Hector Sanchez-Villeda

Development and mapping of SSR markers for maize.

Microsatellite or simple sequence repeat (SSR) markers have wide applicability for genetic analysis in crop plant improvement strategies. The objectives of this project were to isolate, characterize, and map a comprehensive set of SSR markers for maize (Zea mays L.). We developed 1051 novel SSR markers for maize from microsatellite-enriched libraries and by identification of microsatellite-containing sequences in public and private databases. Three mapping populations were used to derive map positions for 978 of these markers. The main mapping population was the intermated B73 × Mo17 (IBM) population. In mapping this intermated recombinant inbred line population, we have contributed to development of a new high-resolution map resource for maize. The primer sequences, original sequence sources, data on polymorphisms across 11 inbred lines, and map positions have been integrated with information on other public SSR markers and released through MaizeDB at URL:www.agron.missouri.edu. The maize research community now has the most detailed and comprehensive SSR marker set of any plant species.

Physical and genetic structure of the maize genome reflects its complex evolutionary history.

Maize (Zea mays L.) is one of the most important cereal crops and a model for the study of genetics, evolution, and domestication. To better understand maize genome organization and to build a framework for genome sequencing, we constructed a sequence-ready fingerprinted contig-based physical map that covers 93.5% of the genome, of which 86.1% is aligned to the genetic map. The fingerprinted contig map contains 25,908 genic markers that enabled us to align nearly 73% of the anchored maize genome to the rice genome. The distribution pattern of expressed sequence tags correlates to that of recombination. In collinear regions, 1 kb in rice corresponds to an average of 3.2 kb in maize, yet maize has a 6-fold genome size expansion. This can be explained by the fact that most rice regions correspond to two regions in maize as a result of its recent polyploid origin. Inversions account for the majority of chromosome structural variations during subsequent maize diploidization. We also find clear evidence of ancient genome duplication predating the divergence of the progenitors of maize and rice. Reconstructing the paleoethnobotany of the maize genome indicates that the progenitors of modern maize contained ten chromosomes.

A Large-Scale Screen for Artificial Selection in Maize Identifies Candidate Agronomic Loci for Domestication and Crop Improvement

Maize (Zea mays subsp mays) was domesticated from teosinte (Z. mays subsp parviglumis) through a single domestication event in southern Mexico between 6000 and 9000 years ago. This domestication event resulted in the original maize landrace varieties, which were spread throughout the Americas by Native Americans and adapted to a wide range of environmental conditions. Starting with landraces, 20th century plant breeders selected inbred lines of maize for use in hybrid maize production. Both domestication and crop improvement involved selection of specific alleles at genes controlling key morphological and agronomic traits, resulting in reduced genetic diversity relative to unselected genes. Here, we sequenced 1095 maize genes from a sample of 14 inbred lines and chose 35 genes with zero sequence diversity as potential targets of selection. These 35 genes were then sequenced in a sample of diverse maize landraces and teosintes and tested for selection. Using two statistical tests, we identified eight candidate genes. Extended gene sequencing of these eight candidate loci confirmed that six were selected throughout the gene, and the remaining two exhibited evidence of selection in the 3′ portion of each gene. The selected genes have functions consistent with agronomic selection for nutritional quality, maturity, and productivity. Our large-scale screen for artificial selection allows identification of genes of potential agronomic importance even when gene function and the phenotype of interest are unknown.

Anchoring 9,371 Maize Expressed Sequence Tagged Unigenes to the Bacterial Artificial Chromosome Contig Map by Two-Dimensional Overgo Hybridization

Our goal is to construct a robust physical map for maize (Zea mays) comprehensively integrated with the genetic map. We have used a two-dimensional 24 × 24 overgo pooling strategy to anchor maize expressed sequence tagged (EST) unigenes to 165,888 bacterial artificial chromosomes (BACs) on high-density filters. A set of 70,716 public maize ESTs seeded derivation of 10,723 EST unigene assemblies. From these assemblies, 10,642 overgo sequences of 40 bp were applied as hybridization probes. BAC addresses were obtained for 9,371 overgo probes, representing an 88% success rate. More than 96% of the successful overgo probes identified two or more BACs, while 5% identified more than 50 BACs. The majority of BACs identified (79%) were hybridized with one or two overgos. A small number of BACs hybridized with eight or more overgos, suggesting that these BACs must be gene rich. Approximately 5,670 overgos identified BACs assembled within one contig, indicating that these probes are highly locus specific. A total of 1,795 megabases (Mb; 87%) of the total 2,050 Mb in BAC contigs were associated with one or more overgos, which are serving as sequence-tagged sites for single nucleotide polymorphism development. Overgo density ranged from less than one overgo per megabase to greater than 20 overgos per megabase. The majority of contigs (52%) hit by overgos contained three to nine overgos per megabase. Analysis of approximately 1,022 Mb of genetically anchored BAC contigs indicates that 9,003 of the total 13,900 overgo-contig sites are genetically anchored. Our results indicate overgos are a powerful approach for generating gene-specific hybridization probes that are facilitating the assembly of an integrated genetic and physical map for maize.

