Use of CD40L immunoconjugates to overcome the defective immune response to vaccines for infections and cancer in the aged

Multiple investigators have reported thepresence of defects in the immune response of the elderly [Castle In: Clin Infect Dis 31:578, 2000; Ortqvist et al. In: Eur Respir J 30:414–422, 2007; Saurwein-Teissl et al. In: J Immunol 168:5893, 2002; Haynes et al. In: Proc Natl Acad Sci USA 100:15053–15058, 2003]. These defects reduce the magnitude of the immune response to infection and to vaccination. In individuals greater than 55 years of age, the probability of developing a fully protective neutralizing antibody response to the yearly multivalent particle inactivated influenza vaccine is less than 20% [Jefferson et al. In: Lancet 264:1165–1174, 2005; Goodwin et al. In: Vaccine 24:1159–1169, 2006; Jackson et al. In: Lancet 372:398–405, 2008; Simonsen and Taylor In: Lancet 7:658–666, 2007]. The defects in the aged immune system that are responsible for this limited response to vaccination in the older age groups include functional defects of the antigen presenting cells, functional defects in CD4 helper CD4 T cells and monocytes, and an altered microenvironment [Eaton et al. In: J Exp Med 200:1613–1622, 2004; Dong et al. In: J Gen Virol 84:1623–1628, 2003; Deng et al. In: Immunology 172:3437–3446, 2004; Cella et al. In: J Exp Med 184:747–752, 1996]. Starting at puberty, the involution of the thymus and the consequent reduction of the export of naïve T cells specific to neo-antigens leads to the reduction of the ratio of antigen naïve to memory cells as chronological age advances [Prelog In: AutoimmunRev 5:136–139, 2006; McElhaney et al. In: J Immunology 176:6333–6339, 2006]. Changes in glycosylation of T cells and target antigens acquired during the aging process and the antibodies to these new glycopeptides and glycoproteins may also contribute to a reduction in the functioning of the adaptive immune response [Ishii et al. In: J Clin Neurosci 14:110–115, 2007; Shirai et al. In: Clin Exp Immunol 12:455–464, 1972; Adkins and Riley In: Mech AgeingDev 103:147–164, 1998; Ben-Yehuda and Weksler In: Cancer Investigation 10:525–531, 1992]. One of the more interesting examples of the functional defects in the cells of the adaptive immune response is a reduced level of expression in the surface cytoadhesion and activation receptor molecules on CD4 helper T cells undergoing activation during vaccination. Upon infection or vaccination, CD40L is typically increased on the surface of CD4 helper T cells during activation, and this increased expression is absolutely essential to the CD40L promotion of expansion of antigen-specific B cells and CD 8 effector T cells in response to infection or vaccination [Singh et al. In: Protein Sci 7:1124–1135, 1998; Grewal and Flavell In: Immunol Res 16: 59–70, 1997; Kornbluth In: J Hematother Stem Cell Res 11:787–801, 2002; Garcia de Vinuesa et al. In: Eur J Immunol 29:3216–3224, 1999]. In aged human beings and mice, the reduced levels of expression of CD40 ligand (CD40L) in activated CD4 helper T cells is dramatically reduced [Eaton et al. In: J Exp Med 200:1613–1622, 2004; Dong et al. In: J Gen Virol 84:1623–1628, 2003]. To circumvent the reduction in CD40L expression and the subsequent reduction in immune response in the elderly, we have developed a chimeric vaccine comprised of the CD40L linked to the target antigen, in a replication incompetent adenoviral vector and in booster protein. This review will discuss the implementation the potential use of this approach for the vaccination of the older populations for cancer and infection.     

Attenuation of TORC1 signaling delays replicative and oncogenic RAS-induced senescence

Numerous stimuli, including oncogenic signaling, DNA damage or eroded telomeres trigger proliferative arrest, termed cellular senescence. Accumulating evidence suggests that cellular senescence is a potent barrier to tumorigenesis in vivo, however oncogene induced senescence can also promote cellular transformation.¹ Kang TW, Yevsa T, Woller N, Hoenicke L, Wuestefeld T, Dauch D, et al. Senescence surveillance of pre-malignant hepatocytes limits liver cancer development. Nature 2011; 479:547 - 51; http://dx.doi.org/10.1038/nature10599; PMID: 22080947 [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]^,2 Rodier F, Campisi J. Four faces of cellular senescence. J Cell Biol 2011; 192:547 - 56; http://dx.doi.org/10.1083/jcb.201009094; PMID: 21321098 [Crossref], [PubMed], [Web of Science ®] , [Google Scholar] Several oncogenes, whose overexpression results in cellular senescence, converge on the TOR (target of rapamycin) pathway. We therefore examined whether attenuation of TOR results in delay or reversal of cellular senescence. By using primary human fibroblasts undergoing either replicative or oncogenic RAS-induced senescence, we demonstrated that senescence can be delayed, and some aspects of senescence can be reversed by inhibition of TOR, using either the TOR inhibitor rapamycin or by depletion of TORC1 (TOR Complex 1). Depletion of TORC2 fails to affect the course of replicative or RAS-induced senescence. Overexpression of REDD1 (Regulated in DNA Damage Response and Development), a negative regulator of TORC1, delays the onset of replicative senescence. These results indicate that TORC1 is an integral component of the signaling pathway that mediates cellular senescence.     

The Conserved miR-51 microRNA Family Is Redundantly Required for Embryonic Development and Pharynx Attachment in Caenorhabditis elegans

