Ali Pirani
Affymetrix
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Publication
Featured researches published by Ali Pirani.
BMC Genomics | 2013
Andreas Kranis; Almas Gheyas; Clarissa Boschiero; Frances Turner; Le Yu; Sarah Smith; Richard Talbot; Ali Pirani; Fiona Brew; Peter K. Kaiser; Paul Hocking; Mark Fife; Nigel Salmon; Janet E. Fulton; Tim M. Strom; G. Haberer; Steffen Weigend; Rudolf Preisinger; Mahmood Gholami; Saber Qanbari; Henner Simianer; Kellie Watson; John Woolliams; David W. Burt
BackgroundHigh density (HD) SNP genotyping arrays are an important tool for genetic analyses of animals and plants. Although the chicken is one of the most important farm animals, no HD array is yet available for high resolution genetic analysis of this species.ResultsWe report here the development of a 600 K Affymetrix® Axiom® HD genotyping array designed using SNPs segregating in a wide variety of chicken populations. In order to generate a large catalogue of segregating SNPs, we re-sequenced 243 chickens from 24 chicken lines derived from diverse sources (experimental, commercial broiler and layer lines) by pooling 10–15 samples within each line. About 139 million (M) putative SNPs were detected by mapping sequence reads to the new reference genome (Gallus_gallus_4.0) of which ~78 M appeared to be segregating in different lines. Using criteria such as high SNP-quality score, acceptable design scores predicting high conversion performance in the final array and uniformity of distribution across the genome, we selected ~1.8 M SNPs for validation through genotyping on an independent set of samples (n = 282). About 64% of the SNPs were polymorphic with high call rates (>98%), good cluster separation and stable Mendelian inheritance. Polymorphic SNPs were further analysed for their population characteristics and genomic effects. SNPs with extreme breach of Hardy-Weinberg equilibrium (P < 0.00001) were excluded from the panel. The final array, designed on the basis of these analyses, consists of 580,954 SNPs and includes 21,534 coding variants. SNPs were selected to achieve an essentially uniform distribution based on genetic map distance for both broiler and layer lines. Due to a lower extent of LD in broilers compared to layers, as reported in previous studies, the ratio of broiler and layer SNPs in the array was kept as 3:2. The final panel was shown to genotype a wide range of samples including broilers and layers with over 100 K to 450 K informative SNPs per line. A principal component analysis was used to demonstrate the ability of the array to detect the expected population structure which is an important pre-investigation step for many genome-wide analyses.ConclusionsThis Affymetrix® Axiom® array is the first SNP genotyping array for chicken that has been made commercially available to the public as a product. This array is expected to find widespread usage both in research and commercial application such as in genomic selection, genome-wide association studies, selection signature analyses, fine mapping of QTLs and detection of copy number variants.
Plant Biotechnology Journal | 2016
Mark O. Winfield; Alexandra M. Allen; Amanda J. Burridge; Gary L. A. Barker; Harriet R. Benbow; Paul A. Wilkinson; Jane A. Coghill; Christy Waterfall; Alessandro Davassi; Geoff Scopes; Ali Pirani; Teresa Webster; Fiona Brew; Claire Bloor; Julie King; Claire West; Simon Griffiths; I. P. King; Alison R. Bentley; Keith J. Edwards
Summary In wheat, a lack of genetic diversity between breeding lines has been recognized as a significant block to future yield increases. Species belonging to bread wheats secondary and tertiary gene pools harbour a much greater level of genetic variability, and are an important source of genes to broaden its genetic base. Introgression of novel genes from progenitors and related species has been widely employed to improve the agronomic characteristics of hexaploid wheat, but this approach has been hampered by a lack of markers that can be used to track introduced chromosome segments. Here, we describe the identification of a large number of single nucleotide polymorphisms that can be used to genotype hexaploid wheat and to identify and track introgressions from a variety of sources. We have validated these markers using an ultra‐high‐density Axiom® genotyping array to characterize a range of diploid, tetraploid and hexaploid wheat accessions and wheat relatives. To facilitate the use of these, both the markers and the associated sequence and genotype information have been made available through an interactive web site.
Plant Journal | 2015
Yun-Gyeong Lee; Namhee Jeong; Ji Hong Kim; Kwanghee Lee; Kil Hyun Kim; Ali Pirani; Bo-Keun Ha; Sung-Taeg Kang; Beom-Seok Park; Jung-Kyung Moon; Namshin Kim; Soon-Chun Jeong
Cultivated soybean (Glycine max) suffers from a narrow germplasm relative to other crop species, probably because of under-use of wild soybean (Glycine soja) as a breeding resource. Use of a single nucleotide polymorphism (SNP) genotyping array is a promising method for dissecting cultivated and wild germplasms to identify important adaptive genes through high-density genetic mapping and genome-wide association studies. Here we describe a large soybean SNP array for use in diversity analyses, linkage mapping and genome-wide association analyses. More than four million high-quality SNPs identified from high-depth genome re-sequencing of 16 soybean accessions and low-depth genome re-sequencing of 31 soybean accessions were used to select 180,961 SNPs for creation of the Axiom(®) SoyaSNP array. Validation analysis for a set of 222 diverse soybean lines showed that 170,223 markers were of good quality for genotyping. Phylogenetic and allele frequency analyses of the validation set data indicated that accessions showing an intermediate morphology between cultivated and wild soybeans collected in Korea were natural hybrids. More than 90 unanchored scaffolds in the current soybean reference sequence were assigned to chromosomes using this array. Finally, dense average spacing and preferential distribution of the SNPs in gene-rich chromosomal regions suggest that this array may be suitable for genome-wide association studies of soybean germplasm. Taken together, these results suggest that use of this array may be a powerful method for soybean genetic analyses relating to many aspects of soybean breeding.
