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CNV DETECTION AND ASSOCIATION STUDIES IN THE BROWN SWISS CATTLE BREED
Get PDFSintesi – Italiano
Gli scopi, i materiali, i metodi usati, i risultati e le conclusioni dei tre studi sono organizzati in tre capitoli. La sintesi generale dei tre studi e quindi divisa in base a questi tre capitoli.
Capitolo 1
La determinazione dei “copy number variants” (CNV) è fondamentale per la valutazione dei tratti genomici in diverse specie in quanto rappresentano una fonte principale della variabilità genetica, influenzando l’espressione genica, la variabilità fenotipica, la adattabilità e la predisposizione all’insorgenza di malattie. Lo scopo di questo studio è stato quello di ottenere una mappa genomica di CNV utilizzando i dati ottenuti dall’Illumina Bovine SNP50 BeadChip di 651 tori di razza Bruna Italiana. Per l’identificazione dei CNV e delle regioni CNV (CNVR) sono stati usati i software PennCNV e SVS7 (Golden Helix).
Sono stati identificati un totale di 5,099 e 1,289 CNVs con i software PennCNV ed SVS7 rispettivamente. Questi CNV sono stati raggruppati a livello di popolazione in 1,101 (220 delezioni, 774 duplicazioni e 107 complex) e 277 (185 delezioni, 56 duplicazioni e 36 complex) CNVR. Dieci dei CNVR selezionati sono stati validati sperimentalmente attraverso qPCR. La GO e la pathway analysis effettuate hanno identificato i geni (corretti per la false discovery rate) localizzati nelle CNVR e correlati a diversi processi biologici, componenti cellulari, funzioni metaboliche e vie metaboliche. Tra questi, sono stati identificati i geni FCGR2B, PPARalpha, KATNAL1, DNAJC15, PTK2, TG, STAT family, NPM1, GATA2, LMF1 e ECHS1, già noti in letteratura, per la loro associazione con diversi caratteri quantitativi nei bovinia. Sebbene ci sia una variabilità nell’identificazione dei CNVR attraverso l’utilizzo di diversi metodi e piattaforme, questo studio ha permesso l’identificazione dei CNVR nella Bruna Italiana, sovrapponendo quelli già identificati in altre razze e identificandone dei nuovi, producendo quindi nuove conoscenze per gli studi di associazione con caratteri quantitativi di interesse nei bovini.
Capitolo 2
Scoprire variazioni genetiche come i Copy Number Variants (CNVs) nei bovini, fornisce l’opportinità di studiare la loro associazione con caratteri quantitativi. I CNVs sono sequenze di DNA di lunghezza 50 bp fino a diverse Mb, che possono variare in numero di copie rispetto ad un genoma di riferimento. Lo scopo di questo studio è stato quello di identificare i CNVs in 1,410 campioni di razza Bruna Svizzera usando informazioni derivanti dall’ Illumina Bovine HD SNP chip, che include 777,962 SNPs. Dopo uno stringente controllo di qualità, i CNVs sono stati identificati con i software Golden Helix SVS 8.3.1 (SVS) e PennCNV e sono stati raggruppati in regioni CNV (CNVRs) a livello di popolazione (i.e. CNVs sovrapposti) utilizzando il software BEDTools. I CNVR comuni ai due software sono stati definiti come regioni consensus. I geni all’interno delle CNVR consensus sono stati annotati con un’analisi GO utilizzando DAVID Bioinformatics Resources 6.7. Per poter validare i risultati, sono state eseguite PCR quantitative su 15 CNVR selezionate.
Con il software SVS sono stati identificati 25,030 CNVs successivamente raggruppati in 398 CNVR, che comprendevano 30 duplicazioni, 344 delezioni e 24 complex CNVR (che contenevano sia duplicazioni che delezioni) coprendo il 3.92% del genoma bovino. Il software PennCNV ha identificato 62,341 CNV, corrispondenti a 5,578 CNVRs che comprendevano 2,638 duplicazioni, 2,404 delezioni e 537 complex CNVR, coprendo il 7.68% del genoma bovino. La lunghezza di queste CNVR variava da 1,244 bp a 1,381,355 bp. Sono state trovate 563 CNVR consensus che coprivano il 2.29% del UMD 3.1 bovine genome assembly. Di queste, 24 erano duplicazioni, 300 erano delezioni e 239 erano CNVR complex. Un totale di 775 official gene IDs sono stati annotati nelle CNVR consensus. Tra i 537 geni con informazioni funzionali, la GO e la pathway analysis è stata riportata per quelli che clusterizzavano con un p-value < 0.05. Le PCR quantitative hanno validato con successo 14 delle 15 CNVR selezionate.
Il risultato di questo studio è una prima analisi genomica integrale della razza Bruna Svizzera basata sull’Illumina Bovine HD SNP chip su un numero cosi grande di animali che arricchisce la mappa CNV nel genoma bovino. I risultati forniscono inoltre informazioni preziose per successivi studi sui CNV. Infine, i risultati della mappa CNVR sono informativi per i caratteri funzionali, produttivi e sanitari considerati nei programmi di selezione nella razza Bruna Svizzera.