A major question about cytokinesis concerns the role of the septin proteins, which localize to the division site in all animal and fungal cells but are essential for cytokinesis only in some cell types. For example, in Schizosaccharomyces pombe, four septins localize to the division site, but deletion of the four genes produces only a modest delay in cell separation. To ask if the S. pombe septins function redundantly in cytokinesis, we conducted a synthetic-lethal screen in a septin-deficient strain and identified seven mutations. One mutation affects Cdc4, a myosin light chain that is an essential component of the cytokinetic actomyosin ring. Five others cause frequent cell lysis during cell separation and map to two loci. These mutations and their dosage suppressors define a signaling pathway (including Rho1 and a novel arrestin) for repairing cell-wall damage. The seventh mutation affects the poorly understood RNA-binding protein Scw1 and severely delays cell separation when combined either with a septin mutation or with a mutation affecting the septin-interacting, anillin-like protein Mid2, suggesting that Scw1 functions in a pathway parallel to that of the septins. Taken together, our results suggest that the S. pombe septins participate redundantly in one or more pathways that cooperate with the actomyosin ring during cytokinesis and that a septin defect causes septum defects that can be repaired effectively only when the cell-integrity pathway is intact.THE fission yeast Schizosaccharomyces pombe provides an outstanding model system for studies of cytokinesis (McCollum and Gould 2001; Balasubramanian et al. 2004; Pollard and Wu 2010). As in most animal cells, successful cytokinesis in S. pombe requires an actomyosin ring (AMR). The AMR begins to assemble at the G₂/M transition and involves the type II myosin heavy chains Myo2 and Myp2 and the light chains Cdc4 and Rlc1 (Wu et al. 2003). Myo2 and Cdc4 are essential for cytokinesis under all known conditions, Rlc1 is important at all temperatures but essential only at low temperatures, and Myp2 is essential only under stress conditions. As the AMR constricts, a septum of cell wall is formed between the daughter cells. The primary septum is sandwiched by secondary septa and subsequently digested to allow cell separation (Humbel et al. 2001; Sipiczki 2007). Because of the internal turgor pressure of the cells, the proper assembly and structural integrity of the septal layers are essential for cell survival.Septum formation involves the β-glucan synthases Bgs1/Cps1/Drc1, Bgs3, and Bgs4 (Ishiguro et al. 1997; Le Goff et al. 1999; Liu et al. 1999, 2002; Martín et al. 2003; Cortés et al. 2005) and the α-glucan synthase Ags1/Mok1 (Hochstenbach et al. 1998; Katayama et al. 1999). These synthases are regulated by the Rho GTPases Rho1 and Rho2 and the protein kinase C isoforms Pck1 and Pck2 (Arellano et al. 1996, 1997, 1999; Nakano et al. 1997; Hirata et al. 1998; Calonge et al. 2000; Sayers et al. 2000; Ma et al. 2006; Barba et al. 2008; García et al. 2009b). The Rho GTPases themselves appear to be regulated by both GTPase-activating proteins (GAPs) and guanine-nucleotide-exchange factors (GEFs) (Nakano et al. 2001; Calonge et al. 2003; Iwaki et al. 2003; Tajadura et al. 2004; Morrell-Falvey et al. 2005; Mutoh et al. 2005; García et al. 2006, 2009a,b). In addition, septum formation and AMR function appear to be interdependent. In the absence of a normal AMR, cells form aberrant septa and/or deposit septal materials at random locations, whereas a mutant defective in septum formation (bgs1) is also defective in AMR constriction (Gould and Simanis 1997; Le Goff et al. 1999; Liu et al. 1999, 2000). Both AMR constriction and septum formation also depend on the septation initiation network involving the small GTPase Spg1 (McCollum and Gould 2001; Krapp and Simanis 2008). Despite this considerable progress, many questions remain about the mechanisms and regulation of septum formation and its relationships to the function of the AMR.One major question concerns the role(s) of the septins. Proteins of this family are ubiquitous in fungal and animal cells and typically localize to the cell cortex, where they appear to serve as scaffolds and diffusion barriers for other proteins that participate in a wide variety of cellular processes (Longtine et al. 1996; Gladfelter et al. 2001; Hall et al. 2008; Caudron and Barral 2009). Despite the recent progress in elucidating the mechanisms of septin assembly (John et al. 2007; Sirajuddin et al. 2007; Bertin et al. 2008; McMurray and Thorner 2008), the details of septin function remain obscure. However, one prominent role of the septins and associated proteins is in cytokinesis. Septins concentrate at the division site in every cell type that has been examined, and in Saccharomyces cerevisiae (Hartwell 1971; Longtine et al. 1996; Lippincott et al. 2001; Dobbelaere and Barral 2004) and at least some Drosophila (Neufeld and Rubin 1994; Adam et al. 2000) and mammalian (Kinoshita et al. 1997; Surka et al. 2002) cell types, the septins are essential for cytokinesis. In S. cerevisiae, the septins are required for formation of the AMR (Bi et al. 1998; Lippincott and Li 1998). However, this cannot be their only role, because the AMR itself is not essential for cytokinesis in this organism (Bi et al. 1998; Korinek et al. 2000; Schmidt et al. 2002). Moreover, there is no evidence that the septins are necessary for AMR formation or function in any other organism. A further complication is that in some cell types, including most Caenorhabditis elegans cells (Nguyen et al. 2000; Maddox et al. 2007) and some Drosophila cells (Adam et al. 2000; Field et al. 2008), the septins do not appear to be essential for cytokinesis even though they localize to the division site.S. pombe has seven septins, four of which (Spn1, Spn2, Spn3, and Spn4) are expressed in vegetative cells and localize to the division site shortly before AMR constriction and septum formation (Longtine et al. 1996; Berlin et al. 2003; Tasto et al. 2003; Wu et al. 2003; An et al. 2004; Petit et al. 2005; Pan et al. 2007; Onishi et al. 2010). Spn1 and Spn4 appear to be the core members of the septin complex (An et al. 2004; McMurray and Thorner 2008), and mutants lacking either of these proteins do not assemble the others at the division site. Assembly of a normal septin ring also depends on the anillin-like protein Mid2, which colocalizes with the septins (Berlin et al. 2003; Tasto et al. 2003). Surprisingly, mutants lacking the septins are viable and form seemingly complete septa with approximately normal timing. These mutants do, however, display a variable delay in separation of the daughter cells, suggesting that the septins play some role(s) in the proper completion of the septum or in subsequent processes necessary for cell separation (Longtine et al. 1996; An et al. 2004; Martín-Cuadrado et al. 2005).It is possible that the septins localize to the division site and yet are nonessential for division in some cell types because their role is redundant with that of some other protein(s) or pathway(s). To explore this possibility in S. pombe, we screened for mutations that were lethal in combination with a lack of septins. The results suggest that the septins cooperate with the AMR during cytokinesis and that, in the absence of septin function, the septum is not formed properly, so that an intact system for recognizing and repairing cell-wall damage becomes critical for cell survival.     

The secreted Alzheimer-related amyloid precursor protein fragment has an essential role in C. elegans

Mutations in the gene encoding the amyloid precursor protein (APP) or the enzymes that process APP are correlated with familial Alzheimer disease. Alzheimer disease is also associated with insulin resistance (type 2 diabetes). In our recently published study,¹ Ewald CY, Raps DA, Li C. APL-1, the Alzheimer’s Amyloid precursor protein in Caenorhabditis elegans, modulates multiple metabolic pathways throughout development. Genetics 2012; 191:493 - 507; http://dx.doi.org/10.1534/genetics.112.138768; PMID: 22466039 [Crossref], [PubMed], [Web of Science ®] , [Google Scholar] we obtained genetic evidence that the extracellular fragment of APL-1, the C. elegans ortholog of human APP, may act as a signaling molecule to modulate insulin and nuclear hormone pathways in C. elegans development. In addition, independent of insulin and nuclear hormone signaling, high levels of the extracellular fragment of APL-1 (sAPL-1) leads to a temperature-sensitive embryonic lethality, which is dependent on activity of a predicted receptor protein tyrosine phosphatase (MOA-1/R155.2). Furthermore, this embryonic lethality is enhanced by knockdown of a predicted prion-like protein (pqn-29). The precise molecular mechanisms underlying these processes remain to be determined. Here, we present hypothetical models as to how sAPL-1 signaling influences metabolic and developmental pathways. Together, with previous findings in mammals that the extracellular domain of mammalian APP (sAPP) binds to a death-receptor,² Nikolaev A, McLaughlin T, O’Leary DD, Tessier-Lavigne M. APP binds DR6 to trigger axon pruning and neuron death via distinct caspases. Nature 2009; 457:981 - 9; http://dx.doi.org/10.1038/nature07767; PMID: 19225519 [Crossref], [PubMed], [Web of Science ®] , [Google Scholar] our findings support the model that sAPP signaling affects critical biological processes.     

