fluoxetine Action on Synaptic Transmission in Caenorhabditis elegans

Fluoxetine is one of the most commonly prescribed medications for many behavioral and neurological disorders. Fluoxetine acts primarily as an inhibitor of the serotonin reuptake transporter (SERT) to block the removal of serotonin from the synaptic cleft, thereby enhancing serotonin signals. While the effects of fluoxetine on behavior are firmly established, debate is ongoing whether inhibition of serotonin reuptake is a sufficient explanation for its therapeutic action. Here, we provide evidence of two additional aspects of fluoxetine action through genetic analyses in Caenorhabditis elegans. We show that fluoxetine treatment and null mutation in the sole SERT gene mod-5 eliminate serotonin in specific neurons. These neurons do not synthesize serotonin but import extracellular serotonin via MOD-5/SERT. Furthermore, we show that fluoxetine acts independently of MOD-5/SERT to regulate discrete properties of acetylcholine (Ach), gamma-aminobutyric acid (GABA), and glutamate neurotransmission in the locomotory circuit. We identified that two G-protein–coupled 5-HT receptors, SER-7 and SER-5, antagonistically regulate the effects of fluoxetine and that fluoxetine binds to SER-7. Epistatic analyses suggest that SER-7 and SER-5 act upstream of AMPA receptor GLR-1 signaling. Our work provides genetic evidence that fluoxetine may influence neuronal functions and behavior by directly targeting serotonin receptors.FLUOXETINE is a selective serotonin reuptake inhibitor (SSRI) and has made a major impact on the treatment of many behavioral disorders. The empirical action of SSRIs is blocking the serotonin reuptake transporter (SERT). SERT is localized in the plasma membrane and transports extracellular serotonin (5-HT) into the cytoplasm (Blakely et al. 1991; Hoffman et al. 1991), this being the major mechanism of terminating 5-HT signaling. Consequently, SSRIs are thought to exert therapeutic effects by blocking SERT from removal of 5-HT in the synaptic clef, thereby increasing the level of 5-HT signals (Schatzberg and Nemeroff 2004). However, several observations point to additional actions of SSRIs on the 5-HT system and neuronal functions. First, knockout of SERT in mouse caused a marked reduction of 5-HT in the brain (Bengel et al. 1998). Second, a variety of studies with cultured mammalian cells and mouse brain slices showed that SSRIs and tricyclic antidepressant agents (TCAs) have high affinities to many 5-HT receptor subtypes and act as agonists or antagonists depending on particular receptors being tested (Ni and Miledi 1997; Kroeze and Roth 1998; Eisensamer et al. 2003). Third, genetic analyses