Evolution of genomes, host shifts and the geographic spread of SARS-CoV and related coronaviruses.

Severe acute respiratory syndrome (SARS) is a novel human illness caused by a previously unrecognized coronavirus (CoV) termed SARS-CoV. There are conflicting reports on the animal reservoir of SARS-CoV. Many of the groups that argue carnivores are the original reservoir of SARS-CoV use a phylogeny to support their argument. However, the phylogenies in these studies often lack outgroup and rooting criteria necessary to determine the origins of SARS-CoV. Recently, SARS-CoV has been isolated from various species of Chiroptera from China (e.g., Rhinolophus sinicus) thus leading to reconsideration of the original reservoir of SARS-CoV. We evaluated the hypothesis that SARS-CoV isolated from Chiroptera are the original zoonotic source for SARS-CoV by sampling SARS-CoV and non-SARS-CoV from diverse hosts including Chiroptera, as well as carnivores, artiodactyls, rodents, birds and humans. Regardless of alignment parameters, optimality criteria, or isolate sampling, the resulting phylogenies clearly show that the SARS-CoV was transmitted to small carnivores well after the epidemic of SARS in humans that began in late 2002. The SARS-CoV isolates from small carnivores in Shenzhen markets form a terminal clade that emerged recently from within the radiation of human SARS-CoV. There is evidence of subsequent exchange of SARS-CoV between humans and carnivores. In addition SARS-CoV was transmitted independently from humans to farmed pigs (Sus scrofa). The position of SARS-CoV isolates from Chiroptera are basal to the SARS-CoV clade isolated from humans and carnivores. Although sequence data indicate that Chiroptera are a good candidate for the original reservoir of SARS-CoV, the structural biology of the spike protein of SARS-CoV isolated from Chiroptera suggests that these viruses are not able to interact with the human variant of the receptor of SARS-CoV, angiotensin-converting enzyme 2 (ACE2). In SARS-CoV we study, both visually and statistically, labile genomic fragments and, putative key mutations of the spike protein that may be associated with host shifts. We display host shifts and candidate mutations on trees projected in virtual globes depicting the spread of SARS-CoV. These results suggest that more sampling of coronaviruses from diverse hosts, especially Chiroptera, carnivores and primates, will be required to understand the genomic and biochemical evolution of coronaviruses, including SARS-CoV. © The Willi Hennig Society 2008. © The Willi Hennig Society 2008.

Severe acute respiratory syndrome (SARS) is a recently described human infectious disease caused by a previously unrecognized coronavirus, SARS‐CoV (Ksiazek et al., 2003). Between November 2002 and August 2003, there were 8422 cases and 916 deaths from SARS (WHO, 2003). These numbers are not on the scale of major epidemics such as seasonal forms of influenza infecting humans, but in an era of rapid globalization, the potential for a pandemic was significant. SARS‐CoV infection has not been reported among humans since the early days of 2004. However, there remain conflicting reports on the animal reservoir of SARS‐CoV. Guan et al. (2003) and Kan et al. (2005) implicate small carnivores whereas Li et al. (2005) and Lau et al. (2005) asserted that Chiroptera are the animal reservoir of SARS‐CoV. In a comprehensive review of CoV among Chiroptera, Tang et al. (2006) argued that the origin of SARS‐CoV remains unknown.

Among humans, serological surveys indicate that SARS‐CoV viruses were circulating in subepidemic levels in 2001 in residents of Hong Kong (data from mainland China is not available) (Zheng et al., 2004). Also, in describing the world's largest SARS epidemic in Beijing, Pang et al. (2003) point out that “It is possible that some SARS cases were not counted before mid‐April 2003 when the extent of the outbreak was fully recognized.”

In a search for the animal reservoir of SARS‐CoV outside of urban areas Kan et al. (2005) surveyed farmed Parguma larvata (Himalayan palm civet) in 25 farms spread over 12 provinces in South‐east China and found no evidence of SARS‐CoV infection. SARS‐CoV in carnivores was isolated to animals in the Xinyuan market, in the suburbs of Guangzhou, China. Vijaykrishna et al. (2007) make the argument that Chiroptera are a reservoir for a wide variety of coronaviruses (SARS and non‐SARS) that affect humans and animals. Before the SARS outbreak, coronaviruses were known primarily from animals of agricultural importance in which they cause respiratory and enteric infections (Siddell et al., 1983). The human strains CoV‐229E and CoV‐OC43, which are distantly related to SARS‐CoV, cause mild respiratory illnesses similar to the common cold (Mahony and Richardson, 2005). Recently Dominguez et al. (2007) have shown that Chiroptera (Myotis occultus and Eptesicus fuscus from the Rocky Mountains of Colorado, USA, carry group 1 coronaviruses. Our preliminary analyses show that these CoVs from Rocky Mountain Chiroptera are very closely related to group 1 CoV that infect humans (e.g., CoV‐229E and CoV‐OC43).

Genomic sequence data

The genome of a coronavirus is comprised of a single‐stranded, positive‐sensed RNA molecule 27–31 kilobases in length (Lai, 1990). Before the SARS‐CoV outbreak coronavirus diversity was poorly documented, especially at the genomic level. However, coronavirus research has been invigorated since the sequencing of the first SARS‐CoV isolate (Marra et al., 2003; Rota et al., 2003). For example, in the wake of SARS, two novel human coronaviruses were found [HKU1, GenBank (http://www.ncbi.nlm.nih.gov) accession AY597011 (Woo et al., 2005); and NL63, GenBank accession NC_005831 (van der Hoek et al., 2004)]. Also notable are the release of new genomic sequences for SARS‐CoV among carnivores, artiodactyls, humans and Chiroptera (Guan et al., 2003; Chinese SARS Molecular Epidemiology Consortium, 2004; Tu et al., 2004; Chen et al., 2005; Lau et al., 2005; Li et al., 2005; Tang et al., 2006).

Guan et al. (2003) sequenced several partial and complete genomes from SARS‐CoV isolated in 2003 from two small carnivore hosts Parguma larvata and Nyctereutes procyonoides (raccoon dog) that were for sale in live animal markets in Shenzhen, Guangdong Province, China. Complete and partial genomes of the coronaviruses isolated from P. larvata[SARS‐CoV SZ1, SZ16, SZ3; GenBank accessions AY304489, AY304488 and AY304486] and Nyctereutes procyonoides (SARS‐CoV SZ13; GenBank accession AY304487) became available publically in September 2003 but were updated in November 2003. A complete genome of a SARS‐CoV isolated from P. larvata host was released in January, 2005 (SARS‐CoV HC/SZ/61/03; GenBank accession AY515512). A complete genome of SARS‐CoV isolated from Melogale moschata, the Chinese ferret badger, was released in March, 2005 (SARS coronavirus CFB/SZ/94/03; GenBank accession AY545919).

Several, but not all of the genomes of the coronaviruses isolated from small carnivores contain a specific 29‐nucleotide region (CCTACTGGTTACCAACCTGAATGGAATAT, e.g., positions 27869–27897 in the of AY304488) in a protein with an unknown function. It was initially reported that this 29‐nucleotide region was absent from all human SARS‐CoV isolates sequenced with the notable exception of one isolate from Guangdong that contains the 29‐nucleotide region (GD01 GenBank accession AY278489) (Guan et al., 2003); however, several human isolates were later discovered to contain the region. Owing to the perceived potential of the 29‐nucleotide region as a clue to the animal origins and subsequent adaptation of SARS‐CoV to human hosts, this 29‐nucleotide region garnered media attention as early as May 2003 as a “29‐nucleotide deletion” in human SARS‐CoV that enabled animal to human transmission (Bradsher and Altman, 2003; Enserink, 2003).

