biology
letters
Biol. Lett. (2012) 8, 783-786
doi:10.1098/rsbl.2012.0331
Published online 16 May 2012
Evolutionary biology
Cross Mark
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More than 1000
ultraconserved
elements provide evidence
that turtles are the sister
group of archosaurs
Nicholas G. Crawford1*, Brant C. Faircloth,
John E. McCormack, Robb T. Brumfield34,
Kevin Winkers and Travis C. Glenn
Department of Biology, Boston University, Boston, MA 02215, USA
2 Department of Ecology and Evolutionary Biology, University of
California, Los Angeles, CA 90095, USA
Museum of Natural Science, and Department of Biological Sciences,
Louisiana State University, Baton Rouge, LA 70803, USA
5 University of Alaska Museum, 907 Yukon Drive, Fairbanks,
AK 99775, USA
Department of Environmental Health Science and Georgia Genomics
Facility, University of Georgia, Athens, GA 30602, USA
* Author for correspondence (ngcrawford@gmail.com).
We present the first genomic-scale analysis
addressing the phylogenetic position of turtles,
using over 1000 loci from representatives of
all major reptile lineages including tuatara.
Previously, studies of morphological traits posi-
tioned turtles either at the base of the reptile
tree or with lizards, snakes and tuatara (lepido-
saurs), whereas molecular analyses typically
allied turtles with crocodiles and birds (archo-
saurs). A recent analysis of shared microRNA
families found that turtles are more closely
related to lepidosaurs. To test this hypothesis
with data from many single-copy nuclear loci dis-
persed throughout the genome, we used sequence
capture, high-throughput sequencing and pub-
lished genomes to obtain sequences from 1145
ultraconserved elements (UCEs) and their vari-
able flanking DNA. The resulting phylogeny
provides overwhelming support for the hypothesis
that turtles evolved from a common ancestor of
birds and crocodilians, rejecting the hypothesized
relationship between turtles and lepidosaurs.
Keywords: turtles; ultraconserved elements;
phylogenomics; evolution; archosaurs
Molecular studies using mitochondrial (4,6-8,16)
and nuclear DNA (5,9-14,17] typically place turtles
sister to archosaurs (crocodilians and birds; figure 1).
This molecular hypothesis was recently contradicted
by a phylogeny reconstructed from microRNAs [15]
that allied turtles with lepidosaurs. Lyson et al. [15]
suggested that prior molecular evidence for a turtle-
archosaur relationship may be the result of analytical
artefacts. If true, the hypothetical relationship between
turtles and lepidosaurs (Ankylpoda) should appear
throughout the genomes of these organisms.
Here, we test the Ankylopoda hypothesis and address
the evolutionary origin of turtles. We reconstruct a rep-
tile phylogeny using ultraconserved elements (UCES)
[18] and their flanking sequence that we obtained
using sequence capture of DNA from a tuatara and
two species each of crocodilians, squamates and turtles
(table 1). We used UCEs because they are easily aligned
portions of extremely divergent genomes (19), allowing
many loci to be interrogated across evolutionary time-
scales, and because sequence variability within UCES
increases with distance from the core of the targeted
UCE (20), suggesting that phylogenetically informative
content in flanking regions can inform hypotheses
spanning different evolutionary timescales. To break
up long branches and mitigate potential problems with
long-branch attraction, we selected species representing
the span of diversity within major reptilian lineages
(i.e. the most divergent crocodilians, lepidosaurs
and turtles).
2. MATERIAL AND METHODS
We enriched DNA libraries prepared with Nextera kits (Epicentre, Inc.,
Madison, WI, USA) using a synthesis (Mycroarray, Inc., Ann Arbor,
MI, USA or Agilent, Inc., Santa Clara, CA, USA) of RNA probes
[20] targeting 2386 UCEs and their flanking sequence. We generated
sequences for each enriched library using single-end, 100-base sequen-
cing on an Illumina GAIIx. After quality filtering, we assembled reads
into contigs using Velvet [21], and we matched contigs to the UCE
loci, removing duplicate hits. We generated alignments using
MUSCLE [22], and we excluded loci having missing data in any
taxon. Following alignment, we estimated the appropriate finite-sites
.
