Classic (extensive) orchards in Croatia

Hrvatska ima vrlo povoljne pomoekološke uvjete za uzgoj voćaka. Tradicija uzgoja voćaka duga je više stoljeća, a voćke su se uzgajale na gotovo svim seoskim gospodarstvima, te dijelom i u urbanim sredinama. Intenzivan uzgoj voćaka počeo se značajnije širiti polovinom prošlog stoljeća. Intenzivan uzgoj je u određenoj mjeri potisnuo interes za klasičnim, ali se postojeći voćnjaci visokostablašica uglavnom nisu krčili već su u većoj mjeri bili zapušteni. U novije vrijeme klasični voćnjaci ponovno postaju aktualni. Njihova uloga očituje se u očuvanju genetske raznolikosti, kako voćnih vrsta, tako i biljaka općenito. Posebna vrijednost tih voćnjaka očituje se u očuvanju tipičnog krajobraza ruralnih sredina, te kao osnove sustava organske proizvodnje voća i voćnih prerađevina. U ukupnim površinama voćnjaka u Hrvatskoj, intenzivni (plantažni) voćnjaci zauzimaju 24%, a preostali dio od oko 21.800 ha otpada na klasične voćnjake. U pojedinim županijama udio klasičnih voćnjaka je značajno veći, pa primjerice u Krapinsko-zagorskoj, Karlovačkoj, Varaždinskoj, Primorsko-goranskoj i Ličko-senjskoj županiji klasični voćnjaci visokostablašica zauzimaju više od 95% površina pod voćem. Među voćnim vrstama najviše se na klasičan način uzgajaju trešnje (92,0%), zatim slijede: orah (90,0%), šljiva (89,9%), marelica (87,2%), kruška (75,4%), višnja (73,4%), dok je značajno niži udio breskve i nektarine (53,3%), i najniži jabuke (43,2%).Croatia has very favourable ecological conditions for growing fruit trees. The tradition of growing fruit trees has a long history, and fruit was cultivated at almost all farms, and partly in the urban areas. Intensive cultivation of fruit trees began to expand significantly from the middle of last century. Intensive farming to some extent pushed interest for the classic growing system and the existing classic orchards were generally not managed properly and were largely neglected. In recent years, the classic orchards made again become current. Their role is reflected in the preservation of genetic diversity, both fruit species, and plants in general. The special value of these orchards is reflected in the preservation of the typical landscape of rural areas, as well as the basics of organic production of fruits and fruit products. In respect of the total acreage of orchards in Croatia, intensive (plantation) orchards occupy 24%, and the remaining part of about 21 800 ha are traditional orchards. In some counties, the share of traditional orchards is significantly higher, so for example in Krapinsko-zagorska, Karlovačka, Varaždinska, Primorsko-goranska and Ličko-eenjska, where classic orchards occupy more than 95% of the area under the fruit. Among the fruit species mostly traditionally grown are cherries (92.0%), followed by: nut (90.0%), plums (89.9%), apricots (87.2%), pears (75.4%), cherries (73.4%), while a significantly lower share is that of peaches and nectarines (53.3%), and the lowest are apples (43.2%)

Comparative cytogenomics

TC Hsu (17 April 1917 – 9 July 2003) has been called “the father of mammalian cytogenetics”. In 1952, he developed the hypotonic solution spreading method for mammalian chromosomes following a fortunate error in making up a solution, paving the way for Tjio and Levan to report the human chromosome number as 2n = 46 in 1956. TC’s career started in China, as an insect geneticist, before settling in the US, mostly working in Texas, and moving to the exciting world of mammalian cytogenetics. He established one of the first “Frozen Zoos” with cultures of animals from A to Z (aardvark to zebra), and used numerous species to study chromosome biology and comparative evolution. At the end of his lengthy career, he was using in situ hybridization to understand the nature of non-telomeric heterochromatin and organization of chromosomes. Now, with the new methods available including high-resolution in situ hybridization, chromosome sorting, high volume sequencing and bioinformatics, we can learn about the evolution of chromosomes, comparing and contrasting diverse genotypes, species, families and even the kingdoms of plants, fungi and animals, to build a picture of key events in evolution. Many of the same changes may be seen in abnormal karyotypes and disease, normally deleterious. However, the occasional chromosomal or whole-genome changes, beyond those from mutation and recombination, can provide the novel variation leading to evolutionary success, arguably over evolutionary time giving rise to all modern lineages. The field of comparative cytogenomics is developing rapidly (see www.cytogenomics.org and www.molcyt.com) and able to show how species have evolved in the past and letting us consider paths for their evolutionary future

