Table Of ContentSturkie’s Avian Physiology
Sixth Edition
Edited by
Colin G. Scanes
Department of Biological Sciences, University of Wisconsin,
Milwaukee, WI, USA
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Dedication
To all who have inspired me—my wife,
my parents, my children, my mentors, my colleagues,
and my students and to Paul Sturkie,
who I had the privilege of knowing.
Preface
The new edition is staying true to the vision of Paul Sturkie with magnetoreception, and other senses in birds. The vol-
with the two foci of avian physiology—domesticated birds ume also returns to its roots in earlier editions with chap-
(mainly chickens) and wild birds. The volume has a cohort ters on blood, as well as carbohydrate, lipid, and protein
of returning authors who have extensively revised their metabolism.
chapters. In addition, there are multiple new chapters and The professionalism and support of Pat Gonzalez at
new authors. Some of the more recent research approaches Elsevier are gratefully acknowledged.
(e.g., genomics, transcriptomics, and proteomics) are cov-
ered in the initial chapters. Moreover, new chapters address Colin G. Scanes
recent work including the control of feed intake, endocrine Department of Biological Science, University of
disruptors, the metabolic challenges of migration together Wisconsin, Milwaukee, Milwaukee, WI, USA
xxi
Contributors
Numbers in parenthesis indicate the pages on which the authors’ contributions begin.
Rebecca Alan (667), College of the Environment and Life Yupaporn Chaiseha (717), School of Biology,
Sciences, University of Rhode Island, Kingston, RI, USA Institute of Science, Suranaree University of Technology,
Thailand
Adam Balic (403), The Roslin Institute & R(D)SVS, Univer-
sity of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK Helen E. Chmura (847), Department of Neurobiology,
Physiology and Behavior, University of California, Davis,
C.M. Bishop (919), School of Biological Sciences, Bangor
CA, USA
University, Bangor, Gwynedd, UK
Larry Clark (89), United States Department of
Julio Blas (769), Estación Biológica de Doñana, Consejo
Agriculture, Animal and Plant Health Inspection Service,
Superior de Investigaciones Científicas (CSIC), Seville,
Wildlife Services, National Wildlife Research Center, Fort
Spain
Collins, CO, USA
Meredith Bohannon (979), Department of Animal and Avian
Mark A. Cline (469), Department of Animal and Poultry
Sciences, University of Maryland, College Park, MD, USA
Sciences, Virginia Tech, Blacksburg, VA, USA
Walter Bottje (39), Department of Poultry Science, Divi-
Jamie M. Cornelius (847), Department of Neurobiology,
sion of Agriculture, University of Arkansas, Fayetteville,
Physiology and Behavior, University of California, Davis,
AR, USA
CA, USA
Eldon J. Braun (285, 975), Department of Physiology,
Dane A. Crossley II (193), Developmental Integra-
College of Medicine, University of Arizona, Tucson, AZ, USA
tive Biology Research Cluster, Department of Biologi-
Kathleen R. Brazeal (847), Department of Neurobiology,
cal Sciences, University of North Texas, Denton, TX,
Physiology and Behavior, University of California, Davis,
USA
CA, USA
Christopher G. Dacke (549), Pharmacology Division,
Shane C. Burgess (25), Vice Provost and Dean, Agriculture
School of Pharmacy and Biomedical Science, University of
& Life Sciences; Director Arizona Experiment Station; The
Portsmouth, Portsmouth, UK
University of Arizona, Tucson, AZ, USA
Veerle M. Darras (535), Department of B iological Sciences,
Warren W. Burggren (739), Developmental and
Virginia Tech, Blacksburg, VA, USA; D epartment of Biol-
Integrative Biology, Department of Biological Science,
ogy, Katholieke Universiteit Leuven, Leuven, Belgium
University of North Texas, Denton, TX, USA
Alistair Dawson (907), NERC Centre for Ecology &
P.J. Butler (919), School of Biosciences, University of Bir-
Hydrology, Midlothian, Edinburgh, UK
mingham, Edgbaston, Birmingham, UK
