Evolution of oligomeric state through allosteric pathways that mimic ligand binding.

Evolution and design of protein complexes are almost always viewed through the lens of amino acid mutations at protein interfaces. We showed previously that residues not involved in the physical interaction between proteins make important contributions to oligomerization by acting indirectly or allosterically. In this work, we sought to investigate the mechanism by which allosteric mutations act, using the example of the PyrR family of pyrimidine operon attenuators. In this family, a perfectly sequence-conserved helix that forms a tetrameric interface is exposed as solvent-accessible surface in dimeric orthologs. This means that mutations must be acting from a distance to destabilize the interface. We identified 11 key mutations controlling oligomeric state, all distant from the interfaces and outside ligand-binding pockets. Finally, we show that the key mutations introduce conformational changes equivalent to the conformational shift between the free versus nucleotide-bound conformations of the proteins.This is the accepted manuscript. The final version is available from AAAS at http://www.sciencemag.org/content/346/6216/1254346.abstract

Metaphors in Nanomedicine: The Case of Targeted Drug Delivery

International audienceThe promises of nanotechnology have been framed by a variety of metaphors, that not only channel the attention of the public, orient the questions asked by researchers, and convey epistemic choices closely linked to ethical preferences. In particular, the image of the 'therapeutic missile' commonly used to present targeted drug delivery devices emphasizes precision, control, surveillance and efficiency. Such values are highly praised in the current context of crisis of pharmaceutical innovation where military metaphors foster a general mobilization of resources from multiple fields of cutting-edge research. The missile metaphor, reminiscent of Paul Ehrlich's 'magic bullet', has framed the problem in simple terms: how to deliver the right dose in the right place at the right moment? Chemists, physicists and engineers who design multi-functional devices operating in vitro can think in such terms, as long as the devices are not actually operating through the messy environment of the body. A close look at what has been done and what remains to be done suggests that the metaphor of the "therapeutic missile" is neither sufficient, nor even necessary. Recent developments in nanomedicine suggest that therapeutic efficacy cannot be obtained without negotiating with the biological milieu and taking advantage of what it affords. An 'oïkological' approach seems more appropriate, more heuristic and more promising than the popular missile. It is based on the view of organism as an oikos that has to be carefully managed. The dispositions of nanocapsules have to be coupled with the affordances of the environment. As it requires dealing with nanoparticles as relational entities (defined by their potential for interactions) rather than as stable substances (defined by intrinsic properties) this metaphor eventually might well change research priorities in nanotechnology in general

Approaches in biotechnological applications of natural polymers

Natural polymers, such as gums and mucilage, are biocompatible, cheap, easily available and non-toxic materials of native origin. These polymers are increasingly preferred over synthetic materials for industrial applications due to their intrinsic properties, as well as they are considered alternative sources of raw materials since they present characteristics of sustainability, biodegradability and biosafety. As definition, gums and mucilages are polysaccharides or complex carbohydrates consisting of one or more monosaccharides or their derivatives linked in bewildering variety of linkages and structures. Natural gums are considered polysaccharides naturally occurring in varieties of plant seeds and exudates, tree or shrub exudates, seaweed extracts, fungi, bacteria, and animal sources. Water-soluble gums, also known as hydrocolloids, are considered exudates and are pathological products; therefore, they do not form a part of cell wall. On the other hand, mucilages are part of cell and physiological products. It is important to highlight that gums represent the largest amounts of polymer materials derived from plants. Gums have enormously large and broad applications in both food and non-food industries, being commonly used as thickening, binding, emulsifying, suspending, stabilizing agents and matrices for drug release in pharmaceutical and cosmetic industries. In the food industry, their gelling properties and the ability to mold edible films and coatings are extensively studied. The use of gums depends on the intrinsic properties that they provide, often at costs below those of synthetic polymers. For upgrading the value of gums, they are being processed into various forms, including the most recent nanomaterials, for various biotechnological applications. Thus, the main natural polymers including galactomannans, cellulose, chitin, agar, carrageenan, alginate, cashew gum, pectin and starch, in addition to the current researches about them are reviewed in this article.. }To the Conselho Nacional de Desenvolvimento Cientfíico e Tecnológico (CNPq) for fellowships (LCBBC and MGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nvíel Superior (CAPES) (PBSA). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and COMPETE 2020 (POCI-01-0145-FEDER-006684) (JAT)

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Sampling strategies to measure the prevalence of common recurrent infections in longitudinal studies

