Software and Databases for managing and selecting molecular markers

General introduction

Pathway approach for candidate gene identification and introduction to metabolic pathway databases.

Identification of polymorphisms in data-based sequences

Databases (General and Crop Specific)

Germplasm GRIN: http://www.ars-grin.gov/npgs/ TGRC: http://tgrc.ucdavis.edu/

Sequence NCBI: http://www.ncbi.nlm.nih.gov/ SGN: http://solgenomics.net/

Metabolic PlantCyc: http://www.plantcyc.org:1555/PLANT/server.html?

New format to NCBI

Access current and past scientific lit.

Increased emphasis on phenotypic data

Germplasm databases

Crop specific germplasm resources

Example: QTL for color uniformity in elite crosses

QTL Trait Origin

2 L, YSD S. lyc.

4 YSD S. lyc.

6 L, Hue ogc

7 L, Hue S. hab.

11 L, Hue S. lyc.Audrey Darrigues, Eileen Kabelka

Carotenoid Biosynthesis: Candidate pathway for genes that affect color and color uniformity.

Disclaimer: this is not the only candidate pathway…

http://www.arabidopsis.org/help/tutorials/aracyc_intro.jsp

Databases that link pathways to genes

http://metacyc.org/

http://www.plantcyc.org/

http://sgn.cornell.edu/tools/solcyc/

http://www.arabidopsis.org/biocyc/index.jsp

http://www.arabidopsis.org/help/tutorials/aracyc_intro.jsp

External Plant Metabolic databasesCapCyc (Pepper) (C. anuum) CoffeaCyc (Coffee) (C. canephora) SolCyc (Tomato) (S. lycopersicum) NicotianaCyc (Tobacco) (N. tabacum) PetuniaCyc (Petunia) (P. hybrida) PotatoCyc (Potato) (S. tuberosum)

SolaCyc (Eggplant) (S. melongena)

Databases that link pathways to genes

http://www.plantcyc.org:1555/

Note: missing step (lycopene isomerase, tangerine)

Check boxes (Note: MetaCyc has many more choices, but no plants)

Scroll down page

Capsicum annum sequence retrieved

http://www.ncbi.nlm.nih.gov/

Select database

Query CCACCACCATCCTCACTTTAACCCACAAATCCCACTTTCTTTGGCCTAATTAACAATTTT |||||||||||||||||||||||||||||||||| ||||||||||||||||||||||||| Sbjct CCACCACCATCCTCACTTTAACCCACAAATCCCATTTTCTTTGGCCTAATTAACAATTTT

Zeaxanthin epoxidase

Probable location on Chromosome 2

Alignment of Z83835 and EF581828 reveals 5 SNPs over ~2000 bp

51 annotated loci

Information missing from other databases is here…

Candidates identified in other databases are here

Comment on the databases:

Information is not always complete/up to date.

Display is not always optimal, and several steps may be needed to go from pathway > gene > potential marker.

Sequence data has error associated with it. eSNPs are not the same as validated markers.

Germplasm data may also have error (e.g. PI 128216)

There is a wealth of information organized and available.

The previous example detailed how we might identify sequence based markers for trait selection.

Query CCACCACCATCCTCACTTTAACCCACAAATCCCACTTTCTTTGGCCTAATTAACAATTTT |||||||||||||||||||||||||||||||||| ||||||||||||||||||||||||| Sbjct CCACCACCATCCTCACTTTAACCCACAAATCCCATTTTCTTTGGCCTAATTAACAATTTT

Improving efficiency of selection in terms of 1) relative efficiency of selection, 2) time, 3) gain under selection and 4) cost will benefit from markers for both forward and background selection.

Remainder of Presentation will focus onWhere to apply markers in a programForward and background selectionMarker resourcesAlternative population structures and size

Relative efficiency of selection: r(gen) x {Hi/Hd}

Line performance over locations > MAS > Single plant

Line-mean heritability (H) for color H H

Trait plant SE line SE Prop Vp SEBRIX 0.14 0.09 0.40 0.26Color-L 0.11 0.04 0.57 0.22 L-MAS 0.25 0.15Color-Hue 0.07 0.04 0.39 0.23 Hue-MAS 0.15 0.06Color unif. -L 0.14 0.11 0.63 0.25 Ldiff-MAS 0.28 0.16Color unif. -Hue 0.13 0.10 0.64 0.23 Hdiff-MAS 0.32 0.14

Indirect Selection

Comparison of direct selection with indirect selection (MAS).

