Mike Hanafey

Bio: Mike Hanafey is an academic researcher from DuPont. The author has contributed to research in topics: Indel & Gene mapping. The author has an hindex of 4, co-authored 4 publications receiving 299 citations.

Insertion-deletion polymorphisms in 3' regions of maize genes occur frequently and can be used as highly informative genetic markers.

Abstract: Single-nucleotide polymorphisms (SNPs) are the most frequent variations in the genome of any organism SNP discovery approaches such as resequencing or data mining enable the identification of insertion deletion (indel) polymorphisms These indels can be treated as biallelic markers and can be utilized for genetic mapping and diagnostics In this study 655 indels have been identified by resequencing 502 maize (Zea mays) loci across 8 maize inbreds (selected for their high allelic variation) Of these 502 loci, 433 were polymorphic, with indels identified in 215 loci Of the 655 indels identified, single-nucleotide indels accounted for more than half (548%) followed by two- and three-nucleotide indels A high frequency of 6-base (34%) and 8-base (23%) indels were also observed When analysis is restricted to the B73 and Mol7 genotypes, 53% of the loci analyzed contained indels, with 42% having an amplicon size difference Three novel miniature inverted-repeat transposable element (MITE)-like sequences were identified as insertions near genes The utility of indels as genetic markers was demonstrated by using indel polymorphisms to map 22 loci in a B73 x Mo17 recombinant inbred population This paper clearly demonstrates that the resequencing of 3' EST sequence and the discovery and mapping of indel markers will position corresponding expressed genes on the genetic map

High-Throughput Identification, Database Storage and Analysis of SNPs in EST Sequences

Abstract: Single nucleotide polymorphisms (SNPs) are the most frequent form of DNA variation and disease-causing mutations in many genes. Due to their abundance and slow mutation rate within generations, they are thought to be the next generation of genetic markers that can be used in a myriad of important biological, genetic, pharmacological, and medical applications. There are several strategies both experimental, and in-silico for SNP discovery and mapping. Experimental SNP discovery consists of a number of labourious steps that make this process complex and expensive. In-silico discovery has been proposed as an alternative discovery method that makes use and takes advantage of large data sets with potential SNP information that have been generated with other purposes and have not been used as a SNP information source yet. However, in order to successfully apply the in-silico method to large data sets, the following challenges need to be addressed: First it is necessary to build an integrated SNP pipeline that handles data processing steps smoothly from the beginning (collecting sequence information) to end (SNPs in the database). Also, SNP detection tool parameters have to be optimized to satisfy specific goals of the project. Finally, SNP data could not be fully used until the in-silico method is validated experimentally. In this paper we present a design and implementation of an in-silico SNP detection software pipeline that exploits the existence of large EST (expressed sequence tag) data sets and effectively addresses the above challenges. First, the pipeline allows for smooth data transition between its different components by implementing data interfaces that translate the data formats of the different tools in the different stages. Second, we optimized PolyBayes parameters for SNP detection in maize EST. Finally, we implemented a user interface that along with the database structure created allows the scientist to perform preliminary analysis of the data and to perform basic statistics on the SNP data prior to experimental validation. The pipeline works with two different types of sequence assemblers (PHRAP (http://www.phrap.org/) and CAT from DoubleTwist (http://www.doubletwist.com/). It uses a Bayesian engine for SNP detection (PolyBayes), selects relevant polymorphism information which is then uploaded into a database. We detected 2439 SNPs and 822 insertion deletions (INDELs) with a PolyBayes probability higher than 0.99 on the public set of 68,000 maize ESTs. The user interface allowed us analyzing the polymorphism information right after discovery in several ways that allowed us to gain insight into the distribution and significance of the newly acquired data.

