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Margaret	Woodhouse	
MaizeGDB	
	
Gale	and	Devos,	1998,	PNAS
What is a pan-genome?
A	pan-genome	represents	the	full	complement	
of	diversity	within	a	clade,	or	the	union	of	all	
genes	or	SNPs	across	a	representaAve	selecAon	
of	genomes
•  A	single	reference	genome	cannot	represent	
the	diversity	within	a	given	species	
•  Advances	in	sequencing	technology	and	
lowered	costs	has	made	generaAng	a	pan-
genome	a	feasible	goal	for	many	genome	
research	groups	
Why a pan-genome?
The first pan-genome: S. agalactiae
•  Microbial	pan-genome	of	
Streptococcus	agalac.ae	
•  Released	in	2005	
•  Comprised	of	eight	S.	
agalac.ae	genomes	(8x	
coverage;	~1.8Mb	in	size)	
•  Whole-genome	alignments	
were	done	using	the	
MUMmer	alignment	program	
•  Gene	sequence	similarity	was	
determined	by	translated	
protein	sequence	similarity	
TeTelin	et	al	2005	PNAS	doi:		10.1073/pnas.0506758102	
Reference	lacking	sequence	similarity	
to	other	accessions	(white	space)	
Reference	sharing	sequence	similarity	in	the	same	
syntenic	posiAon	across	all	accessions	
Reference	sharing	sequence	similarity	in	some	accessions	but	not	in	the	same	syntenic	posiAon
A recent pan-genome: rice
•  a	pan-genome	dataset	of	the	O.	
sa.va–O.	rufipogon	species	
complex	(430Mb	in	size)	
•  deep	sequencing	(115X)	of	66	
divergent	accessions	into	conAgs	
•  ConAgs	were	anchored	to	the	
reference	genome	using	the	
MUMmer	alignment	program	
•  Predicted	genes	in	conAgs	were	
aligned	against	reference	genome	
with	BLASTN	to	determine	gene	
presence-absence	in	conAgs	
Zhou	et	al	2018	Nature	GeneAcs	doi:	10.1038/s41588-018-0041-z
A future pan-genome: maize
Nested Association Population (NAM)
•  25	diverse	inbred	lines,	plus	
the	reference	line	B73	
•  All	25	complete	genomes	
are	currently	being	
sequenced,	assembled,	and	
annotated	by	the	NAM	
Sequencing	ConsorAum	
•  Each	genome	is	
approximately	2	gigabases	
in	size	
•  Whole-genome	alignment	
to	create	the	pan-genome	
D.	Hufnagel,	ISU,	unpublished
Species with existing pan-genomes
•  Human	pan-genome	
•  Dozens	of	microbial	pan-genomes	
•  Many	crop	plant	pan-genomes	(though	mostly	
re-sequencing	efforts)	
– pepper	
– soybean		
– rice		
– wheat		
– maize
Usually	the	comparisons	done	to	create	a	pan-
genome	include		
•  whole-genome	alignment		
•  or	alignment	of	short	reads	to	a	reference	
sequence.	
Methods of creating a pan-genome
Features of a pan-genome (genes as unit)
•  Core	genome	(C):	Made	up	of	genes	present	in	all	accessions	in	the	pan-
genome	
•  “Dispensible”	genome	(D):	The	genes	that	are	present	in	some,	but	not	
all,	accessions	in	the	pan-genome	
•  Orphan	genes	(O):	Lineage-specific	genes;	found	only	within	a	parAcular	
accession	
	Accession	1	
Accession	2	
Accession	3	
O	 C	 C	
C	
C	
C	
C	
D	
D	
D	
D	
Pan-genome	 C	 C	D	D	 O	
D
Types of pan-genomes
1.	Reference-based:	All	accessions	are	mapped	to	a	single	reference	
Ø  pros:	fast	and	easy;	can	be	represented	as	a	fasta	file	(consensus	sequence)	
Ø  cons:	does	not	represent	genes	that	are	present	in	other	accessions	but	
missing	in	the	reference	
Accession	1	
Accession	2	
Reference	
O	 C	 C	
C	
C	
C	
C	
D	
D	
D	
D	
Pan-genome	 C	 C	D	D	
D	
X
2.	All-against-all:	The	pan-genome	includes	the	total	diversity	of	all	
accessions	studied	
Ø  pros:	contains	the	total	diversity	among	all	accessions	
Ø  cons:	can’t	be	easily	represented	as	a	fasta	file;	very	slow;	eats	CPU	
Types of pan-genomes
Accession	1	
Accession	2	
Accession	3	
O	 C	 C	
C	
C	
C	
C	
D	
D	
D	
D	
Pan-genome	 C	 C	D	D	 O	
D
Pan-genome formats
•  Consensus	fasta	file:	all	variaAon	across	accessions	are	collapsed	
into	a	consensus	sequence	
•  Used	for	either	SNP	diversity	or	whole-genome	alignment	against	a	
reference	sequence	
Ø  pros:	blastable/alignable	
Ø  cons:	Hard	to	represent	large	regions	of	variaAon;	difficult	to	
represent	an	all-against-all	pan-genome	
sorghum			5’	AGTAAGACCTGATGCAT	3’	
setaria				5’	AGCAAGACCTGATGCAT	3’	
rice				5’	AGCAAGACCTGATGCAT	3’	
consensus				5’	AGCAAGACCTGATGCAT	3’	
pineapple				5’	AGAATGACCTGATTCCT	3’
•  Graphical	format:	variaAon	represented	as	a	graph	with	nodes	and	
