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Linkage maps from multiple genetic crosses and
loci linked to growth-related virulent phenotype
in Plasmodium yoelii
Jian Li
a,b,1
, Sittiporn Pattaradilokrat
b,1
, Feng Zhu
a,1
, Hongying Jiang
b
, Shengfa Liu
a
, Lingxian Hong
a
, Yong Fu
c
, Lily Koo
d
,
Wenyue Xu
c
, Weiqing Pan
e
, Jane M. Carlton
f
, Osamu Kaneko
g
, Richard Carter
h
, John C. Wootton
i
, and Xin-zhuan Su
b,2
a
State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361005, People’s Republic of China;
b
Laboratory of
Malaria and Vector Research, and
d
Research Technologies Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health,
Bethesda, MD 20892;
c
Department of Pathogenic Biology, Third Military Medical University, Chongqing 400038, People’s Republic of China;
e
Department of
Pathogen Biology, Second Military Medical University, Shanghai 200433, People’s Republic of China;
f
Department of Medical Parasitology, Langone Medical
Center, New York University, New York, NY 10010;
g
Department of Protozoology, Institute of Tropical Medicine and the Global Center of Excellence Program,
Nagasaki University, Nagasaki 852-8523, Japan;
h
Division of Biological Sciences, Institute of Cell, Animal and Population Biology, Ashworth Laboratories,
University of Edinburgh, Edinburgh EH9 3JT, United Kingdom; and
i
Computational Biology Branch, National Center for Biotechnology Information, National
Library of Medicine, National Institutes of Health, Bethesda, MD 20894
Edited by Thomas E. Wellems, National Institutes of Health, Bethesda, MD, and approved May 27, 2011 (received for review February 9, 2011)
Plasmodium yoelii is an excellent model for studying malaria path-
ogenesis that is often intractable to investigate using human para-
sites; however, genetic studies of the parasite have been hindered
by lack of genome-wide linkage resources. Here, we performed 14
genetic crosses between three pairs of P. yoelii clones/subspecies,
isolated 75 independent recombinant progeny from the crosses,
and constructed a high-resolution linkage map for this parasite.
Microsatellite genotypes from the progeny formed 14 linkage
groups belonging to the 14 parasite chromosomes, allowing assign-
ment of sequence contigs to chromosomes. Growth-related virulent
phenotypes from 25 progeny of one of the crosses were signifi-
cantly associated with a major locus on chromosome 13 and with
two secondary loci on chromosomes 7 and 10. The chromosome 10
and 13 loci are both linked to day 5 parasitemia, and their effects on
parasite growth rate are independent but additive. The locus on
chromosome 7 is associated with day 10 parasitemia. The chromo-
some 13 locus spans ∼220 kb of DNA containing 51 predicted genes,
including the P. yoelii erythrocyte binding ligand, in which a C741Y
substitution in the R6 domain is implicated in the change of growth
rate. Similarly, the chromosome 10 locus spans ∼234 kb with 71
candidate genes, containing a member of the 235-kDa rhoptry pro-
teins (Py235) that can bind to the erythrocyte surface membrane.
Atypical virulent phenotypes among the progeny were also ob-
served. This study provides critical tools and information for genetic
investigations of virulence and biology of P. yoelii.
genetic mapping
|
inheritance
|
crossover
|
rodent
The rodent malaria parasite Plasmodium yoelii is an important
model for studying malaria biology and pathogenesis. Because
a malaria disease phenotype represents the outcome of the host-
parasite interaction, the use of inbred mice to control host genetic
background variation is critical for studying the influence of par-
asite virulent factors on a disease phenotype. Many genetically
distinct (or similar) strains of P. yoelii and subspecies exhibiting
a wide range of variations in growth rate and pathogenicity in their
rodent hosts are available, which can be explored for studying
disease and/or growth phenotypes. Compared with Plasmodium
falciparum and Plasmodium chabaudi chabaudi (1–3), however,
genetic studies in P. yoelii have been limited (2, 4, 5), partly be-
cause of the lack of genetic markers and well-characterized phe-
notypes. Recently, hundreds of polymorphic microsatellite (MS)
markers have been developed from the P. yoelii genome (6), set-
ting the stage for development of genome-wide genetic maps for
this parasite. Additionally, a strategy called linkage group selec-
tion (LGS) was developed to map the determinants affecting se-
lectable rodent malaria traits (2, 7). Indeed, a C713R substitution
in the gene encoding the P. y. yoelii erythrocyte binding ligand
(PyEBL) was recently linked to parasite growth rate and virulence
using the LGS technique, although other determinants are likely
to play a role (8, 9). [Note: There are three subspecies of P. yoelii
(P. yoelii yoelii, P. yoelii nigeriensis, and P. yoelii killicki) and two
subspecies of P. chabaudi (P. chabaudi chabaudi and P. chabaudi
adami). P. yoelii is used here to refer generally to P. yoelii lines and
subspecies; subspecies and lines will be specified in the text when
necessary.] For mapping genes affecting complex traits or pheno-
types that cannot be selected, however, evaluation of phenotypes
from individual progeny of genetic crosses is necessary. De-
velopment of a genetic map and collection of genetic cross progeny
with differences in disease phenotypes will provide important tools
for studying such malaria disease phenotypes in detail.
Although the P. y. yoelii genome was the first rodent malaria
parasite genome sequenced, the assembly is still fragmented be-
cause of the currently low coverage and lack of a genetic map to
guide the assembly (10). Recently, a rodent malaria syntenic map
was constructed based on genomic sequences from three rodent
malaria parasites (P. y. yoelii,P. c. chabaudi,andPlasmodium
berghei) and sequence synteny to the genomic sequence of P. fal-
ciparum (11); however, thousands of sequence gaps still exist, and
many contigs are yet to be assigned to their proper chromosomes.
Increasing sequence coverage may close additional gaps, but de-
velopment of physical and genetic maps will be necessary for
assigning all the contigs to chromosomal positions and for as-
sembling the chromosomes completely.
Here, we have performed 14 individual genetic crosses using six
parasite lines/subspecies, cloned 75 independent recombinant
progeny from the crosses, genotyped 82 recombinant progeny from
genetic crosses of four parental pairs (including 7 progeny from a
previous P. y. yoelii YM ×P. y. yoelii A/C cross) (12) with hundreds
of MS markers, and developed a high-resolution linkage map. We
also identified three genetic loci, including the gene encoding
PyEBL, linked to quantitative growth-related virulent pheno-
Author contributions: X.-z.S. designed research; J.L., S.P., F.Z., Y.F., and L.K. performed
research; S.L., L.H., W.X., W.P., and O.K. contributed new reagents/analytic tools; J.L., S.P.,
H.J., L.K., J.M.C., R.C., J.C.W., and X.-z.S. analyzed data; and J.L., S.P., J.M.C., O.K., R.C.,
J.C.W., and X.-z.S. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
Freely available online through the PNAS open access option.
1
J.L., S.P., and F.Z. contributed equally to this work.
2
To whom correspondence should be addressed. E-mail: xsu@niaid.nih.gov.
See Author Summary on page 12575.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
1073/pnas.1102261108/-/DCSupplemental.