of the nematode Caenorhabditis elegans in our laboratory and others showed that fluoxetine and the TCA imipramine (Tofrani) could influence behavior independent of SERT function (Weinshenker et al. 1995; Ranganathan et al. 2001; Dempsey et al. 2005). In this study, we carried out a systematic survey of SSRIs treatment in C. elegans to gain new insights into actions of SSRIs on the 5-HT system and other neurotransmitter systems.In both vertebrates and invertebrates, 5-HT functions as a neuromodulator to either facilitate or inhibit synaptic transmission of other neurotransmitters (Fink and Gothert 2007). Modulation of synaptic activity by 5-HT signaling underscores the synaptic plasticity involved in stress responses, learning, adaptation, and memory (Kandel 2001; Zhang et al. 2005). The role of 5-HT in C. elegans was initially identified through pharmacological experiments showing that exogenous 5-HT can promptly induce changes in a variety of behaviors, including feeding, egg laying, and locomotion (Avery and Horvitz 1990; Weinshenker et al. 1995; Nurrish et al. 1999). The relevance of these behaviors to endogenous 5-HT has since been validated through studies of mutants of 5-HT signaling. Importantly, multiple 5-HT receptors may function in distinct cells synergistically or antagonistically to regulate a specific behavior (Carnell et al. 2005; Dernovici et al. 2007; Murakami and Murakami 2007; Hapiak et al. 2009). In nearly all tested paradigms, fluoxetine and imipramine induce behavioral changes similarly to exogenous 5-HT (Weinshenker et al. 1995; Nurrish et al. 1999), implying that fluoxetine regulates 5-HT inputs to these neural circuits. However, the tryptophan hydroxylase gene tph-1 is required for 5-HT biosynthesis in C. elegans (Sze et al. 2000), mod-5 encodes its sole SERT (Ranganathan et al. 2001), and yet fluoxetine could stimulate egg laying and inhibit locomotion in mod-5 and tph-1 mutants (Weinshenker et al. 1995; Choy and Thomas 1999; Ranganathan et al. 2001; Dempsey et al. 2005). These findings provided a basis for further investigation into genes and synaptic functions regulated by 5-HT and the impact of fluoxetine on 5-HT signaling.Here we present genetic evidence of multifaceted effects of fluoxetine on the 5-HT system and its downstream targets in C. elegans. We show that fluoxetine treatment and loss of MOD-5/SERT function do not simply increase presynaptic 5-HT signals. Rather, they may eliminate 5-HT in specific neurons. Furthermore, fluoxetine acts independently of SERT to regulate 5-HT serotonin receptors and their downstream targets involved in acetylcholine (ACh), gamma-aminobutyric acid (GABA), and glutamate neurotransmission.     

