49

Jacqueline Batley (ed.), Plant Genotyping: Methods and Protocols, Methods in Molecular Biology, vol. 1245,DOI 10.1007/978-1-4939-1966-6_4, © Springer Science+Business Media New York 2015

Chapter 4

Molecular Marker Databases

Kaitao Lai , Michał Tadeusz Lorenc , and David Edwards

Abstract

The detection and analysis of genetic variation plays an important role in plant breeding and this role is increasing with the continued development of genome sequencing technologies. Molecular genetic markers are important tools to characterize genetic variation and assist with genomic breeding. Processing and storing the growing abundance of molecular marker data being produced requires the development of specifi c bioinformatics tools and advanced databases. Molecular marker databases range from species specifi c through to organism wide and often host a variety of additional related genetic, genomic, or phenotypic infor-mation. In this chapter, we will present some of the features of plant molecular genetic marker databases, highlight the various types of marker resources, and predict the potential future direction of crop marker databases.

Key words Molecular marker , Genetic marker , Genetic variation , SNP marker , SSR marker

1 Introduction

The characterization of genetic variation can provide knowledge to help understand the molecular basis of various biological phenom-ena in plants. Phenotype-based genetic markers were used in Gregor Mendel’s experiments in the nineteenth century. Later, phenotype-based genetic markers helped establish the theory of genetic linkage. More recently, DNA-based markers have been developed to over-come the limitations of phenotype-based genetic markers [ 1 ].

While several diverse DNA-based marker types have been developed, single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs, also known as microsatellites) predomi-nate and are widely used in plant breeding, genomic research, and modern genetic analysis [ 2 , 3 ]. Molecular markers are used in plant breeding and genetic research, including mapping of genes and quantitative trait loci (QTL) analysis, phylogenetic studies, comparative genomics, and marker-assisted breeding [ 4 – 6 ].

Most molecular marker databases host SNP and SSR markers [ 7 ]. Some databases also include other types of marker that are not

50

commonly used. These markers include restriction fragment length polymorphism (RFLP), amplifi ed fragment length poly-morphism (AFLP), random amplifi cation of polymorphic DNA (RAPD), short tandem repeat (STR), and diversity arrays technology (DArT).

A SNP is a DNA sequence variation, representing an individual nucleotide base in the genome that differs between individual genomes [ 8 ]. SNPs are regarded as evolutionarily conserved markers and have been used as markers for QTL analysis and in association studies in place of SSRs. There are several approaches to identify and genotype SNPs in plants [ 9 , 10 ] and their diverse applications suggest that they will continue to be the dominant DNA molecular marker in the foreseeable future [ 11 ]. The application of new sequencing methods is leading the discovery of large numbers of SNPs in wheat [ 12 , 13 ], rice [ 14 , 15 ], Brassicas [ 16 ], and other crop species [ 17 , 18 ].

SSRs are highly polymorphic and informative markers. SSRs demonstrate a high degree of transferability between different species and so are regarded as excellent markers for comparative genetic and genomic analysis. PCR primers designed to an SSR from one species frequently amplify a corresponding locus in related species. The mining of SSRs from gene and genome sequence data is now routine [ 19 ], with large numbers of SSRs identifi ed in a range of species including Brassicas [ 20 , 21 ], wheat [ 22 ], and strawberry [ 23 ]. SSR loci also provide hot spots for SNP discovery and SSRs may readily be converted to SNP markers [ 24 ].

Advances in genome sequencing technology and the increasing availability of genome sequences are providing an abundance of dense molecular markers [ 25 , 26 ]. For example, sequence poly-morphisms developed using the Brassica rapa genome sequence [ 27 ] have been used to identify and characterize SNP and poly-morphisms in agronomically important genes in canola ( B. napus ) [ 28 – 30 ]. In addition, the sequencing of isolated chromosome arms in wheat [ 31 – 33 ] has led to the identifi cation of large num-bers of molecular markers [ 22 ].

