GENOTYPE BY ENVIRONMENT INTERACTIONS IN LIVESTOCK BREEDING PROGRAMS: A REVIEW

GENOTYPE BY ENVIRONMENT INTERACTIONS IN LIVESTOCK BREEDING PROGRAMS: A REVIEW HUGO H. MONTALDO n a smple genetc model for a quanttatve trat, the phenotype s consdered as the sum of ndependent genetc and envronmental effects. Often, such a model s not satsfactory for the range of stuatons to whch t s appled. If a genotype by envronment nteracton (GEI) exsts, ths ndependence s lost, and the smple model does not ft the data properly (Falconer, 989). A possble remedy s to extend the model by ncludng a term for GEI. Dckerson (96) defned the GEI as addtonal varaton due to the jont effects of the genotype and envronment, not predctable from ther separate average effects and added that They are mportant to the extent that use of the best combnaton of genotype and envronment would permt more effcent anmal producton. Genotype by envronment nteractons may affect the effcency of selecton programs by reducng the response n the performance trats (.e., growth, mlk producton) n anmals rased under envronmental condtons dfferent to that of the selected ones. These reductons may nvolve reproducton and survval rates n genotypes rased at partcular locatons. The effect of genotype x envronment nteractons resultng from the lack of adaptaton of partcular genotypes to specfc condtons may reduce economc performance when the envronmental condtons of the selected anmals are dfferent from those of the commercal populaton. Genotype by envronment nteracton s a potental source of reduced effcency n genetc mprovement programs nvolvng anmals n tropcal areas and developng countres for three man reasons: ) The utlzaton of germplasm selected or developed n regons wth other clmatc condtons and producton systems s very common (Bondoc et al., 989). Ths approach reflects the lmted number of effcent breedng programs based on local performance data. ) The clmate and other characterstcs of producton systems n tropcal areas create numerous envronmental challenges (food, housng, temperature, pathogens) to effcent producton (Vercoe and Frsch, 99). Adaptablty trats are commonly mentoned and used n selecton programs n tropcal areas (Horst, 98), but appear to be less mportant n more favorable envronments. 3) Economc characterstcs of markets n tropcal regons, whch may be dfferent from those where the anmals were selected, would lead to novel genotype x (economc) envronment nteractons. Vercoe and Frsch (986) dentfed the man envronmental lmtatons for anmal performance n tropcal areas as beng clmatc factors (e.g., hgh temperatures, humdty and solar radaton), external parastes (e.g., tcks and other arthropods), nternal parastes (e.g., gastrontestnal helmnthes), protozoan, bacteral, fungal and vral dseases, and varatons n the quantty and qualty of avalable food. The possble levels for studyng genotype x envronment nteractons n anmals (Barlow, 985) are economc consderatons, producton trats, trat components of producton trats, ndrect trats (physologcal trats), and drect genetc varaton (DNA). From the practcal pont of vew, mplcatons of GEI should be evaluated preferably at the economc level. However, studes performed at the other levels could help n a better understandng of GEI mplcatons n anmal mprovement. Prevous revews have emphaszed methods for estmatng GEI n anmals and the bologcal-statstcal evdence for GEI (Barlow, 98; Vercoe and Frsch, 99; Warwck, 97; Wlson, 974). Ths paper revews the mplcatons of parameter estmates assocated wth GEI on desgn of genetc mprovement programs for anmals, wth partcular emphass on tropcal areas and developng countres. For completeness, some basc methodologcal prncples and some old and some new bologcal-statstcal evdence for GEI n anmals are also ncluded. KEY WORDS / Producton Systems / Breedng Systems / Selecton / Genetc Resources / Breeds / Developng Countres / Recbdo: /03/00. Aceptado: 03/05/00 Hugo H. Montaldo. Ph.D. n Anmal Scence, Unversty of Nebraska-Lncoln. Professor, State Unversty of Guanajuato, Méxco. Address: Insttuto de Cencas Agrícolas, Unversdad de Guanajuato. AP 3, Irapuato, Gto. 36500, Mexco. e-mal: hmontald@dulcnea.ugto.mx JUN 00, VOL. 6 Nº 6 0378-844/0/06/9-07 $ 3.00/0 9