<p>Abstract</p> <p>Background</p> <p>Measuring recurrent infections such as diarrhoea or respiratory infections in epidemiological studies is a methodological challenge. Problems in measuring the incidence of recurrent infections include the episode definition, recall error, and the logistics of close follow up. Longitudinal prevalence (LP), the proportion-of-time-ill estimated by repeated prevalence measurements, is an alternative measure to incidence of recurrent infections. In contrast to incidence which usually requires continuous sampling, LP can be measured at intervals. This study explored how many more participants are needed for infrequent sampling to achieve the same study power as frequent sampling.</p> <p>Methods</p> <p>We developed a set of four empirical simulation models representing low and high risk settings with short or long episode durations. The model was used to evaluate different sampling strategies with different assumptions on recall period and recall error.</p> <p>Results</p> <p>The model identified three major factors that influence sampling strategies: (1) the clustering of episodes in individuals; (2) the duration of episodes; (3) the positive correlation between an individual's disease incidence and episode duration. Intermittent sampling (e.g. 12 times per year) often requires only a slightly larger sample size compared to continuous sampling, especially in cluster-randomized trials. The collection of period prevalence data can lead to highly biased effect estimates if the exposure variable is associated with episode duration. To maximize study power, recall periods of 3 to 7 days may be preferable over shorter periods, even if this leads to inaccuracy in the prevalence estimates.</p> <p>Conclusion</p> <p>Choosing the optimal approach to measure recurrent infections in epidemiological studies depends on the setting, the study objectives, study design and budget constraints. Sampling at intervals can contribute to making epidemiological studies and trials more efficient, valid and cost-effective.</p

Genetic variation in genes regulating skeletal muscle regeneration and tissue remodelling associated with weight loss in chronic obstructive pulmonary disease

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death globally. COPD patients with cachexia or weight loss have increased risk of death independent of body mass index (BMI) and lung function. We tested the hypothesis genetic variation is associated with weight loss in COPD using a genome-wide association study approach. METHODS: Participants with COPD (N = 4308) from three studies (COPDGene, ECLIPSE, and SPIROMICS) were analysed. Discovery analyses were performed in COPDGene with replication in SPIROMICS and ECLIPSE. In COPDGene, weight loss was defined as self-reported unintentional weight loss > 5% in the past year or low BMI (BMI < 20 kg/m2). In ECLIPSE and SPIROMICS, weight loss was calculated using available longitudinal visits. Stratified analyses were performed among African American (AA) and Non-Hispanic White (NHW) participants with COPD. Single variant and gene-based analyses were performed adjusting for confounders. Fine mapping was performed using a Bayesian approach integrating genetic association results with linkage disequilibrium and functional annotation. Significant gene networks were identified by integrating genetic regions associated with weight loss with skeletal muscle protein–protein interaction (PPI) data. RESULTS: At the single variant level, only the rs35368512 variant, intergenic to GRXCR1 and LINC02383, was associated with weight loss (odds ratio = 3.6, 95% confidence interval = 2.3–5.6, P = 3.2 × 10−8) among AA COPD participants in COPDGene. At the gene level in COPDGene, EFNA2 and BAIAP2 were significantly associated with weight loss in AA and NHW COPD participants, respectively. The EFNA2 association replicated among AA from SPIROMICS (P = 0.0014), whereas the BAIAP2 association replicated in NHW from ECLIPSE (P = 0.025). The EFNA2 gene encodes the membrane-bound protein ephrin-A2 involved in the regulation of developmental processes and adult tissue homeostasis such as skeletal muscle. The BAIAP2 gene encodes the insulin-responsive protein of mass 53 kD (IRSp53), a negative regulator of myogenic differentiation. Integration of the gene-based findings participants with PPI data revealed networks of genes involved in pathways such as Rho and synapse signalling. CONCLUSIONS: The EFNA2 and BAIAP2 genes were significantly associated with weight loss in COPD participants. Collectively, the integrative network analyses indicated genetic variation associated with weight loss in COPD may influence skeletal muscle regeneration and tissue remodelling

Genome-wide identification and expression profiling of auxin response factor (ARF) gene family in maize

