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Expression of genes through the growth of mammalian organs

1.

Pantalacci, S. & Semon, M. Transcriptomics of embryos and growing organs: a lifting device for evo – devo. J. Exp. Zool. Mol. Dev. Evol. 324, 363-371 (2015).

2

Silbereis, J.C., Pochareddy, S., Zhu, Y., Li, M., and Sestan, N. The mobile and molecular landscapes of the growing human central nervous system. Neuron 89, 248-268 (2016).

three

DeFalco, T. & Capel, B. Gonad Morphogenesis in Vertebrates: Diverging Means to a Convergent Finish. Annu. Rev. Cell Dev. Biol. 25, 457-482 (2009).

four

Abzhanov, A. von Baer's legislation for the ages: misplaced ideas of the evolution of growth. Genet Developments. 29, 712-722 (2013).

5

Kalinka, A. T. and Tomancak, P. The evolution of the primary embryos of animals: conservation or divergence? Developments Ecol. Evol. 27, 385-393 (2012).

6

Ferner, Ok., Schultz, J.A. and Zeller, U. Comparative anatomy of neonates from the three main mammalian teams (monotremes, marsupials, placentals) and implications for the mammalian new child mammalian morphotype. J. Anat. 231, 798-822 (2017).

7.

Dickinson, M.E. et al. Excessive-throughput discovery of latest growth phenotypes. Nature 537, 508-514 (2016).

eight

Petrovski, S., Wang, Q., Heinzen, E., Allen, A., S. and Goldstein, D. B. Genetic Intolerance to Practical Variation and Interpretation of Private Genomes. PLoS Genet. 9, e1003709 (2013).

9

Lek, M. et al. Evaluation of genetic variation coding for proteins in 60 706 people. Nature 536, 285-291 (2016).

ten.

Cassa, C.A. et al. Estimation of the selective results of heterozygous variants truncating proteins from human exome information. Nat. Broom. 49, 806-810 (2017).

11

Ruderfer, D.M. et al. Fashions of gene intolerance of variation within the variety of uncommon copies in 59 898 human exomes. Nat. Broom. 48, 1107-1111 (2016).

12

Hill, M. A. Embryology Comparability of Carnegie Stadiums https://jeltsch.org/carnegie_stage_comparison (2017).

13

Bakker, B.S. et al. A 3-dimensional interactive digital atlas and a quantitative database on human growth. Science 354, aag0053 (2016).

14

Kerwin, J. et al. The Atlas HUDSEN: a three-dimensional spatial framework (3D) for the examine of gene expression within the growing mind. J. Anat. 217, 289-299 (2010).

15

Butler, H. & Juurlink, B.H. J. Atlas for the staging of mammalian and chick embryos (CRC Press, 1987).

16

Smith, Ok. Ok. Early growth of neural plate, neural crest, and marsupial facial area. J. Anat. 199, 121-131 (2001).

17

Dillman, A.A. et al. Expression, splicing and enhancing of mRNA within the embryonic and grownup mouse cerebral cortex. Nat. Neurosci. 16, 499-506 (2013).

18

Glucksmann, A. Sexual dimorphism in mammals. Biol. Rev. Camb. Philos. Soc. 49, 423-475 (1974).

19

Feng, C.W., Bowles, J. & Koopman, P. Management of entry of mammalian germ cells into meiosis. Mol. Cell. Endocrinol. 382, 488-497 (2014).

20

Soumillon, M. et al. Cell supply and excessive complexity mechanisms of transcriptome within the mammalian testis. Cell Rep. three, 2179-2190 (2013).

21

Ungewitter, E.Ok. & Yao, H.H. Find out how to make a gonad: mobile mechanisms governing the formation of the testes and ovaries. Intercourse Dev. 7, 7-20 (2013).

22

Roux, J. & Robinson-Rechavi, M. Developmental Constraints on the Evolution of the Vertebrate Genome. PLoS Genet. four, e1000311 (2008).

23

Kalinka, A.T. et al. The divergence of gene expression recapitulates the hourglass growth mannequin. Nature 468, 811-814 (2010).

24

Hu, H. et al. Evolution of vertebrates below stress by pleiotropic genes. Nat. College. Evol. 1, 1722-1730 (2017).