Types of genotype by envronment nteractons Intally, nteractons caused by heterogenety of genotypc varances among envronments must be dstngushed from those caused by a lack of correlaton between genotypc performance n dfferent envronments (Yamada, 96; Falconer, 989). Dckerson (977) consdered the genetc correlaton between envronments (r g ) as the most useful crteron for assessng the mportance of GEI n anmal breedng. Genetc correlatons lower than 0.8 are expected to cause mportant reductons n the effcency of breedng programs (Robertson, 959). In the absence of GEI, the expected value of r g s one. Only when the genetc correlaton among envronments s less than one does GEI mpede response to selecton because t can change the optmal composton of the selecton and rejected groups across envronments (Cooper and DeLacy, 994). Heterogenety of varances n stuatons where the genetc correlatons are unty s largely regarded as an effect of scale and not a cause of rerankng. Estmaton Methods There are three man methods for measurng GEI: components of varance, genetc correlatons among envronments, and pattern analyss (Cooper and DeLacy, 994). Heterogenety of genotypc varances among envronments and correlaton among genotypc performance n dfferent envronments are confounded when a standard ANOVA s used to estmate a GEI varance component (Mur et al., 99). Mxed model methodology has been used (see revew by Cameron, 993) to estmate r g unbasedly. Genetc evaluatons usng mxed model methodology n the presence of heterogeneous varances have also been descrbed and ther effectveness evaluated (Garrck and Van Vleck, 987; Reverter et al., 997). An approxmate genetc correlaton between two envronments can be obtaned from the observed correlaton between the predcted breedng values (I) of progeny tested sres n two envronments (r I(),I() ), usng the equaton (Brascamp et al., 985): rg r I(),I() / ( r AI() r AI() ) () where r AI() and r AI() are average relabltes (repeatabltes) of the ndces based on progeny testng,.e., the TABLE I TYPES OF GENOTYPE X ENVIRONMENT INTERACTIONS IN ANIMALS Types Varaton Examples Genotypes Envronments Small Small Sre famles n one herd Large Small Breeds n one herd 3 Small Large Sre famles n dfferent herds 4 Large Large Breeds n dfferent areas Adapted from Dunlop (96). squared correlaton between the ndex and the breedng value (A) wthn envronments and. Ths correlaton s expected to be lower than the genetc correlaton, because the ndces are predctons of A whch contan error terms. For ths reason, the use of uncorrected correlaton estmates between sre or other replcated famly group ndces (predcted breedng values) n two envronments as drect evdence of GEI can be msleadng (Lynch and Walsh, 998). In addton, when usng ths method, t s necessary to set one mnmum value for r AI (e.g. 0.7) n each envronment for each sre, snce equaton () apples only f the sum of random envronmental devatons of the progeny n each envronment equals zero. Ths s true only n sres wth predctons obtaned usng enough progeny numbers n both envronments. Another theoretcal approach, partcularly popular n plant breedng, s the concept of stablty, whch expresses the ablty of one genotype to be less senstve to envronmental nfluences. If the genotypes are consdered fxed effects n a lnear model (.e., breeds), and the envronments are a random sample of many possble producton envronments (locatons or herds), stable genotypes wll have less steep regresson lnes across ordered envronmental levels than non stable ones (Eberhart and Russell, 966; Mur et al., 99; Lynch and Walsh, 998). Ths approach may help n selectng genotypes more adapted to dffcult condtons by retanng for breedng those whch perform better at lower envronmental levels, rather than those wth the maxmum average performance. DNA studes have dentfed sequences related to major genes for quanttatve trats. These can be used for marker-asssted selecton (Jansen, 993). In the future, molecular bology technques may help genetcsts dentfy anmals whch carry specfc genes wth large effects on quanttatve trats or quanttatve trat loc (QTL) capable of ncreasng the productvty or product qualty n specfc envronments. Identfcaton of an mportant number of nteractng QTL capable of ncreasng productvty n specfc envronments, management systems