We prepared a concatenated dataset by partitioning loci by
substitution model prior to analysis using two runs of MrBayes [23]
for 5 000 000 iterations (four chains per run; burn-in: 50%; thinning:
100). We also used each alignment to estimate gene trees incorporating
1000 multi-locus bootstrap replicates, which we integrated into
STEAC and STAR [24] species trees. Additional details concerning
UCE sequence capture methods and phylogenetic methods are
available in Faircloth et al. (20).
1. INTRODUCTION
The evolutionary origin of turtles has confounded the
understanding of vertebrate evolution [1] (figure 1).
Historically, turtles were thought to be early-diverging
reptiles, called anapsids, based on their skull mor-
phology and traits such as dermal armour (2]. Recent
morphological studies that included soft tissue and
developmental characters [3] allied turtles with lepido-
saurs, a group including squamates (lizards and
snakes) and tuataras. However, homoplasy stemming
from the derived skeletal specializations of turtles
limits the utility of phylogenetic inference based on
morphological data to resolve turtle placement (4,5).
3. RESULTS
We enriched genomic DNA for UCEs in corn
snake (Pantherophis guttata), African helmeted turtle
(Pelomedusa subrufa), painted turtle (Chrysemys picta),
American alligator Alligator mississippiensis), saltwater
crocodile (Crocodylus porosus) and tuatara (Sphenodon
tuatara) (table 1). We sequenced a mean of 4.9 million
reads from each library, and from these reads, we
assembled an average of 2648 (+314 s.d.) contigs.
We supplemented these taxa with UCEs extrac-
ted from the chicken (Gallus gallus), zebra finch
(Taeniopygia guttata), Carolina anole lizard (Anolis
carolinensis) and human (Homo sapiens) genome
sequences. We combined the in silico and in vitro data
and generated alignments across all taxa and excluded
all loci having missing data from any taxon. This
Received 9 April 2012
Accepted 26 April 2012
783
This journal is © 2012 The Royal Society
784 N. G. Crawford et al.
UCEs place turtles sister to archosaurs
Table 1. University of California Santa Cruz (UCSC) genome build or specimen ID for each sample, the number of
~100 bp sequence reads, and the total number of UCEs assembled.
common name
binomial
specimen ID/genome build
reads
assembled UCES
African helmeted turtle
American alligator
Carolina anole
corn snake
human
painted turtle
red junglefowl
saltwater crocodile
tuatara
zebra finch
Pelomedusa subrufa
Alligator mississippiensis
Anolis carolinensis
Pantherophis guttata
Homo sapiens
Chrysemys picta
Gallus gallus
Crocodylus porosus
Sphenodon tuatara
Taeniopygia guttata
H20145"
HCD-2620"
H16061"
H15909"
UCSC hg19
H2662"
UCSC galGal3
LM-675
UMFS-10956
UCSC taeGut 1
11 200 032
3 528 983
3 100 147
3 362 738
NA
4 467 644
NA
3 261 088
5 651 932
NA
1972
2320
21110
2168
1748
2261
23600
2218
2199
23450
"From the LSU Museum of Natural Science.
"From the Darwin Crocodile Farm courtesy of L. Miles, S. Isberg and C. Moran.
From the University of Michigan Museum of Zoology courtesy of R. Nussbaum and G. Schneider.
"Although we identified 2386 UCES these organisms, from which lesigned capture obes, owing to slight adjustments to matching
and filtering algorithms, we only recover ca 98% of these UCEs when re-screening these genomic sequences.
(a) morphology
snakes
lizards
tuatara
turtles!
crocodilians
birds
turtles2
mammals
either run. Bayesian analysis of concatenated alignments
and species-tree analysis of 1145 independent gene his-
tories showed turtles to be the sister lineage of extant
archosaurs with complete support (figure 2). Removing
the snake, which had a very long branch, and re-running
all analyses did not change the results.
