Improved Gossypium raimondii Genome Using a Hi-C-based Proximity-Guided Assembly

doi:10.21203/rs.3.rs-63005/v3

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Improved Gossypium raimondii Genome Using a Hi-C-based Proximity-Guided Assembly

https://doi.org/10.21203/rs.3.rs-63005/v3

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Journal Publication

published 05 Aug, 2021

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Introduction: Genome sequence plays an important role in both basic and applied studies. Gossypium raimondii, the putative contributor of the D subgenome of Upland cotton (G. hirsutum), highlights the need to improve the genome quality rapidly and efficiently.

Methods: We performed Hi-C sequencing of G. raimondii and reassembled its genome based on a set of new Hi-C data and previously published scaffolds. We also compared the reassembled genome sequence with the previous published G. raimondii genomes for gene and genome sequence collinearity.

Result: A total of 98.42% of scaffold sequence was clustered successfully, among which 99.72% of the clustered sequence was ordered and 99.92% of the ordered sequence was oriented with high-quality. Further evaluation of results by heat-map and collinearity analysis revealed that the current reassembled genome is significantly improved than the previous one (Wang et al. 2012).

Conclusion: This improvement in G. raimondii genome not only provides a better reference genome to increase study efficiency but also offers a new way to assemble cotton genomes. Furthermore, Hi-C data of G. raimondii may be used for 3D structure research or regulating analysis.

Plant Physiology and Morphology

Plant Molecular Biology and Genetics

Gossypium raimondii

Hi-C

genome assembly

heatmap and collinearity

Over the last decade, next-generation sequencing (NGS) technologies have brought immense improvements in plant genome sequencing throughput and reduced the cost, and many plant genomes have been sequenced using this technology such as F. vesca (Shulaev et al. 2011), C. cajan (Varshney et al. 2012), G. raimondii (Wang et al. 2012; Paterson et al. 2012, Udall et al. 2019), G. arboreum (Li et al. 2014) and G. hirsutum (Li et al. 2015; Zhang et al. 2015). However, de novo assembly of large eukaryotic genomes has remained a great challenge with the NGS platform due to a significant amount of repeat contents. As a result, de novo assembly of chromosome-scale scaffolds has become a major constraint to the completion of a high-quality genome sequence. Compared with the traditional method, like genetic map and physical map, high-throughput chromosome conformation capture (Hi-C) technology has assisted in the assembly of long scaffolds to produce chromosome-scale genome assemblies (Lightfoot et al. 2017). The Hi-C technique is based on existing scaffolds and restriction enzyme cutting sites, which are more evenly distributed and have much higher density.

The Hi-C-based proximity-guided assembly was initially developed to study the three-dimensional (3D) conformation of chromosomes of yeast gene expression (van Berkum et al. 2010). The working principle based on two regular models with Hi-C data: the first one is that the rate of Hi-C interaction is inversely proportional to the genomic distance between the pairs of loci, the second one is that the rate of Hi-C interaction of pairs of loci within a chromosome is significantly higher than that in different chromosomes (Xie et al. 2015). Based on these two models, Hi-C-based proximity-guided assembly was applied for de novo assembling of human, and subsequently for the assembling of mouse and Drosophila genomes which reported good results or improvement (Burton et al. 2013). With the success of testing and verifying this method in Arabidopsis thaliana (Xie et al. 2015), Hi-C based proximity-guide assembly has been reported as an effective and efficient method which subsequently has been used in many other plants.

Besides its commercial value, cotton also serves as a perfect model system for studying cell wall biosynthesis (Zhang et al. 2018), cell elongation (Guo et al. 2017), and polyploidization (Yuan et al. 2015). The Gossypium genus comprises more than 50 species including at least 5 tetraploid species and 45 diploid species. Diploid cottons are divided into 8 sub-genomes, denoted A-G and K based on chromosome pairing relationships (Wendel et al. 1992). Tetraploid cottons, such as cultivated G. hirsutum (AD₁) and G. barbadense(AD₂), had formed by an allopolyploidy event about 1-2 million years ago (Paterson et al. 2012). These tetraploid cotton species share common ancestors with the modern New World species G. raimondii (D₅) and the Old World A-genome species G. herbaceum (A₁) or G. arboreum (A₂). Previously, genomes of different cotton species sequenced and assembled including G. raimondii (Wang et al. 2012), G. arboreum (Li et al. 2014), and G. hirsutum (Li et al. 2015).

