differences in gene density on chicken macrochromosomes and microchromosomes

Differences in gene density on chickenmacrochromosomes and microchromosomesJ Smith, C K Bruley, I R Paton, I Dunn, C T Jones, D Windsor, D R Morrice,A S Law, J Masabanda, A Sazanov, D Waddington, R Fries, D W Burt

Summary

The chicken karyotype comprises six pairs of

large macrochromosomes and 33 pairs of smal-

ler microchromosomes1. Cytogenetic evidence

suggests that microchromosomes may be more

gene-dense than macrochromosomes. In this

paper, we compare the gene densities on

macrochromosomes and microchromosomes

based on sequence sampling of cloned genomic

DNA, and from the distribution of genes

mapped by genetic linkage and physical map-

ping. From these different approaches we

estimate that microchromosomes are twice as

gene-dense as macrochromosomes and show

that sequence sampling is an effective means of

gene discovery in the chicken. Using this

method we have also detected a conserved

linkage between the genes for serotonin 1D

receptor (HTR1D) and the platelet-activating

factor receptor protein gene (PTAFR) on chicken

chromosome 5 and human chromosome 1p34.3.

Taken together with its advantages as an

experimental animal, and public access to

genetic and physical mapping resources, the

chicken is a useful model genome for studies on

the structure, function and evolution of the

vertebrate genome.

Keywords: gene-density, microchromosomes,

sequence-sampling, chicken, gene-mapping,

gene-discovery

Introduction

The chicken karyotype consists of 39 chromo-

some pairs, six large macrochromosomes (see

footnotes) (MACs) and 33 smaller microchro-

mosomes (MICs) (Pollock & Fechheimer 1976;

Fechheimer 1990). Microchromosomes are

found in all birds (TegelstroÈm & Ryttman

1981) and some reptiles (Hinegardner 1976).

The importance of the microchromosomes has

long been debated, but we now know that they

are fully functional chromosomes with centro-

meres and telomeres (Rodionov 1996), contain

genes and show conserved synteny with other

species (Jones et al. 1997). The microchromo-

somes constitute 30% of the total chicken

genome (Smith & Burt 1998), are GC-rich

(Auer et al. 1987) and have a higher CpG

content than the macrochromosomes (McQu-

een et al. 1996). Since 60±70% of known

chicken genes are associated with a CpG-

island, the microchromosomes may represent

a gene-dense fraction of the chicken genome.

This idea is supported by acetylation studies of

histone H4 and analysis of CpG-island-like

sequences in cloned genomic DNA (McQueen

et al. 1998), which indicate that microchromo-

somes are also associated with higher gene

activity.

In this paper we compare the gene densities

on the macrochromosomes and microchromo-

somes based on sequence sampling of cloned

genomic DNA and from the distribution of

genes mapped by genetic linkage and physical

mapping. From these different approaches we

estimate that the microchromosomes are twice

as gene-dense as macrochromosomes. We also

show that sequence sampling can be used as a

means of gene discovery in the relatively

compact chicken genome.

Materials and methods

Isolation of cosmid clones and preparation of

random subclones for DNA sequencing

For sequence sampling, cosmid clones were

picked at random from a commercially avail-

able chicken genomic library (Clontech, Cali-

fornia) and DNA was prepared using Qiagen

purification columns (Qiagen GmbH, Ger-

many). Cosmid clones were found to have

an average insert size of 35 kb. 5 mg cosmid

Animal Genetics,

2000, 31, 96±103

J SmithC K BruleyI R PatonI DunnC T JonesD WindsorD R MorriceA S LawD WaddingtonD W BurtDivision of Molecular

Biology, Roslin Institute(Edinburgh), Roslin,

Midlothian EH25 9PS,

UK

J MasabandaA SazanovR FriesLehrstuhl fur Tierzucht,

TUM, Freising, Weihen-stephan, Munich D-

85350, Germany

Correspondence: Dr David W. Burt.

E-mail: [email protected] are usually classed as chromo-

somes 1±8. However, for this study, we have called

chromosomes 1±6 macrochromosomes and the re-

mainder microchromosomes, as this was the classifi-

cation used by McQueen et al. (1996). We have used

this numbering system here so that direct comparisons

could be made with this earlier work (McQueen et al.

