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.     

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.     

Cis-regulatory Changes at FLOWERING LOCUS T Mediate Natural Variation in Flowering Responses of Arabidopsis thaliana

Flowering time, a critical adaptive trait, is modulated by several environmental cues. These external signals converge on a small set of genes that in turn mediate the flowering response. Mutant analysis and subsequent molecular studies have revealed that one of these integrator genes, FLOWERING LOCUS T (FT), responds to photoperiod and temperature cues, two environmental parameters that greatly influence flowering time. As the central player in the transition to flowering, the protein coding sequence of FT and its function are highly conserved across species. Using QTL mapping with a new advanced intercross-recombinant inbred line (AI-RIL) population, we show that a QTL tightly linked to FT contributes to natural variation in the flowering response to the combined effects of photoperiod and ambient temperature. Using heterogeneous inbred families (HIF) and introgression lines, we fine map the QTL to a 6.7 kb fragment in the FT promoter. We confirm by quantitative complementation that FT has differential activity in the two parental strains. Further support for FT underlying the QTL comes from a new approach, quantitative knockdown with artificial microRNAs (amiRNAs). Consistent with the causal sequence polymorphism being in the promoter, we find that the QTL affects FT expression. Taken together, these results indicate that allelic variation at pathway integrator genes such as FT can underlie phenotypic variability and that this may be achieved through cis-regulatory changes.MOLECULAR analysis of the phenotypic variation in life history traits is key to understanding how plants evolve in diverse natural environments. Among such traits, flowering time is critical for the reproductive success of the plant and is highly variable among natural Arabidopsis thaliana strains, providing an attractive paradigm for studying adaptive evolution (Johanson et al. 2000; Hagenblad and Nordborg 2002; Stinchcombe et al. 2004; Lempe et al. 2005; Shindo et al. 2005; Werner et al. 2005a). Two major environmental parameters that modulate flowering time are light and temperature (Koornneef et al. 1998). Temperature and light conditions vary substantially within the geographical range of A. thaliana, and natural populations presumably need to adapt to the local environment to ensure reproductive success. Flowering in A. thaliana is generally accelerated by long photoperiods, vernalization (exposure to winter-like conditions), and elevated ambient temperatures (Bäurle and Dean 2006). All these cues favor flowering of A. thaliana during spring or early summer, although the contribution from each individual cue and the interactions among them vary depending on the local environmental conditions (Wilczek et al. 2009).Flowering time is controlled through several genetic cascades that converge on a set of integrator genes including FLOWERING LOCUS T (FT), which encodes a protein that is highly conserved in flowering plants (Kardailsky et al. 1999; Kobayashi et al. 1999; Ahn et al. 2006). FT and its homologs are very likely an integral part of the mobile signal (florigen) that is produced in leaves and travels to the shoot apex to induce flowering (Abe et al. 2005; Wigge et al. 2005; Lifschitz et al. 2006; Corbesier et al. 2007; Jaeger and Wigge 2007; Lin et al. 2007; Mathieu et al. 2007; Tamaki et al. 2007; Notaguchi et al. 2008). In A. thaliana, FT expression is controlled by photoperiod, vernalization, and ambient growth temperature. Photoperiod in conjunction with the circadian clock promotes daily oscillations in FT RNA levels, which are greatly elevated at the end of long days. The central role of FT in determining the timing of flowering appears to be conserved in many species, making FT an attractive target for altering flowering time in cereals and other plants of economic importance (recently reviewed by Kobayashi and Weigel 2007; Turck et al. 2008).Wild strains of A. thaliana show extensive variation in flowering time and much of this is due to variation in the activity of the floral repressor FLOWERING LOCUS C (FLC). While some of this variation maps to FLC itself, much of it is due to differential activity at the epistatically acting FRIGIDA (FRI) locus (Michaels and Amasino 1999; Sheldon et al. 1999; Johanson et al. 2000; Michaels et al. 2003; Lempe et al. 2005; Shindo et al. 2005, 2006). Flowering is typically substantially delayed when the FRI/FLC system is active, unless these plants are first vernalized. However, FRI and FLC do not explain all of the flowering time variation seen in wild strains, and functionally divergent alleles of several additional flowering regulators, including CRYPTOCHROME 2 (CRY2), HUA2, FLOWERING LOCUS M (FLM), PHYTOCHROME C (PHYC), and PHYTOCHROME D (PHYD), have been identified in different strains of A. thaliana (Aukerman et al. 1997; Alonso-Blanco et al. 1998; El-Assal et al. 2001; Werner et al. 2005b; Balasubramanian et al. 2006a; Wang et al. 2007). Finally, there are many genotype-by-environment interactions that dramatically affect the contribution of a specific locus to the overall phenotype.The study of natural variation in A. thaliana has been greatly facilitated through the use of recombinant inbred line (RIL) populations (Koornneef et al. 2004). We have recently established two advanced intercross (AI)-RIL sets, in which the genetic map is greatly expanded, allowing for high-resolution QTL mapping (Balasubramanian et al. 2009). Here we use one of the new AI-RIL populations along with an independent F₂ population to identify the molecular basis of a light and temperature-sensitive flowering time QTL that mapped to the promoter of the FT gene. We show that FT is likely the causal gene for variation in light and temperature-sensitive flowering. Our results, in combination with those from other species, suggest that cis-regulatory variation rather than structural variation at FT contributes to phenotypic variation in natural populations.     

