粳稻蒸煮食味品质相关性状的QTL分析

以沈农265和丽江新团黑谷杂交衍生的重组自交系群体(RILs)为实验材料,对12个粳稻(Oryza sativa subsp.japonica)蒸煮食味品质相关性状进行QTL分析。共检测到29个蒸煮食味品质相关的QTLs,分布于除第8染色体外的11条染色体上,LOD值介于2.50–16.47之间,加性效应值为–132.69–471.85,单个QTL贡献率为10.36%–73.24%。在第6染色体RM508–RM253区域检测到1个蒸煮营养食味品质多效性QTL簇,其中q AC6表型贡献率最大,解释73.24%的表型变异;在第10染色体PM166–RM258区域检测到2个与蒸煮食味品质相关的QTLs,分别是控制口感的q CTS10和综合评分的q CCS10。此外,检测到15个与RVA特征谱相关的QTLs,在第6染色体RM253–RM402区域检测到3个与RVA谱特征值相关的QTLs,表型贡献率均大于12%。这些定位结果将为粳稻蒸煮食味相关品质的分子遗传机理研究奠定基础。     

水稻幼苗中胚轴长度QTL及与Fe2+浓度的互作效应的遗传分析

应用珍汕97B/密阳46的RIL群体及其构建的分子连锁图谱,在4个浓度的FeSO4处理下发芽,测定中胚轴长度。采用QTLMapper基因定位软件检测控制中胚轴长度的加性效应QTLs和加性×加性上位性QTLs,分别在1、2、3、4、5、6、7、8、9、11、12等染色体上定位了27个控制中胚轴长度的QTLs,其中在第1、5、9等3条染色体上定位了6个具有加性效应的QTLs。在CK和FeSO41.79mmol/L浓度下,在第5染色体长臂相邻区间检测到1个加性效应QTL,其增效等位基因来自于父本密阳46,它能使中胚轴伸长0.042cm(CK)、0.172cm(1.79mmol/L),贡献率分别为4.3%和11.4%;在高浓度FeSO4(7.16mmol/L和14.32mmol/L)下分别在1、5、9染色体上检测到的4个加性效应QTL,贡献率为3.5%～10.4%,3个QTL中来自于母本珍汕97B的等位基因使中胚轴伸长0.024～0.046cm,1个QTL来自父本的增效等位基因使中胚轴伸长0.033cm。同时在第5染色体长臂上检测到具有显著的加性效应与Fe2 互作效应的QTL1个。     

水稻叶片性状和根系活力的QTL定位

应用由247个株系组成的珍汕97B/密阳46重组自交系(RIL)群体及其分子标记连锁图谱,检测控制剑叶、倒二叶、倒三叶的5个形态性状和控制根系伤流量性状的数量性状座位(QTL)。在9个标记区间检测到控制叶片形态性状的24个QTL,LOD值为2．9～11．8,单个QTL的表型变异贡献率为4．0％～32．5％;分别检测到56对和4对控制叶片形态和根系活力的上位性互作,绝大多数互作发生在2个不表现加性效应的座位之间。与该群体产量性状QTL的研究结果相比较,发现控制叶片性状和根系活力的QTL与产量性状QTL往往处于相似的染色体区间。     

云南元江普通野生稻株高和抽穗期QTL定位研究

以云南元江普通野生稻为供体亲本,在特青的遗传背景下构建了一套BC3高代回交群体。利用117个SSR标记分析383个BC3F2株系的基因型,采用单标记分析法对控制元江普野株高和抽穗期的QTL进行分析。在北京和合肥两个地点试验结果表明,控制株高的QTL分布在第1染色体上,在RM104附近有一个QTL,与sd-1位置相当,其对表现型变异的贡献率在两个地点分别为27％和28％,其加性效应值分别为26．24cm和26．28cm,来自野生稻的等位基因显著提高回交群体的株高;在第1、3、7、8、11染色体共检测到6个控制抽穗期QTL,其中第8染色体RM25附近控制抽穗期的QTL在两个地点的贡献率分别为13％和15％,加性效应值为4．60d和3．65d,来自野生稻的等位基因使回交群体抽穗期延迟。     