1996, 1998).

ã 2000 International Society for Animal Genetics 96

DNA was partially digested with the restric-

tion enzyme CviJI (Cambio), which cuts at the

sequence PuG/CPy. Digestion was carried out

at 37°C for 1 h using 0.2 U enzyme mg±1

DNA. Fragments in the size range of 1±3 kb

were excised from an agarose gel and recov-

ered using a Qiaex II DNA extraction kit

(Qiagen GmbH, Germany). DNA fragments

were subcloned into EcoRV digested pBlue-

scriptSK+ (Stratagene) and plasmid DNA pre-

pared using the Qiagen 48-well system

(Qiagen GmbH, Germany). Gene specific cos-

mids were isolated as described by Buitkamp

et al. (1998).

DNA sequencing of random subclones

Each subclone was sequenced from both DNA

strands using T3 and T7 primers. Sequencing

reactions were carried out using a dye termi-

nator kit (Applied Biosystems, Perkin Elmer,

UK) and separated on an ABI 377 automated

sequencer. Typically, 500±600 nucleotides

were obtained from each primer. Following

sequencing, vector and poor quality sequence

data were removed. Contig assembly was

carried out using the Seqman program (DNAS-

tar). Searches for gene homologies were per-

formed using the GCG (version 8.0)

implementation of the BLAST algorithm

(Altschul et al. 1990). A database `hit' was

deemed to be significant if the probability and

high scores were better than 10±6 and 150,

respectively, for nucleotide searches and better

than 10±3 and 75, respectively, for protein

searches.

Fluorescence in situ hybridisation and physical

mapping of genes

Carried out as described in Smith et al.

(1999).

Genetic mapping of chicken genes

Sequences of chicken genes were obtained from

EMBL or GenBank and named using the human

gene symbol. For loci based on random cDNA

sequences, the lab symbol with an `E' postfix

was utilised, e.g. ROS0044E. Primers were

designed to amplify introns or 39-untranslated

regions, if available. Polymorphisms were iden-

tified in PCR-amplified DNA by variation in

fragment length or as single strand conforma-

tion polymorphisms (SSCP). Primers, PCR con-

ditions and any other information relating to

mapped genes are available at the chicken

genome database ± Arkdb-chick (http://

www.ri.bbsrc.ac.uk/). All markers were scored

on the chicken backcross panels previously

described (Burt et al. 1995) and genetic maps

were constructed using the Map Manager

program (Manly 1993).

Statistical analyses

The estimate for sequence sampling was

standardised by the ratio of lengths of DNA

sequence sampled. This estimate does not

have any measure of uncertainty, such as

standard errors. These can be calculated if the

marker counts are assumed to follow a

Poisson distribution, using a regression

model (McCullagh & Nelder 1989). From

physical (FISH) mapping data, the estimate

of the ratio of microchromosomal to macro-

chromosomal gene densities was calculated as

the ratio of the number of genes mapped,

standardised for the unknown sample lengths

of macro-and microchromosomes, by dividing

the corresponding ratio for anonymous loci.

This allowed for differences in the length of

the genome being sampled by this method.

For genetic linkage data, the logarithms of the

observed counts are equated to those of their

expectations (products of marker densities and

the lengths of genome sampled), giving an

estimate of the logarithm of the relative

densities of genes in macro vs. microchromo-

somes, together with its standard error. A

95% confidence interval for the relative gene

density is the antilogarithm of the estimate on

the log scale � 1.96 times its standard error.

CpG content was analysed by a two-sided

Student's t-test assuming equal variance.

Results and discussion

We used two approaches to examine the

hypothesis that chicken microchromosomes

are more gene-dense than macrochromosomes.

The first approach was based on sequence

sampling of total genomic DNA cloned from

macrochromosomes or microchromosomes and

identification of genes based on homologies

with gene sequences in nucleotide and protein

databases. (`Gene-finder' programs were initi-

ally tested on the chicken sequences we

generated. However these proved to be unsuc-

cessful in predicting the location of genes,

probably due to the contig nature of our DNA

sequences). In the second, we compared the

distribution of genes on macrochromosomes or

microchromosomes based on genetic linkage

and physical mapping data in this paper or

published elsewhere.