(b) mtDNA and nucDNA
snakes
lizards
tuatara
turtles
crocodilians
birds
mammals
(c)
microRNAs
snakes
lizards
turtles
crocodilians
birds
4. DISCUSSION
Genomic-scale phylogenetic analysis of 1145 nuclear
UCE loci agreed with most other molecular studies
[4-14), supporting a sister relationship between turtles
and archosaurs. We found no support for the turtles-
lepidosaur relationship predicted by the Ankylopoda
hypothesis [15] (figure 2). The combination of taxo-
nomic sampling, the genome-wide scale of the
sampling and the robust results obtained, regardless of
analytical method, indicates that the turtle-archosaur
relationship is unlikely to be caused by long-branch
attraction or other analytical artefacts.
Although our results corroborate earlier studies, many
of these studies did not include tuatara. Because tuatara
is an early-diverging lepidosaur, it is important to include
this taxon in studies of turtle evolution as it breaks
up the long-branch leading to squamates (figure 2b).
Of the studies including tuatara, two (6,11] found results
similar to this study, but both were based on a single
locus. The third study [5] was unable to produce a
well-resolved tree from four nuclear genes when the
authors included tuatara in the dataset. Our study is
the first to produce a well-resolved reptile tree that
includes the tuatara and multiple loci.
The discrepancy between our results showing a
strong turtle-archosaur relationship and microRNA
(miRNA) results, which showed a strong turtle-
lepidosaur relationship, may be due to several factors.
Lyson et al. (15) used the presence of four miRNA
gene families, detected among turtles and lepidosaurs
and undetected in the other taxa analysed, to support
the turtle-lepidosaur relationship. Because complete
genomes are unavailable for turtles, tuatara and crocodi-
lians, and because expressed miRNA data are lacking for
most reptiles, the authors collected miRNA sequences
from small RNA expression libraries. miRNAs have
mammals
Figure 1. (a) Depicts the primary morphological hypotheses:
turtles most basally branching reptilian lineage [2] or turtles
related to lepidosaurs [3].' (b) Depicts the primary molecular
hypothesis of a turtle-archosaur alliance (4-14]. ©) Depicts
the tree derived from miRNA loci (15).
resulted in 1145 individual alignments with a mean
length of 406 bp (+100 bp s.d.) per alignment, total-
ling 465 Kbp of sequence. Tracer showed that both
Bayesian analyses converged quickly, having effective
sample size (ESS) scores for log likelihood of
170 and 220. Because posterior probabilities for all
nodes were 1.0, AWTY (http://ceb.csit.fsu.edu/awty)
showed zero variance in the tree topology throughout
Biol. Lett. (2012)
UCEs place turtles sister to archosaurs N. G. Crawford et al. 785
(a)
1.0/100
snake
Pantherophis guttata
and relevant to resolving ancient phylogenetic enigmas
throughout the tree of life [28]. This approach to high-
throughput phylogenomics-based on thousands of
loci—is likely to fundamentally change the way that
systematists gather and analyse data.
1.0/100
lizard
Anolis carolinensis
tuatara
Sphenodon tuatara
(a) Additional information
We provide all data and links to software via Dryad repo-
sitory (doi:10.5061/dryad.75nv22qj) and GenBank
(JQ868813-JQ885411).
1.0/100
side-necked turtle
Pelomedusa subrufa
painted turtle
Chrysemys picta
1.0/100 1.0/100
American alligator
Alligator mississippiensis
saltwater crocodile
Crocodylus porosus
We thank R. Nilsen, K. Jones, M. Harvey, R. Nussbaum,
G. Schneider, D. Ray, D. Peterson, C. Moran, L. Miles,
S. Isberg, C. Mancuso, S. Herke, two anonymous reviewers
and the LSU Genomic Facility. National Science Foundation
grants DEB-1119734, DEB-0841729 and DEB-0956069,
and an Amazon Web Services Education Grant supported
this study. N.G.C., B.C.F., J.E.M. and T.C.G. designed the
study; N.G.C. and B.C.F. performed phylogenetic analysis;
B.C.F. created datasets; J.E.M. performed laboratory work;
all authors helped write the manuscript.