E374–E382
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types (GRVPs) using trait data from individual nonselected
progeny clones.
Results
Frequencies of Clonal Infection and Independent Recombinant
Progeny. We performed 14 independent genetic crosses using the
six P. yoelii lines or subspecies (P. y. yoelii 17XNL ×P. y. nigeriensis
N67, P. y. yoelii BY265 ×P. y. nigeriensis NSM, and P. y. yoelii YM ×
P. y. yoelii 33X). For simplicity, these parasite strains are re-
ferred to as 17XNL, N67, BY265, NSM, YM, 33X, and A/C (for
P. y. yoelii A/C), respectively. Mice (n= 2,326) were injected with
0.6–1.5 infected red blood cells (iRBCs) obtained from mice that
were infected with sporozoites derived from mosquitoes fed on
blood samples containing both parental parasites. Of the 2,326
mice, 889 (38.2%) had parasites in their blood 7–9 d postinjection
(Table 1). DNA samples from the infected mice were genotyped
with 45 MS markers, 18 for the BY265 ×NSM cross, 20 for the
YM ×33X cross, and 28 for the 17XNL ×N67 cross, with some
markers typed in more than one cross. For example, Py2699 was
used to type progeny from the 17XNL ×N67, YM ×33X, and
BY265 ×NSM crosses to verify clonal infections and to identify
recombinant progeny (Datasets S1 and S2). Because the parasite
has a haploid genome in the mouse host, the progeny that carry
only one of the parental alleles at all MS loci typed for each cross
are considered clonal. Among the 889 infected mice, 488 (54.9%)
were found to have clonal infections, including 75 (8.4%) in-
dependent recombinant progeny with unique genotypes and 248
(27.9%) having parasites with parental genotypes (Table 1). We
also genotyped 7 progeny from the YM ×A/C cross performed at
the University of Edinburgh, bringing the total number of prog-
eny typed with MSs to 82.
MS Polymorphism and Genetic Variations Between Parasite Strains.
The 82 independent recombinant progeny identified from the
initial MS typing were further analyzed with additional genome-
wide MS markers. To determine which MSs are polymorphic
between a particular parental pair of the crosses, we first geno-
typed DNA samples from the parental parasites [N67, BY265,
and 17XNL were genotyped previously (6)] with 591 MS markers
(Dataset S1). A panel of polymorphic MS markers for each cross
was selected for typing progeny from the crosses after comparing
PCR product sizes between the parents. Eventually, 485, 499, 339,
and 182 MS markers were shown to be polymorphic between the
parental pairs of BY265 ×NSM, 17XNL ×N67, YM ×33X, and
YM ×A/C crosses, respectively, and were used to type the
progeny of the crosses. Four hundred seventy-seven MS markers
produced genotypes from the 32 progeny of the BY265 ×NSM
cross, 486 MS markers produced genotypes from the 25 progeny
of the 17XNL ×N67 cross, 330 MS markers had genotypes from
the 18 progeny of the YM ×33X cross, and 178 MS markers had
genotypes from the 7 progeny of the YM ×A/C cross, generating
33,939 MS genotypes with a genotype-calling rate of ∼96.0%
(Dataset S2 and Table S1).
More than 82% of the 591 MSs were polymorphic between the
parental pairs of BY265 ×NSM and 17XNL ×N67 (Table S1), in-
dicating highly diverse genomes of the P. yoelii strains or subspecies
from different geographic origins. In contrast, ∼70% and 43% of
the MS markers that were shown to be polymorphic among seven
isolates previously (6) were monomorphic between the parents of
the YM ×A/C and YM ×33X crosses, respectively. Parasites YM,
17XL, and 17XNL emerged as very similar, with fewer than 25
polymorphic MS markers, which reflects their common origin from
17X and is consistent with a previous study based on amplified
fragment length polymorphism (AFLP) (13) (Figs. S1 and S2).
These results showed close relationships and potentially shared
chromosomes or chromosomal segments between the 17X, YM, A/
C, and 33X. Because A/C is a progeny clone from a genetic cross
between P. y. yoelii 17XA (17XA) that was derived from the isolates
17X and 33X, which originated from the same locality in the
Central African Republic as parasite 17X (Fig. S2), it is not sur-
prising to see a close genetic relationship or shared chromosome
segments between17X/YM and 33X.
Comparative Genetic Linkage Maps and Estimates of Genetic
Distances. We first constructed three individual genetic maps
from the three crosses (excluding YM ×A/C, which has only 7
progeny) and estimated the genetic distances from the crosses
using 37 markers that were physically mapped to specific chro-
mosomes previously (11, 14–16) (Fig. S3 and Table S2). These
markers therefore anchored specific linkage groups to their re-
spective chromosomes and were useful in resolving some linkage
groups into independent chromosomes. Although the genome-
wide distances from the 17XNL ×N67 and BY265 ×NSM crosses
were similar [431.2 and 473.7 centimorgan (cM), respectively], the
total genetic distance from the YM ×33X cross was approximately
double those from the other two crosses (807.0 cM) (Table 2).
Despite these differences in estimates of genetic distance, all three
crosses gave relatively even marker intervals (in cM) on all linkage
groups, and the marker orders on each linkage group of the three
crosses were essentially the same. We therefore combined the
genotypes from the 82 progeny of the four crosses to construct
a composite linkage map (Fig. 1 and Fig. S3). The resulting map
totaled 579.2 cM, with markers quite evenly distributed across
each of 14 linkage groups (no interval was >10 cM) (Fig. 1 and
Table 2). Using the estimated genome size of 23 Mb (10), we
obtained an average genome-wide unit recombination rate of 39.7
kb/cM (25.2 cM/Mb) for P. yoelii.
Shared Chromosomal Segments and Lack of Significant Segregation
Bias. Analysis of the marker inheritance patterns also revealed that
some entire chromosomes and long chromosomal segments were
shared among the YM, A/C, and 33X parasites, explaining the
smaller numbers of polymorphic MS markers in the crosses of
these parasites. Chromosomes 2, 3, 5, 7, and 10 [our linkage
groups are numbered to match the chromosome numbers in the
syntenic map of Kooij et al. (11)] and parts of many other chro-
mosomes were monomorphic between YM and A/C (Table 2 and
Table 1. Genetic crosses of P. yoelii performed and numbers of recombinant progeny obtained during this study
Crosses
Crosses
performed
Mice
injected
Mice
infected
% mice
infected
Clonal
progeny
Parental
clones
Recom
progeny
% recom
progeny No. IRP % IRP
17XNL ×N67 4 501 145 28.9 122 84 38 26.2 25 17.2
YM ×33X 3 209 77 36.8 58 10 48 62.3 18 23.4
BY265 ×NSM 7 1,616 667 41.3 308 154 154 23.1 32 4.8
Total 14 2,326 889 38.6 488 248 240 27 75 8.4
Clonal progeny, numbers of progeny that are clonal after being typed with MS markers; Mice infected, numbers of mice infected with parasites; % Mice
infected, percentage of mice infected with parasites; Mice injected, numbers of mice injected with diluted blood/parasites; No. IRP, numbers of independent
recombinant progeny; % IRP, percentage of independent recombinant progeny from total infected mice; Recom progeny, numbers of recombinant progeny;
% Recom progeny, percentage of recombinant progeny from total infected mice.
