Abstract
Background
Cytoplasmic male sterility (CMS) is a maternally inherited trait
failing to produce functional pollen. It plays a pivotal role in the
exploitation of crop heterosis. The specific locus amplified fragment
sequencing (SLAF-seq) as a high-resolution strategy for the
identification of new SNPs on a large-scale is gradually applied for
functional gene mining. The current study combined the bulked segregant
analysis (BSA) with SLAF-seq to identify the candidate genes associated
with fertility restorer gene (Rf) in CMS cotton.
Methods
Illumina sequencing systematically investigated the parents. A
segregating population comprising of 30 + 30 F[2] individuals was
developed using 3096A (female parent) as sterile and 866R (male parent)
as a restorer. The original data obtained by dual-index sequencing were
analyzed to obtain the reads of each sample that were compared to the
reference genome in order to identify the SLAF tag with a polymorphism
in parent lines and the SNP with read-associated coverage. Based on
SLAF tags, SNP-index analysis, Euclidean distance (ED) correlation
analysis, and whole genome resequencing, the hot regions were
annotated.
Results
A total of 165,007 high-quality SLAF tags, with an average depth of
47.90× in the parents and 50.78× in F[2] individuals, were sequenced.
In addition, a total of 137,741 SNPs were detected: 113,311 and 98,861
SNPs in the male and female parent, respectively. A correlation
analysis by SNP-index and ED initially located the candidate gene on
1.35 Mb of chrD05, and 20 candidate genes were identified. These genes
were involved in genetic variations, single base mutations, insertions,
and deletions. Moreover, 42 InDel markers of the whole genome
resequencing were also detected.
Conclusions
In this study, associated markers identified by super-BSA could
accelerate the study of CMS in cotton, and as well as in other crops.
Some of the 20 genes’ preliminary characteristics provided useful
information for further studies on CMS crops.
Electronic supplementary material
The online version of this article (10.1186/s12864-017-4406-y) contains
supplementary material, which is available to authorized users.
Keywords: CMS, High-throughput sequencing, SLAF-seq, Super-BSA, Cotton
Background
As a maternally inherited characteristic, cytoplasmic male sterility
(CMS) plays a major role in crop heterosis research and practice. The
current studies suggest that CMS is caused by mutations in the
correlated genes in the mitochondrial genome and inhibited by fertility
restorer genes in the nuclear genome [[41]1]. This phenomenon exists in
bean [[42]2, [43]3], petunia [[44]4], sorghum [[45]5], and rice
[[46]6]. Fertility restorer gene (Rf), was often found in these crop,
can inhibit the expression of mitochondrial sterility gene. For the
cotton, the gene are not consistent in different sterile lines.
The main cotton hybrids, which have the value of utilization were
Harknessii cytoplasmic male sterile line, Trilobum cytoplasmic male
sterile line, and cytoplasmic sterile line of upland cotton (104-7A,
Xiangyuan A, Jin A). The three-line hybrid selection of China was
primarily derived from the cytoplasmic male sterile lines of the upland
cotton. Since the CMS sources are different, the restorers are also
different, which leads to various theories on the CMS recovery
mechanism of cotton. The fertility restoring characteristics of CMS in
Harknessii cotton were regulated by one dominant gene, Rf1. The sterile
nature of the Trilobum cotton could be restored by either Rf2 of the
Trilobum restorer gene or Rf1 of the Harknessii restorer gene; however,
Rf2 is not able to restore the CMS-D2–2 of Harknessii. Rf1 and Rf2 are
closely linked with a distance of 0.93 cM [[47]7]. The Chinese breeding
varies from the CMS lines of Harknessii and Trilobum. The fertility
restoration of upland cotton CMS line is regulated by two pairs of
independent recovery genes: Rf1 completely dominant and Rf2 partially
dominant. The recovery effect of Rf1 is higher than that of Rf2
[[48]8]. The identification of the molecular marker and gene mapping of
CMS in cotton has also progressed. Liu et al. found 3 SSR and 2 RAPD
markers closely linked to the restorer gene [[49]9]. Feng et al. found
that 3 STS was co-segregated from the restorer gene [[50]10]. Yin et
al. constructed accurate genetic and physical maps of 15 molecular
markers closely linked to the restorer gene that was located on
chromosome 19 (LGD08 linkage group) with a genetic distance of <1 cM,
and the physical location was on 100 kb between the two BAC clone
overlapping regions [[51]11]. Wang et al. suggested that the two Rf
restorer genes might be located on chromosome 19 in the D chromosome
subgroup, i.e. chromosome D5 of the cotton [[52]12, [53]13]. However,
due to differences in the source of sterile cytoplasm and the variation
in nuclear genotypes, the effects of nuclear gene and sterile cytoplasm
are different. Thus, fine positioning and finding new restorer gene
candidates in upland cotton are essential.
