20.500.12556/RUL-127009 Multiscale modelling and systems analysis of potato spatio-temporal immune signalling doctoral dissertation Modeliranje in sistemska analiza prostorsko-časovne imunske signalizacije krompirja na več ravneh doktorska disertacija As sessile organisms, crops interact directly and indirectly with multiple herbivores and pathogens at daily basis, including pests that significantly reduce yields, however, dynamics of crop-pest interactions is relatively poorly understood. One of the world's most important vegetable crops is potato, and can be severely affected by various pathogens. To facilitate the progress in potato research, we focused on methods development and statistical analyses for precise characterisation of spatial and temporal immune signalling pathway dynamics in distinct potato cultivars, at different biological levels. To get a proper representation of genetic information within domesticated genotypes, synergy between bioinformatics, biostatistics, and network analyses approaches was established. Foremost, the potato pan-transcriptome was constructed. DiNAR, a Shiny application, was developed to gain deeper insight in complex phenomena of plant defence, discovering underlying molecular mechanisms and complex patterns. Spatio-temporal gene expression analyses and data visualisation, together with the usage of the graph theory for the modelling of large biological systems and plant defence responses, helped to identify cross-talk mechanisms between different hormone signalling, as well novel and key components relevant to the system. All developed methods and approaches can be easily improved by introduction of new data and can be used for any other species as well. Rastline so vsak dan v interakciji z rastlinojednimi živalmi in patogeni, vključno s škodljivci, ki znatno zmanjšujejo doprinose pridelka. Dinamika medsebojnega vpliva rastlin in škodljivcev je razmeroma slabo raziskana. Na krompir, enega od najpomembnejših poljščin na svetu, močno vplivajo različni patogeni. V doktorskem delu smo se osredotočili na razvoj metod statistične analize za natančnejšo karakterizacijo prostorske in časovne dinamike imunske signalizacije pri različnih sortah krompirja na različnih bioloških ravneh. Za predstavitev genskih informacij znotraj udomačenih genotipov, smo uporabili pristope bioinformatike, biostatistike in analize omrežij. Najprej smo začeli z izgradnjo krompirjevega pan-transkriptoma. Nato smo razvili DiNAR, Shiny aplikacijo, ki nam je omogočila globlji vpogled v zapletene obrambne odgovore rastline, odkrivanje osnovnih molekularnih mehanizmov in kompleksnih vzorcev. Prostorsko-časovne analize ekspresije genov in vizualizacija podatkov, skupaj z uporabo teorije grafov za modeliranje velikih bioloških sistemov, so pomagale prepoznati mehanizme navzkrižnega pogovora med različnimi rastlinskimi hormoni, ter nove ključne komponente pomembne za sistem. Vse razvite metode in pristope je mogoče enostavno nadgraditi z novimi podatki in jih tako uporabiti tudi za druge rastlinske vrste. pan-transcriptome differential networks multi-omics time-series spatial response multi-way interactions plant immune signalling pan-transkriptom diferencialna omrežja omike časovne vrste prostorski odziv večtrofične interakcije imunska signalizacija rastlin true false false Angleški jezik Slovenski jezik Doktorsko delo/naloga 2021-05-13 07:15:10 2021-05-13 07:15:30 2022-09-06 03:49:20 0000-00-00 00:00:00 2021 0 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 2210 63531267 49.pdf 49.pdf 1 E4806852E69A7D164D56BF9FC190E858 edf78e77c6c9445ca25afaa0719c23a63e4eba1107871909fc2c6fbf4d81dd9a 3588680d-b3aa-11eb-a523-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=143206 Biotehniška fakulteta 0 0 0