Finding Consensus on the Reference Genomes : A Chickpea Case Study

Q1 Agricultural and Biological Sciences Legume Science Pub Date : 2024-05-31 DOI:10.1002/leg3.224
P. Castro, A. Carmona, A. Perez-Rial, T. Millan, J. Rubio, J. Gil, J. V. Die
{"title":"Finding Consensus on the Reference Genomes : A Chickpea Case Study","authors":"P. Castro,&nbsp;A. Carmona,&nbsp;A. Perez-Rial,&nbsp;T. Millan,&nbsp;J. Rubio,&nbsp;J. Gil,&nbsp;J. V. Die","doi":"10.1002/leg3.224","DOIUrl":null,"url":null,"abstract":"<p>Chickpea (<i>Cicer arietinum</i> L.) is the second most important grain legume in the world, grown on about 15 million hectares worldwide. The 1990s marked a significant turning point in genetic research on chickpea. In 1991, researchers at Muenster University unveiled the mRNA sequence responsible for an isoflavone oxidoreductase, which was the first sequence available for this species (X60755; Genbank, NCBI). As the new century unfolded, the nucleotide database accumulated over 265 accessions for chickpea. The availability of these new sequences was closely linked to the development of genetic maps. Throughout the 1990s and early 2000s, numerous studies explored populations resulting from crosses between cultivated <i>C. arietinum</i> and wild-sampled accessions of <i>C. reticulatum</i> and <i>C. echinospermum</i> (Benko-Iseppon et al. <span>2003</span>; Gaur and Slinkard <span>1990</span>; Gaur and Stinkard <span>1990</span>; Kazan et al. <span>1993</span>; Pfaff and Kahl <span>2003</span>; Radhika et al. <span>2007</span>; Rakshit et al. <span>2003</span>; Ratnaparkhe, Tekeoglu, and Muehlbauer <span>1998</span>; Santra et al. <span>2000</span>; Simon and Muehibauer <span>1997</span>; Tekeoglu, Santra, et al. <span>2000</span>; Tekeoglu, Tullu, et al., <span>2000</span>; Tekeoglu, Rajesh, and Muehlbauer <span>2002</span>; Winter et al. <span>1999</span>, <span>2000</span>).</p><p>The following advance in genetic maps was represented by those primarily constructed using narrow crosses, focusing on two distinct chickpea types: “desi” and “kabuli”. Molecular markers had played a crucial role in uncovering that kabuli and desi types possessed contrasting genetic backgrounds (Chowdhury, Vandenberg, and Warkentin <span>2002</span>; Iruela et al. <span>2002</span>). As a result, the majority of genetic maps developed during this period were derived from crosses between kabuli and desi chickpea cultivars (Cho et al. <span>2002</span>; Cho, Chen, and Muehlbauer <span>2004</span>; Cobos et al. <span>2005</span>, <span>2007</span>; Iruela et al. <span>2006</span>, <span>2007</span>; Lichtenzveig et al. <span>2006</span>; Millan et al. <span>2003</span>; Sharma et al. <span>2004</span>; Tar'an et al. <span>2007</span>; Udupa and Baum <span>2003</span>).</p><p>The development of microsatellite markers (SSR) expedited the identification of markers closely linked to traits of interest (Choudhary et al. <span>2006</span>, <span>2009</span>; Hüttel et al. <span>1999</span>; Lichtenzveig et al. <span>2005</span>; Sethy, Choudhary, et al. <span>2006</span>; Sethy, Shokeen, et al. <span>2006</span>; Winter et al. <span>1999</span>). However, the valuable information and resources provided by these maps could only be fully utilized when direct comparisons were made using common SSR markers. Although the marker-linkage group assignments in different populations generally agreed, discrepancies between maps arose due to variations in population type and size, marker density at specific genomic regions of interest and software processing. These discrepancies hindered breeders' ability to select appropriate segregating plant materials containing desirable genes. In 2010, an international consortium of leading researchers constructed a consensus genetic map of chickpea based on multiple populations (Millan et al. <span>2010</span>). This consensus map became a valuable practical tool to assist breeders to accurately select suitable markers tightly linked to agronomically important genomic regions for marker-assisted selection.</p><p>Following the consensus genetic map, the first completion of the chickpea genome sequencing (CDC Frontier, a kabuli type) was released in 2013 (Varshney et al. <span>2013</span>). The scientific breakthrough was announced by political representatives of the Indian government (Varshney <span>2016</span>). Using illumina technology, 87.65-Gb of high-quality sequence data were assembled into 530-Mb of genomic sequence scaffolds representing 74% of 740-Mb chickpea genome. More than 25 K out of 28 K non-redundant predicted gene models could be functionally annotated. Since then, the NCBI assembly GCF_000331145.1 has become the de facto reference genome for the kabuli genotype (Jain et al. <span>2022</span>). In another effort to sequence the chickpea genome, ICC4958 (desi genotype) was targeted for generating a draft genome assembly using NGS platforms along with BAC end sequences and a genetic map (Jain et al. <span>2013</span>). Shortly after, an improved version of cultivar ICC 4958 with 2.7-fold increase in the length of pseudomolecules was reported (Parween et al. <span>2015</span>). The desi assembly is currently available in GenBank under the accession ASM34727v4.