or markets, could help to develop a populaton wth specfc advantages under certan envronmental condtons or lmtatons (Drnkwater and Hetzel, 99). Bologcal-statstcal evdence of genotype by envronment nteractons n anmals Dunlop (96) developed a scale of ncreasng lkelhood for the presence of GEI n anmals whch nvolved ncreasng degrees of envronmental and genetc varaton from to 4 (Table I). Interactons are most lkely to be expected n category 4 (breeds n dfferent areas). A classc example of the latter category occurs when both Bos taurus and Bos ndcus cattle are rased n temperate and tropcal areas. An example of category 3 (sre famles n dfferent herds) would be wth poultry where the genetc correlaton between sre progenes reared on the floor and n cages s as low as 0.7 (Prchner, 983). Interactons n stuatons of types (sre famles n one herd) or (breeds n one herd) are less common. Where the envronment cannot, or can only partally, be controlled, as wth plant and fsh producton, or wth range anmals, GEI are mportant. In contrast, where envronmental control s feasble, as wth dary or poultry producton, GEI are less mportant. Wth dary cattle, GEI are small wthn the same geographc area, or between temperate regons. Thus, for example, GEI for productve trats n Holsten was small among the states of Calforna, New York and Wsconsn, and between the US and Span (Carabaño, 988; Carabaño et al., 990). Most studes n temperate areas show lttle or no evdence for strong nteractons between genotype and nutrton n dary cattle (Syrstad, 976). 30 JUN 00, VOL. 6 Nº 6

Selecton responses to the use of selected US Holsten sres for mlk producton n Latn Amerca were estmated to be 53% to 78% of the response observed n the USA. The genetc correlatons ranged from 0.78 to 0.9. Most of the reducton was attrbuted to heterogeneous varances (Stanton et al., 99). Costa et al. (000) reported relatvely large genetc correlatons (0.85-0.88) for mlk and fat producton between Brazl and the USA although hertabltes and phenotypc varances were smaller n Brazl. In a study wth data from Mexco and USA, Cenfuegos-Rvas et al. (999), found genetc correlatons rangng from.60 to.93 for mlk producton between countres. Correlatons were hgher between data from herds wth smlar producton rankng n both countres. Some unpublshed estmates for Holsten herds wth extremely hgh or low producton levels n Mexco showed a low genetc correlaton (0.40) for the frst lactaton records. Ths estmate s very close to the estmate of 0.38 for the genetc correlaton between the genetc values n the Southern and Northern regons of Mexco obtaned by Valenca (00) wth the same data. Ron and Hllel (983) found sgnfcant nteractons for genotype x lactaton number n Holstens n Israel but a very low nteracton genotype x farm producton level. These authors also attempted to determne dfferences n stablty of expressons of sres genotypes across herd producton levels, but there was no evdence of GEI. Abubakar et al. (987) observed a lower breedng effcency and survval n hgh-mlk estmated breedng value (EBV) Holsten bulls compared wth low-mlk EBV bulls n Mexco and Colomba. The relatonshp between mlk producton and survval was the opposte of that observed n the USA, suggestng a possble genotype x envronment nteracton. Valenca (00) however, found a postve genetc correlaton (0.33 to 0.64) between mlk producton and survval trats n Holsten wth Mexcan data. Castllo-Juárez et al. (000) found changes n correlatons between mlk producton and somatc cell score and concepton rate at frst servce wth groups of herd envronment. The genetc correlatons between pars of trats were consstently smaller n hgh envronment herds, suggestng that dfferences n management between the two envronment levels lessened the antagonstc genetc assocaton between the trats studed. The authors suggested that a long-range plan for low envronment herds should focus on mprovng the level of management, whch would greatly reduce the unfavorable correlated changes n lactaton mean somatc cell score and concepton rate at frst servce assocated wth the genetc mprovement of mature equvalent mlk yeld. Syrstad (990) ndcated that there was no evdence of nteracton of producton levels (envronments) x genotypes, represented by several European x Zebu or