Large-scale genotyping plays a major role in genetic association
studies. Specific locus amplified fragment sequencing (SLAF-seq)
provides a high-resolution strategy for large-scale genotyping and can
be applied to various species and populations [[54]14]; for instance,
cucumber [[55]15], Glycine max [[56]16], and sesame [[57]17]. It is
based on reduced representation library (RRL) and high-throughput
sequencing. The technology has several distinguishing characteristics:
i) deep sequencing to ensure genotyping accuracy; ii) reduced
representation strategy to reduce sequencing costs; iii) pre-designed
reduced representation scheme to optimize marker efficiency; and iv)
double barcode system for large populations [[58]14].
In this study, we used the female parent CMS line 3096A (using CMS
104-7A of upland cotton as a recurrent parent line that was breeded
with the backbone parent line for nucleus replacement) of three-line Ji
FRH3018 [[59]18] and the male parent restorer line 866R with strong
restoring power and its combination F[2] segregating population as the
material. Herein, we studied the fine mapping of the restorer gene and
its correlated candidate gene using high-throughput sequencing
platforms. A total of 137,741 SNPs were detected and we found that 20
candidate genes are identified and 19 genes were found annotated in
each database of the candidate genes located on 1.35Mbp of chrD05.
Methods
Test material
The female parent CMS line 3096 from three-line CMS hybrid Ji FRH3018
of upland cotton and the male parent restorer line 866 with strong
restoring power and its combination F[2] segregation population
(30 + 30 mixed pools with extreme characteristics) were used as
research materials.
Test method
Genomes resequencing of CMS line 3096A and fertility restorer line 866R
Sample collection and SLAF library preparation
Fresh leaves were obtained from the parent lines and F[2], frozen with
liquid nitrogen, extracted by the CTAB method, and assessed for the
quality of DNA by 1% agarose gel electrophoresis. The purity of DNA was
examined using the NanoPhotometer® spectrophotometer (Implen, CA, USA).
The DNA concentration was estimated using Qubit® DNA Assay Kit in
Qubit® 2.0 Fluorometer (Life Technologies, CA, USA).
We used 1.5 μg DNA/sample as input material for the preparations of the
sample. We have chosen to use RsaIas restriction enzyme in the
electronic enzyme-digestion projections to the reference genome
sequences of cotton. Sequencing libraries were generated using RsaIof
restriction enzyme according to the manufacturer’s recommendations, and
index codes were added to ascribe the sequences to each sample.
Briefly, the DNA sample was fragmented by sonication to a size of
350 bp. Then, the DNA fragments were end-polished, A-tailed, and
ligated with the full-length adapter for Illumina sequencing by PCR
amplification. Consequently, the PCR products were purified (Agencount®
AMPure® XP, USA), and libraries were analyzed for size distribution by
Agilent2100 Bioanalyzer and quantified by real-time PCR.
Illumina sequencing
The libraries constructed above were sequenced by Illumina HiSeq ™2500
(Illumina, Inc., San Diego, USA) platform at Biomarker Technologies
Corporation in Beijing ([60]http://www.biomarker.com.cn/) and 125 bp
paired-end reads were generated with an insert size approximately
350 bp.
Data analysis, data filtering, and alignment
The recently released genome of Gossypium hirsutum was downloaded from
Cotton Research Institute (CRI) of Nanjing Agricultural University in
China. ([61]http://mascotton.njau.edu.cn/Data.htm, v1.1) and used as a
reference genome [[62]19]. Fastx-toolkit (v 0.0.14–1) was used to
filter out the low-quality reads based on the following criteria: (i)
reads with ≥10% unidentified nucleotides (N); (ii) reads >50% read
length with a Phred quality value ≤10; (iii) reads with the adapter.