Karen M. Dean (979), University of Lethbridge, Lethbridge,
Johan Buyse (443), Laboratory of Livestock Physiol-
Canada
ogy, Department of Biosystems, Faculty of Bioscience
Eddy Decuypere (443), Laboratory of Livestock
Engineering, KU Leuven, Leuven, Belgium
Physiology, Department of Biosystems, Faculty of
Leah Carpenter (979), Department of Animal and Avian
Bioscience Engineering, KU Leuven, Leuven, Belgium
Sciences, University of Maryland, College Park, MD, USA
D. Michael Denbow (337, 469), Department of
Tiffany Carro (979), Department of Animal and Avian Sci-
Animal and Poultry Sciences, Virginia Tech, Blacksburg,
ences, University of Maryland, College Park, MD, USA
VA, USA
Rocco V. Carsia (577), Department of Cell Biology,
Pierre Deviche (695), School of Life Sciences, Arizona
Rowan University School of Osteopathic Medicine,
State University, Tempe, AZ, USA
Stratford, NJ, USA
Jerry B. Dodgson (3), Department of Microbiology and
Vincent M. Cassone (811, 829), Department of Biology,
Molecular Genetics, Michigan State University, East
University of Kentucky, Lexington, KY, USA
Lansing, MI, USA
xxiii
xxiv Contributors
Joëlle Dupont (613), Unité de Physiologie de la Repro- Henrik Mouritsen (113), Institut für Biologie und Um-
duction et des Comportements, Institut National de la weltwissenschaften, Universität Oldenburg, Oldenburg,
Recherche Agronomique, 37380 Nouzilly, France Germany; Research Centre for Neurosensory Sciences,
University of Oldenburg, Oldenburg, Germany
Edward M. Dzialowski (193), Developmental Integra-
tive Biology Research Cluster, Department of Biological Casey A. Mueller (739), Developmental and Integrative
Sciences, University of North Texas, Denton, TX, Biology, Department of Biological Science, University of
USA North Texas, Denton, TX, USA
Mohamed E. El Halawani (717), Department of Animal Mary Ann Ottinger (979), Department of Biology and
Science, University of Minnesota, St. Paul, MN, USA Biochemistry, University of Houston, Houston, TX, USA,
Department of Animal and Avian Sciences, University of
Carol V. Gay (549), Department of Biochemistry and
Maryland, College Park, MD, USA
Molecular Biology, Penn State University, University Park,
PA, USA M. Pines (367), Institute of Animal Sciences, Volcani
Center, Bet Dagan, Israel
Julie Hagelin (89), Institute of Arctic Biology, University
of Alaska Fairbanks, Fairbanks, AK, USA; Alaska Depart- Tom E. Porter (15), Department of Animal and Avian
ment of Fish and Game, Fairbanks, AK, USA Sciences, University of Maryland, College Park, MD, USA
Thomas P. Hahn (847), Department of Neurobiology, Frank L. Powell (301), Division of Physiology, Department
Physiology and Behavior, University of California, Davis, of Medicine, University of California, San Diego, CA, USA
CA, USA
R. Reshef (367), Department of Biology and Department
Alan L. Johnson (635), Center for Reproductive Biology of Evolutionary and Environmental Biology, University of
and Health, The Pennsylvania State University, University Haifa, Haifa, Israel
Park, PA, USA
Nicole Rideau (613), Unité de Recherches Avicoles,
Pete Kaiser (403), The Roslin Institute & R(D)SVS, Uni- Institut National de la Recherche Agronomique, 37380
versity of Edinburgh, Easter Bush, Midlothian, EH25 9RG, Nouzilly, France
UK
Johanna R. Rochester (979), The Endocrine Disruption
John Kirby (667), College of the Environment Exchange, Paonia, CO, USA
and Life Sciences, University of Rhode Island, Kingston,
Colin G. Scanes (167, 421, 455, 489, 497), Department of
RI, USA
Biological Sciences, University of Wisconsin, Milwaukee,
Christine Köppl (71), Cluster of Excellence “Hearin- WI, USA
g4all”, Carl von Ossietzky University, Oldenburg, Germany;
Elizabeth M. Schultz (847), Department of Neurobiology,
Research Center Neurosensory Science, Carl von Ossietzky
Physiology and Behavior, University of California, Davis,
University, Oldenburg, Germany; Department of Neuro-
CA, USA
science, School of Medicine and Health Science, Carl von