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.     

Sexual Isolation in Acinetobacter baylyi Is Locus-Specific and Varies 10,000-Fold Over the Genome

Naturally transformable bacteria acquire chromosomal DNA from related species at lower frequencies than from cognate DNA sources. To determine how genome location affects heterogamic transformation in bacteria, we inserted an nptI marker into random chromosome locations in 19 different strains of the Acinetobacter genus (>24% divergent at the mutS/trpE loci). DNA from a total of 95 nptI-tagged isolates was used to transform the recipient Acinetobacter baylyi strain ADP1. A total of >1300 transformation assays revealed that at least one nptI-tagged isolate for each of the strains/species tested resulted in detectable integration of the nptI marker into the ADP1 genome. Transformation frequencies varied up to ∼10,000-fold among independent nptI insertions within a strain. The location and local sequence divergence of the nptI flanking regions were determined in the transformants. Heterogamic transformation depended on RecA and was hampered by DNA mismatch repair. Our studies suggest that single-locus-based studies, and inference of transfer frequencies from general estimates of genomic sequence divergence, is insufficient to predict the recombination potential of chromosomal DNA fragments between more divergent genomes. Interspecies differences in overall gene content, and conflicts in local gene organization and synteny are likely important determinants of the genomewide variation in recombination rates between bacterial species.HORIZONTAL gene transfer (HGT) contributes to bacterial evolution by providing access to DNA evolved and retained in separate species or strains (Cohan 1994a,b; Bergstrom et al. 2000; Ochman et al. 2000; Feil et al. 2001; Koonin 2003; Lawrence and Hendrickson 2003; Fraser et al. 2007). Multilocus sequence typing (MLST) has provided strong evidence for frequent transfer and recombination of chromosomal DNA between related bacterial strains within the same species (Maiden et al. 1998; Enright et al. 2002). HGT occurring by natural transformation allows bacteria to exploit the presence of nucleic acids in their environment for the purposes of nutrition, DNA repair, reacquisition of lost genes, and/or acquisition of novel genetic diversity (Redfield 1993; Mehr and Seifert 1998; Dubnau 1999; Claverys et al. 2000; Szöllösi et al. 2006; Johnsen et al. 2009). It can be inferred from observations of the presence of extracellular DNA in most environments that bacteria are constantly exposed to DNA from a variety of sources, without such exposure necessarily producing observable changes in the genetic compositions of bacterial populations over evolutionary time (Thomas and Nielsen 2005; Nielsen et al. 2007a,b).The absence of sequence similarity between the donor DNA and the DNA of the recipient bacterium is the strongest barrier to the horizontal acquisition of chromosomal genes in bacteria (Matic et al. 1996; Vulic et al. 1997; Majewski 2001; Townsend et al. 2003) as illegitimate recombination occurs only at extremely low frequencies in bacteria (Hülter and Wackernagel 2008a). Single-locus transfer models have been extensively applied and have demonstrated a log-linear decrease in recombination frequencies with increasing sequence divergence for Bacillus subtilis (Roberts and Cohan, 1993; Zawadzki et al. 1995), Acinetobacter baylyi (Young and Ornston 2001), Escherichia coli (Shen and Huang 1986; Vulic et al. 1997), and Streptococcus pneumoniae (Majewski et al. 2000). For