The remaining clean reads were aligned to the reference cabbage genome
using BWA-MEM (0.7.10-r789) [[63]20] and default parameters. Sequence
Alignment/Map tools (SAMtools) (v1.1) [[64]21] was applied to sort and
index the resulting binary alignment map (BAM) format files. The
duplicates were excluded using Picard tools (v1.102)
([65]http://broadinstitute.github.io/picard/), and the final sorted bam
files were utilized in the downstream analysis. Variant calling and
filtering were performed in order to reduce the inaccuracy of the
alignment. The local realignment around insertions and deletions, the
base quality recalibration of the reads and variant calling was
conducted using GATK Tools version 3.6. GATK Haplotype Caller (HC) was
used for variant calling [[66]22, [67]23]. The variants that fulfilled
the following criteria were retained (1) mapping quality filter
equivalent to PASS; (2) quality depth (QD) >2; (3) mapping quality (MQ)
>40; (5) QUAL >30. Moreover, the variants were filtered further if the
coverage was <10, the cluster SNPs were >2 in a 5 bp window, if the SNP
around the Indel was within 5 bp. SV detection and annotation
BreakDancer was used to predict the five types of structural variants
(SVs): insertions (INSs), deletions (DELs), inversions (INVs),
intra-chromosomal translocations (ITXs), and inter-chromosomal
translocations (CTXs) from next-generation paired-end sequencing reads
utilizing the read pairs mapped with excessive separation distances or
orientation. The SVs with read depth < 2 were filtered. Bedtools was
employed to annotate the detected DELs, INSs, and INVs. The detection
and annotation of CNVs (copy number variations) refers to a normal
variation in the number of copies of ≥1 sections of some genomic
fragments. We used CNVnator (parameters: -call 100) for the
identification of CNVs and bedtools for annotations.
SLAF library construction and high-throughput sequencing
The target fragment was selected by PCR amplification, purification,
sample mixing, and excising from the gel. Illumina HiSeq™2500 was
utilized for sequencing after inspection of the quality of the library.
SLAF tag development and SNP detection
The original data reads were obtained by dual-index sequencing for each
sample. After filtering the sequencing joints of the reads, the
sequencing quality, and the volume of data were assessed. The
efficiency of Rsa I through the control data was used to determine the
accuracy and efficiency of the test procedure. The data reads were
compared to that of the reference genome and the SLAF tag was developed
in parent lines and mixed pools in order to identify the SLAF tag with
a polymorphism in parent lines and SNP with reads coverage [[68]21]. A
correlation analysis was conducted to identify the SNPs on the loci
closely related to the characteristics and determine the candidate
regions according to the correlation thresholds. Finally, a functional
annotation and biological pathway enrichment analysis were conducted to
identify the genes in the candidate regions.
Correlation analysis
SNP-index analysis
The SNP-index of the two mixed pools was calculated using the SNP data
of the parent lines and assessing the loci that might be associated
with the segregation of characteristics through the ΔSNP-index [[69]24,
[70]25]. The SNP-index is calculated as follows:
[MATH: SNP‐indexMut=ρx/ρX+ρx<
/mtr>SNP‐indexWT=ρx/ρX+ρx<
/mtr>ΔSNP‐index=SNP‐indexMut‐SNP‐i
ndexWT :MATH]
Mut and WT are the mutation and wild-type pool of the filial
generation, respectively. ρX and ρx indicate the number of reads of the
alleles of the wild and the mutation parent lines appearing in their
pools, respectively. The difference in each locus between the mutation
and pools can be observed through the ΔSNP-index [[71]26]. In order to
eliminate the false positive locus, the SNP-indexes marked on the same
chromosome can be fit by the position of the marker on the genome. The
region above the threshold is correlated to the parameters. With
respect to the qualitative character, the correlation threshold is the
theoretical ΔSNP-index value of the corresponding population. For
example, the correlation threshold of the F[2] population is 0.67. In
the case of quantitative character the correlation threshold is
obtained by a computer simulation sampling experiment, and the
probability of each marker associated with the target characteristic is
calculated.