SARS‐CoV isolates from Chiroptera contain a different 29‐nucleotide sequence (CCAATACATTACTATTCGGACTGGTTTAT, e.g., positions 27866–27894 in DQ648857, Bat coronavirus BtCoV/279/2005) in a protein with an unknown function. This fragment from isolates of SARS‐CoV derived from Chiroptera is in an orthologous genomic position to the 29‐nucleotide region described above for some SARS‐CoV isolated from small carnivores and humans. When the 29‐nucleotide regions from Chiroptera versus human and carnivore hosts are compared, 12 nucleotide positions are polymorphic (Lau et al., 2005). Under the current sampling of SARS‐CoV, this fragment is exclusive to SARS‐CoV isolated from Chiroptera.

The Chinese SARS Molecular Epidemiology Consortium (2004) published an analysis of molecular evolution of SARS‐CoV within humans during the 2002–03 epidemic. This study included the release of many new genomic sequences of SARS‐CoV from humans infected in the early stages of the outbreak in southern China .

A human SARS‐CoV associated with a re‐emergent case of SARS in Guangzhou, Guangdong Province, China was isolated December 22, 2003. The sequence of this SARS‐CoV spike gene was released in February 2004 (SARS‐CoV GD03T0013; GenBank accession AY525636).

Song et al. (2005) released many full and partial genome sequences of SARS‐CoV isolated from human and palm civet cats collected in southern China into the public domain in 2005 .Kan et al. (2005) released many spike gene and three full genome sequences for SARS‐CoV isolated from human, raccoon dog and civet cat hosts into the public domain in July, 2006 .

Li et al. (2005) published SARS‐CoV nucleoprotein and spike gene sequences (some recently updated as whole genomes) isolated from Chiroptera: Rhinolophus sinicus, Rhinolophus ferrumequinum, Rhinolophus macrotis and Rhinolophus pearsoni. Lau et al. (2005) published three complete SARS‐CoV genomes isolated from the bat Rhinolophus pearsoni and a SARS‐CoV polymerase sequences from Rhinolophus sinicus. Poon et al. (2005) published sequences of RNA‐dependent RNA polymerase (RdRp), polyprotein, and spike genes of a non‐SARS‐CoV isolated from the bat Miniopterous pusillus. Tang et al. (2006) published a review of bat coronaviruses in August, 2006 and released three genomes and 70 gene fragments in July, 2006.

Receptor binding studies

Li et al. (2006) provide a review of the structural biology of the SARS‐CoV spike protein and the variation of the receptor for spike protein on host cells, angiotensin‐converting enzyme 2 (ACE2), among human and carnivore hosts. These authors point out via pairwise alignment that the spike protein of SARS‐CoV isolated from Chiroptera lack a stretch of amino acid residues and have mismatches among other residues that form the receptor‐binding motif for the human variant of ACE2.

There is also empirical evidence concerning the relative affinity of various spike proteins to ACE2 from various hosts. The SARS‐CoV spike proteins tested include: an early epidemic, 2002–03, human isolate (SARS‐CoV, TOR 2), a human isolate tied to sporadic infections in 2003–04 (SARS‐CoV, GD03T0013), and a carnivore isolate (P. larvata, SZ3) from 2003 to 2003 (Li et al., 2005). 2006, 2005) describe and “expected” result for SZ3 and an “unexpected” result for GD03T0013 that both of these spike proteins bound P. larvata ACE2 better than they bound human ACE2. Spike protein from TOR 2 bound ACE2 from P. larvata and human equally well. The unexpected nature of their results is tied to the perception that the SARS‐CoV virus was adapting from carnivore to humans as suggested by prevailing phylogenetic studies of the time (e.g., Guan et al., 2003; Chinese SARS Molecular Epidemiology Consortium, 2004; Kan et al., 2005; Song et al., 2005).

Methods

Demarcation of sequence characters

We compared nucleotide sequences for whole and partially sequenced genomes that were in the public domain as of January 1, 2005. This data set included 83 viruses from a wide host and geographic range (Table 1). First, we compared these genomes with ClustalW under default settings (i.e., gap opening penalty 15 gap extension penalty 6.66, DNA transition weight 0.5) (Thompson et al., 1994) and developed a set of fragment boundaries that accommodated both sequence similarity and unequal sequencing coverage. We then split the genomes along these boundaries and remove all gaps inserted by ClustalW, thus forming 62 sequence fragment characters for POY3 (Wheeler et al., 2006).

Table 1

 GenBank accession numbers and descriptions of genomes and partial genomes of virus exemplars considered in the 83 isolate data set

GenBank accession no.	Name of virus
AF124986	Canine coronavirus
AF124987	Feline infectious peritonitis virus
AF124988	Porcine hemagglutinating encephalomyelitis virus
AF124989	Human coronavirus OC43
AF124990	Rat sialodacryoadenitis coronavirus
AF124991	Turkey coronavirus
AF201929	Murine hepatitis strain 2
AF207902	Murine hepatitis virus ML11
AF208066	Murine hepatitis virus Penn 971
AF208067	Murine hepatitis virus ML10
AF220295	Bovine coronavirus Quebec
AF304460	Human coronavirus 229E
AF391542	Bovine coronavirus LUN
AJ271965	Transmissible gastroenteritis virus
AY278487	SARS coronavirus BJ02
AY278488	SARS coronavirus BJ01
AY278489	SARS coronavirus GD01
AY278490	SARS coronavirus BJ03
AY278491	SARS coronavirus HKU39849
AY278554	SARS coronavirus CUHK W1
AY278741	SARS coronavirus Urbani
AY279354	SARS coronavirus BJ04
AY282752	SARS coronavirus CUHK Su10
AY283794	SARS coronavirus SIN 2500
AY283795	SARS coronavirus SIN 2677
AY283796	SARS coronavirus SIN 2679
AY283797	SARS coronavirus SIN 2748
AY283798	SARS coronavirus SIN 2774
AY291315	SARS coronavirus Frankfurt1
AY291451	SARS coronavirus TW1
AY297028	SARS coronavirus ZJ01
AY304486	SARS coronavirus SZ3 civet cat
AY304487	SARS coronavirus SZ13 civet cat
AY304488	SARS coronavirus SZ16 civet cat
AY304489	SARS coronavirus SZ1 raccoon dog
AY304490	SARS coronavirus GZ43
AY304491	SARS coronavirus GZ60
AY304492	SARS coronavirus HKU 36871
AY304493	SARS coronavirus HKU 65806
AY304494	SARS coronavirus HKU 66078
AY304495	SARS coronavirus GZ50
AY313906	SARS coronavirus GD69
AY321118	SARS coronavirus TWC
AY323977	SARS coronavirus HSR1
AY345986	SARS coronavirus CUHK AG01
AY345987	SARS coronavirus CUHK AG02
AY390556	SARS coronavirus GZ02
AY394978	SARS coronavirus GZ B
AY394979	SARS coronavirus GZ C
AY394980	SARS coronavirus GZ D
AY394981	SARS coronavirus HGZ8L1 A
AY394982	SARS coronavirus HGZ8L1 B
AY394983	SARS coronavirus HSZ2 A
AY394984	SARS coronavirus HSZ A
AY394985	SARS coronavirus HSZ Bb
AY394986	SARS coronavirus HSZ Cb
AY394987	SARS coronavirus HZS2 Fb
AY394989	SARS coronavirus HZS2 D
AY394990	SARS coronavirus HZS2 E
AY394991	SARS coronavirus HZS2 Fc
AY394992	SARS coronavirus HZS2 C
AY394993	SARS coronavirus HGZ8L2
AY394994	SARS coronavirus HSZ Bc
AY394995	SARS coronavirus HSZ Cc
AY394996	SARS coronavirus ZS B
AY394997	SARS coronavirus ZS A
AY394999	SARS coronavirus LC2
AY395000	SARS coronavirus LC3
AY395001	SARS coronavirus LC4
AY395002	SARS coronavirus LC5
AY395003	SARS coronavirus ZS C
AY395004	SARS coronavirus HZS2 Bb
AY515512	SARS coronavirus HC SZ 61 03 civet cat
AY525636	SARS coronavirus GD03T0013
AY567487	Human Coronavirus NL63
AY654624	SARS coronavirus TJF pig
BCU00735	Bovine coronavirus Mebus
NC_001451	Avian infectious bronchitis virus
NC_001846	Murine hepatitis virus MHVA59
NC_003045	Bovine coronavirus
NC_003436	Porcine epidemic diarrhea virus
NC_004718	SARS coronavirus TOR2
NC_005147	Human coronavirus OC43 NL

We use the same ClustalW settings to produce an updated aligned data set of whole and partially sequenced genomes that were in the public domain as of July 21, 2006. The updated data set includes 157 viruses many of which were isolated from Chiroptera and small carnivore hosts (Table 2). We then split the genomes along 66 boundaries and removed all gaps inserted by ClustalW, thus forming an updated set of 67 sequence fragment characters for POY3.