Pharmacogenetic Analysis Reveals a Post-Developmental Role for Rac GTPases in Caenorhabditis elegans GABAergic Neurotransmission

The nerve-cell cytoskeleton is essential for the regulation of intrinsic neuronal activity. For example, neuronal migration defects are associated with microtubule regulators, such as LIS1 and dynein, as well as with actin regulators, including Rac GTPases and integrins, and have been thought to underlie epileptic seizures in patients with cortical malformations. However, it is plausible that post-developmental functions of specific cytoskeletal regulators contribute to the more transient nature of aberrant neuronal activity and could be masked by developmental anomalies. Accordingly, our previous results have illuminated functional roles, distinct from developmental contributions, for Caenorhabditis elegans orthologs of LIS1 and dynein in GABAergic synaptic vesicle transport. Here, we report that C. elegans with function-altering mutations in canonical Rac GTPase-signaling-pathway members demonstrated a robust behavioral response to a GABA_A receptor antagonist, pentylenetetrazole. Rac mutants also exhibited hypersensitivity to an acetylcholinesterase inhibitor, aldicarb, uncovering deficiencies in inhibitory neurotransmission. RNA interference targeting Rac hypomorphs revealed synergistic interactions between the dynein motor complex and some, but not all, members of Rac-signaling pathways. These genetic interactions are consistent with putative Rac-dependent regulation of actin and microtubule networks and suggest that some cytoskeletal regulators cooperate to uniquely govern neuronal synchrony through dynein-mediated GABAergic vesicle transport in C. elegans.EPILEPSY affects 1–2% of the world population and is associated with imbalances between excitatory and inhibitory neurotransmission in the brain (Locke et al. 2009). In particular, interneurons expressing gamma-aminobutyric acid (GABA), the principal inhibitory neurotransmitter in the human brain, are essential for normal neuronal synchronization and maintenance of a seizure threshold in humans (Cossette et al. 2002), rodents (Delorey et al. 1998), and zebrafish (Baraban et al. 2005). A failure of the brain to properly regulate neuronal synchrony can result from ion channel defects (Xu and Clancy 2008), neuropeptide depletion (Brill et al. 2006), brain malformations (Patel et al. 2004), interneuron loss (Cobos et al. 2005), and/or synaptic vesicle recycling failure (Di Paolo et al. 2002), all of which may be caused by disrupting the nerve-cell cytoskeleton. Therefore, further exploration of putative links between cytoskeletal components and neurotransmission may accelerate development of novel therapeutics for epilepsy.Epilepsy associated with cytoskeletal dysfunction often has a developmental basis (Di Cunto et al. 2000; Wenzel et al. 2001; Keays et al. 2007). For example, mutations in LIS1, a dynein motor complex regulator, lead to classical lissencephaly, which is characterized by neuronal migration defects, a lack of convolutions in the brain, mental retardation, and epileptic seizures (Lo Nigro et al. 1997). Yet, observations that lissencephaly-associated seizures worsen after neuronal migration ceases, while LIS1 expression persists, imply that LIS1 also acts in the adult brain (Cardoso et al. 2002).We previously reported that C. elegans with a predicted null mutation (t1550) in lis-1, the worm ortholog of human LIS1, exhibited synaptic vesicle misaccumulations, but not neuronal migration or axon-pathfinding defects, in GABAergic motor neurons. We also observed anterior “epileptic-like” convulsions, which were intense, frequent, and repetitive, with lis-1(t1550) homozygotes in the presence of pentylenetetrazole (PTZ; Williams et al. 2004), an epileptogenic GABA_A receptor antagonist (Huang et al. 2001; Fernandez et al. 2007). PTZ sensitivity was also increased in heterozygous lis-1(t1550) mutants following RNA interference (RNAi) against worm orthologs of associated cortical malformation genes, such as cdk-5 and nud-2, which are known to interact with LIS1 and the dynein motor complex. Depletion of these gene products was coincident with dynein-mediated synaptic vesicle transport defects, not with architectural defects, in GABAergic motor neurons (Locke et al. 2006).Plausible functional interactions among LIS-1, dynein, and Rac GTPases (Rehberg et al. 2005; Kholmanskikh et al. 2006) have not been explored in an intact adult nervous system. C. elegans is ideal for characterizing these interactions due to the availability of weak and strong Rac pathway mutants (Lundquist et al. 2001; Poinat et al. 2002; Lucanic et al. 2006), a comprehensive RNAi library (Kamath et al. 2003), and GFP-based neuronal markers. Here, we combine these tools with pharmacological modifiers of neuronal activity and establish an experimental paradigm that reveals a novel regulatory pathway. This pathway is composed of integrins at the plasma membrane that signal through Racs to dynein-associated proteins, which function to coordinate synaptic vesicle transport in larval and adult GABAergic motor neurons.     