European x natve crosses, on mlk producton. Sgnfcant genetc group x farm nteractons for age at calvng, length of lactaton and calvng nterval were found n Inda. Genetc groups where Holsten x Sahwal crosses wth a dfferent Holsten proporton rangng from 50 to 87.5% (Rao et al., 99). Dfferent economc condtons may lead to GEI when nstead of one trat the economc value of the total producton s consdered. For example, the upgradng of European dual-purpose cattle wth Holsten has ncreased mlk yeld but decreased carcass value. The mprovement n dary performance requres a hgh level of feedng. If a hgh level of feedng s uneconomcal, but beef performance remans economcally attractve, dual-purpose cattle may be more proftable under ths new envronment. Smlar examples can be drawn from beef breedng. A Smmental x Hereford cross may be generally more productve than pure Herefords, but n poor grazng regons, ts hgher mlk potental may lead to unsatsfactory fertlty and make the pure beef breed superor. The breedng goal should, therefore, be determned by the economc condtons of each partcular stuaton (Prchner, 983). Morrs et al. (993) studed genotype x locaton effects on reproductve and maternal trats n beef cattle usng bulls of breeds n crosses wth Angus cows. Important GEI were observed for a number of reproductve, maternal and composte trats, ncludng weght of calf weaned per cow mated (productvty) and cow effcency (the rato of productvty to cow weght). Important GEI were also found when comparng Bos taurus x Bos ndcus crosses (TI) vs. B. taurus x B. taurus crosses (TT) n Nebraska and Florda (Olson et al., 99). The genotype x envronment nteracton was mportant for pregnancy rate; the advantage of TI over TT cows beng greater n Florda (6%) than n Nebraska (%). GEI also were observed for weanng weght and weght per cow exposed to breedng. Advantage for weght per cow exposed to breedng for TI vs. TT cows was greater n Florda (8%) than n Nebraska (6%). In pgs, research has shown mportant GEI for body weght and backfat thckness when the same sres were used on test statons and commercal farms n the Netherlands (Merks, 988a,b; 989). Sre x herd nteractons explaned -3% of the varance for several trats. The genetc correlatons between performances n central statons and farms were 0.4 for daly gan and 0.70 for backfat thckness. Webb and Curran (986) revewed numerous studes n pgs, whch showed that the nteracton genotype x restrcted or ad lbtum feedng affected growth rate, and the nteracton of genotype x test locaton (staton vs. on-farm) was sgnfcant for feed effcency. Smlarly, mportant GEI were found for growth trats n sheep n the Unted Kngdom under dfferent commercal envronments and accordng to sex. The genetc correlaton for growth between males reared under ntensve condtons and females reared on pasture was only 0.37 (Bshop et al., 996). Selecton response n a second envronment When anmals, such as artfcal nsemnaton dary sres, selected n envronment are used n a second envronment, expected genetc response n envronment s: G. = rg rai óa where r G s the genetc correlaton between envronments and, r AI s selecton accuracy for anmals selected on envronment, s A s the genetc addtve standard devaton of the trat on envronment and s selecton ntensty on envronment. Response to selecton wthn envronment s: G = r. AI ó A where r AI s selecton accuracy for anmals selected on envronment and s selecton ntensty on envronment. Assumng =, f r r G AI >r AI, selectng n envronment wll gve a greater selecton response n envronment. Conversely, f r G r AI <r AI, selecton wthn envronment wll gve greater response. Also n stuatons where >, where say, more sres are tested n envronment, use of sres selected on envronment may be more effcent than wthn populaton selecton on envronment. Selecton n several envronments Anmal breeders often wsh to mprove overall performance n a range of envronments. James (96) de- JUN 00, VOL. 6 Nº 6 3