97

Chicken

macrochromosomes

and

microchromosomes

ã 2000 International Society for Animal Genetics, Animal Genetics 31, 96±103

Comparison of gene densities on macrochromo-

somes and microchromosomes based on se-

quence sampling of genomic DNA

Cosmid clones were selected at random and

physically mapped to either macrochromosomes

or microchromosomes by FISH. Sixteen cosmid

clones were characterised further, 8 mapped to a

macrochromosome and 8 to a microchromosome

(Table 1). Random subclones were made for each

cosmid clone by partial digestion with the

restriction enzyme Cvi JI (Xia et al. 1987; Gin-

grich et al. 1996). Sufficient random subclones

were sequenced to provide at least 40% coverage

of each cosmid clone. High quality, vector-free

sequences were then used to search nucleotide

and protein databases for gene homologies using

the BLAST algorithm (Altschul et al. 1990). The

results are summarised in Table 1. Within the

cosmid clones that mapped to macrochromo-

somes three gene homologies were found: TGFb

receptor (TGFBR1), serotonin 1D receptor

(HTR1D) and platelet-activating factor receptor

protein (PTAFR) genes. The genes for HTR1D and

PTAFR were found in the same cosmid clone and

are also linked in human on chromosome 1, at

1p36.3±34.3 and 1p35±34.3, respectively. Four

gene homologies were found in the microchro-

mosomal cosmid clones: opioid-binding cell

adhesion molecule gene (OPCML), hydroxybuty-

rate dehydrogenase (BDH), a scavenger receptor-

like protein homologous to human M130 antigen

and a homologue of the human zinc-finger

protein KIIA0677 (Ishikawa et al. 1998). From

the number of genes found in the cosmid clones

isolated from macrochromosomes and micro-

chromosomes and the amount of DNA sequenced

we estimate that the gene-density of the micro-

chromosomes is 1.3 times that of macrochromo-

somes (Table 1).

If only the euchromatic portion of the genome

were analysed, the results would be very similar

as the chicken is known to contain a very low

percentage of heterochromatin (12% compared

Table 1. Cosmid sequence sampling data

Cosmid

name

Physical

location Gene homology

Length of

match (bp)

P-value

of match CpG/kb

No. of

sequences

Total

sequence

read (bp)

Average

sequence

read (bp)

Assembled

sequence

(bp)

COS 08 MACS None 15 52 24076 463 16423

COS 16 MACS None 15 72 38808 539 26788

COS 27 MACS Serotonin 1D receptor (HTR1D) 157/251 3.6e-24 19 80 27600 345 18262

MACS Platelet activating factor receptor (PTAFR) 158/233 7.2e-33

COS 28 MACS Transforming growth factor beta receptor

Type 1 (TGFBR1)

191 2.8e-69 9 106 34132 322 13537

COS 30 MACS None 15 61 22509 369 14785

COS 33 MACS None 10 66 22704 344 14226

COS 34 MACS None 12 77 29953 389 15069

COS 35 MACS None 14 90 29970 333 12199

ALL 14 604 229752 380 131289

COS 01 MICS None 24 80 41600 520 21480

COS 07 MICS Hydroxybutyrate dehydrogenase (BDH) 91/109 7.9e-22 17 49 17738 362 13570

COS 14 MICS M130 antigen-like 201/287 8.1e-45 21 46 22540 490 12248

COS 20 MICS Opioid binding cell adhesion molecular

(OPCML)

2.4e-51 27 114 48678 427 24010

COS 21 MICS None 21 72 37512 521 19354

COS 31 MICS None 29 68 23936 352 11710

COS 32 MICS KIAA0677 protein 103/128 3.1e-24 14 88 25256 287 15577

COS 36 MICS None 21 64 21696 339 13266

ALL 22 581 238956 411 131215

Table 2. Gene density on macrochromosomes and microchromosomes based on genetic and physical mapping

Genetic linkage* Physical linkagey

Chr. No. Sizez (Mb) Anonymous Gene Relative densityx Anonymous Gene Relative density

MAC (5A + Z) 843 193 58 20 14

MIC (33A + W) 357 85 56 2.3 20 18 1.3

*See Table 3.

ySee Table 4.

zSmith & Burt 1998.

xUsing physical sizes (Mb) as shown in this Table.