BMC Genomics | 2014
Ezequiel L. Nicolazzi; Matteo Picciolini; Francesco Strozzi; Robert D. Schnabel; Cindy Lawley; Ali Pirani; Fiona Brew; Alessandra Stella
BackgroundCurrently, six commercial whole-genome SNP chips are available for cattle genotyping, produced by two different genotyping platforms. Technical issues need to be addressed to combine data that originates from the different platforms, or different versions of the same array generated by the manufacturer. For example: i) genome coordinates for SNPs may refer to different genome assemblies; ii) reference genome sequences are updated over time changing the positions, or even removing sequences which contain SNPs; iii) not all commercial SNP ID’s are searchable within public databases; iv) SNPs can be coded using different formats and referencing different strands (e.g. A/B or A/C/T/G alleles, referencing forward/reverse, top/bottom or plus/minus strand); v) Due to new information being discovered, higher density chips do not necessarily include all the SNPs present in the lower density chips; and, vi) SNP IDs may not be consistent across chips and platforms. Most researchers and breed associations manage SNP data in real-time and thus require tools to standardise data in a user-friendly manner.DescriptionHere we present SNPchiMp, a MySQL database linked to an open access web-based interface. Features of this interface include, but are not limited to, the following functions: 1) referencing the SNP mapping information to the latest genome assembly, 2) extraction of information contained in dbSNP for SNPs present in all commercially available bovine chips, and 3) identification of SNPs in common between two or more bovine chips (e.g. for SNP imputation from lower to higher density). In addition, SNPchiMp can retrieve this information on subsets of SNPs, accessing such data either via physical position on a supported assembly, or by a list of SNP IDs, rs or ss identifiers.ConclusionsThis tool combines many different sources of information, that otherwise are time consuming to obtain and difficult to integrate. The SNPchiMp not only provides the information in a user-friendly format, but also enables researchers to perform a large number of operations with a few clicks of the mouse. This significantly reduces the time needed to execute the large number of operations required to manage SNP data.
BMC Genomics | 2015
Ezequiel L. Nicolazzi; Andrea Caprera; Nelson Nazzicari; Paolo Cozzi; Francesco Strozzi; Cindy Lawley; Ali Pirani; Chandrasen Soans; Fiona Brew; Hossein Jorjani; Gary Evans; Barry Simpson; Gwenola Tosser-Klopp; Rudiger Brauning; John L. Williams; Alessandra Stella
BackgroundIn recent years, the use of genomic information in livestock species for genetic improvement, association studies and many other fields has become routine. In order to accommodate different market requirements in terms of genotyping cost, manufacturers of single nucleotide polymorphism (SNP) arrays, private companies and international consortia have developed a large number of arrays with different content and different SNP density. The number of currently available SNP arrays differs among species: ranging from one for goats to more than ten for cattle, and the number of arrays available is increasing rapidly. However, there is limited or no effort to standardize and integrate array- specific (e.g. SNP IDs, allele coding) and species-specific (i.e. past and current assemblies) SNP information.ResultsHere we present SNPchiMp v.3, a solution to these issues for the six major livestock species (cow, pig, horse, sheep, goat and chicken). Original data was collected directly from SNP array producers and specific international genome consortia, and stored in a MySQL database. The database was then linked to an open-access web tool and to public databases. SNPchiMp v.3 ensures fast access to the database (retrieving within/across SNP array data) and the possibility of annotating SNP array data in a user-friendly fashion.ConclusionsThis platform allows easy integration and standardization, and it is aimed at both industry and research. It also enables users to easily link the information available from the array producer with data in public databases, without the need of additional bioinformatics tools or pipelines. In recognition of the open-access use of Ensembl resources, SNPchiMp v.3 was officially credited as an Ensembl E!mpowered tool. Availability at http://bioinformatics.tecnoparco.org/SNPchimp.