1.0/100
zebra finch
Taeniopygia guttata
1.0/100
chicken
Gallus gallus
human
Homo sapiens
(b)
snake
lizard
tuatara
turtles
crocodilians
birds
human
0.03 substitutions/site
Figure 2. (a) Reptilian phylogeny estimated from 1145 ultra-
conserved loci using Bayesian analysis of concatenated data
and species-tree methods, yielding identical topologies. Node
labels indicate posterior probability/bootstrap support. (6)
Phylogram of the UCE phylogeny generated with STEAC.
1 Lee, M. S. Y., Reeder, T. W., Slowinski, J. B. & Lawson,
R. 2004 Resolving reptile relationships. In Assembling
the tree of life (eds J. Cracraft & M. J. Donoghue),
pp. 451-467. Oxford, UK: Oxford University Press.
2 Lee, M. 1997 Reptile relationships turn turtle. Nature
389, 245-246. doi:10.1038/38422)
3 Rieppel, O. 1999 Turtle origins. Science 283, 945-946.
(doi:10.1126/science.283.5404.945)
4 Janke, A., Erpenbeck, D., Nilsson, M. & Aranason, U.
2001 The mitochondrial genomes of the iguana (Iguana
iguana) and the caiman (Caiman crocodylus): implications
for amniote phylogeny. Proc. R. Soc. Lond. B 268, 623-
631. (doi:10.1098/rspb.2000.1402)
5 Hedges, S. & Poling, L. 1999 A molecular phylogeny of
reptiles. Science 283, 998-1001. (doi:10.1126/science.
283.5404.998)
6 Rest, J. S., Ast, J. C., Austin, C. C., Waddell, P. J.,
Tibbetts, E. A., Hay, J. M. & Mindell, D. P. 2003 Mol-
ecular systematics of primary reptilian lineages and the
tuatara mitochondrial genome. Mol. Phylogenet. Evol.
29, 289-297. (doi:10.1016/S1055-7903(03)00108-8)
7 Kumazawa, Y. & Nishida, M. 1999 Complete mitochon-
drial DNA sequences of the green turtle and blue-tailed
mole skink: statistical evidence for archosaurian affinity
of turtles. Mol. Biol. Evol. 16, 784-792. (doi:10.1093/
oxfordjournals.molbev.a026163)
8 Zardoya, R. & Meyer, A. 1998 Complete mitochondrial
genome suggests diapsid affinities of turtles. Proc. Natl
Acad. Sci. USA 95, 14 226-14 231. doi:10.1073/pnas.
95.24.14226)
9 Katsu, Y., Braun, E. L., Guillette Jr, L. J. & Iguchi, T.
2009 From reptilian phylogenomics to reptilian genomes:
analyses of c-fun and DJ-1 proto-oncogenes. Cytogenet.
Genome Res. 127, 79-93. doi:10.1159/000297715)
10 Shedlock, A. M., Botka, C. W., Zhao, S., Shetty, J.,
Zhang, T., Liu, J. S., Deschavanne, P. J. & Edwards,
S. V. 2007 Phylogenomics of nonavian reptiles and the
structure of the ancestral amniote genome. Proc. Natl
Acad. Sci. USA 104, 2767-2772. (doi:10.1073/pnas.
0606204104)
11 Hugall, A. F, Foster, R. & Lee, M. S. Y. 2007 Cali-
bration choice, rate smoothing, and the pattern of
tetrapod diversification according to the long nuclear
gene RAG-1. Syst. Biol. 56, 543-563. doi:10.1080/
10635150701477825)
tissue and developmental-stage-specific expression pro-
files [25,26), which could make the detection of certain
miRNAs challenging. Because preparing and sequencing
libraries is a biased sampling process, the detection prob-
ability for specific targets is variable, and some miRNAs
are likely to be more easily detected than others. Thus,
failures to detect miRNA families are not equivalent to
the absence of miRNA families [27]. We suggest that at
least some of the four miRNA families currently thought
to be unique to lizards and turtles may be present but as
yet undiscovered in other reptiles.