Euclidean distance (ED) algorithm
The ED algorithm evaluates the significant difference between mixed
pools using the sequencing data. It also evaluates the area associated
with the specific parameter [[72]27]. Theoretically, in addition to the
difference in the target character-related loci between the two mixed
pools established by BSA, the others tend to be consistent, and hence,
the ED value of the non-target related loci is equivalent to 0. The
formula for ED is as follows:
[MATH: ED=Amut−Awt2+Cmut−Cwt2+Gmut−Gwt2+Tmut−Twt2<
/msqrt> :MATH]
The larger the ED value, the greater the difference between the two
mixed pools. Amut is the frequency of the A base in the mutation pool,
and Awt is the frequency of the A base in the wild pool; Cmut is the
frequency of the C base in the mutation pool, Cwt is the frequency of
the C base in the wild pool; Gmut is the frequency of the G base in the
mutation pool, Gwt is the frequency of the G base in the wild pool;
Tmut is the frequency of the T base in the mutation pool, Twt is the
frequency of the T base in the wild pool.
In the analysis, the SNP loci with differences in the genotypes between
the two mixed pools are used for calculating the depth of each base in
the different pools and the ED value of each locus. The original ED
value is processed such as to exclude the background interference. In
order to eliminate the false positives, the position of the marker on
the genome can be utilized to fit the labeled ED on the same chromosome
and select the region above the threshold as the region related to the
fertility restoring gene according to the association threshold. In
order to eliminate the false positive locus, the ED values marked on
the same chromosome can be fit according to the position of the marker
on the genome. The region above the threshold is selected as the region
related to the fertility restoring gene according to the correlation
threshold.
Identification of potential candidate genes
The reference genome sequence of the AD genome of tetraploid G.
hirsutum was downloaded. The region related to the target
characteristics was identified in both genome sequences and scanned for
annotated genes using the Multiple Sequence Comparison by
Log-Expectation software.
The Method of InDel (insertion-deletion Length Polymorphism) Markers
Development on the Correlated Region.
Eprimer3 in the EMBOSS (v6.4.0) [[73]28] software package was used on
both ends of these loci sequences to design primers. The PCR reaction
system constituted of 25 μL, containing 2 mmol/L MgCl2, 100 μmol/L
dNTP, 0.2 μmol/L primers, 2 U Taq polymerase, 50 μL template DNA, and
overlying 20 μL mineral oil. The PCR reaction was carried out in type
PE480 DNA amplification equipment at 94 °C degeneration 3 min, 94 °C
modified 30s, 40s, 58 °C annealing stretching up to 72 s, and 72 °C for
40 cycles, followed by a final extension at 72 °C for 10 min. The PCR
products were resolved on 6% polyacrylamide electrophoresis.
Results and analysis
SLAF-seq data analysis and evaluation
The two parent lines and F[2] segregation population were sequenced by
SLAF-seq. Rsa I is selected to construct the SLAF library, and the SLAF
fragment should be between 364 and 414 bp; 38.94 M reads were obtained.
The reads from samples were aligned to the reference genome using the
BWA software, with >80% efficiency, which is normal. For sequencing
results, the average Q30 was 92.01%, and the average GC content was
37.63%. The male parent lines (R restorer lines) retrieved 9,673,045
reads, Q30 was 90.07%, and the average GC content was 37.40%. On the
other hand, the female parent lines (A sterile lines) obtained
9,901,640 reads, Q30 90.65%, and the average GC content was 37.41%. The
filial generation F[2] (aa and ab) retrieved 10,687,924 and 8,679,918
reads, respectively, Q30 was 93.73% and 90.04%, respectively, and the
average GC content was 37.96% and 37.73%, respectively (Table [74]1).
Table 1.
