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DOI: 10.1126/science.1251788
, (2014);345 Science
The International Wheat Genome Sequencing Consortium (IWGSC)
) genomeTriticum aestivum
A chromosome-based draft sequence of the hexaploid bread wheat (
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A chromosome-based draft
sequence of the hexaploid bread
wheat (Triticum aestivum) genome
The International Wheat Genome Sequencing Consortium
(IWGSC)
An ordered draft sequence of the 17-gigabase hexaploid bread
wheat (Triticum aestivum) genome has been produced by se-
quencing isolated chromosome arms. We have annotated 124,201
gene loci distributed nearly evenly across the homeologous chro-
mosomes and subgenomes. Comparative gene analysis of wheat
subgenomes and extant diploid and tetraploid wheat relatives
showed that high sequence similarity and structural conservation
are retained, with limited gene loss, after polyploidization. How-
ever, across the genomes there was evidence of dynamic gene gain,
loss, and duplication since the divergence of the wheat lineages. A
high degree of transcriptional autonomy and no global dominance
was found for the subgenomes. These insights into the genome
biology of a polyploid crop provide a springboard for faster gene
isolation, rapid genetic marker development, and precise breeding
to meet the needs of increasing food demand worldwide.
Lists of authors and affiliations are available in the full article online.
Corresponding author: K. X. Mayer, e-mail: k.mayer@helmholtz-muenchen.de
Read the full article at http://dx.doi.org/10.1126/science.1251788
Ancient hybridizations
among the ancestral genomes
of bread wheat
Thomas Marcussen, Simen R. Sandve,* Lise Heier,
Manuel Spannagl, Matthias Pfeifer, The International Wheat
Genome Sequencing Consortium,† Kjetill S. Jakobsen,
Brande B. H Wulff, Burkhard Steuernagel, Klaus F. X. Mayer,
Odd-Arne Olsen
The allohexaploid bread wheat genome consists of three closely
related subgenomes (A, B, and D), but a clear understanding
of their phylogenetic history has been lacking. We used genome
assemblies of bread wheat and five diploid relatives to analyze
genome-wide samples of gene trees, as well as to estimate evolu-
tionary relatedness and divergence times. We show that the A
and B genomes diverged from a common ancestor ~7 million years
ago and that these genomes gave rise to the D genome through
homoploid hybrid speciation 1 to 2 million years later. Our findings
imply that the present-day bread wheat genome is a product of
multiple rounds of hybrid speciation (homoploid and polyploid)
and lay the foundation for a new framework for understanding
the wheat genome as a multilevel phylogenetic mosaic.
The list of author affiliations is available in the full article online.*Corresponding author.
E-mail: simen.sandve@nmbu.no †The International Wheat Genome Sequencing Consortium
(IWGSC) authors and affiliations are listed in the supplementary materials.
Read the full article at http://dx.doi.org/10.1126/science.1250092
SPECIAL SECTION
SLICING THE WHEAT GENOME
286 18 JULY 2014 • VOL 345 ISSUE 6194
Triticum monococcum
Triticum polonicum L.
Triticum dicoccoides var. araraticum
Triticum boeticum
Triticum macha
Ancestral wheat
Wheat varieties and species (shown) believed to
be the closest living relatives of modern bread wheat
(T. aestivum). Multiple ancestral hybridizations
occurred among most of these species, many of which
are cultivated, and along with T. aestivum represent
a dominant source of global nutrition.
Triticum carthlicum
Published by AAAS
Genome interplay in the
grain transcriptome of hexaploid
bread wheat
Matthias Pfeifer, Karl G. Kugler, Simen R. Sandve, Bujie Zhan,
Heidi Rudi, Torgeir R. Hvidsten, International Wheat Genome
Sequencing Consortium,* Klaus F. X. Mayer, Odd-Arne Olsen†
Allohexaploid bread wheat (Triticum aestivum L.) provides
approximately 20% of calories consumed by humans. Lack of
genome sequence for the three homeologous and highly simi-
lar bread wheat genomes (A, B, and D) has impeded expression
analysis of the grain transcriptome. We used previously unknown
genome information to analyze the cell type–specific expression
of homeologous genes in the developing wheat grain and identified
distinct co-expression clusters reflecting the spatiotemporal pro-
gression during endosperm development. We observed no global
but cell type– and stage-dependent genome dominance, organiza-
tion of the wheat genome into transcriptionally active chromo-
somal regions, and asymmetric expression in gene families related
to baking quality. Our findings give insight into the transcriptional
dynamics and genome interplay among individual grain cell types
in a polyploid cereal genome.
The list of author affiliations is available in the full article online. *The International Wheat
Genome Sequencing Consortium (IWGSC) authors and affiliations are listed in the supplementary
materials. †Corresponding author. E-mail: odd-arne.olsen@nmbu.no
Read the full article at http://dx.doi.org/10.1126/science.1250091
Structural and functional
partitioning of bread wheat
chromosome 3B
Frédéric Choulet,* Adriana Alberti, Sébastien Theil, Natasha
Glover, Valérie Barbe, Josquin Daron, Lise Pingault, Pierre
Sourdille, Arnaud Couloux, Etienne Paux, Philippe Leroy, Sophie
Mangenot, Nicolas Guilhot, Jacques Le Gouis, Francois Balfourier,
Michael Alaux, Véronique Jamilloux, Julie Poulain, Céline Durand,
Arnaud Bellec, Christine Gaspin, Jan Safar, Jaroslav Dolezel, Jane
Rogers, Klaas Vandepoele, Jean-Marc Aury, Klaus Mayer, Hélène
Berges, Hadi Quesneville, Patrick Wincker, Catherine Feuillet
We produced a reference sequence of the 1-gigabase chromosome
3B of hexaploid bread wheat. By sequencing 8452 bacterial artificial
chromosomes in pools, we assembled a sequence of 774 megabases
carrying 5326 protein-coding genes, 1938 pseudogenes, and 85% of
transposable elements. The distribution of structural and functional
features along the chromosome revealed partitioning correlated
with meiotic recombination. Comparative analyses indicated high
wheat-specific inter- and intrachromosomal gene duplication activi-
ties that are potential sources of variability for adaption. In addition
to providing a better understanding of the organization, function,
and evolution of a large and polyploid genome, the availability of a
high-quality sequence anchored to genetic maps will accelerate the
identification of genes underlying important agronomic traits.
The list of author affiliations is available in the full article online.
*Corresponding author. E-mail: frederic.choulet@clermont.inra.fr
Read the full article at http://dx.doi.org/10.1126/science.1249721
m
Triticum tauschii
Triticum dicoccum
Triticum turgidum L
Triticum dicoccoides
Triticum spelta L.
Triticum durum
Triticum searsi
18 JULY 2014 • VOL 345 ISSUE 6194 287
Triticum timopheevii
PHOTOS: SUSANNE STAMP, ERNST MERZ/ETH ZURICH
Published by AAAS
WHEAT GENOME
A chromosome-based draft sequence
of the hexaploid bread wheat
(Triticum aestivum) genome
The International Wheat Genome Sequencing Consortium (IWGSC)*†
An ordered draft sequence of the 17-gigabase hexaploid bread wheat (Triticum aestivum)
genome has been produced by sequencing isolated chromosome arms. We have annotated
124,201 gene loci distributed nearly evenly across the homeologous chromosomes
and subgenomes. Comparative gene analysis of wheat subgenomes and extant diploid
and tetraploid wheat relatives showed that high sequence similarity and structural
conservation are retained, with limited gene loss, after polyploidization. However, across
the genomes there was evidence of dynamic gene gain, loss, and duplication since the
divergence of the wheat lineages. A high degree of transcriptional autonomy and no
global dominance was found for the subgenomes. These insights into the genome
biology of a polyploid crop provide a springboard for faster gene isolation, rapid genetic
marker development, and precise breeding to meet the needs of increasing food
demand worldwide.
Rich in protein, carbohydrates, and min-
erals, bread wheat (Triticum aestivum L.)
is one of the world’s most important ce-
real grain crops, serving as the staple food
source for 30% of the human population.
Between 2000 and 2008, wheat production fell
by 5.5% primarily because of climatic trends (1),
and, in 5 of the past 10 years, worldwide wheat
production was not sufficient to meet demand
(2). With the global population projected to ex-
ceed 9 billion by 2050, researchers, breeders and
growersarefacingthechallengeofincreasing
wheat production by about 70% to meet future
demands (3,4). Concurrently, growers are facing
rising fertilizer and other input costs, weather
extremes resulting from climate change, increas-
ing competition between food and nonfood uses,
and declining annual yield growth (5). A rapid
paradigm shift in science-based advances in wheat
genetics and breeding, comparable to the first
green revolution of the 1960s, will be essential
to meet these challenges. As for other major cereal
crops (rice, maize, and sorghum), new knowledge
and molecular tools using a reference genome
sequence of wheat are needed to underpin breed-
ing to accelerate the development of new wheat
varieties.
One key factor in the success of wheat as a
global food crop is its adaptability to a wide range
of climatic conditions. This is attributable, in part,
to its allohexaploid genome structure, which arose
as a result of two polyploidization events (Fig. 1).