Jean Simon (613), Unité de Recherches Avicoles, Institut
Ossietzky University, Oldenburg, Germany
National de la Recherche Agronomique, 37380 Nouzilly,
Wayne J. Kuenzel (135), Poultry Science Center, Univer-
France
sity of Arkansas, Fayetteville, AR, USA
Toshie Sugiyama (549), Department of Agrobiology, Nii-
Vinod Kumar (811), Department of Zoology, University of
gata University, Niigata, Japan
Delhi, Delhi, India
Hiroshi Tazawa (739), Developmental and Integrative
Dusan Kunec (25), Institut für Virologie, Zentrum für
Biology, Department of Biological Science, University of
Infektionsmedizin, Freie Universität Berlin, Robert-von-
North Texas, Denton, TX, USA
Ostertag-Str. 7, Berlin, Germany
Sandra G. Velleman (379), The Ohio State University/
Scott A. MacDougall-Shackleton (847), Departments of
OARDC, Wooster, OH, USA, South Dakota State Univer-
Psychology and Biology, University of Western Ontario,
sity, Brookings, SD, USA
Canada
Jorge Vizcarra (667), Department of Food and Animal
Douglas C. McFarland (379), The Ohio State University/
Sciences, Alabama A&M University, Huntsville, AL, USA
OARDC, Wooster, OH, USA, South Dakota State Univer-
Heather E. Watts (847), Department of Biology, Loyola
sity, Brookings, SD, USA
Marymount University, Los Angeles, CA, USA
F.M. Anne McNabb (535), Department of Biological
Scott Werner (89), United States Department of Agriculture,
Sciences, Virginia Tech, Blacksburg, VA, USA; Depart-
Animal and Plant Health Inspection Service, Wildlife Servic-
ment of Biology, Katholieke Universiteit Leuven, Leuven,
es, National Wildlife Research Center, Fort Collins, CO, USA
Belgium
Contributors xxv
J. Martin Wild (55), Department of Anatomy with Takashi Yoshimura (829), Laboratory of Animal
Radiology, Faculty of Medical and Health Sciences, Physiology, Graduate School of Bioagricultural Scienc-
University of Auckland, Auckland, New Zealand es, Nagoya University, Furo-cho, Chikusa-ku, Nagoya,
Japan, Avian Bioscience Research Center, Graduate School
Shlomo Yahav (869), Department of Poultry and
of Bioagricultural Sciences, Nagoya University, Furo-cho,
Aquaculture Sciences, Institute of Animal Sciences, ARO,
Chikusa-ku, Nagoya, Japan
The Volcani Center, Bet-Dagan, Israel
Chapter 1
Avian Genomics
Jerry B. Dodgson
Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
1.1 INTRODUCTION
1.3 CHROMOSOMES
The fifth edition of Sturkie’s contained neither an avian
1.3.1 Karyotypes
genomics chapter, nor any of the subsequent three chap-
ters in this edition. Their inclusion here reflects the fact Avian karyotypes have been unusually stable during evo-
that all aspects of physiology have become intertwined lution (Burt et al., 1999; Ellegren, 2010). The ancestral
with our understanding of genes and genomes. The early avian karyotype is predicted to have 2n = 80 chromosomes,
history of this transition is discussed elsewhere (Siegel with the only subsequent change in chicken (2n = 78) being
et al., 2006), but the keystone event was the sequenc- a fusion between ancestral chromosomes 4 and 10 (Shi-
ing of the chicken genome (International Chicken busawa et al., 2004; Griffin et al., 2007). However, there
Genome Sequencing Consortium, 2004). Soon, we will are exceptions, with avian chromosome numbers ranging
have genome sequences for thousands of avian species from 40 to 126 (Griffin et al., 2007). A particular feature
(Genome 10K Community of Scientists, 2009), but the of avian karyotypes is that most species have numerous
fundamental challenge will remain: learning how to read “microchromosomes”, a trait they share with some, but not
the fascinating stories of avian physiological adaptations all, nonavian reptiles (Janes et al., 2010). The definition of a
and evolution from a long string of a billion or so A, T, microchromosome is somewhat arbitrary (Masabanda et al.,
G, and C nucleotides per bird. 2004), but, generally, microchromosomes are too small to
discriminate by size in standard karyotypes.