Fine Mapping in 94 Inbred Mouse Strains Using a High-Density Haplotype Resource

The genetics of phenotypic variation in inbred mice has for nearly a century provided a primary weapon in the medical research arsenal. A catalog of the genetic variation among inbred mouse strains, however, is required to enable powerful positional cloning and association techniques. A recent whole-genome resequencing study of 15 inbred mouse strains captured a significant fraction of the genetic variation among a limited number of strains, yet the common use of hundreds of inbred strains in medical research motivates the need for a high-density variation map of a larger set of strains. Here we report a dense set of genotypes from 94 inbred mouse strains containing 10.77 million genotypes over 121,433 single nucleotide polymorphisms (SNPs), dispersed at 20-kb intervals on average across the genome, with an average concordance of 99.94% with previous SNP sets. Through pairwise comparisons of the strains, we identified an average of 4.70 distinct segments over 73 classical inbred strains in each region of the genome, suggesting limited genetic diversity between the strains. Combining these data with genotypes of 7570 gap-filling SNPs, we further imputed the untyped or missing genotypes of 94 strains over 8.27 million Perlegen SNPs. The imputation accuracy among classical inbred strains is estimated at 99.7% for the genotypes imputed with high confidence. We demonstrated the utility of these data in high-resolution linkage mapping through power simulations and statistical power analysis and provide guidelines for developing such studies. We also provide a resource of in silico association mapping between the complex traits deposited in the Mouse Phenome Database with our genotypes. We expect that these resources will facilitate effective designs of both human and mouse studies for dissecting the genetic basis of complex traits.PHENOTYPIC variation among inbred mouse strains exposed to a disease-causing agent (be it genetic, infectious, or environmental) provides potential insight into human disease processes that often cannot be practically achieved through direct human studies. Indeed, hundreds of phenotype measurements related to human diseases are available for dozens of inbred strains in common use over the past 50–100 years (Bogue et al. 2007; Grubb et al. 2009). As with the direct study of chronic disease in humans, key steps toward determining the genetic underpinnings of this phenotypic variation are to develop a catalog of the genetic variation among inbred mouse strains and to interpret the structure of variation patterns across the strains. Recent advances in high-throughput genotyping and DNA resequencing technologies are making it possible to rapidly uncover the genetic variation maps of many model organisms (Lindblad-Toh et al. 2005; Mackay and Anholt 2006; Borevitz et al. 2007; Frazer et al. 2007; International Hapmap Consortium 2007; Star Consortium 2008). A recent whole-genome resequencing study of 15 inbred mouse strains captured a significant fraction of the genetic variation among a limited number of strains, allowing researchers to infer patterns of genetic variation and to identify the ancestral origin of the genetic variation (Frazer et al. 2007; Yang et al. 2007). Yet the availability and common experimental employment of hundreds of inbred strains, including >190 stocks available from the Jackson Laboratory, motivates the need for a high-density variation map for a larger set of strains. We have assembled the Mouse HapMap, a resource consisting of a dense set of genotypes for a total of 138,980 unique biallelic single nucleotide polymorphisms (SNPs) in 94 inbred mouse strains at an average spacing of 20 kb on chromosomes 1–19 and X.This resource is ideal for performing high-resolution mapping studies under QTL peaks. We evaluate the feasibility and effectiveness of such studies by examining a typical study from the Mouse Phenome Database (MPD) (Bogue et al. 2007; Grubb et al. 2009) (http://www.jax.org/phenome) and measure the statistical power to detect genetic associations in regions of various sizes. We provide several resources to the mouse genetics community for supporting such studies and a webserver that can estimate the significance threshold, compute the statistical power of a proposed study, and perform in the fine mapping of measured phenotypes. In addition, we provide a database of associations for all phenotypes contained in the MPD. The web resources are available at http://mouse.cs.ucla.edu/.     

PASTEC: An Automatic Transposable Element Classification Tool

Summary

The classification of transposable elements (TEs) is key step towards deciphering their potential impact on the genome. However, this process is often based on manual sequence inspection by TE experts. With the wealth of genomic sequences now available, this task requires automation, making it accessible to most scientists. We propose a new tool, PASTEC, which classifies TEs by searching for structural features and similarities. This tool outperforms currently available software for TE classification. The main innovation of PASTEC is the search for HMM profiles, which is useful for inferring the classification of unknown TE on the basis of conserved functional domains of the proteins. In addition, PASTEC is the only tool providing an exhaustive spectrum of possible classifications to the order level of the Wicker hierarchical TE classification system. It can also automatically classify other repeated elements, such as SSR (Simple Sequence Repeats), rDNA or potential repeated host genes. Finally, the output of this new tool is designed to facilitate manual curation by providing to biologists with all the evidence accumulated for each TE consensus.

Availability

PASTEC is available as a REPET module or standalone software (http://urgi.versailles.inra.fr/download/repet/REPET_linux-x64-2.2.tar.gz). It requires a Unix-like system. There are two standalone versions: one of which is parallelized (requiring Sun grid Engine or Torque), and the other of which is not.     

mStruct: Inference of Population Structure in Light of Both Genetic Admixing and Allele Mutations