Unraveling the Complex Trait of Crop Yield With Quantitative Trait Loci Mapping in Brassica napus

Yield is the most important and complex trait for the genetic improvement of crops. Although much research into the genetic basis of yield and yield-associated traits has been reported, in each such experiment the genetic architecture and determinants of yield have remained ambiguous. One of the most intractable problems is the interaction between genes and the environment. We identified 85 quantitative trait loci (QTL) for seed yield along with 785 QTL for eight yield-associated traits, from 10 natural environments and two related populations of rapeseed. A trait-by-trait meta-analysis revealed 401 consensus QTL, of which 82.5% were clustered and integrated into 111 pleiotropic unique QTL by meta-analysis, 47 of which were relevant for seed yield. The complexity of the genetic architecture of yield was demonstrated, illustrating the pleiotropy, synthesis, variability, and plasticity of yield QTL. The idea of estimating indicator QTL for yield QTL and identifying potential candidate genes for yield provides an advance in methodology for complex traits.YIELD is the most important and complex trait in crops. It reflects the interaction of the environment with all growth and development processes that occur throughout the life cycle (Quarrie et al. 2006). Crop yield is directly and multiply determined by yield-component traits (such as seed weight and seed number). Yield-related traits (such as biomass, harvest index, plant architecture, adaptation, resistance to biotic and abiotic constraints) may also indirectly affect yield by affecting the yield-component traits or by other, unknown mechanisms. Increasing evidence suggests that “fine-mapped” quantitative trait loci (QTL) or genes identified as affecting crop yield involve diverse pathways, such as seed number (Ashikari et al. 2005; Tian et al. 2006b; Burstin et al. 2007; Xie et al. 2008; Xing et al. 2008; Xue et al. 2008), seed weight (Ishimaru 2003; Song et al. 2005; Shomura et al. 2008; Wang et al. 2008; Xie et al. 2006, 2008; Xing et al. 2008; Xue et al. 2008), flowering time (Cockram et al. 2007; Song et al. 2007; Xie et al. 2008; Xue et al. 2008), plant height (Salamini 2003; Ashikari et al. 2005; Xie et al. 2008; Xue et al. 2008), branching (Clark et al. 2006; Burstin et al. 2007; Xing et al. 2008), biomass yield (Quarrie et al. 2006; Burstin et al. 2007), resistance and tolerance to biotic and abiotic stresses (Khush 2001; Brown 2002; Yuan et al. 2002; Waller et al. 2005; Zhang 2007; Warrington et al. 2008), and root architecture (Hochholdinger et al. 2008).Many experiments have explored the genetic basis of yield and yield-associated traits (yield components and yield-related traits) in crops. Summaries of identified QTL have been published for wheat (MacCaferri et al. 2008), barley (Von Korff et al. 2008), rice, and maize (http://www.gramene.org/). The results show several common patterns. First, QTL for yield and yield-associated traits tend to be clustered in the genome, which suggests that the QTL of the yield-associated traits have pleiotropic effects on yield. Second, this kind of pleiotropy has not been well analyzed genetically. The QTL for yield (complicated factor), therefore, have not been associated with any yield-associated traits (relatively simple factors, such as plant height). Therefore, they are unlikely to predict accurately potential candidate genes for yield. Third, only a few loci (rarely >10) have been found for each of these traits. Thus, the genetic architecture of yield has remained ambiguous. Fourth, trials were carried out in a few environments and how the mode of expression of QTL for these complex traits might respond in different environments is unclear.In this study, the genetic architecture of crop yield was analyzed through the QTL mapping of seed yield and eight yield-associated traits in two related populations of rapeseed (Brassica napus) that were grown in 10 natural environments. The complexity of the genetic architecture of seed yield was demonstrated by QTL meta-analysis. The idea of estimating indicator QTL (QTL of yield-associated traits, which are defined as the potential genetic determinants of the colocalized QTL for yield) for yield QTL in conjunction with the identification of candidate genes is described.     

Genetic Modifiers of dFMR1 Encode RNA Granule Components in Drosophila

Mechanisms of neuronal mRNA localization and translation are of considerable biological interest. Spatially regulated mRNA translation contributes to cell-fate decisions and axon guidance during development, as well as to long-term synaptic plasticity in adulthood. The Fragile-X Mental Retardation protein (FMRP/dFMR1) is one of the best-studied neuronal translational control molecules and here we describe the identification and early characterization of proteins likely to function in the dFMR1 pathway. Induction of the dFMR1 in sevenless-expressing cells of the Drosophila eye causes a disorganized (rough) eye through a mechanism that requires residues necessary for dFMR1/FMRP''s translational repressor function. Several mutations in dco, orb2, pAbp, rm62, and smD3 genes dominantly suppress the sev-dfmr1 rough-eye phenotype, suggesting that they are required for dFMR1-mediated processes. The encoded proteins localize to dFMR1-containing neuronal mRNPs in neurites of cultured neurons, and/or have an effect on dendritic branching predicted for bona fide neuronal translational repressors. Genetic mosaic analyses indicate that dco, orb2, rm62, smD3, and dfmr1 are dispensable for translational repression of hid, a microRNA target gene, known to be repressed in wing discs by the bantam miRNA. Thus, the encoded proteins may function as miRNA- and/or mRNA-specific translational regulators in vivo.THE subcellular localization and regulated translation of stored mRNAs contributes to cellular asymmetry and subcellular specialization (Lecuyer et al. 2007; Martin and Ephrussi 2009). In mature neurons, local protein synthesis at active synapses may contribute to synapse-specific plasticity that underlies persistent forms of memory (Casadio et al. 1999; Ashraf et al. 2006; Sutton and Schuman 2006; Richter and Klann 2009). During this process, synaptic activity causes local translation of mRNAs normally stored in translationally repressed synaptic mRNPs (Sutton and Schuman 2006; Richter and Klann 2009). While specific neuronal translational repressors and microRNAs have been implicated in this process, their involvement in local translation that underlies memory, as well as the underlying mechanisms, are generally not well understood (Schratt et al. 2006; Keleman et al. 2007; Kwak et al. 2008; Li et al. 2008; Richter and Klann 2009). Furthermore, it remains possible that there are neuron-specific, mRNA-specific, and stimulus-pattern specific pathways for neuronal translational control (Raab-Graham et al. 2006; Giorgi et al. 2007).The Fragile-X Mental Retardation protein (FMRP) is among the best studied of neuronal translational repressors, in part due to its association with human neurodevelopmental disease (Pieretti et al. 1991; Mazroui et al. 2002; Gao 2008). Consistent with function in synaptic translation required for memory formation, mutations in FMRP are associated with increased synaptic translation, enhanced LTD, increased synapse growth, and also with enhanced long-term memory (Zhang et al. 2001; Huber et al. 2002; Bolduc et al. 2008; Dictenberg et al. 2008).FMRP co-immunoprecipitates with components of the RNAi and miRNA machinery and appears to be required for aspects of miRNA function in neurons (Caudy et al. 2002; Ishizuka et al. 2002; Jin et al. 2004b; Gao 2008). In addition, FMRP associates with neuronal polyribosomes as well as with Staufen-containing ribonucleoprotein (mRNP) granules easily observed in neurites of cultured neurons (Feng et al. 1997; Krichevsky and Kosik 2001; Mazroui et al. 2002; Kanai et al. 2004; Barbee et al. 2006; Bramham and Wells 2007; Bassell and Warren 2008; Dictenberg et al. 2008). FMRP-containing neuronal mRNPs contain not only several ubiquitous translational control molecules, but also CaMKII and Arc mRNAs, whose translation is locally controlled at synapses (Rook et al. 2000; Krichevsky and Kosik 2001; Kanai et al. 2004; Barbee et al. 2006). Thus, FMRP-containing RNA particles are probably translationally repressed and transported along microtubules from the neuronal cell body to synaptic sites in dendrites where local synaptic activity can induce their translation (Kiebler and Bassell 2006; Dictenberg et al. 2008).The functions of FMRP/dFMR1 in mRNA localization as well as miRNA-dependent and independent forms of translational control is likely to require several other regulatory proteins. To identify such proteins, we used a previously designed and validated genetic screen (Wan et al. 2000; Jin et al. 2004a; Zarnescu et al. 2005). The overexpression of dFMR1 in the fly eye causes a “rough-eye” phenotype through a mechanism that requires (a) key residues in dFMR1 that mediate translational repression in vitro; (b) Ago1, a known components of the miRNA pathway; and (c) a DEAD-box helicase called Me31B, which is a highly conserved protein from yeast (Dhh1p) to humans (Rck54/DDX6) functioning in translational repression and present on neuritic mRNPs (Wan et al. 2000; Laggerbauer et al. 2001; Jin et al. 2004a; Coller and Parker 2005; Barbee et al. 2006; Chu and Rana 2006). To identify other Me31B-like translational repressors and neuronal granule components, we screened mutations in 43 candidate proteins for their ability to modify dFMR1 induced rough-eye phenotype. We describe the results of this genetic screen and follow up experiments to address the potential cellular functions of five genes identified as suppressors of sev-dfmr1.     