Genetic linkage maps represent the order of known molecular genetic markers along a given chromosome for a given species. Comparative mapping is a valuable technique to identify similarities and differences between species [ 34 ]. Many marker databases pro-vide a CMap map visualization tool or their own customized viewer tools for displaying data, including chromosomes and genetic mark-ers with associated mapping locations in the form of genetic linkage maps or comparative maps. A list of molecular marker databases is presented in Table 1 . In addition, web links and references for relevant marker databases are presented in Table 2 .

Kaitao Lai et al.

51

(con

tinue

d)

Tabl

e 1

Exam

ples

of m

olec

ular

mar

ker d

atab

ases

with

diff

eren

t typ

es o

f mar

kers

Data

base

nam

e Vi

ewer

SN

Ps

SSRs

RF

LPs

RAPD

s AF

LPs

ESTs

BA

Cs

DArT

s DN

A pr

obes

PC

R pr

imer

s

auto

SNPd

b *

+

Bra

ssica

.info

+

+ +

+ +

Bra

ssica

rap

a ge

nom

e da

taba

se

* +

Chi

ckpe

a ro

ot E

ST

data

base

+

Cot

ton

Mar

ker

Dat

abas

e (C

MD

) *

+ +

+

Gen

Ban

k db

SNP

* +

Gra

inge

nes

* +

+ +

+ +

+ +

Gra

men

e *

+ +

+ +

+ +

+ +

+

ICR

ISA

T

+

Leg

ume

Info

rmat

ion

Syst

em (

LIS

) *

+ +

+ +

+

Mai

zeG

DB

+

+ +

+ +

Moc

caD

B

+ +

+

Panz

ea

* +

+

Ric

e G

enom

e A

nnot

atio

n Pr

ojec

t *

+

SSR

Pri

mer

+

SSR

tax

onom

y tr

ee

+

Molecular Marker Databases

52

Tabl

e 1

(con

tinue

d)

Data

base

nam

e Vi

ewer

SN

Ps

SSRs

RF

LPs

RAPD

s AF

LPs

ESTs

BA

Cs

DArT

s DN

A pr

obes

PC

R pr

imer

s

SOL

Gen

omic

s N

etw

ork

(SG

N)

* +

+ +

+ +

SoyB

ase

* +

+ +

+ +

+

tfG

DR

Pro

ject

Web

site

*

+

Tri

ticea

e M

appe

d E

ST

Dat

aBas

e ve

r.2.0

(T

riM

ED

B)

* +

+

Veg

Mar

ks

* +

+ +

Whe

at g

enom

e in

form

atio

n +

+

* in

dica

tes

that

thi

s da

taba

se p

rovi

des

view

er, +

indi

cate

s th

at t

his

data

base

sup

plie

s th

is t

ype

of m

arke

r

Kaitao Lai et al.

53

Tabl

e 2

Exam

ples

of m

olec

ular

mar

ker d

atab

ases

rela

ted

to c

rop

impr

ovem

ent

Data

base

nam

e W

eb li

nk

Refe

renc

es

auto

SNPd

b ht

tp:/

/au

tosn

pdb.

appl

iedb

ioin

form

atic

s.co

m.a

u/

[ 60 ,

62 ,

63 ]

Bra

ssica

.info

ht

tp:/

/w

ww

.bra

ssic

a.in

fo/

reso

urce

/m

arke

rs.p

hp

[ 56 ]

Bra

ssica

rap

a ge

nom

e da

taba

se

http

://

bras

sica

db.o

rg/

brad

/ge

netic

Mar

ker.p

hp

[ 75 ]

Chi

ckpe

a ro

ot E

ST d

atab

ase

http

://

ww

w.ic

risa

t.or

g/w

hat-

we-

do/

biot

echn

olog

y/C

pest

/ho

me.

asp

[ 73 ]

Cot

ton

Mar

ker

Dat

abas

e (C

MD

) ht

tp:/

/w

ww

.cot

tonm

arke

r.org

/cg

i-bi

n/cm

d_se

arch

_mar

ker_

resu

lt.cg

i [ 5

9 ]

Gen

Ban

k db

SNP

http

://

ww

w.n

cbi.n

lm.n

ih.g

ov/

proj

ects

/SN

P/

[ 76 –

78 ]