Table 2

 GenBank accession numbers and descriptions of genomes and partial genomes of virus exemplars considered in the 157 isolate data set

GenBank accession no.	Name of virus
AF124986	Canine coronavirus
AF124987	Feline infectious peritonitis
AF124988	Porcine hemagglutinating encep
AF124989	Human coronavirus strain OC43
AF124990	Rat sialodacryoadenitis CoV
AF124991	Turkey coronavirus
AF201929	Murine hepatitis 2
AF207902	Murine hepatitis ML 11
AF208066	Murine hepatitis Penn 97 1
AF208067	Murine hepatitis ML 10
AF220295	Bovine coronavirus Quebec
AF304460	Human coronavirus 229E
AF391542	Bovine CoV LUN
AJ271965	Transmissible gastroenteritis
AP006557	SARS coronavirus TWH
AP006558	SARS coronavirus TWJ
AP006559	SARS coronavirus TWK
AP006560	SARS coronavirus TWS
AP006561	SARS coronavirus TWY
AY278487	SARS coronavirus BJ02
AY278488	SARS coronavirus BJ01
AY278489	SARS coronavirus GD01
AY278490	SARS coronavirus BJ03
AY278491	SARS coronavirus HKU 39849
AY278554	SARS coronavirus CUHK W1
AY278741	SARS coronavirus Urbani
AY279354	SARS coronavirus BJ04
AY282752	SARS coronavirus CUHK Su10
AY283794	SARS coronavirus Sin2500
AY283795	SARS coronavirus Sin2677
AY283796	SARS coronavirus Sin2679
AY283797	SARS coronavirus Sin2748
AY283798	SARS coronavirus Sin2774
AY291315	SARS coronavirus Frankfurt 1
AY291451	SARS coronavirus TW1
AY297028	SARS coronavirus ZJ01
AY304486	SARS coronavirus SZ3
AY304487	SARS coronavirus SZ13
AY304488	SARS coronavirus SZ16
AY304489	SARS coronavirus SZ1
AY304490	SARS coronavirus GZ43
AY304491	SARS coronavirus GZ60
AY304492	SARS coronavirus HKU 36871
AY304493	SARS coronavirus HKU 65806
AY304494	SARS coronavirus HKU 66078
AY304495	SARS coronavirus GZ50
AY310120	SARS coronavirus FRA
AY313906	SARS coronavirus GD69
AY321118	SARS coronavirus TWC
AY323977	SARS coronavirus HSR
AY338174	SARS coronavirus Taiwan TC1
AY338175	SARS coronavirus Taiwan TC2
AY345986	SARS coronavirus CUHK AG01
AY345987	SARS coronavirus CUHK AG02
AY345988	SARS coronavirus CUHK AG03
AY348314	SARS coronavirus Taiwan TC3
AY350750	SARS coronavirus PUMC01
AY357075	SARS coronavirus PUMC02
AY357076	SARS coronavirus PUMC03
AY390556	SARS coronavirus GZ02
AY394850	SARS coronavirus WHU
AY394977	SARS coronavirus GZ A
AY394978	SARS coronavirus GZ B
AY394979	SARS coronavirus GZ C
AY394980	SARS coronavirus GZ D
AY394981	SARS coronavirus HGZ8L1 A
AY394982	SARS coronavirus HGZ8L1 B
AY394983	SARS coronavirus HSZ2 A
AY394984	SARS coronavirus HSZ A
AY394985	SARS coronavirus HSZ Bb
AY394986	SARS coronavirus HSZ Cb
AY394987	SARS coronavirus HZS2 Fb
AY394988	SARS coronavirus JMD
AY394989	SARS coronavirus HZS2 D
AY394990	SARS coronavirus HZS2 E
AY394991	SARS coronavirus HZS2 Fc
AY394992	SARS coronavirus HZS2 C
AY394993	SARS coronavirus HGZ8L2
AY394994	SARS coronavirus HSZ Bc
AY394995	SARS coronavirus HSZ Cc
AY394996	SARS coronavirus ZS B
AY394997	SARS coronavirus ZS A
AY394998	SARS coronavirus LC1
AY394999	SARS coronavirus LC2
AY395000	SARS coronavirus LC3
AY395001	SARS coronavirus LC4
AY395002	SARS coronavirus LC5
AY395003	SARS coronavirus ZS C
AY395004	SARS coronavirus HZS2 Bb
AY427439	SARS coronavirus AS
AY461660	SARS coronavirus SoD
AY463059	SARS coronavirus Shanghai QXC1
AY485277	SARS coronavirus Sino1 11
AY485278	SARS coronavirus Sino3 11
AY502923	SARS coronavirus TW10
AY502924	SARS coronavirus TW11
AY502925	SARS coronavirus TW2
AY502926	SARS coronavirus TW3
AY502927	SARS coronavirus TW4
AY502928	SARS coronavirus TW5
AY502929	SARS coronavirus TW6
AY502930	SARS coronavirus TW7
AY502931	SARS coronavirus TW8
AY502932	SARS coronavirus TW9
AY508724	SARS coronavirus NS 1
AY515512	SARS coronavirus HC SZ 61 03
AY525636	SARS coronavirus GD03T0013
AY545914	SARS coronavirus HC SZ 79 03
AY545915	SARS coronavirus HC SZ DM1 03
AY545916	SARS coronavirus HC SZ 266 03
AY545917	SARS coronavirus HC GZ 81 03
AY545918	SARS coronavirus HC GZ 32 03
AY545919	SARS coronavirus CFB SZ 94 03
AY559082	SARS coronavirus Sin852
AY559084	SARS coronavirus Sin3765V
AY559085	SARS coronavirus Sin848
AY559086	SARS coronavirus Sin849
AY559093	SARS coronavirus Sin845
AY559095	SARS coronavirus Sin847
AY559096	SARS coronavirus Sin850
AY567487	Human Coronavirus NL63
AY568539	SARS coronavirus GZ0401
AY572034	SARS coronavirus civet007
AY572035	SARS coronavirus civet010
AY572038	SARS coronavirus civet020
AY613947	SARS coronavirus GZ0402
AY613948	SARS coronavirus PC4‐13
AY613949	SARS coronavirus PC4‐136
AY613950	SARS coronavirus PC4‐227
AY613951	SARS coronavirus PC4‐127
AY613952	SARS coronavirus PC4‐205
AY613953	SARS coronavirus GZ0403
AY627044	SARS coronavirus PC4‐115
AY627045	SARS coronavirus PC4‐137
AY627046	SARS coronavirus PC4‐145
AY627047	SARS coronavirus PC4‐199
AY627048	SARS coronavirus PC4‐241
AY654624	SARS coronavirus TJF
AY686863	SARS coronavirus A022
AY686864	SARS coronavirus B039
AY864197	Bat coronavirus strain 61
BCU00735	Bovine coronavirus Mebus
DQ022305	Bat SARS coronavirus HKU3 1
DQ071613	Bat SARS coronavirus Rp1
DQ071614	Bat SARS coronavirus Rp2
DQ071615	Bat SARS coronavirus Rp3
DQ084199	Bat SARS coronavirus HKU3 2
DQ084200	Bat SARS coronavirus HKU3 3
DQ412042	Bat SARS coronavirus Rf1
DQ412043	Bat SARS coronavirus Rm1
DQ648857	Bat coronavirus BtCoV 279 2005
NC_001451	Avian infectious bronchitis
NC_001846	Murine hepatitis virus
NC_003045	Bovine coronavirus
NC_003436	Porcine epidemic diarrhea virus
NC_004718	SARS coronavirus Toronto 2
NC_005147	Human coronavirus OC43

We produced a data set of 113 whole genomes of SARS‐CoV from human, Chiroptera, swine and carnivore hosts (Table 3) that were available to the public as of July 21, 2006. We used a single outgroup, human coronavirus NL63 (GenBank accession no. AY567487). The sequences in this data set were similar enough to align without splitting them into sequence fragment characters. Together these 114 complete genome sequences were aligned using default settings in ClustalW. This alignment was analyzed with standard tree search methods.