Among these cotton species, the genome of G. raimondii has the lowest complexity which has been sequenced and assembled using the next-generation Illumina paired-end sequencing strategy (Wang et al. 2012). Approximately 73% (281 scaffolds) of the assembled sequences were anchored to 13 chromosomes, covering 88.1% of the genome, while only 52.4% (228 scaffolds) of the total sequence was both ordered and oriented. The completeness and accuracy of the previous sequenced and assembled genome of G. raimondii (Wang et al. 2012) were relatively low due to higher numbers of repeat elements and low numbers of genetic markers. In the present study, we conducted a de novo Hi-C sequencing of G. raimondii, and incorporated the new Hi-C data with the existing G. raimondii scaffolds (Wang et al. 2012) to improve the quality of the D-genome.

1. Tissue collection and Hi-C sequencing

1.1 Plant materials

The seeds of G. raimondii D_5-1 were planted in an incubator at constant environmental conditions having 27^ᵒC temperature, 60% relative humidity, 16/8-h light/dark photoperiod, and 100% fluorescent light. When the sixth euphylla came out, these seedlings were transplanted into big pots. Approximately 3-gram young leaves from G. raimondii plants were collected and immediately treated with formaldehyde.

1.2 Hi-C pipeline

During this study, we have used the same Hi-C pipeline as in Arabidopsis thaliana (Xie, Zheng et al. 2015). Before starting this experiment, we have tested the integrity of DNA from the formaldehyde-treated tissue, and then the DNA was isolated and digested by MboI instead of HindIII because of the shorter recognition site (only four bases of MboI). The resulting sticky ends were filled with nucleotides in which cytosine is biotinylated, and ligated the adjacent blunt ends to a chimeric circle under extremely dilute conditions. Subsequently, DNA was purified and broken into 300-500 base pairs using ultrasonic, pull-down the biotin-labeled DNA and performed the PCR reaction (10 cycles). After DNA purification, the finished Hi-C library was sequenced with an Illumina Hiseq (PE150). A total of 570,412,361 read-pairs were obtained.

2. Genome assembly based on Hi-C data

Assembling of G. raimondii genome involved three steps. First, valid Hi-C paired-end reads and contact matrix with a resolution of 100 kb were generated by HiC-Pro (Servant, Varoquaux et al. 2015). The raw sequence data with low quality, unmapped and invalid mapped paired reads were filtered out by HiC-Pro and contact-matrix based on interaction frequency was created. HiC-Pro results show that 95.6% of sequences is clean Q30 bases, showing a good quality of sequence data. After the Hi-C data were filtered out, 81.95% of uniquely mapped sequences are valid paired-end reads. Thus, the valid paired-end reads (223,304,666) were used for further genome assembly. At the second step, Errors in scaffolds of the initial draft assembly were identified and corrected following the Aedes aegypti’s de novo assembly procedure (Dudchenko, Batra et al. 2017). Briefly, the errors were corrected by identifying the bins where a scaffold’s long-range contact pattern changes abruptly, which is unlikely for a correct scaffold. We cut out the error bins as a new scaffold. There are 259 errors within scaffolds. At the third step, the G. raimondii genome was assembled with the Hi-C data by Lachesis (Burton et al. 2013),which contained clustering, ordering, and orienting. Lastly, the assembled G. raimondii genome was assessed by heat-map and collinear analysis.

3 Repeats and gene annotation

Repeat sequences of G. raimondii genome were masked by RepeatMasker (v4.0.8; Smit et al. 2019) with a custom library generated from RepeatModeler(v2.0.1; Flynn et al. 2020). Repeat-masked sequences were obtained as a draft genome in gene prediction. de novo prediction, homology-based prediction and transcriptome-based prediction were combined to annotate the draft genome of G. raimondii. glimmerHMM (v3.0.4; Chrysanthou et al. 2011) and AUGUSTUS(v3.3.2; Stanke et al. 2006) were run for de novo prediction, We used 9 transcriptomes (SRR389181, SRR203240, SRR203250, SRR8878792, SRR8878720, SRR8878562, SRR8878553, SRR8878556, SRR8878559) of G.raimondii from different organs and growth stage to predict genes; Homologous proteins from arabidopsis, maize, and rice were input into GenomeThreader (v1.6.1; Gremme. 2015) to train models for homology-based prediction. Sequences of transcriptome samples were aligned to draft genome by HISAT2 (v2.1.0; Kim et al. 2019) and transcripts were assembled by StringTie (v1.3.6; Pertea et al. 2015). All files in general feature format were integrated into a final genome annotation file by EvidenceModeler (v1.1.1; Haas et al. 2008).