Li et al. PNAS
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MICROBIOLOGY PNAS PLUS
Dataset S2); similarly, markers from chromosomes 2 and 10 and
parts of chromosomes 3, 5, 6, 7, and 12 were monomorphic in the
YM ×33X cross. Because YM, which derives from 17X, and 33X
were from two independent wild isolates of the same location
(Fig. S2B), the results suggested that either 17X or 33X was a
progeny of a cross involving an ancestor of the other parent that
occurred in the wild before they were isolated.
We also examined the possibility of segregation bias by plot-
ting the ratios of parental genotypes along each of the 14 chro-
mosomes (Fig. 2A). No statistically significant distortion was
Table 2. Informative MS markers, crossover counts, and genetic distances from crosses of different parental combinations
YM ×A/C BY265 ×NSM 17XNL ×N67 YM ×33X All crosses
(7 progeny) (32 progeny) (25 progeny) (18 progeny) (82 progeny)
Chr MS CO G. Dis, cM MS CO G. Dis, cM MS CO G. Dis, cM MS CO G. Dis, cM MS CO G. Dis, cM
161—31 6 20.9 31 5 21.8 27 3 18.0 34 15 21.1
200—11 7 23.0 12 1 4.2 1 0 —12 8 14.5
300—15 7 23.2 17 3 13.1 4 1 5.9 17 11 19.2
4126 —24 8 27.0 26 9 38.7 20 9 58.8 27 32 42.6
510—28 5 17.4 25 1 5.0 10 2 12.0 30 8 15.7
6114 —20 7 26.8 23 3 13.2 16 13 88.0 28 27 38.3
710—24 3 10.4 24 9 38.0 16 11 70.1 25 23 33.4
8304 —38 12 40.2 36 13 56.6 35 20 123.6 41 49 64.9
9232 —39 15 50.5 39 11 47.5 38 9 55.1 47 37 54.8
10 1 0 —31 10 33.4 30 7 30.6 1 0 —33 17 31.7
11 8 4 —48 17 61.1 49 12 60.1 41 17 106.0 52 50 70.0
12 12 0 —39 12 43.8 40 5 22.3 11 0 —44 17 40.7
13 50 4 —56 16 54.9 59 12 52.7 56 27 180.7 67 59 77.3
14 12 6 —49 12 41.1 51 6 27.4 37 13 88.8 53 37 55.0
UA 11 24 24 17 29
Total 178 31 —477 137 473.7 486 97 431.2 330 125 807.0 539 390 579.2
Chr, chromosome; CO, crossover counts; G. Dis, genetic distances in cM; MS, numbers of polymorphic microsatellites; UA, unassigned.
12
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Fig. 1. A composite P. yoelii genetic map constructed from genetic crosses of four parental combinations. Genetic distances between MS markers on the 14
chromosomes of 82 progeny were calculated using Mapmaker/Exp3.0. The linkage groups corresponding to the 14 chromosomes in the syntenic map (11) are
marked from 1 to 14. The numbers between two ticks on the left side of the vertical lines are genetic distances in centimorgans, and the names of the MS
markers are on the right side of vertical lines. Additional names and clusters of the MS markers can be found in Fig. S3. Note that chromosome numbering in
P. yoelii and other rodent Plasmodium sp. is different from that of P. falciparum. The thick bars on chromosomes 10 and 13 mark the two loci linked to a GRVP.
E376
|
www.pnas.org/cgi/doi/10.1073/pnas.1102261108 Li et al.
present (Fig. 2B); however, the largest (nonsignificant) deviation
from the expected 1:1 ratio occurred at regions of chromosomes
7 and 13 close to loci associated with growth phenotypes (see
below), which may reflect contributions of these loci to parasite
fitness. The relative lack of segregation distortion is an advantage
for genetic mapping in P. yoelii and contrasts with the significantly
skewed inheritance reported for a few chromosomal regions in
genetic crosses of P. falciparum (1, 3) and Toxoplasma gondii (17).
Assignment of Orphan Contigs to Chromosomes. The linkage maps
were compared with the composite synteny chromosome maps of
three rodent malaria parasites (11). Except for four contigs, the
linkage maps placed the contigs with MS markers in the same
order of those in the synteny map (Dataset S2). A contig with MS
Py2653 was assigned to chromosome 7 in the synteny map, but the
inheritance pattern of the MS in the progeny of the BY265×NSM
and 17XNL ×N67 crosses matched those of Py1080 on chromo-
some 6. Similarly, the contig with Py1484 initially placed on
chromosome 7 of the synteny map was assigned to chromosome
12, and the contig with Py517′initially assigned to chromosome 13
matched MS Py353′on chromosome 14 (Dataset S2). Finally, the
positions of the contigs containing Py1803 and Py35 on chromo-
some 13 were reversed in the synteny map.
Our linkage maps also assigned 28 orphan contigs (∼159 kb)
that were not assigned to the synteny maps previously to 13 of
the 14 linkage groups (those in gray background in Dataset S2).
These genetic maps and the placement of the contigs in linkage
groups will greatly facilitate the assembly and completion of the
genome sequence.
Mapping Genes Contributing to GRVPs. We next applied the linkage
map to analyze the GRVP in the 17XNL ×N67 cross. Between the
two parasites used as parents in the genetic crosses, N67 grows
faster than 17XNL, showing a strong early burst of rapid growth
associated with greater virulence. The difference in parasitemia
between N67 and 17XNL was the largest at day 5 postinjection of
1×10
5
iRBCs, when N67 parasitemia reached 20–60% but the
17XNL parasitemia was 1–10% (Fig. 3 A–C). Accordingly, we
counted day 5 parasitemia in replicate mice injected with the 25
progeny from the 17XNL ×N67 cross (Fig. 3Dand Dataset S3).
The 25 progeny from the 17XNL ×N67 cross produced relatively
consistent growth phenotypes in replicate mice and could be
largely classified into either a fast- or slow-growth phenotype,
representing the phenotypes of N67 or 17XNL, respectively;
however, some progeny clones had unstable phenotypes (e.g., in-
consistently producing either slow or fast growth in replicate
infections of isogenic mice) (Dataset S3). For example, three of
the eight mice infected with progeny G007#3 had a fast-growth
phenotype at day 5, whereas the remaining five had a slow-growth
phenotype (a third mouse reached 32% parasitemia at day 7).
Quantitative trait loci (QTL) linkage analysis was performed
using the parasitemia data from the 25 progeny of the 17XNL ×
N67 cross. We first used two distinct conservative statistical phe-
notype-genotype association strategies (nonparametric Wilcoxon
rank statistics and mutual information) that make no assumptions
about pedigree, given that we had high marker density but rela-
tively few progeny and that the parents can also be included to
234 Chromosome
15
68
7910
11 12 13 14
0.2
0
0.4
0.6
0.8
1.0
Allele Ratio
A
234
15
68
7910 11 12 13 14
0100 200
Marker number 400
300
0
1
2
3
1
2
3
Log(1/P)
B
Fig. 2. Plots of parental genotype inheritance among the progeny of
the three genetic crosses. (A) Ratios of alleles from one parent of each of the
crosses were calculated and plotted. Green, ratios of YM alleles over the
total alleles from the progeny of the YM ×33X cross; red, ratios of 17XNL
alleles over the total alleles from the progeny of the 17XNL ×N67 cross; and
black, ratios of BY265 alleles over the total alleles from the progeny of the
BY265 ×NSM cross. (B) Log(1/P) values are plotted upward (gray) for dis-
tortion toward 17XNL and downward (blue) for distortion toward N67.
