Computational approaches for comparative genomics and transcriptomics using 454 sequencing technology

The development and application of computational tools has consistently played an integral role in the advancement of genomics research, leading to the sequencing, assembly and annotation of hundreds of genomes over the last two decades. However, over the last two years, the research community has embraced an array of new high-throughput, cost-effective technologies, referred to as the "next-generation sequencing technologies" , which are poised to alter the landscape of genomics research in the path to accelerated biological discovery. This imminent scientific revolution can, however, happen only if a) new computational tools are developed to cater to the type of data generated by these new technologies; and b) efficient computational frameworks are implemented to seamlessly integrate both new and old tools and enable biologists to answer domain-specific questions. The goal of this thesis is to address the latter need in the context of two projects — one toward the sequencing the genome of a new extremophile microbe and another toward enabling transcriptomics in tree fruit species for which the underlying genomics is not yet fully understood. Both projects use the 454 sequencing technology, which is one of the next-generation sequencing technologies. More specifically, the contributions of the thesis are in the development and application of computational frameworks that have led to the generation of the first known 454-sequencing based draft assembly of the Sulfolobus solfataricus strain 98/2 genome along with its comparative genomics, and to the enabling of 454-sequencing based transcriptomics characterization of apple, pear and cherry. It is expected that the methods and computational frameworks implemented as part of this thesis will have a broader applicability in the near future for projects in comparative genomics and transcriptomics that use next-generation sequencing technologies. The thesis is the result of the collaboration among the WSU Department of Horticulture, WSU School of Molecular Biosciences and the WSU School of EECS

GIO-Genes in Order-A Suite of Scripts for Identification and Mapping of SNP Markers in GBS Data

<p>GIO-Genes in Order-A Suite of Scripts for Identification and Mapping of SNP Markers in GBS Data. </p

Genome-wide identification and analysis of the ALTERNATIVE OXIDASE gene family in diploid and hexaploid wheat

A comprehensive understanding of wheat responses to environmental stress will contribute to the long-term goal of feeding the planet. ALERNATIVE OXIDASE (AOX) genes encode proteins involved in a bypass of the electron transport chain and are also known to be involved in stress tolerance in multiple species. Here, we report the identification and characterization of the AOX gene family in diploid and hexaploid wheat. Four genes each were found in the diploid ancestors Triticum urartu, and Aegilops tauschii, and three in Aegilops speltoides. In hexaploid wheat (Triticum aestivum), 20 genes were identified, some with multiple splice variants, corresponding to a total of 24 proteins for those with observed transcription and translation. These proteins were classified as AOX1a, AOX1c, AOX1e or AOX1d via phylogenetic analysis. Proteins lacking most or all signature AOX motifs were assigned to putative regulatory roles. Analysis of protein-targeting sequences suggests mixed localization to the mitochondria and other organelles. In comparison to the most studied AOX from Trypanosoma brucei, there were amino acid substitutions at critical functional domains indicating possible role divergence in wheat or grasses in general. In hexaploid wheat, AOX genes were expressed at specific developmental stages as well as in response to both biotic and abiotic stresses such as fungal pathogens, heat and drought. These AOX expression patterns suggest a highly regulated and diverse transcription and expression system. The insights gained provide a framework for the continued and expanded study of AOX genes in wheat for stress tolerance through breeding new varieties, as well as resistance to AOX-targeted herbicides, all of which can ultimately be used synergistically to improve crop yield

Rapid gene-based SNP and haplotype marker development in non-model eukaryotes using 3'UTR sequencing