<p>Abstract</p> <p>Background</p> <p>Auxin signaling is vital for plant growth and development, and plays important role in apical dominance, tropic response, lateral root formation, vascular differentiation, embryo patterning and shoot elongation. Auxin Response Factors (ARFs) are the transcription factors that regulate the expression of auxin responsive genes. The <it>ARF </it>genes are represented by a large multigene family in plants. The first draft of full maize genome assembly has recently been released, however, to our knowledge, the <it>ARF </it>gene family from maize (<it>ZmARF </it>genes) has not been characterized in detail.</p> <p>Results</p> <p>In this study, 31 maize (<it>Zea mays </it>L.) genes that encode ARF proteins were identified in maize genome. It was shown that maize <it>ARF </it>genes fall into related sister pairs and chromosomal mapping revealed that duplication of <it>ZmARFs </it>was associated with the chromosomal block duplications. As expected, duplication of some <it>ZmARFs </it>showed a conserved intron/exon structure, whereas some others were more divergent, suggesting the possibility of functional diversification for these genes. Out of these 31 <it>ZmARF </it>genes, 14 possess auxin-responsive element in their promoter region, among which 7 appear to show small or negligible response to exogenous auxin. The 18 <it>ZmARF </it>genes were predicted to be the potential targets of small RNAs. Transgenic analysis revealed that increased miR167 level could cause degradation of transcripts of six potential targets (<it>ZmARF3</it>, <it>9</it>, <it>16</it>, <it>18</it>, <it>22 </it>and <it>30</it>). The expressions of maize <it>ARF </it>genes are responsive to exogenous auxin treatment. Dynamic expression patterns of <it>ZmARF </it>genes were observed in different stages of embryo development.</p> <p>Conclusions</p> <p>Maize <it>ARF </it>gene family is expanded (31 genes) as compared to <it>Arabidopsis </it>(23 genes) and rice (25 genes). The expression of these genes in maize is regulated by auxin and small RNAs. Dynamic expression patterns of <it>ZmARF </it>genes in embryo at different stages were detected which suggest that maize <it>ARF </it>genes may be involved in seed development and germination.</p

First RNA-seq approach to study fruit set and parthenocarpy in zucchini (Cucurbita pepo L.)