The first of these is estimated to have occurred
several hundred thousand years ago and brought
together the genomes of two diploid species re-
lated to the wild species Triticum urartu (2n=
2x=14;AA;2nis the number of chromosomes
in each somatic cell and 2xis the basic chro-
mosome number) and a species from the Sitopsis
section of Triticum that is believed to be related
to Aegilops speltoides (2n=14;SS)(6). This hy-
bridization formed the allotetraploid Triticum
turgidum (2n=4x= 28; AABB), an ancestor of
wild emmer wheat cultivated in the Middle
East and T. turgidum sp. durum grown for pasta
today. A second hybridization event between
T. turgidum andadiploidgrassspecies,Aegilops
tauschii (DD), produced the ancestral allohexaploid
T. aestivum (2n=6x= 42, AABBDD) (6,7), which
has since been cultivated as bread wheat and ac-
counts for over 95% of the wheat grown worldwide.
With 21 pairs of chromosomes, bread wheat
is structurally an allopolyploid with three ho-
meologous sets of seven chromosomes in each
of the A, B, and D subgenomes. Genetically,
however, it behaves as a diploid because homeol-
ogous pairing is prevented through the action of
Ph genes (8).Eachofthesubgenomesislarge,
about 5.5 Gb in size and carries, in addition to
related sets of genes, a high proportion (>80%)
of highly repetitive transposable elements (TEs)
(9,10).
The large and repetitive nature of the genome
has hindered the generation of a reference ge-
nome sequence for bread wheat. Early work
focused primarily on coding sequences that rep-
resent less than 2% of the genome. Coordinated
efforts generated over 1 million expressed sequence
tags (ESTs), 40,000 unigenes (www.ncbi.nlm.nih.
gov/dbEST/dbEST_summary.html), and 17,000 full-
length complementary DNA (cDNA) sequences
(11). These resources have enabled studies of in-
dividual genes and facilitated the development
of microarrays and marker sets for targeted gene
association and expression studies (12–14). At
least 7000 ESTs have been assigned to chromosome-
specific bins (15), providing an initial view of
subgenome localization and chromosomal orga-
nization and facilitating low-resolution mapping
of traits. More recently, high-throughput low-cost
sequencing technologies have been applied to
assemble the gene space of T. urartu (16)and
Ae. tauschii (17), two diploid species related to
bread wheat (Fig. 1). About 60,000 genic se-
quences were also putatively assigned to the
bread wheat A, B, or D subgenomes by using
assembled Illumina (Illumina, Incorporated,
San Diego, CA) sequence data for Triticum
monococcum and Ae. tauschii and cDNAs from
Ae. speltoides to guide gene assemblies of five-
fold whole-genome sequence reads from T.
aestivum ‘Chinese Spring’(18). These re-
sources have contributed information about
the genes of hexaploid wheat and its wild
diploid relatives and have underpinned the
SCIENCE sciencemag.org 18 JULY 2014 •VOL 345 ISSUE 6194 1251788-1
*All authors with their affiliations appear at the end of this paper.
†Corresponding author: K. X. Mayer (k.mayer@helmholtz-muenchen.
de)
Fig. 1. Schematic diagram of the relationships between wheat genomes with polyploidization his-
tory and genealogy. Names and nomenclature for the genomes are indicated within circles that provide
a schematic representation of the chromosomal complement for each species. Time estimates are from
Marcussen et al.(45). mya, million years ago.
development of large sets of single-nucleotide
polymorphism (SNP) markers (19–21). To date,
however, relatively little is known about the
position and distribution of genes on each of
the bread wheat chromosomes and their evo-
lution during the polyploidization events that
resulted in the emergence of the hexaploid
species.
Survey sequencing the bread
wheat genome
We used aneuploid bread wheat lines derived
from double ditelosomic stocks of the hexaploid
wheat cultivar Chinese Spring (22)toisolate,
sequence, and assemble de novo each individual
chromosome arm [except for 3B, which was iso-
latedandsequencedasacompletechromosome
(23)]. This approach reduced the complexity of
assembling a highly redundant genome and en-
abled the differentiation of genes present in
multiple copies and highly conserved homologs.
Each chromosome arm, representing between
1.3 and 3.3% of the genome (24), was purified by
flow-cytometric sorting and sequenced to a depth
of between 30× and 241× with Illumina technol-
ogy platforms (25). The paired end sequence reads
were assembled with the short-read de novo as-
sembly tool ABySS (25,26). A high proportion
of reads assembled into contigs of repetitive se-
quence less than 200 base pairs (bp) and were
excluded from the final assembly of 10.2 Gb.
The quality of the assemblies and purity of chro-
mosome arm preparations were assessed by using
alignment to bin-mapped ESTs (15) and to the
virtualbarleygenome(27). Summary statistics for
the chromosome arm assemblies are shown in
Tables 1 to 3. Compared with cytogenetically es-
timated chromosome sizes (24),thesequenceas-
semblies represent 61% of the genome sequence,
with the L50 of repeat-masked assemblies ranging
from 1.7 to 8.9 kb.
Repetitive DNA
We assessed the TE and sequence repeat space
across the whole wheat genome and compared
the repeat content of the A, B, and D subgenomes
(25). From the frequency of mathematically de-
fined repeats (MDRs; 20mers) (28), we estimated
that24to26%ofthesequencereadscontain
high copy number repeats, represented by 20mers
with more than 1000 copies. In total, 81% of raw
reads and 76.6% of assembled sequences con-
tained repeats, the latter showing reduced rep-
resentation of Gypsy long terminal repeat (LTR)
retrotransposons, as well as Mutator and Mariner-
type DNA transposons.
Analysis of the distribution of transposons
across the three subgenomes revealed that class
I elements (retroelements) were more abundant
in the A genome chromosomes relative to B or
D(A>B>D),whereasclassIIelements(DNA
transposons) showed the reverse (D > B > A).
The most pronounced differences were observed
between deteriorated and thus unclassifiable
LTR retrotransposons, which showed a gradient
of abundance across the subgenomes (A > D > B)
distinct from other class I or class II elements.
We hypothesize that unclassifiable LTR retrotrans-
posons represent older (and thus more deteri-
orated) elements that were modified through
polyploidization and ongoing TE amplification
or degeneration. Assuming the amplification/
degeneration dynamics are similar within each ge-
nome, the distribution of LTR retrotransposons
across the three subgenomes suggest that the
B genome progenitor contained a lower number
of LTR retroelements and that transposon activity
post-polyploidization has introduced a higher
proportion of more recentamplificationsinto
the B genome.
We observed a substantial reduction (down
to 19.6%) in the TE content associated with the
0.8% (615 Mb) of the chromosomal survey se-
quences (CSSs) representing contigs containing
high-confidence genes (for definition see below)
(25). The analysis revealed a marked depletion
of all class I elements in the neighborhood of
genes, with the exception of non-LTR retrotrans-
posons, which were enriched twofold. CACTA
transposons accounted for the greatest pro-
portion of the observed 67% reduction in class
II elements, whereas minor components, espe-
cially Harbinger and miniature inverted-repeat
TEs, were enriched. Selective exclusion of high-
copy transposons that undergo epigenetic silenc-
ing and reduce expression by heterochromatin
spreading (29) may result in depletion of repeat
element types in the vicinity of genes.
miRNAs
A total of 270 different putative microRNA mol-
ecules (miRNAs) (49 not previously reported)
1251788-2 18 JULY 2014 •VOL 345 ISSUE 6194 sciencemag.org SCIENCE
Table 1. Sequencing, assembly, and GenomeZipper statistics for wheat A genome chromosome arms. Sequence indicates the total assembled sequence
(>200 bp); number of contigs is after filtering of highly repetitive sequence assemblies; syntenic loci is the number of gene loci anchored to reference gene; and
the last row is the number of total anchored gene loci. Blank entries in all tables indicate data not applicable; fl-cDNA, full-length cDNA; nonred., nonredundant.
1AS 1AL 2AS 2AL 3AS 3AL 4AS 4AL 5AS 5AL 6AS 6AL 7AS 7AL ∑
Assembly
Chromosome
size (Mbp) 275 523 391 508 360 468 317 539 295 532 336 369 407 407 5,727
Sequence (Mbp) 178.1 250 255.2 328.2 201.8 247.2 282.3 362 198.8 318.1 219.2 214.4 198 252.4 3,505.7
Coverage (x-fold) 0.65 0.48 0.65 0.65 0.56 0.53 0.89 0.67 0.67 0.60 0.65 0.58 0.49 0.62 0.62
L50 (bp) 2,242 2,639 2,398 2,688 1,404 1,346 2,782 3,053 3,509 2,078 2,669 2,154 1,470 2,271
Repeat
No. of contigs 34,793 26,746 34,722 45,893 33,943 43,823 32,079 64,364 19,719 47,572 28,041 34,030 44,175 35,586 542,486
L50 4,769 6,369 6,678 6,677 3,846 3,789 7,499 6,601 8,713 5,355 7,091 6,589 4,397 5,849
GenomeZipper
No. of markers 147 380 139 278 106 332 167 200 150 309 174 286 169 278 3,115
No. of wheat
fl-cDNAs 95 241 162 258 134 240 153 189 54 231 94 181 178 155 2,365
No. of nonred.
contigs 937 1,750 1,673 2,499 1,323 2,300 848 2,613 574 2,495 811 1,422 2,100 1,600 22,945
No. of syntenic
gene loci 544 1,515 1,155 1,816 850 1,628 842 1,642 405 1,821 647 1,073 1,228 1,049 16,215
No. of anchored
gene loci 649 1,811 1,262 2,032 929 1,864 948 1,777 522 2,050 794 1,279 1,349 1,269 18,535
POP-Seq Positioning
No. of contigs 38,940 45,649 34,853 32,941 31,094 49,586 25,068 27,248 5,578 35,333 28,234 30,828 31,628 32,435 449,415
No. of anchored
gene loci 972 1,720 1,452 1,913 788 1,302 883 1,702 137 1,579 1,145 1,305 1,305 1,094 17,297
No. of anchored
gene loci 618 1,257 1,408 1,903 769 1,469 778 1,116 678 2,432 995 1,458 1,405 1,711 17,997
were identified corresponding to 98,068 pre-
dicted miRNA-coding loci (25). Only 1668 loci
(1.7%) evidenced expression on the basis of pub-
licly available ESTs and of RNA sequencing
(RNA-seq) data reported in this work, con-
sistent with previous analyses in wheat (30,31).