水稻耐亚铁毒QTLs的定位

亚铁毒是潜育性水稻土中限制水稻产量的主要因子。利用龙杂8503／IR64的F2和等价的F3群体,在营养液中培养来定位耐亚铁毒的QTLs。通过构建101SSR标记的遗传连锁图谱来确定耐亚铁毒QTLs的位置和特性。借助叶片棕色斑点指数、株高和最大根长3个性状,利用营养液在水稻苗期来评价F2单株、F3群体和亲本龙杂8503、IR64,共检测到叶片棕色斑点指数、株高和最大根长的QTLs20个,分布在水稻的10条染色体上,表明这些性状受多基因控制。控制叶片棕色斑点指数的QTLs分别定位在第1染色体的RM315-RM212、第2染色体的RM6-RM240和第4染色体的RM252-RM451之间。与前人的研究结果比较发现：1）位于第4染色体RM252-RM451之间的控制叶片棕色斑点指数的QTL与水稻功能图谱上控制叶绿素含量减少的QTL的位置一致。另一个位于第1染色体的RM315-RM212之间的控制叶片棕色斑点指数的QTL与水稻功能图谱上位于C178-R2635之间控制叶绿素含量的QTL连锁。2）位于第2染色体RM6-RM240之间的第3个控制叶片棕色斑点指数的QTL与位于RZ58-CD0686的控制钾吸收的QTL连锁。     

大白菜部分形态性状的QTL定位与分析

应用352个标记位点的大白菜AFLP和RAPD图谱和一套栽培品种间杂交获得的重组自交系群体,采用复合区间作图的方法对大白菜9个形态性状进行QTL定位及遗传效应研究。在14个连锁群上检测到50个QTL:其中控制株型的QTL有5个;控制株高的QTL有6个;控制开展度的QTL有5个;控制最大叶长的QTL有7个;控制最大叶宽的QTL有4个;控制叶形指数的QTL有6个;控制中肋长的QTL有7个;控制中肋宽的QTL有4个;控制抽苔的QTL有6个。另外,估算了单个QTL的遗传贡献率和加性效应。这将为大白菜品种改良中形态性状的分子标记辅助选择提供理论依据。     

爆裂玉米膨化倍数QTL分析及其环境稳定性

膨化倍数是爆裂玉米最重要的品质指标。以普通玉米自交系丹232和爆裂玉米自交系N04杂交构建的259个F2：3家系为定位群体,采用完全随机区组设计在郑州春播和夏播条件下测定了膨化倍数。利用覆盖玉米10条染色体的183对多态性分子标记构建连锁图,采用复合区间作图法（CIM）进行QTL定位分析,采用多区间作图法（MIM）分析定位QTL间的互作效应。共检测出22个QTLs,单个QTL的贡献率为3．07％～12．84％,累计贡献率为66．46％和51．90％。其中5个QTLs在两种环境条件下均检测到,3个QTLs（qPF-6-1、qPF-8-1和qPF-1-3）的贡献率大于10％。大多数QTLs的加性效应值大于显性效应,表现为加性、部分显性、显性和超显性基因作用方式的QTLs数目在两种环境下分别为4、5、0、2和2、5、2、2。仅6对（占2．60％）QTLs或标记区间存在显著互作效应,表现为AA、DA或DD互作方式。     

水、旱条件下稻米蒸煮和营养品质性状与土壤水分环境互作分析及其QTL定位

以旱稻品种IRAT109与水稻品种越富杂交构建的DH群体的116个株系及其亲本为材料,在水、旱2种栽培条件下种植,研究了稻米蒸煮和营养品质性状的变化规律,在水、旱2个土壤水分环境下对直链淀粉含量(AC)、胶稠度(GC)、碱消值(GT)和蛋白质含量(PC)4个蒸煮和营养品质性状进行QTL定位及QTLs与环境互作分析。结果表明,以上4个品质性状在水、旱2种不同栽培条件下差异较大,说明这些性状受水分条件影响较大,旱栽条件下稻米蒸煮和营养各品质性状均有不同程度的升高,其中蛋白质含量平均提高37.9%。QTL分析结果表明,4个稻米品质性状在2个环境中的表现型值都为连续分布,均存在超亲遗传类型,共检测到7个加性效应QTL与稻米蒸煮和营养品质性状4项指标有关,分别位于第1、2、3、6、8、11染色体上,单个QTLs对性状的贡献率在1.91%～19.77%之间。位于第3染色体上控制碱消值的QGt3,第6染色体上控制直链淀粉含量的QAc6,在2个不同土壤水分条件下均与环境存在显著互作,对环境互作的贡献率分别为8.99%和47.86%。控制直链淀粉含量的2对上位性QTLs与土壤水分环境显著互作,贡献率较大,分别为32.54%和11.82%。并筛选到5个主效QTL(QGt6b、QGt8、QGt11、QGc1和QPc2)在抗旱育种中可用于蒸煮和营养各品质性状MAS改良。     