rved formulae for maxmzng the average selecton response for two envronments usng a selecton ndex approach. Knghorn and Swan (99) descrbed how to apply a multtrat, best lnear, unbased predcton model to optmal multple-envronment evaluaton wth varance-covarance structures among relatves n dfferent envronments, ncludng the numerator relatonshp matrx. Wth two envronments, there are several optons for selecton (Falconer, 95). They are selecton n one envronment (ether good or bad ), separate selecton of two strans n both envronments, and selecton on an ndex combnng performance n both envronments. Falconer (990) defned selecton performed n a bad envronment as antagonstc and selecton performed n a good envronment as synergstc. In laboratory organsms, antagonstc selecton s sgnfcantly better for mprovng the average mean of the selected trats. In a classcal experment wth pgs (Fowler and Ensmnger, 960), two populatons were selected for growth rate on ad lbtum and restrcted feedng. When swtched to the opposte regme, the populaton selected under restrcted feedng grew faster n both regmes. Usng genotype by envronmental nteracton parameters to optmze selecton programs Genotype by major envronment nteractons wll change the rankng of the genotypes wthn each major envronment, suggestng the possble need to desgn as many breedng programs as envronments. In small scale breedng programs, ths strategy may nvolve ncreased costs and reduced selecton effcency. Methods are therefore requred to evaluate the possble outcomes of alternatve desgns. Once the magntude and bologcal and economc nature of the GEI have been evaluated, these parameters could be used to evaluate the effectveness of selecton across or wthn major producton-marketng envronments (Dckerson, 96, 977). The man parameters are genetc correlatons among economc objectves for dfferent envronments. Interactons Among Genotype and Random Envronments TABLE II EFFECT OF INCREASING THE NUMBER OF TESTING ENVIRONMENTS (K) ON GENETIC RESPONSE IN A POPULATION OF 000 ANIMALS k h /r g * 0./0. 0./0.4 0./0.8 0.4/0. 0.4/0.4 0.4/0.8 0.8/0. 0.8/0.4 0.8/0.8.00.00.00.00.00.00.00.00.00 5..49..0.05.0.0.0.00 0 3..76.3.5.07.04.0.0.00 0 4.3.06.43.0.09.05.0.0.0 50 6.47.5.58.6..06.03.0.0 00 8.47.87.69.30.4.07.03.0.0 * h /r g = hertablty/genetc correlaton among envronments. Total response to selecton n several envronments s proportonal to the genetc correlaton between genotypes n dfferent envronments (r g ). The rato of selecton response at constant selecton ntensty, derved by averagng selecton responses measurng performance wthn k random envronments relatve to selectng n one envronment, s (Dckerson, 96): [(+(nk-) h )/(+(n-) h + n (k-) r g h )] / () f a total of nk anmals are tested (n n each envronment). For nk=000 anmals tested, progress of the rato wth k s shown n Table II for dfferent levels of r g and hertablty. The mpact of ncreasng k wll be greater when the trat has a low hertablty and a low genetc correlaton. GEI may sgnfcantly reduce the accuracy of estmates of the genetc values of the genotypes by ntroducng addtonal sources of varaton nto the phenotype (genotype x random envronment nteracton). Merks (988a) extended formula () to a full sb desgn to estmate the effect of genotype x random envronmental nteractons of a breedng program n pgs. Assumng each sre has m ltters of sze n n N herds, selecton n all herds smultaneously produce a response of G N wth Nmn ndvduals per sre. In the case of selecton n a sngle herd, the response s G. The formula (3) for the ncrease n selecton response wth ncreasng measured envronments and constant selecton ntensty s G ( ( )( 0.5 ) ( )0.5 G ( ( )( 0.5 ) ( )0.5 ( )0.5 N + n h + c + n mn h = + n h + c + n m h + nm N h rg were c stands for the common envronmental and non-addtve effects between lttermates wthn herds and h s the hertablty of the trat. Ths formula shows that the advantage of ncrease N s to mnmze the error from r g when measurng the sutablty of each genotype by dstrbutng the representatves of the genotype over as many herds (envronments) as possble (Merks, 988a). Interactons Among Genotype and Major Envronments If GEI occur among k mportant producton envronments, choce between separate ntal genotypes and selecton programs n each envronment vs. a sngle ntal genotype wth contnung selecton for general adaptablty to all k envronments can be based upon the hertablty (h ) and the relatve economc mportance (e ) of the performance n each envronment and ther genetc correlatons (r gj ). If e are equal, average response at constant selecton ntensty n the specfc -th envronment from selecton based upon average adaptablty to k envronments (P k ) relatve to selecton n one envronment wll be roughly (Dckerson, 977): ( h + h r j g ) GfromP j k = G fromp (4) h k[+ ( k ) h h r ] ( k ) Equaton (4) may be used whether or not a hgher response wll be obtaned by performng selecton for general adaptaton to k major (e.g., re- j g j 0.5 (3) gonal) envronments. Assumng equal hertablty n each envronment and equal genetc correlaton among all pars of envronments, equaton (4) smplfes to: ( + (k-) r g )/(k [ + (k-) h r g ]) 0.5 (5) 3 JUN 00, VOL. 6 Nº 6