Traditional methods for analyzing population structure, such as the Structure program, ignore the influence of the effect of allele mutations between the ancestral and current alleles of genetic markers, which can dramatically influence the accuracy of the structural estimation of current populations. Studying these effects can also reveal additional information about population evolution such as the divergence time and migration history of admixed populations. We propose mStruct, an admixture of population-specific mixtures of inheritance models that addresses the task of structure inference and mutation estimation jointly through a hierarchical Bayesian framework, and a variational algorithm for inference. We validated our method on synthetic data and used it to analyze the Human Genome Diversity Project–Centre d''Etude du Polymorphisme Humain (HGDP–CEPH) cell line panel of microsatellites and HGDP single-nucleotide polymorphism (SNP) data. A comparison of the structural maps of world populations estimated by mStruct and Structure is presented, and we also report potentially interesting mutation patterns in world populations estimated by mStruct.THE deluge of genomic polymorphism data, such as the genomewide multilocus genotype profiles of variable numbers of tandem repeats (i.e., microsatellites) and single-nucleotide polymorphisms (SNPs), has fueled the long-standing interest in analyzing patterns of genetic variations to reconstruct the ancestral structures of modern human populations. Genetic ancestral information can shed light on the evolutionary history and migrations of modern populations (Bowcock et al. 1994; Rosenberg et al. 2002; Conrad et al. 2006). It also provides guidelines for more accurate association studies (Roeder et al. 1998) and is useful for many other population genetics problems (Queller et al. 1993; Hammer et al. 1998; Templeton 2002).Various methods have been proposed for stratifying population structures on the basis of multilocus genotype information from a set of individuals. For example, Pritchard et al. (2000) proposed a model-based approach implemented in the program Structure, which uses a statistical methodology known as the allele-frequency admixture model to stratify population structures. This model, and admixture models in general arising in genetic and other contexts (Blei et al. 2003), belongs to a more general class of hierarchical Bayesian models known as the mixed membership models (Erosheva et al. 2004). Such a model postulates that an empirical multiple-instance sample, such as the ensemble of genetic markers of an individual, is made up of either independently and identically distributed (iid) instantiations (Pritchard et al. 2000) or spatially coupled (Falush et al. 2003) instantiations, from multiple population-specific fixed-dimensional multinomial distributions of marker alleles [known as allele-frequency profiles, AP (Falush et al. 2003)]. Under this assumption, the admixture model identifies each ancestral population by a specific AP (that defines a unique vector of allele frequencies of each marker in each ancestral population) and displays the fraction of contributions from each AP in a modern individual genome as an admixing vector (also known as an ancestral proportion vector or structure vector) in a structural map over the population sample in question. Figure 1 shows an example of a structural map of four modern populations inferred from a portion of the HapMap multipopulation data set by Structure. In this population structural map, the admixing vector underlying each individual is represented as a thin vertical line of unit length and multiple colors, with the height of each color reflecting the fraction of the individual''s genome originated from a certain ancestral population denoted by that color and formally represented by a unique AP. This method has been applied to the Human Genome Diversity Project–Centre d''Etude du Polymorphisme Humain (HGDP–CEPH) Human Genome Diversity Cell Line Panel in Rosenberg et al. (2002) and many other studies, and has unraveled interesting patterns in the genetic structures of the world population. However, even though Structure was originally built on a genetic admixture model, in reality the structural patterns derived by Structure in various studies often turn out to be distinct clusters among the study populations (e.g., Figure 1), which has led many to think of it as a clustering program rather than a tool for uncovering genetic admixing as it was supposed to do. The design limitation of the Structure model behind this issue motivated us to develop a new approach in this article to analyze admixed genetic samples.Open in a separate windowFigure 1.—Population structural map inferred by Structure on HapMap data consisting of four populations.A recent extension of Structure, known as Structurama (Pella and Masuda 2006; Huelsenbeck and Andolfatto 2007), relaxes the finite dimensional assumption on ancestral populations in the admixture model by employing a Dirichlet process prior over the ancestral allele-frequency profiles. This allows automatic estimation of the maximum a posteriori probable number of ancestral populations. This extension is a useful improvement since it eliminates the need for manual selection of the number of ancestral populations. Anderson and Thompson (2002) address the problem of classifying species hybrids into categories, using a model-based Bayesian clustering approach implemented in the NewHybrid program. While this problem is not exactly identical to the problem of stratifying the structure of highly admixed populations, it is useful for structural analysis of populations that were recently admixed. The BAPS program (Corander et al. 2003) also uses a Bayesian approach to find the best partition of a set of individuals into subpopulations on the basis of genotypes. Parallel to the aforementioned model-based approaches for genomic structural analysis, direct algebraic