Group testing problems in experimental molecular biology

In group testing, the task is to determine the distinguished members of a set of objects L by asking subset queries of the form ``does the subset Q of L contain a distinguished object?'' The primary biological application of group testing is for screening libraries of clones with hybridization probes. This is a crucial step in constructing physical maps and for finding genes. Group testing has also been considered for sequencing by hybridization. Another important application includes screening libraries of reagents for useful chemically active zones. This preliminary report discusses some of the constrained group testing problems which arise in biology.Comment: 7 page

A branch-and-cut approach to physical mapping with end-probes

A fundamental problem in computational biology is the construction of physical maps of chromosomes from hybridization experiments between unique probes and clones of chromosome fragments in the presence of error. Alizadeh, Karp, Weisser and Zweig (Algorithmica 13:1/2, 52-76, 1995) first considered a maximum-likelihood model of the problem that is equivalent to finding an ordering of the probes that minimizes a weighted sum of errors, and developed several effective heuristics. We show that by exploiting information about the end-probes of clones, this model can be formulated as a weighted Betweenness Problem. This affords the significant advantage of allowing the well-developed tools of integer linear-programming and branch-and-cut algorithms to be brought to bear on physical mapping, enabling us for the first time to solve small mapping instances to optimality even in the presence of high error. We also show that by combining the optimal solution of many small overlapping Betweenness Problems, one can effectively screen errors from larger instances, and solve the edited instance to optimality as a Hamming-Distance Traveling Salesman Problem. This suggests a new combined approach to physical map construction

Strategies for Sequence Assembly of Plant Genomes

The field of plant genome assembly has greatly benefited from the development and widespread adoption of next-generation DNA sequencing platforms. Very high sequencing throughputs and low costs per nucleotide have considerably reduced the technical and budgetary constraints associated with early assembly projects done primarily with a traditional Sanger-based approach. Those improvements led to a sharp increase in the number of plant genomes being sequenced, including large and complex genomes of economically important crops. Although next-generation DNA sequencing has considerably improved our understanding of the overall structure and dynamics of many plant genomes, severe limitations still remain because next-generation DNA sequencing reads typically are shorter than Sanger reads. In addition, the software tools used to de novo assemble sequences are not necessarily designed to optimize the use of short reads. These cause challenges, common to many plant species with large genome sizes, high repeat contents, polyploidy and genome-wide duplications. This chapter provides an overview of historical and current methods used to sequence and assemble plant genomes, along with new solutions offered by the emergence of technologies such as single molecule sequencing and optical mapping to address the limitations of current sequence assemblies

Algebraic correction methods for computational assessment of clone overlaps in DNA fingerprint mapping

<p>Abstract</p> <p>Background</p> <p>The Sulston score is a well-established, though approximate metric for probabilistically evaluating postulated clone overlaps in DNA fingerprint mapping. It is known to systematically over-predict match probabilities by various orders of magnitude, depending upon project-specific parameters. Although the exact probability distribution is also available for the comparison problem, it is rather difficult to compute and cannot be used directly in most cases. A methodology providing both improved accuracy and computational economy is required.</p> <p>Results</p> <p>We propose a straightforward algebraic correction procedure, which takes the Sulston score as a provisional value and applies a power-law equation to obtain an improved result. Numerical comparisons indicate dramatically increased accuracy over the range of parameters typical of traditional agarose fingerprint mapping. Issues with extrapolating the method into parameter ranges characteristic of newer capillary electrophoresis-based projects are also discussed.</p> <p>Conclusion</p> <p>Although only marginally more expensive to compute than the raw Sulston score, the correction provides a vastly improved probabilistic description of hypothesized clone overlaps. This will clearly be important in overlap assessment and perhaps for other tasks as well, for example in using the ranking of overlap probabilities to assist in clone ordering.</p

LTC: a novel algorithm to improve the efficiency of contig assembly for physical mapping in complex genomes