高丹草氢氰酸含量性状的QTL定位分析

为了深入开展高丹草低氢氰酸含量性状的QTL精细定位、基因图位克隆、功能解析及分子标记辅助育种,该研究以二倍体杂交高丹草F_2代群体500个分离单株无性系及其亲本为材料,在课题组前期已构建出的高丹草高密度分子遗传连锁图谱的基础上,利用区间作图法对两年两地测定的高丹草氢氰酸含量性状进行了QTL定位分析。结果显示:(1)在4个不同环境下高丹草氢氰酸含量性状的广义遗传率分别为61.70%、72.05%、40.16%和69.25%,表明氢氰酸含量是既受环境影响又受微效多基因控制的数量性状,而且其群体测定值频率呈明显单峰正态性分布特点,符合QTL定位要求。(2)在LOD2.5的条件下,共检测到16个与氢氰酸含量性状相关的QTLs,其分布在LG1、LG2、LG4、LG6、LG7、LG8和LG10连锁群上。(3)16个QTLs中能重复检测到的稳定QTLs有9个,遗传贡献率范围为1.17%～39.9%,其中贡献率大于20%的主效QTLs有Qcn2-2、Qcn4-1、Qcn6和Qcn6-1共4个。该研究结果明确了各QTLs的遗传效应和分子标记位点。     

芥菜型油菜每角籽粒数QTL 的上位性互作和环境互作分析

【目的】为揭示芥菜型油菜及芸薹属作物每角籽粒数形成的分子机理,提高和改良芥菜型油菜产量和育种工作奠定基础。【方法】研究以包含221个芥菜型油菜株系的重组自交系(recombinant inbred line, RIL)群体为材料,在5个环境条件下对每角籽粒数性状进行加性QTL、加性×加性上位互作及环境互作分析。【结果】(1)共检测到7个与每角籽粒数相关的加性QTL,主要分布在芥菜型油菜A02、A03、A05、A08、B02和B03等染色体上,其加性效应分布在(-11.642 4)～4.524 6之间,其中qSS2-71的加性效应和遗传率均最大,分别达到-11.642 4和14.44%,其余6个加性QTL的加性效应和遗传率均较小;(2)检测到7对影响每角籽粒数的加性×加性QTL上位互作效应及其与环境的互作效应,上位性QTL互作效应值分布在(-4.930 8)～4.193 6之间,7对上位性QTL与不同环境互作的遗传力均接近0;(3)每角籽粒数性状的广义遗传率为80.98%,狭义遗传率为30.98%。【结论】综合分析,芥菜型油菜每角籽粒数受一定环境影响,但控制该性状的加性效应受环境影响较小...     

Mapping QTLs for Plant Phenology and Production Traits Using Indica Rice (Oryza sativa L.) Lines Adapted to Rainfed Environment

Drought is a major abiotic stress limiting rice production and yield stability in rainfed ecosystems. Identifying quantitative trait loci (QTL) for rice yield and yield components under water limited environments will help to develop drought resilient cultivars using marker assisted breeding (MAB) strategy. A total of 232 recombinant inbred lines of IR62266/Norungan were used to map QTLs for plant phenology and production traits under rainfed condition in target population of environments. A total of 79 QTLs for plant phenology and production traits with phenotypic variation ranging from 4.4 to 72.8% were detected under non-stress and drought stress conditions across two locations. Consistent QTLs for phenology and production traits were detected across experiments and water regimes. The QTL region, RM204-RM197-RM217 on chromosome 6 was linked to days to 50% flowering and grain yield per plant under both rainfed and irrigated conditions. The same genomic region, RM585-RM204-RM197 was also linked to harvest index under rainfed condition with positive alleles from Norungan, a local landrace. QTLs for plant production and drought resistance traits co-located near RM585-RM204-RM197-RM217 region on chromosome 6 in several rice genotypes. Thus with further fine mapping, this region may be useful as a candidate QTL for MAB, map-based cloning of genes and functional genomics studies for rainfed rice improvement.     