eigen-decomposition and dimensionality reduction methods, such as the Eigensoft program (Patterson et al. 2006) based on principal components analysis (PCA), offer an alternative approach to explore and visualize the ancestral composition of modern populations and facilitate formal statistical tests for significance of population differentiation. However, unlike the model-based methods such as Structure, where each inferred ancestral population bears a concrete genetic meaning as a population-specific allele-frequency profile, the eigenvectors computed by Eigensoft represent the mutually orthogonal directions in an abstract low-dimensional ancestral space, in which population samples can be embedded and visualized; these eigenvectors can be understood as mathematical surrogates of independent genetic sources underlying a population sample, but lack a concrete interpretation under a generative genetic inheritance model (from here on, we use the term “inheritance model” to describe the process by which a descendant allele is derived from an ancestral allele). Analyses based on Eigensoft are usually limited to two-dimensional ancestral spaces, offering limited power in stratifying highly admixed populations.This progress notwithstanding, an important aspect of population admixing that is largely missing in the existing methods is the effect of allele mutations between the ancestral and current alleles of genetic markers, which can dramatically influence the accuracy of the structural estimation of current populations. It can also reveal additional information about population evolution, such as the relative divergence time and migration history of admixed populations.Consider, for example, the Structure model. Since an AP merely represents the frequency of alleles in an ancestral population rather than the actual allelic content or haplotypes of the alleles themselves, the admixture models developed so far on the basis of APs do not model genetic changes due to mutations from the ancestral alleles. Indeed, a serious pitfall of the model underlying Structure, as pointed out in Excoffier and Hamilton (2003), is that there is no mutation model for modern individual alleles with respect to hypothetical common prototypes in the ancestral populations. That means every unique allele in the modern population is assumed to have a distinct ancestral proportion, rather than allowing the possibility of it just being a descendant of some common ancestral allele that can also give rise to other closely related alleles at the same locus of other individuals in the modern population. Thus, while Structure aims to provide ancestry information for each individual and each locus, there is no explicit representation of the “ancestors” as a physical set of “founding alleles.” Therefore, the inferred population structural map emphasizes revealing the contributions of abstract population-specific ancestral proportion profiles, which does not necessarily reflect individual diversity or the extent of genetic changes with respect to the founders. Due to this limitation, Structure does not enable inference of the founding genetic patterns, the age of the founding alleles, or the population divergence time (Excoffier and Hamilton 2003).The lack of an appropriate allele mutation model in a structural inference program can also compromise our ability to reliably assess the amount or level of genetic admixing in different populations. The Structure model, like several other related models (Blei et al. 2003), is based on the fundamental assumption of the presence of genetic admixing among multiple founding populations. However, as we shall see later, on real population data such as the HGDP–CEPH panel, it produces results that favor clustering individuals into predominantly one allele-frequency profile or another, thus leading us to conclude that there was little or no admixing between the ancestral human populations. We believe that this occurs due to the absence of a mutation model in Structure. While a partitioning of individuals would be desirable for clustering them into groups, it does not offer enough biological insight into the intermixing of the populations.In this article, we present mStruct (which stands for Structure under mutations), based on a new model: an admixture of population-specific mixtures of inheritance models (AdMim). Statistically, AdMim is an admixture of mixture models, which represents each ancestral population as a mixture of ancestral alleles each with its own inheritance process and each modern individual as an “ancestry vector” (or structure vector) that reflects membership proportions of the ancestral populations. As we explain shortly, mStruct facilitates estimation of both the structural map of populations and the mutation parameters of either SNP or microsatellite alleles under various contexts. A new variational inference algorithm, which is much faster than the MCMC algorithm used for Structure, was developed for estimating the structure vectors and other genetic parameters of interest. We compare our method with Structure on simulated genotype data and on the microsatellite and SNP genotype data of world populations (Rosenberg et al. 2002; Conrad et al. 2006). Our results using microsatellite data reveal the presence of significant levels of genetic admixing among the founding populations underlying the HGDP–CEPH cell line panel, as well as consequences of expansion of humans out of Africa. Our results suggest that the inability of Structure to model mutations during genetic admixing could have caused it to detect correct clustering but very low levels of genetic admixing in each modern population in the HGDP–CEPH data. We also report interesting visualizations of genetic divergence in world populations revealed by the mutation patterns estimated by mStruct. The mStruct software has been implemented in C++ and is available for download at http://www.sailing.cs.cmu.edu/mstruct.html.     