Mining results of the high-throughput sequencing data
Sample ID Total map (%) Properly mapped (%) Total Reads Q30 percentage
(%) GC percentage (%)
R 99.11 95.42 9,673,045 90.07 37.4
A 99.35 95.77 9,901,640 90.65 37.41
aa 99.18 95.41 10,687,924 93.73 37.96
ab 99.41 95.76 8,679,918 90.04 37.73
[75]Open in a new tab
Development of SLAF tag and SNP
A total of 165,007 SLAF tags have been developed. The average
sequencing depth of the parent lines was 47.90× and that of the mixed
pools was 50.78×. Of these, the male parent lines obtained 16,173 SLAF
tags with an average sequencing depth of 46.01×. The female parent
lines obtained 161,854 SLAF tags, and the average sequencing depth was
49.78×; whereas, the filial generation F[2] retrieved 163,688 and
163,189 SLAF tags, respectively, and the average sequencing depth was
55.96× + 45.59× (Table [76]2).
Table 2.
Sequencing data of the developed SLAF markers
Sample ID SLAF number Total depth Average depth
R 161,173 7,415,507 46.01×
A 161,854 8,057,541 49.78×
aa 163,688 9,159,461 55.96×
ab 163,189 7,440,285 45.59×
[77]Open in a new tab
SNPs were primarily detected by GATK software. According to the
positioning results of the sequencing reads to the reference genome,
GATK performs the local realignment, GATK mutation detection, samtools
mutation detection, and identifying the overlapped mutation loci of
GATK and samtools in order to ensure the accuracy of SNP, and obtain
the final SNP loci set. A total of 137,741 SNPs were detected, of
which, the male parent SNPs were 113,311, and the heterozygosity of
SNPs in the sample was 4.19%. The female parent SNPs were 98, 861, and
the heterozygosity was 5.37%. The filial generation F[2] demonstrated
82,874 and 75,961 SNPs, respectively, and the heterozygosity was 20.55
and 19.28%, respectively (Table [78]3). The distribution of SLAF tags
and SNP markers on different chromosomes was enumerated
(Additional file [79]1), chrA01 had the maximum number of SLAF tags,
while chrA08 exhibited the maximum number of SNP markers. According to
the distribution of SLAF and SNP on the chromosome, the chromosome
distribution map of SLAF tag and SNP is plotted. The specific
distribution is shown in Fig. [80]1.
Table 3.
The statistic results of each sample SNP
Sample ID Total SNP SNP number Heterozygous locus numbers ratio (%)
R 137,741 113,311 4.19
A 137,741 98,861 5.37
aa 137,741 82,874 20.55
ab 137,741 75,961 19.28
[81]Open in a new tab
Note: Total SNP: Total number of SNP is detected, SNP num: The number
of SNPs in the corresponding samples detected, Heterozygous locus
numbers ratio (%):The heterozygous locus numbers account for the
proportion of all locus of SNPs in the sample
Fig. 1.
Fig. 1
[82]Open in a new tab
SLAF distribution and SNP markers on chromosome. Note: The abscissa is
the length of the chromosome. Each yellow band represents a chromosome.
The genome is divided by every 1Mbp. The more the number of SLAF tags
in each window, the deeper the color and lesser the number of SLAF
tags, the lighter the color. The darker area in the figure is the area
where the SLAF tags are centrally distributed. The left panel shows the
distribution of the SLAF tag, and the right panel is the distribution
of SNP
Correlation analysis by SNP-index and ED
Before the correlation analysis by SNP-index, 137,741 SNPs are
filtered. A total of 16 SNP loci with multiple mutations are also
filtered out. 102,105 loci with reads support <4 in the mixed pools are
filtered out, and 27,289 loci that do not exist in the parent lines are
filtered out. Finally, 8331 SNPs were obtained for the follow-up
analysis. Using the SNP-index method, the correlation threshold was
0.67 according to the theoretical separation ratio of the experimental
population. 20 association regions (Fig. [83]2) containing the genes
were obtained, located at chr D05.
Fig. 2.