Added credence for a late Dodo extinction date

Considerable controversy surrounds the extinction date for the dodo (Raphus cucullatus), and the last uncontrovertibly confirmed sighting is ascribed to Volkert Evertsz on an islet off Mauritius in 1662. Nevertheless, both Roberts and Solow (2003), using a statistical technique, and Hume et al. (2004 HumeJP, MartillDM, DewdneyC. 2004. Dutch diaries and the demise of the dodo. Nature. 429:6992.[Crossref], [Web of Science ®] , [Google Scholar]), drawing on Lamotius' hunting diaries (1685–1688), place the extinction date as late as 1690 and 1693, respectively. A well-known account of Benjamin Harry from 1681 seems to have been frequently dismissed as unreliable or anecdotal. Our purpose here is to provide new background information on Harry's scientific credentials that adds considerable credence to his 1681 report and thus adds to the likelihood of a late date for the dodo's demise, in agreement with the 1690 lower bound.     

Identification of the Major Sex-Determining Region of Turbot (Scophthalmus maximus)

Sex determination in fish is a labile character in evolutionary terms. The sex-determining (SD) master gene can differ even between closely related fish species. This group is an interesting model for studying the evolution of the SD region and the gonadal differentiation pathway. The turbot (Scophthalmus maximus) is a flatfish of great commercial value, where a strong sexual dimorphism exists for growth rate. Following a QTL and marker association approach in five families and a natural population, we identified the main SD region of turbot at the proximal end of linkage group (LG) 5, close to the SmaUSC-E30 marker. The refined map of this region suggested that this marker would be 2.6 cM and 1.4 Mb from the putative SD gene. This region appeared mostly undifferentiated between males and females, and no relevant recombination frequency differences were detected between sexes. Comparative genomics of LG5 marker sequences against five model species showed no similarity of this chromosome to the sex chromosomes of medaka, stickleback, and fugu, but suggested a similarity to a sex-associated QTL from Oreochromis spp. The segregation analysis of the closest markers to the SD region demonstrated a ZW/ZZ model of sex determination in turbot. A small proportion of families did not fit perfectly with this model, which suggests that other minor genetic and/or environmental factors are involved in sex determination in this species.SEX ratio is a central demographic parameter directly related to the reproductive potential of individuals and populations (Penman and Piferrer 2008). The phenotypic sex depends on the processes of both sex determination and sex differentiation. Exogenous factors, such as temperature, hormones, or social behavior, can modify the gonad development pathway in fish (Baroiller and D''Cotta 2001; Piferrer and Guiguen 2008). Both genetic (GSD) and environmental sex determination has been reported in this group (Devlin and Nagahama 2002; Penman and Piferrer 2008), although primary sex determination is genetic in most species (Valenzuela et al. 2003). Among GSD, single, multiple, or polygenic sex-determining (SD) gene systems have been documented (Kallman 1984; Matsuda et al. 2002; Lee et al. 2004; Vandeputte et al. 2007).Sex determination in fish can evolve very rapidly (Woram et al. 2003; Peichel et al. 2004; Ross et al. 2009). Different sex determination mechanisms have been reported between congeneric species and even between populations of the same species (Almeida-Toledo and Foresti 2001; Lee et al. 2004; Mank et al. 2006). The evolution of sex chromosomes involves the suppression of recombination between homologous chromosomes probably to maintain sex-related coadapted gene blocks (Charlesworth et al. 2005; Tripathi et al. 2009). The sex determination pathway appears to be less conserved than other developmental processes (Penman and Piferrer 2008). However, differences are more related to the top of the hierarchy in the developmental pathway, while downstream genes are more conserved (Wilkins 1995; Marín and Baker 1998). As a consequence, the SD master gene in fish can vary among related species (Kondo et al. 2003; Tanaka et al. 2007; Alfaqih et al. 2009). In this sense, fish represent an attractive model for studying the evolution of SD mechanisms and sex chromosomes (Peichel et al. 2004; Kikuchi et al. 2007).A low proportion of fish species have demonstrated sex-associated chromosome heteromorphisms (Almeida-Toledo and Foresti 2001; Devlin and Nagahama 2002; Penman and Piferrer 2008). This is congruent with the rapid evolution of the SD region in fish, and thus in most species the male and female version of this chromosome region appears largely undifferentiated. In spite of this, indirect clues related to progenies of sex/chromosome-manipulated individuals or to segregation of morphologic/molecular sex-associated markers indicate that mechanisms of sex determination in fish are similar to other vertebrates (Penman and Piferrer 2008). With the arrival of genomics, large amounts of different genetic markers and genomic information are available for scanning genomes to look for their association with sex determination. Quantitative trait loci (QTL) (Cnaani et al. 2004; Peichel et al. 2004) or marker association (Felip et al. 2005; Chen et al. 2007) approaches have been used to identify the SD regions in some fish species. Also, microarrays constructed from gonadal ESTs have been applied to detect differentially expressed genes in the process of gonadal differentiation (Baron et al. 2005). Further, the increased genomic resources in model and aquaculture species have allowed the development of both comparative genomics (Woram et al. 2003; Kikuchi et al. 2007; Tripathi et al. 2009) and candidate gene (Shirak et al. 2006; Alfaqih et al. 2009) strategies to identify and characterize the SD region in fish. This has permitted the identification of the SD region in eight fish, including both model and aquaculture species (reviewed in Penman and Piferrer 2008).The turbot is a highly appreciated European aquaculture species, whose harvest is expected to increase from the current 9000 tons to >15,000 tons in 2012 (S. Cabaleiro, personal communication). Females of this species reach commercial size 4–6 months before males do, explaining the interest of the industry in obtaining all-female populations. Although some differences between families can be observed in the production process at farms, sex ratio is usually balanced at ∼1:1. Neither mitotic nor meiotic chromosomes have shown sex-associated heteromorphisms in turbot (Bouza et al. 1994; Cuñado et al. 2001). The proportion of sexes observed in triploid and especially gynogenetic progenies moved Cal et al. (2006a,b) to suggest an XX/XY mechanism in turbot with some additional, either environmental or genetic, factor involved. However, Haffray et al. (2009) have recently claimed a ZZ/ZW mechanism on the basis of the analysis of a large number of progenies from steroid-treated parents. These authors also suggested some (albeit low) influence of temperature in distorting sex proportions after the larval period. Finally, hybridizations between brill (Scophthalmus rhombus) and turbot render monosex progenies, depending on the direction of the cross performed, which suggests different SD mechanisms in these congeneric species (Purdom and ThaCker 1980).In this study, we used the turbot genetic map (Bouza et al. 2007, 2008; Martínez et al. 2008) to look for sex-associated QTL in this species. The identification of a major QTL in a specific linkage group (LG) in the five families analyzed prompted us to refine the genetic map at this LG and to perform a comparative genomics approach against model fish species for a precise location and characterization of the putative SD region. Also, sex-associated QTL markers were screened in a large natural population to provide additional support to our findings and to obtain population parameters at sex-related markers that could aid in interpreting the evolution of this genomic region.     