instance, heterogamic transformation between nonmutator isolates at the rpoB locus of B. mojavensis is undetectable at sequence divergences >16.7% (Zawadzki et al. 1995) and between S. pneumoniae isolates with sequence divergences >18% (Majewski et al. 2000). In A. baylyi, the nonmutator sequence divergence limit for detectable transformation at the pcaH locus of strain ADP1 was found to be 20% (Young and Ornston 2001), and up to 24% overall divergence yielded transformants at 16S rRNA loci in strain DSM587 (Strätz et al. 1996).Several recent studies also show that short stretches (<200 bp) of DNA sequence identity can facilitate additive or substitutive integration of longer stretches (>1000 bp) of heterologous DNA in bacteria (Prudhomme et al. 1991, 2002; de Vries and Wackernagel 2002; Hülter and Wackernagel 2008a). Thus, the uptake of DNA in bacteria can facilitate larger substitutions within gene sequences and the integration of additional DNA material on the basis of recombination initiated in flanking DNA stretches (either at one or both ends) with high sequence similarity (Nielsen et al. 2000). On the other hand, segments of heterologous DNA interrupting the synteny of homologous DNA have also been shown to be a barrier in intraspecies transformation in S. pneumoniae (Pasta and Sicard 1996, 1999).The various studies of the interspecies transfer potential of single genes demonstrate that the immediate local sequence divergence of the transferred locus is of high importance in determining recombination frequencies in hosts up to 20% divergent (at the housekeeping gene level). However, it can be hypothesized that the broader structural, organizational, and biochemical properties of the genome region surrounding a particular locus will determine its transfer potential to more divergent host species (Cohan 2001; Lawrence 2002). The interspecies transfer potential of various genome regions/loci between more diverged species (>20% at the housekeeping gene level) may therefore differ substantially from a log-linear model (determined experimentally for more closely related species) as local gene organization becomes less conserved with evolutionary time. The barriers to gene exchange between divergent bacterial species is likely a combination of inefficient recombination due to both mismatched base pairs (the main determinator in the log-linear model) and conflicting gene order and organization across the local recombining DNA regions. In addition, selective barriers due to negative effects on host fitness of the transferred DNA regions may become increasingly important for the removal of recombination events from the bacterial population. Recent bioinformatics-based genome analysis of E. coli and Salmonella genomes suggests various parts of the bacterial genome may have different suceptibilities to undergo evolutionarily successful recombination leading to temporal fragmentation of speciation (Lawrence 2002; Retchless and Lawrence 2007). Nevertheless, few studies have experimentally tested the effect of variable species and chromosome locations of genes on their transfer potential between bacteria (Ravin and Chen 1967; Ravin and Chakrabarti 1975; Siddiqui and Goldberg 1975; Cohan et al. 1991; Huang et al. 1991; Fall et al. 2007).Here, we determine to what extent genome location contributes to sexual isolation between the recipient A. baylyi strain ADP1 and 19 sequence divergent (24–27% divergent at the mutS/trpE loci) donor Acinetobacter strains and species (carrying a selectable nptI gene in a total of 95 random genome locations).     