<p>Abstract</p> <p>Background</p> <p>Physical maps are the substrate of genome sequencing and map-based cloning and their construction relies on the accurate assembly of BAC clones into large contigs that are then anchored to genetic maps with molecular markers. High Information Content Fingerprinting has become the method of choice for large and repetitive genomes such as those of maize, barley, and wheat. However, the high level of repeated DNA present in these genomes requires the application of very stringent criteria to ensure a reliable assembly with the FingerPrinted Contig (FPC) software, which often results in short contig lengths (of 3-5 clones before merging) as well as an unreliable assembly in some difficult regions. Difficulties can originate from a non-linear topological structure of clone overlaps, low power of clone ordering algorithms, and the absence of tools to identify sources of gaps in Minimal Tiling Paths (MTPs).</p> <p>Results</p> <p>To address these problems, we propose a novel approach that: (i) reduces the rate of false connections and Q-clones by using a new cutoff calculation method; (ii) obtains reliable clusters robust to the exclusion of single clone or clone overlap; (iii) explores the topological contig structure by considering contigs as networks of clones connected by significant overlaps; (iv) performs iterative clone clustering combined with ordering and order verification using re-sampling methods; and (v) uses global optimization methods for clone ordering and Band Map construction. The elements of this new analytical framework called Linear Topological Contig (LTC) were applied on datasets used previously for the construction of the physical map of wheat chromosome 3B with FPC. The performance of LTC vs. FPC was compared also on the simulated BAC libraries based on the known genome sequences for chromosome 1 of rice and chromosome 1 of maize.</p> <p>Conclusions</p> <p>The results show that compared to other methods, LTC enables the construction of highly reliable and longer contigs (5-12 clones before merging), the detection of "weak" connections in contigs and their "repair", and the elongation of contigs obtained by other assembly methods.</p

Construction of a map-based reference genome sequence for barley, Hordeum vulgare L.

Barley (Hordeum vulgare L.) is a cereal grass mainly used as animal fodder and raw material for the malting industry. The map-based reference genome sequence of barley cv. `Morex' was constructed by the International Barley Genome Sequencing Consortium (IBSC) using hierarchical shotgun sequencing. Here, we report the experimental and computational procedures to (i) sequence and assemble more than 80,000 bacterial artificial chromosome (BAC) clones along the minimum tiling path of a genome-wide physical map, (ii) find and validate overlaps between adjacent BACs, (iii) construct 4,265 non-redundant sequence scaffolds representing clusters of overlapping BACs, and (iv) order and orient these BAC clusters along the seven barley chromosomes using positional information provided by dense genetic maps, an optical map and chromosome conformation capture sequencing (Hi-C). Integrative access to these sequence and mapping resources is provided by the barley genome explorer (BARLEX).Peer reviewe

Toward 959 nematode genomes

The sequencing of the complete genome of the nematode Caenorhabditis elegans was a landmark achievement and ushered in a new era of whole-organism, systems analyses of the biology of this powerful model organism. The success of the C. elegans genome sequencing project also inspired communities working on other organisms to approach genome sequencing of their species. The phylum Nematoda is rich and diverse and of interest to a wide range of research fields from basic biology through ecology and parasitic disease. For all these communities, it is now clear that access to genome scale data will be key to advancing understanding, and in the case of parasites, developing new ways to control or cure diseases. The advent of second-generation sequencing technologies, improvements in computing algorithms and infrastructure and growth in bioinformatics and genomics literacy is making the addition of genome sequencing to the research goals of any nematode research program a less daunting prospect. To inspire, promote and coordinate genomic sequencing across the diversity of the phylum, we have launched a community wiki and the 959 Nematode Genomes initiative (www.nematodegenomes.org/). Just as the deciphering of the developmental lineage of the 959 cells of the adult hermaphrodite C. elegans was the gateway to broad advances in biomedical science, we hope that a nematode phylogeny with (at least) 959 sequenced species will underpin further advances in understanding the origins of parasitism, the dynamics of genomic change and the adaptations that have made Nematoda one of the most successful animal phyla

The Physical and Genetic Framework of the Maize B73 Genome

Maize is a major cereal crop and an important model system for basic biological research. Knowledge gained from maize research can also be used to genetically improve its grass relatives such as sorghum, wheat, and rice. The primary objective of the Maize Genome Sequencing Consortium (MGSC) was to generate a reference genome sequence that was integrated with both the physical and genetic maps. Using a previously published integrated genetic and physical map, combined with in-coming maize genomic sequence, new sequence-based genetic markers, and an optical map, we dynamically picked a minimum tiling path (MTP) of 16,910 bacterial artificial chromosome (BAC) and fosmid clones that were used by the MGSC to sequence the maize genome. The final MTP resulted in a significantly improved physical map that reduced the number of contigs from 721 to 435, incorporated a total of 8,315 mapped markers, and ordered and oriented the majority of FPC contigs. The new integrated physical and genetic map covered 2,120 Mb (93%) of the 2,300-Mb genome, of which 405 contigs were anchored to the genetic map, totaling 2,103.4 Mb (99.2% of the 2,120 Mb physical map). More importantly, 336 contigs, comprising 94.0% of the physical map (∼1,993 Mb), were ordered and oriented. Finally we used all available physical, sequence, genetic, and optical data to generate a golden path (AGP) of chromosome-based pseudomolecules, herein referred to as the B73 Reference Genome Sequence version 1 (B73 RefGen_v1)