Profiling Sex-Specific piRNAs in Zebrafish

Piwi proteins and their partner small RNAs play an essential role in fertility, germ-line stem cell development, and the basic control and evolution of animal genomes. However, little knowledge exists regarding piRNA biogenesis. Utilizing microfluidic chip analysis, we present a quantitative profile of zebrafish piRNAs expressed differentially between testis and ovary. The sex-specific piRNAs are derived from separate loci of repeat elements in the genome. Ovarian piRNAs can be categorized into groups that reach up to 92 members, indicating a sex-specific arrangement of piRNA genes in the genome. Furthermore, precursor piRNAs preferentially form a hairpin structure at the 3′end, which seem to favor the generation of mature sex-specific piRNAs. In addition, the mature piRNAs from both the testis and the ovary are 2′-O-methylated at their 3′ ends.SMALL RNAs, ranging from 19 to 30 nucleotides (nt) in length, constitute a large family of regulatory molecules with diverse functions in invertebrates, vertebrates, plants, and fungi (Bartel 2004; Nakayashiki 2005). Two major classes of small RNAs are microRNAs (miRNAs) and small interfering RNAs (siRNAs). The functions of small RNAs have been conserved through evolution; they have been shown to inhibit gene expression at the levels of mRNA degradation, translational repression, chromatin modification, heterochromatin formation, and DNA elimination (Mochizuki et al. 2002; Bartel 2004; Kim et al. 2005; Brodersen and Voinnet 2006; Lee and Collins 2006; Vaucheret 2006).Over the past few years, focus on the genetics of small RNAs has helped clarify the mechanisms behind the regulation of these molecules. While hundreds of small RNAs have been identified from mammalian somatic tissues, relatively little is known about small RNAs in germ cells. A recent breakthrough has been the identification of small RNAs that associate with Piwi proteins (piRNAs) from Drosophila and mammalian gonads (Aravin et al. 2001, 2006; Girard et al. 2006; Grivna et al. 2006; Vagin et al. 2006; Watanabe et al. 2006). piRNAs and their interacting proteins Ziwi/Zili have also been identified in zebrafish (Houwing et al. 2007, 2008). Increasing evidence indicates that piRNAs play roles mainly in germ cell differentiation and genomic stability (Carthew 2006; Lau et al. 2006; Vagin et al. 2006; Brennecke et al. 2007; Chambeyron et al. 2008; Klattenhoff and Theurkauf 2008; Kuramochi-Miyagawa et al. 2008; Kim et al. 2009; Lim et al. 2009; Unhavaithaya et al. 2009). Moreover, although piRNAs are mostly expressed in germ line cells, recent studies showed piRNA expression in nongerm cells, for example, T-cell lines (Jurkat cells and MT4) (Azuma-Mukai et al. 2008; Yeung et al. 2009), indicating other functions such as in the immune system. piRNAs do not appear to be derived from double-stranded RNA precursors, and their biogenesis mechanisms, although unclear, may be distinct from those of siRNA and miRNA. Recently, two distinct piRNA production pathways were further proposed: the “ping-pong” model (Brennecke et al. 2007; Gunawardane et al. 2007) and the Ago3-independent piRNA pathway centered on Piwi in somatic cells (Li et al. 2009; Malone et al. 2009). However, the mechanistic pathways of piRNA activity and their biogenesis are still largely unknown.Teleost fishes comprise >24,000 species, accounting for more than half of extant vertebrate species, displaying remarkable variation in morphological and physiological adaptations (see review in Zhou et al. 2001). Recently, Houwing et al. (2007, 2008) reported findings on Ziwi/Zili and associated piRNAs, implicating roles in germ cell differentiation, meiosis, and transposon silencing in the germline of the zebrafish. However, some of the identified zebrafish piRNAs are nonrepetitive and nontransposon-related piRNAs, suggesting that piRNAs may have additional unknown roles. In this study, we show that for males and females, piRNAs are specifically derived from separate loci of the repeat elements, and that ovarian piRNAs are far more often associated in groups. Genomic analysis of piRNAs indicates a tendency to folding at the 3′ end of the piRNA precursor, which may favor cleavage of the piRNA precursor to generate mature sex-specific piRNAs. Furthermore, methylation modification occurs at the 2′-O-hydroxyl group on the ribose of the final 3′ nucleotide in both the testis and the ovary.     

Association Mapping of Quantitative Disease Resistance in a Natural Population of Loblolly Pine (Pinus taeda L.)