Lethal Mutagenesis in Viruses and Bacteria

In this work we study how mutations that change physical properties of cell proteins (stability) affect population survival and growth. We present a model in which the genotype is presented as a set folding free energies of cell proteins. Mutations occur upon replication, so stabilities of some proteins in daughter cells differ from those in the parent cell by amounts deduced from the distribution of mutational effects on protein stability. The genotype–phenotype relationship posits that the cell''s fitness (replication rate) is proportional to the concentration of its folded proteins and that unstable essential proteins result in lethality. Simulations reveal that lethal mutagenesis occurs at a mutation rate close to seven mutations in each replication of the genome for RNA viruses and at about half that rate for DNA-based organisms, in accord with earlier predictions from analytical theory and experimental results. This number appears somewhat dependent on the number of genes in the organisms and the organism''s natural death rate. Further, our model reproduces the distribution of stabilities of natural proteins, in excellent agreement with experiments. We find that species with high mutation rates tend to have less stable proteins compared to species with low mutation rates.MUTATION rates play an important role in the evolution and adaptation of bacteria and viruses. Considerable experimental evidence suggests that high mutation rates in RNA virus populations have powered their rapid evolution (Eggers and Tamm 1965; Domingo et al. 1978; de la Torre et al. 1990; Domingo 2000). However, artificially elevated mutation rates were shown to have deleterious effects on the fitness of RNA viruses and to eventually lead to extinction of the viral population beyond certain mutation rate thresholds (Loeb et al. 1999; Sierra et al. 2000; Pariente et al. 2001; Grande-Perez et al. 2002; Anderson et al. 2004; Freistadt et al. 2004; Bull et al. 2007; Graci et al. 2007, 2008; Zeldovich et al. 2007). This observation is called lethal mutagenesis for RNA viruses. Several authors proposed to use lethal mutagenesis to cure or control infection with RNA viruses, using certain mutagens (Anderson et al. 2004; Freistadt et al. 2004). The possibility of lethal mutagenesis in bacteria was also suggested and studied recently (Gessler 1995; Andre and Godelle 2006; Bull and Wilke 2008).Previously, many attempts have been made, using population genetics, to theoretically describe the effect of mutation rates on the survival of a population (Muller 1964; Haigh 1978; Gessler 1995). The effect has frequently been described within the paradigm of Muller''s ratchet (Muller 1964; Haigh 1978; Andersson and Hughes 1996), where the genome of an asexual organism accumulates stochastic deleterious mutations in an irreversible manner, leading to the systematic decrease in the fitness of the organism. The concept of Muller''s ratchet applies to finite, asexual populations. It states that if back mutations cannot occur, eventually any finite asexual population will accumulate deleterious mutations and the mutation-free wild-type genotype would be lost. While such models provided some useful insights into the phenomenon of lethal mutagenesis, they often assume a single fitness peak and absence of back or compensating mutations and depend heavily on arbitrary parameters, such as selection coefficients or deleterious mutation rates. Such analyses therefore lack a more fundamental connection between the physical properties of the proteins within the organism, the metabolic network of the organism, and the feedback relationship between the mutation rate and organismal fitness.In recent years, several theories of lethal mutagenesis have been proposed (Guo et al. 2004; Bull et al. 2007; Zeldovich et al. 2007; Bull and Wilke 2008). In a marked departure from earlier phenomenological approaches Zeldovich et al. (2007) suggested a model assuming that the loss of protein stability would lead to the loss of essential functions within the organism and therefore to a lethal phenotype. The evolution of a population in this model was mapped to a diffusion process in a multidimensional hypercube where each dimension represented stability of proteins encoded by an essential gene and adsorbing boundary conditions at ΔG=0 boundaries [where ΔG is the difference between free energy of the folded and unfolded proteins, which is the thermodynamic measure of protein stability (Zeldovich et al. 2007)] were imposed to account for the fact that loss of stability confers a lethal phenotype on an organism. This model differs from previous approaches in that, instead of depending on arbitrarily calibrated parameters such as selection coefficients or deleterious mutation rates, it is based only on the statistical distribution of proteins'' folding free energy change after point mutations, which was directly derived from in vitro experiments. Furthermore, it predicts a lethal mutagenesis threshold that is consistent with experimental findings and discovers a deep relation between fundamental biophysical properties of proteins, the mutation rate, and organismal fitness.However, despite these insights, the model proposed by Zeldovich et al. (2007) is based on a number of simplifying assumptions. First, it assumes a uniform mutation supply within the population, meaning that at any time, mutations could occur in any organism in the population with an equal and constant probability. However, in real biological systems mutations are coupled to replication. While the formalism developed by Zeldovich et al. (2007) allows one to consider the case when mutations are coupled to replication (see Methods in Zeldovich et al. 2007), this formalism gives numerically accurate predictions for the coupled mutation–replication only in the limit of low mutation rates. However, lethal mutagenesis occurs when the mutation rate is relatively high (approximately six mutations per genome per replication according to Crotty et al. 2001 and Zeldovich et al. 2007). Second, the model developed in Zeldovich et al. (2007) assumes a very simple “Θ-function-like” fitness landscape whereby fitness is the same for all protein stabilities as long as proteins are stable; i.e., it is flat for all ΔG<0. However, in reality as proteins become less stable they spend a greater fraction of time in the unfolded state, reducing therefore the effective concentration of functional proteins, which may affect fitness. Our study overcomes these limitations in a new computational model as outlined below.If the organism has a conservative replication mechanism, as is the case for RNA viruses, then mutations would occur, with certain probabilities, only in the descendant copy, while the parent copy would remain unchanged (that may also be the case in organisms with double-stranded genomes, where the methylation mechanism keeps a master copy of the genome preserved). If the organism has semiconservative replication, as in bacteria and DNA viruses and double-stranded RNA viruses, then mutations could happen with certain probabilities in both daughter organisms.Here we present a detailed study of the fitness effect of protein stability changing mutations, based on the coupled mutation–replication scenario and more explicit physical consideration of the effect of protein stability on fitness. Simulating evolution and population growth in this model, we observe lethal mutagenesis in conservative and semiconservative replicating populations. Further, we show how stationary distribution of protein stabilities (folding free energies) emerges and discuss the physical and evolutionary reasons for the observed moderate stability of proteins.     