Table 3

 GenBank accession numbers and descriptions of whole genomes of virus exemplars considered in the 114 isolate data set

AP006557	SARS coronavirus TWH
AP006558	SARS coronavirus TWJ
AP006559	SARS coronavirus TWK
AP006560	SARS coronavirus TWS
AP006561	SARS coronavirus TWY
AY278487	SARS coronavirus BJ02
AY278488	SARS coronavirus BJ01
AY278489	SARS coronavirus GD01
AY278490	SARS coronavirus BJ03
AY278491	SARS coronavirus HKU 39849
AY278554	SARS coronavirus CUHK W1
AY278741	SARS coronavirus Urbani
AY279354	SARS coronavirus BJ04
AY282752	SARS coronavirus CUHK Su10
AY283794	SARS coronavirus Sin2500
AY283795	SARS coronavirus Sin2677
AY283796	SARS coronavirus Sin2679
AY283797	SARS coronavirus Sin2748
AY283798	SARS coronavirus Sin2774
AY291315	SARS coronavirus Frankfurt 1
AY291451	SARS coronavirus TW1
AY297028	SARS coronavirus ZJ01
AY304486	SARS coronavirus SZ3
AY304488	SARS coronavirus SZ16
AY304495	SARS coronavirus GZ50
AY310120	SARS coronavirus FRA
AY313906	SARS coronavirus GD69
AY321118	SARS coronavirus TWC
AY323977	SARS coronavirus HSR
AY338174	SARS coronavirus Taiwan TC1
AY338175	SARS coronavirus Taiwan TC2
AY345986	SARS coronavirus CUHK AG01
AY345987	SARS coronavirus CUHK AG02
AY345988	SARS coronavirus CUHK AG03
AY348314	SARS coronavirus Taiwan TC3
AY350750	SARS coronavirus PUMC01
AY357075	SARS coronavirus PUMC02
AY357076	SARS coronavirus PUMC03
AY390556	SARS coronavirus GZ02
AY394850	SARS coronavirus WHU
AY394978	SARS coronavirus GZ B
AY394979	SARS coronavirus GZ C
AY394981	SARS coronavirus HGZ8L1 A
AY394982	SARS coronavirus HGZ8L1 B
AY394983	SARS coronavirus HSZ2 A
AY394985	SARS coronavirus HSZ Bb
AY394986	SARS coronavirus HSZ Cb
AY394987	SARS coronavirus HZS2 Fb
AY394988	SARS coronavirus JMD
AY394989	SARS coronavirus HZS2 D
AY394990	SARS coronavirus HZS2 E
AY394991	SARS coronavirus HZS2 Fc
AY394992	SARS coronavirus HZS2 C
AY394993	SARS coronavirus HGZ8L2
AY394994	SARS coronavirus HSZ Bc
AY394995	SARS coronavirus HSZ Cc
AY394996	SARS coronavirus ZS B
AY394997	SARS coronavirus ZS A
AY394998	SARS coronavirus LC1
AY394999	SARS coronavirus LC2
AY395000	SARS coronavirus LC3
AY395001	SARS coronavirus LC4
AY395002	SARS coronavirus LC5
AY395003	SARS coronavirus ZS C
AY395004	SARS coronavirus HZS2 Bb
AY427439	SARS coronavirus AS
AY461660	SARS coronavirus SoD
AY463059	SARS coronavirus ShanghaiQXC1
AY485277	SARS coronavirus Sino1 11
AY485278	SARS coronavirus Sino3 11
AY502923	SARS coronavirus TW10
AY502924	SARS coronavirus TW11
AY502925	SARS coronavirus TW2
AY502926	SARS coronavirus TW3
AY502927	SARS coronavirus TW4
AY502928	SARS coronavirus TW5
AY502929	SARS coronavirus TW6
AY502930	SARS coronavirus TW7
AY502931	SARS coronavirus TW8
AY502932	SARS coronavirus TW9
AY508724	SARS coronavirus NS 1
AY515512	SARS coronavirus HC SZ 61 03
AY545914	SARS coronavirus HC SZ 79 03
AY545915	SARS coronavirus HC SZ DM1 03
AY545916	SARS coronavirus HC SZ 266 03
AY545917	SARS coronavirus HC GZ 81 03
AY545918	SARS coronavirus HC GZ 32 03
AY545919	SARS coronavirus CFB SZ 94 03
AY559082	SARS coronavirus Sin852
AY559084	SARS coronavirus Sin3765V
AY559085	SARS coronavirus Sin848
AY559086	SARS coronavirus Sin849
AY559093	SARS coronavirus Sin845
AY559095	SARS coronavirus Sin847
AY559096	SARS coronavirus Sin850
AY567487	Human Coronavirus NL63
AY568539	SARS coronavirus GZ0401
AY572034	SARS coronavirus civet007
AY572035	SARS coronavirus civet010
AY572038	SARS coronavirus civet020
AY613947	SARS coronavirus GZ0402
AY613948	SARS coronavirus PC4 13
AY613949	SARS coronavirus PC4136
AY613950	SARS coronavirus PC4227
AY654624	SARS coronavirus TJF
AY686863	SARS coronavirus A022
AY686864	SARS coronavirus B039
DQ022305	Bat SARS coronavirus HKU3 1
DQ071615	Bat SARS coronavirus Rp3
DQ084199	Bat SARS coronavirus HKU3 2
DQ084200	Bat SARS coronavirus HKU3 3
DQ412043	Bat SARS coronavirus Rm1
DQ648857	Bat coronavirus BtCoV 279 2005
NC_004718	SARS coronavirus Toronto 2

Sensitivity analysis plus tree fusion under direct optimization

Direct optimization (Wheeler, 1996) works by creating parsimonious hypothetical ancestral sequences at internal nodes of a cladogram. The key difference between direct optimization and multiple alignment is that in direct optimization evolutionary differences in sequence length are accommodated, not by the use of gap characters, but rather by allowing insertion–deletion events between ancestral and descendant sequences. In direct optimization, evolutionary base substitution and insertion–deletion events are treated with the same edit costs that are used in standard studies using static alignment followed by search for a set of optimal tree(s). However, in direct optimization, alignment is dynamic in that a novel set of putative sequence homologies is considered each time a novel topology is considered. The best set(s) of homologies is discovered by searching for the topology(ies) that minimizes the global cost of substitution and indel events.

Moreover, we varied alignment parameter sets across five sets of edit costs ranging from unitary costs for nucleotide insertion–deletions, transversions and transitions to costs with upweighted insertion–deletions and transversions (4, 5) (Wheeler, 1995). This process of parallel direct optimization across many edit costs not only allows for analysis of whether the results are sensitive to parameter choice, but when also coupled with a genetical algorithm can shorten the computation time necessary to find satisfactory results (treated below).

