Zatybekov Alibek, Abugalieva Saule, Didorenko Svetlana, Gerasimova Yelena, Sidorik Ivan, Anuarbek Shynar, Turuspekov Yerlan
Institute of Plant Biology and Biotechnology, Almaty, Kazakhstan, 050040.
Kazakh Research Institute of Agriculture, Almalybak vil., Almaty region, Kazakhstan, 040909.
BMC Plant Biol. 2017 Nov 14;17(Suppl 1):179. doi: 10.1186/s12870-017-1125-0.
In recent years soybean is becoming one of the most important oilseed crops in Kazakhstan. Only within the last ten years (2006-2016), the area under soybean is expanded from 45 thousand hectares (ha) in 2006 to 120 thousand ha in 2016. The general trend of soybean expansion is from south-eastern to eastern and northern regions of the country, where average temperatures are lower and growing seasons are shorter. These new soybean growing territories were poorly examined in terms of general effects on productivity level among the diverse sample of soybean accessions. In this study, phenotypic data were collected in three separate regions of Kazakhstan and entire soybean sample was genotyped for identification of marker-trait associations (MTA).
In this study, the collection of 113 accessions representing five different regions of the World was planted in 2015-2016 in northern, eastern, and south-eastern regions of Kazakhstan. It was observed that North American accessions showed the highest yield in four out of six trials especially in Northern Kazakhstan in both years. The entire sample was genotyped with 6 K SNP Illumina array. 4442 SNPs found to be polymorphic and were used for whole genome genotyping purposes. Obtained SNP markers data and field data were used for GWAS (genome-wide association study). 30 SNPs appear to be very significant in 42 MTAs in six studied environments.
The study confirms the efficiency of GWAS for the identification of molecular markers which tag important agronomic traits. Overall thirty SNP markers associated with time to flowering and maturation, plant height, number of fertile nodes, seeds per plant and yield were identified. Physical locations of 32 identified out of 42 total MTAs coincide well with positions of known analogous QTLs. This result indicates importance of revealed MTAs for soybean growing regions in Kazakhstan. Obtained results would serve as required prerequisite for forming and realization of specific breeding programs towards effective adaptation and increased productivity of soybean in three different regions of Kazakhstan.
近年来,大豆正成为哈萨克斯坦最重要的油料作物之一。仅在过去十年(2006 - 2016年)间,大豆种植面积就从2006年的4.5万公顷扩大到2016年的12万公顷。大豆种植区域扩张的总体趋势是从该国东南部向东部和北部地区,这些地区平均气温较低且生长季节较短。就大豆不同种质对生产力水平的总体影响而言,这些新的大豆种植区域尚未得到充分研究。在本研究中,在哈萨克斯坦的三个不同地区收集了表型数据,并对整个大豆样本进行基因分型以鉴定标记 - 性状关联(MTA)。
在本研究中,2015 - 2016年在哈萨克斯坦的北部、东部和东南部地区种植了代表世界五个不同地区的113份种质。观察到北美种质在六个试验中的四个试验中产量最高,特别是在哈萨克斯坦北部的两年试验中。使用Illumina 6K SNP芯片对整个样本进行基因分型。发现4442个SNP具有多态性,并用于全基因组基因分型。获得的SNP标记数据和田间数据用于全基因组关联研究(GWAS)。在六个研究环境中的42个MTA中,有30个SNP显得非常显著。
该研究证实了GWAS在鉴定标记重要农艺性状的分子标记方面的有效性。总体而言,鉴定出了与开花和成熟时间、株高、有效节数、单株种子数和产量相关的30个SNP标记。在总共42个MTA中鉴定出的32个的物理位置与已知类似QTL的位置非常吻合。这一结果表明所揭示的MTA对哈萨克斯坦大豆种植区的重要性。获得的结果将作为在哈萨克斯坦三个不同地区制定和实施针对大豆有效适应和提高生产力的特定育种计划的必要前提条件。