Capitolo 3
I Copy Number Variations (CNV) possono essere usati negli studi di associazione per rivelare la base genetica della variazione fenotipica di caratteri quantitativi. I CNV sono sequenze di DNA di 50 bp fino a qualche Mb, che possono variare in numero di copie rispetto ad un genoma di riferimento. Fino ad oggi, nessuno studio di associazione genome-wide (GWAS) con i CNV e caratteri quantitavivi è stato descritto in una popolazione cosi ampia (cioè di 1,116 campioni) della razza bovina Bruna Svizzera. Lo scopo di questo studio era quello di eseguire delle GWAS utilizzando i CNV precedentemente mappati, con caratteri funzionali, produttivi e sanitari al fine di valutare il loro impatto sull’allevamento e sulla selezione. Gli studi di associazione con i CNV sono stati effettuati con il software Golden Helix SVS 8.4.4 utilizzando un correlation-trend test model. I geni all’interno dei CNV significativamente associati per ogni carattere sono stati annotati con un’analisi GO usando DAVID Bioinformatics Resources 6.7. Sono stati identificati 56 CNV significativamente associati con uno o più degli otto caratteri valutati. I segnali di associazione più forti erano dati da tre CNV sul cromosoma 12 per il carattere grasso. I CNV associati si sovrappongono con 23 geni diversi, annotati sul Bos taurus genome assembly (UMD3.1).Abstract – English
The aims, material and methods, results and conclusions of the three studies are organized in three different chapters. The general abstract is therefore divided according to these chapters.
Chapter 1
The determination of copy number variation (CNV) is very important for the evaluation of genomic traits in several species because they are a major source for the genetic variation, influencing gene expression, phenotypic variation, adaptation and the development of diseases. The aim of this study was to obtain a CNV genome map using the Illumina Bovine SNP50 BeadChip data of 651 bulls of the Italian Brown Swiss breed. PennCNV and SVS7 (Golden Helix) software were used for the detection of the CNVs and Copy Number Variation Regions (CNVRs). A total of 5,099 and 1,289 CNVs were identified with PennCNV and SVS7 software, respectively. These were grouped at the population level into 1101 (220losses, 774 gains, 107 complex) and 277 (185losses, 56 gains and 36 complex) CNVRs. Ten of the selected CNVRs were experimentally validated with a qPCR experiment. The GO and pathway analyses were conducted and they identified genes (false discovery rate corrected) in the CNVR related to biological processes, cellular component, molecular function and metabolic pathways. Among those, we found the FCGR2B, PPARalpha, KATNAL1, DNAJC15, PTK2, TG, STAT family, NPM1, GATA2, LMF1, ECHS1 genes, already known in literature because of their association with various traits in cattle. Although there is variability in the CNVRs detection across methods and platforms, this study allowed the identification of CNVRs in Italian Brown Swiss, overlapping those already detected in other breeds and finding additional ones, thus producing new knowledge for association studies with traits of interest in cattle.
Chapter 2
Detecting genetic variation such as Copy Number Variants (CNVs) in cattle provides the opportunity to study their association with quantitative traits. CNVs are DNA sequences of 50 bp up to several Mb long, which can vary in copy number in comparison with a reference genome. The aim of this study was to investigate CNVs in 1,410 samples of the Brown Swiss cattle breed using Illumina Bovine HD SNP chip information, which includes 777,962 SNPs. After stringent quality control, CNVs were called with the Golden Helix SVS 8.3.1 (SVS) and PennCNV software and were summarized to CNV regions (CNVRs) at a population level (i.e. overlapping CNVs), using BEDTools. Additionally, common CNVRs between the two software were set as consensus regions. Genes within consensus CNVRs were annotated with a GO analysis using the DAVID Bioinformatics Resources 6.7. In order to validate these results, quantitative PCRs were executed on 15 selected CNVRs.
The SVS software identified 25,030 CNVs summarized to 398 CNVRs, which comprised 30 gains, 344 losses and 24 complex CNVRs (i.e. containing both losses and gains), covering 3.92% of the bovine genome. The PennCNV software identified 6,2341 CNVs summarized to 5,578 CNVRs, which comprised 2,638 gains, 2,404 losses and 537 complex CNVRs, covering 7.68% of the bovine genome. The length of these CNVRs ranged from 1,244 bp to 1,381,355 bp. A total of 563 consensus CNVRs were found covering 2.29 % of the UMD 3.1 bovine genome assembly. Of these, 24 were gains, 300 were losses and 239 were complex CNVRs. A total of 775 official gene IDs were annotated in the consensus CNVRs. Among the 537 genes with functional information, the GO and pathway analysis was reported for those who clustered with a p-value < 0.05. The quantitative PCRs successfully validated 14 (93.33%) of the selected CNVRs.
The result of this study is the first comprehensive genomic analysis of the Brown Swiss breed based on the Illumina Bovine HD SNP chip on such a large number of animals that enriches the CNV map in the bovine genome. These findings also provide valuable information for further CNV studies. Finally, the results of the CNVR map delivers new information for functional, health and productive traits considered in selection programs of the Brown Swiss breed.
Chapter 3
Copy Number Variation (CNV) can be used in association studies to disclose genetic basis of quantitative traits phenotypic variation. CNVs are DNA sequences of 50 bp up to several Mb long, which can vary in number of copies in comparison with a reference genome. Up to date, no genome-wide association study (GWAS) with CNVs and quantitative traits in such a large Brown Swiss population (i.e. with 1,116 samples) has been described. The purpose of this study was to perform a GWAS using CNVs with functional, health and productive traits and to asses the impact on farming and breeding practices. The CNV – association studies were performed with the Golden Helix SVS 8.4.4 software using a correlation-trend test model. Genes within significant associated CNVs for each trait were annotated with a GO analysis using the DAVID Bioinformatics Resources 6.7. A total of 56 CNVs were significantly associated with one or more of the eight evaluated traits. The greatest association signals were given by three CNVs on chromosome 12 for the fat yield trait and on BTA23 for udder traits. The associated CNVs overlap with 23 different genes annotated on the Bos taurus genome assembly (UMD3.1)
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