Table 4

 Phylogenetic position of carnivore and swine relative to human SARS‐CoV isolates in trees calculated under various edit costs under direct optimization for the 83 isolate data set

Indel cost	TV cost	TS cost	Tree length	Position of SARS CoV isolated from carnivores and swine in tree
1	1	1	44737	Terminal, nested within SARS CoV isolated from humans
2	2	1	71583	Terminal, nested within SARS CoV isolated from humans
2	1	1	51209	Terminal, nested within SARS CoV isolated from humans
4	2	1	82802	Terminal, nested within SARS CoV isolated from humans
8	2	1	96851	Terminal, nested within SARS CoV isolated from humans

Table 5

 Phylogenetic position of carnivore and swine relative to human SARS‐CoV isolates in trees calculated under various edit costs under direct optimization for the 157 isolate data set

Indel cost	TV cost	TS cost	Tree length	Position of SARS CoV isolated from carnivores and swine in tree	Position of SARS CoV isolated from Chiroptera in tree
1	1	1	60614	Terminal, nested within SARS‐  CoV isolated from humans	Basal to SARS‐CoV isolated from  humans, carnivores and swine
2	2	1	98057	Terminal, nested within SARS‐  CoV isolated from humans	Basal to SARS‐CoV isolated from  humans, carnivores and swine
2	1	1	74521	Terminal, nested within SARS‐  CoV isolated from humans	Basal to SARS‐CoV isolated from  humans, carnivores, and swine
4	2	1	123885	Terminal, nested within SARS‐  CoV isolated from humans	Basal to SARS‐CoV isolated from  humans, carnivores, and swine
8	2	1	154549	Terminal, nested within SARS‐  CoV isolated from humans	Most basal to SARS‐CoV isolated from  humans, carnivores, and swine. Two  isolates from Chiroptera are terminal

Initial tree build strategies under direct optimization

We analyzed the 83 (1, 4; Table 1) and 157 (2, 5; Table 2) isolate data sets with direct optimization into phylogenetic trees as implemented in POY3 on a 16 processor cluster of Linux PC based workstations running in parallel over a gigabit Ethernet switch. We used both parallel build and multibuild strategies (Janies and Wheeler, 2001). (POY3 parallel build commands: ‐parallel ‐replicates 9 ‐fitchtrees  ‐quick ‐staticapprox  ‐notbr ‐maxtrees  10). (POY3 multibuild  commands: parallel ‐multibuild  ‐buildsperreplicate  16 ‐approxbuild  ‐nodiscrepancies  ‐norandomizeoutgroup  ‐sprmaxtrees  2 ‐tbrmaxtrees  2 ‐fitchtrees  ‐holdmaxtrees  2 ‐quick ‐staticapprox  ‐replicates 2 ‐buildmaxtrees  2).

Figure 1

 Phylogenetic tree produced by direct optimization of 83 coronavirus isolates based on whole and partial genomes (sampling in Table 1). Branches with black traces indicate presence of the 29‐nucleotide region, CCTACTGGTTACCAACCTGAATGGAATAT (e.g., positions 27869–27897 in AY278489) in an uncharacterized protein of variants of the SARS‐CoV that infect small carnivores and humans. White traces indicate the absence of this region. In this analysis, the evolution of insertions and deletions of this region is labile and complex.

Figure 4

 Phylogenetic tree produced by direct optimization of 83 coronavirus isolates based on whole and partial genomes (sampling in Table 1). The evolution of hosts is optimized on the genome‐based tree as shown by the colors traced on the branches. Note that the SARS‐CoV isolates from carnivores (purple trace: civet cat Parguma larvata, raccoon dog Nyctereutes procyonoides, and ferret badger Melogale moschata) and artiodactyls (light blue trace: pig, Sus scrofa) are nested within a large clade of SARS‐CoV isolates from humans (yellow trace: Homo sapiens), which are basal among SARS‐CoV. The search method for the genomic data was direct optimization. Parsimony optimization was used for the host data. The edit costs were indels 1, transversions 1, transitions 1.

Figure 2

 Phylogenetic tree produced by direct optimization of whole and partial coronavirus genomes produced of 157 isolates (sampling in Table 2). Branches with black traces indicate presence of the 29‐nucleotide region, CCTACTGGTTACCAACCTGAATGGAATAT (e.g., positions 27869–27897in AY278489) in an uncharacterized protein of variants of the SARS‐CoV that infect small carnivores and humans. Branches with green traces indicate the presence of the 29‐nucleotide region CCAATACATTACTATTCGGACTGGTTTAT (e.g., positions 27866–27894 in DQ648857) in an uncharacterized protein of all SARS‐CoV isolated from Chiroptera. White traces indicate the absence of either region. In this analysis, the evolution of insertions and deletions of these regions is labile and complex.

Figure 5

 Phylogenetic tree produced by direct optimization of whole and partial coronavirus genomes produced of 157 isolates (sampling in Table 2). Note that the SARS‐CoV isolates from Chiroptera (black trace: Rhinolophus sinicus, Rhinolophus ferrumequinum, Rhinolophus macrotis and Rhinolophus pearsoni) are basal among the entire SARS‐CoV clade. SARS‐CoV isolates from small carnivores (purple trace) and artiodactyls (light blue trace) are nested within a clade of SARS‐CoV isolates from humans (yellow trace), although there were several exchanges between humans and carnivores. The search method for the genomic data was direct optimization. Parsimony optimization was used for the host data. The edit costs were indels 1, transversions 1, transitions 1.

Genetical algorithms under direct optimization

Next, we used POY3 to perform tree fusion, a search heuristic first presented in a phylogenetic context by Goloboff (1999) to address the problem of composite optima. With a set of various near suboptimal trees such as produced during direct optimization analysis, often some taxa are in an optimal configuration in some of the trees but no one tree is optimal for all taxa. We applied the following POY3 commands to a concatenated file named “ALL.TREES” containing trees collected under various edit costs (POY3 commands: ‐parallel ‐fitchtrees ‐treefuse ‐fusemingroup 5‐fusemaxtrees 10‐fuselimit 100‐slop 5‐checkslop  10‐maxtrees  10‐topofile  ALL.TREES ‐molecularmatrix  $ALIGNMENTPARAMETERS).

Standard tree search for aligned data

For the 114 isolate multiple alignment we ran a new technology search in TNT (Goloboff et al., 2003b) under equally weighted parsimony and stabilized the consensus 10 times (Fig. 6). We also ran these data under maximum likelihood under the GTR + GAMMA and CAT models of nucleotide substitution for 1000 randomly generated maximum parsimony trees in RAXML (Stamatakis, 2006) on a computing cluster.

Figure 6

 Note that the SARS‐CoV isolates from Chiroptera (black trace) are basal to the entire SARS‐CoV clade. The SARS‐CoV isolates from carnivores (purple trace) and artiodactyls (light blue trace) are nested within a large clade of SARS‐CoV isolates from humans (yellow trace), although there were exchanges of SARS‐CoV between humans and carnivores. The tree search and character optimization were conducted under equally weighted parsimony.

Character optimization on flat trees

We optimized the position of the animal SARS‐CoV isolates in the best tree(s) produced by tree fusion in each parameter set with the program MESQUITE (Maddison and Maddison, 2004) using the option: trace character history: parsimony ancestral states. All best trees from the parameter study were used for study of the relative topological position of isolates in various hosts (4, 5).

For flat tree presentation of the optimization of: various 29‐nucleotide fragments, key amino acid mutations, and host character states we used MESQUITE with trees for the 83 (1, 4) and 157 isolate datasets (2, 5, and supplemental data at http://supramap.osu.edu/cov) produced by direct optimization under unitary edit costs (indels = 1, transversions = 1, transitions = 1).

For flat tree and geographic visualization studies (treated next) we used a binary version (using the TNT command randtree*) of the 114 isolate strict consensus tree produced by ClustalW alignment and parsimony search (6, 3).