Dotted lines represent the P<0.01 genome-wide significance threshold
estimated using a Bonferroni correction based on the number of genetic
intervals in the genome map. The largest (nonsignificant) deviation from the
expected 1:1 ratio occurred at regions of chromosomes 7 and 13 close to the
loci associated with the GRVP (Fig. 3).
A
010 15 20 25
5
40
0
80
Parasitemia
Day post infection
B
40
0
80
010 15 20 25
5
Parasitemia
Day post infection
0
20
40
60
Parasitemia
Progeny
D
0
5
10
15
05
10 15
20
Daypostinfection
Ratio parasitmia
(N67/17XNL)
C
40
20
0
60
80
0
51015
20
E
Day post infection
%Pa
rasitemia
N67
N67C
Fig. 3. Measurements of growth rate (parasitemia) of the parents of the 17XNL ×N67 cross. Mean parasitemia and SEs of the 17XNL parasite (A), mean
parasitemia and SEs of the N67 parasite (B), ratios of parasitemia N67/17XNL at days 2–16 postinfection (C), and day 5 parasitemia from the parents and
progeny of the 17XNL ×N67 cross (D) are shown. In D,thefirst two bars from the left are the parents 17XNL and N67, respectively. SEs were from at least four
mice. (E) Mean parasitemia with SEs from mice infected with N67 and N67C parasites. A total of 15 and 5 C57BL/6 mice were injected with 1 ×10
5
N67C and
N67 parasites, respectively. All the mice infected with N67C died at day 7, whereas the majority of the mice infected with N67 were still alive at day 17 when
experiments were stopped.
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increase the sample size using these methods (Materials and
Methods). The result identified a major peak on chromosome 13
containing the PyEBL gene (genome-wide P<1×10
−5
)and
a minor peak on chromosome 10 (P<1×10
−2
) (Fig. 4A). As
a distinct phenotype, day 10 parasitemia was analyzed and found to
be weakly associated with a locus on chromosome 7 (P= 0.05 after
1,000 permutations) (Fig. 4B). We also used R/qtl (18) to identify
loci linked to the GRVP; again, the chromosome 13 and chro-
mosome 10 loci were the two major peaks with logarithm of odds
scores of 3.4 and 3.2, respectively (Fig. 4C). There was also a peak
on chromosome 7, but it was not statistically significant. The
chromosome 13 locus spans a DNA segment of ∼220 kb (between
MS markers Py2123 and Py2609) and contains 28 P. yoelii contigs
and 51 predicted genes, including the gene encoding PyEBL
(Table S3), and the chromosome 10 locus covers ∼234 kb (between
MS markers Py280 and Py1597) containing 28 P. yoelii contigs and
71 predicted genes (Table S4), including a gene encoding a mem-
ber of the 235-kDa rhoptry proteins that can bind to the erythro-
cyte surface membrane (19).
We also investigated the possibility of interactions among
genome-wide markers, particularly between the two loci linked
to day 5 parasitemia in the 17XNL ×N67 cross. Using standard
interval mapping (the expectation and maximization method) in
R/qtl, we found no statistically significant epistasis among ge-
nome-wide markers (Fig. 5A), including no interaction between
the loci on chromosome 10 and chromosome 13 (P= 0.31);
instead, the three notable two-locus effects were all additive,
namely, chromosome 10/chromosome 13 (P= 0.005), chromo-
some 7/chromosome 10 (P= 0.012), and chromosome 13/chro-
mosome 13 (P= 0.011) (Fig. 5A). The two interacting loci on
chromosome 13 are 18 cM apart and are inversely additive, with
one containing pyebl and one at the beginning of the chromo-
some that has a minimum QTL peak (Fig. 4C). The chromosome
10 and chromosome 13 loci are estimated to explain ∼23% and
∼25% of the phenotype variance (totaling ∼70% if combined;
P<0.001), respectively. From the mutual information method,
the percentages explained by the chromosome 10 and chromo-
some 13 loci to the association with the day 5 parasitemia are
23% and 37%, respectively. Given the relatively broad bands of
uncertainty on estimates of relative contributions and the small
sample size of 25 progeny, these values from R/qtl and mutual
information can be considered to be in good agreement. Indeed,
the progeny carrying N67 alleles at both chromosome 13 and
chromosome 10 loci had the highest level of parasitemia at day 5
compared with those carrying one or both of the 17XNL alleles
(Fig. 5B).
Unique C741Y Substitution in PyEBL Is Likely Associated with the
GRVP in the N67 Background. The loci on chromosomes 7 and 10
have not been previously reported and require further in-
vestigation to identify the gene(s) playing a role in parasite
growth; however, the locus on chromosome 13 contains the pyebl
gene, which was previously linked to a GRVP both by LGS in the
YM ×33X cross and by genetic manipulation implicating a single
C713R substitution (position 713 in the YM sequence) in the
PyEBL R6 domain as the crucial determinant (8, 9). Our mapping
of the primary locus to chromosome 13 strongly suggests that
PyEBL again plays a role in the GRVP in N67. We therefore
sequenced the N67 PyEBL gene to determine whether this
C713R substitution is also present in the N67 parasite. We found
39 amino acid substitutions and two indels between 17XNL and
N67 (Fig. S4); however, the C713R substitution seen in YM does
not exist in N67. Instead, a C741Y substitution (with the other
changes) was present in the R6 domain (Fig. S4). Interestingly,
a parasite submitted to MR4 (http://www.mr4.org/) under the
name of P. y. yoelii 33X(Pr3) [for simplicity, 33X(Pr3) will be
used] has an identical PyEBL sequence and a very similar geno-
mic background to that of N67, except for the C741Y substitution
in N67 (Fig. S4 and Table S5). Among 21 MS markers typed, only
a single MS had different alleles between N67 and 33X(Pr3),
whereas all the 21 MSs had different alleles among 33X and 33X
(Pr3)/N67 (Table S5). The results suggest that N67 and 33X(Pr3)
are closely related or isogenic and that the 33X(Pr3) in our hands
was not the original parasite derived from 33X. We therefore
designated this parasite N67C for having a 741C in PyEBL. Al-
though N67C grows slightly slower than N67 in the early infection,
it is more virulent than N67 because all the N67C-infected mice
died at day 7, whereas mice infected with N67 died at approxi-
mately day 15 after a decline in parasitemia on day 7 (Fig. 3 A
and E). The difference in the GRVP between N67 and N67C is
0
1
2
3
1
23 465
8
79
10
11 13
12 14
C
LOD score
0100 400
300
200
0
0.5
1.0
1.5
Log(1/P)
Chromosome/marker position
0.3
0.2
MI
0.1
123 4567 8 91011 12 13 14
0.0
B
A
Fig. 4. Genetic loci linked to the GRVP. (A) Plots of mutual information scores and MS markers across the 14 P. yoelii chromosomes using day 5 parasitemia
from the 25 progeny and the parents of the 17XNL ×N67 cross. MI, mutual information. (B) Plots of log(1/P) and MS markers using day 10 parasitemia. (C) Plot
of logarithm of odds scores using R/qtl (Materials and Methods) after natural logarithm transformation of the day 5 parasitemia data so that the dataset is
normally distributed. LOD, logarithm of odds. Multiple calculation methods, including maximum likelihood and extended Haley–Knott regression, were
evaluated; all produced the essentially the same results. The horizontal dashed lines indicate significant levels at P= 0.001 (A), P=0.05(B), and P=0.05(C).