Similarly, we observed that class II DNA trans-
posons, specifically TcMar transposons, were
predominantly found in miRNAs. For 87 % of
the putative miRNA-coding loci, at least one
putative target gene was identified in the
wheat CSS. A total of 6615 predicted miRNA-
coding sequences (44 with evidence of expres-
sion) were characterized by at least one mature
sequence and one target site covered by the
same repeat element. This suggests that an
acti ve miRNA could arise when an advantageous
regulatory niche evolves from a series of random
SCIENCE sciencemag.org 18 JULY 2014 •VOL 345 ISSUE 6194 1251788-3
Table 3. Sequencing, assembly, and GenomeZipper statistics for wheat D genome chromosome arms. Sequence indicates the total assembled
sequence (>200 bp); number of contigs is after filtering of highly repetitive sequence assemblies; syntenic loci is the number of gene loci anchored to
reference gene; and the last row is the number of total anchored gene loci.
1DS 1DL 2DS 2DL 3DS 3DL 4DS 4DL 5DS 5DL 6DS 6DL 7DS 7DL ∑
Assembly
Chromosome
size (Mbp) 224 381 317 412 321 450 232 417 259 491 324 389 381 347 4,937
Sequence (Mbp) 128,2 254,4 166 261.6 145.4 186.5 142.1 347.6 148 236.8 156.6 199.8 209.1 222.9 2,805
Coverage (x-fold) 0.57 0.67 0.52 0.63 0.45 0.41 0.61 0.83 0.57 0.48 0.48 0.51 0.55 0.64 0.57
L50 (bp) 2,850 2561 1241 701 515 967 3278 1013 2,353 2,647 4,297 2,077 1,967 3,638
Repeat
No. of contigs 17,725 35,770 43,044 110,446 46,795 69,259 18,245 197,398 22,449 34,622 16,077 26,236 36,701 26,737 701,504
L50 6,622 6,297 4,635 3,247 1,697 2941 7428 1855 5945 7049 8,904 6,821 5,031 7,399
GenomeZipper
No. of markers 258 653 457 739 379 633 269 498 225 744 297 411 579 515 6,657
No. of wheat
fl-cDNAs 89 251 177 323 128 244 130 255 99 375 103 208 200 212 2,794
No. of nonred.
contigs 968 2,797 3,023 5,804 2,933 3,712 1,231 3,174 890 3,436 973 1,923 3,006 2,083 35,953
No. of syntenic
gene loci 474 1,483 1,197 2,141 799 1,575 779 1,277 454 2,073 538 1,117 1,222 1,099 16,228
No. of anchored
gene loci 642 1,882 1,475 2,542 1,051 1,923 912 1,582 598 2,482 758 1,347 1,592 1,423 20,209
POP-Seq Anchoring
No. of contigs 7,686 24,149 24,652 31,359 26,447 37,874 14,198 23,842 14,458 29,604 18,701 23,763 41,796 31,832 350,361
Table 2. Sequencing, assembly, and GenomeZipper statistics for wheat B genome chromosome arms. Sequence indicates the total assembled
sequence (>200 bp); number of contigs is after filtering of highly repetitive sequence assemblies; syntenic loci is the number of gene loci anchored to
reference gene; and the last row is the number of total anchored gene loci.
1BS 1BL 2BS 2BL 3B 4BS 4BL 5BS 5BL 6BS 6BL 7BS 7BL ∑
Assembly
Chromosome
size (Mbp)
314 535 422 506 993 391 430 290 580 415 498 360 540 6,274
Sequence (Mbp) 212.8 299.4 292 404.5 638.6 308.2 248.7 174.5 415.2 210.2 257.4 206.1 259.6 3,927.2
Coverage (x-fold) 0.68 0.56 0.69 0.80 0.64 0.79 0.58 0.60 0.72 0.51 0.52 0.57 0.48 0.63
L50 (bp) 3,287 3,120 3,711 2,941 2,655 3,463 1,974 3,315 2,924 2,366 2,031 2,428 1,556
Repeat
No. of contigs 26,050 29,783 35,743 75,879 75,022 38,515 46,576 18,001 75,887 29,566 35,727 24,119 58,554 569,422
L50 7,413 7,151 8,069 6,890 6,855 8,755 5,883 7,365 7,537 4,972 4,824 6,435 4,144
GenomeZipper
No. of markers 78 348 278 428 500 46 145 167 404 217 245 140 198 3,194
No. of wheat
fl-cDNAs 78 219 155 268 479 97 170 66 360 88 147 109 137 2,373
No. of nonred.
contigs 776 1,927 1,859 3,079 5,011 893 1,634 576 3,296 915 1,525 1,172 1,890 24,553
No. of syntenic
gene loci 485 1,485 1,181 1,973 3,123 788 1,155 426 2,315 565 1,003 733 1,050 16,282
No. of anchored
gene loci 546 1,745 1,388 2,265 3,490 819 1,243 565 2,600 728 1,177 838 1,203 18,607
POP-Seq Anchoring
No. of contigs 31,038 50,219 33,603 54,522 99,341 50,927 41,135 19,794 49,140 30,962 38,064 48,514 50,397 597,656
No. of anchored
gene loci
956 1,881 1,588 2,389 3,772 1,365 1,433 727 2,857 831 996 1,055 1251 21,101
TE insertions and may represent a means by
which a network of putative miRNAs and target
genes may develop, even before miRNA activa-
tion (32).
Protein-coding genes
Annotation of protein-coding gene sequences
in the CSS assemblies had its basis in com-
parisons to annotated genes in related grasses
[Brachypodium distachyon (33), Oryza sativa
(34), Sorghum bicolor (35), and Hordeum vulgare
(27)], as well as publically available wheat full-
length cDNAs (fl-cDNAs) (11)andRNA-seqdata
generated from five tissues of a Chinese Spring
cultivar a t three different developmental stages.
Briefly, the reference grass coding sequences
and wheat transcript resources were mapped
separately to assembled CSS contigs, and the
alignments were merged to define the exact co-
ordinates of gene loci, alternative splicing forms,
and transcripts with no similarity to related grass
genes (25).
This analysis identified 976,962 loci with
1,265,548 distinct splicing variants. A total of
133,090 loci showing homology to related grass
genes were classified as high confidence (HC)
gene calls. These were further subdivided into
four groups (HC1 to HC4) on the basis of the
proportion of the length of the reference gene
covered by a predicted locus. Of these, 124,201
(93.3%) genes were annotated on individual
chromosome arm sequences, and the remain-
ing 6.7% corresponded to wheat transcripts,
which were not detected in the CSS assem-
blies (Fig. 2A). In total, 55,249 (44%) of the loci
assigned to chromosomes were classified as
HC1, that is, representing functional genes span-
ning at least 70% of the length of the support-
ing evidence (Table 4). The remaining 56% of
HC genes comprised genes that were fragmented
in the assembly and thus could only be par-
tially structurally defined or were classified as
gene fragments and pseudogenes. We expect
that many of these will be merged as further
sequencing improves the coverage and quality
of genic sequences. On the basis of the level of
completion of the assembly and the detection
rate of HC1 genes (25), we estimated that the
wheat genome contains 106,000 functional protein-
coding genes. This supports gene number esti-
mates ranging between 32,000 and 38,000 for
each diploid subgenome in hexaploid wheat and
is consistent with findings in related diploid
species (16–18,20,36).
Consistent with observations of high levels of
non–protein-coding loci in both plants (27,37)
and animals (38), 890,576 loci did not share any,
or only low, similarity with related grass genes.
Loci with low sequence similarity (88,998) were
defined as low-confidence (LC) genes, and the
remainder were classified as repeat-associated,
noncoding, or non–homology-supported loci (25).
More than 96% of public wheat ESTs (HarvEST)
mappedtotheCSSgenesets(BLASTN;Evalue
<10
−10
), including 89% that correspond to HC
gene-coding loci, demonstrating that the CSS
assemblies contain a high representation of
the current gene inventory of the bread wheat
genome.
Our analysis revealed that 49% of the HC
genes exhibit alternative splicing (AS) with an
average of 2.6 transcripts per locus. This may be
an underestimation, because 69% of the most
complete gene loci (HC1) were alternatively spliced
with an average of 3.5 transcripts per locus.
Evidence that additional AS variants will be
identified has already emerged from a prelim-
inary assessment of gene structure prediction
using proteomics analyses. In a study of 63 genes,
50 (81%) structures were confirmed, 8 (13%) pro-
vided evidence for alternative gene structures,
whereas 5 were absent in the structural gene
calls. Extrapolating these data to the whole
genome, we estimate that hexaploid bread
wheat encodes more than 300,000 distinctive
protein-coding transcripts. The proportion of
genes exhibiting AS appeared to be similar in all
three subgenomes and is consistent with the
transcriptional complexity reported for plant
species such as Arabidopsis thaliana (39) and
H.vulgare (27).
Gene distribution and order
Analysis of the gene distribution across the three
subgenomes revealed a higher number of gene
lociontheBsubgenome(44,523;35%)compared
with the A and D subgenomes, which contained
40,253 (33%) and 39,425 (32%), respectively (Fig.