98

Smith, Bruley, Paton

et al.


to 36% in human), most of which is located on the

Z and W sex chromosomes (Bloom et al. 1993).

We used the average CpG content of cosmid

clones from macrochromosomes and microchro-

mosomes as an indirect measure of the abun-

dance of CpG islands (Table 1). It was not

possible to count the number of CpG islands

directly because sequencing of cosmid clones

was not complete and we were also unable to

tell from sequencing data alone, whether the

DNA was methylated or not in vivo, and thus a

true CpG-island. From our sample of cloned

chicken genomic DNA we estimate that micro-

chromosomal DNA has a CpG content 1.6 times

that of macrochromosomal DNA (P < 0.001 and

95% confidence intervals of 1.2, 2.1). Whether

the differences in CpG content are related to

gene content or a structural feature of micro-

chromosomes has still to be determined.

On macrochromosomes we find a gene homol-

ogy every 44 kb and once every 33 kb on

microchromosomes. Previous sequencing of the

genomes of C. elegans and S. cerevisiae have

shown that only 50% of all genes are found by

database searches alone (Jones 1995). A similar

rate is found in the chicken based on partial

cDNA sequences (Bumstead and Burt, personal

communication). Therefore these estimates,

based on database searches alone, are likely to

be underestimated by a factor of two. The true

gene densities may therefore approach a gene

every 22 kb on macrochromosomes and one gene

every 17 kb on microchromosomes. From the

size of the chicken macrochromosomes and

microchromosomes (Smith & Burt 1998;

Table 2) we estimate that these chromosome

fractions contain 38000 and 21000 genes, respec-

tively. Our estimate of 59000 genes as the total

number of genes in the chicken genome is similar

to the number estimated for other vertebrates.

Although a reasonable method for finding

genes in the chicken, the sequence sampling

method has not provided us with an accurate

estimate of gene density due to the small sample

of gene homologues. Many more clones would

have to be examined in order for a more realistic

evaluation of gene density by this method. We

then went on to examine physical and genetic

mapping data in order to establish a more

confident assessment of the gene density on

the microchromosomes compared to the macro-

chromosomes.

