Enabling food security requires access to a broad range of genetic resources to facilitate crop breeding. This need is increased in a climate change scenario, which will require the production of novel crops adapted to new conditions. However, many major crops have reduced genetic diversity due to the genetic bottlenecks that they have experienced during their domestication and subsequent breeding. Crop wild relatives (CWRs) remain underexploited in plant breeding programmes, mostly because of the lack of knowledge of their cross-compatibility with crops. In this study, we use a combination of phylogenetic distance metrics, cytogenetic compatibility data (e.g. chromosome number and ploidy) and information about breeding systems to predict interspecific cross-compatibility between crop and wild species and hence identify crop wild phylorelatives (CWPs) (i.e. CWRs that can breed with the crop). We illustrate this concept using cultivated asparagus as a model by integrating previous cross-compatibility knowledge and CWR classifications into a phylogenetic framework reconstructed using available sequence data. Our approach aims to reinforce the use of the gene pool classification system of CWRs of Harlan and De Wet, since CWPs are estimated to belong to the secondary gene pool and non-CWPs to the tertiary gene pool. Identifying CWPs unlocks novel uses of genetic resources, although such data are available for less than half of the known CWRs (43.4% with sequence data and 32.5% with known ploidy). The need to conserve plants that provide or enhance provisioning ecosystem services, including CWRs, is clear if we are to rise to the global challenge of ensuring food security for all. However, basic knowledge about their conservation status is still lacking, with only c. 20% of CWRs assigned an IUCN red list assessment, 23% of which are Data Deficient (DD). Using the CWP classification presented here to define CWRs will contribute towards helping to prioritize CWRs for IUCN assessments and, where prioritised, conservation.

中文翻译：

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作物野生亲缘种（CWP）：系统发生距离，细胞遗传相容性和育种系统数据可估算作物野生相对基因库分类

实现粮食安全需要获取广泛的遗传资源，以促进作物育种。在气候变化的情况下，这种需求增加了，这将需要生产适应新条件的新型农作物。但是，由于许多主要农作物在驯化和随后的育种过程中遇到了遗传瓶颈，因此遗传多样性降低了。作物野生亲缘种（CWR）在植物育种计划中仍未得到充分利用，这主要是由于缺乏对它们与作物交叉兼容性的了解。在这项研究中，我们结合了系统发育距离指标，细胞遗传相容性数据（例如 染色体数目和倍性）以及有关育种系统的信息，以预测作物和野生物种之间的种间交叉兼容性，从而确定作物野生的亲缘种（CWP）（即可以随作物繁殖的CWR）。我们通过将以前的交叉兼容性知识和CWR分类整合到使用可用序列数据重建的系统发育框架中，来说明使用栽培芦笋作为模型的这一概念。我们的方法旨在加强对Harlan和De Wet CWR的基因库分类系统的使用，因为估计CWP属于二级基因库，而非CWP属于第三级基因库。鉴定CWP可以解锁遗传资源的新用途，尽管此类数据可用于不到一半的已知CWR（序列数据为43.4％，已知倍性为32.5％）。如果我们要应对确保所有人的粮食安全的全球挑战，那么保护提供或增强供应生态系统服务的工厂（包括CWR）的需求就很明显。但是，仍然缺乏关于其保护状况的基本知识，只有c。20％的CWR分配了IUCN红色清单评估，其中23％是数据不足（DD）。使用此处介绍的CWP分类来定义CWR，将有助于帮助为IUCN评估和（在优先考虑的情况下）保护确定CWR的优先级。