Fig. 2
[84]Open in a new tab
The distribution of SNP-index-associated values on chromosome. Note:
The abscissa is the chromosome name. The color point represents the
calculated SNP-index (or ΔSNP-index) value, and the black line is the
fitted SNP-index (or ΔSNP-index) value. The top graph illustrates the
distribution of the SNP-index values in h mixed pool; the middle graph
is the distribution of the SNP-index values in L mixed pool; the bottom
graph is the distribution of the ΔSNP-index values, where the magenta
line represents the theoretical threshold line
Similarly, before correlation analysis by ED, 137,741 SNPs should also
be filtered out. 102,114 loci with read support <4 in any mixed pool
are first filtered out, resulting in 35,627 high-quality and
reliability loci. Therefore, a total of 14,226 different loci were
identified between the two mixed pools. The correlation value was
calculated by ED, and the median + 3SD of all the loci fitted values
was considered as the correlation threshold of the analysis: 0.4969. A
total of 351 correlated genes (Fig. [85]3) were obtained according to
the correlation threshold.
Fig. 3.
Fig. 3
[86]Open in a new tab
The distribution of ED-associated values on chromosome. Note: The
abscissa is the chromosome name. The color point represents the ED
value of each SNP locus. The black line is the fitted ED value, and the
red dotted line represents the significantly associated threshold. The
higher the ED value, the better the correlation effect
Finally, the intersection of the associated genes obtained from the
above two methods was found to be located on the candidate gene on
1.35 Mb of chrD05, and about 20 candidate genes were identified
(Table [87]4). A correlation analysis of the genetic information to the
associated region is summarized in the Additional file [88]2.
Table 4.
The information of the association region
Assocition region Chromosome ID Start End Size (Mb) Gene number
I chrD05 37,535,705 37,755,211 0.22 6
II chrD05 39,558,551 40,416,294 0.86 12
III chrD05 40,531,406 40,804,095 0.27 2
Total 1.35 20
[89]Open in a new tab
Gene functional annotations in related area correlation region
The 20 genes in the correlated region are compared to the databases of
NR, SwissProt [[90]29], GO [[91]30], COG, and KEGG [[92]31] using BLAST
software. Finally, the annotations of 19 genes were obtained
(Additional file [93]3). A total of 19/20 genes were found annotated in
each database. Of these, annotations of 8 genes in KEGG, participating
in 10 signaling pathways were found, including plant hormone signal
transduction, protein output, DNA replication, homologous
recombination, mismatch repair, nucleotide excision repair, ribosome,
nitrogen metabolism, purine, and pyrimidine metabolism. In the DNA
replication pathway, the enrichment factor 29.37 was a significant
difference (p = 0.00186).
Differences in sterile and restorer line on the correlated region
The genomes of the CMS line 3096A and fertility restorer line 866R were
sequenced at 19× and 20× read depth, respectively, by Illumina
sequencing of the paired-end libraries. Using the cotton AD-genome
sequence as a reference, genetic variations, single base mutations,
insertions, and deletions as compared to the reference genome were
identified. The comparison of the structure of the genomes of the
sterile and restorer lines on the correlated region revealed that the
restorer line was located on the SV of the correlated region; however,
the sterile line was not found on the SV as compared to the reference
genome. We found that 7 SVs, 4 SVs are deletion and 3 SVs are
interchromosomal translocation, are on the restorer line (Table [94]5).
A total of 1607 indels were found in the correlated region, including
1246 intergenic indels, 3 exonic indels, involving 3 genes:
Gh_D05G3001, Gh_D05G3028, and Gh_D05G3039; we found 242 intronic
indels, 51 upstream indels and 65 downstream indels. A total of 13,175
SNP loci exhibited differences in the correlated region of the sterile
and restorer lines, including 10,711 intergenic SNPs, 1858 intronic
SNPs, 254 upstream SNPs, 227 downstream SNPs, 124 exonic SNPs and 2
splicing SNPs in reference to the genes, Gh_D05G3005 and Gh_D05G3038.
Nonsynonymous SNPs were found in 16 exonic regions, 1 stop-gain SNP was
identified in Gh_D05G3042, and a stop-loss SNP was discovered in
Gh_D05G3031.
Table 5.