25

Hazkani-Covo, E., Wool, D. & Graur, D. In Search of the Phylotypic Stage of Vertebrates: Molecular Examination of the Creating Hourglass Mannequin and von Baer's Third Regulation. J. Exp. Zool. B Mol. Dev. Evol. 304B, 150-158 (2005).

26

Garfield, D. A. and Wray, G. A. Comparative Embryology With out Microscope: Utilizing Genomic Approaches to Understanding the Evolution of Improvement. J. Biol. eight, 65 (2009).

27

Koscielny, G. et al. The Worldwide Consortium for Mouse Phenotyping Internet Portal, a unified entry level for knockout mice and related phenotyping information. Nucleic Acids Res. 42, D802 to D809 (2014).

28

Kosiol, C. et al. Optimistic choice patterns in six mammalian genomes. PLoS Genet. four, e1000144 (2008).

29

Kaessmann, H. Origins, evolution and phenotypic influence of latest genes. Genome Res. 20, 1313-1326 (2010).

30

Stern, D. L. Evolutionary biology of growth and drawback of variation. Evolution 54, 1079-1091 (2000).

31.

Carroll, S. B. Evolution at two ranges: on genes and type. PLoS Biol. three, e245 (2005).

32

Duret, L. & Mouchiroud, D. Determinants of substitution charges in mammalian genes: the sample of expression impacts the depth of choice however not the speed of mutation. Mol. Biol. Evol. 17, 68-74 (2000).

33

Winter, E.E., Goodstadt, L. & Ponting, C.P. Excessive charges of secretion, evolution, and illness of proteins amongst tissue-specific genes. Genome Res. 14, 54-61 (2004).

34

Galis, F. & Metz, J. A. To check the vulnerability of the phylotypic stage: on modularity and evolutionary conservation. J. Exp. Zool. 291, 195-204 (2001).

35

Sears, Ok., Maier, J. A., Sadier, A., Sorensen, D. and City, D. J. Dedication of the developmental origins of mammalian member range. Genesis 56, e23079 (2018).

36

Plant, T.M., Ramaswamy, S., Simorangkir, D. & Marshall, G. R. Postnatal and pubertal growth of the Rhesus monkey testis (Macaca mulatta). Ann. NY Acad. Sci. 1061, 149-162 (2005).

37

Bruneau, B. G. Signaling and transcription networks within the growth and regeneration of the center. Harb Spring Spring. Perspective. Biol. 5, a008292 (2013).

38

Carelli, F.N., Liechti, A., Halbert, J., Warnefors, M. and Kaessmann, H. Reassignment of promoters and activators throughout mammalian evolution. Nat. Widespread. 9, 4066 (2018).

39

Marin, R. et al. Convergent origination of a dosing compensation mechanism just like that of Drosophila in a line of reptiles. Genome Res. 27, 1974-1987 (2017).

40

Wu, T. D. & Nacu, S. Fast and Tolerant SNP Detection of Advanced Variants and Splicing in Brief Reads. Bioinformatics 26, 873-881 (2010).

41

Anders, S., Pyl, P.T & Huber, W. HTSeqa Python framework for working with excessive throughput sequencing information. Bioinformatics 31, 166-169 (2015).

42

Robinson, M.D., McCarthy, D.J. & Smyth, G.Ok. edgeR: a bioconductive software program bundle for the evaluation of differential expression of digital gene expression information. Bioinformatics 26, 139-140 (2010).

43

Li, H. et al. The format of sequence / map alignment and SAMtools. Bioinformatics 25, 2078-2079 (2009).

44

Picard. http://broadinstitute.github.io/picard (2015).

45

Le, S., Josse, J. & Husson, F. FactomineR: an R bundle for multivariate evaluation. J. Stat. Softw. 25, 1-18 (2008).

46

R Core Workforce. A: A language and an atmosphere for statistical computing (2014).

47

Anavy, L. et al. BLIND order of programs of large-scale transcriptomic growth time. Improvement 141, 1161-1166 (2014).

48.

Love, M. I., Huber, W. and Anders, S. Reasonable estimate of fold change and dispersion for seq-RNA information with DESeq2. Genome Biol. 15, 550 (2014).

49

Quinlan, A.R. & Corridor, I.M. BEDTools: A versatile suite of utilities for evaluating genomic traits. Bioinformatics 26, 841-842 (2010).