Figure 3

 Binary representation of strict consensus tree produced by multiple alignment followed by tree search under parsimony of 114 whole coronavirus genomes. Branches with black traces indicate presence of the 29‐nucleotide region, CCTACTGGTTACCAACCTGAATGGAATAT (e.g., positions 27869–27897 in AY278489) in an uncharacterized protein of variants of the SARS‐CoV that infect small carnivores and humans. Branches with green traces indicate the presence of the 29‐nucleotide region CCAATACATTACTATTCGGACTGGTTTAT (e.g., positions 27866–27894 in DQ648857) in an uncharacterized protein of all SARS‐CoV isolated from Chiroptera. White traces indicate the absence of either region. In this analysis the evolution of insertions and deletions of these regions is simple.

Projection of a tree, key mutations and metadata into a virtual globe

We used the methods described in Janies et al. (2007) to project a binary representation of the tree found for 114 isolates in TNT into a virtual globe (http://supramap.osu.edu/cov/janiesetal2008covsars.kmz). One subtle difference was that in this case we used an apomorphy list derived from PAUP* (version 4.0b10; Swofford, 2002) using the command describe trees:output list of apomorphies. We drew data on host and date of isolation from Lau et al. (2005; GenBank, or the International Committee on Taxonomy of Viruses database (http://www.ncbi.nlm.nih.gov/ICTVdb).

Spike protein mutations

Not all nucleotide records for coronaviruses in GenBank had translations to proteins. To get amino acid data of interest we translated nucleotide records into proteins in the Genetic Data Environment (http://www-bimas.cit.nih.gov/gde_sw.html) and checked these translations against reference amino acid sequences from GenBank. Amino acid sequences were aligned with ClustalW. Amino acid positions 479 and 487 of the spike protein were optimized on a tree using apomorphy commands of PAUP for tree projections. Optimizations of these amino acid positions were also conducted in MESQUITE for flat tree visualization (supplemental data at http://supramap.osu.edu/cov).

Genotype–phenotype correlation studies

We used the options: trace and chart of MACCLADE (Maddison and Maddison, 2000) to perform the concentrated changes test (Maddison, 1990) with the presence of the region CCTACTGGTTACCAACCTGAATGGAATAT as the independent character and the infection of carnivores as the dependent character. Any ambiguities in the optimization were resolved using the DELTRAN option. The CCT test was performed using simulation sample size of 100 000 iterations.

Sensitivity analysis of outgroup choice

Rooting an evolutionary tree is a critical step to polarize the temporal sequence of genomic and phenotypic changes and clarify the relationships of the organisms. Unlike Snijder et al. (2003) who used an equine torovirus outgroup (as the taxonomy suggests might be suitable http://www.ncbi.nlm.nih.gov/ICTVdb/Ictv/index.htm), we could not verify the suitability of an outgroup from outside the coronaviruses. Our investigation using BLAST (Altschul et al., 1997) [default values as implemented in GenBank http://www.ncbi.nlm.nih.gov (i.e., expect = 10)] indicated to us that no arterivirus or torovirus genome in GenBank bears significant nucleotide similarity with any coronavirus. As outgroups, we used genomes and partial genomes from non‐SARS coronaviruses (1, 2). We choose many candidate outgroup taxa to maximize host and antigenic diversity. Clades formed by antigenic group 1, group 2, and group 3 coronaviruses have significant branch lengths between each other and the SARS‐CoV clade. Finding the ingroup root when the available outgroups are markedly divergent can be challenging. The divergence can be a result of rapid mutation rates, recombination events, inadequate sampling, multiple evolutionary origins, or a combination of these phenomena. Thus we performed several experimental searches in which a random outgroup selected from non‐SARS taxa was used. The results of these searches were assessed to see whether our phylogenetic and host evolution results were affected by outgroup choice. To perform these randomization experiments, we output an implied alignment (Wheeler, 2003) resulting from each parameter set and best tree. (POY3 commands: ‐phastwincladfile  $IMPLIEDALIGNMENT.phast ‐topodiagnoseonly  ‐topofile  $ALIGNMENTPARAMETERS.TREE). Next, for each implied alignment we used 1000 replicate new technology tree searches (TNT command: XMULT 2) (Goloboff et al., 2003b). In each search replicate, we randomly deleted a subset of the outgroup taxa and assessed: (1) whether the most basal taxon in the SARS ingroup was stable, and (2) whether the most basal taxon of the SARS ingroup was ever an isolate from an animal host (scripts available from the authors).

Resampling

We performed jackknife GC resampling in TNT (Goloboff et al., 2003a,b) on the ClustalW alignment of the 114 isolate data set and the implied alignment from unitary costs for the 83 and 157 isolate data sets as specified by the following commands: resample  jak  rep1000 [xm  = lev5 rep5] from 0.

We performed 1000 bootstrap resampling replicates in RAXML (Stamatakis, 2006) with the following commands: ‐f d ‐m GTRCAT  ‐# 1000 ‐b 12345 ‐n MultipleBootstrap.

Results

Direct optimization searches

Best tree lengths for the direct optimization searches under various parameters are reported for the 83 isolate data set in Table 4 and for the 157 isolate data set in Table 5. The resampling values are reported as supplemental data at http://supramap.osu.edu/cov/.

Multiple alignment to standard tree search

For the 114 isolate data set, a best score of 22 363 steps under equally weighted parsimony was hit 107 times and 87 trees were retained. A strict consensus of 59 nodes was stabilized 10 times (Fig. 6). The best RAXML tree for this alignment was found under GTRGAMMA at –ln likelihood of 111006.264984. RAXML trees with host character optimization and resampling values are available in supplemental data at http://supramap.osu.edu/cov/.

Evolution of host shifts among coronaviruses

In the 83 isolate data set in all parameter sets considered, we found the SARS‐CoV isolates from P. larvata, N. procyonoides (Carnivora) and Sus scrofa (Artiodactyla) to occur in terminal positions of the trees, nested well within a large clade of SARS‐CoV isolated from humans (Fig. 4, Table 4). Thus, based on genomic evidence, SARS‐CoV occurred in P. larvata, N. procyonoides and S. scrofa after SARS‐CoV occurred in humans (4, 3). The shift of SARS‐CoV from human hosts to S. scrofa host is independent of the shift from human host to small carnivore hosts (N. procyonoides and S. scrofa).

In the 83 isolate tree recovered under unitary costs, the polarity of host shift is ambiguous between the SARS‐CoV isolate from N. procyonoides (HC/SZ/61/03) and the SARS‐CoV isolate GD03T0013 from humans. GD03T0013 is closely related to SARS‐CoV isolated from civets served in a restaurant in Guangzhou, China in late 2003 and early 2004. No epidemiological data link the GD03T0013 human case to exposure to laboratory isolates of SARS‐CoV (Wang et al., 2005).

In the 157 isolate data set, under all parameters we found the SARS‐CoV isolates from P. larvata, N. procyonoides and S. scrofa were terminal, nested well within a large clade of SARS‐CoV isolated from humans (Fig. 5, Table 5). In the analysis of these data under most parameter sets the SARS‐CoV isolated from Chiroptera were basal to SARS‐CoV isolated from humans, carnivores and swine. A solitary minor exception to this pattern occurred under an extremely biased edit cost model of indels 8, transversions 2, transitions 1 (Table 5). In this analysis, two of four isolates of SARS‐CoV from Chiroptera occur in terminal rather than basal positions.

In the 157 isolate tree recovered under unitary costs, the human SARS‐CoV isolate GD03T0013 is closely related to civet as well as human isolates SARS‐CoV. This is consistent with the result that there were bidirectional exchanges of SARS‐CoV between humans and carnivores.