Does Gene Translocation Accelerate the Evolution of Laterally Transferred Genes?

Lateral gene transfer (LGT) and gene rearrangement are essential for shaping bacterial genomes during evolution. Separate attention has been focused on understanding the process of lateral gene transfer and the process of gene translocation. However, little is known about how gene translocation affects laterally transferred genes. Here we have examined gene translocations and lateral gene transfers in closely related genome pairs. The results reveal that translocated genes undergo elevated rates of evolution and gene translocation tends to take place preferentially in recently acquired genes. Translocated genes have a high probability to be truncated, suggesting that translocation followed by truncation/deletion might play an important role in the fast turnover of laterally transferred genes. Furthermore, more recently acquired genes have a higher proportion of genes on the leading strand, suggesting a strong strand bias of lateral gene transfer.GENE insertions and deletions, together with gene translocations play important roles in bacterial genome evolution (Garcia-Vallvé et al. 2000; Ochman and Jones 2000; Tillier and Collins 2000a; Fraser-Liggett 2005). Gene insertions and deletions, as the essential driving forces in influencing gene content (Kunin and Ouzounis 2003), have received a great deal of attention. Various methods have been employed to study gene insertions and deletions previously; for instance, there are studies of population dynamics (Nielsen and Townsend 2004), such as a birth-and-death model of evolution (Berg and Kurland 2002; Novozhilov et al. 2005), phylogeny-dependent studies including parsimony methods (Daubin et al. 2003a,b; Mirkin et al. 2003; Hao and Golding 2004), and maximum-likelihood methods (Hao and Golding 2006b, 2008b). It has been shown that recently laterally transferred genes have high evolutionary rates and high rates of gene turnover (Daubin et al. 2003b; Hao and Golding 2004, 2006b).Gene rearrangement has also been commonly studied as another important driving force that shapes bacterial genomes (for a review, see Rocha 2004). Gene order changes in genomes are history dependent; for instance, fewer gene rearrangements are expected among more closely related species. Gene order within genomes has therefore been used to reconstruct phylogeny (Sankoff et al. 2000; Tamames 2001; Rogozin et al. 2004; Belda et al. 2005). Previous studies have focused mainly on lateral gene transfer (LGT) and gene rearrangement individually, but little is known about any association between laterally transferred genes and gene rearrangements. The study of gene order of laterally acquired genes might shed some light on the understanding of the LGT process.In this study, we have examined gene translocations and lateral gene transfers in closely related genome pairs. It is shown that the proportion of translocated genes among recently acquired genes is always high, while the proportion of translocated genes is always low in ancient genes, suggesting that gene translocation tends to take place in recently transferred genes. The results also reveal that translocated genes have elevated rates of evolution compared with positionally conserved genes and gene truncation is more prevalent in translocated genes. These findings suggest that gene translocation might accelerate the gene turnover of recently transferred genes and/or that genes likely to undergo translocation are those genes more likely to be laterally transferred and dispensable for the genome. Furthermore, the proportion of recently acquired genes is higher on the leading strand, suggesting that laterally transferred genes are biased toward being on the leading strand. After lateral transfer, some genes could be translocated to the lagging strand and some translocated genes are likely to be eliminated during evolution.     

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.