Next-generation survey sequencing and the molecular organization of wheat chromosome 6B.

コムギのゲノム配列の概要解読に成功 -コムギの新品種開発の加速化に期待-. 京都大学プレスリリース. 2014-07-24.Common wheat (Triticum aestivum L.) is one of the most important cereals in the world. To improve wheat quality and productivity, the genomic sequence of wheat must be determined. The large genome size (∼17 Gb/1 C) and the hexaploid status of wheat have hampered the genome sequencing of wheat. However, flow sorting of individual chromosomes has allowed us to purify and separately shotgun-sequence a pair of telocentric chromosomes. Here, we describe a result from the survey sequencing of wheat chromosome 6B (914 Mb/1 C) using massively parallel 454 pyrosequencing. From the 4.94 and 5.51 Gb shotgun sequence data from the two chromosome arms of 6BS and 6BL, 235 and 273 Mb sequences were assembled to cover ∼55.6 and 54.9% of the total genomic regions, respectively. Repetitive sequences composed 77 and 86% of the assembled sequences on 6BS and 6BL, respectively. Within the assembled sequences, we predicted a total of 4798 non-repetitive gene loci with the evidence of expression from the wheat transcriptome data. The numbers and chromosomal distribution patterns of the genes for tRNAs and microRNAs in wheat 6B were investigated, and the results suggested a significant involvement of DNA transposon diffusion in the evolution of these non-protein-coding RNA genes. A comparative analysis of the genomic sequences of wheat 6B and monocot plants clearly indicated the evolutionary conservation of gene contents

Revealing phenotype-associated functional differences by genome-wide scan of ancient haplotype blocks

<div><p>Genome-wide scans for positive selection have become important for genomic medicine, and many studies aim to find genomic regions affected by positive selection that are associated with risk allele variations among populations. Most such studies are designed to detect recent positive selection. However, we hypothesize that ancient positive selection is also important for adaptation to pathogens, and has affected current immune-mediated common diseases. Based on this hypothesis, we developed a novel linkage disequilibrium-based pipeline, which aims to detect regions associated with ancient positive selection across populations from single nucleotide polymorphism (SNP) data. By applying this pipeline to the genotypes in the International HapMap project database, we show that genes in the detected regions are enriched in pathways related to the immune system and infectious diseases. The detected regions also contain SNPs reported to be associated with cancers and metabolic diseases, obesity-related traits, type 2 diabetes, and allergic sensitization. These SNPs were further mapped to biological pathways to determine the associations between phenotypes and molecular functions. Assessments of candidate regions to identify functions associated with variations in incidence rates of these diseases are needed in the future.</p></div

Signatures of ancient haplotype blocks with population-specific positive selection.

<p>(A) Some important loci adapted to ancient African environment arose (red triangle) and formed haplotype blocks. The haplotype blocks spread during human migration, and some mutations may have occurred for adaptation to each environment (blue and green triangles). This change is a signature of an ancient haplotype block with population-specific positive selection. (B) A proposed network model to represent the positive selection signature. Each node represents the population in a region. Throughout this paper, red, blue, and green nodes represent populations in Africa, Europe, and Asia, respectively. Arrows represent migration routes. Edges represent relationships between populations. In this work, relationships were evaluated using t-statistic scores that represent degrees of difference between populations. Asterisks represent mutations.</p

Classification of ancient haplotype blocks.

<p>Eight clusters of ancient haplotype blocks obtained by clustering based on the network of populations and their t-statistic score profiles. The number on each edge represents the average t-statistic score; smaller scores reflect shorter edges.</p

Summary of screening results.

<p>Summary of screening results.</p

Pathways for which the genes in the top 1% of ancient haplotype blocks are enriched.

<p>Pathways for which the genes in the top 1% of ancient haplotype blocks are enriched.</p

Pipeline for ancient haplotype block scan and functional annotation.

<p>(A) Novel procedure for ancient haplotype block scan using HHDs. (B) Functional annotation procedure based on biological pathways. Each box shows materials or tools used in that step.</p

Example of ancient haplotype blocks identified in this work.

<p>Four haplotype blocks identified in all three populations (YRI, CEU, and ASN) are shown. The region of overlap between the dashed lines is defined as the ancient haplotype block.</p

Score distributions for each cluster.

<p>The score distribution of ancient haplotype blocks is shown for each cluster. The clusters can be classified into three groups: I, II, and III. Group I consists of Cluster 1 (blue). Group II consists of Clusters 2, 3, 4, and 5 (red). Group III consists of Clusters 6, 7, and 5′ (green).</p

Assumed scenarios for the clusters in the top 1% of blocks.

<p>Each node represents a population, and each edge represents the degree of the t-statistic score between two populations. Red, blue, and green nodes represent YRI, CEU, and ASN populations, respectively. Asterisks represent mutations. The mutations were assumed to occur during or after migration, and are represented by asterisks on the arrows or the edges, respectively.</p