Deterministic Model: Robustness Analysis of the Period and Amplitude of the Internal cAMP Oscillations with Respect to Perturbations in the Model Parameters and Initial Conditions

<p>The first row shows the distribution in the period of the deterministic model for one cell with 5%, 10%, and 20% perturbations, and the second row shows the amplitude distribution. The peak bar at 20 min for the period distributions represents the number of cells that are not oscillating. The proportion of cells that are not oscillating increases from 2% to 25% as the size of the perturbation increases. The distributions of the amplitudes also show a similar tendency, i.e., the mean value decreases and the standard deviation increases as the magnitude of the perturbation increases. Each plot is the result of 100 simulations for different random samples of the model parameters, the cell volume, and initial conditions using a uniform distribution about the nominal values.</p

Extended Stochastic Model (Five Cells): Robustness Analysis of the Period and Amplitude of the Internal cAMP Oscillations with Respect to Perturbations in the Model Parameters and Initial Conditions

<p>The first row shows the period distribution of the stochastic model for three cells with 5%, 10%, and 20% perturbations, and the second row shows the amplitude distribution. The peak bar at 20 min for the period distributions represents the total number of cells that are not oscillating. The proportion of non-oscillating cells increases from 0% to 12% as the size of the perturbation increases, which is smaller than the proportion seen in either the deterministic or stochastic single cell models. The distributions of the amplitudes show a similar tendency, i.e., the mean decreases and the standard deviation increases as the magnitude of the perturbation increases. Each plot is the result of 100 simulations for different random samples of the model parameters, the cell volume, and initial conditions using a uniform distribution about the nominal values.</p

<i>Dictyostelium</i> cAMP Oscillations

<div><p>(A) The model of [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0030218#pcbi-0030218-b005" target="_blank">5</a>] for the network underlying cAMP oscillations in <i>Dictyostelium</i>. The nominal parameter values for the model are taken from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0030218#pcbi-0030218-b006" target="_blank">6</a>,<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0030218#pcbi-0030218-b009" target="_blank">9</a>] and are given by: <i>k</i>₁ = 2.0 min⁻¹, <i>k</i>₂ = 0.9 <i>μ</i>M⁻¹ min⁻¹, <i>k</i>₃ = 2.5 min⁻¹, <i>k</i>₄ = 1.5 min⁻¹, <i>k</i>₅ = 0.6 min⁻¹, <i>k</i>₆ = 0.8 <i>μ</i>M⁻¹ min⁻¹, <i>k</i>₇ = 1.0 <i>μ</i>M min⁻¹, <i>k</i>₈ = 1.3 <i>μ</i>M⁻¹ min⁻¹ , <i>k</i>₉ = 0.3 min⁻¹, <i>k</i>₁₀ = 0.8 <i>μ</i>M⁻¹ min⁻¹, <i>k</i>₁₁ = 0.7 min⁻¹, <i>k</i>₁₂ = 4.9 min⁻¹, <i>k</i>₁₃ = 23.0 min⁻¹, and <i>k</i>₁₄ = 4.5 min⁻¹. A perturbation of magnitude 2% in the model parameters which causes the oscillations to cease is given by [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0030218#pcbi-0030218-b010" target="_blank">10</a>]: <i>k</i>₁ = 1.9600, <i>k</i>₂ = 0.8820, <i>k</i>₃ = 2.5500, <i>k</i>₄ = 1.5300, <i>k</i>₅ = 0.5880, <i>k</i>₆ = 0.8160, <i>k</i>₇ = 1.0200, <i>k</i>₈ = 1.2740, <i>k</i>₉ = 0.3060, <i>k</i>₁₀ = 0.8160, <i>k</i>₁₁ = 0.6860, <i>k</i>₁₂ = 4.9980, <i>k</i>₁₃ = 22.5400, and <i>k</i>₁₄ = 4.5900.</p><p>(B) With the above perturbation in the parameter values, the deterministic model stops oscillating. The stochastic model, on the other hand, continues to exhibit stable and robust oscillations.</p></div