TABLE III AVERAGE EXPECTED RESPONSE FOR WITHIN ENVIRONMENT SELECTION AS A PROPORTION OF THE AVERAGE RESPONSE IN K MAJOR ENVIRONMENTS k h /r g * 0.8/0.8 0.8/0.5 0.8/0.3 0.5/0.8 0.5/0.5 0.5/0.3 0.3/0.8 0.3/0.5 0.3/0.3.00.00.00.00.00.00.00.00.00 0.99 0.90 0.83.08 0.95 0.86.4 0.99 0.88 3 0.99 0.86 0.76. 0.94 0.8.3.0 0.85 4 0.99 0.84 0.7.5 0.94 0.79.30.04 0.84 5.00 0.83 0.70.6 0.95 0.78.34.06 0.84 00.00 0.79 0.6.6.00 0.77.6.7 0.98 000.00 0.79 0.6.6.00 0.77.63.9.00 * h /r g = hertablty/genetc correlaton among envronments. Fgure. Genetc response per year n standard devaton unts (SD) for the commercal populaton usng adult and juvenle MOET nucleus wth dfferent genetc correlaton. Applcaton of equaton (5) shows that unless the value of hertablty s hgh and the genetc correlaton s low, the response n one envronment s not reduced sgnfcantly wth an ncrease n the number of major testng envronments (Table III). For -5 major envronments, wth hertablty values rangng from 0.3 to 0.5, a reducton n effcency would be expected only wth values of r g < 0.3. Programs based on the evaluaton of genotypes for several major envronments would seem to be robust aganst reductons n r g values and number of testng envronments. The smplfed assumptons n equaton (5), however, may not be realstc for many cases. Fgure depcts the effect of dfferent values of r g between adult and juvenle multple ovulaton and embryo transfer (MOET) nucleus and commercal populatons n dary cattle (Bondoc and Smth, 993). The responses are expressed n standard devatons of the commercal populaton. A lnear relatonshp exsts between the expected response and r g assocated wth each selecton program. Ths relatonshp may also occur when a country s mportng semen from sres evaluated n another country. If the frst country s evaluatng bulls by usng progeny testng wth data obtaned at the commercal level, the entre system could be consdered as another major envronment f the test envronment s dfferent from that of the mportng country. Ths case s smlar to that when sres or semen from a nucleus populaton are used n the commercal populaton of one country. Herarchcal Systems In herarchcal mprovement programs such as n pg breedng, two types of genetc correlatons can be defned wth respect of the consequences of GEI on genetc progress (Brascamp et al., 985; Merks, 988a). ) r G s defned as the genetc correlaton across levels of a genetc program and s typcally the correlaton between the test (nucleus) and commercal envronments. ) r g s defned as the common genetc correlaton among random envronments (herds) wthn one level of a genetc program. If r g <, the GEI wll reduce the accuracy of the estmaton of breedng values f nsuffcent numbers of random envronmental levels (herds, locatons) are used. Collectng data for evaluaton from several herds wll help overcome ths problem. Evaluatng the mpact of GEI n a herarchcal genetc program may nvolve nteractons between and wthn the major envronments, for whch four parameters are necessary; ht the hertablty of the trat (or ndex) at the level of the testng populaton (nucleus), C h, the hertablty at the level of the commercal populaton; and r G and r g as defned before. In ths case, the genetc response at the commercal level s reduced when r or r G g values are less than one, and possbly by r ³ r g, whch means G that testng at the commercal level could help ncrease the genetc response. Generally h T > h C, because the anmals tested n the nucleus populaton usually perform n a more unform envronment and because more trats can be measured more accurately. In ths stuaton, the best approach s to make the test envronment as smlar as possble to the commercal envronment