This work is the first to investigate the placement of
turtles within reptiles using a genomic-scale analysis of
single-copy DNA sequences and a complete sampling
of the major relevant evolutionary lineages. Because
UCEs are conserved across most vertebrate groups
[20] and found in groups including yeast and insects
[19], our framework is generalizable beyond this study
Biol. Lett. (2012)
Journal of Mammalogy, 88(1):24–31, 2007
HEMOGLOBIN FUNCTION AND PHYSIOLOGICAL ADAPTATION
TO HYPOXIA IN HIGH-ALTITUDE MAMMALS
JAY F. STORZ*
School of Biological Sciences, University of Nebraska, Lincoln, NE 68588, USA
Understanding the biochemical mechanisms that enable high-altitude animals to survive and function under
conditions of hypoxic stress can provide important insights into the nature of physiological adaptation. Evidence
from a number of high-altitude vertebrates indicates that modifications of hemoglobin function typically play
a key role in mediating an adaptive response to chronic hypoxia. Because much is known about structure-
function relationships of mammalian hemoglobins and their physiological role in oxygen transport, the study of
hemoglobin variation in high-altitude mammals holds much promise for understanding the nature of adaptation
to hypoxia from the level of blood biochemistry to the level of whole-organism physiology. In this review I 1st
discuss basic biochemical principles of hemoglobin function and the nature of physiological adaptation to high-
altitude hypoxia in mammals. I then discuss a case study involving a complex hemoglobin polymorphism in
North American deer mice (Peromyscus maniculatus) that illustrates how integrative studies of protein function
and fitness-related physiological performance can be used to obtain evolutionary insights into genetic
mechanisms of adaptation.
Key words: adaptation, altitude, deer mouse, ecological physiology, evolutionary physiology, hemoglobin, hypoxia, natural
selection, oxygen transport, Peromyscus maniculatus
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High-altitude environments present a number of physiolog-
ical challenges for endothermic animals, as they are character-
ized by a lower partial pressure of oxygen (Po) and lower
ambient temperatures compared to low-altitude environments
at similar latitudes. The reduced Po, at high altitude results in
reduced oxygen loading in the lungs such that the blood may
not carry a sufficient supply of oxygen to the cells of respiring
tissues (Bencowitz et al. 1982; Bouverot 1985; Turek et al.
1973). This reduced level of tissue oxygenation can impose
severe constraints on aerobic metabolism and may therefore
influence an animal's food requirements, water requirements,
the capacity for sustained locomotor activity, and the capacity
for internal heat production.
Although the genetic basis of hypoxia tolerance has yet to be
fully elucidated in any vertebrate species, evidence from a
number of mammals, birds, and amphibians indicates that
modifications of hemoglobin function often play a key role
in mediating an adaptive response to high-altitude hypoxia
(Perutz 1983). In all vertebrates other than cyclostomes, the
hemoglobin protein is a heterotetramer, composed of 2 a-chain
and 2 B-chain polypeptides. In mammals and birds, the
different subunit polypeptides are encoded by different sets
of duplicated genes that are located on different chromosomes
(Hardison 2001). Because much is known about structure-
function relationships of mammalian hemoglobins and their
role in oxygen transport (reviewed by Perutz 1983, 2001;
Poyart et al. 1992; Weber and Fago 2004), the study of hemo-
globin variation in species that are native to high altitude pro-
vides a unique opportunity to understand the nature of genetic
adaptation to hypoxic stress from the level of blood bio-
chemistry to the level of whole-organism physiology. In this
review I 1st provide some background information about hemo-
globin function and the nature of physiological adaptation to
high-altitude hypoxia. I then discuss a case study involving a
complex hemoglobin polymorphism in deer mice (Peromyscus
maniculatus) that illustrates how integrative studies of protein
function and fitness-related physiological performance can be
used to obtain evolutionary insights into genetic mechanisms
of adaptation.