THe reassembled genome was evaluated in three aspects, completeness, consistence, and continuity. We evaluated continuity according to the length of scaffoldN50 calculated by our python script. Completeness was checked by BUSCO(v4.1.4; Simão et al. 2015) and consistency was evaluated by comparative analysis between our reassembled genome and other published genomes of G. Raimondii. Genome aligned were performed by minimap2(v2.1; Heng. 2018) and dot plots were generated by dotPlotly (https://github.com/tpoorten/dotPlotly/). Orthologous genes of G. Raimondii genomes were detected by Orthofinder(v2.5.1; Emms et al. 2015), visualization of orthologous gene detection were implemented by jcvi (https://github.com/tanghaibao/jcvi). All parameters of software in this article were set as default.

1 Assembling results

The genome of G.raimondii was reassembled using Hi-C data. About 98.42% of total sequence length was clustered successfully, among which 99.72% and 97.37% of the clustered sequence were ordered and high-quality ordered, respectively. And approximately 99.92% of the ordered sequence was oriented with high-quality. The statistics of pseudo-chromosome length are shown in Table 1, while the indicator statistics of the initial draft genome and reassembly results are shown in Tables 2 and 3, respectively. From the parameters like scaffolds number, N50 and N60 of previously draft genome and reassemble genome, we found that the G. raimondii genome using a Hi-C-based proximity-guided assembly is much better than the reported draft genome (Wang et al. 2012).

2 genome assessment results

The quality of the reassembled genome could be verified in four aspects. First, BUSCO analysis reported 97.2% (>90%) completeness scores for the reassembled genome, indicating it is complete. Compared to ~32000 genes in the old draft genome (besides scaffolds), 3,8975 genes have been found in the annotation of the reassembled genome. Second, The heat-map directly proves the validity of the processing methods. Based on the two regular models as we mentioned above, the heat-map of the reassembled results revealed that the diagonal interaction is much higher. The boundaries of each pseudo-chromosome are relatively clear and it is under low background noise that shows good reassembling results (Fig. 1). Third, we compared the draft genome and reassembled genome with two previous genome assemblies of G. raimondii (Paterson et al. 2012, Udall et al. 2019) (Fig. 2). The reassemble genome had a general agreement in their alignments with two previous genome assemblies than the draft genome. Fourth, we compared homologous genes in the draft genome and reassembled genome with which in two previous genome assemblies of G. raimondii (Paterson et al. 2012, Udall et al. 2019) (Fig. 3), it showed a good agreement, and the size of chromosome in the reassembled genome is more believable than the draft genome.

In the present study, we applied de novo Hi-C sequencing of the G. raimondii genome to improve the quality and accuracy of its previously reported draft genome from Wang et al. (2012). Results from the comparative analysis of different parameters between the draft genome (Wang et al. 2012) and the current reassembled genome showed a significantly improved quality as compared to the previous one. And Hi-C data can be used in a future study as basic data, such as 3D model genome.

NGS: next generation sequencing

Hi-C: high-throughput chromosome conformation capture

CAAS: Chinese Academy of Agricultural Science

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

Not applicable.

Funding

Not applicable.

Authors' contributions

Yang QH and Song GL conceived and designed the experiments; all authors performed data analysis and interpretation; Yang QH, Javaria A, Liu S and Song GL wrote the manuscript.

Acknowledgements

This work was supported by CAAS.

Data availability:

The reassembled genome sequences and annotation files will be upload after received.

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Table 1 The statistics of pseudo-chromosome length.

We named the reassemble chromosome by its length order. The length of chromosome contained the 100 bp N between neighboring scaffolds.

Pseudo-chromosome

Length (bp)

chr1

chr2

chr3

chr4

chr5

chr6

chr7

chr8

chr9

chr10

chr11

chr12

chr13

Total anchored
Unanchored

53,706,613

58,208,992

49,533,501

60,231,643

63,950,048

49,383,601

65,258,068

56,972,542

68,312,541

60,016,945

62,276,721

37,762,904

59,096,274

744,710,393
14,054,600

Table 2 The statistics of the draft genome.