The Chromosomal Passenger Complex (CPC): From Easy Rider to the Godfather of Mitosis

Abstract: Successful cell division requires the precise and timely coordination of chromosomal, cytoskeletal and membrane trafficking events. These processes are regulated by the competing actions of protein kinases and phosphatases. Aurora B is one of the most intensively studied kinases. In conjunction with inner centromere protein (INCENP), borealin (also known as Dasra) and survivin it forms the chromosomal passenger complex (CPC). This complex targets to different locations at differing times during mitosis, where it regulates key mitotic events: correction of chromosome-microtubule attachment errors; activation of the spindle assembly checkpoint; and construction and regulation of the contractile apparatus that drives cytokinesis. Our growing understanding of the CPC has seen it develop from a mere passenger riding on the chromosomes to one of the main controllers of mitosis.

SNP frequency, haplotype structure and linkage disequilibrium in elite maize inbred lines

Abstract: Recent studies of ancestral maize populations indicate that linkage disequilibrium tends to dissipate rapidly, sometimes within 100 bp. We set out to examine the linkage disequilibrium and diversity in maize elite inbred lines, which have been subject to population bottlenecks and intense selection by breeders. Such population events are expected to increase the amount of linkage disequilibrium, but reduce diversity. The results of this study will inform the design of genetic association studies. We examined the frequency and distribution of DNA polymorphisms at 18 maize genes in 36 maize inbreds, chosen to represent most of the genetic diversity in U.S. elite maize breeding pool. The frequency of nucleotide changes is high, on average one polymorphism per 31 bp in non-coding regions and 1 polymorphism per 124 bp in coding regions. Insertions and deletions are frequent in non-coding regions (1 per 85 bp), but rare in coding regions. A small number (2–8) of distinct and highly diverse haplotypes can be distinguished at all loci examined. Within genes, SNP loci comprising the haplotypes are in linkage disequilibrium with each other. No decline of linkage disequilibrium within a few hundred base pairs was found in the elite maize germplasm. This finding, as well as the small number of haplotypes, relative to neutral expectation, is consistent with the effects of breeding-induced bottlenecks and selection on the elite germplasm pool. The genetic distance between haplotypes is large, indicative of an ancient gene pool and of possible interspecific hybridization events in maize ancestry.

Systematic exploration of essential yeast gene function with temperature-sensitive mutants

Abstract: Conditional temperature-sensitive (ts) mutations are valuable reagents for studying essential genes in the yeast Saccharomyces cerevisiae. We constructed 787 ts strains, covering 497 (∼45%) of the 1,101 essential yeast genes, with ∼30% of the genes represented by multiple alleles. All of the alleles are integrated into their native genomic locus in the S288C common reference strain and are linked to a kanMX selectable marker, allowing further genetic manipulation by synthetic genetic array (SGA)-based, high-throughput methods. We show two such manipulations: barcoding of 440 strains, which enables chemical-genetic suppression analysis, and the construction of arrays of strains carrying different fluorescent markers of subcellular structure, which enables quantitative analysis of phenotypes using high-content screening. Quantitative analysis of a GFP-tubulin marker identified roles for cohesin and condensin genes in spindle disassembly. This mutant collection should facilitate a wide range of systematic studies aimed at understanding the functions of essential genes.

SNP markers and their impact on plant breeding.

Abstract: The use of molecular markers has revolutionized the pace and precision of plant genetic analysis which in turn facilitated the implementation of molecular breeding of crops. The last three decades have seen tremendous advances in the evolution of marker systems and the respective detection platforms. Markers based on single nucleotide polymorphisms (SNPs) have rapidly gained the center stage of molecular genetics during the recent years due to their abundance in the genomes and their amenability for high-throughput detection formats and platforms. Computational approaches dominate SNP discovery methods due to the ever-increasing sequence information in public databases; however, complex genomes pose special challenges in the identification of informative SNPs warranting alternative strategies in those crops. Many genotyping platforms and chemistries have become available making the use of SNPs even more attractive and efficient. This paper provides a review of historical and current efforts in the development, validation, and application of SNP markers in QTL/gene discovery and plant breeding by discussing key experimental strategies and cases exemplifying their impact.