</p><p>However, after these important achievements, other improved and curated sequences have become available, but the hosting of these sequences is outside the NCBI reference database. Thus, based on the analysis of recombination patterns, the kabuli genome was improved (Bayer et al. <span>2015</span>) and made available in 2016 in the repository <i>CyVerse Data Commons</i>, (dataset Kabuli_UWA-v.2.6.3; Edwards <span>2016</span>). More recently, using in situ Hi-C data, an improved chromosome-length genome assembly of chickpea was developed. The dataset is available under Cicar.CDCFrontier_v2.0 in the online repository <i>Legumepedia</i> (Garg et al. <span>2022</span>).</p><p>There is no doubt that the availability of several genomes will have a massive impact in a variety of ways, including diversity assessment, genome structure validation, and gene–trait association. One of the overwhelming uses of genomes is in the availability of high-density molecular markers which can be used to quickly map agronomically desirable traits and to identify candidate genes within a region of interest. The issue, however, emerges when different results are shown based solely on the specific genome sequences each research group employs. Variations in the sequence of a genome can lead to substantial differences in the organization of genetic information. For example, GWAS analyses may reveal the existence of SNPs in significant <i>loci</i>. An insightful approach involves examining the gene expression profiles of genes located in the vicinity of these identified <i>loci</i>. Such an analysis can shed light on the functional roles of these genes, demonstrating their potential as modulators of specific traits. However, when variations in a genomic sequence are solely based on different sequence versions, the notion of mapping genes to the vicinity of a <i>locus</i>, the promoter sequences analysis, or the identification of cis-acting variants, may lose its biological relevance, ultimately yielding misleading results (Figure 1).</p><p>In essence, this situation replicates the problem encountered in the 1990s with genetic maps, where findings were not readily transferable between studies. It is not uncommon for reviewers of present-day scientific manuscripts to inquire about the choice of one genome sequence over another. In our latest study, we successfully identified genomic blocks associated with Ascochyta blight resistance utilizing the reference CDC Frontier. During the peer-review process, we were requested to employ a different sequence as the reference, necessitating us to map the markers from one sequence to another (Carmona et al. <span>2023</span>). It is our opinion that the selection of a reference sequence should not be left to the discretion of reviewers, editors, or even researchers. The NCBI Reference Sequence Database offers a comprehensive, integrated, non-redundant, and generally well-annotated collection of reference sequences. Occasionally, even when an improved version is released, raw data supporting the new assemblies may be accessible as a BioProject in NCBI. Moreover, certain repositories hosting the new assemblies provide useful analytical resources such as BLAST, which serves as NCBI's flagship alignment tool. The question is: Would it not be beneficial to have the improved versions of genomes available on NCBI itself? The centralized availability of sequences would provide us with convenient updates on the latest genome versions, eliminating the need to navigate through multiple web pages or become familiar with the local setting tools of individual repositories.</p><p>The selection of the reference is open to discussion. There are several forums where this meeting could take place. Both, the International Legume Society Conference and the International Congress on Legume Genetics and Genomics, with a mission to bring together scientists who work on research aspects of legume biology using genetic and genomic tools, with those working on applied aspects and breeding of crop and pasture species is an excellent opportunity for this debate to reach a conclusion. However, the debate must be addressed by the research community in advance in an open and constructive way. Plant breeding is an ever-evolving scientific field, constantly adapting to the advancements in technology. The emergence of genomics and the availability of genome sequences have proven to be an invaluable asset to plant breeders, empowering them to harness the vast diversity of plant species. A well-established pipeline, supported by widely accepted tools and genome references, enables the development of novel cultivars with enhanced traits. This equips us to effectively tackle both current and future challenges.</p><p><b>P. Castro:</b> Conceptualization; Writing – original draft; Writing – review and editing. <b>A. Carmona:</b> Conceptualization; Formal analysis; Writing – review and editing. <b>A. Perez-Rial:</b> Conceptualization; Writing – review and editing. <b>T. Millan:</b> Conceptualization; Writing – review and editing. <b>J. Rubio:</b> Conceptualization; Funding acquisition; Writing – review and editing. <b>J. Gil:</b> Conceptualization; Writing – review and editing. <b>J. V. Die:</b> Conceptualization; Funding acquisition; Writing – original draft; Writing – review and editing.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":17929,"journal":{"name":"Legume Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/leg3.224","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Legume Science","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/leg3.224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 0

