Hailong Ning

Prof. Hailong Ning

Northeast Agricultural University
orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 November 2018 in Frontiers in Plant Science
Verified
Journal Article
Open access
PDF file
KZKaixin Zhang
Kaixin Zhang
SLShulin Liu
Shulin Liu
WLWenbin Li
Wenbin Li
SLShiping Liu
Shiping Liu
XLXiyu Li
Xiyu Li
Hailong NingHailong Ning
Hailong Ning
Protein content (PC), an important trait in soybean (Glycine max) breeding, is controlled by multiple genes with relatively small effects. To identify the quantitative trait nucleotides (QTNs) controlling PC, we conducted a multi-locus genome-wide association study (GWAS) for PC in 144 four-way recombinant inbred lines (FW-RILs). All the FW-RILs were phenotyped for PC in 20 environments, including four locations over 4 years with different experimental treatments. Meanwhile, all the FW-RILs were genotyped using SoySNP660k BeadChip, producing genotype data for 109,676 non-redundant single-nucleotide polymorphisms. A total of 129 significant QTNs were identified by five multi-locus GWAS methods. Based on the 22 common QTNs detected by multiple GWAS methods or in multiple environments, pathway analysis identified 8 potential candidate genes that are likely to be involved in protein synthesis and metabolism in soybean seeds. Using superior allele information for 22 common QTNs in 22 elite and 7 inferior lines, we found higher superior allele percentages in the elite lines and lower percentages in the inferior lines. These findings will contribute to the discovery of the polygenic networks controlling PC in soybean, increase our understanding of the genetic foundation and regulation of PC, and be useful for molecular breeding of high-protein soybean varieties.

16 July 2020 in Frontiers in Genetics
Verified
Journal Article
Open access
PDF file
ZQZhongying Qi
Zhongying Qi
JSJie Song
Jie Song
KZKaixin Zhang
Kaixin Zhang
SLShulin Liu
Shulin Liu
XTXiaocui Tian
Xiaocui Tian
Hailong NingHailong Ning
Hailong Ning
Hundred-seed weight (HSW) is an important measure of yield and a useful indicator to monitor the inheritance of quantitative traits affected by genotype and environmental conditions. To identify quantitative trait nucleotides (QTNs) and mine genes useful for breeding high-yielding and high-quality soybean (Glycine max) cultivars, we conducted a multilocus genome-wide association study (GWAS) on HSW of soybean based on phenotypic data from 20 different environments and genotypic data for 109,676 single-nucleotide polymorphisms (SNPs) in 144 four-way recombinant inbred lines. Using five multilocus GWAS methods, we identified 118 QTNs controlling HSW. Among these, 31 common QTNs were detected by various methods or across multiple environments. Pathway analysis identified three potential candidate genes associated with HSW in soybean. We used allele information to study the common QTNs in 20 large-seed and 20 small-seed lines and identified a higher percentage of superior alleles in the large-seed lines than in small-seed lines. These observations will contribute to construct the gene networks controlling HSW in soybean, which can improve the genetic understanding of HSW, and provide assistance for molecular breeding of soybean large-seed varieties.

14 February 2020 in Frontiers in Plant Science
Verified
Journal Article
Open access
PDF file
YFYanlong Fang
Yanlong Fang
SLShulin Liu
Shulin Liu
QDQuanzhong Dong
Quanzhong Dong
KZKaixin Zhang
Kaixin Zhang
ZTZhixi Tian
Zhixi Tian
Hailong NingHailong Ning
Hailong Ning
Plant height is an important target for soybean breeding. It is a typical quantitative trait controlled by multiple genes and is susceptible to environmental influences. Here, we carried out phenotypic analysis of 156 recombinant inbred lines derived from “Dongnong L13” and “Henong 60” in nine environments at four locations over 6 years using interval mapping and inclusive composite interval mapping methods. We performed quantitative trait locus (QTL) analysis by applying pre-built simple-sequence repeat maps. We detected 48 QTLs, including nine significant QTLs detected by multiple methods and in multiple environments. Meanwhile, genotyping of all lines using the SoySNP660k BeadChip produced 54,836 non-redundant single-nucleotide polymorphism (SNP) genotypes. We used five multi-locus genome-wide association analysis methods to locate 10 quantitative trait nucleotides (QTNs), four of which overlap with previously located QTLs. Five candidate genes related to plant height are predicted to lie within 200 kb of these four QTNs. We identified 19 homologous genes in Arabidopsis, two of which may be associated with plant height. These findings further our understanding of the multi-gene regulatory network and genetic determinants of soybean plant height, which will be important for breeding high-yielding soybean.

15 June 2020 in Molecular Breeding
Verified
Journal Article
Closed access
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JSJie Song
Jie Song
SSSun Sun
Sun Sun
KZKaixin Zhang
Kaixin Zhang
SLShulin Liu
Shulin Liu
JWJiajing Wang
Jiajing Wang
Hailong NingHailong Ning
Hailong Ning

1 January 2021 in Biotechnology & Biotechnological Equipment
Verified
Journal Article
Open access
GHGuofu Hu
Guofu Hu
BWBo Wang
Bo Wang
TGTing Gong
Ting Gong
RLRan Li
Ran Li
XGXin Guo
Xin Guo
Hailong NingHailong Ning
Hailong Ning
Soybean plants have high protein content and can be used as a supplementary source of high-protein feed. To map quantitative trait loci (QTL) for the content of crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF) and dry weight of plant (DWP) in R2 stage of soybean, two recombinant inbred lines, RIL3613 and RIL6013, containing 134 and 156 RILs, derived from the cross of Dongnong L13 × Heihe 36 and Dongnong L13 × Henong 60, were planted for two consecutive years. Based on a simple sequence repeat (SSR) linkage map, QTLs of CP, NDF, ADF and DWP were mapped by interval mapping (IM) and inclusive composite interval mapping method (ICIM) using additive effect, epistatic effect and environmental interaction model. The variance components of genotype, environment and genotype × environment (G × E) interaction for quality and yield traits in the two RIL populations were significant under multiple environmental conditions. Eighteen additive effect QTLs on 10 of 20 soybean chromosomes explained 7.02%–15.67% and 2.13%–11.42% of the phenotypic variation in RIL3613 and RIL6013, respectively. Three epistatic QTL pairs related to CP and six ones for DWP were identified. Eight additive effect QTLs for CP, eight ones for NDF, three ones for ADF, and another three ones for DWP were identified by genotype × environment interaction analysis. One epistatic QTL for CP, 11 epistatic QTL pairs for ADF and 38 ones for NDF were identified. These results can provide better understanding of the genetic basis of soybean feed quality and yield.

9 January 2021 in Theoretical and Applied Genetics
Verified
Journal Article
Closed access
PDF file
XLXiyu Li
Xiyu Li
PWPing Wang
Ping Wang
KZKaixin Zhang
Kaixin Zhang
SLShulin Liu
Shulin Liu
ZQZhongying Qi
Zhongying Qi
Hailong NingHailong Ning
Hailong Ning