Population Structure With Localized Haplotype Clusters

We propose a multilocus version of F_ST and a measure of haplotype diversity using localized haplotype clusters. Specifically, we use haplotype clusters identified with BEAGLE, which is a program implementing a hidden Markov model for localized haplotype clustering and performing several functions including inference of haplotype phase. We apply this methodology to HapMap phase 3 data. With this haplotype-cluster approach, African populations have highest diversity and lowest divergence from the ancestral population, East Asian populations have lowest diversity and highest divergence, and other populations (European, Indian, and Mexican) have intermediate levels of diversity and divergence. These relationships accord with expectation based on other studies and accepted models of human history. In contrast, the population-specific F_ST estimates obtained directly from single-nucleotide polymorphisms (SNPs) do not reflect such expected relationships. We show that ascertainment bias of SNPs has less impact on the proposed haplotype-cluster-based F_ST than on the SNP-based version, which provides a potential explanation for these results. Thus, these new measures of F_ST and haplotype-cluster diversity provide an important new tool for population genetic analysis of high-density SNP data.GENOME-WIDE data sets from worldwide panels of individuals provide an outstanding opportunity to investigate the genetic structure of human populations (Conrad et al. 2006; International Hapmap Consortium 2007; Jakobsson et al. 2008; Auton et al. 2009). Populations around the globe form a continuum rather than discrete units (Serre and Paabo 2004; Weiss and Long 2009). However, notions of discrete populations can be appropriate when, for example, ancestral populations were separated by geographic distance or barriers such that little gene flow occurred.F_ST (Wright 1951; Weir and Cockerham 1984; Holsinger and Weir 2009) is a measure of population divergence. It measures variation between populations vs. within populations. One can calculate a global measure, assuming that all populations are equally diverged from an ancestral population, or one can calculate F_ST for specific populations or for pairs of populations while utilizing data from all populations (Weir and Hill 2002). One use of F_ST is to test for signatures of selection (reviewed in Oleksyk et al. 2010).F_ST may be calculated for single genetic markers. For multiallelic markers, such as microsatellites, this is useful, but single-nucleotide polymorphisms (SNPs) contain much less information when taken one at a time, and thus it is advantageous to calculate averages over windows of markers (Weir et al. 2005) or even over the whole genome. The advantage of windowed F_ST is that it can be used to find regions of the genome that show different patterns of divergence, indicative of selective forces at work during human history.Another measure of human evolutionary history is haplotype diversity. Haplotype diversity may be measured using a count of the number of observed haplotypes in a region or by the expected haplotype heterozygosity based on haplotype frequencies in a region. Application of this regional measure to chromosomal data can be achieved by a haplotype block strategy (Patil et al. 2001) or by windowing (Conrad et al. 2006; Auton et al. 2009).One problem with the analysis of population structure based on genome-wide panels of SNPs is that a large proportion of the SNPs were ascertained in Caucasians, potentially biasing the results of the analyses. Analysis based on haplotypes is less susceptible to such bias (Conrad et al. 2006). This is because haplotypes can be represented by multiple patterns of SNPs; thus lack of ascertainment of a particular SNP does not usually prevent observation of the haplotype. On a chromosome-wide scale, one cannot directly use entire haplotypes, because all the haplotypes in the sample will almost certainly be unique, thus providing no information on population structure. Instead one can use haplotypes on a local basis, either by using windows of adjacent markers or by using localized haplotype clusters, for example those obtained from fastPHASE (Scheet and Stephens 2006) or BEAGLE (Browning 2006; Browning and Browning 2007a).Localized haplotype clusters are a clustering of haplotypes on a localized basis. At the position of each genetic marker, haplotypes are clustered according to their similarity in the vicinity of the position. Both fastPHASE and BEAGLE use hidden Markov modeling to perform the clustering, although the specific models used by the two programs differ.Localized haplotype clusters derived from fastPHASE have been used to investigate haplotype diversity, to create neighbor-joining trees of populations, and to create multidimensional scaling (MDS) plots (Jakobsson et al. 2008). It was found that haplotype clusters showed different patterns of diversity to SNPs, while the neighbor-joining and MDS plots were similar between haplotype clusters and SNPs.In this work, we apply windowed F_ST methods to localized haplotype clusters derived from the BEAGLE program (Browning and Browning 2007a,b, 2009). We consider population-average, population-specific, and pairwise F_ST estimates (Weir and Hill 2002). Population-average F_ST''s either assume that all the populations are equally diverged from a common ancestor, which is not realistic, or represent the average of a set of population-specific values. This can be convenient in that the results are summarized by a single statistic; however, information is lost. A common procedure is to calculate F_ST for each pair of populations, and these values reflect the degree of divergence between the two populations. Different levels of divergence are allowed for each pair of populations but each estimate uses data from only that pair of populations. On the other hand, population-specific F_ST''s allow unequal levels of divergence in a single analysis that makes use of all the data.We compare results from the localized haplotype clusters to those using SNPs directly. The results of applying localized haplotype clusters to population-specific F_ST estimation are very striking, showing better separation of populations and a more realistic pattern of divergence than for population-specific F_ST estimation using SNPs directly. We also use BEAGLE''s haplotype clusters in a haplotype diversity measure and investigate the relationship between this measure of haplotype-cluster diversity and the recombination rate.     