Genetic resistance to disease incited by necrotrophic pathogens is not well understood in plants. Whereas resistance is often quantitative, there is limited information on the genes that underpin quantitative variation in disease resistance. We used a population genomic approach to identify genes in loblolly pine (Pinus taeda) that are associated with resistance to pitch canker, a disease incited by the necrotrophic pathogen Fusarium circinatum. A set of 498 largely unrelated, clonally propagated genotypes were inoculated with F. circinatum microconidia and lesion length, a measure of disease resistance, data were collected 4, 8, and 12 weeks after inoculation. Best linear unbiased prediction was used to adjust for imbalance in number of observations and to identify highly susceptible and highly resistant genotypes (“tails”). The tails were reinoculated to validate the results of the full population screen. Significant associations were detected in 10 single nucleotide polymorphisms (SNPs) (out of 3938 tested). As hypothesized for genes involved in quantitative resistance, the 10 SNPs had small effects and proposed roles in basal resistance, direct defense, and signal transduction. We also discovered associated genes with unknown function, which would have remained undetected in a candidate gene approach constrained by annotation for disease resistance or stress response.GENETIC interactions between host and pathogen populations result in abundant natural variation in the genes involved in host disease resistance. Most of the studies leading to identification and cloning of disease resistance genes are focused on major gene disease resistance (Johal and Briggs 1992; Dangl and Jones 2001; Jones and Dangl 2006). In cases where resistance is associated with single genes, genetic effects are large in magnitude and detection is straightforward. In contrast, quantitative disease resistance is typically conditioned by many genes with relatively small effects. Quantitative resistance is generally considered to be more durable but also more difficult to investigate relative to major gene resistance, since the effects of individual genes are small and phenotyping experiments must be performed with high levels of precision. As a consequence, the genes and mechanisms of quantitative disease resistance are poorly understood, in part due to the smaller effect of individual genes on the resistance phenotype. Interactions between plants and necrotrophic pathogens often exhibit quantitative resistance (Balint-Kurti et al. 2008; Poland et al. 2009).Pitch canker disease of loblolly pine and other pine species is incited by the necrotrophic pathogen Fusarium circinatum and is manifest as resinous lesions in stems and branches (Dwinell et al. 1985; Enebak and Stanosz 2003; Carey et al. 2005; Sakamoto and Gordon 2006). There is evidence for heritable resistance to pitch canker in loblolly pine (Kayihan et al. 2005) as well as other pine species (Hodge and Dvorak 2000, 2007). In this article we report the first population-wide phenotypic screen of a clonally propagated population of loblolly pine for association testing (Eckert et al. 2010). Clonal propagation of this population enabled precise phenotyping, which was required to obtain the resolution needed to identify candidates for quantitative disease resistance loci.Pine species in general exhibit high levels of nucleotide variation and low linkage disequilibrium (LD) (Brown et al. 2004). An association genetic approach relies on the premise that historical, unrecorded recombination events over many generations have reduced LD between markers and quantitative trait loci such that only those marker-trait pairs that are tightly linked remain detectable; this may enable “fine mapping” to identify genes underlying quantitative variation (Flint-Garcia et al. 2003; Neale and Savolainen 2004). Association-based approaches have been used to identify candidate genes underlying traits in plants (Zhao et al. 2007; Stich et al. 2008; Wang et al. 2008; Yahiaoui et al. 2008; Inostroza et al. 2009; Stracke et al. 2009), based in part on applications in humans (D''alfonso et al. 2002; McGuffin et al. 2003; Easton et al. 2007; Lee et al. 2007), livestock (Martinez et al. 2006; Charlier et al. 2008; Goddard and Hayes 2009), and Drosophila (Kennington et al. 2007; Norry et al. 2007; Jiang et al. 2009). Recent association studies in tree species have evaluated single candidate genes or a modest number of candidate genes for association (Thumma et al. 2005; Gonzalez-Martinez et al. 2007, 2008; Ingvarsson et al. 2008; Eckert et al. 2009a). Association mapping has been used to identify disease resistance genes in several crop species including sugarcane, maize, barley, and potato (Flint-Garcia et al. 2005; Wei et al. 2006; Yu and Buckler 2006; Malosetti et al. 2007; Stich et al. 2008; Inostroza et al. 2009; Murray et al. 2009). The population analyzed in this study was genotyped at 3938 SNP loci that were selected without regard to the functional annotation of ESTs from which they were derived. Thus, we reasoned that the status of any particular marker as a candidate disease resistance gene would be determined by association testing, as opposed to previous studies in which markers were typically evaluated on the basis of their presumed roles in disease resistance in other species.Several different, but not mutually exclusive hypotheses have been proposed regarding the genetic origins of quantitative resistance (Poland et al. 2009), providing a useful framework for understanding evolution of resistance to necrotrophic pathogens. These six hypotheses proposed by Poland et al. (2009) predict that quantitative disease resistance is conditioned by: (1) genes regulating morphological and developmental phenotypes; (2) mutations in genes involved in basal defense causing small, incremental levels of resistance; (3) components of chemical warfare, through the action of genes producing antibiotic or antifungal compounds; (4) genes involved in defense signal transduction pathways; (5) weak forms of defeated R genes; and/or (6) genes not yet known to be involved in disease resistance.In this study, our main objective was to evaluate the genetic architecture of pitch canker disease resistance: to quantify the extent to which genes contribute to variation in the disease phenotype, to evaluate the hypothesis that disease resistance was quantitative, and to identify candidate genes for resistance as well as quantify their magnitude of effect. In the process of identifying candidate genes for resistance we were also able to evaluate support for hypotheses recently put forth by Poland et al. (2009) regarding the biological roles and origins of quantitative resistance genes.     

Estimating Breeding Values With Molecular Relatedness and Reconstructed Pedigrees in Natural Mating Populations of Common Sole,Solea Solea