The 114 isolate trees that result from analyses using multiple alignment and standard tree searches under parsimony and maximum likelihood show a pattern of host shifts similar to those described for the direct optimization searches. SARS‐CoV isolated from Chiroptera are basal to SARS‐CoV under alignment plus parsimony search or alignment plus maximum likelihood search. In all results from the 114 isolate data set SARS‐CoV isolated from carnivores are terminal and nested within a large clade of SARS‐CoV isolated from humans and there is evidence of bidirectional exchange of SARS‐CoV between humans and carnivores (Fig. 6 and supplemental data at http://supramap.osu.edu/cov).

Evolution of a labile region of the SARS‐CoV genome

In all three isolate sampling regimes the first insertion of the 29‐nucleotide region, CCTACTGGTTACCAACCTGAATGGAATAT, occurs phylogenetically basal to the clade exhibiting the earliest hosts shift among humans and carnivores. However, the result of whether this region covaries with host shifts is dependent on isolate sampling regime.

Locus insertion and deletion among SARS‐CoV from various hosts in the 83 isolate data set

We present the phylogeny for 83 isolates found under unitary costs with tracing depicting the complex pattern of presence and absence of the 29‐nucleotide region CCTACTGGTTACCAACCTGAATGGAATAT (Fig. 1). The pattern of insertion and deletion of the 29‐nucleotide region region includes four to eight insertions and zero to four deletions. However, two host shifts from human to carnivore occur in concert with insertions of the 29‐nucleotide region (Fig. 4). Using Maddison's (1990) concentrated changes test, we find statistically significant correlation between this 29‐nucleotide region and host shifts (CCT = 0.0123).

Locus insertion and deletion among SARS‐CoV in the 157 isolate data set

We optimized the presence of 29 nucleotide sequence regions CCTACTGGTTACCAACCTGAATGGAATAT and CCAATACATTACTATTCGGACTGGTTTAT over the tree calculated for 157 isolates under unitary costs (Fig. 2). The region CCAATACATTACTATTCGGACTGGTTTAT occurs in all wholly sequenced genomes of SARS‐CoV isolated from Chiroptera and is well correlated with this host. In contrast, the region CCTACTGGTTACCAACCTGAATGGAATAT is inserted seven to eight times and deleted four to five times. In terms of host use in this tree, there are five shifts from carnivore to human hosts and two changes from human to carnivore hosts (Fig. 5). Among all these changes in the presence of the 29‐nucleotide region, CCTACTGGTTACCAACCTGAATGGAATAT, and changes in host use, there is only one branch where these two changes occur concurrently. This results in a CCT value of 0.108. Thus the CCTACTGGTTACCAACCTGAATGGAATAT region shows insignificant correlation with the host shift in the 157 isolate data set.

Locus insertion and deletion among SARS in the 114 isolate data set

We optimized the presence and absence of the 29‐nucleotide regions CCTACTGGTTACCAACCTGAATGGAATAT and CCAATACATTACTATTCGGACTGGTTTAT, on a binary representation of strict consensus tree resulting from parsimony search of the 114 isolate data set (Fig. 3). There are no branches where a host shift (Fig. 6) is coincident with an insertion or deletion of this fragment. This result indicates, that like the 157 isolate data set, the insertion of this 29‐nucleotide region is not significantly correlated with a host shift. Moreover, just as in the 157 isolate dataset, the region, CCAATACATTACTATTCGGACTGGTTTAT, occurs in all wholly sequenced genomes of SARS‐CoV isolated from Chiroptera and is well correlated with this host.

Mutations in the spike protein

Li et al. (2005) interpret the distribution of states and polarity of change of position 479 of the SARS‐CoV spike protein as follows. Viruses infecting carnivores contain a basic residue, arginine (R) or lysine (K). Next mutation to a small uncharged residue asparagine (N) allowed infection of humans.

However, in the 157 isolate tree we see a different distribution of genotypes and polarities of change. SARS‐CoV isolated from carnivores exhibit three genotypes at position 479: asparagine (N) arginine (R) or lysine (K). SARS‐CoV infecting humans have two genotypes at position 479: asparagine (N) and arginine (R). SARS‐CoV infecting Chiroptera contain exclusively serine (S) at position 479. SARS‐CoV isolated from the artiodactyl contain asparagine (N). Considering the tree in the 157 isolate data set, we observe the following mutations at in the spike protein: N479K, N479R, S479N, R479N (supplemental data at http://supramap.osu.edu/cov).

Li et al. (2005) also describe diversity and polarity of change for position 487 of the spike protein of SARS‐CoV. They describe SARS‐CoV isolated in 2002–03 to contain threonine (T) and SARS‐CoV isolated from humans and carnivores in 2003–04 to contain serine (S) at position 487.

We observe essentially the same diversity of genotypes at position 487 with some additions. SARS‐CoV infecting Chiroptera contain primarily valine (V) at position 487 with the exception of one isolate that contains an isoluceine (I). SARS‐CoV isolated from the artiodactyl exhibits a threonine (T). However, we observe different polarities of change than those inferred by Li et al. (2005). We observe the muations: V487I, V487T, T487S based on the tree from the 157 isolate data set (supplemental data at http://supramap.osu.edu/cov).

We found a statistically signifcant covariation of mutation T487S in the spike protein with carnivore hosts (Fig. 5 and supplemental data at http://supermap.osu.edu/cov). The CCT is 0.019 with DELTRAN optimization and 0.018 with ACCTRAN optimization.

We find no correlation of the mutations N479K and N479R in the spike protein with change from human to carnivore hosts (Fig. 5 and supplemental data at http://supramap.osu.edu/cov) as there are no branches that share these mutations and a shift in host.

Outgroup choice

As presented in 1, 4, 2, 5, 6, 3 and supplemental figures at http://supermap.osu.edu/cov, we rooted our phylogenies on non‐SARS coronaviruses. Due to the long internal branches (e.g., ranging from 1680 to 3332 steps in the 83 isolate data set) between any antigenic groups and SARS we decided to use this rooting only for visualization.

The rooting we can present in a figure does not fully represent the extent of our analyses. Our tests as to whether our results were sensitive to outgroup choice showed that our results were not affected by outgroup choice. SARS‐CoV isolates from human hosts were consistently basal to any SARS‐CoV isolate from a carnivore host irrespective of outgroup choice.

Discussion

Based on the SARS‐CoV data released as of July 2006, the polarity of host shifts from human to carnivore hosts and humans to artiodactyl host is clear. Simply put, the SARS‐CoV sequence data from animal hosts that has been released as of July 2006 are the results of two zoonotic events that occurred after the 2002–03 outbreak of SARS in humans: one major shift from human to carnivore hosts (with subsequent reversals that were not significant to human outbreaks) and one shift to an artiodactyl. SARS‐CoV isolated from Chiroptera are consistently basal to clades containing SARS‐CoV from human, carnivore and artiodactyl hosts.

Outgroup choice and presentation

Many of the reports that argue for carnivores as the original reservoir of SARS‐CoV use a phylogeny to support their arguments (Guan et al., 2003; Chinese SARS Molecular Epidemiology Consortium, 2004; Kan et al., 2005; Song et al., 2005; Zhang, C et al., 2006). However, the phylogenies in these studies lack outgroup and rooting criteria necessary to derive such evidence for the origins of SARS‐CoV. Outgroups chosen from outside of SARS‐CoV are necessary to test the monophyly of the SARS‐CoV ingroup (Barriel and Tassy, 1998). Moreover in optimal trees, non‐SARS‐CoV outgroups will join the region of the SARS‐CoV subtree that is closest to the ancestor of SARS and provide a point suitable for rooting and subsequent character analysis (Grandcolas et al., 2004).