F1 50:50

BC1 75:25

BC2 87.5:12.5

BC3 93.75:6.25

BC4 96.875:3.125

Expected proportion of Recurrent Parent (RP) genome in BC progeny

Accelerating Backcross Selection

Select for target allele

Select for RP genome at unlinked markers

Select for target allele

Select for RP recombinants at flanking markers

Select for RP genome at unlinked markers

Select for target allele

Select for RP recombinants at flanking markers

Select for RP genome on carrier chromosome

Select for RP genome at unlinked markers

Four-stage selection

Two-stage selection

Three-stage selection

References:

Frisch, M., M. Bohn, and A.E. Melchinger. 1999. Comparison of Selection Strategies for Marker-Assisted Backcrossing of a Gene. Crop Science 39: 1295-1301.

Progeny needed for Background Selection During MAS

20 40 60 80 100 125 150 200Two-StageBC1 76.7 78.7 79.7 80.3 80.7 81.3 81.7 82.2BC2 90.3 91.9 92.8 93.3 93.6 93.9 94.0 94.6BC3 95.8 96.2 97.1 97.3 97.4 97.5 97.6 97.8Three-StageBC1 71.2 72.7 73.4 73.6 73.3 73.2 72.8 72.2BC2 86.1 87.2 88.5 89.3 90.2 90.7 91.3 91.8BC3 94.4 95.7 96.5 96.9 97.2 97.3 97.5 97.6

Q10 of RP genome in percentPopulation Size

Q10 indicates a 90% probability of success

From Frisch et al., 1999.

Two-Stage Selection 60 80 100 125BC1 2880 3840 4800 6000BC2 900 1164 1416 1716BC3 228 264 300 348

Total Marker points 4008 5268 6516 8064Cost 0.15 601.2 790.2 977.4 1209.6

0.20 801.6 1053.6 1303.2 1612.80.25 1002.0 1317.0 1629.0 2016.0

Three-Stage SelectionBC1 2880 3840 4800 6000BC2 492 708 960 1308BC3 250 444 504 576

Total Marker points 3622 4992 6264 7884Cost 0.15 543.3 748.8 939.6 1182.6

0.20 724.4 998.4 1252.8 1576.80.25 905.5 1248.0 1566.0 1971.0

Population Size

Marker Data Points required (Modified from Frisch et al., 1999; based on assumption of 12 chromosomes; initial selection with 4 markers/chromosome)

For effective background selection we need:

Markers for our target locus (C > T SNP for Zep)

Markers on the target chromosome (Chrom. 2)

Markers unlinked to the target chromosome (~2 per chromosome arm)

http://www.tomatomap.net

http://sgn.cornell.edu/

Ovate

HBa0104A12

55 polymorphic markers

44 polymorphic markers

Where can we expect to be?

n = 1 n = 2 n = 3 n = 4 n = 5-10 n > 10Total 806 596 106 34 22 38 10

n = 1 n = 2 n = 3 n = 4 n = 5-10 n > 10Total 127 not tested 64 22 11 23 7

Proportion 0.16 0.60 0.65 0.50 0.61 0.70

TA496 ESTs with SNPs VS H1706 BAC sequences

Where EST Coverage = Allele Coverage

Data based on estimated ~42% of sequence, therefore expect as many as 300 markers for a cross like E6203 x H1706

analysis by Buell et al., unpublished

DOS

UNIX

CygWin (Unix emulator)

BLAST

BLAST

BioPerl

Perl

BioPerl

Perl

Cyc

NCBI

When is the time to move from reliance on public databases to in house pipelines?

In-house database

Complete genome sequences are available for:

Soybean, Corn, Potato, Tomato, Cucumber, and more are coming….

DOS

UNIX

CygWin (Unix emulator)

BLAST

BLAST

BioPerl

Perl

BioPerl

Perl

Cyc

NCBI

When is the time to move from reliance on public databases to in house pipelines?

In-house database

QTL’s mapped in a bi-parental cross may not be appropriate for MAS in all populations…

Marker allele and trait may not be linked in all populations.

Genetic background effects may be population specific.

Original association may be spurious.

QTL detection is dependent on magnitude of the difference between alleles and the variance within marker classes.

Confirmation of phenotype along the way is very important!

Take home messages:

Marker resources exist for forward and background selection in elite x elite crosses in tomato.

Marker resources are currently not sufficient for QTL discovery in bi-parental or AM populations; they will soon be.

The best time to use genetic markers : early generation selection

Restructuring of breeding program to integrate markers may include: 1) Increasing genotypic replication (population size) at the expense of replication (consider augmented designs). 2) Collecting objective data.

References:

Kaepler, 1997. TAG 95:618-621.

Frisch, et al., 1999. Crop Science 39: 1295-1301.

Knapp and Bridges, 1990. Genetics 126: 769-777.

Yu et al., 2006. Nature Genetics 38:203-308.

Van Deynze et al., 2007. BMC Genomics 8:465www.biomedcentral.com/content/pdf/1471-2164-8-465.pdf