Comparison of gene densities on macrochromo-

somes and microchromosomes based on physi-

cal mapping and genetic linkage

The likelihood of mapping a gene to a

Table 3. Genes which have been mapped by FISH

Locus Chr. type R Locus Chr. type R Locus Chr. type R

ASCL1 MACS 0 SCD* MICS 1 IGF1R MICS 0

CCND2* MACS 1 ALDH MICS 0 MC1R MICS 0

CCND2P* MACS 0 NRAMP1* MICS 1 NCAM1* MICS 1

DCN MACS 0 RPL37A* MICS 1 NGFB* MICS 1

GAPD* MACS 0 RPL5* MICS 1 OPCML MICS 0

H5* MACS 0 ABL1 MICS 0 OVM* MICS 1

HISA@* MACS 0 ACACA* MICS 1 PGA@ MICS 0

IGF1* MACS 1 ADORA1 MICS 0 PPY MICS 0

PGR* MACS 1 ADORA3 MICS 0 PRNP MICS 0

UCP2 MACS 0 AK1* MICS 0 RAF1* MICS 0

TGFBR1 MACS 0 ANX2 MICS 0 RARB MICS 0

ACTB* MACS 0 B2M* MICS 0 RNR* MICS 1

CCNC* MACS 1 BBC1 MICS 1 RPL7A* MICS 1

MYB* MACS 0 BMP7 MICS 0 SLC6A4 MICS 0

HMG14* MACS 1 CAMLG MICS 0 SUV3 MICS 1

IL8 MACS 0 CCNE* MICS 1 TAX1 MICS 0

IRF2* MACS 1 CD3E MICS 0 TF* MICS 1

KIT MACS 0 CDC2L1* MICS 1 TRAF1 MICS 0

PGK1* MACS 1 COS0032* MICS 0

CCND1* MACS 1 CRABP1 MICS 0

HTR1D MACS 0 DCM11* MICS 1

MAX* MACS 1 DMD* MICS 1

TGFB3* MACS 1 FASN* MICS 1

TH* MACS 1 FES* MICS 0

AVDL@ MACS 1 FLN2 MICS 0

IFN1* MACS 1 FMOD MICS 0

TRKB* MACS 1 H3F3B* MICS 0

99

Chicken

macrochromosomes

and

microchromosomes


macrochromosome or microchromosome by

physical or genetic methods depends on the

underlying gene density. We therefore made a

comparison of the relative number of genes on

these chromosomes from physical mapping

experiments (Table 3) and genetic linkage

data (Table 4) described in this paper and

elsewhere. Only markers, which had been

Table 4. Genes which have been mapped by genetic linkage analysis

Locus Chr. No. Type R Locus Chr. No. Type R Locus Chr. No. Type R

SMOH 1 SSCP 1 FMR1 4 MICR 0 RYR1 E25C31 SSCP 1

NRCAM* 1 SNP 1 SPP1* 4 HET 1 GNRHR E29C09W09 SSCP 1

GNRH 1 SSCP 1 COM0117E* 4 RFLP 1 IGF1R* E29C09W09 RFLP 1

NAGA* 1 SNP 1 MSX1 4 RFLP 1 AGC1* E29C09W09 SSCP 1

LGALS4* 1 SNP 1 CD8A* 4 RFLP 1 HMX3* E29C09W09 RFLP 1

COM0119E* 1 RFLP 1 CAPN1* 5 HET 1 CYP19 E29C09W09 SSCP 1

IGF1* 1 RFLP 1 RYR3* 5 HET 1 CCNE E30C14W10 SSCP 1

LDHB* 1 RFLP 1 HTR1D 5 SSCP 1 MYH@* E31E21C25W12 MICR 0

GAPD* 1 SNP 1 TGFB3* 5 RFLP 1 ROS0022E E31E21C25W12 MICR 0

HSD3B* 1 SNP 1 COM0089E* 5 RFLP 1 H3F3B* E31E21C25W12 RFLP 1

COM0155E* 1 RFLP 1 DNCL* 5 RFLP 1 FASN* E31E21C25W12 SSCP 1

ROS0044E 1 MICR 0 CKB* 5 HET 1 COM0093E* E31E21C25W12 RFLP 1

ROS0081E 1 MICR 0 BMP4 5 RFLP 1 HLF E31E21C25W12 MICR 0

LAMP1* 1 MICR 0 PRLR* Z SSCP 1 BMP7* E32 RFLP 1

COM0092E* 1 RFLP 1 MSU0068E* Z RFLP 1 FZF* E32 SNP 1

RB1* 1 SNP 1 ROS0072E Z MICR 0 ROS0078E E36C06W08 MICR 0

FUCT4* 1 SNP 1 PTCH* Z SSCP 1 EIF4A2* E36C06W08 RFLP 1

ROS0025E 1 MICR 0 ROS0017E Z MICR 0 SNON* E36C06W08 SNP 1

ROS0055E 1 MICR 0 CHRNB3* Z SNP 1 ROS0073E E38 MICR 0

WNT11* 1 RFLP 1 LPL* Z SSCP 1 CPRR* E38 CLAS 1

SHH 2 SSCP 1 ALDOB* Z SNP 1 COM0152E* E38 RFLP 1

NPY 2 SSCP 1 GGTB2* Z SNP 1 ROS0020E E41W17 MICR 0

ROS0018E 2 MICR 0 ROS0028E 6 MICR 0 RPL7A* E41W17 RFLP 1