In the case of Guan et al. [2003, see their figs 2 and S2) and the Chinese SARS Molecular Epidemiology Consortium (2004); see their fig. S7 of their supplemental materials] these researchers simply force the root position on their drawings such that they represent SARS‐CoV isolates from animal hosts as ancestral. In other drawings, no outgroup is designated (Chinese SARS Molecular Epidemiology Consortium, 2004, fig. 2) or a human SARS‐CoV outgroup is used and the animal SARS‐CoV isolates are omitted from the tree (Chinese SARS Molecular Epidemiology Consortium, 2004, fig. S6). In the case of Song et al. (2005a) human SARS‐CoV is designated as the outgroup. Regression methods are used to construct a rooted tree in which the date of the most recent ancestor is reconstructed as December 2002 (Song et al., 2005). Song et al. (2005) conclude that a source of disease common to humans and civets must be in the environment and further surveys of the CoV in the Guangdong region are warranted. In the case of Zhang, C et al., 2006, fig. 1; and pers. comm.) an outgroup was used for tree construction but not for tests of selection.

Many researchers agree that SARS represents a previously unrecognized fourth lineage of coronaviruses (Marra et al., 2003; Rest and Mindell, 2003; Rota et al., 2003). Thus, the non‐SARS coronaviruses can serve as outgroups to SARS‐CoV. This can be revisited if and when data on viruses closely related to SARS‐CoV become available. Alternatively, other researchers used a torovirus and/or okavirus outgroup(s) to place SARS‐CoV as sister to group 2 coronaviruses (Snijder et al., 2003; Lió and Goldman, 2004). However, based on the data in GenBank, toroviruses and okaviruses bear little sequence similarity to any coronavirus. The danger in use of such distant outgroups is well documented (Wheeler, 1990; Graham et al., 2002). In essence, distant outgroups act as if they are random sequences resulting in spurious attraction to the longest branch available among the ingroup. Indeed the branch lengths between the major clades of coronaviruses in the 83 and 157 isolate datasets of this paper are long. This problem is addressed in the 114 isolate data set. The best approach going forward is to extend sampling of diverse coronavirus genomes to search for outgroups of SARS‐CoV in humans, especially from Chiroptera, carnivores and non‐human primates.

Taxonomic sampling affects analyses

The lack of a good outgroup to SARS‐CoV is tied to (1) poor sampling of non‐SARS coronavirus genomes before the 2002–03 SARS outbreak, and (2) the preoccupation with animals in Chinese markets, farms and restaurants after the outbreak without regard to highly diverse species traded as bush meat in South‐east Asia (Bell et al., 2004). Before the SARS epidemic, the small number of animal coronaviruses that had been sequenced were selected primarily from animals of agricultural importance or model organisms. This lack of sampling of coronaviruses from wild animals is changing as viral surveys of Chiroptera, camelids and bovids are published and in preparation (Chu et al., 2006; Dominguez et al., 2007; Jina et al., 2007; Zhang, X et al., 2007).

Insertion of the 29‐nucleotide regions

Presence of the region CCTACTGGTTACCAACCTGAATGGAATAT is correlated with host switching beween human and carnivore hosts in the 83 isolate data set but is insignificantly correlated with switches from human to carnivore hosts in the larger (114 and 157 isolate) data sets. The concentrated changes test (CCT; Madison, 1990) whether a change in one character (e.g., insertion or deletion of the 29‐nucleotide region) and a change in another character (e.g., host phenotype) co‐occur on the same branches of a tree more often than expected by chance. In the case of the 83 isolate data set we observe a significant correlation between the presence of this 29‐nucleotide region and carnivore hosts. In the case of the 157 isolate data set we observe an insignificant correlation. In the case of the 114 isolate data set we do not observe changes that strictly co‐occur. However, we do observe that host shifts in the 114 and 157 isolate data set that host shifts occur in the region of the tree in which changes in the 29‐nucleotide region occurred more basally. Thus, the presence of the 29‐bp region may predispose or be part of a suite of genomic changes associated with host shifts. In light of these results, it is of interest to implement a relaxed concentrated changes test. This test could examine the branches in the vicinity of the change of interest for a correlated change in a second character.

Mutations of the spike gene

Our phylogenetic results shed fresh light on the polarity of mutations and diversity of genotypes in the spike protein of SARS‐CoV. Our results differ from the result of Zhang, C et al. (2006) who using CODEML (Yang, 1997) and HYPY (Kosakovsky Pond and Frost, 2005) for a tree‐based spike nucleotide sequence analysis show that the codon for amino acid position 479 was under positive selection and the codon for amino acid position 487 was not. The trees used to derive these results reflect the same bias seen in other studies—that transmission of SARS‐CoV was from carnivore to human hosts.

Geographic visualization

The pattern of geographic spread of SARS‐CoV is similar to that of avian influenza (H5N1; Janies et al. 2007) in that both viral lineages that have caused recent outbreaks have their origins in Southern China. However, H5N1 and SARS‐CoV contrast in the rapidity in which they moved across the planet. The recent outbreak lineage of H5N1 has spread from Asia to Europe, the Middle East, and Africa during the period of 1996–2005 and has not yet arrived in North America. In contrast, SARS‐CoV spread not only from Asia to Europe but also North America in a matter of months (November 2002–March 2003). These differences are perhaps associated with the fact that SARS‐CoV infected carnivores in urban markets and a cosmopolitan human population with access to world travel. In contrast, H5N1 is currently infecting primarily avian populations and humans that live in rural settings and come into close contact with birds via subsistence farming and food processing.

Further directions

In order to better understand the molecular epidemiology of SARS‐CoV we must develop research programs that include comprehensive sampling and phylogenetic analyses of many whole viral genomes, including outgroups that are closely related to SARS‐CoV. As a result of the previously unrecognized zoonotic threat they pose, several groups have embarked on large‐scale sequencing projects on coronavirus genomes isolated from diverse animal hosts, especially Chiroptera, carnivores and primates. These efforts will help us pinpoint the zoonotic origins of SARS‐CoV, develop an understanding of the zoonotic potential of coronaviruses as well as the genomic changes that underlie host shifts among coronaviruses.

Acknowledgments

Research facilities and funding was provided by the Department of Biomedical Informatics of the Ohio State University College of Medicine. D.J. acknowledges the National Aeronautics and Space Administration (grant NAG 2‐1399). In addition, this material is based upon work supported by, or in part by, the US Army Research Laboratory and the US Army Research Office under contract/grant number W911NF‐05‐1‐0271. D.P. acknowledges support from the National Science Foundation via a grant to the Mathematical Biosciences Institute of the Ohio State University. B.A. was supported by Ohio State University's Research on Research Program. Computational equipment was provided by The Hewlett Packard Corporation (Advanced Technology Platforms Itanium2 Grant, 89910.1) and The Ohio Supercomputer Center (Resource Grant PAS0119). Thanks to Aaron Nile for proofreading.

spike.aa.pos479.pdf. Phylogenetic tree of 157 coronavirus isolates based on whole genomes (sampling in Table 2). This is the same tree as Figs 2 and 5 in the body of the paper except that in this instance the amino acid states at position 479 in the spike locus are traced.

spike.aa.pos487.pdf. Phylogenetic tree of 157 coronavirus isolates based on whole genomes (sampling in Table 2). This is the same tree as Figs 2 and 5 in the body of the paper except that in this instance the amino acid states at position 487 in the spike locus are traced.

cov114.host.raxmltree929.names.pdf. RAXML search under GTRGAMMA for 114 isolates. Character optimization was conducted under equally weighted parsimony

cov114.host.raxmltree929boot.nex. Tree with bootstrap values for RAXML search. To be viewed with MESQUITE.

r1000.cov114.jackknife.log. Jackknife values for 114 isolate data set under equally weighted parsimony. To be viewed with a text editor.

r1000.cov83.jackknife.log. Jackknife values for 83 isolate data set under equally weighted parsimony. To be viewed with a text editor

r1000.cov157.jackknife.log. Jackknife values for 157 isolate data set under equally weighted parsimony. To be viewed with a text editor

janiesetal2007covsars.kmz. Keyhole Markup file depicting the spread of 114 isolates of SARS‐CoV over geography. To be opened with Google Earth. See also readmesarskml.pdf.

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