and to ncorporate procedures, such as progeny testng or two-stage selecton to evaluate anmals at the commercal level (Merks, 988a). A smlar concluson has been expressed wth respect to the convenence of usng nformaton from commercal crossbred anmals to evaluatng purebred canddates, even when the genetc correlaton s < (We and van der Werf, 994). Dscusson In many speces, the populaton s stratfed nto nucleus, multpler and commercal producton levels. These levels are not always conceptually recognzed. In developng countres, where nucleus or even multpler anmals (germplasm) are usually mported, there s an ncreased possblty of GEI affectng the economc expresson of the desred mprovement. Studes on the practcal mplcatons of GEI n these countres and on the ways to crcumvent such nteractons are few. An excepton s mlk producton trats n Holsten cattle among temperate areas, where GEI are of mnor mportance. Adequate assessment of the economc mportance of GEI for many speces s not avalable. In pgs, the practcal mportance of GEI s hgh (Brascamp et al., 985; Webb and Curran, 986). Negatve economc consequences of mportaton of anmals when genetc correlatons are less than unty, could be sometmes partally offset usng ratonal selecton crteron such as selectng dary bulls on proft (Montaldo, 997). As an opton to ncrease productvty by selecton under dffcult envronments, some authors have stressed the mportance of consderng physologcal or adaptablty trats as selecton crtera n breedng programs for tropcal areas (Horst, 98; Vercoe and Frsch, 99). The ncorporaton of these trats nto the selecton process s not easy or straghtforward because of the lack of knowledge about ther economc value and the cost of measurng such trats. Crossbreedng for explotaton of heteross s often an opton for combnng adaptablty and productvty n dffcult envronments. Heteross s generally greater n more severe envronments (Barlow, 98). In tropcal envronments, the offsprng of Brahaman x (Hereford x Shorthorn), have the same growth poten- JUN 00, VOL. 6 Nº 6 33

tal as the Hereford x Shorthorn parents and are almost as resstant to envronmental stress as the Brahaman. In ths case, the crossed offsprng outperform both parental types n all but very low stress or very hgh stress envronments (Vercoe and Frsch, 99). If antagonstc selecton s more effcent than synergstc selecton for developng anmals adapted to a range of heterogeneous envronments, ths may mply that mportant changes are requred n current mprovement methods, where anmals selected under favorable condtons are expected to produce progeny n unfavorable envronments. Webb and Curran (986) found that for pgs the soluton to the problem of low correlaton between the performance n testng staton and farm envronments was to conduct the performance testng n a commercal envronment. They suggested that dentfcaton of factors that cause the GEI (level of feedng, number of pgs per pen) may help n desgnng adequate tests n the future. Other than GEI, the man practcal consequences of subdvdng a populaton for selecton, are ncreased nbreedng and reduced selecton ntensty n smaller populatons (Smth and Qunton, 993). Operatonal and cost consderatons related to the sze of the program are also mportant. These factors usually encourage the development of a sngle breedng program for a relatvely large populaton over a range of envronments (Drnkwater and Hetzel, 99). Important lmtatons on selecton of anmals adapted to specfc condtons, partcularly pasture systems, nclude lack of adequate characterzaton of the envronment and the presence of envronmental condtons that change rapdly, e.g., drought and dsease, or that make proftable anmal producton dffcult or mpossble. Because economc returns from a gven breedng program are obtaned over several generatons, economc and envronmental condtons may change. For ths reason, evaluaton of the consequences of GEI need to be projected nto the future. In populatons adapted to specfc envronments that are dffcult to change, selecton for locally adapted populatons may be the best opton. For any stuaton, comparatve economc performance of canddate genotypes under condtons of the local envronment should be evaluated before a decson s taken. Few comparsons have been made among exotc, local