CP49* 2 RFLP 1 PDE6C* 6 HET 1 ABL1* E41W17 SNP 1

TGFBR1 2 RFLP 1 ACTA2* 6 MICR 0 CD39L1* E41W17 SNP 1

PRL 2 SSCP 1 SCD* 6 SSCP 1 AMBP* E41W17 SNP 1

BMP6 2 RFLP 1 PSAP* 6 RFLP 1 HSF1* E46C08W18 MICR 0

BCL2* 2 MICR 0 CPII* 7 CLAS 1 ITGAM* E46C08W18 MICR 0

ZNF5* 2 SNP 1 ROS0019E 7 MICR 0 POU4F3* E48C28W13 RFLP 1

ROS0023E 2 MICR 0 CD28* 7 RFLP 1 CAMLG* E48C28W13 SNP 1

ROS0074E 2 MICR 0 EEF1B2* 7 RFLP 1 CDX1* E48C28W13 SNP 1

PENK* 2 SNP 1 ROS0021E 8 MICR 0 ROS0083E E48C28W13 MICR 0

CA2* 2 SNP 1 GGTB1* 8 HET 1 MSX2 E48C28W13 RFLP 1

CALB1* 2 RFLP 1 VTG2* 8 HET 1 OPCML E49C20W21 SSCP 1

BMP2 3 RFLP 1 ROS0026E 8 MICR 0 POU2F3* E49C20W21 RFLP 1

TGFB2* 3 RFLP 1 PLA2G2A* 8 HET 1 APOA1* E49C20W21 SNP 1

ACTN2* 3 SNP 1 B@* 16 RFLP 1 W* E49C20W21 CLAS 1

HMX1* 3 RFLP 1 RFP-Y@* 16 RFLP 1 ACACA* E52W19 SSCP 1

T 3 RFLP 1 CPAA* E04 CLAS 1 CRK* E52W19 SSCP 1

IGF2R* 3 SNP 1 CPEE* E04 CLAS 1 AMH E53C34W16 MICR 0

VIP 3 SSCP 1 PGA@* E04 HET 1 TVA* E53C34W16 RFLP 1

ESR* 3 RFLP 1 ARF4* E16C17W22 RFLP 1 CDC2L1* E54 SNP 1

PLN* 3 MICR 0 MIF* E18C15W15 RFLP 1 AGRN* E54 SNP 1

BMP5 3 RFLP 1 IGL@* E18C15W15 MICR 0 ENO1* E54 SNP 1

GSTA2* 3 SNP 1 CRYBB1* E18C15W15 MICR 0 PLOD* E54 SNP 1

ODC1 3 RFLP 1 I* E22C19W28 CLAS 1 SLC2A1* E54 RFLP 1

CPPP* 3 CLAS 1 ROS0054E E22C19W28 MICR 0 TP53* E57 SNP 1

COM0094E* 4 RFLP 1 GLI E22C19W28 SSCP 1 COL1A1* E59C35W20 MICR 0

HMG14A* 4 RFLP 1 TGFB1 E25C31 RFLP 1 ROS0071E E59C35W20 MICR 0

Bold, new gene assignments in this paper.

SSCP-single strand conformation polymorphism; SNP-single nucleotide polymorphism; RFLP-restriction fragment length polymorphism;

MICR-microsatellite; CLAS-classical. R-random; 1 ± clone was mapped with no a priori knowledge of map location; 0 ± clone was mapped

with prior knowledge of its position in the genome and cannot therefore be used in this analysis.

*References in Chicken genome database (http://www.ri.bbsrc.ac.uk/).

100


et al.


mapped at random, i.e. having no a priori

knowledge of physical map location, were

used in this analysis.2

Physical mapping

We have cytogenetically mapped 31 more genes

onto the physical map of the chicken genome

(Table 3) and when combined with published

results brings the total number of genes mapped

at random to 72. It should be noted however,

that the anonymous clones distribute them-

selves between the macro-and microchromo-

somes in a ratio of 50 : 50. This is not the 70 : 30

split which would be expected if the clones

were distributing according to the size of the

genome represented by the two sets of chromo-

somes. It must be assumed therefore, that there

is a cloning bias inherent in the genomic

libraries used for obtaining clones for these

physical mapping studies. The number of

physical markers mapped with no a priori

knowledge of gene content were used as a

correction factor for the true physical size of

chromosomes. This allowed for differences in

the length of the genome being sampled by this

method (see Materials and methods).