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therefore likely caused by the C741Y substitution. Thus, two
different single mutational substitutions associated with high day
5 parasitemia and with destabilizing effects focused on the R6
domain appear to have originated independently in the distinct
PyEBL sequence backgrounds of 17XNL/YM and N67/N67C.
Discussion
Genetic crosses have been performed with several malaria parasite
species, including P. falciparum,P. c. chabaudi, and P. y. yoelii (3, 8,
20–23). The process of cloning, genotyping, and identifying
recombinant progeny has been the most time-consuming pro-
cedure in developing a linkage map and mapping malaria traits.
The numbers of progeny isolated from Plasmodium crosses have
been relatively small; for example, the P. falciparum Dd2 ×HB3
and GB4 ×7G8 crosses have 35 and 33 progeny, respectively (3,
22, 24). Because cloning rodent malaria parasites requires inject-
ing a single parasite into a large number of mice, only 7 progeny
from the YM ×A/C cross were previously obtained (8). In this
study, we obtained 488 cloned parasites from 2,326 mice and
identified 75 independent recombinant progeny from multiple
genetic crosses after genotyping the parasites with hundreds of MS
markers. This study describes the first P. yoelii linkage map, which
represents a significant advance in malaria parasite genetics.
Performing multiple genetic crosses using different parents
allowed comparison of inheritance bias and recombination fre-
quency among crosses. Our study revealed a somewhat greater
genome-wide genetic distance (centimorgans) in the YM ×33X
cross than in the other crosses, possibly reflecting fewer progeny
from this cross or some unknown genetic factors among P. yoelii
strains in control of meiotic recombination frequencies. Never-
theless, in all these crosses, the recombination rates were sub-
stantially less than those previously reported for P. falciparum
and P. c. chabaudi. We found relatively small inheritance bias, in
contrast to previous findings with P. falciparum crosses (1, 3).
Inheritance patterns of chromosomes 7 and 13 were marginally
skewed, possibly reflecting alleles that may promote parasite
survival (e.g., a chromosome 13 locus strongly linked to para-
sitemia at day 5, a chromosome 7 locus weakly linked to para-
sitemia at day 10).
The linkage map provides a solid framework for future im-
provement of the P. yoelii genome assembly. The P. yoelii genome
is currently estimated at 23 Mb but is highly fragmented in 5,687
contigs (10). Although the syntenic map based on sequences from
three rodent parasites and the genome sequence of P. falciparum
had assigned ∼2,400 P. y. yoelii contigs (total length of 15.2 Mb)
to putative chromosomes, there are still many contigs that cannot
be assigned (10, 11). We were able to assign 28 orphan contigs
(∼159 kb) to 13 chromosomes. Additional orphan contigs can
now be assigned to chromosomes or linkage groups if poly-
morphic markers from the contigs can be typed on the progeny of
the genetic crosses. Our genetic map has 14 linkage groups, in
accordance with the 14 nuclear chromosomes of all Plasmodium
species investigated, and the marker order in these linkage groups
matched well with those in the chromosomal synteny maps. The
linkage maps developed in this study provide essential tools for
complete genome assembly of P. yoelii.
The same chromosome 13 locus containing the gene encoding
PyEBL was identified by both the LGS (8) and our classic QTL
mapping based on the phenotypes of individual nonselected
progeny clones. Our study also identified a unique mutation
and a potential different mechanism affecting parasite GRVPs.
These mutations appear to have originated independently in the
diverged PyEBL sequence backgrounds of P. y. yoelii 17X and P. y.
nigeriensis N67, which differ by 39 amino acid substitutions and
two indels. In theory, other genes in the chromosome 13 locus
cannot be excluded as candidates contributing to the GRVP;
however, the differences in the PyEBL are likely to be the primary
determinant for the differences in the GRVP between N67 and
17XNL based on the two previous studies (8, 9). Furthermore,
N67 and N67C have an almost identical genomic background and
the same PyEBL sequence, except for the substitution at C741Y.
The two different single mutational substitutions associated with
higher early parasitemia, C713R in YM (8, 9) and C741Y in N67
identified here, are predicted to have similar disruptive effects on
the R6 domain. Inspection of the homologous EBA-175 R6/KIX
domain crystal structure (25) suggests that both the C713R and
the C741Y substitutions break two different strongly conserved
disulfide bonds (Fig. S4)and act indirectly, partly through sol-
vation effects on the primary hydrophobic core and a hydrophobic
groove in the dimer interface. The disruption of the disulfide
bonds appears to correlate with higher early peak parasitemia
before day 7. N67 (with a 741Y) grows slightly faster than N67C
(741C) at days 2–5, and YM/17XL (with a 713R) also grows faster
than 17XNL (713C). The C741Y substitution may partly explain
the reduced virulence of N67 compared with N67C, but the drop
in parasitemia after day 7 in N67 could be caused by other un-
C1317XNL
C1017XNL C13N67
C10N67
C1317XNL
C1017XNL
C13N67
C13N67
0
10
20
30
40
50
60
% mean parasitemia
10 915
B
P<0.01
P<0.01
P=0.02
915
Chromosome
Chromosome
12
3456 7 8910 11 1213 14
1
2
3
4
5
67
8
9
10
11
12
13
14
A
0
1
2
3
0
2
4
6
LODfLODi
Fig. 5. Interaction and additive effect between the loci on the parasite
chromosomes. (A) Loci with additive effects but no significant interactions
genome-wide were detected. The upper left triangle displays interactions
among pairwise loci. The lower right triangle displays additive effects. LODf,
logarithm of odds additive effect; LODi, logarithm of odds interaction. Sig-
nals of additive effect between markers on chromosomes 10–13, chromo-
somes 7–10, and two loci on chromosome 13 (red arrows) were detected.
The color scale bar shows LOD scores, with those on the left and right cor-
responding to LODi and LODf values, respectively. The two arrows indicate
cutoff LOD scores from 1,000 permutations (LODi = 4.5; LODf = 5.9; P<0.05).
(B) Relationship of parasitemia and different combinations of PyEBL alleles.
Progeny carrying N67 PyEBL alleles at the mapped loci also have significantly
higher parasitemia than those carrying 17XNL alleles (unpaired ttest). The
numbers within each bar are the numbers of progeny in each group.
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known factors too, or it could represent a separate phenotype.
The mechanism of how the change in amino acid in a merozoite
protein affecting parasite early growth remains unknown.