Gra

inge

nes

http

://

whe

at.p

w.u

sda.

gov/

cgi-

bin/

grai

ngen

es/

brow

se.c

gi?c

lass

=mar

ker

[ 45 –

47 ]

Gra

men

e ht

tp:/

/w

ww

.gra

men

e.or

g/db

/m

arke

rs/

mar

ker_

view

[ 4

2 ]

ICR

ISA

T

http

://

ww

w.ic

risa

t.or

g/

[ 74 ]

Leg

ume

Info

rmat

ion

Syst

em (

LIS

) ht

tp:/

/w

ww

.com

para

tive-

legu

mes

.org

/

[ 79 ,

80 ]

Mai

zeG

DB

ht

tp:/

/w

ww

.mai

zegd

b.or

g/pr

obe.

php

[ 81 –

83 ]

Moc

caD

B

http

://

moc

cadb

.mpl

.ird.

fr/

inde

x.ph

p?ca

t=1

[ 58 ]

Panz

ea

http

://

ww

w.p

anze

a.or

g/db

/se

arch

es/

web

form

/m

arke

r_se

arch

[ 8

4 ]

Ric

e G

enom

e A

nnot

atio

n Pr

ojec

t ht

tp:/

/ri

ce.p

lant

biol

ogy.

msu

.edu

/an

nota

tion_

pseu

do_p

utat

ives

sr.s

htm

l [ 5

2 ]

SSR

Pri

mer

2

http

://

fl ora

.acp

fg.c

om.a

u/ss

rpri

mer

2/

[ 68 ]

(con

tinue

d)

Molecular Marker Databases

54

Data

base

nam

e W

eb li

nk

Refe

renc

es

SSR

tax

onom

y tr

ee

http

://

appl

iedb

ioin

form

atic

s.co

m.a

u/pr

ojec

ts/

ssrt

axon

omy/

php/

[ 6

8 ]

SOL

Gen

omic

s N

etw

ork

(SG

N)

http

://

solg

enom

ics.

net/

[ 5

7 ]

SoyB

ase

http

://

soyb

ase.

org/

[ 8

5 ]

tfG

DR

Pro

ject

Web

site

ht

tp:/

/tf

gdr.b

ioin

fo.w

su.e

du/

[8

6]

Tri

ticea

e M

appe

d E

ST D

atab

ase

ver.2

.0 (

Tri

ME

DB

) ht

tp:/

/tr

imed

b.ps

c.ri

ken.

jp/

inde

x.pl

[ 5

0 ]

Veg

Mar

ks

http

://

vegm

arks

.niv

ot.a

ffrc

.go.

jp/

Veg

Mar

ks/

jsp/

page

.do?

tran

sitio

n=m

arke

r

Whe

at g

enom

e in

form

atio

n ht

tp:/

/w

ww

.whe

atge

nom

e.in

fo

[ 65 ,

67 ]

Tabl

e 2

(con

tinue

d)

Kaitao Lai et al.

55

2 Molecular Marker Databases

With the ever increasing amount of genetic and genomic information there is a requirement to manage the data to make it available and accessible to researchers [ 35 , 36 ]. This includes the development of custom visualization tools [ 36 – 38 ] and bioinformatics systems to traverse the genome to phenome divide [ 39 , 40 ]. Many molecular marker databases provide various types of markers for a range of species while some databases provide information on a single type of marker [ 41 ]. The largest single marker database is dbSNP ( http://www.ncbi.nlm.nih.gov/projects/SNP/ ). dbSNP provides SNP data mostly for humans and other vertebrates, although it also includes some plant data.

There are several databases for the grasses. The Gramene data-base ( http://www.gramene.org/ ) hosts many types of markers based on the genomes of rice, maize, grape, and Arabidopsis [ 42 ]. This website provides a search engine, and users can search for spe-cifi c markers. Marker details are displayed in text format, including database cross-references and map positions linked to chromosomes in CMap [ 43 ]. The source of SSR markers includes the International Rice Genome Sequencing Project, IRMI (International Rice Microsatellite Initiative), MaizeGDB, the Cornell SSR library, and the Indian Agricultural Research Institute. Most of the SSR markers are from rice and maize. A total of 2,942 SNP markers from the Gramene database belong to barley and are related to high-throughput SNP genotyping in barley [ 44 ].