Twenty anonymous and 14 genes (random)

have been assigned to the physical maps of

macrochromosomes, and represent a ratio of

0.70 genes/anonymous loci. On the microchro-

mosomes, 20 anonymous and 18 gene markers

(random) have been mapped, and represent a

ratio of 0.90 genes/anonymous loci (Tables 2

and 3). From this physical mapping data, we

estimate that the microchromosomes are 1.3

times (with a 95% confidence interval of 0.5,

3.3) as dense as the macrochromosomes. So far,

108 genes have been mapped by FISH but many

target specific chromosomes or were selected

based on comparative maps with human

(unpublished data). Unfortunately the small

sample size of randomly mapped genes and

the skewed distribution of cloned genomic DNA

is a limitation of this approach. Genetic linkage

data was therefore analysed.

Genetic linkage

In this paper we have mapped a further 46 genes

on the genetic map of the chicken (Table 4) and

together with published data, this brings the

total number of genes mapped at random to 147.

A wide variety of genetic markers (i.e. micro-

satellites, RFLP, RAPD, AFLP, SSCP and CR1)

were used to construct the genetic map, repre-

senting markers on all chicken chromosomes

(Burt & Cheng 1998). We estimate that the

genetic map is almost complete (Smith & Burt

1998) with a new genetic marker having a

greater than 95% chance of linkage to any

other previously mapped marker.

Previous reports by Primmer et al. (1997)

suggested that microsatellite sequences may

not be randomly distributed and may be present

at a lower density on the microchromosomes.

To test this we compared the distribution of

microsatellites and other genetic markers on the

genetic map for both anonymous and gene

sequences (Table 5). For anonymous markers

we expected 70% to map to the macrochromo-

somes and 30% to the microchromosomes based

on their physical size (Smith & Burt 1998).

Contrary to expectations from the work by

Primmer et al. (1997), we found more micro-

satellite markers than expected on the micro-

chromosomes (157 out of 368, which is 43%).

This discrepancy may be explained as a techni-

cal problem with the PRINS technique used by

Primmer et al. (1997) on chicken microchromo-

somes. The distribution of other genetic markers

appears to be at random and is proportional to

Table 5. Distribution of genetic markers on macrochromosomes and microchromosomes*

Chromosomes Microsatellites % Other %

Anonymous genetic markers

MAC (5A + Z) 211 57.3 193 69.4

MIC (33A + W) 157 42.7 85 30.6

Total 368 100.0 278 100.0

Genetic markers of genes

MAC (5A + Z) 13 39.4 58 50.9

MIC (33A + W) 20 60.6 56 49.1

Total 33 100.0 114 100.0

*Based on the East Lansing genetic map (Burt et al. 1995).

2Although `randomness' of cloning cannot be accurately quantified for every gene that has been mapped, we tried

to get as near to this as possible be eliminating genes which we knew had definitely been mapped with prior

knowledge or estimate of map position.

101

Chicken

macrochromosomes

and

microchromosomes


the physical size of each chromosome

(70% : 30%). Consequently, the distribution of

genes based on these kinds of genetic markers

are more likely to mirror the true distribution of

genes over the chicken genome.

Excluding microsatellite-based markers, 58

gene markers have been assigned randomly to

the genetic maps of macrochromosomes

(Table 2). On the microchromosomes, 56 gene

markers have been mapped. When this genetic

mapping data is compared to the physical size

of the genome represented by the two sets of

chromosomes, we estimate that the microchro-

mosomes are 2.3 times as gene-dense as the

macrochromosomes (with a 95% confidence

interval of 1.6, 3.3).

Conclusion

Accurate estimates for the relative gene density

were not possible in earlier studies (McQueen

et al. 1996; McQueen et al. 1998) but suggested a

6-fold difference in gene density (an estimate

based mostly on CpG-island-like sequences in

cloned genomic DNAs) on macrochromosomes

and microchromosomes, and that 75% of all

chicken genes were located on the microchro-

mosomes. If true, this should have been reflected

in significantly more gene homologies being

found by the sequence sampling approach,

possibly 16 gene homologies on the cosmids

isolated from the microchromosomes and only 2

or 3 from the eight macrochromosomal cosmids.