[EN] Background: Zucchini fruit set can be limited due to unfavourable environmental conditions in off-seasons crops that caused ineffective pollination/fertilization. Parthenocarpy, the natural or artificial fruit development without fertilization, has been recognized as an important trait to avoid this problem, and is related to auxin signalling. Nevertheless, differences found in transcriptome analysis during early fruit development of zucchini suggest that other complementary pathways could regulate fruit formation in parthenocarpic cultivars of this species. The development of next-generation sequencing technologies (NGS) as RNA-sequencing (RNA-seq) opens a new horizon for mapping and quantifying transcriptome to understand the molecular basis of pathways that could regulate parthenocarpy in this species. The aim of the current study was to analyze fruit transcriptome of two cultivars of zucchini, a non-parthenocarpic cultivar and a parthenocarpic cultivar, in an attempt to identify key genes involved in parthenocarpy. Results: RNA-seq analysis of six libraries (unpollinated, pollinated and auxin treated fruit in a non-parthenocarpic and parthenocarpic cultivar) was performed mapping to a new version of C. pepo transcriptome, with a mean of 92% success rate of mapping. In the non-parthenocarpic cultivar, 6479 and 2186 genes were differentially expressed (DEGs) in pollinated fruit and auxin treated fruit, respectively. In the parthenocarpic cultivar, 10,497 in pollinated fruit and 5718 in auxin treated fruit. A comparison between transcriptome of the unpollinated fruit for each cultivar has been performed determining that 6120 genes were differentially expressed. Annotation analysis of these DEGs revealed that cell cycle, regulation of transcription, carbohydrate metabolism and coordination between auxin, ethylene and gibberellin were enriched biological processes during pollinated and parthenocarpic fruit set. Conclusion: This analysis revealed the important role of hormones during fruit set, establishing the activating role of auxins and gibberellins against the inhibitory role of ethylene and different candidate genes that could be useful as markers for parthenocarpic selection in the current breeding programs of zucchini.Research worked is supported by the project RTA2014-00078 from the Spanish Institute of Agronomy Research INIA (Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria) and also PP.AVA.AVA201601.7, FEDER y FSE (Programa Operativo FSE de Andalucia 2007-2013 "Andalucia se mueve con Europa"). TPV is supported by a FPI scholarship from RTA2011-00044-C02-01/02 project of INIA. The funding agencies were not involved in the design of the study, collection, analysis, and interpretation of data and in writing the manuscript.Pomares-Viciana, T.; Del Rio-Celestino, M.; Roman, B.; Die, J.; Picó Sirvent, MB.; Gómez, P. (2019). First RNA-seq approach to study fruit set and parthenocarpy in zucchini (Cucurbita pepo L.). BMC Plant Biology. 19:1-20. https://doi.org/10.1186/s12870-019-1632-2S12019Varga A, Bruinsma J. Tomato. In: Monselise SP, editor. CRC Handbook of Fruit Set and Development. Boca Raton: CRC Press; 1986. p. 461–80.Nepi M, Cresti L, Guarnieri M, Pacini E. Effect of relative humidity on water content, viability and carbohydrate profile of Petunia hybrid and Cucurbita pepo pollen. Plant Syst Evol. 2010;284:57–64.Gustafson FG. Parthenocarpy: natural and artificial. Bot Rev. 1942;8:599–654.Robinson RW, Reiners S. Parthenocarpy in summer squash. Hortscience. 1999;34:715–7.Pomares-Viciana T, Die J, Del Río-Celestino M, Román B, Gómez P. Auxin signalling regulation during induced and parthenocarpic fruit set in zucchini. Mol Breeding. 2017;37:56.Ozga JA, Reinecke DM. Hormonal interactions in fruit development. J Plant Growth Regul. 2003;22:73–81.Kim IS, Okubo H, Fujieda K. Endogenous levels of IAA in relation to parthenocarpy in cucumber (Cucumis sativus L). Sci Hortic. 1992;52:1–8.Olimpieri I, Siligato F, Caccia R, Mariotti L, Ceccarelli N, Soressi GP, et al. Tomato fruit set driven by pollination or by the parthenocarpic fruit allele are mediated by transcriptionally regulated gibberellin biosynthesis. Planta. 2007;226:877–88.Cui L, Zhang T, Li J, Lou Q, Chen J. Cloning and expression analysis of Cs-TIR1/AFB2: the fruit development-related genes of cucumber (Cucumis sativus L.). Acta Physiol Plant. 