Abstract

Chickpea (Cicer arietinum L.) is the second most important grain legume in the world, grown on about 15 million hectares worldwide. The 1990s marked a significant turning point in genetic research on chickpea. In 1991, researchers at Muenster University unveiled the mRNA sequence responsible for an isoflavone oxidoreductase, which was the first sequence available for this species (X60755; Genbank, NCBI). As the new century unfolded, the nucleotide database accumulated over 265 accessions for chickpea. The availability of these new sequences was closely linked to the development of genetic maps. Throughout the 1990s and early 2000s, numerous studies explored populations resulting from crosses between cultivated C. arietinum and wild-sampled accessions of C. reticulatum and C. echinospermum (Benko-Iseppon et al. 2003; Gaur and Slinkard 1990; Gaur and Stinkard 1990; Kazan et al. 1993; Pfaff and Kahl 2003; Radhika et al. 2007; Rakshit et al. 2003; Ratnaparkhe, Tekeoglu, and Muehlbauer 1998; Santra et al. 2000; Simon and Muehibauer 1997; Tekeoglu, Santra, et al. 2000; Tekeoglu, Tullu, et al., 2000; Tekeoglu, Rajesh, and Muehlbauer 2002; Winter et al. 1999, 2000).

The following advance in genetic maps was represented by those primarily constructed using narrow crosses, focusing on two distinct chickpea types: “desi” and “kabuli”. Molecular markers had played a crucial role in uncovering that kabuli and desi types possessed contrasting genetic backgrounds (Chowdhury, Vandenberg, and Warkentin 2002; Iruela et al. 2002). As a result, the majority of genetic maps developed during this period were derived from crosses between kabuli and desi chickpea cultivars (Cho et al. 2002; Cho, Chen, and Muehlbauer 2004; Cobos et al. 2005, 2007; Iruela et al. 2006, 2007; Lichtenzveig et al. 2006; Millan et al. 2003; Sharma et al. 2004; Tar'an et al. 2007; Udupa and Baum 2003).