The presence of loci other than the chromosome 13 locus was
implicated in GRVPs in the previous studies (8, 9); however, the
exact locations of the additional determinants were unknown.
Our study now points to two loci on chromosomes 10 and 7 that
are linked to day 5 and day 10 parasitemia, respectively. In-
terestingly, a copy of the Py235 rhoptry protein (PY06636) that
has been implicated in RBC invasion is present in the chromo-
some 10 locus (19, 26). Members of the Py235 rhoptry proteins
have been suggested to be potential factors that may be re-
sponsible for the difference in virulence (27). Moreover, our
results show independent and additive effects for the QTL on
chromosomes 13 and 10, with no evidence for significant epistasis
genome-wide. Three additive effects were found, although the
additive effect from the two loci on chromosome 13 could be
artifact because of no obvious QTL peak at the locus on the
chromosome end and the small sample size. Further studies are
necessary to identify or confirm genes in the other two loci that
contribute to the GRVP. Interestingly, genetic loci contributing
to subtle but quantifiable strain-specific differences in prolifer-
ation rates of P. falciparum parasite Dd2 (faster growth) and HB3
during in vitro cultivation, which were attributed to a decreased
cycle time and increased merozoite production and invasion rates,
have been mapped recently, including a major genetic effect on
chromosome 12 containing 165 candidate genes (28).
Recombinant progeny with atypical growth phenotypes
were obtained after genetic recombination. Display of either fast
or slow growth in a single progeny was observed, which was likely
controlled through gene expression regulation or combinational
effects of multiple genes, or possibly through subtle uncontrolled
environmental effects influencing the mice. Progeny with an in-
termediate growth rate or growth rate higher than that of the
parents were also obtained. These transgressive cases indicate
that clones that are more virulent could be generated in the wild
through genetic recombination in sexual crosses of parasites as well
as by de novo mutations. Indeed, recombinant progeny more vir-
ulent than parental clones have been reported in T. gondii, sug-
gesting that sexual recombination can be a powerful force driving
the natural evolution of virulence (29). Alternatively, deleterious
mutations can accumulate in clonally maintained organisms, and
recombinationmay effectively remove these deleterious mutations
from some progeny, restoring fitness and resulting in progeny with
phenotypes greater than those observed in the parental lines.
Genetic mapping of rodent malaria traits has been largely based
on LGS, which does not require cloning and typing individual
progeny (7). In this procedure, a phenotype-specific selection
pressure is applied to the uncloned progeny of a genetic cross
between two parents with different relevant phenotypes. Selected
and unselected progeny are analyzed using genome-wide quanti-
tative genetic markers. Under selection, the sensitive allele of the
target gene will be removed, leading to a reduced allele frequency
or “selection valley”at the locus carrying the “resistant”gene (7).
LGS has been successfully used to map loci affecting drug
resistance, immunity, and difference in growth rate/virulence (2,
7, 8, 30), which has established LGS as a convenient approach
for mapping selectable malaria traits. Cloning and evaluating in-
dividual progeny from genetic crosses now enables a powerful
genetic mapping approach that can be applied to screen non-
selectable parasite phenotypes or complex traits that are not
amenable to LGS methods. The progeny obtained in this study not
only provide powerful and durable resources for genetic studies
but also allow investigation of inheritance bias and recombina-
tion parameters, such as hotspots. Moreover, the markers ordered
on the 14 chromosomes now provide a chromosomal framework
for improved assembly of the parasite genome sequence. As with
studies that have been done using P. falciparum genetic crosses (22,
31–35), the progeny and genotypes we describe here can be used to
map multiple segregating genetic determinants in this mouse
model, which, in turn, will provide important information for
studying human malaria.
Materials and Methods
Parasites, DNA Sequencing, and MS Typing. The origins of the P. yoelii lines
and the relationships of the cloned lines are summarized in Fig. S2 and Table
S6. Parasites 17XNL, N67, BY265, N67C [under P. y. yoelii 33X(Pr3)], and NSM
were obtained from MR4 (http://www.mr4.org/) or were described pre-
viously (36). YM, 33X, A/C, and P. y. yoelii 17X(A) were obtained from frozen
stocks of the University of Edinburgh (13). YM is a lethal parasite derived
from the nonlethal uncloned isolate 17X following removal of a stabilate
from liquid nitrogen storage in the early 1970s (12, 37); it also has the same
genome and GRVP as 17XL (13). NSM is a mefloquine-resistant parasite se-
lected from P. yoelii NS, a parasite line emerged from an isolate of P. berghei
from Katanga, Belgian Congo, in the early 1970s; however, our genotyping
showed that the N67, NSM, and P. yoelii NS in our hands had essentially the
same genome (Dataset S1) (36). A/C is a progeny from a cross of 33X and
17XA, a pyrimethamine-resistant line that is genetically distinct from clones
17XNL, 17XL, and YM but originated from the same isolate 17X (12, 13) (Fig.
S2). Mosquitoes were from a colony of Anopheles stephensi maintained at
the Laboratory of Malaria and Vector Research, National Institutes of Health
(NIH), and a colony of A. stephensi maintained at the Third Military Medical
University of China. Female inbred strain C57BL/6 and outbred CD-1 and
Kunming mice, aged 6–8 wk, were used in the experiments. All animal
procedures were performed in accordance with animal study protocol LMVR
11E approved by the National Institute of Allergy and Infectious Diseases
Animal Care and Use Committee (NIH) and with the approved protocols of
the Third Military Medical University or Xiamen University in China.
DNA samples were extracted from 20 to 100 μL of heparinized tail blood
from P. yoelii-infected mice using a High Pure PCR Template preparation kit
(Roche). For DNA sequencing of pyebl, oligonucleotide primers 5-CCTCC-
TGTTGCATAGTAGTATTGAT-3 and 5-TTTGATGAACCAAATGCATAGA-3, corre-
sponding to positions 1,407–1,431 and 4,232–4,211 of the P. y. yoelii 17XNL
contig MALPY01471 (GenBank accession no. AABL01001466) (10), were syn-
thesized to amplify a full-length coding region. PCR reactions wereperformed
in a 50-μL volume consisting of 100 ng of genomic DNA in 1×Ultra-high fidelity
Accuzyme mix (Bioline). PCR conditions were as follows: one cycle at 94 °C for
5 min; followed by 35 cycles at 94 °C for 30 s, 55 °C for 1 min, and 68 °C for
4 min; and a final extension at 68 °C for 5 min.The products were treated with
shrimp alkaline phosphatase and exonuclease I before sequencing (38). Se-
quencing reactions were performed in triplicate from different amplification
tubes using an ABI Prism BigDye Terminator ready-to-use reaction kit (Applied
Biosystems). Sequencing primers were described previously (8).
MSs used in this study have been described previously (6, 36). Briefly, PCR
products without any labeling procedures were separated using capillary
electrophoresis performed in a QIAxcel machine (QIAGEN) according to the
manufacturer’s instructions. Genotypes from genetic cross progeny were
scored by matching the PCR product sizes with those from the parents. The
genetic distances between the parasites were calculated using methods
described (36).