BACKGROUND: Sweet cherry (Prunus avium L.), a non-model crop with narrow genetic diversity, is an important member of sub-family Amygdoloideae within Rosaceae. Compared to other important members like peach and apple, sweet cherry lacks in genetic and genomic information, impeding understanding of important biological processes and development of efficient breeding approaches. Availability of single nucleotide polymorphism (SNP)-based molecular markers can greatly benefit breeding efforts in such non-model species. RNA-seq approaches employing second generation sequencing platforms offer a unique avenue to rapidly identify gene-based SNPs. Additionally, haplotype markers can be rapidly generated from transcript-based SNPs since they have been found to be extremely utile in identification of genetic variants related to health, disease and response to environment as highlighted by the human HapMap project. RESULTS: RNA-seq was performed on two sweet cherry cultivars, Bing and Rainier using a 3' untranslated region (UTR) sequencing method yielding 43,396 assembled contigs. In order to test our approach of rapid identification of SNPs without any reference genome information, over 25% (10,100) of the contigs were screened for the SNPs. A total of 207 contigs from this set were identified to contain high quality SNPs. A set of 223 primer pairs were designed to amplify SNP containing regions from these contigs and high resolution melting (HRM) analysis was performed with eight important parental sweet cherry cultivars. Six of the parent cultivars were distantly related to Bing and Rainier, the cultivars used for initial SNP discovery. Further, HRM analysis was also performed on 13 seedlings derived from a cross between two of the parents. Our analysis resulted in the identification of 84 (38.7%) primer sets that demonstrated variation among the tested germplasm. Reassembly of the raw 3'UTR sequences using upgraded transcriptome assembly software yielded 34,620 contigs containing 2243 putative SNPs in 887 contigs after stringent filtering. Contigs with multiple SNPs were visually parsed to identify 685 putative haplotypes at 335 loci in 301 contigs. CONCLUSIONS: This approach, which leverages the advantages of RNA-seq approaches, enabled rapid generation of gene-linked SNP and haplotype markers. The general approach presented in this study can be easily applied to other non-model eukaryotes irrespective of the ploidy level to identify gene-linked polymorphisms that are expected to facilitate efficient Gene Assisted Breeding (GAB), genotyping and population genetics studies. The identified SNP haplotypes reveal some of the allelic differences in the two sweet cherry cultivars analyzed. The identification of these SNP and haplotype markers is expected to significantly improve the genomic resources for sweet cherry and facilitate efficient GAB in this non-model crop

Mapping genes for resistance to stripe rust in spring wheat landrace PI 480035

<div><p>Stripe rust caused by <i>Puccinia striiformis</i> Westend. f. sp. <i>tritici</i> Erikks. is an economically important disease of wheat (<i>Triticum aestivum</i> L.). Hexaploid spring wheat landrace PI 480035 was highly resistant to stripe rust in the field in Washington during 2011 and 2012. The objective of this research was to identify quantitative trait loci (QTL) for stripe rust resistance in PI 480035. A spring wheat, “Avocet Susceptible” (AvS), was crossed with PI 480035 to develop a biparental population of 110 recombinant inbred lines (RIL). The population was evaluated in the field in 2013 and 2014 and seedling reactions were examined against three races (PSTv-14, PSTv-37, and PSTv-40) of the pathogen under controlled conditions. The population was genotyped with genotyping-by-sequencing and microsatellite markers across the whole wheat genome. A major QTL, <i>QYr</i>.<i>wrsggl1-1BS</i> was identified on chromosome 1B. The closest flanking markers were <i>Xgwm273</i>, <i>Xgwm11</i>, and <i>Xbarc187</i> 1.01 cM distal to <i>QYr</i>.<i>wrsggl1-1BS</i>, <i>Xcfd59</i> 0.59 cM proximal and <i>XA365</i> 3.19 cM proximal to <i>QYr</i>.<i>wrsggl1-1BS</i>. Another QTL, <i>QYr</i>.<i>wrsggl1-3B</i>, was identified on 3B, which was significant only for PSTv-40 and was not significant in the field, indicating it confers a race-specific resistance. Comparison with markers associated with previously reported <i>Yr</i> genes on 1B (<i>Yr64</i>, <i>Yr65</i>, and <i>YrH52</i>) indicated that <i>QYr</i>.<i>wrsggl1-1BS</i> is potentially a novel stripe rust resistance gene that can be incorporated into modern breeding materials, along with other all-stage and adult-plant resistance genes to develop cultivars that can provide durable resistance.</p></div

Chromosomal location of quantitative trait loci (QTLs) for stripe rust resistance in the AvS × PI 480035 population.

<p>Chromosomal location of quantitative trait loci (QTLs) for stripe rust resistance in the AvS × PI 480035 population.</p

Heat map of expression profiles for high-confidence <i>TaAOX</i> genes under biotic and abiotic stresses.

<p>Heat map of expression profiles for high-confidence <i>TaAOX</i> genes under biotic and abiotic stresses.</p

Features of AOX proteins in the wheat genomes.

<p>Features of AOX proteins in the wheat genomes.</p