High-throughput simple sequence repeat (SSR) mining saturates the carrot (Daucus carota L.) genome with chromosome-anchored markers

Figures & data

Table 1. Simple sequence repeat (SSR) types in the carrot genome.

Motif length	Number of occurences	Frequency^a (%)	Frequency^b (%)
Mononucleotide	54988	39.63	–
Dinucleotide	75633	54.51	90.29
Trinucleotide	6548	4.72	7.82
Tetranucleotide	1230	0.89	1.47
Pentanucleotide	216	0.16	0.26
Hexanucleotide	144	0.10	0.17
Total	138759	100	100

^a Frequency calculated including mononucleotide SSRs in total SSR count.

^b Frequency calculated excluding mononucleotide SSRs in total SSR count.

Table 2. Most abundant simple sequence repeat (SSR) motifs.

SSR motif	Number of SSRs	Motif frequency^a (%)	Motif frequency^b (%)
A/T	51955	37.44	–
G/C	3033	2.19	–
AT	22848	16.47	27.27
TA	21539	15.52	25.71
GA/TC	9618	6.93	11.48
AG/CT	7493	5.40	8.94
CA/TG	7362	5.31	8.79
GT/AC	6511	4.69	7.77
ATT/AAT	1224	0.88	1.46
TAT/ATA	1066	0.77	1.27
TAA/TTA	850	0.61	1.01

^a Motif frequencies in the overall pool of identified SSRs.

^b Motif frequencies within the pool of SSRs used for marker design (mononucleotide SSRs are excluded).

Only motifs with a frequency of ≥ 0.5% are listed.

Table 3. Statistics on simple sequence repeat (SSR) marker numbers and locations in the carrot genome assembly.

Chromosome	Identified SSRs (di- to hexanucleotide)	Number of markers	Input sequence (Mb)	Marker density^a (kb)	Marker density^b (kb)
1	11923	7824	51.47	5.44	7.10
2	10025	6692	43.91	5.41	7.09
3	11626	7567	50.31	5.47	7.25
4	8226	5602	35.92	5.37	6.82
5	9847	6532	41.96	5.27	7.02
6	8587	5802	36.61	5.22	6.76
7	8338	5523	36.36	5.46	7.10
8	7099	4758	31.75	5.43	7.22
9	8100	5086	33.68	5.32	7.33
Total	83771	55386	361.97	5.38	7.08

^a Frequency calculated including all SSR loci amplified by designed primers.

^b Frequency calculated excluding multi-locus markers.

Table 4. Statistics of cross-species marker transferability to fennel genome assembly.

Chromosome	Number of transferred markers	Number of markers producing ≤ 3 alleles
1	106	75
2	98	74
3	116	92
4	82	62
5	97	67
6	83	60
7	82	54
8	63	50
9	67	44
Total	794	578

Figure 1. A set of polymorphic marker fragments visualized by high-resolution capillary electrophoresis. Electropherograms of different size alleles amplified from carrot landraces are displayed for each marker. Primer sequences of markers can be accessed at https://figshare.com/articles/Marker_data/8593337/2.

Table 5. Informativeness of the codominant, polymorphic markers.

Marker ID	Number of alleles	PIC	He
Chr1-MK398	5	0.65	0.69
Chr1-MK918	4	0.58	0.64
Chr1-MK1932	3	0.51	0.60
Chr2-MK941	3	0.56	0.63
Chr2-MK1131	6	0.75	0.78
Chr2-MK4070	2	0.38	0.50
Chr3-MK30	2	0.37	0.48
Chr3-MK65	2	0.37	0.49
Chr4-MK143	3	0.44	0.54
Chr4-MK512	2	0.37	0.50
Chr4-MK1103	2	0.37	0.50
Chr5-MK762	2	0.35	0.46
Chr5-MK958	5	0.70	0.74
Chr5-MK1835	4	0.62	0.67
Chr5-MK3633	4	0.46	0.53
Chr6-MK102	3	0.56	0.64
Chr6-MK1792	2	0.37	0.49
Chr7-MK454	5	0.73	0.77
Chr7-MK810	2	0.37	0.48
Chr7-MK2167	3	0.51	0.59
Chr8-MK222	2	0.36	0.47
Chr8-MK1609	2	0.37	0.49
Chr9-MK231	4	0.58	0.64
Chr9-MK459	4	0.66	0.71
Chr9-MK1499	2	0.37	0.48

PIC: Polymorphism information content calculated according to Botstein et al. [38].

He: Expected heterozygosity calculated according to Nei [39].

Botstein D, White RL, Skolnick M, et al. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet 1980;32(3):314–331.

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Nei M. Analysis of gene diversity in subdivided populations. PNAS 1973;70(12):3321–3323.

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Data availability statement

All data generated during this study are available at Figshare (https://doi.org/10.6084/m9.figshare.8593337).