2014;36:139–49.De Jong M, Wolters-Arts J, Feron R, Mariani C, Vriezen WH. The Solanum lycopersicum auxin response factor 7 (SlARF7) regulates auxin signalling during tomato fruit set and development. Plant J. 2009;57:160–70.Wang H, Jones B, Li Z, Frasse P, Delalande C, Regad F, Chaabouni S, Latché A, Pech JC, Bouzayen M. The tomato aux/IAA transcription factor IAA9 is involved in fruit development and leaf morphogenesis. Plant Cell. 2005;17(10):2676–92.Goetz M, Vivian-Smith A, Johnson SD, Koltunow AM. AUXIN RESPONSE FACTOR 8 is a negative regulator of fruit initiation in Arabidopsis. Plant Cell. 2006;18(8):1873–86.Mazzucato A, Cellini F, Bouzayen M, Zouine M, Mila I, Minoia S et al. A TILLING allele of the tomato aux/IAA9 gene offers new insights into fruit set mechanisms and perspectives for breeding seedless tomatoes. Mol Breeding. 2015; 35(22):1-15.Blanca J, Cañizares J, Roig C, Ziarsolo P, Nuez F, Picó B. Transcriptome characterization and high throughput SSRs and SNPs discovery in Cucurbita pepo (Cucurbitaceae). BMC Genomics. 2011;12:104.Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009;10(1):57–63.Da Fonseca RR, Albrechtsen A, Themudo GE, Ramos-Madrigal J, Sibbesen JA, Maretty L, et al. Next-generation biology: sequencing and data analysis approaches for non-model organisms. Mar Genomics. 2016;30:3–13.Conesa A, Madrigal P, Tarazona S, Gomez-Cabrero D, Cervera A, McPherson A, et al. A survey of best practices for RNA-seq data analysis. Genome Biol. 2016;17:13.Li J, Cui ZWJ, Zhang T, Guo Q, Xu J, Li J, et al. Transcriptome comparison of global distinctive features between pollination and parthenocarpic fruit set reveals transcriptional phytohormone cross-talk in cucumber (Cucumis sativus L). Plant Cell Physiol. 2014;55(7):1325–42.Fu L, Niu B, Zhu Z, Wu S, Li W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics. 2012;28(23):3150–2.Montero-Pau J, Blanca J, Bombarely A, Ziarsolo P, Esteras C, Martí-Gómez C, et al. De novo assembly of the zucchini genome reveals a whole genome duplication associated with the origin of the Cucurbita genus. Plant Biotechnol J. 2017. https://doi.org/10.1111/pbi.12860 .Vriezen WH, Feron R, Maretto F, Keijman J, Mariani C. Changes in tomato ovary transcriptome demonstrate complex hormonal regulation of fruit set. New Phytol. 2008;177:60–76.Tang N, Deng W, Hu G, Hu N, Li Z. Transcriptome profiling reveals the regulatory mechanism underlying pollination dependent and parthenocarpic fruit set mainly mediated by auxin and gibberellin. PLoS One. 2015;10(4):e0125355.Li J, Yan S, Yang W, Li Y, Xia M, Chen Z, et al. Transcriptomic analysis reveals the roles of microtubule-related genes and transcription factors in fruit length regulation in cucumber (Cucumis sativus L.). Sci Rep. 2015;26(5):8031.Mironov V, De Veylder L, Van Montagu M, Inze D. Cyclin-dependent kinases and cell division in plants- the nexus. Plant Cell. 1999;11(4):509–22.Perrot-Rechenmann C. Cellular responses to auxin: division versus expansion. Cold Spring Harb Perspect Biol. 2010;2(5):a001446.De Veylder L, Beeckman T, Beemster GT, Krols L, Terras F, Landrieu I, et al. Functional analysis of cyclin-dependent kinase inhibitors of Arabidopsis. Plant Cell. 2001;13:1653–68.Nieuwland J, Menges M, Murray JAH. The plant cyclins. In: Inze D, editor. Cell cycle control and plant development, vol. 2007. Oxford: Wiley-Blackwell Publishing; 2007. p. 33–61.Menges M, Samland AK, Planchais S, Murray JA. The D-type cyclin CYCD3;1 is limiting for the G1-to-S-phasetransition in Arabidopsis. Plant Cell. 2006;18:893–906.Boruc J, Mylle E, Duda M, De Clercq R, Rombauts S, Geelen D, et al. Systematic localization of the Arabidopsis core cell cycle proteins reveals novel cell division complexes. Plant Physiol. 2010;152(2):553–65.Sampedro J, Cosgrove DJ. The expansin superfamily. Genome Biol. 2005;6:242.Esmon CA, Tinsley AG, Ljung K, Sandberg G, Hearne LB, Liscum E. A gradient of auxin and auxin-dependent transcription precedes tropic growth responses. Proc Natl Acad Sci. 2006;103:236–41.De Folter S, Busscher J, Colombo L, Losa A, Angenent GC. Transcript profiling of transcription factors genes during siliques development in Arabidopsis. Plant Mol Bio. 2004;56:351–3662004.Son O, Cho HY, Kim MR, Lee H, Lee MS, Song E, et al. Induction of a homeodomain-leucine zipper gene by auxin is inhibited by cytokinin in Arabidopsis roots. Biochem Biophys Res Commun. 2005;326(1):203–9.Olsson ASB, Engstroem P, Seoderman E. The homeobox genes ATHB12 and ATHB7 encode potential regulators of growth in response to water deficit in Arabidopsis. Plant Mol Biol. 2004;55:663–77.Merrow SB, Hopp RJ. Storage effects on winter squashes. Associations between the sugar and starch content of and the degree of preference for winter squashes. J Agric Food Chem. 1961;9:321–6.Berg JM, Tymoczko JL, Stryer L. Carbohydrates. In: Freeman WH, editor. Biochemistry. 