2A). This distribution was not consistent at the
chromosomal level. For example, the gene dis-
tribution across homeologous group 3 chromo-
somes is 30% 3A, 42% 3B, and 28% 3D, whereas
in homeologous group 7 the D genome contains
the highest proportion of genes. These observa-
tions may reflect preexisting differences in the
subgenomes before polyploidization or indicate
that drivers determining the composition of the
genome do not act at the subgenome level but
regionally.
Up to 2.4-fold variation in gene density was
observed on different chromosome arms, rang-
ing from 4.4 loci per Mb (5AS) up to 10.4 loci per
Mb (2DL) (Fig. 2B). Consistent with observations
in rye (40)andthecompletesequenceofwheat
chromosome 3B (23), on average 53.2% of the
1251788-4 18 JULY 2014 •VOL 345 ISSUE 6194 sciencemag.org SCIENCE
Fig. 2. Gene content, density, synteny, structural conservation, and tandemly duplicated genes.
(A) Total number of HC bread wheat genes identified on the A (green), B (purple), and D (orange) sub-
genomes (left) and their distribution on individual chromosome arms or chromosomes (in the case of
group 3) (right). (B) Syntenic conservation of HC and LC genes for each chromosome arm defined by the
ratio of the number of genes anchored in the GenomeZipper and the number of annotated genes
normalized per Mb of physical chromosome(-arm) size. Solid lines visualize average syntenic conservation
for LC (black) and HC (red) genes, and dashed lines give isochores for different percentages of synteny.
(C) Conservation of gene family composition between single chromosome arms. Color-coding in the outer
ring indicates relatedness of the respective branches (A/D > B, light orange; A/B > D, light blue; B/D > A,
light red). Red asterisks mark edges with boot-strapping values > 0.95. (D) Proportion of lineage-specific,
intrachromosomally duplicated genes in the wheat genome compared with other grass genomes. Error
bars indicate deviations among individual chromosomes.
HC genes were located on syntenic chromosomes
compared to B.distachyon (Bd), O.sativa (Os),
and S.bicolor (Sb). The average level of synteny
for genes located on the D genome chromosomes
(58%) was higher than the average for those
on the A (51%) and the B (50%) chromosomes.
Sequence conservation in LC genes is low, and,
in comparison to HC genes, reduced syntenic
conservation is observed. Thus, although the
majority of LC genes are likely to result from
the frequent generation of gene fragments by
double-strand repair mechanisms or are deter-
iorated (pseudo)genes that were fragmented after
the divergence from the other sequenced grass
genomes (10), the retained synteny to other grass
genomes suggests that some LC genes may be
functional.
To determine the extent of gene conservation
across homeologous chromosomes, we clustered
the HC genes into protein families by sequence
similarity (Fig. 2C) (25). With the exception of
chromosome 4AL, the genes on all chromosome
arms clustered with their corresponding homo-
logs. The pattern of clustering observed for 4A
is consistent with a known pericentromeric in-
version and two translocations of segments from
chromosome arms 5AL and 7BS (41,42). All
possible cluster topologies were found between
genes on the A, B, and D genomes. Overall, the
patterns of conservation suggest that the gene
content of the A and B homeologous chromo-
somesismoresimilartotheDgenomechro-
mosomes than to each other. This observation
contradicts a model of bifurcating evolutionary
relationships between the A, B, and D genomes
but is consistent with models of interlineage
hybridization (i.e., reticulate evolution) in the
Triticeae (43,44) and corroborate phylogenomic
analyses that suggest that the D genome is a
product of homoploid hybrid speciation between
A and B genome ancestors >5 million years ago
(45). Although the potential for preexisting dif-
ferences needs to be considered, the preserva-
tion of gene copies in each of the A, B, and D
genomes provides evidence for their structural
autonomy, a likely consequence of independent
pairing during meiosis (46). A high degree of
subgenome autonomy was also reflected in the
observed patterns of gene expression (see below).
We used two independent but complemen-
tary approaches to generate an order for the
many small contigs that comprise the chromo-
some arm assemblies (25). The GenomeZipper
approach (47) combines the syntenic conser-
vation of gene order in grasses (48) and the
known gene orders of fully sequenced grass
genomes (33–35) with high-density SNP-based
genetic maps (21,49)tocreateavirtualgeneorder
in wheat. The number of genes anchored per chro-
mosome (chr.) ranged from 2125 (chr. 6B) to 4404
(chr. 2D) (Table 1). Overall, the GenomeZipper
inferred positions of 21,221, 22,051, and 22,813
genes, respectively, in the A, B, and D genomes.
To complement this, the POPSEQ approach (50)
was used to build an ultradense genetic map
comprising 13.3 million SNPs identified after
shallow-coverage whole-genome sequencing of
90 doubled haploid individuals of the synthetic
W7984 × Opata M85 population (51). This map
assigned a partially overlapping set of 17,297,
21,101, and 17,997 HC genes, respectively, to the
individual chromosomes of the A, B, and D ge-
nomes. The POPSEQ genetic map showed concor-
dance with the gene assignments to flow-sorted
chromosomes (99.4%) and the GenomeZipper
(99.8%). The two inferred gene orders along chro-
mosomes were also largely collinear (Spearman’s
correlation coefficient = 0.85). From both an-
choreddatasets,wewereabletopositionanon-
redundant set of 75,183 HC genes on the 21
chromosomes of bread wheat by genetic map-
ping and/or syntenic conservation.
Gene duplication is frequently observed in plant
genomes, arising from polyploidization or through
tandem or segmental duplication associated with
replication (52). For each wheat chromosome, the
percentage of genes that have undergone lineage-
specific intrachromosomal duplication was deter-
mined with OrthoMCL (53). By using the HC1
genes, we estimated that between 19.1% (chr. 7B)
and 29.7% (chr. 2B) (23.6% average for all chro-
mosomes) of the genes are duplicated on each
chromosome (25). Comparison of the number
of duplicated genes identified by this analysis
for chr. 3B (25.3% of HC1 genes) with the 3B
reference pseudomolecule (37% duplicated genes)
(23) indicated that we are likely underestimating
the number of duplicated genes. This is due to
the fragmented nature of the assemblies obtained
from whole-genome or chromosome-shotgun se-
quences that collapse highly conserved duplicates.
No significant differences in the proportion of
duplicates were observed between the three sub-
genomes (c
2
test, c
2
=3.8,P=0.15).
For each chromosome, an average of 73% of the
duplicates are located on one of the chromosome
arms, suggesting that they may be tandem dupli-
cates that arise through unequal crossing-over
and replication-dependent chromosome break-
age (54)orthroughtheactivityoftransposable
elements. When compared with the percentage
of intrachromosomal duplicates found in rice,
sorghum, barley, maize, and foxtail millet (17 to
20%) (27,33–35,55,56), the proportion of gene
duplications in wheat was significantly higher
(Fig. 2D; Tukey’s honest significant difference,
pairwise P< 0.007).
Comparisons with related species
We assembled sequence data from seven species
related to progenitors of the bread wheat A, B,
and D subgenomes (25). Illumina whole-genome
sequence data and assemblies were generated from
two tetraploid wheat cultivars (AABB) T. turgidum
‘Cappelli’(originating from Italy) and T. turgidum
‘Strongfield’(originating from Canada) as well
as from the diploid genome of Ae. speltoides
(SS). These data were combined with whole-
genome sequence data from T. urartu (AA
uu
)
(16), T. monococcum (AA
mm
), Ae. tauschii (DD)
(17), and Aegilops sharonensis (S
sh
S
sh
). For the
unannotated genomes of T. turgidum,T. monococ-
cum,Ae. speltoides,andAe. sharonensis,pro-
teins of annotated grass genomes (27,33,35,57)
and T. aestivum gene models were projected on
the sequence assemblies.
Genes and gene families in the hexaploid,
tetraploid, and diploid genomes were then com-
pared to assess the dynamics of gene retention
or loss after polyploidization and to define the
core wheat genes. When comparing the sizes of
gene families in Ae. tauschii (17)andT. urartu
(16) diploid genomes with the individual subge-
nomes of hexaploid wheat (Fig. 3, A and B), we
foundthatgenelossmainlyaffectedgenesbe-
longing to expanded families, consistent with pre-
vious observations (18). In contrast, singletons
(i.e., genes without paralogous copies within the
same genome) were not usually subject to gene
loss after polyploidization. Pronounced variations
ofgenecopyretentionorlosspatternswereob-
served depending on the gene family considered.
Highly similar gene retention rates were found
for all bread wheat subgenomes in comparison to
Ae. tauschii and T. urartu [0.91 (A), 0.94 (B), and
0.89 (D) versus Ae. tauschii and 0.91 (A), 0.96 (B),
and 0.91 (D) versus T. urartu](Fig.3,AandB).
The extent of gene loss in the D subgenome, the
most recent addition to the hexaploid genome,
appeared slightly lower than the more ancient
A and B subgenomes. Thus, as observed for
SCIENCE sciencemag.org 18 JULY 2014 •VOL 345 ISSUE 6194 1251788-5
Table 4. Characteristics of HC bread wheat genes. Distinct exons means that exons of two or
more transcripts were counted once if they had identical start and stop positions; mean transcripts
and mean exons are transcripts per locus and exons per locus, respectively; the second mean exons
row shows exons per transcript.