Genetic, Physical, and Informatics Resources for Maize. On the Road to an Integrated Map

Maize ( Zea mays ) is among the most important crop plants in the world. For any crop plant, an integrated genetic and physical map serves as the foundation for numerous studies, especially those aimed at improving the agronomic characteristics of the plant. Once a phenotypically defined locus

A BAC pooling strategy combined with PCR-based screenings in a large, highly repetitive genome enables integration of the maize genetic and physical maps

BackgroundMolecular markers serve three important functions in physical map assembly. First, they provide anchor points to genetic maps facilitating functional genomic studies. Second, they reduce the overlap required for BAC contig assembly from 80 to 50 percent. Finally, they validate assemblies based solely on BAC fingerprints. We employed a six-dimensional BAC pooling strategy in combination with a high-throughput PCR-based screening method to anchor the maize genetic and physical maps.ResultsA total of 110,592 maize BAC clones (~ 6x haploid genome equivalents) were pooled into six different matrices, each containing 48 pools of BAC DNA. The quality of the BAC DNA pools and their utility for identifying BACs containing target genomic sequences was tested using 254 PCR-based STS markers. Five types of PCR-based STS markers were screened to assess potential uses for the BAC pools. An average of 4.68 BAC clones were identified per marker analyzed. These results were integrated with BAC fingerprint data generated by the Arizona Genomics Institute (AGI) and the Arizona Genomics Computational Laboratory (AGCoL) to assemble the BAC contigs using the FingerPrinted Contigs (FPC) software and contribute to the construction and anchoring of the physical map. A total of 234 markers (92.5%) anchored BAC contigs to their genetic map positions. The results can be viewed on the integrated map of maize [1, 2].ConclusionThis BAC pooling strategy is a rapid, cost effective method for genome assembly and anchoring. The requirement for six replicate positive amplifications makes this a robust method for use in large genomes with high amounts of repetitive DNA such as maize. This strategy can be used to physically map duplicate loci, provide order information for loci in a small genetic interval or with no genetic recombination, and loci with conflicting hybridization-based information.

Development of an integrated laboratory information management system for the maize mapping project

MOTIVATION The development of an integrated genetic and physical map for the maize genome involves the generation of an enormous amount of data. Managing this data requires a system to aid in genotype scoring for different types of markers coming from both local and remote users. In addition, researchers need an efficient way to interact with genetic mapping software and with data files from automated DNA sequencing. They also need ways to manage primer data for mapping and sequencing and provide views of the integrated physical and genetic map and views of genetic map comparisons. RESULTS The MMP-LIMS system has been used successfully in a high-throughput mapping environment. The genotypes from 957 SSR, 1023 RFLP, 189 SNP, and 177 InDel markers have been entered and verified via MMP-LIMS. The system is flexible, and can be easily modified to manage data for other species. The software is freely available. AVAILABILITY To receive a copy of the iMap or cMap software, please fill out the form on our website. The other MMP-LIMS software is freely available at http://www.maizemap.org/bioinformatics.htm.

DNAAlignEditor: DNA alignment editor tool

BackgroundWith advances in DNA re-sequencing methods and Next-Generation parallel sequencing approaches, there has been a large increase in genomic efforts to define and analyze the sequence variability present among individuals within a species. For very polymorphic species such as maize, this has lead to a need for intuitive, user-friendly software that aids the biologist, often with naïve programming capability, in tracking, editing, displaying, and exporting multiple individual sequence alignments. To fill this need we have developed a novel DNA alignment editor.ResultsWe have generated a nucleotide sequence alignment editor (DNAAlignEditor) that provides an intuitive, user-friendly interface for manual editing of multiple sequence alignments with functions for input, editing, and output of sequence alignments. The color-coding of nucleotide identity and the display of associated quality score aids in the manual alignment editing process. DNAAlignEditor works as a client/server tool having two main components: a relational database that collects the processed alignments and a user interface connected to database through universal data access connectivity drivers. DNAAlignEditor can be used either as a stand-alone application or as a network application with multiple users concurrently connected.ConclusionWe anticipate that this software will be of general interest to biologists and population genetics in editing DNA sequence alignments and analyzing natural sequence variation regardless of species, and will be particularly useful for manual alignment editing of sequences in species with high levels of polymorphism.

MaizeDB – A Functional Genomics Perspective

MaizeDB (http://www.agron.missouri.edu/) has existed since the early 90’s as a genomespecific database that is grounded in genetic maps, their documentation and annotation. The database management system is robust and has continuously been Sybase. In this brief review we provide an introduction to the database as a functional genomics tool and new accesses to the data: 1) probe tables by bin location 2) BLAST access to map data 3) cMap, a comparative map graphical tool.

Empirical Analysis of Selection Screens for Domestication and Improvement Loci in Maize by Extended DNA Sequencing

Both domestication and crop improvement in maize (Zea mays ssp. mays) have involved selection of specific alleles at genes controlling key morphologic and agronomic traits, resulting in reduced genetic diversity relative to unselected genes. This difference in genetic diversity has led to the development of genomic screens for artificial selection in maize that have identified ∼50 candidate agronomic genes. One limitation of these initial genome screens is that the short length of the alignment (average length < 300 bp) restricts the statistical power and may lead to false positives. The major objective of this research was to provide an empirical determination of the false positive rate of genomic screens for artificial selection in maize. Therefore, we performed extended sequencing throughout the available gene sequence of 27 previously identified selection candidates using maize inbred, maize landrace (for 12 genes), and teosinte (Zea mays ssp. parviglumis) accessions. The extended sequence alignments (average length > 2000 bp) allowed clear separation of strong candidates for selection from those that cannot be distinguished from the tail of the diversity distribution of all maize genes. The extended alignments also allowed linkage disequilibrium to be considered in evaluating a candidates selection status. This proved particularly useful in distinguishing selection at domestication versus subsequent crop improvement.