The development of microsatellite markers (SSR) expedited the identification of markers closely linked to traits of interest (Choudhary et al. 2006, 2009; Hüttel et al. 1999; Lichtenzveig et al. 2005; Sethy, Choudhary, et al. 2006; Sethy, Shokeen, et al. 2006; Winter et al. 1999). However, the valuable information and resources provided by these maps could only be fully utilized when direct comparisons were made using common SSR markers. Although the marker-linkage group assignments in different populations generally agreed, discrepancies between maps arose due to variations in population type and size, marker density at specific genomic regions of interest and software processing. These discrepancies hindered breeders' ability to select appropriate segregating plant materials containing desirable genes. In 2010, an international consortium of leading researchers constructed a consensus genetic map of chickpea based on multiple populations (Millan et al. 2010). This consensus map became a valuable practical tool to assist breeders to accurately select suitable markers tightly linked to agronomically important genomic regions for marker-assisted selection.

Following the consensus genetic map, the first completion of the chickpea genome sequencing (CDC Frontier, a kabuli type) was released in 2013 (Varshney et al. 2013). The scientific breakthrough was announced by political representatives of the Indian government (Varshney 2016). Using illumina technology, 87.65-Gb of high-quality sequence data were assembled into 530-Mb of genomic sequence scaffolds representing 74% of 740-Mb chickpea genome. More than 25 K out of 28 K non-redundant predicted gene models could be functionally annotated. Since then, the NCBI assembly GCF_000331145.1 has become the de facto reference genome for the kabuli genotype (Jain et al. 2022). In another effort to sequence the chickpea genome, ICC4958 (desi genotype) was targeted for generating a draft genome assembly using NGS platforms along with BAC end sequences and a genetic map (Jain et al. 2013). Shortly after, an improved version of cultivar ICC 4958 with 2.7-fold increase in the length of pseudomolecules was reported (Parween et al. 2015). The desi assembly is currently available in GenBank under the accession ASM34727v4.

However, after these important achievements, other improved and curated sequences have become available, but the hosting of these sequences is outside the NCBI reference database. Thus, based on the analysis of recombination patterns, the kabuli genome was improved (Bayer et al. 2015) and made available in 2016 in the repository CyVerse Data Commons, (dataset Kabuli_UWA-v.2.6.3; Edwards 2016). More recently, using in situ Hi-C data, an improved chromosome-length genome assembly of chickpea was developed. The dataset is available under Cicar.CDCFrontier_v2.0 in the online repository Legumepedia (Garg et al. 2022).

There is no doubt that the availability of several genomes will have a massive impact in a variety of ways, including diversity assessment, genome structure validation, and gene–trait association. One of the overwhelming uses of genomes is in the availability of high-density molecular markers which can be used to quickly map agronomically desirable traits and to identify candidate genes within a region of interest. The issue, however, emerges when different results are shown based solely on the specific genome sequences each research group employs. Variations in the sequence of a genome can lead to substantial differences in the organization of genetic information. For example, GWAS analyses may reveal the existence of SNPs in significant loci. An insightful approach involves examining the gene expression profiles of genes located in the vicinity of these identified loci. Such an analysis can shed light on the functional roles of these genes, demonstrating their potential as modulators of specific traits. However, when variations in a genomic sequence are solely based on different sequence versions, the notion of mapping genes to the vicinity of a locus, the promoter sequences analysis, or the identification of cis-acting variants, may lose its biological relevance, ultimately yielding misleading results (Figure 1).