GrainGenes ( http://wheat.pw.usda.gov/cgi-bin/graingenes/ ) hosts multiple types of markers for Triticeae and Avena [ 45 – 47 ]. The website also provides comparative map views for wheat, barley, rye, and oats using CMap. Marker types include SSR, RFLP, and SNP. Most of the SNP makers are from two sources [ 44 , 48 ]. An improved SNP-based consensus genetic map has been devel-oped from 1,133 individuals from ten mapping populations. This database provides a search panel with query name or a list of marker names as input.

MaizeGDB ( http://www.maizegdb.org ) provides a search engine to identify ESTs, AFLPs, RAPD probes, and sequence data for maize. The legume information system (LIS) provides access to markers such as SNP, SSR, RFLP, and RAPDs for diverse legumes, including peanut, soybean, alfalfa, and common bean.

The Panzea ( http://www.panzea.org/ ) database describes the genetic architecture of complex traits in maize and teosinte. This database also provides a marker search interface. Two common types of marker, SNP and SSR, can be searched for. The search results display a list of markers with position details related to different chromosomes. When the marker is selected, the website

Molecular Marker Databases

56

can display this marker in precomputed multiple sequence align-ments using the Look-Align viewer [ 49 ].

TriMEDB (Triticeae mapped EST database) [ 50 ] provides information on mapped cDNA markers that are related between barley and wheat. The current version of TriMEDB provides map- location data for barley and wheat. These data were retrieved from three published barley linkage maps: the barley SNP database of SCRI ( http://bioinf.scri.ac.uk/barley_snpdb/ ), the barley tran-script map of IPK ( http://pgrc.ipk-gatersleben.de/transcript_map/ ), HarvEST barley versions 1.63 and 1.68 ( http://harvest.ucr.edu/ ), and one diploid wheat map [ 51 ]. Users can search the database from the search markers page using marker and chromo-some names. The search results include the name of any retrieved marker, related linkage maps, chromosome number, map posi-tions, primer pairs for PCR, EST contigs for each sequence resource, a link to the cDNA assembly, and comparative maps for the rice genome. The database can be accessed at http://trimedb.psc.riken.jp/ .

The database of the Rice Genome Annotation Project [ 52 ] hosts putative SSRs in the rice genome pseudomolecules ( http://rice.plantbiology.msu.edu/ ). The rice genome annotation project pseudomolecules (Release 7) were used for SSR identifi cation [ 53 ]. This database provides a web interface and displays predicted SSR markers fi ltered by type and/or chromosome, as well as a GBrowse view to display the SSR sequences.

With the exception of some important species, databases for nongrass species tend to be more limited in scope. There are a large number of Brassica molecular markers developed together with bioinformatics resources [ 54 , 55 ]. The central Brassica portal for all things Brassica ( http://www.brassica.info ) provides a link to access to a range of Brassica molecular markers, including SNP/InDel, SSR, RFLP, AFLP, and RAPD. This website provides a summary of available information for Brassica SSRs and provides a means to exchange and distribute these markers at the Brassica microsatellite information exchange [ 56 ].

The Sol Genomics Network database (SGN; http://solgenomics. net/ ) is a clade-oriented database (COD) hosting biological data for species in the Solanaceae and their close relatives. The data types range from chro-mosomes and genes to phenotypes and accessions. SGN hosts more than 20 genetic and physical maps for tomato, potato, pepper, and tobacco with thousands of markers. Genetic marker types in the database include SNP, SSR, AFLP, PCR, and RFLP [ 57 ].

The SoyBase database ( http://soybase.org/ ) hosts genomic and genetic data for soybean. The markers include SNP, SSR, RFLP, RAPD, and AFLP. The markers can be viewed from CMap and have also been linked to their corresponding location in a Gbrowse2 genome viewer. Each marker comes with the genomic sequence, detection method, and information source.

Kaitao Lai et al.