The SV on the correlated region in restorer lines
Chr1 Pos1 Orient-ation1 Chr2 Pos2 Orient-ation2 Type Size Score
num_Reads
D05 40000632 14 + 0- D05 40005953 0 + 16- DEL 5334 99 14
D05 40285089 15 + 0- D05 40286963 1 + 17- DEL 1931 99 15
D05 40356478 17 + 0- D05 40356891 0 + 15- DEL 473 99 13
D05 40643903 13 + 10- D05 40655906 0 + 12- DEL 12091 99 12
D05 39644894 7 + 15- scaffold1082_A05 9062 0 + 14- CTX −318 99 12
D05 37580919 0 + 15- scaffold4041_D05 13444 15 + 0- CTX −318 99 15
D05 39824830 14 + 0- scaffold6268 11207 12 + 14- CTX −318 99 12
[95]Open in a new tab
InDel (insertion-deletion length polymorphism) markers development on the
correlated region
The analysis of the comparison of the correlated regions on the sterile
and restorer lines’ genome sequence found 1607 InDel sites. While
analyzing the sterile and maintainer line amplification of the genomic
DNA and design 165 primers, we found 42 primers (Attached Additional
file [96]4) that distinctly detected the polymorphism, and hence, could
be used as InDel markers. The 42 InDel markup tags, 24 as codominant
markers, and 18 as dominant markers were developed Fig. [97]4. These
will be laid as the underlying foundations for the fine mapping of the
restorer genes.
Fig. 4.
Fig. 4
[98]Open in a new tab
The polymorphic graph of primers. Note: 1–24 Codominant markers 25–42
Dominant markers A: sterile lines R: restorer line
Discussion
The molecular marker discovery and fine mapping of fertility restoring gene
of CMS in cotton
The molecular marker discovery and fine mapping of fertility restorer
gene of CMS in cotton are under intensive research. Yin et al.
established the location of Rf1 on 100 kb between two BAC clone
overlapping regions and selected 5 SSR in proximity to Rf1 by
constructing a BAC library of Gossypium harknessii cytoplasmic male
sterile restorer lines coupled with the genetic and physical maps
recovering gene linkage [[99]11]. Yang et al. screened out 6 EST-SSR
markers (NAU2650, NAU2924, NAU3205, NAU3652, NAU3938, and NAU4040) with
0.327 cM from the fertility restorer Rf1 of CMS in Harknessii cotton
[[100]32]. Wu et al. found that the fertility of CMS-D2 was regulated
by a pair of dominant single gene Rf1, and 13 molecular markers closely
linked to the fertility were screened out. The marker closest to Rf1
was BNL3535 with a genetic distance of 0.049 cM; on the other side
NAU3652 was the nearest marker with a genetic distance of 0.078 cM.
[[101]33]. Wang et al. demonstrated that CIR179–250 was closely linked
to both Rf1 and Rf2, which was located on LGD08 linkage group (D5
chromosome, 19th chromosome) of D genome set with CMS-D2 and CMS-D8
restorer, respectively, of upland cotton used as research material
[[102]13]. Li et al. located Jin-A cytoplasmic male sterile restorer
gene Rf on the 19th chromosome (LGD08) with a distance of 5.4 and
10.3 cM from markers CM042 and CIR179, respectively [[103]34]. You et
al. studied three cotton cytoplasmic male sterile lines and their
corresponding restorers from China, Israel, and the USA, respectively.
The results indicated that 2 restoring genes in the restorers were from
the USA. The Rf1 was positioned between BNL3535 and CIR179 at a
distance of 5.3 cM, while Rf2 was between STS659 and BNL1045 at a
distance of 4.8 cM. Only 1 restoring gene was identified in the
restorers from China, and Rf was between CIR222 and BNL632 at a
distance of 6.7 cM. Only 1 restoring gene was found in the restorers
from Israel, and Rf was between STS147 and CIR179 at a distance of
4.3 cM [[104]35]. According to the SSR primers, we found the recovery
of SSR markers in the gene location map (Table [105]6). Furthermore, we
established that although the sterile line source type was different,
the tags on the reference genome was found on chrD05 between
35,690,656–59,566,733. The present study on the fertility restoration
gene identified the location for chr D05 base sequence as
37,535,705–37,755,211 (0.22Mbp), 39,558,551–40,416,294 (0.86Mbp), and
40,531,406–40,804,095 (0.27Mbp) interval; the sterility-related gene
mapping was reported between NAU2924 and NAU4040 SSR markers. As the
same markers appear in the position of cotton CMS fertility restoring
gene from different sources, it is speculated that the chromosomal
segments of the restoring gene derived from various types of restorer
lines should be consistent. These markers, which are closely linked to
the restorer gene, act as insertion or deletion of the restorer gene
fragment in the process of genetic improvement, resulting in the
altered genetic distance. The present study developed 42 InDel markers
in the correlated region; subsequently, it should be the laid a
foundation for positioning of the cotton fertility restoring genes. The
present results also showed that SLAF-seq technology is an efficient
and high-resolution QTL fine-positioning technique characterized by
high success rate, specificity, stability, and cost-efficiency. The
combination of SLAF-seq technology, SNP_index, and BSA provides an
efficient method for identifying the genomic regions associated with
the characteristics described above.