Plant Biotechnology Journal | 2017
Alexandra M. Allen; Mark O. Winfield; Amanda J. Burridge; Rowena C Downie; Harriet L Benbow; Gary L. A. Barker; Paul A. Wilkinson; Jane A. Coghill; Christy Waterfall; Alessandro Davassi; Geoff Scopes; Ali Pirani; Teresa Webster; Fiona Brew; Claire Bloor; Simon Griffiths; Alison R. Bentley; Mark Alda; Peter Jack; Andrew Phillips; Keith J. Edwards
Summary Targeted selection and inbreeding have resulted in a lack of genetic diversity in elite hexaploid bread wheat accessions. Reduced diversity can be a limiting factor in the breeding of high yielding varieties and crucially can mean reduced resilience in the face of changing climate and resource pressures. Recent technological advances have enabled the development of molecular markers for use in the assessment and utilization of genetic diversity in hexaploid wheat. Starting with a large collection of 819 571 previously characterized wheat markers, here we describe the identification of 35 143 single nucleotide polymorphism‐based markers, which are highly suited to the genotyping of elite hexaploid wheat accessions. To assess their suitability, the markers have been validated using a commercial high‐density Affymetrix Axiom® genotyping array (the Wheat Breeders’ Array), in a high‐throughput 384 microplate configuration, to characterize a diverse global collection of wheat accessions including landraces and elite lines derived from commercial breeding communities. We demonstrate that the Wheat Breeders’ Array is also suitable for generating high‐density genetic maps of previously uncharacterized populations and for characterizing novel genetic diversity produced by mutagenesis. To facilitate the use of the array by the wheat community, the markers, the associated sequence and the genotype information have been made available through the interactive web site ‘CerealsDB’.
PLOS ONE | 2017
Daniela Iamartino; Ezequiel L. Nicolazzi; Curtis P. Van Tassell; James M. Reecy; Eric R. Fritz-Waters; James E. Koltes; Stefano Biffani; Tad S. Sonstegard; Steven G. Schroeder; Paolo Ajmone-Marsan; Riccardo Negrini; Rolando Pasquariello; Paola Ramelli; Angelo Coletta; José Fernando Garcia; Ahmad Ali; L. Ramunno; G. Cosenza; Denise Aparecida Andrade de Oliveira; Marcela G. Drummond; Eduardo Bastianetto; Alessandro Davassi; Ali Pirani; Fiona Brew; John L. Williams
Background The availability of the bovine genome sequence and SNP panels has improved various genomic analyses, from exploring genetic diversity to aiding genetic selection. However, few of the SNP on the bovine chips are polymorphic in buffalo, therefore a panel of single nucleotide DNA markers exclusive for buffalo was necessary for molecular genetic analyses and to develop genomic selection approaches for water buffalo. The creation of a 90K SNP panel for river buffalo and testing in a genome wide association study for milk production is described here. Methods The genomes of 73 buffaloes of 4 different breeds were sequenced and aligned against the bovine genome, which facilitated the identification of 22 million of sequence variants among the buffalo genomes. Based on frequencies of variants within and among buffalo breeds, and their distribution across the genome, inferred from the bovine genome sequence, 90,000 putative single nucleotide polymorphisms were selected to create an Axiom® Buffalo Genotyping Array 90K. Results This 90K “SNP-Chip” was tested in several river buffalo populations and found to have ∼70% high quality and polymorphic SNPs. Of the 90K SNPs about 24K were also found to be polymorphic in swamp buffalo. The SNP chip was used to investigate the structure of buffalo populations, and could distinguish buffalo from different farms. A Genome Wide Association Study identified genomic regions on 5 chromosomes putatively involved in milk production. Conclusion The 90K buffalo SNP chip described here is suitable for the analysis of the genomes of river buffalo breeds, and could be used for genetic diversity studies and potentially as a starting point for genome-assisted selection programmes. This SNP Chip could also be used to analyse swamp buffalo, but many loci are not informative and creation of a revised SNP set specific for swamp buffalo would be advised.
BMC Genomics | 2015
Nahla V. Bassil; Thomas M. Davis; Hailong Zhang; Stephen P. Ficklin; Mike Mittmann; Teresa Webster; Lise L. Mahoney; David Wood; Elisabeth S Alperin; Umesh R. Rosyara; Herma Koehorst-vanc Putten; Amparo Monfort; Daniel J. Sargent; Iraida Amaya; Béatrice Denoyes; Luca Bianco; Thijs van Dijk; Ali Pirani; Amy F. Iezzoni; Dorrie Main; Cameron Peace; Yilong Yang; Vance M. Whitaker; Sujeet Verma; Laurent Bellon; Fiona Brew; Raúl Herrera; Eric van de Weg
Archive | 2013
Hong Gao; Ali Pirani; Teresa Webster; Mei-Mei Shen
Archive | 2017
Daniela Iamartino; Ezequiel L. Nicolazzi; Curtis P. Van Tassell; James M. Reecy; Eric R. Fritz-Waters; James E. Koltes; Stefano Biffani; Tad S. Sonstegard; Steven G. Schroeder; Paolo Ajmone-Marsan; Riccardo Negrini; Rolando Pasquariello; Paola Ramelli; Angelo Coletta; José Fernando Garcia; Ahmad Ali; L. Ramunno; G. Cosenza; Denise Aparecida Andrade de Oliveira; Marcela G. Drummond; Eduardo Bastianetto; Ali Pirani; Fiona Brew; John L. Williams