HC1 HC2 HC3 HC4 S
Gene loci 55,249 14,367 15,475 39,110 124,201
Single exon 9,181 (17%) 3,230 (22%) 4,906 (32%) 20,375 (52%) 37,692 (30%)
Multiple exon 46,068 (83%) 11,137 (78%) 10,569 (68%) 18,735 (48%) 86,509 (70%)
Alternatively
spliced 38,059 (69%) 7,916 (55%) 6,465 (42%) 8,728 (22%) 61,168 (49%)
Mean size (bp) 3,319 2,204 1,608 901 2,216
Transcripts 194,624 37,116 31,957 61,450 325,147
Mean transcripts 3.52 2.58 2.07 1.57 2.62
Distinct exons 538,250 94,864 74,630 117,530 825,274
Mean exons 9.74 6.60 4.82 3.01 6.64
Mean exons
3
6.29 4.45 3.52 2.56 5.1
Mean size (bp) 321 315 314 281 314
the gene content and structural similarities be-
tween individual chromosome arms, we found
no evidence for a gradual gene loss induced by
polyploidization. This may indicate that gene loss
occurred rapidly after polyploid formation, fol-
lowed by stabilization of gene content consistent
with observations in newly created polyploids
(58,59)andgeneretentionincotton(60).
We conducted a clustering analysis of gene
families and determined the number of genes in
thebreadwheatsubgenomesthathaveanor-
tholog in the genomes from the A genome lineage
(T. urartu and T. monococcum), the closest known
relatives for the B lineage (Ae. sharonensis and
Ae. speltoides),theDlineage(Ae. tauschii), as
well as in the tetraploid T. turgidum genome
(Fig.3C).WefoundthattheA,B,andDsubge-
nomes contain very similar proportions of genes
(60.1 to 61.3%) with orthologs in all the related
diploid genomes. We also estimated the contribu-
tion of unique genes of the three subgenomes to
the bread wheat genome. Because the absence of
a particular gene in a single species could be due
to incomplete sequence coverage or assembly er-
rors,onlylineage-specificgenefamilyabsencewas
considered in the analysis. Only a small fraction of
the genes (1.3 to 1.7%) were specific to the A, B, or
D lineages, demarcating the likely upper estimate
of unique genes or gene families added to the
bread wheat gene complement by the individual
subgenomes.
High sequence similarity between genes in
the bread wheat subgenomes impedes efficient
marker development and the identification of
nonsynonymous sequence variations that can
potentially affect gene or protein functionality.
We delineated single-nucleotide variations (SNVs)
between the bread wheat genes and the diploid
and tetraploid related genomes and reconstructed
phylogenetic relationships by using unrooted par-
simony (Fig. 4A) (25). In total, 11,435 SNVs within
6498 genes were specific to bread wheat and
thus have likely been introduced after the sec-
ond polyploidization event. Although most rela-
tionships support the known phylogeny of wheat,
Ae. sharonensis was placed closer to the bread
wheat D subgenome and Ae. tauschii than to Ae.
speltoides and the B genome branch. This sug-
gests that the Sitopsis group, which includes Ae.
sharonensis and Ae. speltoides,isdeeplyfurcated
and related to both D and B genome branches.
The potential impact of all SNVs detected on
proteins was measured by using Grantham amino
acid substitution matrix scores (25,61). Most of
the substitutions (80.8%) in gene sequences were
conservative or moderately conservative and were
randomly distributed across all chromosomes.
However, bread wheat genes contained a higher
proportion of substitutions with a predicted large
impact on the protein functionality (i.e., moder-
ately radical and radical changes) compared with
their closest diploid or tetraploid relatives. This
points to gene redundancy in hexaploid bread
wheat enabling accelerated sequence evolution
and potentially the evolution of novel protein
functions.
We used the bread wheat gene annotation to
analyze the introduction of likely premature
stop codons in diploid and tetraploid related ge-
nomesasameasurefortherateanddegreeof
pseudogenization(Fig.4B).Usingonlythehighest
confidence genes (HC1), 290 (1.6%; T. turgidum A
genome versus T. aestivum A genome) to 636 (3 .6%;
Ae. sharonensi s versus T. aestivum Dgenome)
gene loci had characteristics of pseudogenization
in the respective related diploid genomes com-
pared with the respective bread wheat A, B, and
D subgenomes. Most of these likely pseudogen-
ized loci were specific to the respective genomes,
although overlapping candidate pseudogenized
loci were also observed. However, the numbers
of genes in these categories were small, ranging
from 0.1 to 0.7%. Similar inferred pseudogeniza-
tion rates were found in the A and B subgenomes
of T. turgidum [290 (1.6%) in the A genome and
395 (2.0%) in the B genome, respectively], indi-
cating no preferential pseudogenization or gene
loss in any of the subgenomes. The number of
pseudogenes observed in the D genome was sim-
ilar to that of the A and B subgenomes and their
diploid relatives, suggesting a rapid elimination
process for pseudogenes. These findings are con-
sistent with those from other plants, notably among
Arabidopsis ecotypes (62), and smaller-scale anal-
ysis of pseudogenization dynamics within the
bread wheat genome (63).
Earlier studies showed a high degree of gene
sequence similarity between A, B, and D bread
wheat subgenomes and their related diploid spe-
cies (6). We analyzed the sequence conservation
in bread wheat chromosomes compared to their
diploid and tetraploid relatives to test for inter-
genomic translocations or introgressions (Fig. 4C).
The sequences of genes were highly conserved,
exceeding 99% identity, between the hexaploid
subgenomes and their respective diploid relatives.
High levels of conservation, averaging 97%, were
also found between the A, B, and D lineages.
No gradients in sequence conservation were
apparent along the chromosomes for the most
closely related genomes. However, when compar-
ing more distant genomes (e.g., T. aestivum Dge-
nome versus T. urartu), higher levels of sequence
conservation were observed in genes located in
proximal, pericentromeric, and centromeric re-
gions. These results are consistent with findings
for the 3B pseudomolecule analysis that demon-
strated a partitioning of the chromosome with
variable telomeric regions and a more conserved
central chromosomal region (23). The most pro-
nounced deviation in gene sequence similarity
from the overall distribution is found for chr.
4A, which has undergone a recent inversion and
translocations from chrs. 5A and 7B (41,42)
(Fig. 4C). Other, smaller regions showing altered
similarity profiles were also observed on other
chromosomes (e.g., chrs. 2A and 7B) (25) sug-
gesting the presence of further small transloca-
tions or introgressionsthatmayhaveoccurred
after hybridization.
Hexaploid genome phylogeny
To further test the relatedness of the A, B, and D
subgenomes across the entire wheat genome, we
used syntenic gene alignments to estimate max-
imum likelihood phylogenetic trees. We obta ined
2269 trees and analyzed them for topological
variation. Across all chromosome groups, 40, 35,
and 25% of the gene phylogenies supported AD,
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Fig. 3. Gene conservation and the wheat pan- and core genes. (Aand B) Relationship between gene
family sizes in diploid Ae. tauschii (A) and T. urartu (B) and each subgenome of hexaploid bread wheat
(colors as in Fig. 2A). Boxes visualize the lower and upper quartiles of gene family sizes. Color intensity
indicates the number of gene families in the respective bin. The black line shows a 1:1 gene copy number
relationship for bread wheat, Ae. tauschii,andT. urartu, and colored lines show the regression fit for
observed gene family size in the wheat subgenomes. (C) Percentages of genes of the bread wheat
subgenomes that show significant sequence similarity to other genomes: Core genes correspond to genes
withhitstoallsubgenomesaswellastoT. turgidum and all diploid related progenitor genomes; shared
genes–T. aestivum are genes with hits to any other T. aestivum subgenome but not to T. turgidum or any
of the closest diploid relatives; shared genes–T. turgidum correspond to genes with hits to T. turgidum but
not to any of the closest diploid relatives; shared genes–lineage, with hits to the subgenome’s closest
relative genome but not to T. turgidum or any of the other closest related genomes.
BD, and AB as the closest pairs, respectively.
This genome-wide observation supports previ-
ous findings of discordant phylogenetic signals
within Aegilops and Triticum genera (6,43,45).
Some variation in genome relationships was
found among chromosomes: On group 4 chro-
mosomes, most gene trees supported BD as
closest pairs, whereas group 5 chromosomes
had similar numbers of AD and BD topologies
(AD = BD > AB). Distribution of variation in
phylogenetic signals across homeologous chro-
mosomes can help to better understand the na-
ture of the evolutionary processes underlying
such phylogenetic incongruence. Under incom-
plete lineage sorting and stochastic coalescence,
levels of phylogenetic incongruence will be cor-
related with recombination rates, whereas single
introgression events and limited recombination
are expected to generate local chromosome blocks
of homogenous phylogenetic signals. We used
the inferred gene orders from the GenomeZipper
to test for nonrandom distribution of phyloge-
netic signals along chromosomes. We were un-
able to consistently identify block structures larger
than would be expected by chance. However, it
is possible that the limitations of the inferred
geneorderhampertheabilitytodetectsuch
patterns.
Gene expression
Our study did not reveal any pronounced bias in
gene content, structure, or composition between
the different wheat subgenomes. In paleopolyploid
maize and soybean, transcriptional dominance
of genes derived from one progenitor genome
has been described (64–66). Previous analyses
have shown that rapid initiation of differential
expression of homeologous wheat genes occurs
upon polyploidization with a predominantly ad-
ditive mode (13,67). Sets of homeologous wheat
genes with only one copy present in each of the
subgenomes (triads) were used to test for differ-
ential expression at a genome-wide scale. Ex-
pression correlations were calculated for 6219
triads (18,657 genes) by using RNA-seq data from
five organs (leaf, root, grain, spike, and stem)
(Fig. 5A) (25). Whereas root-derived expression
clustered separately, genes expressed in stem,
leaves, grain, and spike clustered in a subgenome-
specific manner. This indicates that the indi-
vidual subgenomes exhibit a high degree of
regulatory and transcriptional autonomy, with
limited trans (inter-subgenome) regulation (68).