* Correspondent: jstorz2@unl.edu
CIRCULATORY ADJUSTMENTS TO HYPOXIC STRESS
When atmospheric air is drawn into the alveoli of the lungs,
oxygen is under a higher partial pressure than in the pulmonary
capillaries, and it therefore diffuses across the respiratory
membrane into the arterial bloodstream. Once oxygen has en-
tered the bloodstream, it is immediately bound to hemoglobin
in the red blood cells transport the oxygen-consuming
© 2007 American Society of Mammalogists
www.mammalogy.org
24
February 2007
SPECIAL FEATURE-PHYSIOLOGICAL ADAPTATION TO HIGH ALTITUDE
25
blood Co,
mmol-L-1
Bboz
}Cao-CV,
Pao, Po
cells of respiring tissues. The gas exchange ends at the tissue
capillaries as oxygen, released by hemoglobin, diffuses across
the capillary walls through the interstitial fluid to the cells. At
the same time, CO2 and other metabolic end-products enter the
bloodstream and are transported to the lungs by the opposite
route.
At high altitude, the arterial Po, is reduced compared to what
it would be in an oxygen-rich sea-level environment and it
becomes critically important to minimize the corresponding
reduction in tissue oxygenation. In the cascade of Po, across
different compartments of the gas-exchange system, there are 2
main steps where circulatory adjustments can help minimize
the inevitable reduction in tissue Po,: the gradient between
alveolar gas and arterial blood, and that between capillary
blood and the tissues. The Po, gradient between alveolar gas
and arterial blood is normally attributable to a small amount of
venous admixture and unequal matching of ventilation to per-
fusion in the lungs (that is, a mismatch between the diameter of
the airways and the diameter of the pulmonary blood vessels).
The Po, gradient between capillary blood and the tissues results
from unloading of oxygen in the tissue capillary bed. Tissue
gas exchange begins at the arterial inlet to the capillary bed,
and the Po, falls rapidly from the arterial side to the venous
side as oxygen diffuses from the high Po, of the blood to the
low Po, of the interstitial fluid. A meaningful estimate of mean
capillary Po, and the gradient to the cells can be obtained from
measurements of arterial and mixa
mixed-venous Po, gradient can be minimized by increasing
Downloaded from https://academic.oup.com/jmammal/artic
blood Po,, Torr
Fig. 1.—A schematic representation of the oxygen dissociation
curve under physiochemical conditions prevailing in arterial blood
(open circle) and mixed venous blood (solid circle). The y-axis
measures the oxygen concentration in the blood (Co) and the x-axis
are of oxygen in the blood (Po). Cao, and
Cvo, are the oxygen concentrations in arterial and mixed venous
February 2007
SPECIAL FEATURE—PHYSIOLOGICAL ADAPTATION TO HIGH ALTITUDE
25
blood Co,
mmol-L
BDO
>Cao, CV,
Pao-Poz
cells of respiring tissues. The gas exchange ends at the tissue
capillaries as oxygen, released by hemoglobin, diffuses across
the capillary walls through the interstitial fluid to the cells. At
the same time, CO2 and other metabolic end-products enter the
bloodstream and are transported to the lungs by the opposite
route.
At high altitude, the arterial Po, is reduced compared to what
it would be in an oxygen-rich sea-level environment and it
becomes critically important to minimize the corresponding
reduction in tissue oxygenation. In the cascade of Po, across
different compartments of the gas-exchange system, there are 2
main steps where circulatory adjustments can help minimize
the inevitable reduction in tissue Po,: the gradient between
alveolar gas and arterial blood, and that between capillary
blood and the tissues. The Po, gradient between alveolar gas
and arterial blood is normally attributable to a small amount of
venous admixture and unequal matching of ventilation to per-
fusion in the lungs (that is, a mismatch between the diameter of
the airways and the diameter of the pulmonary blood vessels).