P. yoelii Genetic Crosses. Three combinations of genetically distinct clones of
P. yoelii were chosen to produce genetic crosses. Two genetic crosses of (i)
N67 (lethal) ×17XNL (nonlethal) and (ii) YM (lethal) ×33X (nonlethal) were
performed at the NIH laboratory, whereas the genetic cross between BY265
and NSM was conducted at the Third Military Medical University and Xiamen
University of China. The genetic cross between YM and A/C was performed
in David Walliker’s laboratory at the University of Edinburgh, and seven
recombinant clones have been cryopreserved since 1976 (12). Because we
could only handle a limited number of mice at a time, we cloned progeny
from multiple individual crosses of each parental pair. The crosses were also
performed with different phenotypes in mind. For example, we were in-
terested in differences in GRVPs in the N67 ×17XNL and YM ×33X crosses
and drug resistance in the BY265 ×NSM cross (NSM is more resistant to
mefloquine and chloroquine).
The experimental procedures for the production of genetic crosses in
P. yoelii have been described previously (8, 39). Briefly, inbred C57BL/6 or
Kunming outbred (BY265×NSM cross) female mice were coinfected with two
parasites (parents) to be crossed. Parasitemia (percent of parasitized eryth-
rocytes from at least 1,000 cells) from the mice was monitored daily by mi-
croscopic examination of Giemsa-stained thin blood smears. On day 4
postinfection, each infected mouse with male and female gametocytes (av-
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erage parasitemia ∼10–30%) was anesthetized and fed to 50–100 female
mosquitoes per infected mouse. The mouse was then euthanized while under
anesthesia. Seventeen days after feeding, sporozoites were harvested from
infected mosquitoes, and 1 ×10
5
to 5 ×10
5
sporozoites were injected i.p. into
female CD-1 mice to obtain blood-stage parasites representing “uncloned
progeny”of the genetic cross. When blood-stage parasites were microscop-
ically detectable (∼0.1–1% parasitemia), blood samples were drawn from the
infected mice and diluted to 0.6–1.5 iRBCs per 100 μL (inoculum size) before
injection i.v. into recipient mice. Five to nine days after injection, mice were
monitored for the presence of blood-stage malaria parasites. A small volume
(20–50 μL) of mouse tail blood was withdrawn and used for parasite genomic
DNA extraction and MS genotyping. For screening of recombinant progeny,
DNA from cross progeny was typed with a panel of MS markers distributed
on chromosomes 1–14 (Dataset S1). Recombinant progeny were considered
clonal when single MS alleles were found in the MS loci. To improve the
recovery of independent progeny, the parasites were cloned as early as
possible to prevent “overgrowth”of some fast-growing parasites. Moreover,
the parental input ratio was adjusted appropriately for each particular cross
based on the different growth rates of each pair of parents.
Development of Genetic Linkage Maps. We constructed a genetic linkage map
from the MS genotypes and segregation patterns in the progeny of each
individual cross using Mapmaker/Exp 3.0 (40) to order the markers and es-
timate genetic distances between them. We used 37 MS markers within the
contigs that had been physically assigned to chromosomes previously (11,
14–16) as anchors for assigning linkage groups to chromosomes (Dataset S1
and Table S2).
GRVP and Linkage Analysis. To map the determinant(s) that affect the GRVP
between N67 and 17XNL, we evaluated the growth rates of the progeny from
the cross between 17XNL and N67 in female C57BL/6 mice (4–8 mice per single
parasite clone). Each mouse was injected i.v. with an inoculum containing
1×10
5
iRBCs. Parasitemias were monitored daily, as measured by microscopic
examination of Giemsa-stained thin tail blood smears, and recorded in Excel.
QTL Analysis and Statistics. For genome-wide scans of the day 5 parasitemia,
the association between categorical trait value vectors and genotype vectors
was evaluated using Shannon’s mutual information (41) with the genome-
wide P<0.001 threshold (Fig. 4A, dashed horizontal line) estimated using
a noncentral χ
2
test confirmed by simulation (41). The simulation estimated
the null distribution of mutual information under nonassociation using
1,000 permutations and the method described by Nelson and O’Brien (42).
The day 10 parasitemia was treated as a continuous trait, and associated
QTLs were mapped using a ttest statistic and 1,000 permutations. We also
ran scans based on a nonparametric Wilcoxon test for all phenotypes to
provide independent support for the associations, which gave essentially the
same results.
QTL mapping was also conducted using the R/qtl library in R2.12.2 software
(18). Day 5 parasitemia from the 25 progeny of the N67 and 17XNL cross was
natural-log transformed to obtain a normally distributed dataset. One
thousand permutations with a 5% threshold (P= 0.05) were performed
using standard interval mapping (the expectation and maximization
method). A single QTL genome scan was done first; a 2D scan and, finally,
two QTL genome scans were then performed because of two similarly sig-
nificant loci on chromosome 10 and chromosome 13. In principle, the 2D and
two QTL scans could identify additional QTL and two-locus epistatic inter-
actions if they are present.
Statistical Analysis of Inheritance Bias. We measured the statistical signifi-
cance of deviations from the expected 1:1 segregation ratio. For each marker,
we computed the Kendall τ-rank association statistic between the observed
parents and progeny genotype vector and each of the two vectors, simu-
lating complete bias (i.e., with all progeny assigned as one parental type or
the other). The S-plus function cor.test was used with the method “kendall,”
where probabilities of dependence were based on the normal approxima-
tion as described by Prokhorov (43).
ACKNOWLEDGMENTS. We thank Drs. Karl W. Broman and Na Li for advice
on QTL analysis and National Institute of Allergy and Infectious Diseases
intramural editor Brenda Rae Marshall for assistance. This work was
supported by grants from the National Basic Research Program of China, 973
Program (Grant 2007CB513103), the Science Planning Program of Fujian
Province (Grant 2010J1008), and the 111 Project of Education of China
(Grant B06016) as well as by the Intramural Research Program of the Division
of Intramural Research, National Institute of Allergy and Infectious Diseases,
National Institutes of Health. J.C.W. was supported by the Intramural
Program of the National Center for Biotechnology Information, National
Library of Medicine, National Institutes of Health.
1. Su X, et al. (1999) A genetic map and recombination parameters of the human
malaria parasite Plasmodium falciparum. Science 286:1351–1353.
2. Martinelli A, et al. (2005) A genetic approach to the de novo identification of targets
of strain-specific immunity in malaria parasites. Proc Natl Acad Sci USA 102:814–819.
3. Hayton K, et al. (2008) Erythrocyte binding protein PfRH5 polymorphisms determine
species-specific pathways of Plasmodium falciparum invasion. Cell Host Microbe 4:
40–51.
4. Su X, Hayton K, Wellems TE (2007) Genetic linkage and association analyses for trait
mapping in Plasmodium falciparum. Nat Rev Genet 8:497–506.
5. Martinelli A, et al. (2005) An AFLP-based genetic linkage map of Plasmodium
chabaudi chabaudi. Malar J 4:11.
6. Li J, et al. (2009) Hundreds of microsatellites for genotyping Plasmodium yoelii
parasites. Mol Biochem Parasitol 166:153–158.