and crossbreed genotypes under commercal condtons n developng countres. In many cases, the expermental evdence s compromsed by severe defcences n the expermental desgn and by poor characterzaton and samplng of the local breeds (Montaldo and Meza, 999). If nucleus breedng strateges based on MOET are used, dstrbuton of the nucleus among several stes and data collecton from the base populaton level may help reduce the negatve effects of GEI, partcularly when the r g s low (Bondoc and Smth, 993). Thus, n the presence of GEI, an mportant potental advantage exsts for dspersed rather than centralzed, and for open rather than closed nucleus populatons. In many cases, dsease control standards may lmt the use of anmals selected from the base commercal populaton n the nucleus populaton. Smlar restrctons occur n tradtonal mprovement schemes whch use closed, purebred studs to provde males for the multpler and commercal populatons. The accurate estmaton of GEI parameters s crtcal to assess the effectveness of breedng programs for producton systems n developng countres. Use of evaluaton schemes such as progeny testng wth artfcal nsemnaton n several locatons and herds, could reduce the effect of GEI on the response to selecton. Conclusons The practcal and economc mplcatons of GEI wll contnue to domnate the organzaton of anmal breedng programs. Bologcal-statstcal evdence for GEI needs to be consdered together wth economc nformaton durng decson-makng processes nvolvng all trats of nterest. Despte bologcal evdence for GEI for many ndvdual trats n anmals, the mplcatons of GEI on the organzaton of more effcent anmal breedng programs are frequently dffcult to evaluate. Current research on effects of GEI on total productvty n tropcal areas and developng countres should, therefore, be done at the commercal level. Improvements based on closed elte stud or nucleus breedng systems and on mportaton of germplasm are more lkely to be negatvely affected by GEI than those based on extensve recordng of all mportant trats at the commercal level. In ths strategy, dentfcaton of the key major envronmental factors assocated wth GEI wll help optmze the envronments for testng n herarchcal mprovement schemes. Current bologcal evdence suggests that antagonstc selecton under a bad envronment s a better opton for producng anmals adapted to a wde range of envronmental condtons than synergstc selecton under good envronmental condtons. In many cases, ths s the opposte of the current practce n anmal breedng where the nucleus and stud herds are better managed than average commercal operatons. However, many examples exst of successful use of genetc materal selected under dfferent envronmental condtons. In many cases, crossbreedng and creaton of new synthetc breeds mght be the most proftable opton to combne hgh producton levels wth resstance to envronmental condtons. Contnued selecton under commercal condtons wll help to ncrease the frequency of the alleles requred to ncrease productvty under that envronment, as long as the program uses ratonal selecton crtera. The evdence and relatonshps revewed show the mportance of usng replcated random envronments and of ncorporatng records of anmals at commercal level nto evaluaton systems to mnmze the potentally negatve effects of GEI on the rate of genetc progress. Adaptablty and economc value of recently ntroduced populatons should be assessed under commercal envronmental condtons ncludng reasonable restrctons whch are a part of the producton system n the future. Removal of obvous envronmental restrctons for productvty s to be consdered n most cases, before lookng for genetc adaptaton of anmal populatons to bad or rratonal management practces. Comparatve studes wth approprate expermental desgn are mandatory for adequate decson-makng regardng conservaton, ntroducton and crossbreedng of local and recently ntroduced populatons. ACKNOWLEDGMENTS The author thanks Blane E. Johnson for ntal encouragng remarks, Gordon E. Dckerson for stmulatng dscussons, Julus H. J. van der Werf, Steven D. Lukefahr, Manjt S. Kang for suggestons, and Luz A. Fres for helpng wth the Portuguese abstract. Ths paper s dedcated to the memory of Gordon E. Dckerson. 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