edges;	shared	sequence	similarity	is	collapsed	into	a	single	node	
•  Can	be	used	for	all	types	of	pan-genomes	
Ø  pros:	can	represent	large	regions	of	diversity	beTer	than	a	fasta	file	
Ø  cons:	not	blastable/alignable		
Pan-genome formats
Accession	1	
Accession	2	
Accession	3	
CCTG	 ATGCGA	 TCTGAC	ACTC	
ATTC	
GGAC	 ATGCGA	
ATGCGA	
TCTGAC	
TCTGAC	
GGTC	
GGAG	
ATGCGA	 TCTGAC	
ATTC	
ACTC	GGAC	
GGTC	
GGAG	
CCTG	
Pan-genome
Levels of pan-genomes
•  Species-specific:	e.g.	culAvars	within	a	species	(most	common)	
•  Genus-specific:	closely	related	species	within	a	genus	
•  Family-specific:	the	species	within	a	family	(e.g.	Grasses)	
à	Higher-order	clade	pan-genomes	are	possible,	but	complexity	increases	as	
you	go	up	in	clade	since	number	of	shared	genes	declines:	
Sorghum	
Setaria	
Peach	
Pineapple	
Rice	
Dicots	
Monocots	
Tomato	
Species	 #	syntenic	orthologs	in	Sorghum	
Setaria	 31142	
Rice	 28406	
Pineapple	 16147	
Peach	 5317	
Tomato	 1196	Asterids	
Rosids	
Grasses
Challenges of creating whole-genome pan-
genomes for complex genomes
•  Plants	such	as	maize	and	wheat	have	undergone	recent	
polyploidy	events,	have	large	inversions	and	translocaRons	
relaAve	to	outgroups,	and	contain	a	great	number	of	repeat	
elements	
•  These	genomes	also	contain	a	large	number	of	duplicated	
genes	in	cis	and	trans,	and	have	simultaneously	undergone	a	
great	deal	of	gene	deleRon	relaAve	to	outgroups	
•  Therefore,	creaAng	pan-genomes	to	represent	the	extent	of	
the	diversity	in	these	species	is	daunAng
Example:	two	different	maize	inbred	lines	compared		
to	the	reference	maize	line	B73	
hTps://genomevoluAon.org/r/14hzw		
W22	
Mo17	
B73	
Brown:	blast	hit	from	
B73	to	Mo17	
Orange:	blast	hit	from	
B73	to	W22	
Gene	models	
DNA	sequence	in	chromosomal	
coordinates	(chr,	start,	stop)	
Tandem	array	
W22	culAvar
Red	circles:	genes	with	no	syntenic	ortholog	to	B73	
Tandem	array	
hTps://genomevoluAon.org/r/14hzw		
W22	culAvar	
W22	
Mo17	
B73	
Brown:	blast	hit	from	
B73	to	Mo17	
Orange:	blast	hit	from	
B73	to	W22	
Gene	models	
Example:	two	different	maize	inbred	lines	compared		
to	the	reference	maize	line	B73
The role of biological databases
in curating pan-genomes
•  Biological	databases	will	need	to	address	
nomenclature	rules	for	pan-genes	
•  AgBioData	is	in	a	unique	posiAon	to	direct	and	
standardize	naming	convenAons	for	pan-genes	at	
this	early	stage	in	pan-genome	development	
•  Our	understanding	of	the	complexity	of	pan-
genomes	can	help	inform	us	as	to	the	best	
nomenclature	convenAons	to	implement
•  Storing	pan-genomic	data	in	a	public	database	
is	also	a	concern	
•  What	pan-genome	formats	would	we	store?	
How	would	we	connect	funcAonal	data	
(expression	data,	mapping	and	marker	data,	
SNP	data)	to	the	pan-genome	in	a	useful	
manner?	
The role of biological databases
in curating pan-genomes
•  MaizeGDB	will	
soon	be	hosAng	
these	25	genomes	
and	is	working	on	
the	most	efficient	
way	to	do	so	
Case study: the maize Nested Association
Mapping (NAM) founder lines
D.	Hufnagel,	ISU,	unpublished
Some	approaches	MaizeGDB	is	
considering:	
	
Gene	model	pages:	
1.  Storing	all	gene	models	with	
an	ortholog	in	either	B73	or	at	
least	one	other	NAM	line*	in	
a	single	gene	model	page;	
2.  These	pages	will	also	contain	
mapping	and	funcAonal	data	
associated	with	the	NAM	loci	
as	well	as	the	B73	gene	model	
3.  Orphan	NAM	gene	models	
will	have	their	own	page	
Case study: the maize Nested Association
Mapping (NAM) founder lines
*as	determined	by	the	NAM	Sequencing	ConsorAum
Nomenclature:	
•  NAM	gene	models	will	be	given	a	pan-ID	(i.e.	
Z0123456).		
•  All	NAM	gene	models	that	share	orthology	will	
share	a	single	pan-ID.	
	
Case study: the maize Nested Association
Mapping (NAM) founder lines
•  There	are	various	ways	of	represenAng	a	pan-
genome	
•  Pan-genomes	can	be	very	complex	in	certain	
species	
•  Biological	databases	will	need	to	determine	
Ø How	to	assign	pan-IDs	
Ø What	sorts	of	pan-genome	formats	to	host	
Ø The	most	efficient	way	to	host	pan-genomes	
Summary
AgBioData: Complexity and Diversity of the Pan-Genome

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