In essence, this situation replicates the problem encountered in the 1990s with genetic maps, where findings were not readily transferable between studies. It is not uncommon for reviewers of present-day scientific manuscripts to inquire about the choice of one genome sequence over another. In our latest study, we successfully identified genomic blocks associated with Ascochyta blight resistance utilizing the reference CDC Frontier. During the peer-review process, we were requested to employ a different sequence as the reference, necessitating us to map the markers from one sequence to another (Carmona et al. 2023). It is our opinion that the selection of a reference sequence should not be left to the discretion of reviewers, editors, or even researchers. The NCBI Reference Sequence Database offers a comprehensive, integrated, non-redundant, and generally well-annotated collection of reference sequences. Occasionally, even when an improved version is released, raw data supporting the new assemblies may be accessible as a BioProject in NCBI. Moreover, certain repositories hosting the new assemblies provide useful analytical resources such as BLAST, which serves as NCBI's flagship alignment tool. The question is: Would it not be beneficial to have the improved versions of genomes available on NCBI itself? The centralized availability of sequences would provide us with convenient updates on the latest genome versions, eliminating the need to navigate through multiple web pages or become familiar with the local setting tools of individual repositories.

The selection of the reference is open to discussion. There are several forums where this meeting could take place. Both, the International Legume Society Conference and the International Congress on Legume Genetics and Genomics, with a mission to bring together scientists who work on research aspects of legume biology using genetic and genomic tools, with those working on applied aspects and breeding of crop and pasture species is an excellent opportunity for this debate to reach a conclusion. However, the debate must be addressed by the research community in advance in an open and constructive way. Plant breeding is an ever-evolving scientific field, constantly adapting to the advancements in technology. The emergence of genomics and the availability of genome sequences have proven to be an invaluable asset to plant breeders, empowering them to harness the vast diversity of plant species. A well-established pipeline, supported by widely accepted tools and genome references, enables the development of novel cultivars with enhanced traits. This equips us to effectively tackle both current and future challenges.

P. Castro: Conceptualization; Writing – original draft; Writing – review and editing. A. Carmona: Conceptualization; Formal analysis; Writing – review and editing. A. Perez-Rial: Conceptualization; Writing – review and editing. T. Millan: Conceptualization; Writing – review and editing. J. Rubio: Conceptualization; Funding acquisition; Writing – review and editing. J. Gil: Conceptualization; Writing – review and editing. J. V. Die: Conceptualization; Funding acquisition; Writing – original draft; Writing – review and editing.