In those birds with fewer chromosomes (falcons, Nishida
1.2 GENOME SIZE
et al., 2008; hawks and eagles, de Oliveira et al., 2005; stone
Haploid avian genomes are generally the smallest among curlew, Nie et al., 2009), some, but not all, microchromo-
amniotes (www.genomesize.com), averaging 1.35 Gb (bil- somes have fused to ancestral macrochromosomes or to
lion base pairs). A narrow range separates the smallest each other. It remains difficult to determine orthologous
(black-chinned hummingbird, 0.9 Gb) and largest (ostrich, relationships because sequences derived from one spe-
2.1 Gb) species. Their compactness reflects the low fre- cies’ microchromosomes often fail to hybridize to those of
quency of repetitive elements that derive from transposons another species (e.g., Nie et al., 2009), suggestive of high
and their descendent sequences (International Chicken content of rapidly evolving repetitive DNA. However, in
Genome Sequencing Consortium, 2004). Avian genome size general, translocations appear to have been very rare during
correlates with physiological measures, such as with red cell avian evolution (Griffin et al., 2007), in comparison to the
size and (inversely) with metabolic rate (Gregory, 2002). It somewhat more common frequency of chromosome inver-
was proposed that small genomes were selected during the sions (Warren et al., 2010; Zhang et al., 2011; Skinner and
evolution of flight (Hughes and Hughes, 1995). However, Griffin, 2012). Interestingly, in turkeys there appears to be
Organ et al. (2007) suggested that contraction in genome size a predominance of acrocentric (centromere at or near one
preceded the acquisition of flight, and nonadaptive and neu- telomere) chromosomes (Zhang et al., 2011), whereas in
tral explanations for small bird genomes also have support falcons and hawks the trend is towards metacentric (centro-
(Lynch and Conery, 2003; Nam and Ellegren, 2012). mere near the middle) chromosomes (Nishida et al., 2008).
Sturkie’s Avian Physiology.
Copyright © 2015 Elsevier Inc. All rights reserved. 3
4 PART | I Undergirding Themes
1.3.2 Sex Chromosomes are sequenced from DNA fragments within a selected size
range. Even for genomes with deep coverage, this generates
Another characteristic that all birds share with some non-
hundreds to thousands of scaffolds that, ideally, are ordered
avian reptiles is the use of a ZW sex chromosome arrange-
and aligned using physical (based on mapping of recombi-
ment in which males are homogametic (ZZ) and females
nant clones in bacterial artificial chromosome (BAC) vec-
are heterogametic (ZW). However, sex determination has
tors) and/or linkage maps (Table 1.1).
evolved independently several times within the vertebrates,
The chicken (International Chicken Genome Sequenc-
although common genes or a common set of autosomes may
ing Consortium, 2004) and zebra finch (Warren et al., 2010)
be reused (Marshall Graves and Peichel, 2010; Ellegren,
were sequenced by the Sanger method, in which reads are
2010). The ratite W is minimally diverged from the Z (and
derived one-by-one from recombinant clone libraries. This
presumably the ancestral autosome), whereas in other
currently remains the gold standard for genome sequencing
birds, W is smaller, gene-poor, and repeat rich (Marshall
but no longer is cost-effective with the advent of next-gener-
Graves and Shetty, 2001). The Z-specific gene, DMRT1,
ation sequencing (NGS) methods, which directly sequence
appears to play a major role in masculinization (Smith
collections of (uncloned) DNA fragments in a multiparallel
et al., 2009), although it appears that both cell autonomous
manner. NGS read lengths often are shorter and sometimes
and hormonal sex determination pathways exist, with the
more error-prone than Sanger reads, but NGS compensates
interplay between the two yet to be fully elucidated (Zhao
by much higher coverage, such that the consensus sequence
et al., 2010). Further aspects of sexual differentiation are
is at least as accurate. Various NGS methods have been
discussed in later chapters.
developed (Metzker, 2010). The first avian genome to be
sequenced via NGS was that of the turkey (Table 1.1), and
1.3.3 Telomeres and Centromeres we can anticipate an onslaught of new bird genomes soon
(Genome 10K Community of Scientists, 2009).
Birds share the canonical TTAGGG telomere repeat with
all other vertebrates. However, chickens, turkeys, and other
birds possess variable numbers of unusually large telo- 1.4.2 Coverage
mere repeat blocks, even up to 3–4 Mb (million base pairs)
Most current avian genome sequence assemblies contain
in length (Delany et al., 2000; O’Hare and Delany, 2009).