At a global level, the overall pairwise expression
correlation between subgenomes was very similar
(Fig. 5B), and no evidence for genome-wide tran-
scriptional dominance of an individual subge-
nome was observed.
By using hierarchical cluster analysis, we ag-
gregated expressed genes into 13 distinct groups.
These groups show predominant expression in
particular organs (e.g., groups III and XIII in
Fig. 5A) or in one of the subgenomes (e.g., groups
II, IX, and X in Fig. 5A). Pairwise comparisons
of individual expressed homeologous genes in
the groups revealed abundant transcriptional
dominance from specific subgenomes (Fig. 5B).
Overall, 1333 (21%) of the homeologous gene triads
showed an expression bias in one of the pairwise
comparisons, and we detected a similar number of
preferentially transcribed genes (378 to 393) in
each subgenome (permutation test; P<0.05).
For the individual transcriptional groups, how-
ever, between 2% (groups I, IV, and V) and 20%
(groups II and VI) of the genes were found to be
transcriptionally dominant.
These patterns of gene expression across the
three genomes contrast with patterns of gene ex-
pression reported in allopolyploid cotton (69,70);
mesopolyploid Brassica rapa (71); synthetic allo-
tetraploid Arabidopsis (72); and the paleopolyploid
maize genome (64), where one of the genomes
is more transcriptionally active than others. The
apparent autonomy of the three wheat subge-
nomes may be explained by the relatively recent
polyploidization. It may also be related to reg-
ulatory mechanisms that control the transcrip-
tional interplay of homeologous genomes to
balance expression of individual and groups of
genes. While maintaining subgenome-specific
expression profiles, a high degree of orchestration
and functional partitioning between homeologous
genes was also reported in grain development of
bread wheat (68) and has been attributed to the
rapid evolution of cis elements coupled to epi-
genetic mechanisms controlling gene expression
(68,73,74).
Gene family size variation
The relationship between genes important to
wheat adaptation, disease resistance, and end-
use functionality in hexaploid wheat and its
diploid relatives was examined for signs of adap-
tive evolution. These analyses identified three
distinct patterns: gene expansion, gene loss, or
independent gene evolution that may or may
not include expansion or loss. In some cases,
such as the genes containing a NB-ARC domain
characteristic of many plant disease-resistance
genes (75), we observed an expansion within a
single subgenome (Fig. 6A). Indeed, a substantial
expansion in Ae. tauschii,comparedwiththe
other diploid species and the D genome of hexa-
ploid wheat, is consistent with the rich reservoir
of disease-resistance genes known in this species
SCIENCE sciencemag.org 18 JULY 2014 •VOL 345 ISSUE 6194 1251788-7
Fig. 4. Molecular evolution of the wheat lineage. SNVs were identified for coding sequences of
bread wheat genes (TaAA, TaBB, and TaDD) against diploid T. monococcum (AA
mm
), T. urartu (AA
uu
),
Ae. speltoides (SS), Ae. sharonensis (SshSsh), Ae. tauschii (DD), and tetraploid T. turgidum (AABB).
(A) Unrooted phylogeny constructed on the basis of SNVs between bread wheat and its diploid or
tetraploid relatives. The respective numbe r of SNVs in each phylogenetic internodes is indicated with
bar charts (scale at bottom left corner); colors indicate the respective bread wheat subgenome as in
Fig. 2A. (B) Genes with stop codons in the respective related diploid genomes in comparison to the
bread wheat A, B, and D subgenomes. Numbers in node connectors or in the center correspond to
the number of introduced stop codons found in two (node connectors) or all (center) related genomes.
(C) Chromosomal distribution of sequence identity between bread wheat genes and the diploid and
tetraploid relatives for homeologous chromosomes.
(17). In genes coding for the cysteine-rich gliadin
domain, a functional domain characteristic of
storage proteins, we observed a similar number
of genes in all diploid genomes (except T. monococ-
cum) that is higher than the number of genes
found in each of the three hexaploid wheat sub-
genomes (Fig. 6B). This may indicate that gene
loss occurred in hexaploid wheat and that there
is a trend for the gliadin gene family to maintain
some homeostasis with a similar global number
of genes in polyploid and diploid wheat. In other
cases, the patterns observed suggested indepen-
dent evolution of gene families within the different
genomes and subgenomes of wheat. This was seen
for genes associated with abiotic stress tolerance.
For example, for genes encoding the Apetala2
(AP2) DNA binding domain, associated with
drought, heat, salinity, and cold stress–tolerance
responses, we observed fewer AP2 genes in the
A and D genomes of Chinese Spring compared
with the diploid relatives or the B subgenome
(Fig. 6C). Likewise, genes coding for MYB tran-
scription factors, which have also been involved
in abiotic stress response in plants (76), were
underrepresented in the A subgenome of hexa-
ploid wheat and T. monococcum, whereas a higher
frequency was observed in Ae. tauschii (17)and
T. urartu (16)(Fig.6D).
In contrast, there was no evidence of expan-
sion or loss of genes underlying phenology, such
as the vernalization (Vrn1) and photoperiod re-
sponse regulator (Ppd1) genes that differentiate
spring and winter growth habits and sensitivity
to day length, respectively. Similar numbers of
genes were found in the diploids and hexaploid
subgenomes coding for the two functional do-
mains of Vrn1, a MADS-box and K-box domain
(77) (Fig. 6E), and for genes containing the re-
sponse regulator domain and CCT motif typical
of cereal Ppd genes (78) (Fig. 6F). We identified
an additional copy of a Vrn1-like gene in the
hexaploid Chinese Spring A and D genomes
and T. urartu (16) when compared with the re-
maining diploid species. An additional copy of
aPpd1-likegenewasalsoidentifiedintheChi-
nese Spring B genome relative to Ae. sharonesis
and Ae. speltoides (Fig. 6F). Although only small
differences were observed, small increases in
copy number variation of Vrn-A1 (A genome)
and Ppd-B1 (B genome) have been associated
with longer periods of vernalization to potenti-
ate flowering and an early flowering day neutral
phenotype, respectively (79). Thus, the relative
distribution of such patterns in ontology of these
two genes is likely to reflect important factors
that have allowed wheat to adjust its flower-
ing time to adapt to a range of environmental
conditions.
Molecular markers
Wheat improvement relies in part on the use of
molecular markers to improve selection efficien-
cies and to allow the precise transfer of genes
and QTL between different genetic backgrounds.
To enhance the CSS as a genomic resource for
the wheat genetics and breeding community, we
anchored all publicly available DNA markers
that are routinely used for genetic mapping and
marker-assisted breeding in wheat. Because the
majority of these markers are anchored to pheno-
typic maps, anchoring them to the CSS allows
immediate association of CSS to traits targeted
by breeders. In addition, insertion site–based poly-
morphism (ISBP) and SNP markers identified from
recent whole-genome shotgun and transcriptome
sequencing (19) and genotyping by sequencing
(GBS) tags identified by using DArTSeq (Diversity
Arrays Technology, Bruce, Australia) technology
were also anchored. In total, over 3.6 million
marker loci were anchored to the CSS, includ-
ing 1,347,669 marker loci and 2,310,988 SNPs
(Table 5).
Most marker types showed a distribution gra-
dient across subgenomes, with the highest num-
ber associated with the B genome chromosomes
and the lowest with the D genome, reflecting the
differences in the level of polymorphism in these
subgenomes. The proportions of ISBPs, SNPs de-
tected from cultivar sequencing and GBS tags
localized to the D genome ranged between 9.3
and 12%, with the lowest numbers mapping to
the group 4 chromosomes (Table 5). Two hundred
and ninety-two of 1867 simple sequence repeat
(SSR) loci were successfully anchored to the CSS
survey sequence. This low number is not surpris-
ing, given that these loci derive from repetitive AT-
and GC-rich sequences that may be collapsed or
1251788-8 18 JULY 2014 •VOL 345 ISSUE 6194 sciencemag.org SCIENCE
Fig. 6. Sizes of selected gene families and protein domains among hexaploid wheat and diploid
relatives. (A) NB-ARC domain, (B) cysteine-rich gliadin domain, (C)AP2domain,(D) MYB domain,
(E)Vrn1 (MADS-box/K-box domain), and (F)Ppd (photoperiod response regulator/CCT domain).
Fig. 5. Subgenome transcriptional profiling for individual wheat tissues. (A) Two-dimensional hier-
archical cluster analysis of single-copy wheat homeologous gene expression (colors as in Fig. 2A)
compared with organ-specific gene expression. (B) Analysis of log
2
-fold changes in pairwise gene
expression between homeologous genes (averaged across organs). Top graphs depict the distributions
of log
2
fold changes. Dot plots show the fold changes for each triplet ordered as shown in the yaxis in
(A). Colored dots highlight homologs that show significant differential expression (P< 0.05). The
numbers of differentially expressed triplets across all organs are shown at the bottom of the figure.
represented by uneven read coverage in Illumina
sequences (80).
Well over 70 DNA markers are routinely de-
ployed by breeders for agronomic, pest resistance,
and end-use quality, and most are available in
the public domain (http://maswheat.ucdavis.edu).