This contrasts with our more conservative

estimate of around 50% of all chicken genes

being located in the microchromosome fraction,

thus explaining the lower number of sequence

homologies found by sequence sampling. Our

analysis of physical and genetic mapping data

gives us an estimate of around a 1.5-fold to 3.5-

fold difference in gene density, which is not

consistent with the original estimate of a 6-fold

difference. The difference between these two

predictions is probably explained by the differ-

ent approaches taken to identify genes. In this

paper our estimate is based on a direct gene

approach: genetic mapping of previously char-

acterised genes. The work by McQueen et al.

(1996, 1998) is based on differences in CpG

content and other indirect measures of gene

activity, and so may overestimate the true gene

content. For example, the initial FISH method

used is not quantitative and the authors admit to

analysing CG-like fragments, thus conceding

that it may not be just true CpG islands which

were studied.

Recent work by Clark et al. (1999) used a

similar approach to our study and also

attempted to answer the question of gene density

differences by using a sequence sampling

approach. They identified 12 gene homologies

from database searches after sequence scanning

19 chicken cosmids ± 3 hits to macrochromo-

somes and 9 to microchromosomes. Although

contig assembly was not carried out and the total

amount of DNA sequenced was not given, the

gene density difference from this work can be

estimated. Given that there were 8 macro-and 10

microchromosomal clones analysed, and assum-

ing the same amount of sequencing was carried

out on each clone, the gene density difference

can be calculated to be around 2.4 times higher

on the microchromosomes ± a figure which is

very close to our own evaluation.

How did the two-fold difference in gene

density (and CpG islands?) between avian

macrochromosomes and microchromosomes

evolve? In mammalian chromosomes gene den-

sity differences are correlated with chromosome

banding patterns, the R bands having higher

gene densities than the G bands (Craig &

Bickmore 1994). The avian microchromosomes

share many characteristics in common with

these mammalian R bands: high gene density,

high CpG island content (McQueen et al. 1996),

early replication in S phase (McQueen et al.

1998) and an increased rate of recombination of

2±4 fold when compared to the macrochromo-

somes (Rodionov et al. 1992). Why should

microchromosomes differ from macrochromo-

somes in these ways? It has been suggested

(Craig & Bickmore 1994) that meiotic recombi-

nation may tend to initiate in the accessible

chromatin at the promoters of genes. This close

correlation between gene density and recombi-

nation rate is therefore to be expected. Rodionov

(1996) also suggest that the higher recombina-

tion rate on these small chromosomes is to

ensure pairing of chromosomes occurs during

mitosis. This correlation between higher recom-

bination rate and higher gene density, thus

suggests an evolutionary pressure for an

increase in gene density on the microchromo-

somes. Why the microchromosomes arose in the

first place, however, is a question which still

has to be answered.

Acknowledgements

Many thanks to Dr Darren Griffin for invaluable

assistance with the FISH method. This work was

supported by the Biotechnology and Biological

Science Research Council (BBSRC), Ministry of

Agriculture, Fisheries and Food (MAFF) and the

EC Biotechnology programme BIO4-CT95±0287,

as part of the European ChickMAP project.

102


et al.


GenBank Accession Numbers: The nucleotide

sequence data has been submitted to GenBank

under accession numbers: Cosmid 1 (AJ231686±

231708), Cosmid 7 (AJ231709±231736), Cosmid

8 (AJ231737±231764), Cosmid 14 (AJ231765±

231785), Cosmid 16 (AJ231786±231815), Cos-

mid 20 (AJ231816±231844), Cosmid 21

(AJ231845±231871), Cosmid 27 (AJ231872±

231918), Cosmid 28 (AJ231919±231950), Cos-

mid 30 (AJ231951±231979), Cosmid 31

(AJ231980±232004), Cosmid 32 (AJ232005±

232047), Cosmid 33 (AJ232048±232078), Cos-

mid 34 (AJ232079±232106), Cosmid 35

(AJ232107±232137) and Cosmid 36 (AJ232138±

232169).

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Chicken

macrochromosomes

and

microchromosomes


differences in gene density on chicken macrochromosomes and microchromosomes

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