57

VegMarks ( http://vegmarks.nivot.affrc.go.jp/ ) is a database for vegetable genetic markers developed by National Institute of Vegetable and Tea Science (NIVTS) in Japan. This database pro-vides various marker characteristics, including ID number, genetic map position, nucleotide sequence of the clones/PCR primers, and polymorphism data among varieties/accessions for Chinese cabbage, bunching onion, cucumber, eggplant, melon, and tomato. The markers hosted in this database include SNP, SSR, and RFLP. Some marker data is restricted for registered users only. This data-base provides a single map for each chromosome together with marker position information.

MoccaDB ( http://moccadb.mpl.ird.fr/ ) is an integrative database for functional, comparative, and diversity studies in the Rubiaceae family which includes coffee [ 58 ]. It provides an easy access to markers, such as SSR, SNP, and RFLP and related infor-mation data such as PCR assay conditions, cross amplifi cation within related species, locus position on different linkage maps, and diversity parameters. It also provides a search engine for searching related markers by keywords and downloads of related data in Microsoft Offi ce Excel format.

The Cotton Microsatellite Database (CMD) ( http://www.cottonmarker.org/ ) is a curated and integrated web-based relational database providing centralized access to publicly available cotton SSRs. CMD contains publication, sequence, primer, mapping, and homology data for nine major cotton SSR projects, collectively representing 5,484 SSR markers [ 59 ].

In addition to species-specifi c databases, other databases focus on specifi c marker types. The autoSNPdb database [ 60 ] is based on an early pipeline for SNP discovery from EST sequence data [ 24 , 61 ]. It provides an interface facilitating a variety of queries to search for SNPs within known genes from a range of species including Brassica, rice, barley [ 62 ], and wheat [ 63 ]. The SNP identifi cation method was developed based on polymorphisms related to specifi c genes identifi ed through keyword, sequence similarity, or compara-tive genomics approaches. The results provide sequence annotation and SNP information in tabular and graphical format.

There are an increasing number of bioinformatics resources available for wheat [ 64 ]. WheatGenome.info is an integrated database resource which supplies a variety of web-based systems hosting wheat genetic and genomic data. Wheatgenome.info [ 65 ] provides a GBrowse2-based wheat genome viewer, CMap and CMap3D comparative genetic map viewers [ 38 , 43 ]. From the GBrowse2-based wheat genome viewer, wheat reference genomic sequences are currently only available for wheat group 7 chromo-somes [ 31 , 32 ]. SGSautoSNP (Second Generation Sequencing autoSNP) software has been used to identify more than 900 000 SNPs between four Australian varieties along this chromosome

Molecular Marker Databases

58

group [ 66 ]. More SNPs can be expected to be identifi ed between further wheat cultivars as this project develops.

SSR Primer 2 ( http://fl ora.acpfg.com.au/ssrprimer2/ ) [ 67 ] provides the real-time discovery of SSRs within submitted DNA sequences, with the concomitant design of PCR primers for SSR amplifi cation [ 68 ]. The success of this system has been demon-strated in Brassica [ 69 – 71 ] and strawberry [ 23 ].

A chickpea ( Cicer arietinum L) root EST database hosted at ICRISAT ( http://www.icrisat.org/ ) provides access to over 2,800 chickpea ESTs from a library constructed after subtractive suppressive hybridization (SSH) of root tissue from two closely related chickpea genotypes possessing different sources of drought avoidance and tolerance [ 72 ]. This chickpea root EST database is a subset of larger ICRISAT maintained database. ICRISAT ( http://www.icrisat.org/ ) also hosts a nonredundant set of 4,543 SNPs, which were identifi ed between two chickpea genotypes [ 73 ].

3 Conclusions and Future Direction

Molecular marker databases are expanding rapidly as increasing numbers of markers are developed from the latest high- throughput DNA sequencing technologies. There is an increasing challenge to manage and maintain this expanding data as well as integrate marker data with the growth of available genome sequences. Finally, the greatest challenge will be to fully integrate genetic diversity information with heritable trait information, bridging the genome to phenome divide and providing the tools for more advanced breeding and crop improvement.

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