The authors declare no conflicts of interest.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
就参考基因组达成共识:蚕豆案例研究
鹰嘴豆(Cicer arietinum L.)是世界上第二重要的谷物豆类,全球种植面积约 1500 万公顷。20 世纪 90 年代是鹰嘴豆遗传研究的一个重要转折点。1991 年,明斯特大学的研究人员公布了负责异黄酮氧化还原酶的 mRNA 序列,这是该物种的第一个可用序列(X60755;Genbank,NCBI)。进入新世纪后,核苷酸数据库积累了超过 265 个鹰嘴豆序列。这些新序列的出现与遗传图谱的发展密切相关。在整个 20 世纪 90 年代和 21 世纪初,许多研究探索了栽培鹰嘴豆与 C. reticulatum 和 C. echinospermum 的野生取样杂交产生的种群(Benko-Iseppon et al.2003;Gaur 和 Slinkard,1990;Gaur 和 Stinkard,1990;Kazan 等人,1993;Pfaff 和 Kahl,2003;Radhika 等人,2007;Rakshit 等人,2003;Ratnaparkhe、Tekeoglu 和 Muehlbauer,1998;Santra 等人,2000;Simon 和 Muehibauer,1997;Tekeoglu、Santra 等人,2000;Tekeoglu、Tullu 等人,2000;Tekeoglu、Raj 和 Kahl,2000;Tekeoglu、Raj 和 Kahl,2000;Tekeoglu、Raj 和 Kahl,2000、随后,遗传图谱的进展主要体现在利用狭窄杂交构建的图谱上,主要集中在两种不同的鹰嘴豆类型上:"desi "和 "kaba":随后,遗传图谱的进展主要体现在利用狭窄杂交构建的图谱上,主要针对两种不同的鹰嘴豆类型:"desi "和 "kabuli"。分子标记在揭示 kabuli 和 desi 类型具有不同遗传背景方面发挥了关键作用(Chowdhury、Vandenberg 和 Warkentin,2002 年;Iruela 等人,2002 年)。因此,在此期间开发的大部分基因图谱都来自 kabuli 和 desi 鹰嘴豆栽培品种之间的杂交(Cho 等人,2002 年;Cho、Chen 和 Muehlbauer,2004 年;Cobos 等人,2005 年,2007 年;Iruela 等人,2006 年,2007 年;Lichtenzveig 等人,2006 年;Millan 等人,2003 年;Sharma 等人,2004 年;Tar'an 等人,2007 年;Udupa 和 Bailey,2007 年)。微卫星标记(SSR)的开发加快了与感兴趣的性状密切相关的标记的鉴定(Choudhary 等人,2006 年,2009 年;Hüttel 等人,1999 年;Lichtenzveig 等人,2005 年;Sethy, Choudhary 等人,2006 年;Sethy, Shokeen 等人,2006 年;Winter 等人,1999 年)。然而,只有使用常见的 SSR 标记进行直接比较,才能充分利用这些图谱提供的宝贵信息和资源。虽然不同种群的标记连接组分配基本一致,但由于种群类型和大小、特定基因组感兴趣区域的标记密度以及软件处理等方面的差异,不同图谱之间也存在差异。这些差异阻碍了育种者选择含有理想基因的适当分离植物材料的能力。2010 年,一个由顶尖研究人员组成的国际联盟根据多个种群构建了鹰嘴豆的共识遗传图谱(Millan 等,2010 年)。继共识遗传图谱之后,首个鹰嘴豆基因组测序完成品(CDC Frontier,一种卡布利类型)于 2013 年发布(Varshney 等,2013 年)。印度政府的政治代表宣布了这一科学突破(Varshney,2016 年)。利用 illumina 技术,87.65-GB 的高质量序列数据被组装成 530-Mb 的基因组序列支架,占 740-Mb 鹰嘴豆基因组的 74%。在 28 K 个非冗余预测基因模型中,超过 25 K 个可以进行功能注释。此后,NCBI GCF_000331145.1 汇编成为卡布利基因型的实际参考基因组(Jain 等,2022 年)。在鹰嘴豆基因组测序的另一项工作中,ICC4958(desi 基因型)成为利用 NGS 平台以及 BAC 末端序列和遗传图谱生成基因组组装草案的目标(Jain 等人,2013 年)。不久之后,假分子长度增加 2.7 倍的 ICC 4958 栽培品种改良版被报道(Parween 等,2015 年)。然而,在取得这些重要成就之后,其他改良和编辑的序列也陆续问世,但这些序列的托管却在 NCBI 参考数据库之外。因此,基于对重组模式的分析,kabuli基因组得到了改进(Bayer等人,2015年),并于2016年在CyVerse数据共享库中提供(数据集Kabuli_UWA-v.2.6.3;Edwards,2016年)。最近,利用原位 Hi-C 数据,开发了改进的鹰嘴豆染色体组长基因组组装。毫无疑问,多个基因组的可用性将在多样性评估、基因组结构验证和基因-性状关联等多个方面产生巨大影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Legume Science
Legume Science Agricultural and Biological Sciences-Plant Science
CiteScore
7.90
自引率
0.00%
发文量
32
审稿时长
6 weeks
期刊最新文献
Cooking Time, Seed Darkening, and Iron and Zinc Concentrations of Selected Andean Genotypes of Common Bean The Potential Application of Mung Bean (Vigna radiata L.) Protein in Plant-Based Food Analogs: A Review Growth, Yield and Grain Quality of Cowpea (Vigna unguiculata (L.) Walp.) and Weed Flora as Affected by Physical and Chemical Methods of Weed Control Unveiling Phenotypic and Environmental Dynamics: Exploring Genetic Stability and Adaptability of Faba Bean Cultivars in Norwegian Climates Genetic Analysis for Seed Yield and Yield-Related Traits in Tepary Bean (Phaseolus acutifolius A. Gray) Under Drought-Stress and Non-stress Conditions
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1