about 90–95% of their respective euchromatic genomes
Although the purpose of these mega-telomeres remains
(typically 1.1–1.2 Gb; Table 1.1). Coverage is usually esti-
unknown, they map preferentially, but not obligatorily, to
mated by the fraction of different mRNA transcripts that can
specific chromosomes (Delany et al., 2007; O’Hare and
be found within the assembly. Highly repetitive heterochro-
Delany, 2009). Chicken centromeres also merit special
matic sequences, especially when repeated in tandem, are
mention. Although most contain typical long (>100 kb
nearly impossible to assemble and are missing from all ver-
pairs) arrays of chromosome-specific simple repeats, the
tebrate genomes, but these contain few genes. For example,
centromeres of GGA5, GGA27, and GGAZ are remarkably
centromeres (however, see Shang et al., 2010), telomeres,
short (∼30 kb) and lack the usual repeat structure (Shang and rDNA (tandem repeats that encode ribosomal RNA, on
et al., 2010). Being able to clone and manipulate these cen-
GGA16) are generally missing altogether or shown as gaps,
tromeres by homologous recombination (Shang et al., 2013)
and very little of the repeat-rich/gene-poor W chromosome
promises to make the chicken the primary model system
is usually assembled. Sequence scaffolds are ordered and
for the study of vertebrate centromeres. A final point is that
aligned along chromosomes for birds that have dense linkage
the zebra finch and probably other birds possess a germ-
maps and/or BAC contig physical maps, sometimes assum-
line restricted chromosome, with a function that remains
ing a common local order with closely related genomes
obscure (Itoh et al., 2009).
(comparative maps); however, most NGS-derived avian
genomes currently are unordered (Table 1.1). Sequence scaf-
1.4 GENOME SEQUENCES folds that cannot be placed are arbitrarily clustered on chrUn
(chromosome unknown) or, for example, chr1_random if the
1.4.1 Approach
chromosome but not the location is known, or simply pro-
All bird genomes sequenced to date have employed a whole vided as a list of unplaced scaffolds. Even for the chicken,
genome shotgun method, in which overlaps between mil- it has been impossible to align sequence scaffolds with spe-
lions of random reads are used to assemble contiguous cific smaller microchromosomes (GGA29–31, GGA33–38,
blocks of sequence (i.e., contigs) along the genome. Due to and most of GGA16 and 32), so any such sequence is on
their relatively low repeat content, avian genomes are ideal chrUn. In part, this is due to a paucity of aligning markers;
for shotgun sequencing. Contigs are then assembled into however, more generally, microchromosomal DNA is poorly
scaffolds (i.e., aligned groups of contigs containing size- represented in sequence reads. The reasons remain unclear,
calibrated gaps), using mate-pair reads in which both ends but they likely relate to microchromosomes being rich in
C
h
a
p
t
e
r
1|
A
TABLE 1.1 Avian Reference Genome Sequence Assemblies v
ia
n
Species/ Fold Sequenced Aligned to Scaffold Contig Approximate G
WGS Project1 Assembly1 Method2 Coverage Bases (Gb)3 Chromosome N504 (Mb) N504 (kb) Coverage5 References en
o
m
Chicken Gallus_gallus-4.0 Sanger 6.6× 1.047 Yes 12.9 280 96% International Chicken ic
AADN03 November 2011 Genome Sequencing s
Consortium, 20046
Turkey Turkey_2.01 Roche 30× 1.062 Yes 0.86 12.5 89% Dalloul et al., 2010
ADDD01 February 2011 Illumina
Zebra finch Taeniopygia_ Sanger 6× 1.232 Yes 8.24 38.6 96% Warren et al., 2010
ABQF01 guttata-3.2.4
February 2013
Budgerigar Melopsittacus_ Roche 23× 1.117 No 10.6 55.6 NR 7
AGAI01 undulatus_6.3 Illumina
February 2012
Budgerigar Koren et al. Roche 63× 1.07 No NR 100 NR 8
July 2012 Illumina
Pacific
Biosciences
Collared flycatcher FicAlb_1.4 Illumina 85× 1.116 Yes 7.3 450 NR Ellegren et al., 2012
AGTO01 November 2012
Medium ground GeoFor_1.0 Illumina 115× 1.065 No 5.3 30.5 NR 9
finch AKZB01 June 2012
Large ground finch Rands et al. Roche 6.5× 0.96 No 0.38 30.5 89% Rands et al., 2013
February 2013
Rock pigeon Cliv_1.0 Illumina 63× 1.108 No 3.15 26.6 88% Shapiro et al., 2013
AKCR01 February 2013
Puerto Rican parrot AV1 Illumina 27× 1.175 No 0.019 6.9 76% 10
AOCU01 January 2013
(Continued)
5