Anchoring of these to the CSS would facilitate
identification of SNP markers for development
of high-density marker maps, as a resource of
correlated markers, and to aid map-based cloning
of genes underlying important traits. In total,
we anchored 68 of these markers to 74 contigs in
theCSS.TheapplicationoftheCSSinmarker
improvement was demonstrated with the CAPS
(cleaved amplified polymorphic sequence) marker
Usw47,whichislinkedtoCdu-B1,agenerespon-
sible for reduced grain cadmium content in tetra-
ploid wheat (81,82). Although Usw47 is routinely
used in marker-assisted selection, it is not amen-
able to high-throughput genotyping. Alignment of
the Usw47 sequence against the CSS mapped it
to contig 5BL-10759151. This and eight neigh-
boring contigs in the GenomeZipper contained
33 SNP markers, of which 5 were polymorphic
in a doubled haploid mapping population used
previously to localize Cdu-B1.OfthefiveSNP
markers, two co-segregated, and the remainder
flanked the gene by a single recombination event.
These SNP markers can be readily implemented
now in a high-throughput fashion to select for
reduced grain cadmium content within breeding
programs.
Conclusion
We present the ordered and structured draft
sequence of the bread wheat genome as well as
a comparison between eight related wheat ge-
nomes. We defined a gene catalog for each of the
21 bread wheat chromosomes and positioned
more than 75,000 genes along the chromosomes
by using a combination of high-density wheat SNP
mapping and synteny to sequenced grass ge-
nomes. In contrast to other species (83), poly-
ploidization events in wheat did not cause a
“genome shock”with subsequent rapid genome
changes or functional dominance of one sub-
genome over the others. Intraspecific compara-
tive analyses revealed a dynamic wheat genome
with a high level of plasticity and a changing
gene repertoire shaped by gene losses and gene-
family expansions in all wheat genomes and sub-
genomes, with only a few species-specific genes.
Through interspecific comparisons, we observed
a higher abundance of intrachromosomal gene
duplications in wheat compared with other grass
genomes, which may be a mechanism for func-
tional adaptation and underlie the global suc-
cess of wheat as a cultivated crop.
The detection, chromosomal assignment, and
description of a large proportion of the gene
complement of bread wheat and their positional
assignment on chromosome arms is a major
milestone in facilitating the isolation of genes
underlying agronomically important traits, pro-
viding a reference for future integration into
systems biology, and improving wheat breeding
efficiency. Already, the resources developed in this
work have been used to support the analysis of
selected wheat chromosomes (20,41,84–86).
Last, as demonstrated by the completion of
the reference sequence for chr. 3B (23), this
draft genome sequence and complementary re-
sources will support the assembly and annotation
of the physical map–based reference sequen-
ces for the 21 bread wheat chromosomes.
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Table 5. Number and type of molecular markers mapped on individual chromosomes of the bread wheat genome.
Bin mapped
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Mapped queries 16,876 2,435 282 5,228 5,136 80,820 18,515
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2A 1,614 257 28 356 544 17,502 1,378 84,440 18,349 148,204 272,672
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5A 1,189 155 46 256 343 13,099 893 62,193 12,624 115,085 205,883
6A 1,150 132 63 418 421 12,072 1,127 60,169 15,884 110,850 202,286
7A 1,240 146 120 321 326 13,168 1,474 71,597 15,516 154,748 258,656
∑A
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∑B
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6D 1,132 91 135 289 240 10,504 417 12,042 3,609 23,341 51,800
7D 1,461 230 139 862 243 12,826 767 18,174 3,969 34,344 73,015
∑D
genome 8,726 1,420 428 3,016 1,830 87,606 3,668 101,760 25,420 183,393 417,267
∑28,469 4,069 1,235 7,881 7,609 281,543 24,408 1,058,517 235,213 2,009,713 3,658,657
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ACKNOWL EDGME NTS
The authors would like to thank Graminor AS; Biogemma; Institut
National de la Recherche Agronomique (INRA); International Center
for Agricultural Research in the Dry Areas; Department of
Biotechnology, Ministry of Science and Technology, Government of
India (chr. 2A; grant no. BT/IWGSC/03/TF/2008); and the
Biotechnology and Biological Sciences Research Council (BBSRC UK)
for funding the chromosome sequencing at the Genome Analysis
Centre. Chromosome sequencing at other centers was funded by the
following: chr. 3A—U.S. Department of Agriculture Agriculture and
Food Research Initiative (USDA AFRI) Triticeae-CAP (2011-68002-
30029) and the Kansas Wheat Commission; chr. 3B—grants from the
French National Research Agency (ANR-09- GENM-025 3BSEQ) and
France Agrimer; chr. 6B—grants from the Ministry of Agriculture,
Forestry and Fisheries of Japan “Genomics for agricultural innovation
KGS-1003,1004”,“Genomics based technology for agricultural
improvement, NGB- 1003,”and Nisshin Fl ou r Milling Incorporated; chr.
6D and Triticum durum cv. Strongfield—grants from Genome Canada,
Genome Prairie, University of Saskatchewan Ministry of Agriculture,
Western Grains Research Foundation; chr. 7B—grant no. 199387 from
the Norwegian Research Council and from Graminor AS; chr. 7A and
7D sequence reads were provided by D.E.. Chromosome flow sorting
and DNA preparation was supported through grants P501/12/G090
and P501/12/2554 from the Czech Science foundation. Chromosome
sequence assembly was supported by the BBSRC (UK). K.F.X.M.
acknowledges grants from the German Ministry for Education and
Research (BMBF) Plant2030, TRITEX, Deutsche
Forschungsgemeinschaft (DFG) SFB 924, and EC Transplant. K.E. and
J.R. are supported by sponsors of the IWGSC, which include Arcadia
Biosciences, Australian Centre for Plant Functional Genomics,
Biogemma, Bayer CropScience, Commonwealth Science and
Industrial Research Organisation, Centro Internacional de
Mejoramiento de Maíz y Trigo, Céréales Vallée, Dow AgroSciences,
Dupont, Evogene, Florimond Desprez, Grains Research and
Development Corporation, Graminor, Heartland Plant Innovation,
INRA, KWS, Kansas Wheat Commission, Limagrain, Monsanto, RAGT,
and Syngenta. N.G. is supported by European Commission Marie
Curie Actions (FP7-MC-IIF-Noncollinear Genes). T.W. is supported by
the Swiss National Foundation and P.F., M.C., A.M.S., and L.C. are
supported by the Italian Ministry of Agriculture special project
“MAPPA-5A.”H.B. acknowledges funding from Sabanci University and
the Scientific and Technological Research Council of Turkey. B.W. and
B.S. were funded by the Gatsby Charitable Foundation and the
BBSRC (UK) Grant BB/J003166/1. R.W. is a Trustee Director of
TGAC, Norwich, UK, and A.K. is a shareholder of Diversity Arrays
Technology Pty Ltd. The POPSeq analysis carried out by the U.S.
Department of Energy Joint Genome Institute was supported by the
Office of Science of the U.S. Department of Energy under contract no.
DE-AC02-05CH11231. Additional support for the work was funded
from the Triticeae-CAP, USDA AFRI (2011-68002-30029) to G.J.M.;
the Scottish Government Rural and Environment Science and
Analytical Services Division Research Programme to R.W.; and the
German Ministry of Research and Education (BMBF TRITEX 0315954)
to N.S. Sequence reads and assembled sequences are available at
European Molecular Biology Laboratory/GenBank/DNA Data Bank of
Japan short read archives and sequence repositories, respectively
(PRJEB3955—whole-genome sequences of T. aestivum ‘Chinese
Spring,’T. urartu,Ae. speltoides,Ae. tauschii,T. turgidum;
SRP004490.3—whole-genome sequencing of T. monococcum;
SRP004490—whole-genome sequencing of Ae. tauschii;PRJEB4849
—whole-genome sequences of Ae. sharonensis; PRJEB4750—T.
aestivum RNA-seq data; SRP037990—T. aestivum SynOpDH
mapping population; SRP037781—T. aestivum synthetic opata M85;
SRP037994—T. aestivum synthetic W7984). All data can be accessed
via the IWGSC repository at Unité de Rercherche Génomique Info:
http://wheat-urgi.versailles.inra.fr/Seq-Repository/.
The International Wheat Genome Sequencing Consortium (IWGSC)
Authorship of this paper should be cited as “International Wheat
Genome Sequencing Consortium.”Participants are arranged by
working group. Corresponding authors (*), major contributors (†), and
equally contributing authors (‡)areindicated.