Genetic mapping of QTLs affecting productivity and plant architecture in a full-sib cross from non-inbred parents in Cassava (<Emphasis Type="Italic">Manihot esculenta</Emphasis> Crantz)

An attempt was made to identify quantitative trait loci (QTLs) for several productivity and plant architecture traits in a full-sib progeny of 144 individuals from two non-inbred parents in cassava. A molecular linkage map of this cross constructed previously with over 250 markers was the source of molecular markers. The progeny were grown under field conditions at two locations (Palmira and Quilichao) in Colombia and evaluated in 2 years (1998 and 1999) for architecture and productivity traits. Architecture traits evaluated were plant height (PH), branching height (BH), branching levels (BL), branching index (BI), stem portion with leaves (SPL) and leaf area index (LAI). Productivity traits were those related to total dry matter production and distribution, namely fresh root yield (FRY), fresh shoot yield (FSY), harvest index (HI) and the number of storage roots (NR). Phenotypic evaluation of the traits in this population revealed continuous variation for all traits. Broad-sense heritability estimates, ranged from 36% (for NR) to 94% (for BH). Several significant phenotypic correlations were observed between architecture and productivity traits. Primary QTLs, using the single-QTL model, and secondary QTLs, by a primary QTL interaction model, were detected by interval mapping. A total of 30 primary QTLs and 84 secondary QTLs were detected. We identified 35% of detected QTLs in two or more trials, the other QTLs were environment-specific. These results underscore the significant genotype × environment interactions found for most of the traits. Several genomic segments affecting multiple traits were identified and were in agreement with correlation among traits. All QTLs identified for FRY were found associated with either component traits of productivity or architecture traits. This study suggests that QTLs for plant architecture can be used to improve productivity. However an exhaustive search and analysis of QTLs controlling architecture is required before marker-assisted selection (MAS) for increasing productivity can be initiated.Communicated by H. C. Becker     

Molecular dissection of the genetic relationships of source,sink and transport tissue with yield traits in rice

Source, sink, and translocation capacity of assimilates play important roles during the formation of grain yield. The present study was conducted to characterize the genetic bases of traits representing source, sink and transport tissue, and their relationships with yield traits in rice, by analyzing QTLs for these traits and various ratios among them. The genetic materials were a recombinant inbred population derived from a cross between two indica cultivars Zhenshan 97 and Minghui 63, the parents of the most-widely grown hybrid rice in China. Using a linkage map that covers a total of 1,796 cM based on 221 molecular marker loci, a total of 81 QTLs were identified for the 15 traits studied (three leaf areas as the source, total spikelets per panicle as the sink, the number of large vascular bundles in the stem as transport tissue, three source to sink ratios, three transport tissue to source ratios, one transport tissue to sink ratio and three yield traits). The amount of variation explained by individual QTLs ranged from 1.12% to 24.14%. Five QTLs were identified to show interaction effects with the environment, which explained from 3.19% to 9.15% of the variation. The results showed that close linkage or pleiotropy is the genetic basis for the correlations of grain yield traits with source, sink, transport tissue and the various ratios among them. Of the 25 QTLs identified for source-sink-transport tissue trait, and 43 for various ratios, 8 and 22 QTLs, respectively, were mapped to the similar genomic blocks harboring QTLs for yield traits, especially for grain weight. Co-location of QTLs for yield traits with those for ratios among source, sink and transport tissue may provide a genetic explanation for the physiological expression of yield traits, and also suggest that improvement in ratios among source, sink and transport tissue may result in improvement in yield potential.     