Table 6.
The summary of restorer gene marker in the genome location
Marker Chromosome ID Genome location Source Restorer gene Reference
NAU2924 D5 35690459–35690656 Gossypium harknessii Rf1 Yang [[106]32]
NAU3652 D5 37123844–37124070 Gossypium harknessii Rf1 Yang [[107]32]
Wu [[108]33]
NAU4040 D5 43363683–43363832 Gossypium harknessii Rf1 Yang [[109]32]
NAU2650 D5 44346401–44346571 Gossypium harknessii Rf1 Yang [[110]32]
NAU3205 D5 50573886–50573694 Gossypium harknessii Rf1 Yang [[111]32]
NAU3938 D5 52546928–52547146 Gossypium harknessii Rf1 Yang [[112]32]
BNL3535 D5 54287875–54288016 CMS-D2 Rf1 Wu [[113]33];
You [[114]35]
CIR222 D5 54288233–54287945 Unknown
(China) Rf You [[115]35]
CM042 D5 55139471–55139336 Jin A Rf Li [[116]34]
BNL632 D5 59566733–59566464 Unknown
(China) Rf You [[117]35]
[118]Open in a new tab
Cloning of fertility restorer gene
The cloning of fertility restorer gene in cotton CMS is yet under
investigation. Yang et al. identified the gene containing Rf1 and
conducted the whole length sequencing. The Rf1 locus is found to
contain 5 PPR genes and 2 genes highly homologous to the PPR gene in a
region of approximately 130 kb. Based on gene prediction,
characterization analysis, and the difference in the phylogenetic
sequence analysis, ORF3 is speculated as the Rf1 gene that encodes the
PPR gene and contains the mitochondrial localization signal. ORF3
necessitates functional complementation by transgenesis [[119]36].
Zhang et al. concluded that the starch synthase and the phosphate
-ribose o-aminobenzoic acid transferase (PAT) gene might be associated
with the Rf2 gene in the Trilobum cytoplasm by differential display
technique analysis [[120]37]. Wu and Hou cloned the genes, GH182Rorf392
and GhPG2, related to cotton fertility restoration from the upland
cotton restorer Y18R line. GH182Rorf392 encodes 392 amino acids. The 3′
end of the gene contains a 26 s rRNA sequence, and the 5′ end is a
novel sequence [[121]38, [122]39]. The gene might interact with
ribosomes in organelles such as mitochondria or chloroplasts. GhPG2
codes for polygalacturonase, which is related to the flower organ
development. In recent years, the Rf genes of crops such as corn
[[123]40], rice [[124]41], onion [[125]42], and sorghum [[126]43] have
been cloned successively. Except for corn Rf2 and Rf4 and rice Rf2 and
Rf17, the other known Rf genes belong to the PPR (pentatricopeptide
repeats) gene family. The coding protein of the PPR gene family is
considered to be a single-stranded RNA-binding protein and plays a
vital role in the processing of organelles’ RNA [[127]44]. The Rf gene
encoding protein plays a major role in organelle RNA processing. The N
ends of the Rf gene encoding protein contains the mitochondrial
localization sequences that are transported to mitochondria after
maturing in the cytoplasm, participating in mitochondrial gene
transcription, post-transcriptional processing, and translation for
regulating the plant fertility [[128]45]. These studies provided
further references for exploring the cotton CMS fertility restorer