Principal Investigators: Klaus F. X. Mayer
1
* (k.mayer@helmholtz-muenchen.
de), Jane Rogers
2
* (janerogersh@gmail.com), Jaroslav Doležel
3
*
(dolezel@ueb.cas.cz), Curtis Pozniak
4
* (curtis.pozniak@usask.ca),
Kellye Eversole
2
* (eversole@eversoleassociates.com), Catherine Feuillet
5
*
(catherine.feuillet@bayer.com)
Provision of seed material for ditelosomic wheat lines: Bikram
Gill,
6
Bernd Friebe,
6
Adam J. Lukaszewski,
7
Pierre Sourdille,
14
Takashi R Endo
8
Chromosome sorting and DNA preparation: Jaroslav Doležel,
3
†
Marie Kubaláková,
3
Jarmila Číhalíková,
3
Zdeňka Dubská,
3
Jan Vrána,
3
Romana Šperková,
3
Hana Šimková
3
DNA sequencing: Jane Rogers,
2
†Melanie Febrer,
9
Leah Clissold,
10
Kirsten McLay,
10
Kuldeep Singh,
11
Parveen Chhuneja,
11
Nagendra K. Singh,
12
Jitendra Khurana,
13
Eduard Akhunov,
6
Frédéric Choulet,
14
Pierre Sourdille,
14
Catherine Feuillet,
5
Adriana Alberti,
15
Valérie Barbe,
15
Patrick Wincker,
15
Hiroyuki Kanamori,
16
Fuminori Kobayashi,
16
Takeshi Itoh,
16
Takashi
Matsumoto,
16
Hiroaki Sakai,
16
Tsuyoshi Tanaka,
16
Jianzhong Wu,
16
Yasunari Ogihara,
17
Hirokazu Handa,
16
Curtis Pozniak,
4
P. Ron Maclachlan,
4
Andrew Sharpe,
18
Darrin Klassen,
18
David Edwards,
19
Jacqueline Batley,
19
Odd-Arne Olsen,
20,21
Simen Rød Sandve,
20
Sigbjørn Lien,
37
Burkhard
Steuernagel,
22
Brande Wulff
22
DNA sequence assembly: Mario Caccamo,
10
†Sarah Ayling,
10
Ricardo H. Ramirez-Gonzalez,
10
Bernardo J. Clavijo,
10
Burkhard
Steuernagel,
22
Jonathan Wright
10
Gene annotation: Matthias Pfeifer,
1
Manuel Spannagl,
1
KlausF.X.Mayer
1
†
Genome Zipping: Mihaela M. Martis,
1
Eduard Akhunov,
6
Frédéric
Choulet,
14
Klaus F. X. Mayer
1
†
POPSEQ analysis: Martin Mascher,
23
Jarrod Chapman,
24
Jesse A.
Poland,
25
Uwe Scholz,
23
Kerrie Barry,
24
Robbie Waugh,
26
Daniel S.
Rokhsar,
24
Gary J. Muehlbauer,
27
Nils Stein
28
Repetitive DNA analysis: Heidrun Gundlach,
1
Matthias Zytnicki,
29
Véronique Jamilloux,
29
Hadi Quesneville,
29
Thomas Wicker,
30
KlausF.X.Mayer
1
miRNAs: Primetta Faccioli,
31
‡MorenoColaiacovo,
31
‡Matthias Pfeifer,
1
‡
Antonio Michele Stanca,
31
Hikmet Budak,
32
Luigi Cattivelli
31
†
Genome structure and duplications: Natasha Glover,
14
Mihaela M.
Martis,
1
Frédéric Choulet,
14
Catherine Feuillet,
5
Klaus F. X. Mayer
1
Transcriptome sequencing and expression analysis: Matthias
Pfeifer,
1
Lise Pingault,
14
Klaus F. X. Mayer,
1
†Etienne Paux
14
†
Gene family analysis: Manuel Spannagl,
1
Sapna Sharma,
1
Klaus F. X.
Mayer,
1
†Curtis Pozniak
4
†
Proteogenomics analysis: Rudi Appels,
33
†Matthew Bellgard,
33
Brett Chapman,
33
Matthias Pfeifer
1
Comparative analysis of diploid, tetraploid and hexaploid wheat:
Matthias Pfeifer,
1
Simen Rød Sandve,
20
Thomas Nussbaumer,
1
Kai Christian
Bader,
1
Frédéric Choulet,
14
Catherine Feuillet,
5
Klaus F. X. Mayer
1
†
Development and mappingof marker sets: Eduard Akhunov,
6
Etienne
Paux,
14
Hélène Rimbert,
36
Shichen Wang,
6
Jesse A. Poland,
25
Ron
Knox,
34
Andrzej Kilian,
35
Curtis Pozniak
4
†
Sequence repository: Michael Alaux,
29
†Françoise Alfama,
29
Loïc
Couderc,
29
Véronique Jamilloux,
29
Nicolas Guilhot,
14
Claire Viseux,
29
Mikaël Loaec,
29
Hadi Quesneville
29
Study design: Jane Rogers,
2
Jaroslav Doležel,
3
Kellye Eversole,
2
Catherine Feuillet,
5
Beat Keller,
30
Klaus F. X. Mayer,
1
Odd-Arne
Olsen,
20,21
Sebastien Praud
36
1
Plant Genome and Systems Biology, Helmholtz Zentrum Munich,
Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.
2
IWGSC,
Eversole Associates, 5207 Wyoming Road, Bethesda, MD 20816,
USA.
3
Institute of Experimental Botany, Center of Plant Structural
and Functional Genomics, Šlechtitelů31, 783 71 Olomouc, Czech
Republic.
4
Crop Development Centre, Department of Plant Sciences,
College of Agricultureand Bioresources, University of Saskatchewan, 51
Campus Drive, Saskatoon, SK, Canada.
5
Bayer Crop Science, 3500
Paramount Parkway, Morrisville, NC 27560, USA.
6
Kansas State
University, Department of Plant Pathology, Manhattan, KS 66506–
5502, USA.
7
College of Natural and Agricultural Sciences, Botany and
Plant Sciences, University of California, Riverside, CA 92521, USA.
8
Laboratory of Plant Genetics, Graduate School of Agriculture, Kyoto
University, Kyoto 606-8502, Japan.
9
Genomic Sequencing Unit, University
of Dundee, Dow Street, Dundee DD1 5EH, UK.
10
Genome Analysis Centre,
Norwich Research Park, Norwich, NR4 7UH, UK.
11
School of Agrictural
Biotechnology, Punjab Agricultural University, Ludhiana 141 004, India.
12
National Research Centre on Plant Biotechnology, Indian Agricultural
Research Institute, New Delhi 110 012, India.
13
Interdisciplinary Centre for
PlantGenomicsand Department of Plant Molecular Biology, University
of Delhi, South Campus, New Delhi 110 021, India.
14
INRA–University
Blaise Pascal UMR1095 Genetics, Diversity and Ecophysiology of
Cereals, 5 chemin de Beaulieu, 63039 Clermont-Ferrand, France.
15
Commissariat à l’EnergieAtomiqueGenoscope,CentreNationalde
Séquençage, 2 rue Gaston Crémieux, CP5706, 91057 Evry, France.
16
Plant Genome Research Unit, National Institute of Agrobiological
Sciences,2-1-2,Kan-non-dai,Tsukuba305-8602,Japan.
17
Kihara Institute
for Biological Research, Yokohama City University, Maioka-cho 641-12,
Totsuka-ku, 244-0813 Yokohama, Japan.
18
National Research Council
Canada, 110 Gymnasium Place, Saskatoon, SK, S7N 0W9, Canada.
19
Australian Centre for Plant Functional Genomics, School of Agriculture
and Food Sciences, University of Queensland, St. Lucia, QLD 4072,
Australia, and School of Plant Biology, University of Western Australia,
WA 6009, Australia.
20
Department of Plant Sciences, Center for
Integrative Genetics (CIGENE), Norwegian University of Life Sciences,
1432 Ås, Norw ay.
21
Department of Natural Science and Technology,
Hedmark University College, N-2318, Norway.
22
Sainsbury Laboratory,
Norwich Research Park, Norwich, NR4 7UH, UK.
23
Bioinformatics and
Information Technology, Leibniz Institute o f Plant Genetics and Crop
Plant Research (IPK), D-06466 Seeland OT Gatersleben, Germany.
24
U.S. Department of Energy Joint Genome Institute, 2800 Mitchell
Drive, WalnutCreek, CA 94598, USA.
25
USDA-ARSHard Winter Wheat
Genetics Research Unit and Department of Agronomy, Kansas State
University, Manhattan, KS 66506-5502, USA.
26
James Hutton Institute,
Invergowrie, Dundee DD2 5DA, UK.
27
Department of Agronomy and
Plant Genetics, Department of Plant Biology, University of Minnesota,
St. Paul, MN 55108, USA.
28
Genome Diversity, Leibniz Institute of
Plant Genetics and Crop Plant Research (IPK), D-06466 Seeland OT
Gatersleben, Germany.
29
INRA, UR1164 URGI–Research Unit in Genomics-
Info, INRA de Versailles, Route de Saint-Cyr, Versailles, 78026, France.
30
Institute of Plant Biology, Universityof Zurich,Zollikerstrasse 107, CH-
8008 Zurich, Switzerland.
31
Consiglio per la Ricerca e la sperimentazione in
Agricoltura–Genomics Research Centre, via San Protaso 302, I-29017
Fiorenzuola d’Arda, Italy.
32
SabanciUniversityBiologicalSciencesand
Bioengineering Program, 34956 Istanbul, Turkey.
33
Centre for Comparative
Genomics, Murdoch University, Perth, WA 6150, Australia.
34
Semiarid
Prairie Agricultural Research Centre, Post Office Box 1030, Swift
Current, Saskatchewan S9H 3X2, Canada.
35
Diversity Arrays Technology
Pty Limited, 1 Wilf Crane Crescent, Yarralumla ACT2600, Australia.
36
Biogemma, Centre de Recherche de Chappes, Route d’Ennezat,
63720 Chappes, France.
37
Department of Animal and Aquicultural
Sciences, CIGENE, Norwegian University of Life Sciences, Arboretvelen
6, 1432 Ås, Norway.
Supplementary Materials
www.sciencemag.org/content/345/6194/1251788/suppl/DC1
Materials and Methods
Supplementary Text
Figs. S1 to S60
Tables S1 to S48
References (88–160)
5 February 2014; accepted 2 June 2014
10.1126/science.1251788
SCIENCE sciencemag.org 18 JULY 2014 •VOL 345 ISSUE 6194 1251788-11