Phenotypic variation in the agronomic and morphological traits of Pisum sativum L. germplasm obtained from different parts of the world

A total of 286 genotypes were collected from 39 countries of the world and were evaluated to determine the phenotypic diversity for 17 quantitative traits. Higher degree of coefficient of variation were recorded for grain yield(-5) (52.46%), biomass(-5) (45.73%), fresh pod width(-10) (47.24%), dry pod weight(-1) (40.33%), plant height(-1) (35.25%), harvest index (32.70%) and number of branches(-5). Cluster-II clearly reflected that late genotypes were having lightest pods weight, shortest pod width, and pod length; low grain yield, biomass and harvest index. While genotypes in Cluster-III were in contrast to Cluster-II having heaviest pods weight, longest pods width and length, highest grain yield, biomass and harvest index. Higher PC(-1) values have been determined for days to flower initiation which consequently were contributing weighed positive to days to pods picking, days to flower completion, days to dry pod appearance, days to plant harvesting while negatively contributed to yield producing traits, indicating that late flowering pea germplasm emphasizes more on the vegetative growth and was low yielding. However, higher PC(-2) values have been obtained for number of branches(-5), grain yield and biomass while lower values for days to flowering, days to pods picking, days to flower completion, days to dry pod appearance and days to plant harvesting confirming the fact that early genotypes were high yielding.     

QTLs linked to leaf epicuticular wax,physio-morphological and plant production traits under drought stress in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

Drought stress is the major constraint to rice (Oryza sativa L.) production and yield stability in rainfed ecosystems. Identifying genomic regions contributing to drought resistance will help to develop rice cultivars suitable for rainfed regions through marker-assisted breeding. Quantitative trait loci (QTLs) linked to leaf epicuticular wax, physio-morphological and plant production traits under water stress and irrigated conditions were mapped in a doubled haploid (DH) line population from the cross CT9993-5-10-1-M/IR62266-42-6-2. The DH lines were subjected to water stress during anthesis. The DH lines showed significant variation for epicuticular wax (EW), physio-morphological and plant production traits under stress and irrigated conditions. A total of 19 QTLs were identified for the various traits under drought stress and irrigated conditions in the field, which individually explained 9.6%–65.6% of the phenotypic variation. A region EM15_10-ME8_4-R1394A-G2132 on chromosome 8 was identified for leaf EW and rate of water loss i.e., time taken to reach 70% RWC from excised leaves in rice lines subjected to drought stress. A large effect QTL (65.6%) was detected on chromosome 2 for harvest index under stress. QTLs identified for EW, rate of water loss from excised leaves and harvest index under stress in this study co-located with QTLs linked to shoot and root-related drought resistance traits in these rice lines and might be useful for rainfed rice improvement.     

QTLs for grain dry milling properties, composition and vitreousness in maize recombinant inbred lines

Vitreousness and kernel hardness are important properties for maize processing and end-product quality. In order to examine the genetic basis of these traits, a recombinant inbred line population resulting from a cross between a flint line (F-2) and a semident line (Io) was used to search for vitreousness and kernel composition QTLs. Vitreousness was measured by image processing from a kernel section, while NIR spectroscopy was used to estimate starch, protein, cellulose, lipid and semolina yield. In addition, thousand-grain weight and grain weight per ear were measured. The MQTL method was used to map the QTLs for the different traits. An additional program allowed for the detection of interaction QTLs between markers. The total number of main-effect and interaction QTLs was similar. The QTLs were not evenly distributed but tended to cluster. Such clusters, mixing main-effect and interaction QTLs, were observed at six positions : on chromosomes 1, 2, 3, 6, 8 and 9. Two of them, on chromosomes 6 and 9, concerned both QTLs for kernel-weight traits and QTLs for kernel-composition traits (protein and cellulose). Technological-trait QTLs (vitreousness or semolina yield) were located less than 16 cM from a protein-content QTL on chromosome 2, and were co-located with lipid- and starch-content QTLs on chromosome 8. The co-location of a vitreousness and a semolina-yield QTL at the telomeric end of the chromosome 2 (Bin 2.02) is likely to be meaningful since measurement of these related traits, made by completely different methods (NIRS vs image processing), yielded very close QTLs. A similar location was previously reported independently for a kernel-friability QTL. Comparing the map location of the numerous loci for known-function genes it was shown that three zein loci were closely linked to QTLs for vitreousness on chromosome 3, for semolina yield and starch on chromosome 4, and for protein, cellulose and grain weight on chromosome 9. Some other candidate genes linked to starch precursor metabolism were also suggested on chromosomes 6 and 8. Received: 27 April 2000 / Accepted: 3 July 2000     

Genetic analysis and QTL mapping of early root bulking in an F1 population of non-inbred parents in cassava ( Manihot esculenta Crantz)