7. Culleton R, Martinelli A, Hunt P, Carter R (2005) Linkage group selection: Rapid gene
discovery in malaria parasites. Genome Res 15:92–97.
8. Pattaradilokrat S, Culleton RL, Cheesman SJ, Carter R (2009) Gene encoding
erythrocyte binding ligand linked to blood stage multiplication rate phenotype in
Plasmodium yoelii yoelii. Proc Natl Acad Sci USA 106:7161–7166.
9. Otsuki H, et al. (2009) Single amino acid substitution in Plasmodium yoelii erythrocyte
ligand determines its localization and controls parasite virulence. Proc Natl Acad Sci
USA 106:7167–7172.
10. Carlton JM, et al. (2002) Genome sequence and comparative analysis of the model
rodent malaria parasite Plasmodium yoelii yoelii. Nature 419:512–519.
11. Kooij TW, et al. (2005) A Plasmodium whole-genome synteny map: Indels and synteny
breakpoints as foci for species-specific genes. PLoS Pathog 1:e44.
12. Walliker D, Sanderson A, Yoeli M, Hargreaves BJ (1976) A genetic investigation of
virulence in a rodent malaria parasite. Parasitology 72:183–194.
13. Pattaradilokrat S, Cheesman SJ, Carter R (2008) Congenicity and genetic polymor-
phism in cloned lines derived from a single isolate of a rodent malaria parasite. Mol
Biochem Parasitol 157:244–247.
14. Uzureau P, Barale JC, Janse CJ, Waters AP, Breton CB (2004) Gene targeting demon-
strates that the Plasmodium berghei subtilisin PbSUB2 is essential for red cell invasion
and reveals spontaneous genetic recombination events. Cell Microbiol 6:65–78.
15. Thompson J, et al. (2004) PTRAMP; a conserved Plasmodium thrombospondin-related
apical merozoite protein. Mol Biochem Parasitol 134:225–232.
16. Janse CJ, Carlton JM, Walliker D, Waters AP (1994) Conserved location of genes on
polymorphic chromosomes of four species of malaria parasites. Mol Biochem Parasitol
68:285–296.
17. Khan A, et al. (2005) Composite genome map and recombination parameters derived
from three archetypal lineages of Toxoplasma gondii. Nucleic Acids Res 33:2980–2992.
18. Broman KW, Wu H, Sen S, Churchill GA (2003) R/qtl: QTL mapping in experimental
crosses. Bioinformatics 19:889–890.
19. Preiser PR, Jarra W, Capiod T, Snounou G (1999) A rhoptry-protein-associated
mechanism of clonal phenotypic variation in rodent malaria. Nature 398:618–622.
20. Walliker D, Carter R, Morgan S (1971) Genetic recombination in malaria parasites.
Nature 232:561–562.
21. Walliker D, et al. (1987) Genetic analysis of the human malaria parasite Plasmodium
falciparum. Science 236:1661–1666.
22. Wellems TE, et al. (1990) Chloroquine resistance not linked to mdr-like genes in
a Plasmodium falciparum cross. Nature 345:253–255.
23. Grech K, et al. (2002) Numerous, robust genetic markers for Plasmodium chabaudi by
the method of amplified fragment length polymorphism. Mol Biochem Parasitol 123:
95–104.
24. Su X, Kirkman LA, Fujioka H, Wellems TE (1997) Complex polymorphisms in an
approximately 330 kDa protein are linked to chloroquine-resistant P. falciparum in
Southeast Asia and Africa. Cell 91:593–603.
25. Withers-Martinez C, et al. (2008) Malarial EBA-175 region VI crystallographic structure
reveals a KIX-like binding interface. J Mol Biol 375:773–781.
26. Khan SM, Jarra W, Bayele H, Preiser PR (2001) Distribution and characterisation of the
235 kDa rhoptry multigene family within the genomes of virulent and avirulent lines
of Plasmodium yoelii. Mol Biochem Parasitol 114:197–208.
27. Culleton R, Kaneko O (2010) Erythrocyte binding ligands in malaria parasites:
Intracellular trafficking and parasite virulence. Acta Trop 114:131–137.
28. Reilly Ayala HB, Wacker MA, Siwo G, Ferdig MT (2010) Quantitative trait loci mapping
reveals candidate pathways regulating cell cycle duration in Plasmodium falciparum.
BMC Genomics 11:577.
29. Grigg ME, Bonnefoy S, Hehl AB, Suzuki Y, Boothroyd JC (2001) Success and virulence
in Toxoplasma as the result of sexual recombination between two distinct ancestries.
Science 294:161–165.
30. Pattaradilokrat S, Cheesman SJ, Carter R (2007) Linkage group selection: Towards
identifying genes controlling strain specific protective immunity in malaria. PLoS ONE
2:e857.
31. Vaidya AB, et al. (1995) A genetic locus on Plasmodium falciparum chromosome 12
linked to a defect in mosquito-infectivity and male gametogenesis. Mol Biochem
Parasitol 69:65–71.
Li et al. PNAS
|
August 2, 2011
|
vol. 108
|
no. 31
|
E381
MICROBIOLOGY PNAS PLUS
32. Ferdig MT, et al. (2004) Dissecting the loci of low-level quinine resistance in malaria
parasites. Mol Microbiol 52:985–997.
33. Hayton K, Su XZ (2008) Drug resistance and genetic mapping in Plasmodium
falciparum. Curr Genet 54:223–239.
34. Gonzales JM, et al. (2008) Regulatory hotspots in the malaria parasite genome dictate
transcriptional variation. PLoS Biol 6:e238.
35. Yuan J, et al. (2009) Genetic mapping of targets mediating differential chemical
phenotypes in Plasmodium falciparum. Nat Chem Biol 5:765–771.
36. Li J, et al. (2007) Typing Plasmodium yoelii microsatellites using a simple and
affordable fluorescent labeling method. Mol Biochem Parasitol 155:94–102.
37. Yoeli M, Hargreaves B, Carter R, Walliker D (1975) Sudden increase in virulence in
a strain of Plasmodium berghei yoelii. Ann Trop Med Parasitol 69:173–178.
38. Mu J, et al. (2007) Genome-wide variation and identification of vaccine targets in the
Plasmodium falciparum genome. Nat Genet 39:126–130.
39. Pattaradilokrat S, Li J, Su XZ (2011) Protocol for production of a genetic cross of the
rodent malaria parasites. J Vis Exp, 10.3791/2365.
40. Lander E, et al. (1987) MAPMAKER: An interactive computer package for constructing
primary genetic linkage maps of experimental and natural populations. Genomics 1:
174–181.
41. Dawy Z, et al. (2006) Gene mapping and marker clustering using Shannon’s mutual
information. IEEE/ACM Trans Comput Biol Bioinformatics 3:47–56.
42. Nelson GW, O’Brien SJ (2006) Using mutual information to measure the impact of
multiple genetic factors on AIDS. J Acquir Immune Defic Syndr 42:347–354.
43. Prokhorov AV (2001) Kendall coefficient of rank correlation. Online Encyclopedia of
Mathematics, ed Hazewinkel M (Springer, CWI, Amsterdam).
E382
|
www.pnas.org/cgi/doi/10.1073/pnas.1102261108 Li et al.