Robust Identification of Local Adaptation from Allele Frequencies

Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of “standardized allele frequencies” that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to F_ST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools—a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org.     

Joint Modeling and Registration of Cell Populations in Cohorts of High-Dimensional Flow Cytometric Data

In biomedical applications, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multivariate responses of a panel of markers such as from a signaling network. In multiparametric cytometry, which is often used for analyzing patient samples, such issues are critical. While computational methods can identify cell populations in individual samples, without the ability to automatically match them across samples, it is difficult to compare and characterize the populations in typical experiments, such as those responding to various stimulations or distinctive of particular patients or time-points, especially when there are many samples. Joint Clustering and Matching (JCM) is a multi-level framework for simultaneous modeling and registration of populations across a cohort. JCM models every population with a robust multivariate probability distribution. Simultaneously, JCM fits a random-effects model to construct an overall batch template – used for registering populations across samples, and classifying new samples. By tackling systems-level variation, JCM supports practical biomedical applications involving large cohorts. Software for fitting the JCM models have been implemented in an R package EMMIX-JCM, available from http://www.maths.uq.edu.au/~gjm/mix_soft/EMMIX-JCM/.     

HapZipper: sharing HapMap populations just got easier

The rapidly growing amount of genomic sequence data being generated and made publicly available necessitate the development of new data storage and archiving methods. The vast amount of data being shared and manipulated also create new challenges for network resources. Thus, developing advanced data compression techniques is becoming an integral part of data production and analysis. The HapMap project is one of the largest public resources of human single-nucleotide polymorphisms (SNPs), characterizing over 3 million SNPs genotyped in over 1000 individuals. The standard format and biological properties of HapMap data suggest that a dedicated genetic compression method can outperform generic compression tools. We propose a compression methodology for genetic data by introducing HapZipper, a lossless compression tool tailored to compress HapMap data beyond benchmarks defined by generic tools such as gzip, bzip2 and lzma. We demonstrate the usefulness of HapZipper by compressing HapMap 3 populations to <5% of their original sizes. HapZipper is freely downloadable from https://bitbucket.org/pchanda/hapzipper/downloads/HapZipper.tar.bz2.