Captive populations where natural mating in groups is used to obtain offspring typically yield unbalanced population structures with highly skewed parental contributions and unknown pedigrees. Consequently, for genetic parameter estimation, relationships need to be reconstructed or estimated using DNA marker data. With missing parents and natural mating groups, commonly used pedigree reconstruction methods are not accurate and lead to loss of data. Relatedness estimators, however, infer relationships between all animals sampled. In this study, we compared a pedigree relatedness method and a relatedness estimator (“molecular relatedness”) method using accuracy of estimated breeding values. A commercial data set of common sole, Solea solea, with 51 parents and 1953 offspring (“full data set”) was used. Due to missing parents, for 1338 offspring, a pedigree could be reconstructed with 10 microsatellite markers (“reduced data set”). Cross-validation of both methods using the reduced data set showed an accuracy of estimated breeding values of 0.54 with pedigree reconstruction and 0.55 with molecular relatedness. Accuracy of estimated breeding values increased to 0.60 when applying molecular relatedness to the full data set. Our results indicate that pedigree reconstruction and molecular relatedness predict breeding values equally well in a population with skewed contributions to families. This is probably due to the presence of few large full-sib families. However, unlike methods with pedigree reconstruction, molecular relatedness methods ensure availability of all genotyped selection candidates, which results in higher accuracy of breeding value estimation.To estimate genetic parameters, additive genetic relationships between individuals are inferred from known pedigrees (Falconer and Mackay 1996; Lynch and Walsh 1997). However, in natural populations (Ritland 2000; Thomas et al. 2002) and in captive species where natural mating in groups is used to obtain offspring (Brown et al. 2005; Fessehaye et al. 2006; Blonk et al. 2009) pedigrees are reconstructed. In these populations there is no control on mating structure, and typically unbalanced population structures with highly skewed parental contributions are obtained (Bekkevold et al. 2002; Brown et al. 2005; Fessehaye et al. 2006; Blonk et al. 2009). To reconstruct pedigrees, parental allocation methods are often used (Marshall et al. 1998; Avise et al. 2002; Duchesne et al. 2002). These methods require that all parents be known. For situations where parental information is not available, numerous DNA-marker-based methods for estimating molecular relatedness have been developed (Lynch 1988; Queller and Goodnight 1989; Ritland 2000; Toro et al. 2002). These relatedness estimators determine relationship values between individuals on a continuous scale. Evaluation of relatedness estimators within real and simulated data in both plants and animals (e.g., see Van de Casteele et al. 2001 ; Milligan 2003; Oliehoek et al. 2006; Rodríguez-Ramilo et al. 2007; Bink et al. 2008) has generally focused on bias and sampling error of estimated genetic variances or relatedness values. Relatively little attention has been paid to their efficiency for estimation of breeding values.Two types of relatedness estimators are currently available: method-of-moments estimators and maximum-likelihood estimators. Method-of-moments estimators (e.g., Queller and Goodnight 1989; Li et al. 1993; Ritland 1996; Lynch and Ritland 1999; Toro et al. 2002) determine relationships while calculating sharing of alleles between pairs in different ways. A variant of method-of-moments estimators is the transformation of continuous relatedness values to categorical genealogical relationships using “explicit pedigree reconstruction” (Fernández and Toro 2006) or thresholds (Rodríguez-Ramilo et al. 2007). However, correlations of transformed coancestries with known genealogical coancestries are low (Rodríguez-Ramilo et al. 2007). Several studies have compared different method-of-moments estimators but none revealed one single best estimator (Van de Casteele et al. 2001; Oliehoek et al. 2006; Rodríguez-Ramilo et al. 2007; Bink et al. 2008).Maximum-likelihood (ML) approaches classify animals into a limited number of relationship classes (Mousseau et al. 1998; Thomas et al. 2002; Wang 2004; Herbinger et al. 2006; Anderson and Weir 2007). For each pair a likelihood to fall into a possible relatedness class (e.g., full sib vs. unrelated) is calculated given its genotype and phenotype. ML techniques combined with a Markov chain Monte Carlo approach reconstruct groups with specific relationships jointly and are therefore more efficient than other ML approaches. To minimize standard errors, all discussed ML methods require balanced population structures, large sibling groups, and a large variance of relatedness (Thomas et al. 2002; Wang 2004; Anderson and Weir 2007). Therefore, these methods may not be suitable for natural mating systems.Unlike parental allocation methods, a benefit from relatedness estimators is that essentially all selection candidates are maintained for breeding value estimation, even with missing parents. The question is, however, whether such relatedness estimators also give accurate breeding values to perform selection.In this study, we test suitability of a relatedness estimator to obtain breeding values in a population of common sole, Solea solea (n = 1953) obtained by natural mating. First, we estimate breeding values using pedigree relatedness of animals for which a pedigree could be reconstructed (using parental allocation). This data set (n = 1338) is further referred to as “reduced data set.” We compare results with estimated breeding values using a simple but robust method-of-moments relatedness estimator: “molecular relatedness” (Toro et al. 2002, 2003). Next, we estimate breeding values using molecular relatedness in the full data set (n = 1953). Results show that accuracies of estimated breeding values obtained with molecular relatedness and pedigree relatedness are comparable. Accuracy increases when breeding values are estimated with molecular relatedness in the full data set. This implies that a molecular relatedness estimator can be used to estimate breeding values in captive natural mating populations.     

Patterns and Processes of Genome-Wide Divergence Between North American and African Drosophila melanogaster