5th ed. New York: W H Freeman; 2002.Prabhakar V, Löttgert T, Gigolashvili T, Bell K, Flügge UI, Häusler RE. Molecular and functional characterization of the plastid-localized phosphoenolpyruvate enolase (ENO1) from Arabidopsis thaliana. FEBS Lett. 2009;583(6):983–91.Rius SP, Casati P, Iglesias AA, Gomez-Casati DF. Characterization of Arabidopsis lines deficient in GAPC-1, a cytosolic NAD-dependent glyceraldehyde-3-phosphate dehydrogenase. Plant Physiol. 2008;148(3):1655–67.Van der Linde K, Gutsche N, Leffers HM, Lindermayr C, Müller B, Holtgrefe S, et al. Regulation of plant cytosolic aldolase functions by redox-modifications. Plant Physiol Biochem. 2011;49(9):946–57.Lim H, Cho MH, Jeon JS, Bhoo SH, Kwon YK, Hahn TR. Altered expression of pyrophosphate: fructose-6-phosphate 1-phosphotransferase affects the growth of transgenic Arabidopsis plants. Mol Cells. 2009;27(6):641–9.Baud S, Wuillème S, Dubreucq B, De Almeida A, Vuagnat C, Lepiniec L, et al. Function of plastidial pyruvate kinases in seeds of Arabidopsis thaliana. Plant J. 2007;52:405–19.De Jong M, Mariani C, Vriezen WH. The role of auxin and gibberellin in tomato fruit set. J Exp Bot. 2009;60(5):1523–32.Martínez C, Manzano S, Megías Z, Garrido D, Picó B, Jamilena M. Involvement of ethylene biosynthesis and signalling in fruit set and early fruit development in zucchini squash (Cucurbita pepo L.). BMC Plant Biol. 2013;13:139.Serrani JC, Fos M, Atarés A, Garcia-martinez JL. Effect of gibberellin and auxin on parthenocarpic fruit growth induction in the cv. micro-tom of tomato. J Plant Growth Regul. 2007;26:211–21.Mapelli S. Changes in cytokinin in the fruits of parthenocarpic and normal tomatoes. Plant Sci Lett. 1981;22:227–33.Ulmasov T, Hagen G, Guilfoyle TJ. Activation and repression of transcription by auxin-response factors. Proc Natl Acad Sci U S A. 1999;96:5844–9.Ulmasov T, Hagen G, Guilfoyle TJ. Dimerization and DNA binding of auxin response factors. Plant J. 1999;19:309–19.Tiwari SB, Hagen G, Guilfoyle TJ. Aux/IAA proteins contain a potent transcriptional repression domain. Plant Cell. 2004;16:533–43.Switzenberg JA, Beaudry RM, Grumet R. Effect of CRC:: etr1-1 transgene expression on ethylene production, sex expression, fruit set and fruit ripening in transgenic melon (Cucumis melo L.). Transgenic Res. 2015;24(3):497-507.Nitsch LM, Oplaat C, Feron R, Ma Q, Wolters-Arts M, Hedden P, et al. Abscisic acid levels in tomato ovaries are regulated by LeNCED1 and SlCYP707A1. Planta. 2009;229(6):1335–46.Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B. Mapping and quantifying mammalian transcriptomes by RNA-seq. Nat Methods. 2008;5(7):621–8.Robinson MD, McCarthy DJ, Smyth GK. Edger: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2008;26(1):139–40.Raza K, Mishra A. A novel anticlustering filtering algorithm for the prediction of genes as a drug target. Am J Bio Engi. 2012;2(5):206–11.Van Iterson M, Boer JM, Menezes RX. Filtering, FDR and power. BMCBioinformatics. 2010;11:450.Conesa A, Götz S, Garcia-Gomez JM, Terol J, Talon M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005;21:3674–6.Berardini TZ, Reiser L, Li D, Mezheritsky Y, Muller R, Strait E, Huala E. The Arabidopsis information resource: making and mining the “gold standard” annotated reference plant genome. Genesis. 2015. https://doi.org/10.1002/dvg.22877 .Bairoch A, Apweiler R. The SWISS-PROT protein sequence database and its supplement TrEMBL. Nucleic Acids Res. 2000;28(1):45–8.Johnson M, Zaretskaya I, Raytselis Y, Merezhuk Y, McGinnis S, Madden TL. NCBI BLAST: a better web interface. Nucleic Acids Res. 2008;36:W5–9.Wyatt LE, Strickler SR, Mueller LA, Mazourek M. An acorn squash (Cucurbita pepo ssp. ovifera) fruit and seed transcriptome as a resource for the study of fruit traits in Cucurbita. Hortic Res. 2015;2:14070. https://doi.org/10.1038/hortres.2014.70 .Zhang A, Ren GA, Sun YA, Guo H, Zhang SA, Zhang FA, et al. A high-density genetic map for anchoring genome sequences and identifying QTLs associated with dwarf vine in pumpkin (Cucurbita maxima Duch.). BMC Genomics. 2015;16:1101.Finn RD, Attwood TK, Babbit AB, Bork P, Bridge AJ, Chang HY. InterPro in 2017-beyond protein family and domain annotations. Nucleic Acids Res. https://doi.org/10.1093/nar/gkw1107 .Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Sherlock G. Gene ontology: tool for the unification of biology. Nat Genet. 2000;25(1):25–9.Kanehisa M, Araki M, Goto S, et al. KEGG for linking genomes to life and the environment. Nucleic Acids Res. 2008;36:480–4