50

Nueda, M.J., Tarazona, S. and Conesa, A. Subsequent maSigPro: replace of the maSigPro biSector bundle for the seq-RNA time collection. Bioinformatics 30, 2598-2602 (2014).

51.

Conesa, A., Nueda, M.J., Ferrer, A. and Talón, M. maSigPro: a technique for considerably figuring out differential expression profiles in microarray experiments over time. Bioinformatics 22, 1096-1102 (2006).

52

Zhang, H. M. et al. AnimalTFDB 2.zero: a useful resource for expression, prediction and practical examine of transcription components in animals. Nucleic Acids Res. 43, D76 to D81 (2015).

53

Giorgino, T. Calculation and visualization of dynamic time alignments in R: the bundle dtw. J. Stat. Softw. 31, p. 1-24 (2009).

54

Clancy, B., Darlington, R. B. and Finlay, B. L. Translation of growth time between mammalian species. Neuroscience 105, 7-17 (2001).

55.

Smith, Ok. Ok. Craniofacial growth in marsupial mammals: developmental origins of evolutionary change. Dev. Dyn. 235, 1181-1193 (2006).

56.

Futschik, M. E. & Carlisle, B. Versatile, noise-resistant grouping of temporal information on gene expression. J. Bioinform. Comput. Biol. three, 965-988 (2005).

57

Kumar, L. & E. Futschik, M. Mfuzz: a software program bundle for versatile clustering of microarray information. Bioinformation 2, 5-7 (2007).

58.

Eisenberg, E. & Levanon, E. Y. The genes of man, revisited. Genet Developments. 29, 569-574 (2013).

59

Domazet-Lošo, T. & Tautz, D. An age index of the transcriptome based mostly on phylogeny displays patterns of ontogenetic divergence. Nature 468, 815-818 (2010).

60.

Zhang, Y. E., Vibranovski, M.D., Landback, P., Swamp, G.A. and Lengthy, M. Chromosomal redistribution of predominantly male genes in mammalian evolution with two gene-gene X-ray gene-bursts. PLoS Biol. eight, e1000494 (2010).

61.

Yanai, I. et al. The mid-range genome transcription patterns reveal expression stage relationships within the human tissue specification. Bioinformatics 21, 650-659 (2005).

62

Hensman, J., Lawrence, N. D. & Rattray, M. Bayesian hierarchical modeling of the time collection of gene expression in replicates and clusters sampled irregularly. BMC Bioinformatics 14, 252 (2013).

63.

Hensman, J., Rattray, M. and Lawrence, N. D. Nonparametric speedy clustering of structured time collection. IEEE Trans. Anal mannequin. Mach. Intell. 37, 383-393 (2015).

64.

Hensman, J., Rattray, M. and Lawrence, N., speedy variational inference within the conjugate exponential household. In Proc. Proceedings of NIPS'12 25th Worldwide Convention on Neural Data Processing Methods Vol. 2, 2888-2866 (2014).

65.

Kumar, S., G. Stecher, Suleski, M. & Hedges, S. B. TimeTree: a useful resource for timelines, schedules, and instances of divergence. Mol. Biol. Evol. 34, 1812-1819 (2017).

66.

Vickaryous, M. Ok. & Corridor, B. Ok. Variety, evolution, growth and classification of human cell varieties, with explicit reference to cells derived from the neural crest. Biol. Rev. Camb. Philos. Soc. 81, 425-455 (2006).

67.

Wickham, H. ggplot2: Trendy Graphics for Knowledge Evaluation (Springer-Verlag, 2009).

68.

Auguie, B. gridExtra: Numerous capabilities for "grid" graphics. v.2.2.1 (2015).

69

Wickham, H. Transforming information with the transforming bundle. J. Stat. Softw. 21, 1-20 (2007).

70.

Wickham, H. The mix-application-combination technique for information evaluation. J. Stat. Softw. 40, 1-29 (2011).

71.

Kassambara, A. & Mundt, F. factoextra: Extract and think about the outcomes of multivariate information analyzes. v.1.zero.four (2017).

72.

Wang, J., Vasaikar, S., Shi, Z., Greer, M. and Zhang, B. WebGestalt 2017: a extra complete, highly effective, versatile and interactive toolkit for enrichment evaluation units of genes. Nucleic Acids Res. 45, W130 to W137 (2017).

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