The Po, gradient between capillary blood and the tissues results
from unloading of oxygen in the tissue capillary bed. Tissue
gas exchange begins at the arterial inlet to the capillary bed,
and the Po, falls rapidly from the arterial side to the venous
side as oxygen diffuses from the high Po, of the blood to the
low Po, of the interstitial fluid. A meaningful estimate of mean
capillary Po, and the gradient to the cells can be obtained from
measurements of arterial and mixed venous Po,. The arterial-
mixed-venous Po, gradient can be minimized by increasing
the circulatory conductance of oxygen in the blood. In high-
altitude mammals, one of the primary mechanisms for increas-
ing the circulatory conductance of oxygen involves increasing
the oxygen-binding affinity of hemoglobin.
blood Poz;
Torr
Fig. 1.—A schematic representation of the oxygen dissociation
curve under physiochemical conditions prevailing in arterial blood
(open circle) and mixed venous blood (solid circle). The y-axis
measures the oxygen concentration in the blood (Co) and the x-axis
measures the partial pressure of oxygen in the blood (Po). Cao, and
Cvo, are the oxygen concentrations in arterial and mixed venous
blood, respectively. Pao, and Pvo, are the partial pressures of oxygen
in arterial and mixed venous blood, respectively. The slope of the line
joining the arterial and mixed venous points on the curve denotes the
blood oxygen capacitance coefficient (Bbo, in equations 2 and 3).
Downloaded from https://academic.oup.com/jmammal/article-abstract/88/1/24/927083 by guest on 13 April 2020
ADAPTIVE MODIFICATION OF HEMOGLOBIN
FUNCTION IN HYPOXIA-TOLERANT MAMMALS
When the arterial Po, is reduced because of high-altitude
hypoxia, the transport of oxygen by blood has to serve 2 inter-
related functions: it must maintain a sufficient flux of oxygen to
meet metabolic demand, and it must also maintain an adequate
pressure gradient for oxygen diffusion from the lungs to the
cells of respiring tissues (Bouverot 1985; Monge and León-
Velarde 1991). The 1st of these 2 functions is described by the
following Fick's convection equation:
Vo = Qb(Cao, - Cvo),
(1)
This capacitance coefficient is defined as the slope of the line
connecting the arterial point to the mixed venous point on the
oxygen-hemoglobin dissociation curve (ODC; Fig. 1). Because
of the nonlinear relationship between oxygen concentration and
Po, in blood (which gives rise to the sigmoid shape of the
ODC), the capacitance coefficient Bbo, is not constant.
The maintenance of an adequate pressure gradient for tissue
oxygenation can be understood by rearranging equation 2 as
follows:
Pvo, = Pao, - {1/(Bbo, (Qb/V02)]}, (4)
where Pvo, is viewed as the critical pressure at the vascular
supply source for oxygen diffusion into the cells of respiring
tissues (Bouverot 1985). The product Bbo, (Qb/Vo) is the
specific oxygen blood conductance. Under hypoxia, an
increased oxygen blood conductance helps to maintain
a sufficient driving force for oxygen diffusion to the tissues.
One of the most important mechanisms to compensate for
reduced arterial Po, at high altitude involves shifting the shape
and position of the ODC (Luft 1972). The ODC describes how
the reversible binding of oxygen by hemoglobin depends on
Po, in the blood. At low Po, in the bloodstream, the arterial and
mixed venous points on the ODC would be shifted leftward to
where Vo, is the rate of oxygen consumption, Qb is the total
cardiac blood flow, and Cao, and Cvo, are the oxygen con-
centrations in arterial and mixed venous blood, respectively.
This is equivalent to the following:
Vo = b Bbo, (Pao, – Pvo), (2)
where Pao, - Pvo, is the arterial-mixed-venous Po, difference,
and Bbo,, called the blood oxygen capacitance coefficient
Dejours et al. 1970), is defined by the ratio
Bbox = (Cao, - Cvo)/(Pao - Pvo).
(3)
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