All of the statistics got rid of the short scaffolds (scaffold length < 1000bp).

Parameters

Contigs length (bp)

Scaffolds length (bp)

Contigs number

Scaffolds

number

Total
Max_length
Number>=2000bp
N50
N60

716,234,346
333,622
-
44,885
35,741
27,678

756,905,237
10,920,000
-
1,600,000
1,216,543
947,408

37,849
-
27,412
4,810
6,597
8,872

2,582
-
1,626
139
194
264

Table 3 The statistics of the reassembled G. raimondii genome.

All of the statistics got rid of the short scaffolds (scaffold length < 1000bp).

Parameters	Contigs length (bp)	Scaffolds length (bp)	Contigs number	Scaffolds number
Total Max_length Number>=2000bp N50 N60	716,283,110 333,622 - 44,885 35,740	757,086,669 73,966,406 - 60,016,944 58,208,991	37,921 - 27,412 4,810 6,598	1,329 - 462 6 8


Table 4: The statistics of clustering results.
Sample		Gossypium raimondii
Number of Sequence in Draft Genome Length of Sequence in Draft Genome /bp Number of Sequence in Clustering Rate of Numbers in Clustering /% Length of Sequence in Clustering /bp Rate of Length in Clustering /%		4,974 758,633,485 2,883 57.96 746,659,745 98.42

Table 5: The statistics of ordering results.

Sample

Gossypium raimondii

Number of Sequence in Ordering

Rate of Number in Ordering /%

Length of Sequence in Ordering

Rate of Length in Ordering /%

Number of Sequence in Trunks

Rate of Number in Trunks /%

Length of Sequence in Trunks

Rate of Length in Trunks /%

1,328

46.06

744,578,885

99.72

697

52.48

724,960,878

97.37

Table 6: The statistics of orienting results.
Sample	Gossypium raimondii
Number of Sequence in Orienting Rate of Numbers in Orienting /% Length of Sequence in Orienting /bp Rate of Length in Orienting /%	1,129 85.02 743,948,690 99.92

Table 7: The statistics of pseudo-chromosome length.
Pseudo-chromosome	Scaffolds number	Length /bp
chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 chr9 chr10 chr11 chr12 chr13 Total anchored Unanchored	171 98 93 94 117 76 88 107 69 125 90 99 101 1,328 3,646	73,966,406 65,258,067 63,950,047 62,276,720 60,231,642 60,016,944 59,096,273 58,208,991 56,972,541 53,706,612 51,080,163 49,533,500 30,412,479 744,710,385 14,054,600
We named the reassemble chromosome by its length order. The length of chromosome contained the 100 bp N between neighboring scaffolds.

Table 8: The statistics of the draft genome.
Parameters	Contigs length /bp	Scaffolds length /bp	Contigs number	Scaffolds number
Total Max_length Number>=2000bp N50 N60 N70 N80 N90	716,234,346 333,622 - 44,885 35,741 27,678 19,881 11,331	756,905,237 10,920,000 - 1,600,000 1,216,543 947,408 721,270 439,650	37,849 - 27,412 4,810 6,597 8,872 11,905 16,558	2,582 - 1,626 139 194 264 355 485
All of the statistics got rid of the short scaffolds (scaffold length < 1,000bp).

*Table 9: The statistics of the reassembled Gossypium raimondii* genome.**
Parameters	Contigs length /bp	Scaffolds length /bp	Contigs number	Scaffolds number
Total Max_length Number>=2000bp N50 N60 N70 N80 N90	716,283,110 333,622 - 44,885 35,740 27,675 19,873 11,327	757,086,669 73,966,406 - 60,016,944 58,208,991 56,972,541 53,706,612 49,533,500	37,921 - 27,412 4,810 6,598 8,874 11,907 16,562	1,329 - 462 6 8 9 10 12

All of the statistics got rid of the short scaffolds (scaffold length < 1,000bp).

Supplemental 2: The reassemble genome.

Supplemental file 2 was not provided with this version of the manuscript.

errorbin.bed.xls
Supplemental 1: Table of error bins.

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Improved Gossypium raimondii Genome Using a Hi-C-based Proximity-Guided Assembly

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Results

Discussion

Abbreviations

Declarations

References

Tables

Supplemental File 2

Supplementary Files

Status:

Journal Publication

Version 3