Genomic tools and analyses are now being widely used to understand genome-wide patterns and processes associated with speciation and adaptation. In this article, we apply a genomics approach to the model organism Drosophila melanogaster. This species originated in Africa and subsequently spread and adapted to temperate environments of Eurasia and the New World, leading some populations to evolve reproductive isolation, especially between cosmopolitan and Zimbabwean populations. We used tiling arrays to identify highly differentiated regions within and between North America (the United States and Caribbean) and Africa (Cameroon and Zimbabwe) across 63% of the D. melanogaster genome and then sequenced representative fragments to study their genetic divergence. Consistent with previous findings, our results showed that most differentiation was between populations living in Africa vs. outside of Africa (i.e., “out-of-Africa” divergence), with all other geographic differences being less substantial (e.g., between cosmopolitan and Zimbabwean races). The X chromosome was much more strongly differentiated than the autosomes between North American and African populations (i.e., greater X divergence). Overall differentiation was positively associated with recombination rates across chromosomes, with a sharp reduction in regions near centromeres. Fragments surrounding these high F_ST sites showed reduced haplotype diversity and increased frequency of rare and derived alleles in North American populations compared to African populations. Nevertheless, despite sharp deviation from neutrality in North American strains, a small set of bottleneck/expansion demographic models was consistent with patterns of variation at the majority of our high F_ST fragments. Although North American populations were more genetically variable compared to Europe, our simulation results were generally consistent with those previously based on European samples. These findings support the hypothesis that most differentiation between North America and Africa was likely driven by the sorting of African standing genetic variation into the New World via Europe. Finally, a few exceptional loci were identified, highlighting the need to use an appropriate demographic null model to identify possible cases of selective sweeps in species with complex demographic histories.THE study of genetic differentiation between populations and species has recently been empowered by the use of genomic techniques and analysis (e.g., Noor and Feder 2006; Stinchcombe and Hoekstra 2008). In the past decade, genetic studies of adaptation and speciation have taken advantage of emerging molecular techniques to scan the genomes of diverging populations for highly differentiated genetic regions (e.g., Wilding et al. 2001; Emelianov et al. 2003; Beaumont and Balding 2004; Campbell and Bernatchez 2004; Scotti-Saintagne et al. 2004; Achere et al. 2005; Turner et al. 2005; Vasemagi et al. 2005; Bonin et al. 2006, 2007; Murray and Hare 2006; Savolainen et al. 2006; Yatabe et al. 2007; Nosil et al. 2008, 2009; Turner et al. 2008a,b; Kulathinal et al. 2009). As a result, genome scans can identify candidate regions that may be associated with adaptive evolution between diverging populations and, more broadly, are able to describe genome-wide patterns and processes of population differentiation (Begun et al. 2007; Stinchcombe and Hoekstra 2008).Genome scans in well-studied genetic model species such as Drosophila melanogaster gain particular power because differentiated loci are mapped to a well-annotated genome. Moreover, the evolutionary history of D. melanogaster is rich with adaptive and demographic events with many parallels to human evolution. Most notable is the historical out-of-Africa migration and subsequent adaptation to temperate ecological environments of Europe, Asia, North America, and Australia. This has resulted in widespread genetic and phenotypic divergence between African and non-African populations (e.g., David and Capy 1988; Begun and Aquadro 1993; Capy et al. 1994; Colegrave et al. 2000; Rouault et al. 2001; Takahashi et al. 2001; Caracristi and Schlötterer 2003; Baudry et al. 2004; Pool and Aquadro 2006; Schmidt et al. 2008; Yukilevich and True 2008a,b). Further, certain populations in Africa and in the Caribbean vary in their degree of reproductive isolation from populations in more temperate regions (Wu et al. 1995; Hollocher et al. 1997; Yukilevich and True 2008a,b). In particular, the Zimbabwe and nearby populations of southern Africa are strongly sexually isolated from all other populations, designating them as a distinct behavioral race (Wu et al. 1995).D. melanogaster has received a great deal of attention from the population geneticists in studying patterns of sequence variation across African and non-African populations. Many snapshots have been taken of random microsatellite and SNP variants spread across X and autosomes, and these have generated several important conclusions. Polymorphism patterns in European populations are characterized by reduced levels of nucleotide and haplotype diversity, an excess of high frequency-derived polymorphisms, and elevated levels of linkage disequilibrium relative to African populations (e.g., Begun and Aquadro 1993; Andolfatto 2001; Glinka et al. 2003; Haddrill et al. 2005; Ometto et al. 2005; Thornton and Andolfatto 2006; Hutter et al. 2007; Singh et al. 2007). These results have been generally interpreted as compatible with population size reduction/bottlenecks followed by recent population expansions. On the other hand, African populations are generally assumed either to have been relatively constant in size over time or to have experienced population size expansions. They generally show higher levels of nucleotide and haplotype diversity, an excess of rare variants, and a deficit of high frequency-derived alleles (Glinka et al. 2003; Ometto et al. 2005; Pool and Aquadro 2006; Hutter et al. 2007; but see Haddrill et al. 2005 for evidence of bottlenecks in Africa).Previous work also shows that the ratio of X-linked to autosomal polymorphism deviates from neutral expectations in opposite directions in African and European populations with more variation on the X than expected in Africa and less variation on the X than expected in Europe (Andolfatto 2001; Kauer et al. 2002; Hutter et al. 2007; Singh et al. 2007). The deviation from neutrality in the ratio of X-autosome polymorphism may be explained by positive selection being more prevalent on the X in Europe and/or by a combination of bottlenecks and male-biased sex ratios in Europe and female-biased sex ratios in Africa (Charlesworth 2001; Hutter et al. 2007; Singh et al. 2007). The selective explanation stems from the argument that, under the hitchhiking selection model, X-linked loci are likely to be more affected by selective sweeps than autosomal loci (Maynard Smith and Haigh 1974; Charlesworth et al. 1987; Vicoso and Charlesworth 2006, 2009).The relative contribution of selective and demographic processes in shaping patterns of genomic variation and differentiation is highly debated (Wall et al. 2002; Glinka et al. 2003; Haddrill et al. 2005; Ometto et al. 2005; Schöfl and Schlötterer 2004; Thornton and Andolfatto 2006; Hutter et al. 2007; Singh et al. 2007; Shapiro et al. 2007; Stephan and Li 2007; Hahn 2008; Macpherson et al. 2008; Noor and Bennett 2009; Sella et al. 2009). This is especially the case in D. melanogaster because derived non-African populations have likely experienced a complex set of demographic events during their migration out of Africa (e.g., Thornton and Andolfatto 2006; Singh et al. 2007; Stephan and Li 2007), making population genetics signatures of demography and selection difficult to tease apart (e.g., Macpherson et al. 2008). Thus it is still unclear what role selection has played in shaping overall patterns of genomic variation and differentiation relative to demographic processes in this species.While there is a long tradition in studying arbitrarily or opportunistically chosen sequences in D. melanogaster, genomic scans that focus particularly on highly differentiated sites across the genome have received much less attention. Such sites are arguably the best candidates to resolve the debate on which processes have shaped genomic differentiation within species (e.g., Przeworski 2002). Recently, a genome-wide scan of cosmopolitan populations in the United States and in Australia was performed to investigate clinal genomic differentiation on the two continents (Turner et al. 2008a). Many single feature polymorphisms differentiating Northern and Southern Hemisphere populations were identified. Among the most differentiated loci in common between continents, 80% were differentiated in the same orientation relative to the Equator, implicating selection as the likely explanation (Turner et al. 2008a). Larger regions of genomic differentiation within and between African and non-African populations have also been discovered, some of them possibly being driven by divergent selection (e.g., Dopman and Hartl 2007; Emerson et al. 2008; Turner et al. 2008a, Aguade 2009). Despite this recent progress, we still know relatively little about large-scale patterns of genomic differentiation in this species, especially between African and non-African populations, and whether most of this differentiation is consistent with demographic processes alone or if it requires selective explanations.In this work, we explicitly focus on identifying differentiated sites across the genome between U.S., Caribbean, West African, and Zimbabwean populations. This allows us to address several fundamental questions related to genomic evolution in D. melanogaster, such as the following: (1) Do genome-wide patterns of differentiation reflect patterns of reproductive isolation? (2) Is genomic differentiation random across and within chromosomes or are some regions overrepresented? (3) What are the population genetics properties of differentiated sites and their surrounding sequences? (4) Can demographic historical processes alone explain most of the observed differentiation on a genome-wide level or is it necessary to involve selection in their explanation?In general, our findings revealed that most genomic differentiation within D. melanogaster shows an out-of-Africa genetic signature. These results are inconsistent with the notion that most genomic differentiation occurs between cosmopolitan and Zimbabwean reproductively isolated races. Further, we found that the X is more differentiated between North American and African populations and more strongly deviates from pure neutrality in North American populations relative to autosomes. Nevertheless, our article shows that much of this deviation from neutrality is broadly consistent with several demographic null models, with a few notable exceptions. Athough this does not exclude selection as a possible alternative mechanism for the observed patterns, it supports the idea that most differentiation in D. melanogaster was likely driven by the sorting of African standing genetic variation into the New World.     

Death by over-eating: The Gaucher disease associated gene GBA1, identified in a screen for mediators of autophagic cell death,is necessary for developmental cell death in Drosophila midgut

Autophagy is critical for homeostasis and cell survival during stress, but can also lead to cell death, a little understood process that has been shown to contribute to developmental cell death in lower model organisms, and to human cancer cell death. We recently reported¹ Dasari SK, Bialik S, Levin-Zaidman S, Levin-Salomon V, Merrill AH, Jr., Futerman AH, Kimchi A. Signalome-wide rnai screen identifies gba1 as a positive mediator of autophagic cell death. Cell Death Differ. 2017;24(7):1288-1302. https://doi.org/10.1038/cdd.2017.80. PMID:28574511[Crossref], [PubMed], [Web of Science ®] [Google Scholar] on our thorough molecular and morphologic characterization of an autophagic cell death system involving resveratrol treatment of lung carcinoma cells. To gain mechanistic insight into this death program, we performed a signalome-wide RNAi screen for genes whose functions are necessary for resveratrol-induced death. The screen identified GBA1, the gene encoding the lysosomal enzyme glucocerebrosidase, as an important mediator of autophagic cell death. Here we further show the physiological relevance of GBA1 to developmental cell death in midgut regression during Drosophila metamorphosis. We observed a delay in midgut cell death in two independent Gba1a RNAi lines, indicating the critical importance of Gba1a for midgut development. Interestingly, loss-of-function GBA1 mutations lead to Gaucher Disease and are a significant risk factor for Parkinson Disease, which have been associated with defective autophagy. Thus GBA1 is a conserved element critical for maintaining proper levels of autophagy, with high levels leading to autophagic cell death.