Synchronisation Is Realised through Diffusion of External cAMP

<div><p>(A) Shows the synchronisation mechanism for the case of three interacting <i>Dictyostelium</i> cells. Each cell has a different set of kinetic constants. <i>kⁱ_j</i> is the <i>k_j</i> in the Laub-Loomis model for the <i>i</i>-th cell.</p><p>(B) For twenty individual cells with no interaction and a 10% level of variation in the initial conditions and the kinetic constants between the cells, the internal cAMP oscillations are completely out of phase with each other.</p><p>(C) For the extended model incorporating the diffusion mechanism, with the same level of variation between the cells, the oscillations are synchronised in less than 10 min.</p><p>(D) Even for a 20% level of variation between the cells, the extended model shows highly synchronised oscillations.</p></div

Deterministic and Stochastic Simulations for the Same Worst Case Parameter Combinations Are Performed

<p>The numbers of molecules are sampled with a 0.1 s interval for 10 h, and the distribution of each molecular species is compared. To avoid influences from the initial transient response, only the samples obtained after 5 h are considered when plotting the distributions. The inset of (E) is the distribution for the external cAMP. The noise effect is clearly significant in terms of generating oscillations.</p

Extended Stochastic Model (Ten Cells): Robustness Analysis of the Period and Amplitude of the Internal cAMP Oscillations with Respect to Perturbations in the Model Parameters and Initial Conditions

<p>The first row shows the period distribution of the stochastic model for three cells with 5%, 10%, and 20% perturbations, and the second row shows the amplitude distribution. The peak bar at 20 min for the period distributions represents the total number of cells, which are not oscillating. The proportion of non-oscillating cells increases from 0% to 5% as the size of the perturbation increases, which is much smaller than the proportion seen in all other cases. The distributions of the amplitudes show a similar tendency, i.e., the mean decreases and the standard deviation increases as the magnitude of the perturbation increases. Each plot is the result of 100 simulations for different random samples of the model parameters, the cell volume, and initial conditions using a uniform distribution about the nominal values.</p

A radar-plot comparing features of the plastomes of 21 accessions of Asteraceae, showing, from inside to out, sizes of major plastome regions, GC content, genome size and number of different types of genes.

<p>A radar-plot comparing features of the plastomes of 21 accessions of Asteraceae, showing, from inside to out, sizes of major plastome regions, GC content, genome size and number of different types of genes.</p

Map of the plastome of <i>Taraxacum amplum</i> (A978).

<p>Genes are shown inside or outside the circle to indicate clockwise or counterclockwise transcription direction respectively. The Inverted Repeat (IR, 24,431bp) is indicated by a thicker line for IR1 and IR2. GC content is show in the inner blue graph. Small Single Copy (SSC) and long single copy (LSC) regions are indicated, and the inverted regions (Inv1 and Inv2) within LSC relative to other species are shown as orange arcs. Short tandem repeats (microsatellites and minisatellites) are indicated by blue dots, palindromes by red dots, forward repeats by green dots and reverse repeats by black dots.</p