The genetic basis of early bulking in cassava was studied in a replicated, multi-locational trial using 144 F1 progeny derived from an intra-specific cross between two non-inbred parents. A second, sequential harvest experiment examined the relative importance of eight yield-related traits on early bulking and their QTLs during the crop growth cycle. Our objectives were to identify traits, and genes controlling them, strongly associated with early yield as a first step to marker-assisted improvement of the trait. Multiple linear regression analysis and stepwise regression of early yield on eight yield-related traits revealed harvest index, dry foliage weight and root diameter as the most important factors associated with early yield. A total of 18 QTLs controlling early yield were identified in the first and second experiments and 27 QTLs, 2 for dry foliage weight, 8 for harvest index and 17 for root diameter, in the second experiment. The individual effects of alleles at these QTLs identified ranged from 7% to 33% of the phenotypic variance explained. Seven of 18 QTLs found for early yield (39%) coincided with QTLs associated with one or more traits with significant influence on early yield. The results show that sink and source capacities are very important in determining early yield. The identification of a number of QTLs with positive effect for increased early yield provides an opportunity for marker-assisted selection and improvement of early bulking potential in cassava.     

Mapping and characterisation of QTL × E interactions for traits determining grain and stover yield in pearl millet

A mapping population of 104 F(3) lines of pearl millet, derived from a cross between two inbred lines H 77/833-2 x PRLT 2/89-33, was evaluated, as testcrosses on a common tester, for traits determining grain and stover yield in seven different field trials, distributed over 3 years and two seasons. The total genetic variation was partitioned into effects due to season (S), genotype (G), genotype x season interaction (G x S), and genotype x environment-within-season interaction [G x E(S)]. QTLs were determined for traits for their G, G x S, and G x E(S) effects, to assess the magnitude and the nature (cross over/non-crossover) of environmental interaction effects on individual QTLs. QTLs for some traits were associated with G effects only, while others were associated with the effects of both G and G x S and/or G, G x S and G x E(S) effects. The major G x S QTLs detected were for flowering time (on LG 4 and LG 6), and mapped to the same intervals as G x S QTLs for several other traits (including stover yield, harvest index, biomass yield and panicle number m(-2)). All three QTLs detected for grain yield were unaffected by G x S interaction however. All three QTLs for stover yield (mapping on LG 2, LG 4 and LG 6) and one of the three QTLs for grain yield (mapping on LG 4) were also free of QTL x E(S) interactions. The grain yield QTLs that were affected by QTL x E(S) interactions (mapping on LG 2 and LG 6), appeared to be linked to parallel QTL x E(S) interactions of the QTLs for panicle number m(-2) on (LG 2) and of QTLs for both panicle number m(-2) and harvest index (LG 6). In general, QTL x E(S) interactions were more frequently observed for component traits of grain and stover yield, than for grain or stover yield per se.     

Mapping quantitative trait loci controlling agronomic traits in the spring wheat cross RL4452x'AC Domain'.

Relatively little is known about the genetic control of agronomic traits in common wheat (Triticum aestivum L.) compared with traits that follow Mendelian segregation patterns. A doubled-haploid population was generated from the cross RL4452x'AC Domain' to study the inheritance of the agronomic traits: plant height, time to maturity, lodging, grain yield, test weight, and 1000-grain weight. This cross includes the genetics of 2 western Canadian wheat marketing classes. Composite interval mapping was conducted with a microsatellite linkage map, incorporating 369 loci, and phenotypic data from multiple Manitoba environments. The plant height quantitative trait loci (QTLs), QHt.crc-4B and QHt.crc-4D, mapped to the expected locations of Rht-B1 and Rht-D1. These QTLs were responsible for most of the variation in plant height and were associated with other agronomic traits. An additional 25 agronomic QTLs were detected in the RL4452x'AC Domain' population beyond those associated with QHt.crc-4B and QHt.crc-4D. 'AC Domain' contributed 4 alleles for early maturity, including a major time to maturity QTL on 7D. RL4452 contributed 2 major alleles for increased grain yield at QYld.crc-2B and QYld.crc-4A, which are potential targets for marker-assisted selection. A key test weight QTL was detected on 3B and prominent 1000-grain weight QTLs were identified on 3D and 4A.     

Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress

Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52–38.53%), phenotypic coefficient of variation (20.29–39.85%), heritability (92.50–93.90%), and genetic advance as a percentage of mean (38.68–76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-021-00977-5.